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» Parallel learning to rank for information retrieval
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CIKM
2008
Springer
13 years 9 months ago
Joke retrieval: recognizing the same joke told differently
In a corpus of jokes, a human might judge two documents to be the "same joke" even if characters, locations, and other details are varied. A given joke could be retold w...
Lisa Friedland, James Allan
MIR
2005
ACM
140views Multimedia» more  MIR 2005»
14 years 1 months ago
Multiple random walk and its application in content-based image retrieval
In this paper, we propose a transductive learning method for content-based image retrieval: Multiple Random Walk (MRW). Its basic idea is to construct two generative models by mea...
Jingrui He, Hanghang Tong, Mingjing Li, Wei-Ying M...
WSDM
2012
ACM
285views Data Mining» more  WSDM 2012»
12 years 3 months ago
Probabilistic models for personalizing web search
We present a new approach for personalizing Web search results to a specific user. Ranking functions for Web search engines are typically trained by machine learning algorithms u...
David Sontag, Kevyn Collins-Thompson, Paul N. Benn...
SIGIR
2010
ACM
13 years 11 months ago
Extending average precision to graded relevance judgments
Evaluation metrics play a critical role both in the context of comparative evaluation of the performance of retrieval systems and in the context of learning-to-rank (LTR) as objec...
Stephen E. Robertson, Evangelos Kanoulas, Emine Yi...
CIVR
2010
Springer
276views Image Analysis» more  CIVR 2010»
14 years 14 days ago
Optimizing visual search with implicit user feedback in interactive video retrieval
This paper describes an approach to optimize query by visual example results, by combining visual features and implicit user feedback in interactive video retrieval. To this end, ...
Stefanos Vrochidis, Ioannis Kompatsiaris, Ioannis ...