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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 : revised selected and invited papers / Bettina Berendt [and others] (eds.).

By: Contributor(s): Material type: TextTextSeries: LNCS sublibrary. SL 7, Artificial intelligence. | Lecture notes in computer science ; 4737. | Lecture notes in computer science. Lecture notes in artificial intelligence.Publication details: Berlin ; New York : Springer, ©2007.Description: 1 online resource (vii, [4], 160 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540749509
  • 3540749500
  • 9783540749516
  • 3540749519
  • 6611354085
  • 9786611354084
Other title:
  • Workshop on Web Mining
  • WebMine 2006
Subject(s): Genre/Form: Additional physical formats: Print version:: From Web to social Web.DDC classification:
  • 006.3 22
LOC classification:
  • ZA4235 .W67 2006
Other classification:
  • TP393. 4-532
Online resources:
Contents:
An Analysis of Bloggers, Topics and Tags for a Blog Recommender System -- Combining Web Usage Mining and XML Mining in a Real Case Study -- Extracting and Using Attribute-Value Pairs from Product Descriptions on the Web -- Discovering User Profiles from Semantically Indexed Scientific Papers -- Web Usage Mining in Noisy and Ambiguous Environments: Exploring the Role of Concept Hierarchies, Compression, and Robust User Profiles -- From World-Wide-Web Mining to Worldwide Webmining: Understanding People's Diversity for Effective Knowledge Discovery -- Aspect-Based Tagging for Collaborative Media Organization -- Contextual Recommendation.
In: Springer e-booksSummary: 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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"Web Mining (WebMine) 2006 was organized as part of the 17th European Conference on Machine Learning (ECML) and the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD)"--Page x

Includes bibliographical references and index.

An Analysis of Bloggers, Topics and Tags for a Blog Recommender System -- Combining Web Usage Mining and XML Mining in a Real Case Study -- Extracting and Using Attribute-Value Pairs from Product Descriptions on the Web -- Discovering User Profiles from Semantically Indexed Scientific Papers -- Web Usage Mining in Noisy and Ambiguous Environments: Exploring the Role of Concept Hierarchies, Compression, and Robust User Profiles -- From World-Wide-Web Mining to Worldwide Webmining: Understanding People's Diversity for Effective Knowledge Discovery -- Aspect-Based Tagging for Collaborative Media Organization -- Contextual Recommendation.

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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