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» Learning Semantic Categories from Clickthrough Logs
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CIKM
2007
Springer
15 years 5 months ago
Predictive user click models based on click-through history
Web search engines consistently collect information about users interaction with the system: they record the query they issued, the URL of presented and selected documents along w...
Benjamin Piwowarski, Hugo Zaragoza
86
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WWW
2009
ACM
16 years 8 days ago
How much can behavioral targeting help online advertising?
Behavioral Targeting (BT) is a technique used by online advertisers to increase the effectiveness of their campaigns, and is playing an increasingly important role in the online a...
Jun Yan, Ning Liu, Gang Wang, Wen Zhang, Yun Jiang...
SIGIR
2006
ACM
15 years 5 months ago
Learning user interaction models for predicting web search result preferences
Evaluating user preferences of web search results is crucial for search engine development, deployment, and maintenance. We present a real-world study of modeling the behavior of ...
Eugene Agichtein, Eric Brill, Susan T. Dumais, Rob...
WSDM
2010
ACM
245views Data Mining» more  WSDM 2010»
15 years 9 months ago
Improving Quality of Training Data for Learning to Rank Using Click-Through Data
In information retrieval, relevance of documents with respect to queries is usually judged by humans, and used in evaluation and/or learning of ranking functions. Previous work ha...
Jingfang Xu, Chuanliang Chen, Gu Xu, Hang Li, Elbi...
CIKM
2010
Springer
14 years 10 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