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» Magnitude-preserving ranking algorithms
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CIKM
2008
Springer
15 years 8 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...
SIAMREV
2010
174views more  SIAMREV 2010»
15 years 1 months ago
Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
The affine rank minimization problem consists of finding a matrix of minimum rank that satisfies a given system of linear equality constraints. Such problems have appeared in the ...
Benjamin Recht, Maryam Fazel, Pablo A. Parrilo
KDD
2009
ACM
192views Data Mining» more  KDD 2009»
16 years 6 months ago
Learning optimal ranking with tensor factorization for tag recommendation
Tag recommendation is the task of predicting a personalized list of tags for a user given an item. This is important for many websites with tagging capabilities like last.fm or de...
Steffen Rendle, Leandro Balby Marinho, Alexandros ...
WSDM
2010
ACM
245views Data Mining» more  WSDM 2010»
16 years 3 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...
SIGIR
2009
ACM
16 years 23 days 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-...