Expert systems / knowledge-based systems Books

Book SynopsisOb Juristen, Mediziner oder Ökonomen – Expertenfiguren prägen bereits seit Jahrhunderten die okzidentalen Gesellschaften. Als Träger und Verwalter exklusiver Wissensbestände haben sie eine soziale Sonderstellung inne. Denn sie bestimmen maßgeblich die Zugänglichkeit, Organisation und Ausformung des verfügbaren Wissens und behaupten auf diese Weise eine weitreichende Machtposition, die häufig Kritik provoziert. Gleichwohl sind sie ihrerseits ebenso von den Nicht-Experten abhängig, ist die Expertenrolle doch wesentlich ein Produkt sozialer Aushandlungsprozesse: Experte ist man nicht, man wird es durch die eigene wie auch die fremde Zuschreibung spezifischen Wissens. Der Expertenstatus beruht so zu weiten Teilen auf Momenten der Selbstdarstellung und Inszenierung, auf Symboliken und Habitus. Die Beiträge des vorliegenden Bandes nehmen aus der Perspektive unterschiedlicher Disziplinen europäische und außereuropäische Kulturen diese Mechanismen in Expertenkulturen vom 12. bis zum 21. Jahrhundert in den Blick. Anhand etwa von Wirtschaftsexperten der Gegenwart und von mittelalterlichen Astrologen, niederländischen Nautik-Expertisen der frühen Neuzeit und japanischen Rechtsexperten werden Legitimations- und Kommunikationsstrategien sowie Wissens- und Handlungsformen von Experten sichtbar gemacht.

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Book SynopsisTable of Contents1 Einleitung.- 2 Einstieg in das Arbeiten mit AutoCAD.- 2.1 Anstarten und Beenden des Arbeitens mit AutoCAD.- 2.2 Das Arbeiten mit Dateien.- 2.3 Hilfen für den Benutzer.- 2.4 Festlegen der Zeichnungsgröße.- 3 Das Zeichnen gerader Linien.- 3.1 Der Befehl LINIE.- 3.2 Löschen von Zeichnungselementen.- 3.3 Zeichnen von Linien im Ortho-Modus.- 4 Hilfen beim Zeichnen.- 4.1 Das Arbeiten mit Rastern.- 4.2 Das Arbeiten mit verschiedenen Objektfang-Modi.- 5 Das Arbeiten mit Bildausschnitten.- 5.1 Der Befehl ZOOM.- 5.2 Der Befehl PAN.- 6 Kreise, Kreisbögen und Abrundungen.- 6.1 Das Zeichnen von Kreisen.- 6.2 Das Zeichnen von Kreisbögen.- 6.3 Das Abrunden sich schneidender Linien.- 7 Die Bemaßung von Zeichnungen.- 7.1 Allgemeines zum Bemaßen.- 7.2 Ausführen von Linearbemaßungen.- 7.3 Winkelbemaßungen.- 7.4 Durchmesser- und Radienbemaßung.- 7.5 Weitere Optionen des Bemaßungsbefehls BEM.- 8 Das Arbeiten mit Texten.- 8.1 Der Befehl TEXT.- 8.2 Der Befehl DTEXT.- 8.3 Der Befehl STIL.- 9 Regenerieren von Zeichnungen.- 10 Das Zeichnen von Bändern und Flächen.- 10.1 Der Befehl BAND.- 10.2 Der Befehl SOLID.- 11 Das Schraffieren von Flächen.- 11.1 Das eigentliche Schraffieren.- 11.2 Befehle zum Löschen von Zeichnungsteilen.- 12 Das Zeichnen von Freihandlinien.- 13 Abfrage- und Anzeigebefehle.- 14 Layer-Technik.- 14.1 Der Befehl LAYER.- 14.2 Umbenennen und Löschen von Layern.- 15 Das Arbeiten mit Blöcken.- 15.1 Das Erzeugen von Blöcken.- 15.2 Das Einfügen von Blöcken.- 16 Das Manipulieren von Zeichnungen.- 16.1 Das Verschieben und Spiegeln von Objekten.- 16.2 Das Kopieren von Objekten.- 16.3 Das Ändern von Objekten.- 17 Das Erstellen von Zusammenbau-Zeichnungen.- A Lösungen.- B Zusätzliche Übungsaufgaben.- C Standard-Schraffuren.- D Referenzliste.

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Book SynopsisThis book constitutes the thoroughly refereed joint post-proceedings of three international workshops organized by the Japanese Society for Artificial Intelligence, held in Tokyo, Japan in June 2006 during the 20th Annual Conference JSAI 2006. The volume starts with eight award winning papers of the JSAI 2006 main conference that are presented along with the 21 revised full workshop papers, carefully reviewed and selected for inclusion in the volume.Table of ContentsAwarded Papers.- Overview of Awarded Papers – The 20th Annual Conference of JSAI.- Translational Symmetry in Subsequence Time-Series Clustering.- Visualization of Contents Archive by Contour Map Representation.- Discussion Ontology: Knowledge Discovery from Human Activities in Meetings.- Predicting Types of Protein-Protein Interactions Using a Multiple-Instance Learning Model.- Lattice for Musical Structure and Its Arithmetics.- Viewlon: Visualizing Information on Semantic Sensor Network.- Cooperative Task Achievement System Between Humans and Robots Based on Stochastic Memory Model of Spatial Environment.- People Who Create Knowledge Sharing Communities.- Logic and Engineering of Natural Language Semantics.- Logic and Engineering of Natural Language Semantics (LENLS) 3.- A Dynamic Semantics of Intentional Identity.- Prolegomena to General-Imaging-Based Probabilistic Dynamic Epistemic Logic.- Logical Dynamics of Commands and Obligations.- On Factive Islands: Pragmatic Anomaly vs. Pragmatic Infelicity.- Aspects of the Indefiniteness Effect.- Interpreting Metaphors in a New Semantic Theory of Concept.- Covert Emotive Modality Is a Monster.- Conversational Implicatures Via General Pragmatic Pressures.- Dake-wa: Exhaustifying Assertions.- Unembedded ‘Negative’ Quantifiers.- Learning with Logics and Logics for Learning.- The Fourth Workshop on Learning with Logics and Logics for Learning (LLLL2006).- Consistency Conditions for Inductive Inference of Recursive Functions.- Inferability of Closed Set Systems from Positive Data.- An Extended Branch and Bound Search Algorithm for Finding Top-N Formal Concepts of Documents.- N-Gram Analysis Based on Zero-Suppressed BDDs.- Risk Mining.- Risk Mining - Overview.- Analysis on a Relation Between Enterprise Profit and Financial State by Using Data Mining Techniques.- Unusual Condition Detection of Bearing Vibration in Hydroelectric Power Plants for Risk Management.- Structural Health Assessing by Interactive Data Mining Approach in Nuclear Power Plant.- Developing Mining-Grid Centric e-Finance Portals for Risk Management.- Knowledge Discovery from Click Stream Data and Effective Site Management.- Sampling-Based Stream Mining for Network Risk Management.- Relation Between Abductive and Inductive Types of Nursing Risk Management.

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Book SynopsisThis book constitutes the thoroughly refereed post-conference proceedings of the Third International ICST Conference on Sensor Systems and Software, S-Cube 2012, held in Lisbon, Portugal in June 2012. The 12 revised full papers presented were carefully reviewed and selected from over 18 submissions and four invited talks and cover a wide range of topics including middleware, frameworks, learning from sensor data streams, stock management, e-health, and Web Of Things.Table of ContentsFast conference proceedings.-State-of-the-art report.-Up to date results

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Book SynopsisThis book constitutes the refereed proceedings of the 13th Industrial Conference on Data Mining, ICDM 2013, held in New York, NY, in July 2013. The 22 revised full papers presented were carefully reviewed and selected from 112 submissions. The topics range from theoretical aspects of data mining to applications of data mining, such as in multimedia data, in marketing, finance and telecommunication, in medicine and agriculture, and in process control, industry and society.Table of ContentsTheoretical aspects of data mining; applications of data mining in multimedia data.- Applications of data mining in marketing and in finance.- Applications of data mining in telecommunication.- Applications of data mining in medicine and agriculture.- Applications of data mining in process control, industry and society.

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Book SynopsisMachine learning and data mining are inseparably connected with uncertainty. The observable data for learning is usually imprecise, incomplete or noisy. Uncertainty Modeling for Data Mining: A Label Semantics Approach introduces 'label semantics', a fuzzy-logic-based theory for modeling uncertainty. Several new data mining algorithms based on label semantics are proposed and tested on real-world datasets. A prototype interpretation of label semantics and new prototype-based data mining algorithms are also discussed. This book offers a valuable resource for postgraduates, researchers and other professionals in the fields of data mining, fuzzy computing and uncertainty reasoning.Zengchang Qin is an associate professor at the School of Automation Science and Electrical Engineering, Beihang University, China; Yongchuan Tang is an associate professor at the College of Computer Science, Zhejiang University, China.

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Book SynopsisData matching (also known as record or data linkage, entity resolution, object identification, or field matching) is the task of identifying, matching and merging records that correspond to the same entities from several databases or even within one database. Based on research in various domains including applied statistics, health informatics, data mining, machine learning, artificial intelligence, database management, and digital libraries, significant advances have been achieved over the last decade in all aspects of the data matching process, especially on how to improve the accuracy of data matching, and its scalability to large databases.Peter Christen’s book is divided into three parts: Part I, “Overview”, introduces the subject by presenting several sample applications and their special challenges, as well as a general overview of a generic data matching process. Part II, “Steps of the Data Matching Process”, then details its main steps like pre-processing, indexing, field and record comparison, classification, and quality evaluation. Lastly, part III, “Further Topics”, deals with specific aspects like privacy, real-time matching, or matching unstructured data. Finally, it briefly describes the main features of many research and open source systems available today.By providing the reader with a broad range of data matching concepts and techniques and touching on all aspects of the data matching process, this book helps researchers as well as students specializing in data quality or data matching aspects to familiarize themselves with recent research advances and to identify open research challenges in the area of data matching. To this end, each chapter of the book includes a final section that provides pointers to further background and research material. Practitioners will better understand the current state of the art in data matching as well as the internal workings and limitations of current systems. Especially, they will learn that it is often not feasible to simply implement an existing off-the-shelf data matching system without substantial adaption and customization. Such practical considerations are discussed for each of the major steps in the data matching process.Trade Review"The book is very well organized and exceptionally well written. Because of the depth, amount, and quality of the material that is covered, I would expect this book to be one of the standard references in future years." William E. Winkler, U.S. Bureau of the Census, Washington, DC, USATable of ContentsPart I Overview.- Introduction.- The Data Matching Process.- Part II Steps of the Data Matching Process.- Data Pre-Processing.- Indexing.- Field and Record Comparison.- Classification.- Evaluation of Matching Quality and Complexity.- Part III Further Topics.- Privacy Aspects of Data Matching.- Further Topics and Research Directions.- Data Matching Systems.

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Book SynopsisEmbedded systems have long become essential in application areas in which human control is impossible or infeasible. The development of modern embedded systems is becoming increasingly difficult and challenging because of their overall system complexity, their tighter and cross-functional integration, the increasing requirements concerning safety and real-time behavior, and the need to reduce development and operation costs.This book provides a comprehensive overview of the Software Platform Embedded Systems (SPES) modeling framework and demonstrates its applicability in embedded system development in various industry domains such as automation, automotive, avionics, energy, and healthcare. In SPES 2020, twenty-one partners from academia and industry have joined forces in order to develop and evaluate in different industrial domains a modeling framework that reflects the current state of the art in embedded systems engineering.The content of this book is structured in four parts. Part I “Starting Point” discusses the status quo of embedded systems development and model-based engineering, and summarizes the key requirements faced when developing embedded systems in different application domains. Part II “The SPES Modeling Framework” describes the SPES modeling framework. Part III “Application and Evaluation of the SPES Modeling Framework” reports on the validation steps taken to ensure that the framework met the requirements discussed in Part I. Finally, Part IV “Impact of the SPES Modeling Framework” summarizes the results achieved and provides an outlook on future work.The book is mainly aimed at professionals and practitioners who deal with the development of embedded systems on a daily basis. Researchers in academia and industry may use it as a compendium for the requirements and state-of-the-art solution concepts for embedded systems development.Table of ContentsPart I Starting Situation.- Challenges in Engineering for Software-Intensive Embedded Systems.- Requirements from the Application Domains.- Part II The SPES Modeling Framework.- Introduction to the SPES Modeling Framework.- Requirements Viewpoint.- Functional Viewpoint.- Logical Viewpoint.- Technical Viewpoint.- Modeling Quality Aspects: Safety.- Modeling Quality Aspects: Real-Time.- Part III Application and Evaluation of the SPES Modeling Framework.- Overview of the SPES Evaluation Strategy.- Application and Evaluation in the Automation Domain.- Application and Evaluation in the Automotive Domain.- Application and Evaluation in the Avionics Domain.- Application and Evaluation in the Energy Domain.- Application and Evaluation in the Healthcare Domain.- Evaluation Summary.- Part IV Impact of the SPES Modeling Framework.- Lessons Learned.- Outlook.

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Book SynopsisFür die Printmedienunternehmen haben sich durch das Internet neue Geschäftsfelder eröffnet: Informationen werden sowohl für die Papier- als auch für die Onlineausgabe aufbereitet. Neue Möglichkeiten in der Zusammenarbeit mit Kunden und Produktionspartnern entstehen. Der Leser erhält einen umfassenden Überblick über die neuen Produkte und Prozesse und wird systematisch durch die Begriffsvielfalt geführt; zahlreiche Beispiele veranschaulichen die Anwendungen wie Online-Editiersysteme, webbasierte Projektmanagementtools oder Online-Tracking von Druckaufträgen. Das Thema wird aus zwei Blickwinkeln betrachtet: dem des Unternehmens, das E-Business zur Verbesserung der eigenen Prozesse nutzt, und dem des Printmediendienstleisters, der E-Business-Services für seine Kunden bereitstellt und im Produktionsprozess nutzt. Das Buch liefert Entscheidungshilfen, welche Anwendungen für betriebliche Fragestellungen den größtmöglichen Nutzen versprechen. Ein unentbehrliches Nachschlagewerk für Entscheidungsträger.Table of Contents1 Neue Produkte und Dienstleistungen.- 1.1 Kernkompetenz Druck oder crossmedialer Dienstleister — eine strategische Entscheidung.- 1.2 Internetprasenzen erstellen und pflegen.- 1.3 Datenbanken aufbauen, erweitern und Verfugbarkeit sicherstellen durch Media-Asset-Managernent-Systeme.- 1.4 Database Publishing — aus Datenbanken heraus produzieren.- 1.5 Content-Management-Systeme auswahlen, einrichten und selbst nutzen.- 1.6 E-Commerce-Systeme integrieren.- 1.7 E-Learning-Anwendungen entwickeln.- 1.8 Qualitatssicherung als Dienstleistung.- 2 Prozesseffizienz durch kundenintegrierte Produktion.- 2.1 Standarddatenformate als Voraussetzung fur die vernetzte Produktion.- 2.1.1 PDF/X-3 — der Standard im technischen Workflow.- 2.1.2 JDF — auf dem Weg zum Standard in der vernetzten Produktion.- 2.1.3 XML — der Standard im E-Business.- 2.2 Prozesseffizienz durch Selbstbedienung: der self-directed-customer.- 2.2.1 Online-Kalkulation — schneller als der Kunde schafft es kein Vertrieb.- 2.2.2 Online-Auftragserteilung.- 2.2.3 Online-Preflight.- 2.2.4 Daten andern und Softproof freigeben — das Prinzip des Web-Printing.- 2.2.5 Order-Tracking — Auftragsverfolgung durch den Kunden.- 2.2.6 Angebots- und Auftragsarchivierung.- 2.2.7 Lagerabrufsysteme.- 2.2.8 Online-Bestellsysteme.- 2.2.8.1 Spezialanwendungen fiir Copyshops Beispiel Copymobil.de.- 2.2.8.2 Spezialanwendung fur Mailings Beispiel Mailingfactory der Deutschen Post.- 2.2.8.3 Kundenindividuelles Online-Bestellsystem am Beispiel PSH iWayPrime — Integration bis zur Druckmaschine.- 2.2.8.4 Kundenindividuelles Online-Bestellsystem am Beispiel PrintVis — Integration in die betriebswirtschaftlichen Systeme.- 2.2.8.5 Corporate-Design-Portal am Beispiel der Adam Opel AG.- 2.2.9 Vorgehensweise bei der Einfiihrung von self-directed-customer-Systemen.- 2.3 Prozesseffizienz in der Zusammenarbeit — der Kunde als Co-Produzent.- 2.3.1 Änderungen und Freigaben.- 2.3.1.1 Änderungen und Freigaben im PDF-Dokument.- 2.3.1.2 Änderungen und Freigaben im Team — Beispiel Synapse Insite.- 2.3.2 Online-Editiersysteme — Beispiel StreamGuide Web.- 2.3.3 Remote Proofing.- 3 E-Business fuür Einkäufer.- 3.1 Beschaffungsprozesse beim Kunden und Potenziale des E-Procurement.- 3.2 Online-Marktpäitze — der Verkauf öber Drucksachenvermittler.- 3.3 Angebots- und Auftragsverwaltungssysteme — Effizienz im Einkauf.- 3.3.1 Lieferantenauswahl.- 3.3.2 Auftragsabwicklung.- 4 E-Business fur Druckereien.- 4.1 Marketing und Vertrieb.- 4.1.1 Die eigene Internetprasenz — Neukundengewinnung und Kundenbindung.- 4.1.1.1 Inhalte der Internetprasenz.- 4.1.1.2 E-Marketing.- 4.1.2 Ausschreibungenauf Kunden zugehen ohne Kundenkontakt.- 4.1.3 Reverse Auction — Drucken urn jeden Preis?.- 4.2 Beschaffung.- 4.2.1 Papiereinkauf.- 4.2.1.1 SchneiderSoehne-online.com — kundenindividuelle Preise, Verfiigbarkeit und Liefertermin auf einen Klick.- 4.2.1.2 Marktplatz fur die Papierbeschaffung — Beispiel eN Papiervertriebs GmbH.- 4.2.2 Druckfarben — Beispiel BASF Drucksysteme.- 4.2.3 Bild, Schrift, Grafik & mehr.- 4.2.4 Produktionspartner — wie man neue Zulieferer und freiberufiiche Mitarbeiter findet.- 5 Nachwort.- 6 Glossar.

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Book SynopsisDas Internet bietet Unternehmen und Kunden ganz neue Kommunikationsmöglichkeiten. Via Corporate-Website der Unternehmen können sich Kunden 24 Stunden am Tag mit Informationen über das Unternehmen versorgen. Dies ermöglicht Unternehmen direkten Einfluss auf ihre Kunden auszuüben und gleichzeitig umfangreiche Informationen über diese zu sammeln. Auf der anderen Seite belastet der Anspruch der permanenten Verfügbarkeit zur Gewährleistung eines optimalen Kundenservices das Kundenservice-Potential der Unternehmen. Chatbots entlasten Call-Center und Customer-Support-Abteilungen, da sie bereits 80 % der gestellten Fragen direkt via Website beantworten können. Sie sind 24 Stunden am Tag verfügbar, Kosten werden reduziert. Ferner wird den Benutzern der Umgang mit der Website erleichtert. Die automatisch dokumentierten Unterhaltungen liefern zudem konkrete Einblicke in den tatsächlichen Informationsbedarf der Kunden.Table of Contents1 Einleitung.- 1.1 Zustandsbeschreibung.- 1.2 Problembeschreibung.- 1.3 Problemanalyse.- 1.3.1 Sprachproblematik.- 1.3.2 Divergenz der Bedürfnisse.- 1.3.3 Komplexität verteilter Systeme.- 1.4 Lösungsansatz.- 1.5 Abgrenzung des Themas.- 1.6 Vorgehen.- 2 Grundlagen.- 2.1 Begriffsabgrenzung.- 2.1.1 User Interface.- 2.1.2 Usability.- 2.1.3 Agenten.- 2.1.4 Chatbot.- 2.1.5 Künstliche Intelligenz.- 2.2 Historische Entwicklung.- 2.2.1 Aufweichung der Grenze Mensch-Maschine.- 2.2.2 Human-Computer Interaction (HCI).- 2.2.3 Entwicklung von Chatbots.- 2.2.4 Chatbots im Zentrum der Kritik.- 2.3 Warum Chatbots?.- 2.3.1 Interaktion in natürlicher Sprache.- 2.3.2 Aktive Gesprächsführung.- 2.3.3 Informationsstrukturierung.- 2.3.4 Realisierung von Einsparungspotenzialen.- 2.3.5 Gewinnung von Kundeninformationen.- 2.3.6 Gesteigerte Zugänglichkeit.- 2.4 Formen von Chatbots.- 2.4.1 Verständnisebenen von Chatbots.- 2.4.2 Beispiele.- 3 Gestaltungsgrundsätze.- 3.1 Implikationen adaptiver Funktionalität.- 3.2 Natürliche Sprache.- 3.3 Repräsentierung.- 3.3.1 Tool oder Team?.- 3.3.2 Höflichkeit.- 3.3.3 Komplimente.- 3.3.4 Form der Repräsentierung.- 3.3.5 Persönlichkeit.- 3.3.6 Spezialisten.- 3.3.7 Geschlechts-Stereotypen.- 3.3.8 Verwendung von Stimmen / Personifizierung.- 3.3.9 Bewegung.- 3.3.10 Synchronismus.- 3.4 Glaubhaftigkeit und Vertrauenswürdigkeit.- 3.5 Konzeptionelle Implementierungsrichtlinien.- 3.5.1 Klare Kommunikation.- 3.5.2 Anreize schaffen.- 3.5.3 Konsistenten Multichannel-Kontakt ermöglichen / Integration.- 3.5.4 Kontinuierliche Weiterentwicklung.- 4 Evaluation.- 4.1 Moralische Einwände.- 4.1.1 Evaluation der Kritik.- 4.1.2 Folgerungen.- 4.2 Verständnisproblematik: Kontext und Gesunder Menschenverstand.- 4.2.1 Evaluation der Kritik.- 4.2.2 Folgerungen.- 4.3 Personifizierte Interfaces.- 4.3.1 Evaluation der Kritik.- 4.3.2 Folgerungen.- 4.4 Ineffizienz indirekter Manipulation.- 4.4.1 Evaluation der Kritik.- 4.4.2 Folgerungen.- 4.5 Erkenntnisse aus dem Praxiseinsatz.- 4.5.1 Coca-Cola.- 4.5.2 Defense Logistics Information Service.- 4.5.3 Deutsche Direktbank.- 4.5.4 Deutscher Getränkefabrikant.- 4.5.5 Direkt Anlage Bank.- 4.5.6 Ford.- 4.5.7 Hannoversche Lebensversicherung.- 4.5.8 Interact Commerce.- 4.5.9 Net-tissimo.com.- 4.5.10 One2One.- 4.5.11 Pioneer Investment.- 4.5.12 Schwäbisch-Hall.- 4.5.13 Zusammenfassung.- 5 Anwendungsszenarien.- 6 Ausblick.- 7 Anhang.- 7.1 Übersicht: Anbieter, Anwender, Forschungsgebiete.- 7.2 Interviews.- 7.2.1 Coca-Cola.- 7.2.2 Defense Logistics Information Service.- 7.2.3 Deutsche Direktbank.- 7.2.4 Deutscher Getränkefabrikant.- 7.2.5 Direkt Anlage Bank.- 7.2.6 Hannoversche Lebensversicherung.- 7.2.7 Net-tissimo.com.- 7.2.8 Pioneer Investment.- 7.2.9 Schwäbisch-Hall.- 7.3 AIML-Spezifikation.- 7.3.1 Grundaufbau AIML.- 7.3.2 Reduktion.- 7.3.3 SRAI.- 7.3.4 Lernen (Think).- 7.3.5 Variablen.- 7.3.6 Eigenschaften (Predicates).- 7.3.7 Scripts.- Literatur.

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Book SynopsisDieses essential geht präzise auf die Anforderungen und Lösungsansätze in Datenmigrations- und Konsolidierungsszenarien im SAP-Umfeld ein und präsentiert Fallbeispiele von SAP-Kunden. Der Beitrag unterstützt Unternehmen, die vor Fusionen, Zu- oder Verkäufen oder Umstrukturierungsvorhaben stehen und effiziente und verlässliche Lösungen zur Datenmigration benötigen, um die Organisationsstrukturen und Prozesse innerhalb ihrer Systemlandschaft an die betrieblichen Veränderungen anzupassen. Die Autoren zeigen, wie Unternehmen ihre Systemlandschaft harmonisieren und konsolidieren können und somit einheitliche Strukturen etabliert, die Systemkomplexität reduziert und damit der Geschäftsbetrieb verbessert werden können.Table of ContentsWas Sie in diesem Essential finden können.- Die Bedeutung von Datenmigration und Systemkonsolidierung für den Unternehmenserfolg.- Vereinfachung und Standardisierung bei großen Datenvolumen (Big Data) durch Systemkonsolidierung.- Datenmigration.- Was Sie aus diesem Essential mitnehmen können.

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Book SynopsisThis book is a comprehensive introduction to the methods and algorithms of modern data analytics. It provides a sound mathematical basis, discusses advantages and drawbacks of different approaches, and enables the reader to design and implement data analytics solutions for real-world applications. This book has been used for more than ten years in the Data Mining course at the Technical University of Munich. Much of the content is based on the results of industrial research and development projects at Siemens.Table of ContentsData Analytics - Data and Relations - Data Preprocessing - Data Visualization - Correlation - Regression - Forecasting - Classification - Clustering.

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Book SynopsisFür Leser, die bereits die Grundlagen der Wissensverarbeitung und Computernetzwerke beherrschen, gibt das Buch einen Überblick über innovative Verfahren, die die automatisierte Suche, Recherche, Klassifikation und Verwaltung von Texten im Kontext dezentraler Systeme und vor allem im WWW erlauben. Besondere Aufmerksamkeit wird dabei auf eine personalisierte Verarbeitung gerichtet, die auch zeitliche Aspekte, wie z. B. das digitale Vergessen, einbeziehen. An vielen Stellen werden auf interessante und neuartige Art und Weise Analogien aus anderen Wissensgebieten, so z. B. zur Verarbeitung von Informationen und zum Lernen im menschlichen Gehirn sowie der Natur schlechthin genutzt.Table of ContentsWissensverarbeitung im menschlichen Gehirn - Lernen - Netzwerke für die Textanalyse - Digitale Updates und digitales Vergessen - Exploration von Netzwerkstrukturen - Konzepte des Text Minings in dezentralen Systemen - Informationsmanagement im Web

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Book SynopsisThis book presents a comprehensive and systematic introduction to transforming process-oriented data into information about the underlying business process, which is essential for all kinds of decision-making. To that end, the authors develop step-by-step models and analytical tools for obtaining high-quality data structured in such a way that complex analytical tools can be applied. The main emphasis is on process mining and data mining techniques and the combination of these methods for process-oriented data. After a general introduction to the business intelligence (BI) process and its constituent tasks in chapter 1, chapter 2 discusses different approaches to modeling in BI applications. Chapter 3 is an overview and provides details of data provisioning, including a section on big data. Chapter 4 tackles data description, visualization, and reporting. Chapter 5 introduces data mining techniques for cross-sectional data. Different techniques for the analysis of temporal data are then detailed in Chapter 6. Subsequently, chapter 7 explains techniques for the analysis of process data, followed by the introduction of analysis techniques for multiple BI perspectives in chapter 8. The book closes with a summary and discussion in chapter 9. Throughout the book, (mostly open source) tools are recommended, described and applied; a more detailed survey on tools can be found in the appendix, and a detailed code for the solutions together with instructions on how to install the software used can be found on the accompanying website. Also, all concepts presented are illustrated and selected examples and exercises are provided.The book is suitable for graduate students in computer science, and the dedicated website with examples and solutions makes the book ideal as a textbook for a first course in business intelligence in computer science or business information systems. Additionally, practitioners and industrial developers who are interested in the concepts behind business intelligence will benefit from the clear explanations and many examples.Trade Review“The usage of examples and case studies enable real life application and brings asophisticated text to life. … the book is a comprehensive and thoroughly well thought out introduction to the subject of business intelligence and the reader will not be left wanting as the clear examples are numerous. … Readers interested in the value of data and the concepts behind business intelligence will find the book and its accompanying website highly informative.” (Georgette Banham, bcs, The Chartered Institute for IT, bcs.org, August, 2016)“This book focuses primarily on the data mining, data warehousing, data analytics, data visualization, data presentation, and process analysis dimensions of BI in detail. … One of the noteworthy strengths of this book is the inclusion of comprehensive lists with very recent and relevant references for BI at the end of each chapter. This should make the book very useful for academic research on the topic.” (Satya Prakash Saraswat, Computing Reviews, February, 2016)Table of Contents1 Introduction.- 2 Modeling in Business Intelligence.- 3 Data Provisioning.- 4 Data Description and Visualization.- 5 Data Mining for Cross-Sectional Data.- 6 Data Mining for Temporal Data.- 7 Process Analysis.- 8 Analysis of Multiple Business Perspectives.- 9 Summary.- A Survey on Business Intelligence Tools.

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Book SynopsisThe LNCS journal Transactions on Large-scale Data and Knowledge-centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. This, the 54th issue of Transactions on Large-Scale Data and Knowledge-Centered Systems, contains three fully revised and extended papers and two additional extended keynotes selected from the 38th conference on Data Management - Principles, Technologies and Applications, BDA 2022. The topics cover a wide range of timely data management research topics on temporal graph management, tensor-based data mining, time-series prediction, healthcare analytics over knowledge graphs, and explanation of database query answers.Table of ContentsClock-G: Temporal graph management system.- TSPredIT: Integrated tuning of data preprocessing and time series prediction models.- A guide to the Tucker tensor decomposition for data mining: exploratory analysis, clustering and classification.- Challenges for Healthcare Data Analytics over Knowledge Graphs.- From Database Repairs to Causality in Databases and Beyond.

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Book SynopsisAnwendungssoftware soll zur Optimierung von Geschäftsprozessen beitragen. Vor diesem Hintergrund werden in diesem Lehrbuch anhand eines durchgängigen Fallbeispiels Geschäftsprozesse mit UML modelliert und die fachlichen Anforderungen an das Software-System systematisch abgeleitet. Aufgrund nachvollziehbarer Regeln und Prinzipien werden Klassenmodelle konstruiert. Alternative System-Architekturen werden vorgestellt und erläutert. Es werden Entwurfsmuster anhand anschaulicher Beispiele präsentiert und die Umsetzung des Fallbeispiels in Java anhand von annotiertem Code gezeigt.Table of ContentsObjektorientierte Software-Entwicklung - Geschäftsprozessmodellierung und Anforderungsanalyse - Analyse und Entwurf in der Spezifikationsphase - Gestaltung der Mensch-Computer-Interaktion - CASE und MDA - Entwurf der Systemarchitektur - Ausgewählte Entwurfsmuster mit Beispielen - Anwendungsbeispiel

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Book Synopsis

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Book SynopsisComputational Creativity, Concept Invention, and General Intelligence in their own right all are flourishing research disciplines producing surprising and captivating results that continuously influence and change our view on where the limits of intelligent machines lie, each day pushing the boundaries a bit further. By 2014, all three fields also have left their marks on everyday life – machine-composed music has been performed in concert halls, automated theorem provers are accepted tools in enterprises’ R&D departments, and cognitive architectures are being integrated in pilot assistance systems for next generation airplanes. Still, although the corresponding aims and goals are clearly similar (as are the common methods and approaches), the developments in each of these areas have happened mostly individually within the respective community and without closer relationships to the goings-on in the other two disciplines. In order to overcome this gap and to provide a common platform for interaction and exchange between the different directions, the International Workshops on “Computational Creativity, Concept Invention, and General Intelligence” (C3GI) have been started. At ECAI-2012 and IJCAI-2013, the first and second edition of C3GI each gathered researchers from all three fields, presenting recent developments and results from their research and in dialogue and joint debates bridging the disciplinary boundaries. The chapters contained in this book are based on expanded versions of accepted contributions to the workshops and additional selected contributions by renowned researchers in the relevant fields. Individually, they give an account of the state-of-the-art in their respective area, discussing both, theoretical approaches as well as implemented systems. When taken together and looked at from an integrative perspective, the book in its totality offers a starting point for a (re)integration of Computational Creativity, Concept Invention, and General Intelligence, making visible common lines of work and theoretical underpinnings, and pointing at chances and opportunities arising from the interplay of the three fields.Table of ContentsStakeholder Groups in Computational Creativity Research and Practice.- Weak and Strong Computational Creativity.- Theorem: General intelligence entails creativity, assuming.- The Computational Creativity Complex.- How Models of Creativity and Analogy Need to Answer the Tailorability Concern.- On the role of computers in creativity-support systems.- A computational theory of creativity as everyday reasoning from learned information.- Accounting for creativity within a psychologically realistic cognitive architecture.- E pluribus unum - Formalisation, Use-Cases, and Computational Support for Conceptual Blending.- Creating Meaningful and Poetic Instances of Rhetorical Forms.- Open-Ended Elaborations in Creative Metaphor.- Poetry generation with PoeTryMe.- From MEXICA to MEXICA-impro: the Evolution of a Computer Model for Plot Generation.- Handle: Engineering Artificial Musical Creativity at the "Trickery" Level.- A Culinary Computational Creativity System.- Interactive Meta-Reasoning: Toward a CAD-like environment for designing game-playing agents.- Collective Discovery Events: Web-based Mathematical Problem-solving with Codelets.- A Personal Perspective Into the Future for Computational Creativity.

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Book SynopsisDeep reinforcement learning (DRL) is the combination of reinforcement learning (RL) and deep learning. It has been able to solve a wide range of complex decision-making tasks that were previously out of reach for a machine, and famously contributed to the success of AlphaGo. Furthermore, it opens up numerous new applications in domains such as healthcare, robotics, smart grids and finance. Divided into three main parts, this book provides a comprehensive and self-contained introduction to DRL. The first part introduces the foundations of deep learning, reinforcement learning (RL) and widely used deep RL methods and discusses their implementation. The second part covers selected DRL research topics, which are useful for those wanting to specialize in DRL research. To help readers gain a deep understanding of DRL and quickly apply the techniques in practice, the third part presents mass applications, such as the intelligent transportation system and learning to run, with detailed explanations. The book is intended for computer science students, both undergraduate and postgraduate, who would like to learn DRL from scratch, practice its implementation, and explore the research topics. It also appeals to engineers and practitioners who do not have strong machine learning background, but want to quickly understand how DRL works and use the techniques in their applications.Table of Contents

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Book SynopsisWith the proliferation of GPS devices in daily life, trajectory data that records where and when people move is now readily available on a large scale. As one of the most typical representatives, it has now become widely recognized that taxi trajectory data provides rich opportunities to enable promising smart urban services. Yet, a considerable gap still exists between the raw data available, and the extraction of actionable intelligence. This gap poses fundamental challenges on how we can achieve such intelligence. These challenges include inaccuracy issues, large data volumes to process, and sparse GPS data, to name but a few. Moreover, the movements of taxis and the leaving trajectory data are the result of a complex interplay between several parties, including drivers, passengers, travellers, urban planners, etc. In this book, we present our latest findings on mining taxi GPS trajectory data to enable a number of smart urban services, and to bring us one step closer to the vision of smart mobility. Firstly, we focus on some fundamental issues in trajectory data mining and analytics, including data map-matching, data compression, and data protection. Secondly, driven by the real needs and the most common concerns of each party involved, we formulate each problem mathematically and propose novel data mining or machine learning methods to solve it. Extensive evaluations with real-world datasets are also provided, to demonstrate the effectiveness and efficiency of using trajectory data. Unlike other books, which deal with people and goods transportation separately, this book also extends smart urban services to goods transportation by introducing the idea of crowdshipping, i.e., recruiting taxis to make package deliveries on the basis of real-time information. Since people and goods are two essential components of smart cities, we feel this extension is bot logical and essential. Lastly, we discuss the most important scientific problems and open issues in mining GPS trajectory data.Table of Contents1. Trajectory data map-matching 1.1 Introduction 1.2 Definitions and problem formulation 1.3 SD-Matching algorithm 1.4 Evaluations 1.5 Conclusions and discussions 2. Trajectory data compression 2.1 Introduction 2.2 Basic concepts and system overview 2.3 HCC algorithm 2.4 System implementation 2.5 Evaluations 2.6 Conclusions 3. Trajectory data protection 3.1 Introduction 3.2 Preliminary 3.3 Trajectory protection mechanism 3.4 Performance evaluations 3.5 Conclusions Part II: Enabling Smart Urban Services: Travellers 4. TripPlanner: Personalized trip planning leveraging heterogeneous trajectory data 4.1 Introduction 4.2 TripPlanner System 4.3 Dynamic network modelling 4.4 The two-phase approach 4.5 System evaluations 4.6 Conclusions and future work 5. ScenicPlanner: Recommending the most beautiful driving routes 5.1 Introduction 5.2 Preliminary 5.3 The two-phase approach 5.4 Experimental evaluations 5.5 Conclusion and future work Part III: Enabling Smart Urban Services: Drivers 6. GreenPlanner: Planning fuel-efficient driving routes 6.1 Introduction 6.2 Basic concepts and problem formulation 6.3 Personal fuel consumption model building 6.4 Fuel-efficient driving route planning 6.5 Evaluations 6.6 Conclusions and future work 7. Hunting or waiting: Earning more by understanding taxi service strategies 7.1 Introduction 7.2 Empirical study 7.3 Taxi strategy formulation 7.4 Understanding taxi service strategies 7.5 Conclusions Part IV: Enabling Smart Urban Services: Passengers 8. iBOAT: Real-time detection of anomalous taxi trajectories from GPS traces 8.1 Introduction 8.2 Preliminaries and problem definition 8.3 Isolation-based online anomalous trajectory detection 8.4 Empirical evaluations 8.5 Fraud behaviour analysis 8.6 Conclusions and future work 9. Real-Time imputing trip purpose leveraging heterogeneous trajectory data 9.1 Introduction 9.2 Basic concepts and problem statement 9.3 Imputing trip purposes 9.4 Enabling real-time response 9.5 Evaluations 9.6 Conclusions and future work Part V: Enabling Smart Urban Services: Urban Planners 10. GPS environment friendliness estimation with trajectory data 10.1 Introduction 10.2 Basic concepts 10.3 Methodology 10.4 Experiments 10.5 Limitations and future work 10.6 Conclusions 11. B-Planner: Planning night bus routes using taxi trajectory data 11.1 Introduction 11.2 Candidate bus stop identification 11.3 Bus route selection 11.4 Experimental evaluations 11.5 Conclusions and future work 12. VizTripPurpose: Understanding city-wide passengers’ travel behaviours 12.1 Introduction 12.2 System overview 12.3 Trip2Vec model 12.4 User interfaces 12.5 Case studies 12.6 Conclusions and future work Part VI: Enabling Smart Urban Services: Beyond People Transportation 13. CrowdDeliver: Arriving as soon as possible 13.1 Introduction 13.2 Basic concepts, assumptions and problem statement 13.3 Overview of CrowdDeliver 13.4 Two-phase approach 13.5 Evaluations 13.6 Conclusions and future work 14. CrowdExpress: Arriving by the user-specified deadline 14.1 Introduction 14.2 Preliminary, problem statement and system overview 14.3 Offline package transport network building 14.4 Online taxi scheduling and package routing 14.5 Experimental evaluations 14.6 Conclusions and future work Part VII: Open Issues and Conclusions 15. Open Issues 16. Conclusions

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Book SynopsisThis two volume set (CCIS 1451 and 1452) constitutes the refereed proceedings of the 7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021 held in Taiyuan, China, in September 2021.The 81 papers presented in these two volumes were carefully reviewed and selected from 256 submissions. The papers are organized in topical sections on big data management and applications; social media and recommendation systems; infrastructure for data science; basic theory and techniques for data science; machine learning for data science; multimedia data management and analysis; ​social media and recommendation systems; data security and privacy; applications of data science; education research, methods and materials for data science and engineering; research demo.Table of ContentsBig Data Management and Applications.- Social Media and Recommendation Systems.- Infrastructure for Data Science.- Basic Theory and Techniques for Data Science.- Machine Learning for Data Science.- Multimedia Data Management and Analysis.

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Book SynopsisThis two volume set (CCIS 1451 and 1452) constitutes the refereed proceedings of the 7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021 held in Taiyuan, China, in September 2021.The 81 papers presented in these two volumes were carefully reviewed and selected from 256 submissions. The papers are organized in topical sections on big data management and applications; social media and recommendation systems; infrastructure for data science; basic theory and techniques for data science; machine learning for data science; multimedia data management and analysis; ​social media and recommendation systems; data security and privacy; applications of data science; education research, methods and materials for data science and engineering; research demo.Table of ContentsSocial Media and Recommendation Systems.- Data Security and Privacy.- Applications of Data Science.- Education research, methods and materials for data science and engineering.- Research demo.

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Book SynopsisThis book provides a comprehensive overview of network behavior analysis that mines Internet traffic data in order to extract, model, and make sense of behavioral patterns in Internet “objects” such as end hosts, smartphones, Internet of things, and applications. The objective of this book is to fill the book publication gap in network behavior analysis, which has recently become an increasingly important component of comprehensive network security solutions for data center networks, backbone networks, enterprise networks, and edge networks.The book presents fundamental principles and best practices for measuring, extracting, modeling and analyzing network behavior for end hosts and applications on the basis of Internet traffic data. In addition, it explains the concept and key elements (e.g., what, who, where, when, and why) of communication patterns and network behavior of end hosts and network applications, drawing on data mining, machine learning, information theory, probabilistic graphical and structural modeling to do so. The book also discusses the benefits of network behavior analysis for applications in cybersecurity monitoring, Internet traffic profiling, anomaly traffic detection, and emerging application detections.The book will be of particular interest to researchers and practitioners in the fields of Internet measurement, traffic analysis, and cybersecurity, since it provides a spectrum of innovative techniques for summarizing behavior models, structural models, and graphic models of Internet traffic, and explains how to leverage the results for a broad range of real-world applications in network management, security operations, and cyber-intelligent analysis. After finishing this book, readers will 1) have learned the principles and practices of measuring, modeling, and analyzing network behavior on the basis of massive Internet traffic data; 2) be able to make sense of network behavior for a spectrum of applications ranging from cybersecurity and network monitoring to emerging application detection; and 3) understand how to explore network behavior analysis to complement traditional perimeter-based firewall and intrusion detection systems in order to detect unusual traffic patterns or zero-day security threats using data mining and machine learning techniques. To ideally benefit from this book, readers should have a basic grasp of TCP/IP protocols, data packets, network flows, and Internet applications.Table of ContentsChapter 1: Introduction.- Chapter 2: Background of Network Behavior Modeling and Analysis.- Chapter 3: Behavior Modeling of Network Traffic.- Chapter 4: Structural Modeling of Network Traffic.- Chapter 5: Graphic Modeling of Network Traffic.- Chapter 6: Real-Time Network Behavior Analysis.- Chapter 7: Applications.- Chapter 8: Research Frontiers of Network Behavior Analysis.

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Book SynopsisThis book presents high-quality research papers presented at 2nd International Conference on Smart Data Intelligence (ICSMDI 2022) organized by Kongunadu College of Engineering and Technology at Trichy, Tamil Nadu, India, during April 2022. This book brings out the new advances and research results in the fields of algorithmic design, data analysis, and implementation on various real-time applications. It discusses many emerging related fields like big data, data science, artificial intelligence, machine learning, and deep learning which have deployed a paradigm shift in various data-driven approaches that tends to evolve new data-driven research opportunities in various influential domains like social networks, healthcare, information, and communication applications.Table of ContentsDetection and Analysis of Sentiments on Twitter Using Machine Learning Algorithm.- Malware Attack Detection on IoT Devices Using Machine Learning.- BeSafe: IoT Based Safety Band.- Stock Market Analysis and forecasting with Statistical and Deep Learning Methods.- The paradigm shift in Higher Education from traditional learning to digitalisation.- Designing a socially intelligent system by cognitive modeling of human-environment interaction.- Web-Based recycle Waste Management for Ecommerce.

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Book SynopsisThis book gathers outstanding papers presented at the International Conference on Data Science and Applications (ICDSA 2022), organized by Soft Computing Research Society (SCRS) and Jadavpur University, Kolkata, India, from 26 to 27 March 2022. It covers theoretical and empirical developments in various areas of big data analytics, big data technologies, decision tree learning, wireless communication, wireless sensor networking, bioinformatics and systems, artificial neural networks, deep learning, genetic algorithms, data mining, fuzzy logic, optimization algorithms, image processing, computational intelligence in civil engineering, and creative computing.Table of ContentsCancer Prognosis by Using Machine Learning and Data Science: A systematic review.- Understanding Agriculture Scenario of Punjab: A Qualitative Research of Crop parameter in relation to fertilizer usage.- Face Detection Based Border Security System Using Haar-Cascade and LBPH Algorithm.- Proposed Experimental Design of a Portable COVID-19 Screening Device Using Cough Audio Samples.- Big Data Framework for Analytics Business Intelligence.- Technological Impacts of AI on Hospitality and Tourism Industry.- Improvement of Real-Time Kinematic Positioning Using Kalman Filter-Based Singular Spectrum Analysis during Geomagnetic Storm for Thailand sector.

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Book SynopsisThis two-volume set (CCIS 1879 and 1880) constitutes the refereed proceedings of the 9th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2023 held in Harbin, China, during September 22–24, 2023. The 52 full papers and 14 short papers presented in these two volumes were carefully reviewed and selected from 244 submissions. The papers are organized in the following topical sections:Part I: Applications of Data Science, Big Data Management and Applications, Big Data Mining and Knowledge Management, Data Visualization, Data-driven Security, Infrastructure for Data Science, Machine Learning for Data Science and Multimedia Data Management and Analysis.Part II: Data-driven Healthcare, Data-driven Smart City/Planet, Social Media and Recommendation Systems and Education using big data, intelligent computing or data mining, etc.Table of Contents​Applications of Data Science.- Construction of Software Design and Programming Practice Course in Information and Communication Engineering.- A Self-Attention-Based Stock Prediction Method Using Long Short-Term Memory Network Architecture.- CAD-based Research on the Design of a Standard Unit Cabinet for Custom Furniture of the Cabinet Type.- An Improved War Strategy Optimization Algorithm for Big Data Analytics.- Research on Path Planning of Mobile Robots Based on Dyna-RQ.- Small Target Helmet Wearing Detection Algorithm based on Improved YOLO V5.- Research on Dance Evaluation Technology based on Human Posture Recognition.- Multiple-channel Weight-based CNN Fault Diagnosis Method.- Big Data Management and Applications.- Design and Implementation of Key-Value Database for Ship Virtual Test Platform Based on Distributed System.- Big Data Mining and Knowledge Management.- Research on Multi-modal Time Series Data Prediction Method Based on Dualstage Attention Mechanism.- Prediction of Time Series Data with Low Latitude Features.- Lightweight and Efficient Attention-based Superresolution Generative Adversarial Networks.- The Multisource Time Series Data Granularity Conversion Method.- Outlier Detection Model Based on Autoencoder and Data Augmentation for High-Dimensional Sparse Data.- Dimension Reduction Based on Sampling.- Complex Time Series Analysis Based on Conditional Random Fields.- Feature Extraction of Time Series Data Based on CNNCBAM.- Optimization of a Network Topology Generation Algorithm based on Spatial Information Network.- Data Visualization.- MBTIviz: A Visualization System for Research on Psycho-demographics and Personality.- Data-driven Security.- Distributed Implementation of SM4 Block Cipher Algorithm based on SPDZ Secure Multi-party Computation Protocol.- DP-ASSGD: Differential Privacy Protection Based on Stochastic Gradient Descent Optimization.- Study on Tourism Workers ’ Intercultural Communication Competence.- A Novel Federated Learning with Bidirectional Adaptive Differential Privacy.- Chaos-Based Construction of LWEs in Lattice-Based Cryptosystems.- Security Compressed Sensing Image Encryption Algorithm Based on Elliptic Curve.- Infrastructure for Data Science.- Two-dimensional Code Transmission System Based on Side Channel Feedback.- An Updatable and Revocable Decentralized Identity Management Scheme based on Blockchain.- Cloud-Edge Intelligent Collaborative Computing Model based on Transfer Learning in IoT.- Design and Validation of a Hardware-in-the-loop based Automated Driving Simulation Test Platform.- Machine Learning for Data Science.- Improving Transferability Reversible Adversarial Examples based on Flipping Transformation.- Rolling Iterative Prediction for Correlated Multivariate Time Series.- Multimedia Data Management and Analysis.- Video Popularity Prediction Based on Knowledge Graph and LSTM Network.- Design and Implementation of Speech Generation and Demonstration Research Based on Deep Learning.- Testing and Improvement of OCR Recognition Technology in Export-OrientedChinese Dictionary APP.

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Book SynopsisExplore the role ChatGPT can play in business, including operations, marketing, sales, and delivery. This concise book illustrates how ChatGPT is changing the way individuals interact with machines and how you can take advantage of its capabilities for business. The book starts with an overview of ChatGPT and its impact in the realm of of conversational AI. You will then dive into the technical aspects of ChatGPT and gain an understanding of how machine learning algorithms and natural language processing work in the background. Various business applications of ChatGPT are then discussed, followed by how it can get integrated into your business operations. To wrap things up, you will gain insight into the data and privacy elements that need to be considered while using ChatGPT, and how to maintain its integrity. After completing this book, you will understand the ChatGPT framework and how to integrate it into your own ventures. What You Will Learn Understand the various technologies and techniques utilized in ChatGPT Gain insight into the future of human-machine interaction Analyze the advantages and disadvantages of ChatGPT for your industry Explore the ethical implications of using AI Who This Book Is For Tech enthusiasts who are passionate about artificial intelligence (AI), machine learning, and human-machine interaction.Table of ContentsChapter 1: Introduction to ChatGPT.- Chapter 2: Understand ChatGPT’s Underlying Technology. - Chapter 3: Real World Applications for ChatGPT.- Chapter 4: Enhancing Business Communication with ChatGPT.- Chapter 5: Implementing AI Conversation in Business.- Chapter 6: Security and Ethical Considerations When Using ChatGPT.

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