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» Aggregating User-Centered Rankings to Improve Web Search
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WSDM
2012
ACM
285views Data Mining» more  WSDM 2012»
12 years 2 months ago
Probabilistic models for personalizing web search
We present a new approach for personalizing Web search results to a specific user. Ranking functions for Web search engines are typically trained by machine learning algorithms u...
David Sontag, Kevyn Collins-Thompson, Paul N. Benn...
ICDE
2005
IEEE
127views Database» more  ICDE 2005»
14 years 11 days ago
Static and Dynamic Scoring by Web Page Grouping
Web Search System exists to retrieve necessary information on the WWW space. However, these are not accuracy enough. Then, we propose the technique for using Web Page Grouping tog...
Hitoshi Nakakubo, Takashi Sato
SIGIR
2010
ACM
13 years 10 months ago
Studying trailfinding algorithms for enhanced web search
Search engines return ranked lists of Web pages in response to queries. These pages are starting points for post-query navigation, but may be insufficient for search tasks involvi...
Adish Singla, Ryen White, Jeff Huang
SIGIR
2008
ACM
13 years 6 months ago
The impact of history length on personalized search
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. ...
Yangbo Zhu, Jamie Callan, Jaime G. Carbonell
WWW
2010
ACM
14 years 1 months ago
Sampling high-quality clicks from noisy click data
Click data captures many users’ document preferences for a query and has been shown to help significantly improve search engine ranking. However, most click data is noisy and of...
Adish Singla, Ryen W. White