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ICDM
2005
IEEE
217views Data Mining» more  ICDM 2005»
9 years 2 months ago
Improving Automatic Query Classification via Semi-Supervised Learning
Accurate topical classification of user queries allows for increased effectiveness and efficiency in general-purpose web search systems. Such classification becomes critical if th...
Steven M. Beitzel, Eric C. Jensen, Ophir Frieder, ...
CIKM
2009
Springer
9 years 3 months ago
Semi-supervised learning of semantic classes for query understanding: from the web and for the web
Understanding intents from search queries can improve a user’s search experience and boost a site’s advertising profits. Query tagging via statistical sequential labeling mode...
Ye-Yi Wang, Raphael Hoffmann, Xiao Li, Jakub Szyma...
AAAI
2008
8 years 11 months ago
Semi-Supervised Ensemble Ranking
Ranking plays a central role in many Web search and information retrieval applications. Ensemble ranking, sometimes called meta-search, aims to improve the retrieval performance b...
Steven C. H. Hoi, Rong Jin
WEBI
2005
Springer
9 years 2 months ago
A Semi-Supervised Document Clustering Algorithm Based on EM
Document clustering is a very hard task in Automatic Text Processing since it requires to extract regular patterns from a document collection without a priori knowledge on the cat...
Leonardo Rigutini, Marco Maggini
ACL
2009
8 years 7 months ago
Learning Semantic Categories from Clickthrough Logs
As the web grows larger, knowledge acquisition from the web has gained increasing attention. In this paper, we propose using web search clickthrough logs to learn semantic categor...
Mamoru Komachi, Shimpei Makimoto, Kei Uchiumi, Man...
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