Semantics, Web and Mining

1. Front Matter

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2. EWMF Papers

   1. A Website Mining Model Centered on User Queries

      • Ricardo Baeza-Yates, Barbara Poblete

      Pages 1-17

   2. WordNet-Based Word Sense Disambiguation for Learning User Profiles

      • M. Degemmis, P. Lops, G. Semeraro

      Pages 18-33

   3. Visibility Analysis on the Web Using Co-visibilities and Semantic Networks

      • Peter Kiefer, Klaus Stein, Christoph Schlieder

      Pages 34-50

   4. Link-Local Features for Hypertext Classification

      • Hervé Utard, Johannes Fürnkranz

      Pages 51-64

   5. Information Retrieval in Trust-Enhanced Document Networks

      • Klaus Stein, Claudia Hess

      Pages 65-81

   6. Semi-automatic Creation and Maintenance of Web Resources with webTopic

      • Nuno F. Escudeiro, Alípio M. Jorge

      Pages 82-102

3. KDO Papers on KDD for Ontology

   1. Discovering a Term Taxonomy from Term Similarities Using Principal Component Analysis

      • Holger Bast, Georges Dupret, Debapriyo Majumdar, Benjamin Piwowarski

      Pages 103-120

   2. Semi-automatic Construction of Topic Ontologies

      • Blaž Fortuna, Dunja Mladenič, Marko Grobelnik

      Pages 121-131

   3. Evaluation of Ontology Enhancement Tools

      • Myra Spiliopoulou, Markus Schaal, Roland M. Müller, Marko Brunzel

      Pages 132-146

4. KDO Papers on Ontology for KDD

   1. Introducing Semantics in Web Personalization: The Role of Ontologies

      • Magdalini Eirinaki, Dimitrios Mavroeidis, George Tsatsaronis, Michalis Vazirgiannis

      Pages 147-162

   2. Ontology-Enhanced Association Mining

      • Vojtěch Svátek, Jan Rauch, Martin Ralbovský

      Pages 163-179

   3. Ontology-Based Rummaging Mechanisms for the Interpretation of Web Usage Patterns

      • Mariângela Vanzin, Karin Becker

      Pages 180-195

5. Back Matter

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Finding knowledge – or meaning – in data is the goal of every knowledge d- covery e?ort. Subsequent goals and questions regarding this knowledge di?er amongknowledgediscovery(KD) projectsandapproaches. Onecentralquestion is whether and to what extent the meaning extracted from the data is expressed in a formal way that allows not only humans but also machines to understand and re-use it, i. e. , whether the semantics are formal semantics. Conversely, the input to KD processes di?ers between KD projects and approaches. One central questioniswhetherthebackgroundknowledge,businessunderstanding,etc. that the analyst employs to improve the results of KD is a set of natural-language statements, a theory in a formal language, or somewhere in between. Also, the data that are being mined can be more or less structured and/or accompanied by formal semantics. These questions must be asked in every KD e?ort. Nowhere may they be more pertinent, however, than in KD from Web data (“Web mining”). Thisis due especially to the vast amounts and heterogeneity of data and ba- ground knowledge available for Web mining (content, link structure, and - age), and to the re-use of background knowledge and KD results over the Web as a global knowledge repository and activity space. In addition, the (Sem- tic) Web can serve as a publishing space for the results of knowledge discovery from other resources, especially if the whole process is underpinned by common ontologies.

• association rule mining
• classification
• data mining
• hyperlink mining
• knowledge discovery
• navigation analysis
• ontologies
• pattern mining
• recommender systems
• semantic Web
• semantic Web mining
• taxonomic context
• usage analysis
• usage pattern discover

• Department of Natural Language Processing, Institute for Computer Science, University of Leipzig,  

  Markus Ackermann

• Department of Computer Science, K.U. Leuven, Heverlee, Belgium

  Bettina Berendt

• Dept. of Knowledge Technologies, Jozef Stefan Institute, Ljubljana, Slovenia

  Marko Grobelnik

• Knowledge & Data Engineering Group, University of Kassel, Kassel, Germany

  Andreas Hotho

• Jožef Stefan Institute, Ljubljana, Slovenia

  Dunja Mladenič

• Dipartimento di Informatica, Università di Bari, Bari

  Giovanni Semeraro

• Faculty of Computer Science, Otto-von-Guericke-University Magdeburg, Germany

  Myra Spiliopoulou

• Research Center L3S, Hannover, Germany

  Gerd Stumme

• Dept. Information and Knowledge Engineering, University of Economics, Prague, Prague, Czech Republic

  Vojtěch Svátek

• Human Computer Studies Lab, University of Amsterdam, Amsterdam, The Netherlands

  Maarten Someren

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