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SIGIR
2011
ACM
12 years 10 months ago
Active learning to maximize accuracy vs. effort in interactive information retrieval
We consider an interactive information retrieval task in which the user is interested in finding several to many relevant documents with minimal effort. Given an initial documen...
Aibo Tian, Matthew Lease
COLING
2010
13 years 1 months ago
Negative Feedback: The Forsaken Nature Available for Re-ranking
Re-ranking for Information Retrieval aims to elevate relevant feedbacks and depress negative ones in initial retrieval result list. Compared to relevance feedback-based re-ranking...
Yu Hong, Qing-qing Cai, Song Hua, Jian-Min Yao, Qi...
JCDL
2006
ACM
71views Education» more  JCDL 2006»
14 years 1 months ago
Using controlled query generation to evaluate blind relevance feedback algorithms
Currently in document retrieval there are many algorithms each with different strengths and weakness. There is some difficulty, however, in evaluating the impact of the test quer...
Chris Jordan, Carolyn R. Watters, Qigang Gao
ICMCS
2007
IEEE
132views Multimedia» more  ICMCS 2007»
14 years 1 months ago
Client-Side Relevance Feedback Approach for Image Retrieval in Mobile Environment
With the proliferation of handheld devices, the demand of multimedia information retrieval on mobile devices has attracted more attention. A relevance feedback information retriev...
Ning Yu, Kien A. Hua, Danzhou Liu
KES
2005
Springer
14 years 29 days ago
Using Relevance Feedback to Learn Both the Distance Measure and the Query in Multimedia Databases
Much of the world’s data is in the form of time series, and many other types of data, such as video, image, and handwriting, can easily be transformed into time series. This fact...
Chotirat (Ann) Ratanamahatana, Eamonn J. Keogh