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» Acquiring Explicit User Goals from Search Query Logs
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SIGIR
2008
ACM
13 years 5 months ago
To personalize or not to personalize: modeling queries with variation in user intent
In most previous work on personalized search algorithms, the results for all queries are personalized in the same manner. However, as we show in this paper, there is a lot of vari...
Jaime Teevan, Susan T. Dumais, Daniel J. Liebling
KDD
2009
ACM
248views Data Mining» more  KDD 2009»
13 years 9 months ago
PSkip: estimating relevance ranking quality from web search clickthrough data
1 In this article, we report our efforts in mining the information encoded as clickthrough data in the server logs to evaluate and monitor the relevance ranking quality of a commer...
Kuansan Wang, Toby Walker, Zijian Zheng
DAGSTUHL
2007
13 years 6 months ago
Exploiting Community Behavior for Enhanced Link Analysis and Web Search
Methods for Web link analysis and authority ranking such as PageRank are based on the assumption that a user endorses a Web page when creating a hyperlink to this page. There is a...
Julia Luxenburger, Gerhard Weikum
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
14 years 5 months ago
Query chains: learning to rank from implicit feedback
This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform ...
Filip Radlinski, Thorsten Joachims
WWW
2006
ACM
14 years 5 months ago
Time-dependent semantic similarity measure of queries using historical click-through data
It has become a promising direction to measure similarity of Web search queries by mining the increasing amount of clickthrough data logged by Web search engines, which record the...
Qiankun Zhao, Steven C. H. Hoi, Tie-Yan Liu, Soura...