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ICCV
2003
IEEE
13 years 9 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...
ICITA
2005
IEEE
13 years 10 months ago
Combining Diversity-Based Active Learning with Discriminant Analysis in Image Retrieval
Small-sample learning in image retrieval is a pertinent and interesting problem. Relevance feedback is an active area of research that seeks to find algorithms that are robust wi...
Charlie K. Dagli, ShyamSundar Rajaram, Thomas S. H...
ICPR
2008
IEEE
14 years 5 months ago
Learning weighted distances for relevance feedback in image retrieval
We present a new method for relevance feedback in image retrieval and a scheme to learn weighted distances which can be used in combination with different relevance feedback metho...
Enrique Vidal, Hermann Ney, Roberto Paredes, Thoma...
CIKM
2000
Springer
13 years 8 months ago
Relevance and Reinforcement in Interactive Browsing
We consider the problem of browsing the top ranked portion of the documents returned by an information retrieval system. We describe an interactive relevance feedback agent that a...
Anton Leuski
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, ...