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» Smoothing clickthrough data for web search ranking
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SIGIR
2009
ACM
11 years 8 months ago
Smoothing clickthrough data for web search ranking
Incorporating features extracted from clickthrough data (called clickthrough features) has been demonstrated to significantly improve the performance of ranking models for Web sea...
Jianfeng Gao, Wei Yuan, Xiao Li, Kefeng Deng, Jian...
CIKM
2008
Springer
11 years 3 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...
KDD
2009
ACM
248views Data Mining» more  KDD 2009»
11 years 6 months ago
PSkip: estimating relevance ranking quality from web search clickthrough data
1 In this article, we report our efforts in mining the information encoded as clickthrough data in the server logs to evaluate and monitor the relevance ranking quality of a commer...
Kuansan Wang, Toby Walker, Zijian Zheng
KDD
2007
ACM
192views Data Mining» more  KDD 2007»
12 years 2 months ago
Active exploration for learning rankings from clickthrough data
We address the task of learning rankings of documents from search engine logs of user behavior. Previous work on this problem has relied on passively collected clickthrough data. ...
Filip Radlinski, Thorsten Joachims
DASFAA
2004
IEEE
134views Database» more  DASFAA 2004»
11 years 5 months ago
Applying Co-training to Clickthrough Data for Search Engine Adaptation
The information on the World Wide Web is growing without bound. Users may have very diversified preferences in the pages they target through a search engine. It is therefore a chal...
Qingzhao Tan, Xiaoyong Chai, Wilfred Ng, Dik Lun L...
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