Vector-Space Ranking with Effective Early Termination

Vo Ngoc Anh
Department of Computer Science and Software Engineering, The University of Melbourne, Victoria 3010, Australia.

Owen de Kretser
Department of Computer Science and Software Engineering, The University of Melbourne, Victoria 3010, Australia.

Alistair Moffat
Department of Computer Science and Software Engineering, The University of Melbourne, Victoria 3010, Australia.

Status

Proc. 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, New Orleans, September 2001, 35-42.

Abstract

Considerable research effort has been invested in improving the effectiveness of information retrieval systems. Techniques such as relevance feedback, thesaural expansion, and pivoting all provide better quality responses to queries when tested in standard evaluation frameworks. But such enhancements have been developed in response to a quest for absolute performance, and they can add to the cost of evaluating queries. In this paper we consider the pragmatic issue of how to improve the cost-effectiveness of searching, by including in the assessment metric the expense of query processing. We describe a new inverted file structure using quantized weights that provides superior retrieval effectiveness compared to conventional inverted file structures when early termination heuristics are employed. That is, we are able to reach similar effectiveness levels with less computational cost, and so provide a better cost/performance compromise than previous inverted file organisations.