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CIKM
2010
Springer
13 years 8 months ago
Term necessity prediction
The probability that a term appears in relevant documents ( ) is a fundamental quantity in several probabilistic retrieval models, however it is difficult to estimate without rele...
Le Zhao, Jamie Callan
WSDM
2010
ACM
245views Data Mining» more  WSDM 2010»
14 years 7 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
2008
ACM
13 years 9 months ago
Discriminative probabilistic models for passage based retrieval
The approach of using passage-level evidence for document retrieval has shown mixed results when it is applied to a variety of test beds with different characteristics. One main r...
Mengqiu Wang, Luo Si
CIKM
2005
Springer
14 years 3 months ago
ViPER: augmenting automatic information extraction with visual perceptions
In this paper we address the problem of unsupervised Web data extraction. We show that unsupervised Web data extraction becomes feasible when supposing pages that are made up of r...
Kai Simon, Georg Lausen
CIVR
2010
Springer
199views Image Analysis» more  CIVR 2010»
14 years 2 months ago
Unsupervised multi-feature tag relevance learning for social image retrieval
Interpreting the relevance of a user-contributed tag with respect to the visual content of an image is an emerging problem in social image retrieval. In the literature this proble...
Xirong Li, Cees G. M. Snoek, Marcel Worring