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TREC
2008
13 years 6 months ago
A Study of Adaptive Relevance Feedback - UIUC TREC 2008 Relevance Feedback Experiments
In this paper, we report our experiments in the TREC 2008 Relevance Feedback Track. Our main goal is to study a novel problem in feedback, i.e., optimization of the balance of the...
Yuanhua Lv, ChengXiang Zhai
ICCV
2003
IEEE
13 years 10 months 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...
MIR
2006
ACM
223views Multimedia» more  MIR 2006»
13 years 10 months ago
Adaptive image retrieval using a Graph model for semantic feature integration
The variety of features available to represent multimedia data constitutes a rich pool of information. However, the plethora of data poses a challenge in terms of feature selectio...
Jana Urban, Joemon M. Jose
SIBGRAPI
2008
IEEE
13 years 11 months ago
A Genetic Programming Approach for Relevance Feedback in Region-Based Image Retrieval Systems
This paper presents a new relevance feedback method for content-based image retrieval using local image features. This method adopts a genetic programming approach to learn user p...
Jefersson Alex dos Santos, Cristiano D. Ferreira, ...
TKDE
2008
116views more  TKDE 2008»
13 years 4 months ago
Long-Term Cross-Session Relevance Feedback Using Virtual Features
Relevance feedback (RF) is an iterative process, which refines the retrievals by utilizing the user's feedback on previously retrieved results. Traditional RF techniques solel...
Peng-Yeng Yin, Bir Bhanu, Kuang-Cheng Chang, Anlei...