Relevance feedback method based on vector space basis change

Abstract

The idea of relevance feedback (RF) is to involve the user in the retrieval process to improve the final result set by reformulating the query. The most commonly used methods in RF aim to rewrite the user query. In the vector space model, RF is usually undertaken by re-weighting the query terms without any modification in the vector space basis. In this paper we propose a RF method based on vector space basis change without any modification on the query term weights. The aim of our method is to find a basis which gives a better representation of the documents such that the relevant documents are gathered and the irrelevant ones are kept away from the relevant documents. © 2012 Springer-Verlag Berlin Heidelberg.