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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. REFERENCES
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