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ICCV
2003
IEEE
14 years 23 days ago
Reinforcement Learning for Combining Relevance Feedback Techniques
Relevance feedback (RF) is an interactive process which refines the retrievals by utilizing user’s feedback history. Most researchers strive to develop new RF techniques and ign...
Peng-Yeng Yin, Bir Bhanu, Kuang-Cheng Chang, Anlei...
MM
2005
ACM
172views Multimedia» more  MM 2005»
14 years 1 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
BIBE
2007
IEEE
169views Bioinformatics» more  BIBE 2007»
14 years 1 months ago
Combining Semantics, Context, and Statistical Evidence in Genomics Literature Search
—We present an information retrieval model for combining evidence from concept-based semantics, term statistics, and context for improving search precision of genomics literature...
Jay Urbain, Nazli Goharian, Ophir Frieder
CIVR
2006
Springer
219views Image Analysis» more  CIVR 2006»
13 years 11 months ago
Bayesian Learning of Hierarchical Multinomial Mixture Models of Concepts for Automatic Image Annotation
We propose a novel Bayesian learning framework of hierarchical mixture model by incorporating prior hierarchical knowledge into concept representations of multi-level concept struc...
Rui Shi, Tat-Seng Chua, Chin-Hui Lee, Sheng Gao
CIKM
2010
Springer
13 years 4 months ago
A late fusion approach to cross-lingual document re-ranking
The field of information retrieval still strives to develop models which allow semantic information to be integrated in the ranking process to improve performance in comparison to...
Dong Zhou, Séamus Lawless, Jinming Min, Vin...