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Learning by examples as relevance feedback and relevance feedback as learning by examples

IEE Two-day Seminar. Searching for Information: Artificial Intelligence and Information Retrieval Approaches, 1999
The relevance feedback in information retrieval (IR) is used for query formulation and consists of assessing a sample of retrieved documents. Probably, the most known probabilistic model based on learning from relevance feedback is the so called Robertson and Sparck-Jones' model (RSJ) (S. Robertson and K. Sparck-Jones, 1976; C.
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Image Retrieval and Relevance Feedback

2009
Relevance feedback is a means for refining a query in an information retrieval system by asking the user to specify how relevant each result of the query is. An image retrieval session relying on relevance feedback is interactive and iterative. The session is divided into several consecutive rounds; at every round, the user provides feedback regarding ...
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The Effects of Relevance Feedback Quality and Quantity in Interactive Relevance Feedback

2012
The original publication is available at www.springerlink.com.
Keskustalo, Heikki   +2 more
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Optimization of relevance feedback weights

Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '95, 1995
Chris Buckley, Gerard Salton
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Block-based pseudo-relevance feedback for image retrieval

Journal of Experimental and Theoretical Artificial Intelligence, 2022
Wei-Chao Lin
exaly  

A test of genetic algorithms in relevance feedback

Information Processing and Management, 2002
Cristina López-Pujalte   +1 more
exaly  

Asymmetric bagging and random subspace for support vector machines-based relevance feedback in image retrieval

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006
Dacheng Tao, Xiaoou Tang, Xuelong Li
exaly  

Flexible pseudo-relevance feedback via selective sampling

ACM Transactions on Asian Language Information Processing, 2005
Sakaitetsuya
exaly  

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