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From Web to Social Web: Discovering and Deploying User and Content Profiles

Workshop on Web Mining, WebMine 2006, Berlin, Germany, September 18, 2006

  • Conference proceedings
  • © 2007

Overview

Editors:
  1. Bettina Berendt
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  2. Andreas Hotho
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  3. Dunja Mladenic
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  4. Giovanni Semeraro
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 4737)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: WebMine 2006.

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Table of contents (8 papers)

  1. Front Matter

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  2. An Analysis of Bloggers, Topics and Tags for a Blog Recommender System

    • Conor Hayes, Paolo Avesani, Uldis Bojars
    Pages 1-20

  3. Combining Web Usage Mining and XML Mining in a Real Case Study

    • Federico Michele Facca
    Pages 21-40

  4. Extracting and Using Attribute-Value Pairs from Product Descriptions on the Web

    • Katharina Probst, Rayid Ghani, Marko Krema, Andy Fano, Yan Liu
    Pages 41-60

  5. Discovering User Profiles from Semantically Indexed Scientific Papers

    • Giovanni Semeraro, Pierpaolo Basile, Marco de Gemmis, Pasquale Lops
    Pages 61-81

  6. Web Usage Mining in Noisy and Ambiguous Environments: Exploring the Role of Concept Hierarchies, Compression, and Robust User Profiles

    • Olfa Nasraoui, Esin Saka
    Pages 82-101

  7. From World-Wide-Web Mining to Worldwide Webmining: Understanding People’s Diversity for Effective Knowledge Discovery

    • Bettina Berendt, Anett Kralisch
    Pages 102-121

  8. Aspect-Based Tagging for Collaborative Media Organization

    • Oliver Flasch, Andreas Kaspari, Katharina Morik, Michael Wurst
    Pages 122-141

  9. Contextual Recommendation

    • Sarabjot Singh Anand, Bamshad Mobasher
    Pages 142-160

  10. Back Matter

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  1. From Web to Social Web: Discovering and Deploying User and Content Profiles

Keywords

About this book

The World Wide Web is a rich source of information about human behavior. It containslarge amount of data organizedvia interconnected Web pages,traces of information search, user feedback on items of interest, etc. In addition to large data volumes, one of the important characteristics of the Web is its dynamics, where content,structure and usagearechanging over time. This showsup in the rise of related research areas like communities of practice, knowledge mana- ment, Web communities, and peer-to-peer. In particular the notion of colla- rative work and thus the need of its systematic analysis become more and more important. For instance, to develop e?ective Web applications, it is essential to analyze patterns hidden in the usage of Web resources, their contents and their interconnections. Machine learning and data mining methods have been used extensively to ?nd patterns in usage of the network by exploiting both contents and link structures. We have investigated these topics in a series of workshops on Semantic Web Mining (2001, 2002) at the European Conference on Machine Learning / Pr- ciples and Practice of Knowledge Discovery from Databases (ECML/PKDD) conference series, in the selection of papers for the post-proceedings of the - ropean Web Mining Forum 2003 Workshop, published as the Springer LNAI volume 3209 “Web Mining: From Web to Semantic Web” in 2004, as well as in the Knowledge Discovery and Ontologies workshop in 2004 and in the selection ofpapersfor thepost-proceedingsofthe ECML/PKDD2005jointworkshopson Web Mining (European Web Mining Forum) and on Knowledge Discovery and

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