Search (5 results, page 1 of 1)

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Content

Introduction.- Ontology Development.- Compliance using Metadata.- Variety Management for Big Data.- Text Mining in Economics.- Generation of Natural Language Texts.- Sentiment Analysis.- Building Concise Text Corpora from Web Contents.- Ontology-Based Modelling of Web Content.- Personalized Clinical Decision Support for Cancer Care.- Applications of Temporal Conceptual Semantic Systems.- Context-Aware Documentation in the Smart Factory.- Knowledge-Based Production Planning for Industry 4.0.- Information Exchange in Jurisdiction.- Supporting Automated License Clearing.- Managing cultural assets: Implementing typical cultural heritage archive's usage scenarios via Semantic Web technologies.- Semantic Applications for Process Management.- Domain-Specific Semantic Search Applications.

RSWK

Semantic Web

Subject

Semantic Web

Theme

Semantic Web

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Abstract

Class-tested and coherent, this textbook teaches information retrieval, including web search, text classification, and text clustering from basic concepts. Ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students. Slides and additional exercises are available for lecturers. - This book provides what Salton and Van Rijsbergen both failed to achieve. Even more important, unlike some other books in IR, the authors appear to care about making the theory as accessible as possible to the reader, on occasion including short primers to certain topics or choosing to explain difficult concepts using simplified approaches. Its coverage [is] excellent, the quality of writing high and I was surprised how much I learned from reading it. I think the online resources are impressive.

Content

Inhalt: Boolean retrieval - The term vocabulary & postings lists - Dictionaries and tolerant retrieval - Index construction - Index compression - Scoring, term weighting & the vector space model - Computing scores in a complete search system - Evaluation in information retrieval - Relevance feedback & query expansion - XML retrieval - Probabilistic information retrieval - Language models for information retrieval - Text classification & Naive Bayes - Vector space classification - Support vector machines & machine learning on documents - Flat clustering - Hierarchical clustering - Matrix decompositions & latent semantic indexing - Web search basics - Web crawling and indexes - Link analysis Vgl. die digitale Fassung unter: http://nlp.stanford.edu/IR-book/pdf/irbookprint.pdf.

LCSH

Semantic Web

RSWK

Semantic Web (BVB)
World Wide Web / Suchmaschine (HBZ)

Subject

Semantic Web (BVB)
World Wide Web / Suchmaschine (HBZ)
Semantic Web

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Content

Inhalt: 1. Einleitung (A. Dengel, A. Bernardi) 2. Wissensrepräsentation (A. Dengel, A. Bernardi, L. van Elst) 3. Semantische Netze, Thesauri und Topic Maps (O. Rostanin, G. Weber) 4. Das Ressource Description Framework (T. Roth-Berghofer) 5. Ontologien und Ontologie-Abgleich in verteilten Informationssystemen (L. van Elst) 6. Anfragesprachen und Reasoning (M. Sintek) 7. Linked Open Data, Semantic Web Datensätze (G.A. Grimnes, O. Hartig, M. Kiesel, M. Liwicki) 8. Semantik in der Informationsextraktion (B. Adrian, B. Endres-Niggemeyer) 9. Semantische Suche (K. Schumacher, B. Forcher, T. Tran) 10. Erklärungsfähigkeit semantischer Systeme (B. Forcher, T. Roth-Berghofer, S. Agne) 11. Semantische Webservices zur Steuerung von Prooduktionsprozessen (M. Loskyll, J. Schlick, S. Hodeck, L. Ollinger, C. Maxeiner) 12. Wissensarbeit am Desktop (S. Schwarz, H. Maus, M. Kiesel, L. Sauermann) 13. Semantische Suche für medizinische Bilder (MEDICO) (M. Möller, M. Sintek) 14. Semantische Musikempfehlungen (S. Baumann, A. Passant) 15. Optimierung von Instandhaltungsprozessen durch Semantische Technologien (P. Stephan, M. Loskyll, C. Stahl, J. Schlick)

RSWK

Semantic Web / Information Extraction / Suche / Wissensbasiertes System / Aufsatzsammlung
Semantic Web / Web Services / Semantische Modellierung / Ontologie <Wissensverarbeitung> / Suche / Navigieren / Anwendungsbereich / Aufsatzsammlung

Subject

Semantic Web / Information Extraction / Suche / Wissensbasiertes System / Aufsatzsammlung
Semantic Web / Web Services / Semantische Modellierung / Ontologie <Wissensverarbeitung> / Suche / Navigieren / Anwendungsbereich / Aufsatzsammlung

Theme

Semantic Web

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Abstract

For undergraduate or advanced undergraduate courses in Classical Natural Language Processing, Statistical Natural Language Processing, Speech Recognition, Computational Linguistics, and Human Language Processing. An explosion of Web-based language techniques, merging of distinct fields, availability of phone-based dialogue systems, and much more make this an exciting time in speech and language processing. The first of its kind to thoroughly cover language technology at all levels and with all modern technologies this text takes an empirical approach to the subject, based on applying statistical and other machine-learning algorithms to large corporations. The authors cover areas that traditionally are taught in different courses, to describe a unified vision of speech and language processing. Emphasis is on practical applications and scientific evaluation. An accompanying Website contains teaching materials for instructors, with pointers to language processing resources on the Web. The Second Edition offers a significant amount of new and extended material.

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Abstract

Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned. Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases. Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.