Broadening vector space schemes for improving the quality of information retrieval

Authors:
Kotagiri Ramamohanarao;Laurence A. F. Park
Affiliations:
ARC Centre for Perceptive and Intelligent Machines in Complex Environments, The Department of Computer Science and Software Engineering, The University of Melbourne, Australia;ARC Centre for Perceptive and Intelligent Machines in Complex Environments, The Department of Computer Science and Software Engineering, The University of Melbourne, Australia
Venue:
APWeb'05 Proceedings of the 7th Asia-Pacific web conference on Web Technologies Research and Development
Year:
2005

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Abstract

The vector space model (VSM) of information retrieval suffers in two areas, it does not utilise term positions and it treats every term as being independent. We examine two information retrieval methods based on the simple vector space model. The first uses the query term position flow within the documents to calculate the document score, the second includes related terms in the query by making use of term correlations. Both of these methods show significant improvements over the VSM precision while keeping the query time to speeds similar to those of the VSM.