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Grammar-based task analysis of web logs
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Source Conference on Information and Knowledge Management archive
Proceedings of the thirteenth ACM international conference on Information and knowledge management table of contents
Washington, D.C., USA
POSTER SESSION: Posters P-2 table of contents
Pages: 244 - 245  
Year of Publication: 2004
ISBN:1-58113-874-1
Authors
Savitha Srinivasan  IBM Almaden Research Center, San Jose, CA
Arnon Amir  IBM Almaden Research Center, San Jose, CA
Prasad Deshpande  IBM Almaden Research Center, San Jose, CA
Vladimir Zbarsky  IBM Almaden Research Center, San Jose, CA
Sponsors
SIGIR: ACM Special Interest Group on Information Retrieval
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

The daily use of Internet-based services is involved with hundreds of different tasks being performed by multiple users. A single task is typically involved with a sequence of Web URLs invocation. We study the problem of pattern detection in Web logs to identify tasks performed by users, and analyze task trends over time using a grammar-based framework. Our results are demonstrated on a corporate Intranet portal application with 7000 users over a 6 week period and demonstrate compelling business value from this high-level task analysis.




Collaborative Colleagues:
Savitha Srinivasan: colleagues
Arnon Amir: colleagues
Prasad Deshpande: colleagues
Vladimir Zbarsky: colleagues