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» Learning to rank query reformulations
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WWW
2011
ACM
14 years 8 months ago
Learning to re-rank: query-dependent image re-ranking using click data
Our objective is to improve the performance of keyword based image search engines by re-ranking their baseline results. To this end, we address three limitations of existing searc...
Vidit Jain, Manik Varma
MM
2005
ACM
172views Multimedia» more  MM 2005»
15 years 7 months ago
Learning the semantics of multimedia queries and concepts from a small number of examples
In this paper we unify two supposedly distinct tasks in multimedia retrieval. One task involves answering queries with a few examples. The other involves learning models for seman...
Apostol Natsev, Milind R. Naphade, Jelena Tesic
CIKM
2008
Springer
15 years 3 months ago
Searching the wikipedia with contextual information
We propose a framework for searching the Wikipedia with contextual information. Our framework extends the typical keyword search, by considering queries of the type q, p , where q...
Antti Ukkonen, Carlos Castillo, Debora Donato, Ari...
209
Voted
FGR
2011
IEEE
354views Biometrics» more  FGR 2011»
14 years 5 months ago
Hierarchical ranking of facial attributes
Abstract— We propose a novel hierarchical structured prediction approach for ranking images of faces based on attributes. We view ranking as a bipartite graph matching problem; l...
Ankur Datta, Rogerio Feris, Daniel A. Vaquero
144
Voted
CIKM
2008
Springer
15 years 3 months ago
Learning latent semantic relations from clickthrough data for query suggestion
For a given query raised by a specific user, the Query Suggestion technique aims to recommend relevant queries which potentially suit the information needs of that user. Due to th...
Hao Ma, Haixuan Yang, Irwin King, Michael R. Lyu