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» Learning Semantic Categories from Clickthrough Logs
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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
CIKM
2009
Springer
13 years 12 months ago
Exploring relevance for clicks
Mining feedback information from user click-through data is an important issue for modern Web retrieval systems in terms of architecture analysis, performance evaluation and algor...
Rongwei Cen, Yiqun Liu, Min Zhang, Bo Zhou, Liyun ...
WWW
2008
ACM
14 years 6 months ago
Using subspace analysis for event detection from web click-through data
Although most of existing research usually detects events by analyzing the content or structural information of Web documents, a recent direction is to study the usage data. In th...
Ling Chen 0002, Yiqun Hu, Wolfgang Nejdl
KDD
2002
ACM
169views Data Mining» more  KDD 2002»
14 years 5 months ago
Optimizing search engines using clickthrough data
This paper presents an approach to automatically optimizing the retrieval quality of search engines using clickthrough data. Intuitively, a good information retrieval system shoul...
Thorsten Joachims
WWW
2007
ACM
14 years 6 months ago
Acquiring ontological knowledge from query logs
We present a method for acquiring ontological knowledge using search query logs. We first use query logs to identify important contexts associated with terms belonging to a semant...
Satoshi Sekine, Hisami Suzuki