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ICITA
2005
IEEE
14 years 1 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...
JCO
2010
75views more  JCO 2010»
13 years 6 months ago
A quadratic lower bound for Rocchio's similarity-based relevance feedback algorithm with a fixed query updating factor
Rocchio’s similarity-based relevance feedback algorithm, one of the most important query reformation methods in information retrieval, is essentially an adaptive supervised lear...
Zhixiang Chen, Bin Fu, John Abraham
CIKM
2009
Springer
14 years 2 months ago
Exploring relevance for clicks
Mining feedback information from user click-through data is an important issue for modern Web retrieval systems in terms of architecture analysis, performance evaluation and algor...
Rongwei Cen, Yiqun Liu, Min Zhang, Bo Zhou, Liyun ...
ECIR
2008
Springer
13 years 9 months ago
Use of Implicit Graph for Recommending Relevant Videos: A Simulated Evaluation
In this paper, we propose a model for exploiting community based usage information for video retrieval. Implicit usage information from a pool of past users could be a valuable sou...
David Vallet, Frank Hopfgartner, Joemon M. Jose
WWW
2005
ACM
14 years 8 months ago
Comparing relevance feedback algorithms for web search
We evaluate three different relevance feedback (RF) algorithms, Rocchio, Robertson/Sparck-Jones (RSJ) and Bayesian, in the context of Web search. We use a target-testing experimen...
Vishwa Vinay, Kenneth R. Wood, Natasa Milic-Frayli...