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The impact of history length on personalized search
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Annual ACM Conference on Research and Development in Information Retrieval archive
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval table of contents
Singapore, Singapore
POSTER SESSION: Posters group 1: evaluation, text collections and user/personalized IR table of contents
Pages 715-716  
Year of Publication: 2008
ISBN:978-1-60558-164-4
Authors
Yangbo Zhu  Carnegie Mellon University, Pittsburgh, PA, USA
Jamie Callan  Carnegie Mellon University, Pittsburgh, PA, USA
Jaime Carbonell  Carnegie Mellon University, Pittsburgh, PA, USA
Sponsors
ACM: Association for Computing Machinery
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
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ABSTRACT

Personalized search is a promising way to better serve different users' information needs. Search history is one of the major information sources for search personalization. We investigated the impact of history length on the effectiveness of personalized ranking. We carried out task-based user study for Web search, and obtained ranked relevance judgments for all queries. Query contexts derived from previous queries in the same task are used to re-rank results for the current query. Experimental results show that the performance of personalization generally improves as more queries are accumulated, but most of the benefits come from a few immediately preceding queries.



Collaborative Colleagues:
Yangbo Zhu: colleagues
Jamie Callan: colleagues
Jaime Carbonell: colleagues