Pruning Strategies for Mixed-Mode Querying

Vo Ngoc Anh
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. 2006 ACM CIKM Int. Conf. Information and Knowledge Management, Arlington, VA, November 2006, pages 190-197.

Abstract

Web information retrieval systems face a range of unique challenges, not the least of which is the sheer scale of the data that must be handled. Also specific to web retrieval is that queries may be a mix of Boolean and ranked features, and documents may have static score components that must also be factored into the ranking process. In this paper we consider a range of query semantics used in web retrieval systems, and show that impact-sorted indexes provide support for dynamic pruning mechanisms and in doing so allow fast document-at-a-time resolution of typical mixed-mode queries, even on relatively large volumes of data. Our techniques also extend to more complex query semantics, including the use of phrase, proximity, and structural constraints.

Full text

http://doi.acm.org/10.1145/1183614.1183645.