Information retrieval Books
Springer Nature Switzerland AG Mobile Applications: Design, Development and
Book SynopsisUsing Android as a reference, this book teaches the development of mobile apps designed to be responsive, trustworthy and robust, and optimized for maintainability. As the share of mission-critical mobile apps continues to increase in the ever-expanding mobile app ecosystem, it has become imperative that processes and procedures to assure their reliance are developed and included in the software life cycle at opportune times. Memory, CPU, battery life and screen size limitations of smartphones coupled with volatility associated with mobile environments underlines that the quality assurance strategies that proved to be successful for desktop applications may no longer be effective in mobile apps. To that effect, this book lays a foundation upon which quality assurance processes and procedures for mobile apps could be devised. This foundation is composed of analytical models, experimental test-beds and software solutions. Analytical models proposed in the literature to predict software quality are studied and adapted for mobile apps. The efficacy of these analytical models in prejudging the operations of mobile apps under design and development is evaluated. A comprehensive test suite is presented that empirically assesses a mobile app’s compliance to its quality expectations. Test procedures to measure quality attributes such as maintainability, usability, performance, scalability, reliability, availability and security, are detailed. Utilization of test tools provided in Android Studio as well as third-party vendors in constructing the corresponding test-beds is highlighted. An in-depth exploration of utilities, services and frameworks available on Android is conducted, and the results of their parametrization observed through experimentation to construct quality assurance solutions are presented. Experimental development of some example mobile apps is conducted to gauge adoption of process models and determine favorable opportunities for integrating the quality assurance processes and procedures in the mobile app life cycle. The role of automation in testing, integration, deployment and configuration management is demonstrated to offset cost overheads of integrating quality assurance process in the life cycle of mobile apps. Table of ContentsAbbreviations and Acronyms List of Figures List of Tables Listing 1 Software Life Cycle 1.1 Process Models 1.2 Functional Specifications 1.2.1 User Stories 1.2.2 UML Use Case Diagrams 1.2.3 Software Requirements Specifications 1.3 Non-Functional Requirements 1.4 Test Driven Development 1.4.1 Acceptance Tests 1.4.2 Unit Tests 1.5 Continuous Integration and Delivery 1.5.1 Software Configuration Management 1.5.2 Continuous Integration and Delivery Summary EXERCISES REFERENCES 2 Development Fundamentals 2.1 Graphical User Interface 2.1.1 GUI Objects and Layouts 2.1.2 Event Handling 2.1.3 Redirection 2.2 Data Storage 2.2.1 Key-value Pairs 2.2.2 Files 2.2.3 Database Systems 2.2.4 Personal Data Storage 2.3 Data Connectivity 2.3.1 Web Access 2.3.2 Short Message Service 2.4 Concurrency 2.4.1 Threads and Asynchronous Tasks 2.4.2 Processes 2.5 Location and Sensor APIs Summary EXERCISES REFERENCES 3 Software Quality Assessment 3.1 Functional Requirements Testing 3.1.1 Equivalence Class Partitioning 3.1.2 Boundary Value Analysis 3.1.3 Domain Test Design 3.2 Maintainability 3.2.1 Sub-Characteristics 3.2.2 Maintainability Measures 3.3 Usability and Accessibility 3.3.1 Models 3.3.2 Evaluation 3.4 Performance Testing 3.4.1 Latency Measurement 3.4.2 GUI Performance 3.4.3 Memory Usage 3.4.4 Network Usage 3.4.5 Battery Usage 3.5 Scalability Testing 3.5.1 Scalability Models 3.5.2 Load Test Design 3.6 Reliability Testing 3.6.1 Growth Models 3.6.2 Fault Injection 3.6.3 Operational Profile 3.6.4 Reliability Test Design 3.7 Availability 3.7.1 Availability Models 3.7.2 Stress Testing 3.8 Safety 3.8.1 FMEA 3.8.2 FTA 3.9 Security 3.9.1 Vulnerabilities and Threat Analysis 3.9.2 Security Testing 3.10 Static Code Analysis Summary EXERCISES REFERENCES 151 4 Maintainability and Multi-Platform Development 4.1 Software Patterns 4.1.1 Programming Paradigms 4.1.2 Design Patterns 4.1.3 Architecture Patterns 4.2 Design Description 4.2.1 Structural 4.2.2 Behavioral 4.3 Multi-Platform Development 4.3.1 Native Development 4.3.2 Hybrid 4.3.3 Cross-Platform Development Summary EXERCISES REFERENCES 5 User Interaction Optimization 5.1 Multimodality 5.1.1 Touch Gestures 5.1.2 Motion Gestures 5.1.3 Verbal Gestures 5.1.4 Visual Gestures 5.1.5 Accessibility Frameworks 5.2 Navigation Controls 5.3 Dashboards 5.4 Custom GUI 5.5 Animated GUI Summary EXERCISES REFERENCES 6 Performance Acceleration 6.1 Data Compression 6.1.1 Lossless Compression 6.1.2 Lossy Compression 6.2 Data I/O Optimization 6.2.1 File System I/O 6.2.2 Network I/O 6.3 Rendering Pipelines 6.3.1 Animation Rendering 6.3.2 Video Rendering 6.3.3 Augmented Reality 6.3.4 Hardware Acceleration 6.4 Parallel Programming 6.4.1 Thread Priority 6.4.2 Data Parallel Computation Summary EXERCISES REFERENCES 7 Scalability Provisioning 7.1 Scalable Media Transport 7.2 Scalable Local Storage 7.2.1 Data Models 7.2.2 Data Structures and Query Plan 7.2.3 Location Queries 7.3 Scalable Design Patterns 7.3.1 Data Cache 7.3.2 Event Notifications 7.3.3 Task Scheduling 7.4 GUI Scalability Summary EXERCISES REFERENCES 8 Reliability Assurance 8.1 Thread Safe Patterns 8.1.1 Serializing GUI Updates 8.1.2 Serializing Shared Memory Access 8.1.3 Thread Synchronization 8.2 Memory Leaks 8.3 Reliable Persistent Storage 8.3.1 Isolation and Consistency 8.3.2 Atomicity and Durability 8.3.3 Sharded Persistent Storage 8.4 Data Validation 8.4.1 Input Validation 8.4.2 Integrity Constraints 8.5 Stateful Data Transport Summary EXERCISES REFERENCES 9 Availability and Fault-Tolerance 9.1 Availability Primitives 9.1.1 Design Diversity 9.1.2 Broadcast Primitives 9.2 Critical Communication Availability 9.2.1 Network Fault Tolerance 9.2.2 Design Diverse Emergency Communication Architecture 9.3 Sensor Fusion and Redundancy 9.4 Data Availability 9.4.1 Data Synchronization 9.4.2 Data Sharing 9.5 Battery Power Saving Summary EXERCISES REFERENCES 10 Security and Trust 10.1 Cryptographic Primitives 10.1.1 Symmetric Cryptography 10.1.2 Asymmetric Cryptography 10.1.3 Message Digest 10.1.4 Message Authentication Codes 10.1.5 Digital Signatures 10.2 Secure Web Access 10.2.1 User Authentication 10.2.2 Authentication Delegation and Single Sign On 10.2.3 Access and Authorization Delegation 10.2.4 Peer-Authentication and Confidentiality 10.3 Secure Network Access 10.3.1 Transport Layer Security 10.3.2 Layer 3 Security 10.3.3 Layer 2 Security 10.4 Secure System Access 10.4.1 Mobile Application Authenticity 10.4.2 Securing Inter-Application Communication 10.4.3 Permissions and Access Control Summary EXERCISES REFERENCES Appendix A Appendix B B.1 Compile and Deploy a Servlet B.2 Compile and Deploy a Web Socket Hub B.3 Configure Tomcat to Enable SSL B.4 Install and Configure Jenkins B.5 Install Metrics Reloaded Index
£75.99
Springer Nature Switzerland AG Service-Oriented and Cloud Computing: 8th IFIP WG 2.14 European Conference, ESOCC 2020, Heraklion, Crete, Greece, September 28–30, 2020, Proceedings
Book SynopsisThis book constitutes the refereed proceedings of the 8th IFIP WG 2.14 European Conference on Service-Oriented and Cloud Computing, ESOCC 2020, held in Heraklion, Crete, Greece, in September 2020. The 6 full and 8 short papers presented in this volume were carefully reviewed and selected from 20 submissions. The main event mapped to the main research track which focused on the presentation of cutting-edge research in both the service-oriented and cloud computing areas. In conjunction, an industrial track was also held attempting to bring together academia and industry through showcasing the application of service-oriented and cloud computing research, especially in the form of case studies, in the industry.The chapters ‘Identification of Comparison Key Elements and their Relationships for Cloud Service Selection’ and ‘Technology-Agnostic Declarative Deployment Automation of Cloud Applications’ are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.Table of ContentsFormal Methods.- Testing conformance in multi-component enterprise application management.- Formalizing Event-Driven Behavior of Serverless Applications.- Probabilistic Verification of Outsourced Computation Based on Novel Reversible PUFs.- Cloud Service and Platform Selection.- Multiplayer game backends: A Comparison of commodity cloud-based approaches.- Are Cloud Platforms Ready for Multi-Cloud?.- Identification of Comparison Key Elements and their Relationships for Cloud Service Selection.- Deployment and Workflows.- Deployable Self-Contained Workflow Models.- Technology-Agnostic Declarative Deployment Automation of Cloud Applications.- Blockchain-Based Healthcare Workflows in Federated Hospital Clouds.- Monitoring.- Monitoring Behavioral Compliance with Architectural Patterns based on Complex Event Processing.- Towards Real-Time Monitoring of Data Centers using Edge Computing.- Modeling Users' Performance: Predictive Analytics in an IoT Cloud Monitoring System.- Data Distribution and Analytics.- Multi-Source Distributed System Data for AI-powered Analytics.- Blockchain- and IPFS-based Data Distribution for the Internet of Things.
£44.99
Springer Nature Switzerland AG Society with Future: Smart and Liveable Cities: First EAI International Conference, SC4Life 2019, Braga, Portugal, December 4-6, 2019, Proceedings
Book SynopsisThis book constitutes the refereed post-conference proceedings of the First International Conference on Society with Future: Smart and Liveable Cities, SC4Life 2019, which took place in Braga, Portugal, in December 2019. The 13 revised full papers were carefully reviewed and selected from 19 submissions. The conference has brought researchers, developers, and practitioners who are leveraging and develoing new knowledge on the topic of smart cities, offering more efficiency to main infrastructures, utilities and services, creating a sustainable urban environment that improves the quality of life for its citizens and enhances economic development.Table of ContentsSustainable road infrastructures using smart materials, NDT, and FEM-based crack prediction.- Quantifying the carbon dioxide emissions resulting from awareness-raising actions of sustainable mobility.- Leak Detection in Water Distribution Networks via Pressure Analysis using a Machine Learning Ensemble.- Solutions for Improving the Energy Efficiency of Buildings Refurbishment Image recognition to improve positioning in smart urban environments.- An Hybrid Novel Layered Architecture and Case Study : IoT for Smart Agriculture and Smart LiveStock.- Agrilogistics - A Genetic Programming Based Approach.- Real World Third-Person with Multiple Point-of-Views for Immersive Mixed Reality.- Internet of Things for Enhanced Smart Cities: A Review, Roadmap and Case Study on Air Quality Sensing.- Smart pedestrian network: an integrated conceptual model for improving walkability.- Building future societies? A brief analysis of Braga’s School Bus project.- City rankings and the citizens: exposing representational and participatory gaps.- Mobility time style: For an integrated view of time and mobilities in societies with a future.
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Springer Nature Switzerland AG Similarity Search and Applications: 13th International Conference, SISAP 2020, Copenhagen, Denmark, September 30 – October 2, 2020, Proceedings
Book SynopsisThis book constitutes the refereed proceedings of the 13th International Conference on Similarity Search and Applications, SISAP 2020, held in Copenhagen, Denmark, in September/October 2020. The conference was held virtually due to the COVID-19 pandemic.The 19 full papers presented together with 12 short and 2 doctoral symposium papers were carefully reviewed and selected from 50 submissions. The papers are organized in topical sections named: scalable similarity search; similarity measures, search, and indexing; high-dimensional data and intrinsic dimensionality; clustering; artificial intelligence and similarity; demo and position papers; and doctoral symposium.Table of ContentsScalable Similarity Search.- Accelerating Metric Filtering by Improving Bounds on Estimated Distances.- Differentially Private Sketches for Jaccard Similarity Estimation.- Pivot Selection for Narrow Sketches by Optimization Algorithms.- mmLSH: A Practical and Efficient Technique for Processing Approximate Nearest Neighbor Queries on Multimedia Data.- Parallelizing Filter-Verification based Exact Set Similarity Joins on Multicores.- Similarity Search with Tensor Core Units.- On the Problem of p1 in Locality-Sensitive Hashing.- Similarity Measures, Search, and Indexing.- Confirmation Sampling for Exact Nearest Neighbor Search.- Optimal Metric Search Is Equivalent to the Minimum Dominating Set Problem.- Metrics and Ambits and Sprawls, Oh My: Another Tutorial on Metric Indexing.- Some branches may bear rotten fruits: Diversity browsing VP-Trees.- Continuous Similarity Search for Evolving Database.- Taking advantage of highly-correlated attributes in similarity queries with missing values.- Similarity Between Points in Metric Measure Spaces.- High-dimensional Data and Intrinsic Dimensionality.- GTT: Guiding the Tensor Train Decomposition.- Noise Adaptive Tensor Train Decomposition for Low-Rank Embedding of Noisy Data.- ABID: Angle Based Intrinsic Dimensionality.- Sampled Angles in High-Dimensional Spaces.- Local Intrinsic Dimensionality III: Density and Similarity.- Analysing Indexability of Intrinsically High-dimensional Data using TriGen.- Reverse k-Nearest Neighbors Centrality Measures and Local Intrinsic Dimension.- Clustering.- BETULA: Numerically Stable CF-Trees for BIRCH Clustering.- Using a Set of Triangle Inequalities to Accelerate K-means Clustering.- Angle-Based Clustering.- Artificial Intelligence and Similarity.- Improving Locality Sensitive Hashing by Efficiently Finding Projected Nearest Neighbors.- SIR: Similar Image Retrieval for Product Search in E-Commerce.- Cross-Resolution deep features based Image Search.- Learning Distance Estimators from Pivoted Embeddings of Metric Objects.- Demo and Position Papers.- Visualizer of Dataset Similarity using Knowledge Graph.- vitrivr-explore: Guided Multimedia Collection Exploration for Ad-hoc Video Search.- Running experiments with confidence and sanity.- Doctoral Symposium.- Temporal Similarity of Trajectories in Graphs.- Relational Visual-Textual Information Retrieval.
£71.24
Springer Nature Switzerland AG The Elements of Big Data Value: Foundations of
Book SynopsisThis open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation. Table of ContentsPart I: Ecosystem Elements of Big Data Value.- The European Big Data Value Ecosystem.- Stakeholder Analysis of Data Ecosystems.- A Roadmap to Drive Adoption of Data Ecosystems.- Achievements and Impact of the Big Data Value Public-Private Partnership: The Story so Far.- Part II: Research and Innovation Elements of Big Data Value.- Technical Research Priorities for Big Data.- A Reference Model for Big Data Technologies.- Data Protection in the Era of Artificial Intelligence: Trends, Existing Solutions and Recommendations for Privacy-Preserving Technologies.- A Best Practice Framework for Centres of Excellence in Big Data and Artificial Intelligence.- Data Innovation Spaces.- Part III: Business, Policy, and Societal Elements of Big Data Value.- Big Data Value Creation by Example.- Business Models and Ecosystem for Big Data.- Innovation in Times of Big Data and AI: Introducing the Data-Driven Innovation (DDI) Framework.- The Road to Big Data Standardisation.- The Role of Data Regulation in Shaping AI: An Overview of Challenges and Recommendations for SMEs.- Part IV: Emerging Elements of Big Data Value.- Data Economy 2.0: From Big Data Value to AI Value and a European Data Space.
£34.99
Springer Nature Switzerland AG Internet of Things from Hype to Reality: The Road
Book SynopsisThis revised textbook presents updated material on its core content: an end-to-end IoT architecture that is comprised of devices, network, compute, storage, platform, applications along with management and security components. As with the second edition, it is organized into six main parts: an IoT reference model; fog computing and the drivers; IoT management and applications; smart services in IoT; IoT standards; and case studies. This edition’s features include overhaul of the IoT Protocols (Chapter 5) to include an expanded treatment of low-power wide area networks including narrow band IoT (NB-IoT) protocol, updated IoT platforms and capabilities (Chapter 7) to include comparison of commercially available platforms (e.g. AWS IoT Platform, Google Cloud IoT Platform, Microsoft Azure IoT Platform, and PTC ThinkWorx), updated security (Chapter 8) to include approaches for securing IoT devices with examples of IoT devices used in security attacks and associated solutions including MUD and DICE, and finally new Appendix B to include six IoT project detailed for students.Table of ContentsIntroduction.- Part I: IoT Overview and Architecture.- IoT Timeline.- IoT Reference Model.- Evolution of IoT Protocol Stack.- State of the Industry.- Part II: Fog Computing.- Why Fog.- Defining the Fog.- Data In Motion.- Part III: IoT Management and Applications.- IoT Management.- IoT Security.- IoT Traffic Engineering.- IoT Applications.- Part IV: IoT-Based Smart Services.- Smart Service Framework.- Creating Smart Services.- Service Creation, development and delivery.- Ecosystems Partners.- Services reference architecture.- Part V: IoT Standards.- OneM2M.- ATSI.- ETSI.- IEEE.- Part VI: Invited Chapters.- IoT Business Models.- Open Source Initiatives.- Data in Motion. The Blockchain in IoT.- Conclusion.
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Springer Nature Switzerland AG Smart Objects and Technologies for Social Good: 7th EAI International Conference, GOODTECHS 2021, Virtual Event, September 15–17, 2021, Proceedings
Book SynopsisThis book constitutes the refereed post-conference proceedings of the 7th EAI International Conference on Smart Objects and Technologies for social Good, GOODTECHS 2021, held in September 2021. Due to COVID-19 pandemic the conference was held virtually. The 24 full papers presented were selected from 53 submissions and issue design, implementation, deployment, operation, and evaluation of smart objects and technologies for social good. Social goods are products and services provided through private enterprises, government, or non-profit institutions and are related to healthcare, safety, sports, environment, democracy, computer science, and human rights. The papers are arranged in tracks on machine learning; IoT; social considerations of technology; technology and ageing; healthcare.Table of ContentsLearning.- Balancing activity recognition and privacy preservation with a multi-objective evolutionary algorithm.- Biometric data capture as a way to identify lack f physical activity in daily life.- Comparative Analysis of Process Mining Algorithms in Python.- COVID-19 Next Day Trend ForecastAnomaly Detection in Cellular IoT with Machine Learning.- Internet of Things.- A Smart IoT System for Water Monitoring and Analysis.- Decentralising the Internet of Medical Things with Distributed Ledger Technologies and Off-Chain Storages: a Proof of Concept.- Towards a Monitoring Framework for Users of Retirement Houses with Mobile Sensing.- Temporal authorization graphs: Pros, Cons and Limits.- Advanced 5G Network Slicing Isolation Using Enhanced VPN+ for Healthcare Verticals.- Social considerations of technology.- GuideSwarm: A Drone Network Design to Assist Visually-impaired People.- LISA - Lingua Italiana dei Segni Accessibile: A Progressive Web App to Support Communication Between Deaf People and Public Administrations.- Building emotionally stable, inclusive, and healthy communities with ICT: from state of the art to PSsmile app.- issue design, implementation, deployment, operation, and evaluation of smart objects and technologies for social good. Social goods are products and services provided through private enterprises, government, or non-profit institutions and are related to healthcare, safety, sports, environment, democracy, computer science, and human rights. The papers are arranged in tracks on machine learning; IoT; social considerations of technology; technology and ageing; healthcare.- Machine Management Technology for Institutional Environment in Pandemic Times.- Technology and ageing.- Augmented Reality, Vrtual Reality and Mixed Reality as driver tools for promoting cognitive activity and avoid isolation in ageing population.- Ageing@home: A secure 5G welfare technology solution for elderlies.- Defining the instruments for zero-measurement of psychological well-being at older adults.- DERCA Tool: A set of Tests for Analysis of Elderly Dexterity in Information and Communications Technologies.- Building Inclusive Environments for All Ages with Citizens.- Healthcare.- The New Era of Technology applied to Cardiovascular Patients: State-of-the-art and Questionnaire applied for a System Proposal.- Co-design and engineering of user requirements for a novel ICT healthcare solution in Murcia, Spain.- What do nurses and carers in Portual wish and need from a digital intelligent assistant for nursing applications.- Examining Furniture Preferences of The Elderly in Greece.
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Springer Technical and Regulatory Perspectives on
Book Synopsis1. Introduction.- 2. Regulatory Initiatives.- 3. Biases, Fairness, and Non-discrimination.- 4. Transparency.- 5. Privacy and Security.- 6. Conclusions and Open Challenges.
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Springer Information Access in the Era of Generative AI
Book Synopsis1. Introduction.- 2. Foundations of Generative IR.- 3. Interactions With Generative IR Systems.- 4. Adapting Generative IR Systems to Users, Tasks, and Scenarios.- 5. Improving Generative IR Systems Based on User Feedback.- 6. Generative IR Evaluation.- 7. Sociotechnical Implications of Generative AI for Information Access.- 8. Recommendation in the Era of Generative AI.- 9. Designing for the Future of Information Access with Generative IR.
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Springer Advanced Multimodal Compatibility Modeling and Recommendation
Book SynopsisIntroduction.- Related Work.- Category-guided Multimodal Compatibility Modeling.- Try-on-guided Multimodal Compatibility Modeling.- Attribute-enhanced Multimodal Recommendation.- Modality Correlation-based Multimodal Recommendation.- Efficient Hashing-based Multimodal Recommendation.- Research Frontiers.
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Springer Metadata and Semantic Research
Book Synopsis.- Track on Metadata, Linked Data, Semantics and Ontologies - General Session..- Towards MatCore: A Unified Metadata Standard for Materials Science..- DATA-FW: An Ontology Network for Annotating Open Datasets..- A Proposed Methodology for Sub-Ontology Development in Comprehensive Scientific Investigation Methods and Tooling..- Representation Learning on IoT Knowledge Graphs..- The Use-Case of Enhanced AEON in Education..- A RAG Approach for Generating Competency Questions in Ontology Engineering..- Modeling Modern and Historical Data as a Knowledge Graph: A Case Study for Earthquake Data..- Towards a Knowledge Graph for Models and Algorithms in Applied Mathematics..- Developing data sets for training OCR/HTR systems for the late 19th century Greek texts..- JobHive: A Semantic Path-Based Platform for E-Recruitment Recommendation..- Track on Open Repositories, Research Information Systems & Data Infrastructures. .- Making Sense of Metadata Mess: Alignment & Risk Assessment for Diatom Data Use Case. .- A Health Tourism Ontology Framework for Versatile Applications..- Cross-referencing Metadata through an extension of the MEDFORD language..- Aligning Data Management Plans with Community Standards using FAIR Implementation Profiles..- A Greek Music Audiovisual Collections platform: presentation of the open source ReasonableGraph platform for music collections..- Track on Digital Libraries, Information Retrieval, Big, Linked, Social & Open Data..- The integration of the Pinakes Model to the IFLA Library Reference Model. .- The Convergence of Open Data, Linked Data, Ontologies, and Large Language Models: Enabling Next-Generation Knowledge Systems..- Semantic enrichment of metadata in the Rede Bibliodata..- Track on Cultural Collections & Application..- On the interoperability between Archival and Library Authorities..- Applying new standards to legacy data for semantic interoperability and multilingualism: a case study at the National Library of Greece..- CTP Ontology: An Ontology for Creating and Structuring Cultural Thematic Paths..- Ontological Patterns for Modelling Art Exhibitions: an initial investigation..- Building a transliteration tool to enhance the exchange of metadata about Greek authors..- Track on European and National Projects; and 8th DOAbLE - Papers for Libraries, Archives, Museums..- Creation of a music ontology in the framework of the project Greek Music Audiovisual Collections (M.EL.O.S.). .- Metadata-driven Cross-Infrastructure Integration between Solid Earth and Marine sciences in the GEO-INQUIRE project..- Public libraries - aggregators of new and reusable knowledge resources for the users' creative development..- Track on Agriculture, Food & Environment (AgroSEM'24..- Vector Spaces Model: A Knowledge Integration Method for Research on Linkage Relationships in Agricultural Science and Technology. .- Track on Digital Humanities and Digital Curation..- The semantics of emotion: Exploring Synonym Rings to evaluate emotive contexts in translations across Sinhala and English.
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Springer Knowledge Discovery Knowledge Engineering and Knowledge Management
Book Synopsis.- Knowledge Discovery and Information Retrieval..- Closeness Centrality: Definition, and Its Computation for Homogeneous Multilayer Networks..- Automatic Categorization of Software Repository Domains with Minimal Resources..- Personalized Book Recommendations for Adults Using Deep Learning and Sophisticated Filtering Approaches..- Dimensionality reduction of environmental data to predict species distribution..- Is There an Optimal Depth of Residual Networks?..- Modeling Interdependencies and Cascading Effects of Disasters on Critical Infrastructures..- Knowledge Engineering and Ontology Development..- Mechanical Fault Prediction Based on Event Knowledge Graph and Deep Learning..- BioSTransformers for Health Ontologies Merging..- Methodology For Real Estate Recommendation Based on Customer Behavior Knowledge as Context Approach..- UpKG: A Framework for Integrating and Evaluating Novel Domains into Knowledge Graphs..- An Approach Based on the Multifaceted Ontology to Development of Event Series Processing Tools..- A Study of the Perceived Quality and Functionality of DEMO Process and Fact Models in the Health Domain and Improvements on Its Action Model..- Knowledge Management and Information Systems..- Revolutionary Synergy: The Fusion of Data Mesh and Data Fabric for Strategy Analytics in GRAPHYP Knowledge Graph..- An Innovative Framework for Threshold Exceedance Forecasting in Timeseries Using Survival Analysis..- Promoting Sustained Use of Assistive Technology Among the Elderly: A User Experience and Causal Attribution Theory Perspective on Caregiver Utterances..- Knowledge Management in Financial Software Support Team: A Prototype Based on Ontology..- A Conceptual Model for Mapping Organizational Knowledge Ecosystem.
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Springer The Semantic Web
Book SynopsisResearch: An Algebraic Foundation for Knowledge Graph Construction.- Inductive Higher Order Embeddings.- ReaLitE: Enrichment of Relation Embeddings in Knowledge Graphs using Numeric Literals.- Evaluating Approximate Nearest Neighbour Search Systems on Knowledge Graph Embeddings.- On Evaluation Metrics for Complex Matching based on Reference Alignments.- Kastor: Fine-tuned Small Language Models for Shape-based Active Relation Extraction.- Predicting the Road Ahead: A Knowledge Graph based Foundation Model for Scene Understanding in Autonomous Driving.- ANTS: Abstractive Entity Summarization in Knowledge Graphs.- Delete/Rederive with Marking for Update Streams.- Balancing Privacy and Utility: Semantic Anonymization of Time-aware Knowledge Graphs.- Training-free Score Calibration for Complex Query Decomposition.- Information-aware Entity Indexing in Knowledge Graphs to Enable Semantic Search.- Explainable Temporal Fact Validation Through Constraints Discovery in Knowledge Graphs.- Multi-dataset and transfer learning using gene expression knowledge graphs for patient diagnosis.- Robustness Evaluation of Knowledge Graph Embedding Models under Non-targeted Attacks.- Predicting clinical outcomes from patient care pathways represented with temporal knowledge graphs.- AvengER: Ensembling and Fine-Tuning LLMs for Select Prompts in Entity Resolution.- Ontology Generation using Large Language Models.- Towards Practicable Algorithms for Rewriting Graph Queries beyond DL-Lite.- Designing Hierarchies for Optimal Hyperbolic Embedding.- RDF-based Semantics for Selective Disclosure and Zero-knowledge Proofs on Verifiable Credentials.- Taxonomy Inference for Tabular Data Using Large Language Models.- GeoRDF2vec – Learning Location-Aware Entity Representations in Knowledge Graphs.- RelCheck: Improving Relation Extraction with Ontology-Guided and LLM-Based Validation.- Analyzing the Influence of Knowledge Graph Information on Relation Extraction.- Extending Shape Expressions with an inheritance mechanism.
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Springer The Semantic Web
Book SynopsisIn-Use: Towards Open Archival Linked Data (ALD): The Case of Swedish National Archives.- Language-Based Testing for Knowledge Graphs.- OWL strict: A Constrained OWL Fragment to avoid Ambiguities for Knowledge Graph Practitioners.- py-amr2fred: A Python Library for Converting Text into OWL-Compliant RDF Knowledge Graphs.- LLM-Supported Mapping Generation for Semantic Manufacturing Treasure Hunting.- Knowledge Graph Construction for Health, Lifestyle and Fitness Applications.- Semantic Technologies for Global Governance: A Hybrid AI Approach to Tracking and Monitoring WHO Resolutions.- Research Knowledge Graphs: the Shifting Paradigm of Scholarly Information Representation. Resource: MOOC on Linguistic Linked Data.- OntoAligner: A Comprehensive Modular and Robust Python Toolkit for Ontology Alignment.- Interoperable Interpretation and Evaluation of ODRL Policies.- The Semantic Web Language Server: enhancing the developer experience for Semantic Web practitioners.- mobilityDCAT-AP: a Metadata Specification for Enhanced Cross-border Mobility Data Sharing.- LLMs4SchemaDiscovery: A Human-in-the-Loop Workflow for Scientific Schema Mining with Large Language Models.- DBpedia-TKG: Capturing Wikipedia’s Evolution as Temporal Knowledge Graphs.- LLM-KG-Bench 3.0: A Compass for Semantic Technology Capabilities in the Ocean of LLMs.- Incremunica: Web-based Incremental View Maintenance for SPARQL.- ShowVoc: a Thorough Platform for Publishing and Browsing Linked Open Datasets.- Procedural Knowledge Ontology (PKO).
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Springer Business Process Management
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Springer Similarity Search and Applications
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Springer Knowledge Discovery Knowledge Engineering and Knowledge Management
Book Synopsis.- Knowledge Discovery and Information Retrieval..- Identification of Sex-Specific Gene Signatures for Atopic Dermatitis Using Machine Learning Models..- Subset Pretraining for Enhancing Neural Network Training Efficiency..- Enhancing Text Embeddings for Emotion Detection: A Study on Dimensionality Reduction and Lexicon Filtering..- Knowledge Graph Mining-Based Personalized Learning Path Recommendation for English Learning: Leveraging Adaptive Techniques for Improved Outcomes..- Enhanced Prediction of Post-Myocardial Infarction Complications:Dual-Modality Analysis with Optimized Flow Cytometry Preprocessing and Feature Visualization..- A Generative Framework for Web Pages Classification Using Multi-Modal Topic Fusion..- A Systematic Literature Review on LLM-Based Content Classification..- Enhanced Document and Database Integration for Advanced Question-Answering in Enterprise Contract Management with LLMs and Agents..- Knowledge Engineering and Ontology Development..- Enhancing Bilateral International Trade Flow Analysis with Knowledge Graph Embeddings..- Knowledge Management and Information Systems..- Semantic Support in Standardized Environments..- From Lessons Learned to Project Triumph: Unveiling the Enablers and Barriers in Construction..- How Does Automation Impact Healthcare Operations? A Model to Describe the Impact of Robotic Process Automation and AI-Enhanced Intelligent Automation in Healthcare..- Uncertainty Analysis in Socio-Economic Dynamic Microsimulation Models: A Literature Review..- Utilizing ER Model Extraction for an Industry Data Validation Use Case..- Design and Validation of a Digital Mindset Model: A Combination of Organizational Culture Theory and Design Science..- Artificial Intelligence for Improving Drivers’ Emotional Intelligence: An Innovative Approach for Safer Roads..- Systemic View on Creating Knowledge Maps: Putting the Pieces Together.
£64.99
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Advances in Intelligent Data Analysis: Third
Book SynopsisFormanyyearstheintersectionofcomputing anddataanalysiscontainedme- based statistics packages and not much else. Recently, statisticians have - braced computing, computer scientists have started using statistical theories and methods, and researchers in all corners have invented algorithms to nd structure in vast online datasets. Data analysts now have access to tools for exploratory data analysis, decision tree induction, causal induction, function - timation,constructingcustomizedreferencedistributions,andvisualization,and thereareintelligentassistantsto adviseonmatters ofdesignandanalysis.There aretoolsfortraditional,relativelysmallsamples,andalsoforenormousdatasets. In all, the scope for probing data in new and penetrating ways has never been so exciting. The IDA-99 conference brings together a wide variety of researchers c- cerned with extracting knowledge from data, including people from statistics, machine learning, neural networks, computer science, pattern recognition, da- base management, and other areas.The strategiesadopted by people from these areas are often di erent, and a synergy results if this is recognized. The IDA series of conferences is intended to stimulate interaction between these di erent areas,sothatmorepowerfultoolsemergeforextractingknowledgefromdataand a better understanding is developed of the process of intelligent data analysis. The result is a conference that has a clear focus (one application area:intelligent data analysis) and a broad scope (many di erent methods and techniques).Table of ContentsLearning.- From Theoretical Learnability to Statistical Measures of the Learnable.- ALM: A Methodology for Designing Accurate Linguistic Models for Intelligent Data Analysis.- A “Top-Down and Prune” Induction Scheme for Constrained Decision Committees.- Mining Clusters with Association Rules.- Evolutionary Computation to Search for Strongly Correlated Variables in High-Dimensional Time-Series.- The Biases of Decision Tree Pruning Strategies.- Feature Selection as Retrospective Pruning in Hierarchical Clustering.- Discriminative Power of Input Features in a Fuzzy Model.- Learning Elements of Representations for Redescribing Robot Experiences.- “Seeing“ Objects in Spatial Datasets.- Intelligent Monitoring Method Using Time Varying Binomial Distribution Models for Pseudo-Periodic Communication Traffic.- Visualization.- Monitoring Human Information Processing via Intelligent Data Analysis of EEG Recordings.- Knowledge-Based Visualization to Support Spatial Data Mining.- Probabilistic Topic Maps: Navigating through Large Text Collections.- 3D Grand Tour for Multidimensional Data and Clusters.- Classification and Clustering.- A Decision Tree Algorithm for Ordinal Classification.- Discovering Dynamics Using Bayesian Clustering.- Integrating Declarative Knowledge in Hierarchical Clustering Tasks.- Nonparametric Linear Discriminant Analysis by Recursive Optimization with Random Initialization.- Supervised Classification Problems: How to Be Both Judge and Jury.- Temporal Pattern Generation Using Hidden Markov Model Based Unsupervised Classification.- Exploiting Similarity for Supporting Data Analysis and Problem Solving.- Multiple Prototype Model for Fuzzy Clustering.- A Comparison of Genetic Programming Variants for Data Classification.- Fuzzy Clustering Based on Modified Distance Measures.- Building Classes in Object-Based Languages by Automatic Clustering.- Integration.- Adjusted Estimation for the Combination of Classifiers.- Data-Driven Theory Refinement Using KBDistAl.- Reasoning about Input-Output Modeling of Dynamical Systems.- Undoing Statistical Advice.- A Method for Temporal Knowledge Conversion.- Applications.- Intrusion Detection through Behavioral Data.- Bayesian Neural Network Learning for Prediction in the Australian Dairy Industry.- Exploiting Sample-Data Distributions to Reduce the Cost of Nearest-Neighbor Searches with Kd-Trees.- Pump Failure Detection Using Support Vector Data Descriptions.- Data Mining for the Detection of Turning Points in Financial Time Series.- Computer-Assisted Classification of Legal Abstracts.- Sequential Control Logic Inferring Method from Observed Plant I/O Data.- Evaluating an Eye Screening Test.- Application of Rough Sets Algorithms to Prediction of Aircraft Component Failure.- Media Mining.- Exploiting Structural Information for Text Classification on the WWW.- Multi-agent Web Information Retrieval: Neural Network Based Approach.- Adaptive Information Filtering Algorithms.- A Conceptual Graph Approach for Video Data Representation and Retrieval.
£94.99
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Begriffliche Wissensverarbeitung: Methoden und
Book SynopsisDieses Buch stellt Methoden der Begrifflichen Wissensverarbeitung vor und präsentiert Anwendungen aus unterschiedlichen Praxisfeldern. Im Methodenteil wird in moderne Techniken der Begrifflichen Datenanalyse und Wissensverarbeitung eingeführt. Hierbei werden die mathematischen Grundlagen abgehandelt und durch zahlreiche Beispiele anschaulich gemacht. Der zweite Teil des Buches richtet sich verstärkt an potentielle Anwender. An ausgewählten Anwendungen wird die Vorgehensweise bei der Datenanalyse und dem Information Retrieval mit den Methoden der Begrifflichen Wissensverarbeitung vorgestellt und ihr Potential aufgezeigt.Table of ContentsI: Methoden der Begrifflichen Wissensverarbeitung.- Begriffe und Implikationen.- ConImp - Ein Programm zur Formalen Begriffsanalyse.- Ähnlichkeit als Distanz in Begriffsverbänden.- Datenanalyse mit Fuzzy-Begriffen.- Terminologische Merkmalslogik in der Formalen Begriffsanalyse.- II: Anwendungen der Begrifflichen Wissensverarbeitung.- Formale Begriffsanalyse im Software Engineering.- Zugriffskontrolle bei Programmsystemen und im Datenschutz mittels Formaler Begriffsanalyse.- Inhaltliche Erschließung des Bereichs 'Sozialorientierte Gestaltung von Informationstechnik' - Ein begriffsanalytischer Ansatz.- Wissensdarstellungen in Informationssystemen, Fragetypen und Anforderungen an Retrievalkomponenten.- Ein TOSCANA-Erkundungssystem zur Literatursuche.- Ein Erkundungssystem zum Baurecht: Methoden der Entwicklung eines TOSCANA-Systems.- Begriffliche Erkundung semantischer Strukturen von Sprechaktverben.- Grundwerte, Ziele und Maßnahmen in einem regionalen Krankenhaus - Eine Anwendung des Verfahrens GABEK.- Normen- und regelgeleitete internationale Kooperationen - Formale Begriffsanalyse in der Politikwissenschaft.- Entwicklung eines kontextuellen Methodenkonzeptes mit Hilfe der Formalen Begriffsanalyse an Beispielen zum Risikoverständnis.- Über Möglichkeiten der Formalen Begriffsanalyse in der Mathematischen Archäochemie.
£59.99
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Web Information Retrieval
Book SynopsisWith the proliferation of huge amounts of (heterogeneous) data on the Web, the importance of information retrieval (IR) has grown considerably over the last few years. Big players in the computer industry, such as Google, Microsoft and Yahoo!, are the primary contributors of technology for fast access to Web-based information; and searching capabilities are now integrated into most information systems, ranging from business management software and customer relationship systems to social networks and mobile phone applications.Ceri and his co-authors aim at taking their readers from the foundations of modern information retrieval to the most advanced challenges of Web IR. To this end, their book is divided into three parts. The first part addresses the principles of IR and provides a systematic and compact description of basic information retrieval techniques (including binary, vector space and probabilistic models as well as natural language search processing) before focusing on its application to the Web. Part two addresses the foundational aspects of Web IR by discussing the general architecture of search engines (with a focus on the crawling and indexing processes), describing link analysis methods (specifically Page Rank and HITS), addressing recommendation and diversification, and finally presenting advertising in search (the main source of revenues for search engines). The third and final part describes advanced aspects of Web search, each chapter providing a self-contained, up-to-date survey on current Web research directions. Topics in this part include meta-search and multi-domain search, semantic search, search in the context of multimedia data, and crowd search.The book is ideally suited to courses on information retrieval, as it covers all Web-independent foundational aspects. Its presentation is self-contained and does not require prior background knowledge. It can also be used in the context of classic courses on data management, allowing the instructor to cover both structured and unstructured data in various formats. Its classroom use is facilitated by a set of slides, which can be downloaded from www.search-computing.org.Trade ReviewFrom the reviews:“The book covers not only a wide range, but everything that is essential to the topic of Web information retrieval. … this book is an excellent starting point into the field of Web information retrieval, and can be recommended for classroom use.” (Gottfried Vossen, zbMATH, Vol. 1283, 2014)“... this book is a valuable resource for students and instructors in web IR, primarily as a reference to supplement course teaching. Researchers and practitioners should find the book a useful quick reference guide for key concepts, techniques, and recent trends in web IR.” (Wingyan Chung, ACM Computing Reviews, July 2014)Table of ContentsPart I Principles of Information Retrieval.- An Introduction to Information Retrieval.- The Information Retrieval Process.- Information Retrieval Models.- Classification and Clustering.- Natural Language Processing for Search.- Part II Information Retrieval for the Web.- Search Engines.- Link Analysis.- Recommendation and Diversification for the Web.- Advertising in Search.- Part III Advanced Aspects of Web Search.- Publishing Data on the Web.- Meta-Search and Multi-Domain Search.- Semantic Search.- Multimedia Search.- Search Process and Interfaces.- Human Computation and Crowd Search.
£59.99
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Web Information Retrieval
Book SynopsisWith the proliferation of huge amounts of (heterogeneous) data on the Web, the importance of information retrieval (IR) has grown considerably over the last few years. Big players in the computer industry, such as Google, Microsoft and Yahoo!, are the primary contributors of technology for fast access to Web-based information; and searching capabilities are now integrated into most information systems, ranging from business management software and customer relationship systems to social networks and mobile phone applications.Ceri and his co-authors aim at taking their readers from the foundations of modern information retrieval to the most advanced challenges of Web IR. To this end, their book is divided into three parts. The first part addresses the principles of IR and provides a systematic and compact description of basic information retrieval techniques (including binary, vector space and probabilistic models as well as natural language search processing) before focusing on its application to the Web. Part two addresses the foundational aspects of Web IR by discussing the general architecture of search engines (with a focus on the crawling and indexing processes), describing link analysis methods (specifically Page Rank and HITS), addressing recommendation and diversification, and finally presenting advertising in search (the main source of revenues for search engines). The third and final part describes advanced aspects of Web search, each chapter providing a self-contained, up-to-date survey on current Web research directions. Topics in this part include meta-search and multi-domain search, semantic search, search in the context of multimedia data, and crowd search.The book is ideally suited to courses on information retrieval, as it covers all Web-independent foundational aspects. Its presentation is self-contained and does not require prior background knowledge. It can also be used in the context of classic courses on data management, allowing the instructor to cover both structured and unstructured data in various formats. Its classroom use is facilitated by a set of slides, which can be downloaded from www.search-computing.org.Trade ReviewFrom the reviews:“The book covers not only a wide range, but everything that is essential to the topic of Web information retrieval. … this book is an excellent starting point into the field of Web information retrieval, and can be recommended for classroom use.” (Gottfried Vossen, zbMATH, Vol. 1283, 2014)“... this book is a valuable resource for students and instructors in web IR, primarily as a reference to supplement course teaching. Researchers and practitioners should find the book a useful quick reference guide for key concepts, techniques, and recent trends in web IR.” (Wingyan Chung, ACM Computing Reviews, July 2014)Table of ContentsPart I Principles of Information Retrieval.- An Introduction to Information Retrieval.- The Information Retrieval Process.- Information Retrieval Models.- Classification and Clustering.- Natural Language Processing for Search.- Part II Information Retrieval for the Web.- Search Engines.- Link Analysis.- Recommendation and Diversification for the Web.- Advertising in Search.- Part III Advanced Aspects of Web Search.- Publishing Data on the Web.- Meta-Search and Multi-Domain Search.- Semantic Search.- Multimedia Search.- Search Process and Interfaces.- Human Computation and Crowd Search.
£44.99
Springer Information Retrieval
Book Synopsis.- Play to Your Strengths: Collaborative Intelligence of Conventional Recommender Models and Large Language Models..- A Dual-Aligned Model for Multimodal Recommendation..- CASINet: A Context-Aware Social Interaction Rumor Detection Network..- A Claim Decomposition Benchmark for Long-form Answer Verification..- Dual-granularity Hierarchical Fusion Network for Multimodal Humor Recognition on Memes..- Exploring the Potential of Dimension Reduction in Building Efficient Dense Retrieval Systems..- Relation Extraction Model Based on Overlap Rules and Abductive Learning..- Multi-task Instruction Tuning for Temporal Question Answering over Knowledge Graphs..- On the Capacity of Citation Generation by Large Language Models..- Are Large Language Models More Honest in Their Probabilistic or Verbalized Confidence?..- QUITO: Accelerating Long-Context Reasoning through Query-Guided Context Compression.
£44.99
Springer Science of Cyber Security
Book Synopsis.- A Novel Scoring Algorithm Against HID Attacks Based on Static Text Feature Matching..- Identifying Ransomware Functions through Microarchitectural Side-channel Analysis..- STARMAP: Multi-machine Malware Analysis System for Lateral Movement Observation..- LogSHIELD: A Graph-based Real-time Anomaly Detection Framework using Frequency Analysis..- Completeness Analysis of Mobile Apps’ Privacy Policies by Using Deep Learning..- Characterizing the Evolution of Psychological Tactics and Techniques Exploited by Malicious Emails..- Matching Knowledge Graphs for Cybersecurity Countermeasures Selection..- Graph-Based Profiling of Dependency Vulnerability Remediation..- Characterizing the Evolution of Psychological Factors Exploited by Malicious Emails..- An Enhanced Firewall for IoT Security..- Exploring the Effects of Cybersecurity Awareness and Decision-Making Under Risk..- SVSM-KMS: Safeguarding Keys for Cloud Services with Encrypted Virtualization..- GNNexPIDS: An Interpretation Method for Provenance-based Intrusion Detection Based on GNNExplainer..- Performance Evaluation of Lightweight Cryptographic Ciphers on ARM Processor for IoT Deployments..- AutoCRAT: Automatic Cumulative Reconstruction of Alert Trees..- FAF-BM: An Approach for False Alerts Filtering using BERT Model with Semi-supervised Active Learning..- Smart Home Cyber Insurance Pricing..- Exhaustive Exploratory Analysis of Low Degree Maximum Period NLFSRs By Graph Analysis..- Integrating Consortium Blockchain and Attribute-Based Searchable Encryption for Automotive Threat Intelligence Sharing Model..- Multi-Modal Multi-Task Tiered Expert (M3TTE): An Effective Method for CDN Website Classification..- Malware Variant Detection Based on Knowledge Transfer and Ensemble Learning..- An Efficient IOC-Driven BigData Tracing and Backtracking Model for Emergency Response..- Integrating CP-ABE and Device Fingerprint into Federated Learning..- Automatic Alert Categories Standardization for Heterogeneous Devices with Incomplete Semantic Knowledge Based on LSTM..- Family Similarity-Enhanced Implicit Data Augmentation for Malware Classification.
£64.99
Springer How Large Language Models Can Help Your Search Project
Book SynopsisPart I: Large Language Models.- 1. Introduction to Large Language Models.- 2. The Open Source Landscape.- 3. The Commercial Landscape.- Part II: Large Language Models and Search.- 4. Applying Large Language Models to Search.- 5. What Large Language Model Is the Best for You?.- 6. Rabbit Holes.- Part III: How to Use Open Source Software to Interact with Large Language Models.- 7. Open Source Frameworks and Projects.- 8. Popular Open Source Search Engines.
£35.99
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG E-Librarian Service: User-Friendly Semantic
Book SynopsisThis book introduces a new approach to designing E-Librarian Services. With the help of this system, users will be able to retrieve multimedia resources from digital libraries more efficiently than they would by browsing through an index or by using a simple keyword search. E-Librarian Services combine recent advances in multimedia information retrieval with aspects of human-machine interfaces, such as the ability to ask questions in natural language; they simulate a human librarian by finding and delivering the most relevant documents that offer users potential answers to their queries. The premise is that more pertinent results can be retrieved if the search engine understands the meaning of the query; the returned results are therefore logical consequences of an inference rather than of keyword matches. Moreover, E-Librarian Services always provide users with a solution, even in situations where they are unable to offer a comprehensive answer.Trade ReviewFrom the reviews:“The subtitle gives a much better idea of what this book is really about. … it offers a demonstration of their applicability within a narrow computer science framework. … the primary audience is computer science researchers. … It is interesting as an illustration of where information retrieval is heading, an explanation of the relationship between the semantic web and natural language processing, and a glimpse of the potential power of these new ways of representing knowledge.” (Toby Burrows, Australian Library Journal, Vol. 61 (2), May, 2012)Table of ContentsPart I: Information Retrieval in Digital Libraries.- Introduction to Digital Libraries.- Search Engines.- Part II: Key Technologies of E-Librarian Services.- Semantic Web and Ontologies.- Description Logics and Reasoning.- Natural Language Processing.- Multimedia Information Retrieval.- Part III: Design and Utilization of E-Librarian Services.- Ontological Approach.- Design of the Natural Language Processing Module.- Designing the Multimedia Information Retrieval Module.- Implementation, Configuration, and Deployment.- Best Practices.- Part IV: Appendix.- A - XML SChema Primitive Datatypes.- B - Reasoning Algorithms.- C - Syntactic Difference.- D - Brown Tag Set.- E - Part-of-Speech-Taggers and Parsers.- References.
£40.49
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Enabling Real-Time Business Intelligence: 5th International Workshop, BIRTE 2011, Held at the 37th International Conference on Very Large Databases, VLDB 2011, Seattle, WA, USA, September 2, 2011, Revised Selected Papers
Book SynopsisThis book constitutes the thoroughly refereed conference proceedings of the 5th International Workshop on Business Intelligence for the Real-Time Enterprise, BIRTE 2011, held in Seattle, WA, USA, in September 2011, in conjunction with VLDB 2011, the International Conference on Very Large Data Bases. The series of BIRTE workshops aims to provide a forum for researchers to discuss and advance the foundational science and engineering required to enable real-time business intelligence as well as novel applications and solutions based on these foundational techniques.The volume contains 6 research papers, which have been carefully reviewed and selected from 12 submissions, plus the 3 keynotes presented at the workshop. The topics cover all stages of the business intelligence cycle, including capturing of real-time data, handling of temporal or uncertain data, performance issues, event management, and the optimization of complex ETL workflows.The volume contains 6 research papers, which have been carefully reviewed and selected from 12 submissions, plus the 3 keynotes presented at the workshop. The topics cover all stages of the business intelligence cycle, including capturing of real-time data, handling of temporal or uncertain data, performance issues, event management, and the optimization of complex ETL workflows.Table of ContentsBlink: Not Your Father’s Database!.- MemcacheSQL – A Scale-Out SQL Cache Engine.- A Cost-Aware Strategy for Merging Differential Stores in Column-Oriented In-Memory DBMS.- Microsoft SQL Server Parallel Data Warehouse: Architecture Overview.- Relax and Let the Database Do the Partitioning Online.- Adaptive Processing of Multi-Criteria Decision Support Queries.- Scalable Social Graph Analytics Using the Vertical Analytic Platform.- A Near Real-Time Personalization for eCommerce Platform.
£37.99
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG On the Move to Meaningful Internet Systems: OTM 2013 Workshops: Confederated International Workshops: OTM Academy, OTM Industry Case Studies Program, ACM, EI2N, ISDE, META4eS, ORM, SeDeS, SINCOM, SMS and SOMOCO 2013, Graz, Austria, Septembe
Book SynopsisThis volume constitutes the refereed proceedings of the international workshops, Confederated International Workshops: OTM Academy, OTM Industry Case Studies Program, ACM, EI2N, ISDE, META4eS, ORM, SeDeS, SINCOM, SMS and SOMOCO 2013, held as part of OTM 2013 in Graz, Austria, in September 2013. The 75 revised full papers presented together with 12 posters and 5 keynotes were carefully reviewed and selected from a total of 131 submissions. The papers are organized in topical sections on: On The Move Academy; Industry Case Studies Program; Adaptive Case Management and other non-workflow approaches to BPM; Enterprise Integration, Interoperability and Networking; Information Systems in Distributed Environment; Methods, Evaluation, Tools and Applications for the Creation and Consumption of Structured Data for the e-Society; Fact-Oriented Modeling; Semantics and Decision Making; Social Media Semantics; Social and Mobile Computing for collaborative environments; cooperative information systems; Ontologies, Data Bases and Applications of Semantics.Table of ContentsOn The Move Academy.- Industry Case Studies Program.- Adaptive Case Management and other non-workflow approaches to BPM.- Enterprise Integration, Interoperability and Networking.- Information Systems in Distributed Environment.- Methods, Evaluation, Tools and Applications for the Creation and Consumption of Structured Data for the e-Society.- Fact-Oriented Modeling.-Semantics and Decision Making.- Social Media Semantics.- Social and Mobile Computing for collaborative environments.- Cooperative information systems.- Ontologies, Data Bases and Applications of Semantics.
£42.74
Springer Verlag, Singapore Quantum Image Processing
Book SynopsisThis book provides a comprehensive introduction to quantum image processing, which focuses on extending conventional image processing tasks to the quantum computing frameworks. It summarizes the available quantum image representations and their operations, reviews the possible quantum image applications and their implementation, and discusses the open questions and future development trends. It offers a valuable reference resource for graduate students and researchers interested in this emerging interdisciplinary field.Table of Contents1.Introduction and Overview.- 2. Quantum Image Representations.- 3. Quantum Image Operations.- 4. Quantum Image Security.- 5. Quantum Image Understanding.- 6. Quantum Multimedia Techniques.- 7. Summary and Discussion.
£98.99
Springer Advanced Filter Structure Handbook
Book SynopsisChapter 1. Introduction.- Chapter 2. Read-Only Filters.- Chapter 3. Space-Resilient Filters.- Chapter 4. Streaming Filters.- Chapter 5. Range Filters.
£134.99
O'Reilly Media Search Patterns
Book SynopsisSearch is among the most disruptive innovations of our time. It influences what we buy and where we go. It shapes how we learn and what we believe. This book explores design patterns that apply across the categories of web, ecommerce, enterprise, desktop, mobile, social, and realtime search and discovery.
£25.59
John Wiley & Sons Inc OntologyBased Information Retrieval for
Book SynopsisWith the advancements of semantic web, ontology has become the crucial mechanism for representing concepts in various domains. For research and dispersal of customized healthcare services, a major challenge is to efficiently retrieve and analyze individual patient data from a large volume of heterogeneous data over a long time span. This requirement demands effective ontology-based information retrieval approaches for clinical information systems so that the pertinent information can be mined from large amount of distributed data. This unique and groundbreaking book highlights the key advances in ontology-based information retrieval techniques being applied in the healthcare domain and covers the following areas: Semantic data integration in e-health care systems Keyword-based medical information retrieval Ontology-based query retrieval support for e-health implementation Ontologies as a database management system technology for medicalTable of ContentsPreface xix Acknowledgment xxiii 1 Role of Ontology in Health Care 1Sonia Singla 1.1 Introduction 2 1.2 Ontology in Diabetes 3 1.2.1 Ontology Process 4 1.2.2 Impediments of the Present Investigation 5 1.3 Role of Ontology in Cardiovascular Diseases 6 1.4 Role of Ontology in Parkinson Diseases 8 1.4.1 The Spread of Disease With Age and Onset of Disease 10 1.4.2 Cost of PD for Health Care, Household 11 1.4.3 Treatment and Medicines 11 1.5 Role of Ontology in Depression 13 1.6 Conclusion 15 1.7 Future Scope 15 References 15 2 A Study on Basal Ganglia Circuit and Its Relation With Movement Disorders 19Dinesh Bhatia 2.1 Introduction 19 2.2 Anatomy and Functioning of Basal Ganglia 21 2.2.1 The Striatum-Major Entrance to Basal Ganglia Circuitry 22 2.2.2 Direct and Indirect Striatofugal Projections 23 2.2.3 The STN: Another Entrance to Basal Ganglia Circuitry 25 2.3 Movement Disorders 26 2.3.1 Parkinson Disease 26 2.3.2 Dyskinetic Disorder 27 2.3.3 Dystonia 28 2.4 Effect of Basal Ganglia Dysfunctioning on Movement Disorders 29 2.5 Conclusion and Future Scope 31 References 31 3 Extraction of Significant Association Rules Using Pre- and Post-Mining Techniques—An Analysis 37M. Nandhini and S. N. Sivanandam 3.1 Introduction 38 3.2 Background 39 3.2.1 Interestingness Measures 39 3.2.2 Pre-Mining Techniques 40 3.2.2.1 Candidate Set Reduction Schemes 40 3.2.2.2 Optimal Threshold Computation Schemes 41 3.2.2.3 Weight-Based Mining Schemes 42 3.2.3 Post-Mining Techniques 42 3.2.3.1 Rule Pruning Schemes 43 3.2.3.2 Schemes Using Knowledge Base 43 3.3 Methodology 44 3.3.1 Data Preprocessing 44 3.3.2 Pre-Mining 46 3.3.2.1 Pre-Mining Technique 1: Optimal Support and Confidence Threshold Value Computation Using PSO 46 3.3.2.2 Pre-Mining Technique 2: Attribute Weight Computation Using IG Measure 48 3.3.3 Association Rule Generation 50 3.3.3.1 ARM Preliminaries 50 3.3.3.2 WARM Preliminaries 52 3.3.4 Post-Mining 56 3.3.4.1 Filters 56 3.3.4.2 Operators 58 3.3.4.3 Rule Schemas 58 3.4 Experiments and Results 59 3.4.1 Parameter Settings for PSO-Based Pre-Mining Technique 60 3.4.2 Parameter Settings for PAW-Based Pre-Mining Technique 60 3.5 Conclusions 63 References 65 4 Ontology in Medicine as a Database Management System 69Shobowale K. O. 4.1 Introduction 70 4.1.1 Ontology Engineering and Development Methodology 72 4.2 Literature Review on Medical Data Processing 72 4.3 Information on Medical Ontology 75 4.3.1 Types of Medical Ontology 75 4.3.2 Knowledge Representation 76 4.3.3 Methodology of Developing Medical Ontology 76 4.3.4 Medical Ontology Standards 77 4.4 Ontologies as a Knowledge-Based System 78 4.4.1 Domain Ontology in Medicine 79 4.4.2 Brief Introduction of Some Medical Standards 81 4.4.2.1 Medical Subject Headings (MeSH) 81 4.4.2.2 Medical Dictionary for Regulatory Activities (MedDRA) 81 4.4.2.3 Medical Entities Dictionary (MED) 81 4.4.3 Reusing Medical Ontology 82 4.4.4 Ontology Evaluation 85 4.5 Conclusion 86 4.6 Future Scope 86 References 87 5 Using IoT and Semantic Web Technologies for Healthcare and Medical Sector 91Nikita Malik and Sanjay Kumar Malik 5.1 Introduction 92 5.1.1 Significance of Healthcare and Medical Sector and Its Digitization 92 5.1.2 e-Health and m-Health 92 5.1.3 Internet of Things and Its Use 94 5.1.4 Semantic Web and Its Technologies 96 5.2 Use of IoT in Healthcare and Medical Domain 98 5.2.1 Scope of IoT in Healthcare and Medical Sector 98 5.2.2 Benefits of IoT in Healthcare and Medical Systems 100 5.2.3 IoT Healthcare Challenges and Open Issues 100 5.3 Role of SWTs in Healthcare Services 101 5.3.1 Scope and Benefits of Incorporating Semantics in Healthcare 101 5.3.2 Ontologies and Datasets for Healthcare and Medical Domain 103 5.3.3 Challenges in the Use of SWTs in Healthcare Sector 104 5.4 Incorporating IoT and/or SWTs in Healthcare and Medical Sector 106 5.4.1 Proposed Architecture or Framework or Model 106 5.4.2 Access Mechanisms or Approaches 108 5.4.3 Applications or Systems 109 5.5 Healthcare Data Analytics Using Data Mining and Machine Learning 110 5.6 Conclusion 112 5.7 Future Work 113 References 113 6 An Ontological Model, Design, and Implementation of CSPF for Healthcare 117Pooja Mohan 6.1 Introduction 117 6.2 Related Work 119 6.3 Mathematical Representation of CSPF Model 122 6.3.1 Basic Sets of CSPF Model 123 6.3.2 Conditional Contextual Security and Privacy Constraints 123 6.3.3 CSPF Model States CsetofStates 124 6.3.4 Permission Cpermission 124 6.3.5 Security Evaluation Function (SEFcontexts) 124 6.3.6 Secure State 125 6.3.7 CSPF Model Operations 125 6.3.7.1 Administrative Operations 125 6.3.7.2 Users’ Operations 127 6.4 Ontological Model 127 6.4.1 Development of Class Hierarchy 127 6.4.1.1 Object Properties of Sensor Class 129 6.4.1.2 Data Properties 129 6.4.1.3 The Individuals 129 6.5 The Design of Context-Aware Security and Privacy Model for Wireless Sensor Network 129 6.6 Implementation 133 6.7 Analysis and Results 135 6.7.1 Inference Time/Latency/Query Response Time vs. No. of Policies 135 6.7.2 Average Inference Time vs. Contexts 136 6.8 Conclusion and Future Scope 137 References 138 7 Ontology-Based Query Retrieval Support for E-Health Implementation 143Aatif Ahmad Khan and Sanjay Kumar Malik 7.1 Introduction 143 7.1.1 Health Care Record Management 144 7.1.1.1 Electronic Health Record 144 7.1.1.2 Electronic Medical Record 145 7.1.1.3 Picture Archiving and Communication System 145 7.1.1.4 Pharmacy Systems 145 7.1.2 Information Retrieval 145 7.1.3 Ontology 146 7.2 Ontology-Based Query Retrieval Support 146 7.3 E-Health 150 7.3.1 Objectives and Scope 150 7.3.2 Benefits of E-Health 151 7.3.3 E-Health Implementation 151 7.4 Ontology-Driven Information Retrieval for E-Health 154 7.4.1 Ontology for E-Heath Implementation 155 7.4.2 Frameworks for Information Retrieval Using Ontology for E-Health 157 7.4.3 Applications of Ontology-Driven Information Retrieval in Health Care 158 7.4.4 Benefits and Limitations 160 7.5 Discussion 160 7.6 Conclusion 164 References 164 8 Ontology-Based Case Retrieval in an E-Mental Health Intelligent Information System 167Georgia Kaoura, Konstantinos Kovas and Basilis Boutsinas 8.1 Introduction 167 8.2 Literature Survey 170 8.3 Problem Identified 173 8.4 Proposed Solution 174 8.4.1 The PAVEFS Ontology 174 8.4.2 Knowledge Base 179 8.4.3 Reasoning 180 8.4.4 User Interaction 182 8.5 Pros and Cons of Solution 183 8.5.1 Evaluation Methodology and Results 183 8.5.2 Evaluation Methodology 185 8.5.2.1 Evaluation Tools 186 8.5.2.2 Results 187 8.6 Conclusions 189 8.7 Future Scope 190 References 190 9 Ontology Engineering Applications in Medical Domain 193Mariam Gawich and Marco Alfonse 9.1 Introduction 193 9.2 Ontology Activities 195 9.2.1 Ontology Learning 195 9.2.2 Ontology Matching 195 9.2.3 Ontology Merging (Unification) 195 9.2.4 Ontology Validation 196 9.2.5 Ontology Verification 196 9.2.6 Ontology Alignment 196 9.2.7 Ontology Annotation 196 9.2.8 Ontology Evaluation 196 9.2.9 Ontology Evolution 196 9.3 Ontology Development Methodologies 197 9.3.1 TOVE 197 9.3.2 Methontology 198 9.3.3 Brusa et al. Methodology 198 9.3.4 UPON Methodology 199 9.3.5 Uschold and King Methodology 200 9.4 Ontology Languages 203 9.4.1 RDF-RDF Schema 203 9.4.2 OWL 205 9.4.3 OWL 2 205 9.5 Ontology Tools 208 9.5.1 Apollo 208 9.5.2 NeON 209 9.5.3 Protégé 210 9.6 Ontology Engineering Applications in Medical Domain 212 9.6.1 Ontology-Based Decision Support System (DSS) 213 9.6.1.1 OntoDiabetic 213 9.6.1.2 Ontology-Based CDSS for Diabetes Diagnosis 214 9.6.1.3 Ontology-Based Medical DSS within E-Care Telemonitoring Platform 215 9.6.2 Medical Ontology in the Dynamic Healthcare Environment 216 9.6.3 Knowledge Management Systems 217 9.6.3.1 Ontology-Based System for Cancer Diseases 217 9.6.3.2 Personalized Care System for Chronic Patients at Home 218 9.7 Ontology Engineering Applications in Other Domains 219 9.7.1 Ontology Engineering Applications in E-Commerce 219 9.7.1.1 Automated Approach to Product Taxonomy Mapping in E-Commerce 219 9.7.1.2 LexOnt Matching Approach 221 9.7.2 Ontology Engineering Applications in Social Media Domain 222 9.7.2.1 Emotive Ontology Approach 222 9.7.2.2 Ontology-Based Approach for Social Media Analysis 224 9.7.2.3 Methodological Framework for Semantic Comparison of Emotional Values 225 References 226 10 Ontologies on Biomedical Informatics 233Marco Alfonse and Mariam Gawich 10.1 Introduction 233 10.2 Defining Ontology 234 10.3 Biomedical Ontologies and Ontology-Based Systems 235 10.3.1 MetaMap 235 10.3.2 GALEN 236 10.3.3 NIH-CDE 236 10.3.4 LOINC 237 10.3.5 Current Procedural Terminology (CPT) 238 10.3.6 Medline Plus Connect 238 10.3.7 Gene Ontology 239 10.3.8 UMLS 240 10.3.9 SNOMED-CT 240 10.3.10 OBO Foundry 240 10.3.11 Textpresso 240 10.3.12 National Cancer Institute Thesaurus 241 References 241 11 Machine Learning Techniques Best for Large Data Prediction: A Case Study of Breast Cancer Categorical Data: k-Nearest Neighbors 245Yagyanath Rimal 11.1 Introduction 246 11.2 R Programming 250 11.3 Conclusion 255 References 255 12 Need of Ontology-Based Systems in Healthcare System 257Tshepiso Larona Mokgetse 12.1 Introduction 258 12.2 What is Ontology? 259 12.3 Need for Ontology in Healthcare Systems 260 12.3.1 Primary Healthcare 262 12.3.1.1 Semantic Web System 262 12.3.2 Emergency Services 263 12.3.2.1 Service-Oriented Architecture 263 12.3.2.2 IOT Ontology 264 12.3.3 Public Healthcare 265 12.3.3.1 IOT Data Model 265 12.3.4 Chronic Disease Healthcare 266 12.3.4.1 Clinical Reminder System 266 12.3.4.2 Chronic Care Model 267 12.3.5 Specialized Healthcare 268 12.3.5.1 E-Health Record System 268 12.3.5.2 Maternal and Child Health 269 12.3.6 Cardiovascular System 270 12.3.6.1 Distributed Healthcare System 270 12.3.6.2 Records Management System 270 12.3.7 Stroke Rehabilitation 271 12.3.7.1 Patient Information System 271 12.3.7.2 Toronto Virtual System 271 12.4 Conclusion 272 References 272 13 Exploration of Information Retrieval Approaches With Focus on Medical Information Retrieval 275Mamata Rath and Jyotir Moy Chatterjee 13.1 Introduction 276 13.1.1 Machine Learning-Based Medical Information System 278 13.1.2 Cognitive Information Retrieval 278 13.2 Review of Literature 279 13.3 Cognitive Methods of IR 281 13.4 Cognitive and Interactive IR Systems 286 13.5 Conclusion 288 References 289 14 Ontology as a Tool to Enable Health Internet of Things Viable 5G Communication Networks 293Nidhi Sharma and R. K. Aggarwal 14.1 Introduction 293 14.2 From Concept Representations to Medical Ontologies 295 14.2.1 Current Medical Research Trends 296 14.2.2 Ontology as a Paradigm Shift in Health Informatics 296 14.3 Primer Literature Review 297 14.3.1 Remote Health Monitoring 298 14.3.2 Collecting and Understanding Medical Data 298 14.3.3 Patient Monitoring 298 14.3.4 Tele-Health 299 14.3.5 Advanced Human Services Records Frameworks 299 14.3.6 Applied Autonomy and Healthcare Mechanization 300 14.3.7 IoT Powers the Preventive Healthcare 301 14.3.8 Hospital Statistics Control System (HSCS) 301 14.3.9 End-to-End Accessibility and Moderateness 301 14.3.10 Information Mixing and Assessment 302 14.3.11 Following and Alerts 302 14.3.12 Remote Remedial Assistance 302 14.4 Establishments of Health IoT 303 14.4.1 Technological Challenges 304 14.4.2 Probable Solutions 306 14.4.3 Bit-by-Bit Action Statements 307 14.5 Incubation of IoT in Health Industry 307 14.5.1 Hearables 308 14.5.2 Ingestible Sensors 308 14.5.3 Moodables 308 14.5.4 PC Vision Innovation 308 14.5.5 Social Insurance Outlining 308 14.6 Concluding Remarks 309 References 309 15 Tools and Techniques for Streaming Data: An Overview 313K. Saranya, S. Chellammal and Pethuru Raj Chelliah 15.1 Introduction 314 15.2 Traditional Techniques 315 15.2.1 Random Sampling 315 15.2.2 Histograms 316 15.2.3 Sliding Window 316 15.2.4 Sketches 317 15.2.4.1 Bloom Filters 317 15.2.4.2 Count-Min Sketch 317 15.3 Data Mining Techniques 317 15.3.1 Clustering 318 15.3.1.1 STREAM 318 15.3.1.2 BRICH 318 15.3.1.3 CLUSTREAM 319 15.3.2 Classification 319 15.3.2.1 Naïve Bayesian 319 15.3.2.2 Hoeffding 320 15.3.2.3 Very Fast Decision Tree 320 15.3.2.4 Concept Adaptive Very Fast Decision Tree 320 15.4 Big Data Platforms 320 15.4.1 Apache Storm 321 15.4.2 Apache Spark 321 15.4.2.1 Apache Spark Core 321 15.4.2.2 Spark SQL 322 15.4.2.3 Machine Learning Library 322 15.4.2.4 Streaming Data API 322 15.4.2.5 GraphX 323 15.4.3 Apache Flume 323 15.4.4 Apache Kafka 323 15.4.5 Apache Flink 326 15.5 Conclusion 327 References 328 16 An Ontology-Based IR for Health Care 331J. P. Patra, Gurudatta Verma and Sumitra Samal 16.1 Introduction 331 16.2 General Definition of Information Retrieval Model 333 16.3 Information Retrieval Model Based on Ontology 334 16.4 Literature Survey 336 16.5 Methodolgy for IR 339 References 344
£164.66
Association for Computing Machinery Data Cleaning
Book SynopsisFocuses on data cleaning, which is used to refer to all kinds of tasks and activities to detect and repair errors in the data. Rather than focus on a particular data cleaning task, the book gives an overview of the end-to-end data cleaning process, describing various error detection and repair methods.Table of Contents Preface Figure and Table Credits Introduction Outlier Detection Data Deduplication Data Transformation Data Quality Rule Definition and Discovery Rule-Based Data Cleaning Machine Learning and Probabilistic Data Cleaning Conclusion and Future Thoughts References Index Author Biographies
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Association for Computing Machinery Event Mining for Explanatory Modeling
Book SynopsisIntroduces the concept of Event Mining for building explanatory models from analyses of correlated data. Such a model may be used as the basis for predictions and corrective actions. The idea is to create, via an iterative process, a model that explains causal relationships in the form of structural and temporal patterns in the data.
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Morgan & Claypool Publishers Event Mining for Explanatory Modeling
Book SynopsisIntroduces the concept of Event Mining for building explanatory models from analyses of correlated data. Such a model may be used as the basis for predictions and corrective actions. The idea is to create, via an iterative process, a model that explains causal relationships in the form of structural and temporal patterns in the data.
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O'Reilly Media The Information Diet
Book SynopsisAnd just as too much junk food can lead to obesity, too much junk information can lead to cluelessness. The Information Diet shows you how to thrive in this information glut-what to look for, what to avoid, and how to be selective.
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O'Reilly The Art of Capacity Planning 2e
Book SynopsisThis hands-on guide provides the knowledge and tools you need to measure, deploy, and manage your web application infrastructure before you experience explosive growth. In this thoroughly updated edition, authors Arun Kejariwal (MZ) and John Allspaw provide a systematic, robust, and practical approach to capacity planning.
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John Wiley & Sons Inc New Challenges for Knowledge: Digital Dynamics to
Book SynopsisDigital technologies are reshaping every field of social and economic lives, so do they in the world of scientific knowledge. “The New Challenges of Knowledge” aims at understanding how the new digital technologies alter the production, diffusion and valorization of knowledge. We propose to give an insight into the economical, geopolitical and political stakes of numeric in knowledge in different countries. Law is at the center of this evolution, especially in the case of national and international confusion about Internet, Science and knowledge.Trade Review“Sharing economy models are rippling through the world of scientific knowledge and research; open access brings challenges for developers, researchers, and policy makers – all treated here in the context of law-making” The Magpi, issue 60, Aug 2017Table of ContentsIntroduction . xiii Part 1. Production: Global Knowledge and Science in the Digital Era 1 Chapter 1. Current Knowledge Dynamics 3 1.1. Transparency of scientific data 4 1.2. Transparency of experimental protocol 6 1.3. A necessary form of research engineering 7 1.4. Confusion between data and scientific results: avoiding manipulation of research results 8 Chapter 2. Digital Conditions for Knowledge Production 11 2.1. An economic system oriented toward innovation 11 2.2. What of knowledge and indeed the concept of the commons? 13 2.3. From analog to digital 14 2.4. User–producer: civil society enters the knowledge production system 16 2.5. The interactions between the various spheres of knowledge production 18 2.6. Collaboration between society and knowledge: producing authorities should be put into perspective 20 Chapter 3. The Dual Relationship between the User and the Developer 23 3.1. Legal arrangements for knowledge-sharing using development platforms 23 3.2. The user contributes to the creation and development of content process 25 Chapter 4. Researchers’ Uses and Needs for Scientific and Technical Information 29 4.1. The CNRS survey 29 4.2. Diverse uses and dual needs 31 4.3. An explanation through differentiated scientific analysis 33 Chapter 5. New Tools for Knowledge Capture 37 5.1. The growth of metadata exploitation 37 5.2. Are we moving toward a semantic Web? 38 5.3. Tools and limits for metadata processing 39 5.4. The challenges of the semantic Web 40 Chapter 6. Modes of Knowledge Sharing and Technologies 43 6.1. Data storage technologies and access allowing knowledge sharing 43 6.2. Exchange platforms and catalogs 44 6.3. Knowledge-processing and digital editions 45 Part 2. Sharing Mechanisms: Knowledge Sharing and the Knowledge-based Economy 47 Chapter 7. Business Model for Scientific Publication 49 7.1. The current economic model is changing so as to adapt to new conditions for knowledge sharing 49 7.2. Creation of a new model 51 7.3. The issues raised by the creation of a new economic model 52 7.4. A new economic model struggling to fine its niche 54 Chapter 8. Actor Strategy: International Scientific Publishing, Services with High Added Value and Research Communities 57 8.1. Publishing, editing and existing: live issues within the publication of Scientific and Technical Information (STI) 58 8.2. Who is subject to it? The other players in scientific publishing 59 8.3. The characteristics of SMS (Science of Man and Society) 60 8.4. Existing without publishing? New STI directions 62 8.5. Alternatives to scientific publishing 63 Chapter 9. New Approaches to Scientific Production 67 9.1. New means of access to scientific production: innovative models 67 9.2. Two main objectives: accelerating knowledge sharing and promoting scientific collaboration 71 9.3. The need for new analytical tools and the risk of reprivatization of scientific knowledge. 72 9.4. The absence of the usage doctrine and the risk of reprivatization of science: the case of social networks 74 Chapter 10. The Geopolitics of Science 77 10.1. National convergent research models 78 10.2. Science is a source of international cooperation 81 10.3. International scientific cooperation is accelerating 84 Chapter 11. Copyright Serving the Market 85 Part 3. Enhancement Knowledge Rights and Public Policies in the Wake of Digital Technology 89 Chapter 12. Legal Protection of Scientific Research Results in the Humanities and Social Sciences 91 12.1.Different legal protections for different kinds of science 91 12.2. Why protect? 92 12.3. How to protect 93 12.4. Protect against whom? 98 12.5. Changing the challenges of Internet protection 99 12.6. Legal obstacles related to the author’s right 100 Chapter 13. Development of Knowledge and Public Policies 103 13.1. Knowledge enhancement concerns everyone 104 13.2. What are the public policies for enhancing knowledge? 105 13.3. State establishment of connections between actors: a key tool in knowledge enhancement 107 13.4. Comparing the United States and the European Union 109 Chapter 14. From Author to Enhancer 111 14.1. Enhancing scientific research is a complex process 112 14.2. Scientific research enhancement follows a legislative framework intended to promote innovation 114 Chapter 15. The Right to Knowledge: Moving Toward a Universal Law? 117 15.1. Unclear regulatory frameworks 118 15.2. Developing legal frameworks related to the Internet is complicated 121 15.3. Proposals for developing legal frameworks for the Internet 123 Chapter 16. Governing by Algorithm 127 16.1. Statistics that foreshadow algorithms 128 16.2. Algorithmic governance and democratic opportunities 130 Chapter 17. Public Data and Science in e-Government 133 17.1. Disseminating data and disseminating science: a new requirement 134 17.2. Public data in the e-government 137 17.3. Science within e-government 139 Chapter 18. Surveillance, Sousveillance, Improper Capturing 141 18.1. The traditional legal framework for information capture 142 18.2. The clear need for a specific law 145 Chapter 19. Public Knowledge Policies in the Digital Age 149 19.1. GAFA domination and the oligopolization of the market 150 19.2. Isolated digital ecosystems 152 19.3. Regulation through competition law 153 19.4. Data protection: moving toward a law for the digital community 154 Chapter 20. The Politics of Creating Artificial Intelligence 157 20.1. History 158 20.2. Artificial intelligence has become a priority for public and private actors 160 20.4. The appearance of legal problems 162 Chapter 21. Security Policies in Artificial Intelligence 165 21.1. Security as a comment on machines and data 166 21.2. From the security of machines to the security of humans 169 Conclusion 175 Postscript 177 Glossary 179 Bibliography 185 Index 201
£125.06
ISTE Ltd and John Wiley & Sons Inc Information Retrieval in Digital Environments
Book SynopsisInformation retrieval is a central and essential activity. It is indeed difficult to find a human activity that does not need to retrieve information in an environment which is often increasingly digital: moving and navigating, learning, having fun, communicating, informing, making a decision, etc. Most human activities are intimately linked to our ability to search quickly and effectively for relevant information, the stakes are sometimes extremely important: passing an exam, voting, finding a job, remaining autonomous, being socially connected, developing a critical spirit, or simply surviving. The author of this book presents a summary of work undertaken over several years relative to the behaviors and cognitive processes involved in information retrieval in digital environments. He presents several examples of theoretical models and studies to better understand the difficulties, behaviors and strategies of individuals searching for information in digital environments.Table of ContentsCHAPTER 1. INFORMATION RETRIEVAL IN DIGITAL ENVIRONMENTS: DEBATE AND SCIENTIFIC DIRECTIONS 1 1.1. Information retrieval, current and future challenges 1 1.2. What are we talking about? 3 1.3. Interaction and navigation at the heart of information retrieval 7 1.4. Why should we be interested in information retrieval? 9 1.4.1. Economy: maximize profitability and minimize risks 10 1.4.2. Information technology: mathematical concepts of the relevance of information 12 1.4.3. Robotics: improving movements and interactions 14 CHAPTER 2. CONCEPTUAL AND METHODOLOGICAL APPROACHES TO INFORMATION RETRIEVAL IN DIGITAL ENVIRONMENTS 19 2.1. The approaches of information sciences: the precursors 19 2.2. The Marchionini sequential iterative model 21 2.3. The holistic model of Kuhlthau 23 2.4. The first studies of psychology and cognitive ergonomics 26 2.5. The cyclic model of David, Song, Hayes and Fredin 31 2.6. The skills-centered model of Brand-Gruwel 33 2.7. Kitajima’s predictive model 36 2.8. The hyper-specialized model of Sharit, Hernandez, Czaja and Pirolli 39 2.9. The Landscape Model “diversion” by Dinet 42 CHAPTER 3. INFORMATION RETRIEVAL: PSYCHOERGONOMIC APPROACH 49 3.1. Introduction 49 3.2. Identifying difficulties in modifying interfaces 51 3.2.1. Hierarchical task analysis 52 3.2.2. Analysis of the end users’ behavior 55 3.2.3. Implications for the (re)design of interfaces 61 3.3. Anticipating the needs of users 63 3.3.1. “If we built it, they will come” 64 3.3.2. The analysis of users’ expectations and behaviors 65 3.3.3. Prospective ergonomics and technological innovation 70 3.3.4. Anticipating and understanding the needs of users: the method of staff made up of community experts 73 3.3.5. An example of application of the method of staff made up of community experts 76 3.4. The motor dimension 79 3.4.1. Motor ability and information retrieval in digital environments 79 3.4.2. Toward a lexicon of intuitive gestures 85 3.5. The social dimension and collaborative 88 3.5.1. From individual research to collaborative information retrieval 89 3.5.2. Benefits and limitations of collaborative information retrieval 90 3.6. Impact of emotional ties between collaborators 92 3.6.1. Ties between collaborators and impact on information retrieval 94 3.6.2. “RCI-Web”: software to assist information retrieval 97 3.7. The cultural dimension 102 3.7.1. About the importance of the home page 102 3.7.2. Culture and design of Websites’ home pages: an ergonomic inspection 105 3.7.3. Information retrieval culture and behavior navigation 107 3.8. The visual exploration strategies109 3.8.1. Impact of the typographical marking (bottom-up approach) 112 3.8.2. Impact of the mental model (top-down approach) 117 CONCLUSION 123 BIBLIOGRAPHY 125 INDEX 165
£125.06
ISTE Ltd and John Wiley & Sons Inc Recommender Systems
Book SynopsisAcclaimed by various content platforms (books, music, movies) and auction sites online, recommendation systems are key elements of digital strategies. If development was originally intended for the performance of information systems, the issues are now massively moved on logical optimization of the customer relationship, with the main objective to maximize potential sales. On the transdisciplinary approach, engines and recommender systems brings together contributions linking information science and communications, marketing, sociology, mathematics and computing. It deals with the understanding of the underlying models for recommender systems and describes their historical perspective. It also analyzes their development in the content offerings and assesses their impact on user behavior.Table of ContentsPREFACE xi Gérald KEMBELLEC, Ghislaine CHARTRON and Imad SALEH CHAPTER 1. GENERAL INTRODUCTION TO RECOMMENDER SYSTEMS 1 Ghislaine CHARTRON and Gérald KEMBELLEC 1.1. Putting it into perspective 1 1.2. An interdisciplinary subject 2 1.3. The fundamentals of algorithms 4 1.3.1. Collaborative filtering 4 1.3.2. Content filtering 7 1.3.3. Hybrid methods 9 1.3.4. Conclusion on historical recommendation models 11 1.4. Content offers and recommender systems 11 1.4.1. Culture and recommender systems 11 1.4.2. Recommender systems and the e-commerce of content 16 1.4.3. The behavior of users 18 1.5. Current issues 19 1.6. Bibliography 19 CHAPTER 2. UNDERSTANDING USERS’ EXPECTATIONS FOR RECOMMENDER SYSTEMS: THE CASE OF SOCIAL MEDIA 25 Jean-Claude DOMENGET and Alexandre COUTANT 2.1. Introduction: the omnipresence of recommender systems 25 2.2. The social approach to prescription 27 2.2.1. The theory of the prescription and online interactions 27 2.2.2. Conditions for recognition of the prescription 29 2.2.3. The specificities of social media 30 2.3. Users who do not focus on the prescriptions of platforms 31 2.3.1. Facebook: the link, the type of activity and the context 32 2.3.2. Twitter: prescription between peers and explanation of prescription 38 2.3.3. Conditions for the recognition of a prescription: announcement and enunciation 44 2.4. A guide for considering recommender systems adapted to different forms of social media 45 2.5. Conclusion 48 2.6. Bibliography 49 CHAPTER 3. RECOMMENDER SYSTEMS AND SOCIAL NETWORKS: WHAT ARE THE IMPLICATIONS FOR DIGITAL MARKETING? 53 Maria MERCANTI-GUÉRIN 3.1. Social recommendations: an ancient practice revived by the digital age 54 3.1.1. Recommendations: a difficult management for brands 55 3.1.2. Internet recommendations: social presence and personalized recommendations 55 3.2. Social recommendations: how are they used for e-commerce? 58 3.2.1. Efficiency of recommender systems with regard to the performance of e-commerce websites 58 3.2.2. Recommender systems used by social networks: from e-commerce to social commerce 59 3.3. Conclusion 66 3.4. Bibliography 68 CHAPTER 4. RECOMMENDER SYSTEMS AND DIVERSITY: TAKING ADVANTAGE OF THE LONG TAIL AND THE DIVERSITY OF RECOMMENDATION LISTS 71 Muriel FOULONNEAU, Valentin GROUÈS, Yannick NAUDET and Max CHEVALIER 4.1. The stakes associated with diversity within recommender systems 72 4.1.1. Individual diversity or the individual perception of diversity 73 4.1.2. The stakes and impacts of aggregate diversity 74 4.2. Recommendation algorithms and diversity: trends, evaluation and optimization 77 4.2.1. The tendency for recommendation algorithms to focus on the head 78 4.2.2. The evaluation of diversity in recommender systems 80 4.2.3. Recommendation algorithms which favor individual diversity 81 4.2.4. Recommendation algorithms which favor aggregate diversity 81 4.2.5. The shift toward user-centered diversity approaches 82 4.3. Conclusion and new directions 85 4.4. Bibliography 87 CHAPTER 5. ISONTRE: INTELLIGENT TRANSFORMER OF SOCIAL NETWORKS INTO A RECOMMENDATION ENGINE ENVIRONMENT 93 Rana CHAMSI ABU QUBA, Salima HASSAS, Usama FAYYAD, Hammam CHAMSI and Christine GERTOSIO 5.1. Summary 93 5.2. Introduction 94 5.3. Latest developments, definition and history 97 5.3.1. Collaborative filtering techniques 97 5.3.2. General use social networks: what do they contain? 97 5.3.3. Social recommendation 99 5.3.4. The recommendation of concepts 100 5.4. iSoNTRE 101 5.4.1. iSoNTRE: transformer of social networks 102 5.4.2. iSoNTRE: the core of recommendation 107 5.5. Experiments 110 5.5.1. The preparation of data 110 5.5.2. Testing methodology 110 5.5.3. The creation of avatars 111 5.5.4. Results 112 5.5.5. Discussion 113 5.6. Conclusion 114 5.7. Bibliography 115 CHAPTER 6. A TWO-LEVEL RECOMMENDATION APPROACH FOR DOCUMENT SEARCH 119 Manel HMIMIDA and Rushed KANAWATI 6.1. Introduction 119 6.2. Tag recommendation: a brief state of the art 120 6.3. The hypertagging system 122 6.3.1. Metadata 122 6.3.2. Architecture 123 6.4. Recommendation approach 124 6.4.1. Presentation 124 6.4.2. Recommendation algorithm 126 6.5. Evaluation 127 6.5.1. Generation of facets 127 6.5.2. Generation of association rules 129 6.5.3. Evaluation of recommendation rules 130 6.6. Conclusion 131 6.7. Bibliography 132 CHAPTER 7. COMBINING CONFIGURATION AND RECOMMENDATION TO ENABLE AN INTERACTIVE GUIDANCE OF PRODUCT LINE CONFIGURATION 135 Raouia TRIKI , Raúl MAZO and Camille SALINESI 7.1. Introduction 135 7.2. Context 137 7.2.1. Configuration 137 7.2.2. Recommendation 139 7.2.3. Obstacles and challenges of interactive PL configuration 141 7.3. Overview of the proposed approach 142 7.4. Preliminary evaluation 148 7.5. Discussion and related work 148 7.5.1. Recommendation techniques 148 7.6. Conclusion and future work 151 7.7. Bibliography 151 CHAPTER 8. SEMIO-COGNITIVE SPACES: THE FRONTIER OF RECOMMENDER SYSTEMS 157 Hakim HACHOUR, Samuel SZONIECKY and Safia ABOUAD 8.1. Introduction 157 8.2. Latest developments: finalized activities, recommender systems and the relevance of information 159 8.2.1. Cognitive dynamics of finalized activities 159 8.2.2. The foundations of recommender systems 161 8.2.3. What information relevance? 166 8.3. Observable interests for decision theory: a combination of content-based, collaboration based and knowledge-based recommendations 169 8.3.1. Methodology: meta-analysis and modeling of the process 169 8.3.2. Analysis and modeling of a macro-process for responding to a call for R&D projects 171 8.3.3. Analysis and model of a socio-organizational tool for the management of customer complaints 173 8.4. Discussion and conclusions 177 8.4.1. Discussion: the performance of the filtering methods and semio-cognitive criteria for relevance 177 8.5. Conclusions: recommender systems linked to finalized activities 181 8.5.1. The localization of activities and geographical information systems: a new kind of data 182 8.5.2. Transparency of the use of personal data, data protection and ownership 183 8.6. Acknowledgments 185 8.7. Bibliography 185 CHAPTER 9. THE FRENCH-SPEAKING LITERARY PRESCRIPTION MARKET IN NETWORKS 191 Louis WIART 9.1. Introduction 191 9.2. The economy of prescription 193 9.2.1. The notion of prescription 193 9.2.2. From the advisors market to the prescription market 194 9.3. Methodology 196 9.4. The competitive structure of the market of online social networks of readers 197 9.4.1. Pure player networks and the audience strategy 199 9.4.2. Amateur networks and the survival strategy 201 9.4.3. Backed networks and the hybridization strategy 202 9.5. The organization of prescription 204 9.5.1. Social prescription 205 9.5.2. Editorial prescription 206 9.5.3. Algorithmic prescription 207 9.6. Conclusion: what legitimacy for literary prescription? 208 9.7. Appendix: list of interviews undertaken 210 9.8. Bibliography 210 CHAPTER 10. PRESENTATION OF OFFERED SERVICES: BABELIO, A RECOMMENDATION ENGINE DEDICATED TO BOOKS 213 Vassil STEFANOV, Guillaume TEISSEIRE and Pierre FRÉMAUX 10.1. Introduction 213 10.2. The problem of qualitative pertinence 216 10.3. The problem of quantitative pertinence 217 10.4. Balancing recall and precision 217 10.5. The issue of sparse data 218 10.6. Performance and scalability 218 10.7. A few issues specific to books 219 CHAPTER 11. PRESENTATION OF THE OFFER OF SERVICES: NOMAO, RECOMMENDER SYSTEMS AND INFORMATION SEARCH 221 Estelle DELPECH, Laurent CANDILLIER and Étienne CHAI 11.1. Introduction: the actors of Internet recommendation 221 11.2. Approaches to recommendation 222 11.3. Nomao: a local outlets search and recommendation engine 223 11.3.1. Popularity score 223 11.3.2. Affinity score 224 11.3.3. Social recommendation 225 11.4. Prospects: the move toward interactive recommender systems 225 11.5. Appendix 226 LIST OF AUTHORS 227 INDEX 231
£125.06
ISTE Ltd and John Wiley & Sons Inc Enterprise Interoperability: Interoperability for
Book SynopsisEnterprises and organizations of any kind embedded in today's economic environment are deeply dependent on their ability to take part in collaborations. Consequently, it is strongly required for them to get actively involved for their own benefit in emerging, potentially opportunistic collaborative enterprise networks. The concept of “interoperability” has been defined by INTEROP-VLab as “The ability of an enterprise system or application to interact with others at a low cost in a flexible approach”. Consequently, interoperability of organizations appears as a major issue to succeed in building on the fly emerging enterprise networks. The International Conference on Interoperability for Enterprise Systems and Applications (I-ESA 2014) was held under the motto “interoperability for agility, resilience and plasticity of collaborations” on March 26-28, 2014 and organized by the Ecole des Mines d’Albi-Carmaux, France on behalf of the European Laboratory for Enterprise Interoperability (INTEROP-VLab). On March 24-25, co-located with the conference eight workshops and one doctoral symposium were held in four tracks complementing the program of the I-ESA’14 conference. The workshops and the doctoral symposium address areas of greatest current activity focusing on active discussions among the leading researchers in the area of Enterprise Interoperability. This part of the conference helps the community to operate effectively, building co-operative and supportive international links as well as providing new knowledge of on-going research to practitioners. The workshops and doctoral symposium aimed at exploiting new issues, challenges and solutions for Enterprise Interoperability (EI) and associated domains of innovation such as Smart Industry, Internet-Of-Things, Factories of the Future, EI Applications and Standardisation. These proceedings include the short papers from the I-ESA’14 workshops and the doctoral symposium. The book is split up into 9 sections, one for each workshop and one for the doctoral symposium. All sections were organized following four tracks: (1) EI and Future Internet / Factory of the Future; (2) EI Application Domains and IT; (3) EI Standards; (4) EI Doctoral Symposium. For each section, a workshop report is provided summarizing the content and the issues discussed during the sessions. The goal of the first track was to offer a discussion opportunity on interoperability issues regarding the use of Internet of Things on manufacturing environment (Workshops 1 and 3) on one hand, and regarding the potential of innovation derived from the use of digital methods, architectures and services such as Smart Networks (Workshops 2 and 4) on the other hand. The second track focused on particular application domains that are looking for innovative solutions to support their strong collaborative needs. Thus, the track developed one workshop on the use of EI solution for Future City-Logistics (Workshop 5) and one on the use of EI solutions for Crisis / Disaster Management (Workshop 6). The third track studied the recent developments in EI standardization. Two workshops were dedicated to this issue. The first one has proposed to focus on the management of standardization (Workshop 8) and the second one has chosen to work on the new knowledge on standardization developments in the manufacturing service domain (Workshop 9). The last track, the doctoral symposium presented research results from selected dissertations. The session discussed EI knowledge issues, notably in terms of gathering through social networks or Internet of Things and of exploitation through innovative decision support systems.Table of ContentsPreface xiM. LAURAS, M. ZELM, B. ARCHIMÈDE, F. BÉNABEN, G. DOUMEINGTS Workshop 1. IoT Interoperability for Manufacturing: Challenges and Experiences 1 ReportD. ROTONDI 2 Smart Industry Services in Times of Internet of Things and Cloud Computing 5M. SERRANO, P. DIMITROPOULOS Designing and Executing Interoperable IoT Manufacturing Systems 15U. KANNENGIESSER, G. WEICHHART Internet of Things Research on Semantic Interoperability to Address Manufacturing Challenges 21P. COUSIN, M. SERRANO, J. SOLDATOS Manufacturing Integration Challenges: Top-Down Interoperability and Bottom-Up Comprehensiveness Towards a Global Information Backbone for Smart Factory 31V.K. NGUYEN An Improved Decision Support System in Factory Shop-Floor through an IoT Approach 37P. PETRALI Leveraging IoT Interoperability for Enhanced Business Process in Smart, Digital and Virtual Factories 43J. SOLA, A. GONZALEZ, O. LAZARO Workshop 2. Future Internet Methods, Architectures and Services for Digital Business Innovation in Manufacturing, Health and Logistics Enterprises 49 Report 50S. GUSMEROLI, G. DOUMEINGTS Future Internet Technologies and Platforms to Support Smart, Digital and Virtual and Business Processes for Manufacturing 53J. SOLA, A. GONZALEZ, O. LAZARO Delivering Care in a Future Internet59 C. THUEMMLER, T. JELL FITMAN Verification and Validation Method: Business Performance Indicators and Technical Indicators 64G. DOUMEINGTS, B. CARSALADE, M. RAVELOMANANTSOA, F. LAMPATHAKI, P. KOKKINAKOS, D. PANOPOULOS Validation and Quality in FI-PPP e-Health Use Case, FI-STAR Project 71P. COUSIN, S. FRICKER, D. FEHLMY, F. LE GALL, M. FIEDLER Workshop 3. ICT Services and Interoperability for Manufacturing 81 Report82K. POPPLEWELL Intelligent Systems Configuration Services for Flexible Dynamic Global Production Networks 85R.I.M. YOUNG, K. POPPLEWELL, F.-W. JAEKEL, B. OTTO, G. BHULLAR Binding Together Heterogeneous Future Internet Services in Manufacturing Workplaces 91M. SESANA, S. GUSMEROLI, R. SANGUINI Holistic, Scalable and Semantic Approach at Interoperable Virtual Factories 95G. PAVLOV, V. MANAFOV, I. PAVLOVA, A. MANAFOV Predictive Industrial Maintenance: A Collaborative Approach 101F. FERREIRA, A. SHAMSUZZOHA, A. AZEVEDO, P. HELO On Optimizing Collaborative Manufacturing Processes in Virtual Factories 108D. SCHULLER, R. HANS, S. ZÖLLER, R. STEINMETZ Modelling Interoperability-Related, Economic and Efficiency Benefits in Dynamic Manufacturing Networks through Cognitive Mapping 115O.I. MARKAKI, S. KOUSSOURIS, P. KOKKINAKOS, D. PANOPOULOS, D. ASKOUNIS Cloud-Based Interoperability for Dynamic Manufacturing Networks 122D. STOCK, A. BILDSTEIN A smart Mediator to Integrate Dynamic Networked Enterprises 128C. DIOP, A. KAMOUN, E. MEZGHANI, M. ZOUARI, E. EXPOSITO Workshop 4. SmartNets – Collaborative Development and Production of Knowledge-Intensive Products and Services 135 Report 136A. LAU The Industrial Model of Smart Networks for SME Collaboration: Implementation and Success Stories 139A. LAU, M. TILEBEIN, T. FISCHER Towards a Conceptual Model of the Resource Base for Hyperlinking in Innovation Networks 146S.-V. REHM, S. GROSS Enhanced Incubators: Fostering Collaboration, Growth and Innovation 152T.J. MARLOWE, V. KIROVA, M. MOHTASHAMI Application of the SmartNets Methodology in Manufacturing Service Ecosystems 158M. HIRSCH, D. OPRESNIK, H. MATHEIS Application of a Domain-Specific Language to Support the User-Oriented Definition of Visualizations in the Context of Collaborative Product Development 164T. RESCHENHOFER, I. MONAHOV, F. MATTHES Workshop 5. Collaboration Issues for City-Logistics 171 Report – G. MACE-RAMETE, J. GONZALEZ-FELIU 172 Simulation-Based Analysis of Urban Freight Transport with Stochastic Features 175N. HERAZO-PADILLA, J.R. MONTOYA-TORRES, S. NIETO-ISAZA, L. RAMIREZ POLO, L. CASTRO, D. RAMÍREZ, C.L. QUINTERO-ARAÚJO Impacts of Urban Logistics on Traffic Flow Dynamics 181N. CHIABAUT, J.-M. SIGAUD, G. MARQUES, J. GONZALEZ-FELIU A Basic Collaborative City Logistics’ Solution: The Urban Consolidation Centre 188L. FAURE, B. MONTREUIL, G. MARQUÈS, P. BURLAT VRP Algorithms for Decision Support Systems to Evaluate Collaborative Urban Freight Transport Systems 196J. GONZALEZ-FELIU, J.-M. SALANOVA GRAU The Last Food Mile Concept as a City Logistics Solution for Perishable Products: The Case of Parma's Food Urban Distribution Center 202E. MORGANTI, J. GONZALEZ-FELIU Supporting Decision for Road Crisis Management through an Agile and Collaborative Information System 208G. MACÉ-RAMÈTE, F. BÉNABEN, M. LAURAS, J. LAMOTHE Workshop 6. Applications of Advanced Technologies in the Context of Disaster Relief and Crisis Management 213 Report – A. CHARLES214 Enhancing the Emergency Response Using an Event-Driven System 216A.-M. BARTHE-DELANOË, F. BÉNABEN, M. LAURAS, S. TRUPTIL Designing Decision Support Systems for Humanitarian Organisations: Requirements and Issues 222K. SAKSRISATHAPORN, A. CHARLES, A. BOURAS From Global to Local Disaster Resilience: The Case of Typhoon Haiyan 228T. COMES, B. VAN DE WALLE Workshop 8. Corporate Standardisation Management 235 Report – K. JAKOBS 236 Lack of Openness as a Potential Failure in Standardisation Management: Lessons Learnt from Setbacks in European Learning Technology Standardisation 238T. HOEL The Individual in Standard Setting: Selection, Training, Motivation in the Public Sector 244G. CANARSLAN A Framework for the Management of Intra-Organizational Security Process Standardization 250C. SILLABER, M. BRUNNER, R. BREU Standards Roles in Hacklin's Strategic Model: Cases in the Space Sector 256K. BENMEZIANE, A. MIONE Standardization Management and Decision-Making: The Case of a Large Swedish Automotive Manufacturer 261A. FOUKAKI Some Factors Influencing Corporate ICT Standardisation Management 267K. JAKOBS Workshop 9. Standardisation Developments for Enterprise Interoperability and the Manufacturing Service Domain 273 Report – M. ZELM, D. CHEN 274 Towards Standardisation in Manufacturing Service Engineering of Ecosystem 277M. ZELM, G. DOUMEINGTS Framework for Manufacturing Servitization: Potentials for standardization 283D. CHEN, S. GUSMEROLI How Can Existing Standards Support Service Life Cycle Management 290M. FREITAG, M. HIRSCH, J. NEUHÜTTLER An Approach to Interoperability Testing to Speed up the Adoption of Standards 295A. BRUTTI, P. DE SABBATA, N. GESSA A Common Vocabulary to Express Standardization Features: Towards the Interoperability of Industrial Data Standards 301A.-F. CUTTING-DECELLE, G.-I. MAGNAN, C. MOUTON, R.I.M. YOUNG An Info*Engine-Based Architecture to Support Interoperability with Windchill System 308M. ANIS DHUIEB, F. BELKADI, F. LAROCHE, A. BERNARD Doctoral Symposium 315 Report – B. ARCHIMÈDE, J. LAMOTHE 316 Build Enterprise Relationship Network to Support Collaborative Business 318L. WANG, S. LIU, L. WU, L. PAN, X. MENG Analysing Internet of Things to Feed Internet of Knowledge: Support Decision-Making in Crisis Context 325A. SIRKO, S. TRUPTIL, A.-M. BARTHE- DELANOË, F. BÉNABEN On the Interoperability in Marine Pollution Disaster Management 331V. NICOLESCU, M. CARAIVAN, G. SOLOMON, V. CIUPINA A Framework for Characterizing Collaborative Networks of Organizations 337A. MONTARNAL, X. FERNANDEZ, J. LAMOTHE, F. GALASSO, C. THIERRY, F. BÉNABEN, M. LAURAS Index of Authors 343
£125.96
Morgan & Claypool Publishers Text Data Management and Analysis: A Practical
Book SynopsisRecent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic.This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data.Table of Contents PART I. OVERVIEW AND BACKGROUND Introduction Background Text Data Understanding MeTA: A Unified Toolkit for Text Data Management and Analysis PART II. TEXT DATA ACCESS Overview of Text Data Access Retrieval Models Feedback Search Engine Implementation Search Engine Evaluation Web Search Recommender Systems PART III. TEXT DATA ANALYSIS Overview of Text Data Analysis Word Association Mining Text Clustering Text Categorization Text Summarization Topic Analysis Opinion Mining and Sentiment Analysis PART IV. UNIFIED TEXT DATA MANAGEMENT ANALYSIS SYSTEM Toward a Unified System for Text Management and Analysis Appendix A. Bayesian Statistics Appendix B. Expectation-Maximization Appendix C. KL-divergence and Dirichlet Prior Smoothing References Index Authors Biographies
£84.15
Morgan & Claypool Publishers Text Data Management and Analysis: A Practical
Book SynopsisRecent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content. As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text. The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic.This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks. The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data.Table of Contents PART I. OVERVIEW AND BACKGROUND Introduction Background Text Data Understanding MeTA: A Unified Toolkit for Text Data Management and Analysis PART II. TEXT DATA ACCESS Overview of Text Data Access Retrieval Models Feedback Search Engine Implementation Search Engine Evaluation Web Search Recommender Systems PART III. TEXT DATA ANALYSIS Overview of Text Data Analysis Word Association Mining Text Clustering Text Categorization Text Summarization Topic Analysis Opinion Mining and Sentiment Analysis PART IV. UNIFIED TEXT DATA MANAGEMENT ANALYSIS SYSTEM Toward a Unified System for Text Management and Analysis App. A. Bayesian Statistics App. B. Expectation-Maximization App. C. KL-divergence and Dirichlet Prior Smoothing References Index Authors Biographies
£95.20
Springer Nature Switzerland AG Knowledge Graphs: Methodology, Tools and Selected
Book SynopsisThis book describes methods and tools that empower information providers to build and maintain knowledge graphs, including those for manual, semi-automatic, and automatic construction; implementation; and validation and verification of semantic annotations and their integration into knowledge graphs. It also presents lifecycle-based approaches for semi-automatic and automatic curation of these graphs, such as approaches for assessment, error correction, and enrichment of knowledge graphs with other static and dynamic resources.Chapter 1 defines knowledge graphs, focusing on the impact of various approaches rather than mathematical precision. Chapter 2 details how knowledge graphs are built, implemented, maintained, and deployed. Chapter 3 then introduces relevant application layers that can be built on top of such knowledge graphs, and explains how inference can be used to define views on such graphs, making it a useful resource for open and service-oriented dialog systems. Chapter 4 discusses applications of knowledge graph technologies for e-tourism and use cases for other verticals. Lastly, Chapter 5 provides a summary and sketches directions for future work. The additional appendix introduces an abstract syntax and semantics for domain specifications that are used to adapt schema.org to specific domains and tasks.To illustrate the practical use of the approaches presented, the book discusses several pilots with a focus on conversational interfaces, describing how to exploit knowledge graphs for e-marketing and e-commerce. It is intended for advanced professionals and researchers requiring a brief introduction to knowledge graphs and their implementation. Table of ContentsIntroduction: What is a Knowledge Graph?.- How to build a Knowledge Graph.- How to use a Knowledge Graph.- Why we need Knowledge Graphs: Applications.- Conclusions.- References.- Appendix.- Index.
£47.49
Springer Nature Switzerland AG Privacy and Identity Management: 15th IFIP WG
Book SynopsisThis book contains selected papers presented at the 15th IFIP WG 9.2, 9.6/11.7, 11.6/SIG 9.2.2 International Summer School on Privacy and Identity Management, held in Maribor, Slovenia, in September 2020.*The 13 full papers included in this volume were carefully reviewed and selected from 21 submissions. Also included is a summary paper of a tutorial. As in previous years, one of the goals of the IFIP Summer School was to encourage the publication of thorough research papers by students and emerging scholars. The papers combine interdisciplinary approaches to bring together a host of perspectives, such as technical, legal, regulatory, socio-economic, social or societal, political, ethical, anthropological, philosophical, or psychological perspectives.*The summer school was held virtually.Table of ContentsTutorial Paper.- Don’t Tell Them now (or at all) – End User Notification Duties under GDPR and NIS Directive.- Selected Student Papers.- Ethical Principles for Designing Responsible Offensive Cyber Security Training.- Longitudinal collection and analysis of mobile phone data with local differential privacy.- Privacy-preserving IDS for In-Car-Networks with Local Differential Privacy.- Strong customer authentication in online payments under GDPR and PSD2: a case of cumulative application.- Privacy in Payment in the Age of Central Bank Digital Currency.- Analysing drivers’ preferences for privacy enhancing car-to-car communication systems.- Learning Analytics and Privacy - Respecting Privacy in Digital Learning Scenarios.- Preserving Privacy in Caller ID Applications.- “Identity management by design” with a technical Mediator under the GDPR.- Open about the open-rate? State of email tracking in marketing emails and its effects on user's privacy.- Privacy Respecting Data Sharing and Communication in mHealth: A Case Study.- Privacy-preserving Analytics for Data Markets using MPC.- Towards models for privacy preservation in the face of metadata exploitation.
£42.74
Springer Nature Switzerland AG Cohesive Subgraph Search Over Large Heterogeneous
Book SynopsisThis SpringerBrief provides the first systematic review of the existing works of cohesive subgraph search (CSS) over large heterogeneous information networks (HINs). It also covers the research breakthroughs of this area, including models, algorithms and comparison studies in recent years. This SpringerBrief offers a list of promising future research directions of performing CSS over large HINs.The authors first classify the existing works of CSS over HINs according to the classic cohesiveness metrics such as core, truss, clique, connectivity, density, etc., and then extensively review the specific models and their corresponding search solutions in each group. Note that since the bipartite network is a special case of HINs, all the models developed for general HINs can be directly applied to bipartite networks, but the models customized for bipartite networks may not be easily extended for other general HINs due to their restricted settings. The authors also analyze and compare these cohesive subgraph models (CSMs) and solutions systematically. Specifically, the authors compare different groups of CSMs and analyze both their similarities and differences, from multiple perspectives such as cohesiveness constraints, shared properties, and computational efficiency. Then, for the CSMs in each group, the authors further analyze and compare their model properties and high-level algorithm ideas.This SpringerBrief targets researchers, professors, engineers and graduate students, who are working in the areas of graph data management and graph mining. Undergraduate students who are majoring in computer science, databases, data and knowledge engineering, and data science will also want to read this SpringerBrief.Table of Contents1. Introduction2. Preliminaries3. CSS on Bipartite Networks4. CSS on Other General HINs5. Comparison Analysis6. Related Work on CSMs and solutions7. Future Work and Conclusion
£37.99
Springer International Publishing AG Automated Taxonomy Discovery and Exploration
Book SynopsisThis book provides a principled data-driven framework that progressively constructs, enriches, and applies taxonomies without leveraging massive human annotated data. Traditionally, people construct domain-specific taxonomies by extensive manual curations, which is time-consuming and costly. In today’s information era, people are inundated with the vast amounts of text data. Despite their usefulness, people haven’t yet exploited the full power of taxonomies due to the heavy curation needed for creating and maintaining them. To bridge this gap, the authors discuss automated taxonomy discovery and exploration, with an emphasis on label-efficient machine learning methods and their real-world usages. Taxonomy organizes entities and concepts in a hierarchy way. It is ubiquitous in our daily life, ranging from product taxonomies used by online retailers, topic taxonomies deployed by news outlets and social media, as well as scientific taxonomies deployed by digital libraries across various domains. When properly analyzed, these taxonomies can play a vital role for science, engineering, business intelligence, policy design, e-commerce, and more. Intuitive examples are used throughout enabling readers to grasp concepts more easily.Table of ContentsIntroduction.- Concept Set Expansion.- Taxonomy Construction.- Taxonomy Enrichment.- Taxonomy-Guided Classification.- Conclusions.
£44.99
