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» Online learning from click data for sponsored search
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CIKM
2008
Springer
13 years 9 months ago
Are click-through data adequate for learning web search rankings?
Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...
Zhicheng Dou, Ruihua Song, Xiaojie Yuan, Ji-Rong W...
CIKM
2010
Springer
13 years 6 months ago
Clickthrough-based translation models for web search: from word models to phrase models
Web search is challenging partly due to the fact that search queries and Web documents use different language styles and vocabularies. This paper provides a quantitative analysis ...
Jianfeng Gao, Xiaodong He, Jian-Yun Nie
WSDM
2009
ACM
138views Data Mining» more  WSDM 2009»
14 years 2 months ago
Integration of news content into web results
Aggregated search refers to the integration of content from specialized corpora or verticals into web search results. Aggregation improves search when the user has vertical intent...
Fernando Diaz
KDD
2009
ACM
245views Data Mining» more  KDD 2009»
14 years 8 months ago
Mining rich session context to improve web search
User browsing information, particularly their non-search related activity, reveals important contextual information on the preferences and the intent of web users. In this paper, ...
Guangyu Zhu, Gilad Mishne
SIGIR
2010
ACM
13 years 11 months ago
Learning more powerful test statistics for click-based retrieval evaluation
Interleaving experiments are an attractive methodology for evaluating retrieval functions through implicit feedback. Designed as a blind and unbiased test for eliciting a preferen...
Yisong Yue, Yue Gao, Olivier Chapelle, Ya Zhang, T...