The field of information retrieval still strives to develop models which allow semantic information to be integrated in the ranking process to improve performance in comparison to...
We address the challenge of semantic gap reduction for image retrieval through an improved SVM-based active relevance feedback framework, together with a hybrid visual and concept...
The aim of latent semantic indexing (LSI) is to uncover the relationships between terms, hidden concepts, and documents. LSI uses the matrix factorization technique known as singu...
We present a new approach for personalizing Web search results to a specific user. Ranking functions for Web search engines are typically trained by machine learning algorithms u...
David Sontag, Kevyn Collins-Thompson, Paul N. Benn...
Simple word matching between the user query and document is common, as are mis-matches of meaning that occur as a consequence, and errors in recall. These defects in the "bag...