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» Smoothing clickthrough data for web search ranking
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SIGIR
2010
ACM
15 years 1 months ago
Comparing click-through data to purchase decisions for retrieval evaluation
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 ...
MM
2006
ACM
164views Multimedia» more  MM 2006»
15 years 3 months ago
Scalable relevance feedback using click-through data for web image retrieval
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...
En Cheng, Feng Jing, Lei Zhang, Hai Jin
WWW
2006
ACM
15 years 10 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...
108
Voted
WSDM
2012
ACM
285views Data Mining» more  WSDM 2012»
13 years 5 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...
KDD
2006
ACM
198views Data Mining» more  KDD 2006»
15 years 10 months ago
Event detection from evolution of click-through data
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...