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Knowledge Discovery Enhanced with Semantic and Social Information

  • Book
  • © 2009

Overview

Editors:
  1. Bettina Berendt

    1. Department of Computer Science, Katholieke Universiteit Leuven, Heverlee, Belgium

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  2. Dunja Mladenič

    1. J. Stefan Institute, Ljubljana, Slovenia

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  3. Marco Gemmis

    1. Dipartimento di Informatica, Università degli Studi “Aldo Moro”, Bari, Italy

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  4. Giovanni Semeraro

    1. Dipartimento di Informatica, Università degli Studi “Aldo Moro”, Bari, Italy

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  5. Myra Spiliopoulou

    1. ITI/FIN, Faculty of Computer Science, Otto-von-Guericke-Universitaet Magdeburg, Magdeburg, Germany

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  6. Gerd Stumme

    1. Fachgebiet Wissensverarbeitung, Universität Kassel, Kassel, Germany

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  7. Vojtěch Svátek

    1. University of Economics, Prague, Praha 3, Czech Republic

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  8. Filip Železný

    1. Faculty of Electrical Engineering, Department of Cybernetics, Czech Technical University, Prague 6, Czech Republic

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  • Presents latest results on knowledge discovery enhanced with semantic and social information

Part of the book series: Studies in Computational Intelligence (SCI, volume 220)

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Table of contents (8 chapters)

  1. Front Matter

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  2. Prior Conceptual Knowledge in Machine Learning and Knowledge Discovery

    1. Front Matter

      Pages 1-1
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    2. On Ontologies as Prior Conceptual Knowledge in Inductive Logic Programming

      • Francesca A. Lisi, Floriana Esposito
      Pages 3-17

    3. A Knowledge-Intensive Approach for Semi-automatic Causal Subgroup Discovery

      • Martin Atzmueller, Frank Puppe
      Pages 19-36

    4. A Study of the SEMINTEC Approach to Frequent Pattern Mining

      • Joanna Józefowska, Agnieszka Ławrynowicz, Tomasz Łukaszewski
      Pages 37-51

    5. Partitional Conceptual Clustering of Web Resources Annotated with Ontology Languages

      • Floriana Esposito, Nicola Fanizzi, Claudia d’Amato
      Pages 53-70

    6. The Ex Project: Web Information Extraction Using Extraction Ontologies

      • Martin Labský, Vojtěch Svátek, Marek Nekvasil, Dušan Rak
      Pages 71-88

    7. Dealing with Background Knowledge in the SEWEBAR Project

      • Jan Rauch, Milan Šimůnek
      Pages 89-106

  3. Web Mining 2.0

    1. Front Matter

      Pages 107-107
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    2. Item Weighting Techniques for Collaborative Filtering

      • Linas Baltrunas, Francesco Ricci
      Pages 109-126

    3. Using Term-Matching Algorithms for the Annotation of Geo-services

      • Miha Grčar, Eva Klien, Blaž Novak
      Pages 127-143

  4. Back Matter

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Keywords

About this book

This book is a showcase of recent advances in knowledge discovery enhanced with semantic and social information. It includes eight contributed chapters that grew out of two joint workshops at ECML/PKDD 2007.
There is general agreement that the effectiveness of Machine Learning and Knowledge Discovery output strongly depends not only on the quality of source data and the sophistication of learning algorithms, but also on additional input provided by domain experts. There is less agreement on whether, when and how such input can and should be formalized as explicit prior knowledge.
The six chapters in the first part of the book aim to investigate this aspect by addressing four different topics: inductive logic programming; the role of human users; investigations of fully automated methods for integrating background knowledge; the use of background knowledge for Web mining. The two chapters in the second part are motivated by the Web 2.0 (r)evolution and the increasingly strong role of user-generated content. The contributions emphasize the vision of the Web as a social medium for content and knowledge sharing.

Editors and Affiliations

  • Department of Computer Science, Katholieke Universiteit Leuven, Heverlee, Belgium

    Bettina Berendt

  • J. Stefan Institute, Ljubljana, Slovenia

    Dunja Mladenič

  • Dipartimento di Informatica, Università degli Studi “Aldo Moro”, Bari, Italy

    Marco Gemmis, Giovanni Semeraro

  • ITI/FIN, Faculty of Computer Science, Otto-von-Guericke-Universitaet Magdeburg, Magdeburg, Germany

    Myra Spiliopoulou

  • Fachgebiet Wissensverarbeitung, Universität Kassel, Kassel, Germany

    Gerd Stumme

  • University of Economics, Prague, Praha 3, Czech Republic

    Vojtěch Svátek

  • Faculty of Electrical Engineering, Department of Cybernetics, Czech Technical University, Prague 6, Czech Republic

    Filip Železný

Bibliographic Information

  • Book Title: Knowledge Discovery Enhanced with Semantic and Social Information

  • Editors: Bettina Berendt, Dunja Mladenič, Marco Gemmis, Giovanni Semeraro, Myra Spiliopoulou, Gerd Stumme, Vojtěch Svátek, … Filip Železný

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-642-01891-6

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2009

  • Hardcover ISBN: 978-3-642-01890-9Published: 29 June 2009

  • Softcover ISBN: 978-3-642-42609-4Published: 06 November 2014

  • eBook ISBN: 978-3-642-01891-6Published: 09 July 2009

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: X, 143

  • Topics: Computational Intelligence, Artificial Intelligence, Semantics

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