From Co-occurrence to Lexical Cohesion for Automatic Query Expansion

摘要

Designing an efficient Information Retrieval System (IRS) is still a big challenge and an open research problem. To overcome some of the problems of Information retrieval system, researchers have investigated query expansion (QE) techniques to help users in formulating better queries and hence improve efficiency of an Information Retrieval System. The scope of this work is limited to Pseudo Relevance Feedback based Query Expansion. Most of the work done in Pseudo Relevance Based Automatic query expansion is based on selecting the terms using co-occurrence based measures, which has some inherent limitations. Keeping in view limitations of co-occurrence based query expansion; we have tried to explore the utility of lexical based measures for expanding the query. This paper investigates the use of query expansion based on lexical links and proposes an algorithm for Lexical Cohesion Based Query Expansion (LCBQE). Based on theoretical justification and intensive experiments on TREC data set, we suggest that lexical based methods are at least as good as co-occurrence based measures and in some cases may work better than cooccurrence based measures. Depending on the nature of query, lexical based measures have great potential for improving the performance of an information retrieval system.