Traditional retrieval evaluation uses explicit relevance judgments which are expensive to collect. Relevance assessments inferred from implicit feedback such as click-through data...
Katja Hofmann, Bouke Huurnink, Marc Bron, Maarten ...
Relevance feedback (RF) has been extensively studied in the content-based image retrieval community. However, no commercial Web image search engines support RF because of scalabil...
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...
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...
Previous efforts on event detection from the web have focused primarily on web content and structure data ignoring the rich collection of web log data. In this paper, we propose t...
Qiankun Zhao, Tie-Yan Liu, Sourav S. Bhowmick, Wei...