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KDD
2007
ACM
192views Data Mining» more  KDD 2007»
16 years 8 days 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
ICPR
2004
IEEE
16 years 29 days ago
Compact Representation of Multidimensional Data Using Tensor Rank-One Decomposition
This paper presents a new approach for representing multidimensional data by a compact number of bases. We consider the multidimensional data as tensors instead of matrices or vec...
Hongcheng Wang, Narendra Ahuja
CIKM
2008
Springer
15 years 1 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...
ERCIMDL
2010
Springer
158views Education» more  ERCIMDL 2010»
15 years 29 days ago
Ranking Entities Using Web Search Query Logs
Abstract Searching for entities is an emerging task in Information Retrieval for which the goal is finding well defined entities instead of documents matching the query terms. In t...
Bodo Billerbeck, Gianluca Demartini, Claudiu S. Fi...
KDD
2009
ACM
248views Data Mining» more  KDD 2009»
15 years 4 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