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Web Usage Mining
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Author(s): Bamshad Mobasher (DePaul University, USA)
Copyright: 2005
Pages: 5
Source title:
Encyclopedia of Data Warehousing and Mining
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-59140-557-3.ch229
PurchaseView Web Usage Mining on the publisher's website for pricing and purchasing information. |
Abstract
With the continued growth and proliferation of e-commerce, Web services, and Web-based information systems, the volumes of clickstream and user data collected by Web-based organizations in their daily operations have reached astronomical proportions. Analyzing such data can help these organizations determine the lifetime 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.
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