Relevance Feedback (RF) is a technique allowing to enrich an initial query according to the user feedback in order to get results closer to the user’s information need. This pape...
This paper introduces a composite relevance feedback approach for image retrieval using transaction-based and SVM-based learning. A transaction repository is dynamically constructe...
There is an increasing amount of structure on the Web as a result of modern Web languages, user tagging and annotation, and emerging robust NLP tools. These meaningful, semantic, ...
The learning-enhanced relevance feedback has been one of the most active research areas in content-based image retrieval in recent years. However, few methods using the relevance ...
This paper proposes a novel view of the information generated by relevance feedback. Latent semantic analysis is adapted to this view to extract useful inter-query information. Th...