A Query Expansion Method based on a Weighted Word Pairs Approach

In this paper we propose a query expansion method to improve accuracy of a text retrieval system. Our technique makes use of explicit relevance feedback to expand an initial query with a structured representation called Weighted Word Pairs. Such a structure can be automatically extracted from a set of documents and uses a method for term extraction based on the probabilistic Topic Model. Evaluation has been conducted on TREC-8 repository and performances obtained using standard WWP and Kullback Leibler Divergency query expansion approaches have been compared