Databases / Data management Books

Book SynopsisDigital Innovation in Space Science.- Legal regimes for Space data.- Regulating space data management.- High Performance Computing, AI, the Metaverse and quantum computing to transform space data management.- AI applications of Space Data.- Blockchain-enabled Satellite Onboard Computing for Smart Contract: Benefits for Multi-sided Markets and IoT Applications.- On the use of available space monitoring data for improving the risk of collision avoidance.- Optimising collection, transmission and transformation of space data to take up security challenges.- A Fragile Watermarking Approach for Earth Observation Data Integrity Protection.- Deepness: Deep Neural Remote Sensing QGIS Plugin.- Earth Observation Data Transfer at Limitations of Small Satellite Missions.- Earth Observation Data Management and Offer: the experience of the ARIC.- Using satellite data to estimate NO2 concentrations in mainland UK from 2005 to 2021.- Integration of Terrestrial and Non-Terrestrial Networks: challenges and perspectives within the RESTAR project.- Estimate the ice volume of Earth's glaciers with deep learning and remote sensing.- Can life exist without water? A data driven approach.

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Book Synopsis.- Recommender System..- Hierarchical Review-based Recommendation with Contrastive Collaboration..- Adaptive Augmentation and Neighbor Contrastive Learning for Multi-Behavior Recommendation..- Automated Modeling of Influence Diversity with Graph Convolutional Network for Social Recommendation..- Contrastive Generator Generative Adversarial Networks for Sequential Recommendation..- Distribution-aware Diversification for Personalized Re-ranking in Recommendation..- KMIC: A Knowledge-aware Recommendation with Multivariate Intentions Contrastive Learning..- Logic Preference Fusion Reasoning on Recommendation..- MHGNN: Hybrid Graph Neural Network with Mixers for Multi-interest Session-aware Recommendation..- Mixed Augmentation Contrastive Learning for Graph Recommendation System..- Noise-Resistant Graph Neural Networks for Session-based Recommendation..- S2DNMF: A Self-supervised Deep Nonnegative Matrix Factorization Recommenda

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Book SynopsisThis book gathers a selection of peer-reviewed papers presented at the 4th Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2022) conference, held in Bangkok, Thailand, on December 16–17. The contributions, prepared by an international team of scientists and engineers, cover the latest advances and challenges made in the field of big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.

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Book SynopsisThe book presents papers from the 7th International Conference on Big Data and Cloud Computing Challenges (ICBCC 2022). The book includes high-quality, original research on various aspects of big data and cloud computing, offering perspectives from the industrial and research communities on addressing the current challenges in the field. This book discusses key issues and highlights recent advances in a single broad topic applicable to different sub-fields by exploring various multidisciplinary technologies. This book supports the transfer of vital knowledge to next-generation researchers, students, and practitioners in academia and industry.Table of ContentsTable of contents: Track 1: Architecture Sample topics include, - Cloud Infrastructure as a Service -Cloud Platform as a Service -Cloud federation and hybrid cloud infrastructure -Programming models and systems/tools -Green data center -Networking technologies for data center -Cloud system design with FPGA, GPU, and APU -Monitoring, management and maintenance -Economic and business models -Dynamic resource provisioning Track 2: MapReduce Sample topics include, -Performance characterization and optimization -MapReduce on multi-core, GPU -MapReduce on hybrid distributed environments -MapReduce on opportunistic / heterogeneous computing systems -Extension of the MapReduce programming model -Debugging and simulation of MapReduce systems -Data-intensive applications using MapReduce -Optimized storage for MapReduce applications -Fault-tolerance & Self-capabilities Track 3: Security and Privacy -Accountability -Audit in clouds -Authentication and authorization -Cryptographic primitives -Reliability and availability -Trust and credential management -Usability and security -Security and privacy in clouds -Legacy systems migration -Cloud Integrity and Binding Issues Track 4: Services and Applications -Cloud Service Composition -Query and discovery models for cloud services -Trust and Security in cloud services -Change management in cloud services -Organization models of cloud services -Innovative cloud applications and experiences -Business process and workflow management -Service-Oriented Architecture in clouds Track 5: Virtualization -Server, storage, network virtualization -Resource monitoring -Virtual desktop -Resilience, fault tolerance -Modeling and performance evaluation -Security aspects -Enabling disaster recovery, job migration -Energy efficient issues Track 6. HPC on Cloud -Load balancing for HPC clouds -Middleware framework for HPC clouds -Scalable scheduling for HPC clouds -HPC as a Service -Performance Modeling and Management -Programming models for HPC clouds -HPC cloud applications -Optimal cloud deployment for HPC Track 7. Big Data Science and Foundations -Novel Theoretical Models for Big Data -New Computational Models for Big Data -Data and Information Quality for Big Data -New Data Standards Track 8.Big Data Infrastructure -Cloud/Grid/Stream Computing for Big Data -High Performance/Parallel Computing Platforms for Big Data -Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment -Energy efficient Computing for Big Data -Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data -Software Techniques and Architectures in Cloud/Grid/Stream Computing Big Data Open Platforms -New Programming Models for Big Data beyond Hadoop/MapReduce, STORM -Software Systems to Support Big Data Computing Track 9. Big Data Management -Advanced database and Web Applications -Novel Data Model and Databases for Emerging Hardware -Data Preservation -Data Provenance -Interfaces to Database Systems and Analytics Software Systems -Data Protection, Integrity and Privacy Standards and Policies -Information Integration and Heterogeneous and Multi-structured Data Integration -Data management for Mobile and Pervasive Computing -Data Management in the Social Web -Crowd sourcing -Spatiotemporal and Stream Data Management -Scientific Data Management -Workflow Optimization -Database Management Challenges: Architecture, Storage, User Interfaces Track 10. Big Data Search and Mining -Social Web Search and Mining -Web Search -Algorithms and Systems for Big Data Search -Distributed, and Peer-to-peer Search -Big Data Search Architectures, Scalability and Efficiency -Data Acquisition, Integration, Cleaning, and Best Practices -Visualization Analytics for Big Data -Computational Modeling and Data Integration -Large-scale Recommendation Systems and Social Media Systems -Cloud/Grid/Stream Data Mining- Big Velocity Data -Link and Graph Mining -Semantic-based Data Mining and Data Pre-processing -Mobility and Big Data Track 11. Big Data Security & Privacy -Intrusion Detection for Gigabit Networks -Anomaly and APT Detection in Very Large Scale Systems -High Performance Cryptography -Visualizing Large Scale Security Data -Threat Detection using Big Data Analytics -Privacy Threats of Big Data -Privacy Preserving Big Data Collection/Analytics -HCI Challenges for Big Data Security & Privacy -User Studies for any of the above -Sociological Aspects of Big Data Privacy Track 12. Big Data Applications -Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance -Business, Law, Education -Transportation, Retailing, Telecommunication -Big Data Analytics in Small Business Enterprises (SMEs) -Big Data Analytics in Government, Public Sector and Society in General -Real-life Case Studies of Value Creation through Big Data Analytics -Big Data as a Service -Big Data Industry Standards -Experiences with Big Data Project Deployments Track 13. Recent trends -Semantic Cloud -Mobile Cloud -e-Healthcare Applications in Cloud -Cloud analytics for Internet of Things (IoT) -Smart Grid -Fog Computing -Edge Computing -Deep Learning -CNN

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Book SynopsisThis book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. The volume is a collection of peer reviewed research papers presented at Seventh International Conference on Data Management, Analytics and Innovation (ICDMAI 2023), held during 20 – 22 January, 2023 in Pune, India. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.Table of ContentsA Smart System to Classify Walking and Sitting Activity based on EEG Signal.- Monitoring urban water-logging using SAR - A Mumbai case study.- Suspicious Event Detection of Cargo Vessels based on AIS Data.- Identifying Trends using Improved Affinity Propagation (IMAP) Clustering Algorithm on Evolving Data Stream.- Graphology based behavior prediction : Case study analysis.- Statistics Driven Suspicious Event Detection of Fishing Vessels based on AIS Data.- Distributed Reduced Alphabet Representation for Predicting Proinflammatory Peptides.- Prakruti Nishchitikaran of Human Body using Supervised Machine Learning Approach.- X-ABI: Towards Parameter Efficient Multilingual Adapter Based Inference for Cross-Lingual Transfer.- Comparative Study of Depth Estimation from 2-D Scene Using Deep Learning Model.- DCNN-based Transfer Learning approaches for Gender Recognition.- Analysis of Machine Learning Algorithms for COVID Detection Using Deep Learning.- Real-time learning towards assets allocation.- Named Entity Recognition over Dialogue Dataset using Pre-trained Transformers.- A Comparative Study of Distance-based Clustering Algorithms in Fuzzy Failure Modes and Effects Analysis.- Economical Solution to Automatic Evaluation of an OMR Sheet Using Image Processing.- Defense and evaluation against covert channel based attacks in Android smartphones.- From Bricks to Clicks: The Potential of Big Data Analytics for Revolutionizing the Information Landscape in Higher Education Sector.- Data science approaches to public health: case studies using routine health data from India.- Arboviral Epidemic Disease Forecasting - A Survey on Diagnostics and Outbreak Models.- Convolution Neural Network for Weed Detection.- Machine Learning Model for Brain Stock Prediction.- Analysis of Covid-19 Genome using Continuous Wavelet Transform.

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Book SynopsisMaster the art of machine learning and data science by diving into the essence of mathematical logic with this comprehensive textbook. This book focuses on the widely applicable information criterion (WAIC), also described as the Watanabe-Akaike information criterion, and the widely applicable Bayesian information criterion (WBIC), also described as the Watanabe Bayesian information criterion. The book expertly guides you through relevant mathematical problems while also providing hands-on experience with programming in Python and Stan. Whether you’re a data scientist looking to refine your model selection process or a researcher who wants to explore the latest developments in Bayesian statistics, this accessible guide will give you a firm grasp of Watanabe Bayesian Theory.The key features of this indispensable book include: A clear and self-contained writing style, ensuring ease of understanding for readers at various levels of expertise. 100 carefully selected exercises accompanied by solutions in the main text, enabling readers to effectively gauge their progress and comprehension. A comprehensive guide to Sumio Watanabe’s groundbreaking Bayes theory, demystifying a subject once considered too challenging even for seasoned statisticians. Detailed source programs and Stan codes that will enhance readers’ grasp of the mathematical concepts presented. A streamlined approach to algebraic geometry topics in Chapter 6, making Bayes theory more accessible and less daunting. Embark on your machine learning and data science journey with this essential textbook and unlock the full potential of WAIC and WBIC today!Table of ContentsOver view of Watanabe's Bayes.- Introduction to Watanabe Bayesian Theory.- MCMC and Stan.- Mathematical Preparation.- Regular Statistical Models.- Information Criteria.- Algebraic Geometry.- The Essence of WAOIC.- WBIC and Its Application to Machine Learning.

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Book SynopsisThis two-volume set LNAI 13995 and LNAI 13996 constitutes the refereed proceedings of the 15th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2023, held in Phuket, Thailand, during July 24–26, 2023.The 65 full papers presented in these proceedings were carefully reviewed and selected from 224 submissions. The papers of the 2 volume-set are organized in the following topical sections: Case-Based Reasoning and Machine Comprehension; Computer Vision; Data Mining and Machine Learning; Knowledge Integration and Analysis; Speech and Text Processing; and Resource Management and Optimization.Table of Contents​Case-Based Reasoning and Machine Comprehension.- On the improvement of the reasoning cycle in case-based reasoning.- Exploring incompleteness in Case-Based Reasoning: a strategy for overcoming challenge.- Leveraging both Successes and Failures in Case-Based Reasoning for Optimal Solutions.- Transfer Learning for Abnormal Behaviors Identification in Examination Room from Surveillance Videos: A Case Study in Vietnam.- A Novel Question-Context Interaction Method for Machine Reading Comprehension.- Granular Computing to Forecast Alzheimer’s Disease Distinctive Individual Development.- Computer Vision.- AdVLO: Region selection via Attention-driven for Visual LiDAR Odometry.- Intelligent Retrieval System on Legal Information.- VSNet: Vehicle State Classification for Drone Image with Mosaic Augmentation and Soft-label Assignment.- Creating High-Resolution Adversarial Images against Convolutional Neural Networks with the Noise Blowing-Up Method.- Faster Imputation Using Singular Value Decomposition for Sparse Data.- Combination of deep learning and ambiguity rejection for improving image-based disease diagnosis.- Data Mining and Machine Learning.- Towards Developing an Automated Chatbot for Predicting Legal Case Outcomes: A Deep Learning Approach.- Fuzzy-Based Factor Evaluation System for Momentum Overweight Trading Strategy.- Enhancing Abnormal-Behavior-based Stock Trend Prediction Algorithm with Cost-sensitive Learning Using Genetic Algorithms.- Leveraging Natural Language Processing in Persuasive Marketing.- Direction of the Difference between Bayesian Model Averaging and the Best-Fit Model on Scarce-Data Low-Correlation Churn Prediction.- Tree-based Unified Temporal Erasable-itemset Mining.- Design Recovery of Data Model Hidden in JSON File.- Accurate lightweight calibration methods for mobile low-cost particulate matter sensors.- Generating music for video games with real-time adaptation to gameplay pace.- Detecting Sensitive Data with GANs and Fully Convolutional Networks.- An Unsupervised Deep Learning Framework for Anomaly Detection.- Extracting top-k high utility patterns from multi-level transaction databases.- Lightweight and Efficient Privacy-Preserving Multimodal Representation Inference via Fully Homomorphic Encryption.- Neural Machine Translation with Diversity-enabled Translation Memory.- GIFT4Rec: An effective side Information Fusion Technique apply to Graph neural network for cold-start recommendation.- A Decision Support System for Improving Lung Cancer Prediction based on ANN.- Emotion detection from text in social networks.- Finite Libby-Novick Beta Mixture Model: An MML-Based Approach.- Artificial Intelligences on Automated Context-Brain Recognition with Mobile Detection Devices.- A Novel Meta-Heuristic Search Based on Mutual Information for Filter-Based Feature Selection.- Discovering prevalent co-location patterns without collecting co-location instances.- Integrating Geospatial Tools for Air Pollution Prediction: A Synthetic City Generator Framework for Efficient Modeling and Visualization.- Design of an Automated CNN Composition Scheme with Lightweight Depth-Correlated Convolution for Space-Limited Applications.

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Book SynopsisThis two-volume set LNAI 13995 and LNAI 13996 constitutes the refereed proceedings of the 15th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2023, held in Phuket, Thailand, during July 24–26, 2023. The 65 full papers presented in these proceedings were carefully reviewed and selected from 224 submissions. The papers of the 2 volume-set are organized in the following topical sections: Case-Based Reasoning and Machine Comprehension; Computer Vision; Data Mining and Machine Learning; Knowledge Integration and Analysis; Speech and Text Processing; and Resource Management and Optimization.Table of ContentsKnowledge Integration and Analysis.- A New Data Transformation and Resampling Approach for Prediction of Yield Strength of High-Entropy Alloys.- A Semi-Formal Approach to Describing Semantics of Data Modeling Patterns.- Obfuscating LLVM IR with the Application of Lambda Calculus.- Structural and Compact Latent Representation Learning on Sparse Reward Environments.- A Survey of Explainable Artificial Intelligence Approaches for Sentiment Analysis.- Social collective model of non-internet social networks.- A Data-driven Scheduling Strategy for Mobile Air Quality Monitoring Devices.- Hybrid approaches to sentiment analysis of social media data.- Integrating Ontology-based Knowledge to Improve BiomedicalMulti-Document Summarization Model.- An Improvement of Diachronic Embedding for Temporal Knowledge Graph Completion.- DCA-based weighted bagging: A new ensemble learning approach.- Deep-learning- and GCN-based Aspect-level Sentiment Analysis Methods on Balanced and Unbalanced Datasets.- Applying the Malmquist productivity index model to assess the performance of the coffee enterprise in DakLak Vietnam.- A Cluster-Constrained Graph Convolutional Network for Protein– Protein Association networks.- Fuzzy logic framework for ontology concepts alignment.- Can Ensemble Calibrated Learning enhance Link Prediction? A Study on Commonsense Knowledge.- Multi-criteria Approaches to Explaining Black Box Machine Learning Models.- Improving Loss Function for Polyp Detection Problem.- Flow Plugin Network for Conditional Generation.- Speech and Text Processing.- Investigating the Impact of Parkinson’s Disease on Brain Computations An Online Study of Healthy Controls and PD Patients.- Speech Enhancement using Dynamical Variational AutoEncoder.- Vietnamese Multidocument Summarization using Subgraph Selection-based Approach with Graph-informed Self-attention mechanism.- NegT5: A Cross-Task Text-to-Text Framework for Negation in Question Answering.- An Empirical Study on Punctuation Restoration for English, Mandarin, and Code-switching Speech.- Novel Topic Models for Parallel Topics Extraction from Multilingual Text.- Adapting Code-Switching Language Models with Statistical-Based Text Augmentation.- Improving Hotel Customer Sentiment Prediction by Fusing Review Titles and Contents.- Resource management and optimization.- In support of push-based streaming for the computing continuum.- Effective method of implementing constrained optimization problems using data instances.- Scheduling Deep Learning Training in GPU Cluster Using the Model-similarity-based Policy.

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Book SynopsisThis volume LNCS 14252 constitutes the refereed proceedings of 25th International Conference on Information and Communications Security, ICICS 2023, held in Tianjin, China, during November 18–20, 2023. The 38 full papers presented together with 6 short papers were carefully reviewed and selected from 181 submissions. The conference focuses on: Symmetric-Key Cryptography; Public-Key Cryptography; Applied Cryptography; Authentication and Authorization; Privacy and Anonymity; Security and Privacy of AI; Blockchain and Cryptocurrencies; and System and Network Security. Table of Contents​Symmetric-Key Cryptography.- SAT-aided Differential Cryptanalysis of Lightweight Block Ciphers Midori, MANTIS and QARMA.- Improved Related-Key Rectangle Attack against the Full AES-192.- Block Ciphers Classification Based on Randomness Test Statistic Value via LightGBM.- Cryptanalysis of Two White-Box Implementations of the CLEFIA Block Cipher.- PAE: Towards More Efficient and BBB-secure AE From a Single Public Permutation.- Public-Key Cryptography.- A Polynomial-time Attack on G2SIDH.- Improvements of Homomorphic Secure Evaluation of Inverse Square Root.- Oblivious Transfer from Rerandomizable PKE.- Forward Secure Lattice-based Ring Signature Scheme in the Standard Model.- Applied Cryptography.- Secure Multi-Party Computation with Legally-Enforceable Fairness.- On-demand Allocation of Cryptographic Computing Resource with Load Prediction.- Private Message Franking with After Opening Privacy.- Semi-Honest 2-Party Faithful Truncation from Two-Bit Extraction.- Outsourcing Verifiable Distributed Oblivious Polynomial Evaluation from Threshold Cryptography.- Authentication and Authorization.- PiXi: Password Inspiration by Exploring Information.- Security Analysis of Alignment-Robust Cancelable Biometric Scheme for Iris Verification.- A Certificateless Conditional Anonymous Authentication Scheme for Satellite Internet of Things.- BLAC: A Blockchain-based Lightweight Access Control Scheme in Vehicular Social Networks.- Privacy and Anonymity.- Link Prediction-Based Multi-Identity Recognition of Darknet Vendors.- CryptoMask: Privacy-preserving Face Recognition.- Efficient Private Multiset ID Protocols.- Zoomer: A Website Fingerprinting Attack against Tor Hidden Services.- An Enhanced Privacy-preserving Hierarchical Federated Learning Framework for IoV.- Security and Privacy of AI.- Revisiting the Deep Learning-based Eavesdropping Attacks via Facial Dynamics from VR Motion Sensors.- Multi-scale Features Destructive Universal Adversarial Perturbations.- Pixel-Wise Reconstruction of Private Data in Split Federated Learning.- Neural Network Backdoor Attacks Fully Controlled by Composite Natural Utterance Fragments.- Black-Box Fairness Testing with Shadow Models.- Graph Unlearning using Knowledge Distillation.- AFLOW: Developing Adversarial Examples under Extremely Noise-limited Settings.- Learning to Detect Deepfakes via Adaptive Attention and Constrained Difference.- A Novel Deep Ensemble Framework for Online Signature Verification Using Temporal and Spatial Representation.- Blockchain and Cryptocurrencies.- SCOPE: A Cross-Chain Supervision Scheme for Consortium Blockchains.- Subsidy Bridge: Rewarding Cross-blockchain Relayers with Subsidy.- Towards Efficient and Privacy-Preserving Anomaly Detection of Blockchain-based Cryptocurrency Transactions.- Blockchain based Publicly Auditable Multi-Party Computation with Cheater Detection.- BDTS: Blockchain-based Data Trading System.- Illegal Accounts Detection on Ethereum using Heterogeneous Graph Transformer Networks.- System and Network security.- DRoT: A Decentralised Root of Trust for Trusted Networks.- Finding Missing Security Operation Bugs via Program Slicing and Differential Check.- TimeClave: Oblivious In-enclave Time series Processing System.- Efficient and Appropriate Key Generation Scheme in Different IoT Scenarios.- A Fake News Detection Method Based on A Multimodal Cooperative Attention Network.

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Book SynopsisThe book is a comprehensive guide that explores the concept of data economy and its implications in today's world. The book discusses the principles and components of the ecosystem, the challenges and opportunities presented by data monetization, and the potential risks related to data privacy. Real-life examples and case studies are included to understand the concepts better. The book is suitable for individuals in data science, economics, business, and technology and for students, academics, and policymakers. It is an excellent read for anyone interested in the data economy.Table of ContentsChapter 1: Data Economy.- Chapter 2: Navigating the Data Deluge: Challenges and Opportunities.- Chapter 3: Data Monetization.- Chapter 4: Demographic Trend of Data Economy.- Chapter 5: The Economy of Data Privacy.- Chapter 6: Application of Data Economy.

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Book SynopsisThis introductory textbook teaches the simple development of geospatial applications based on the principles and software tools of geospatial data science. It introduces a new generation of geospatial technologies that have emerged from the development of the Semantic Web and the linked data paradigm, and shows how data scientists can use them to build environmental applications easily. Geospatial data science is the science of collecting, organizing, analyzing, and visualizing geospatial data. Since around 2010, there has been extensive work in the area of geospatial data science using semantic technologies and linked data, from researchers in the areas of the Semantic Web, Geospatial Databases and Geoinformatics. The main results of this research have been the publication of the OGC standard GeoSPARQL and the implementation of a number of linked data tools supporting this standard. Up to now, there has been no textbook that enables someone to teach this material to undergraduate or graduate students.The material of the book is developed in a tutorial style and it is appropriate for an introductory course on the subject. This can be an advanced undergraduate course or a graduate course offered by Computer Science or GIS faculty. It is a hands-on approach and every chapter contains exercises that help students master the material.The book is accompanied by a Web site where solutions to some of the exercises are given together with supplementary material such as datasets and code. Most of the material in the book has been tried in the "Knowledge Technologies" course taught by the first author in the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens since 2012.

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Book SynopsisThis introductory textbook teaches the simple development of geospatial applications based on the principles and software tools of geospatial data science. It introduces a new generation of geospatial technologies that have emerged from the development of the Semantic Web and the linked data paradigm, and shows how data scientists can use them to build environmental applications easily. Geospatial data science is the science of collecting, organizing, analyzing, and visualizing geospatial data. Since around 2010, there has been extensive work in the area of geospatial data science using semantic technologies and linked data, from researchers in the areas of the Semantic Web, Geospatial Databases and Geoinformatics. The main results of this research have been the publication of the OGC standard GeoSPARQL and the implementation of a number of linked data tools supporting this standard. Up to now, there has been no textbook that enables someone to teach this material to undergraduate or graduate students.The material of the book is developed in a tutorial style and it is appropriate for an introductory course on the subject. This can be an advanced undergraduate course or a graduate course offered by Computer Science or GIS faculty. It is a hands-on approach and every chapter contains exercises that help students master the material.The book is accompanied by a Web site where solutions to some of the exercises are given together with supplementary material such as datasets and code. Most of the material in the book has been tried in the "Knowledge Technologies" course taught by the first author in the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens since 2012.

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Book Synopsis*One-stop reference for administration and management of Oracle 10g Database *9i predecessor was a best seller; this edition covers all new features, with fully field-tested examples—not just "showcase" examples *Contains essential primers on Unix, Linux and Windows NT management and on SQL and PL/SQL programming; ideal for new/aspiring DBAsTable of ContentsA table of contents is not available for this title.

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Trade Review"Most executives are familiar with big data, business intelligence (BI), analytics, business performance management, business process management, and fact-based decision-making, but they are uncertain about how to best deploy them to create business value. In this book you will find both content and features that will help you plan and execute BI strategically. Worthy of special mention is the treatment of big data and analytics. The hype around both topics is especially high, and it is easy to think that they are so new and different that they need to be treated in special ways. This book provides a clear understanding of the ways that big data and analytics both differ from the past but also the many ways that they are just a logical extension of what has come before. When viewed in this context, the strategic planning for BI and analytics in the world of big data is very similar to planning for BI in general. If you need to think about BI (and all the related topics) strategically in your company, I’m confident that you will find this book to be very helpful." --Hugh Watson, Professor and C. Herman and Mary Virginia Terry Chair of Business Administration, Terry College of Business, University of Georgia and Senior Editor, Business Intelligence JournalTable of Contents1. The Personal Face of Business Intelligence 2. Business Intelligence in the Era of Big Data and Cognitive Business 3. The Strategic Importance of Business Intelligence 4. BI Opportunity Analysis 5. Prioritizing BI Opportunities (BIOs) 6. Leveraging BI for Performance Management, Process Improvement, and Decision Support 7. Meeting the Challenges of Enterprise BI 8. General Management Perspectives on Technical Topics

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