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SIGIR
2008
ACM
15 years 1 months ago
Learning to rank at query-time using association rules
Some applications have to present their results in the form of ranked lists. This is the case of many information retrieval applications, in which documents must be sorted accordi...
Adriano Veloso, Humberto Mossri de Almeida, Marcos...
WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
13 years 9 months ago
Learning to rank with multi-aspect relevance for vertical search
Many vertical search tasks such as local search focus on specific domains. The meaning of relevance in these verticals is domain-specific and usually consists of multiple well-d...
Changsung Kang, Xuanhui Wang, Yi Chang, Belle L. T...
IBPRIA
2009
Springer
15 years 6 months ago
Large Scale Online Learning of Image Similarity through Ranking
ent abstract presents OASIS, an Online Algorithm for Scalable Image Similarity learning that learns a bilinear similarity measure over sparse representations. OASIS is an online du...
Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio
142
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CIKM
2009
Springer
14 years 11 months ago
Interactive relevance feedback with graded relevance and sentence extraction: simulated user experiments
Research on relevance feedback (RFB) in information retrieval (IR) has given mixed results. Success in RFB seems to depend on the searcher's willingness to provide feedback a...
Kalervo Järvelin
AMR
2006
Springer
96views Multimedia» more  AMR 2006»
15 years 5 months ago
Learning to Retrieve Images from Text Queries with a Discriminative Model
This work presents a discriminative model for the retrieval of pictures from text queries. The core idea of this approach is to minimize a loss directly related to the retrieval pe...
David Grangier, Florent Monay, Samy Bengio