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Web Usage Mining

  • Bing LiuEmail author
  • Bamshad Mobasher
  • Olfa Nasraoui
Chapter
Part of the Data-Centric Systems and Applications book series (DCSA)

Abstract

With the continued growth and proliferation of e-commerce, Web services, and Web-based information systems, the volumes of clickstream, transaction data, and user profile data collected by Web-based organizations in their daily operations has reached astronomical proportions. Analyzing such data can help these organizations determine the life-time value of clients, design cross-marketing strategies across products and services, evaluate the effectiveness of promotional campaigns, optimize the functionality of Web-based applications, provide more personalized content to visitors, and find the most effective logical structure for their Web space. This type of analysis involves the automatic discovery of meaningful patterns and relationships from a large collection of primarily semi-structured data, often stored in Web and applications server access logs, as well as in related operational data sources.

Keywords

Singular Value Decomposition Association Rule Recommender System Query Expansion Collaborative Filter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of Illinois, ChicagoChicagoUSA

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