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» Online learning from click data for sponsored search
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WSDM
2009
ACM
191views Data Mining» more  WSDM 2009»
14 years 2 months ago
Generating labels from clicks
The ranking function used by search engines to order results is learned from labeled training data. Each training point is a (query, URL) pair that is labeled by a human judge who...
Rakesh Agrawal, Alan Halverson, Krishnaram Kenthap...
ICASSP
2011
IEEE
12 years 11 months ago
Exploiting query click logs for utterance domain detection in spoken language understanding
In this paper, we describe methods to exploit search queries mined from search engine query logs to improve domain detection in spoken language understanding. We propose extending...
Dilek Hakkani-Tür, Larry Heck, Gökhan T&...
SIGIR
2009
ACM
14 years 2 months ago
Global ranking by exploiting user clicks
It is now widely recognized that user interactions with search results can provide substantial relevance information on the documents displayed in the search results. In this pape...
Shihao Ji, Ke Zhou, Ciya Liao, Zhaohui Zheng, Gui-...
WSDM
2012
ACM
207views Data Mining» more  WSDM 2012»
12 years 3 months ago
Domain bias in web search
This paper uncovers a new phenomenon in web search that we call domain bias — a user’s propensity to believe that a page is more relevant just because it comes from a particul...
Samuel Ieong, Nina Mishra, Eldar Sadikov, Li Zhang
CIKM
2009
Springer
14 years 2 months ago
Post-rank reordering: resolving preference misalignments between search engines and end users
No search engine is perfect. A typical type of imperfection is the preference misalignment between search engines and end users, e.g., from time to time, web users skip higherrank...
Chao Liu, Mei Li, Yi-Min Wang