Information Retrieval with a Hybrid Automatic Query Expansion and Data Fusion Procedure

Authors:
Yunjie Xu;Michel Benaroch
Affiliations:
School of Computing, Department of Information Systems, National University of Singapore, 3 Science Drive 2, Singapore 117 543. xuyj@comp.nus.edu.sg;School of Management, Syracuse University, Syracuse, NY 13244, USA
Venue:
Information Retrieval
Year:
2005

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Abstract

We propose a hybrid information retrieval (IR) procedure that builds on two well-known IR approaches: data fusion and query expansion via relevance feedback. This IR procedure is designed to exploit the strengths of data fusion and relevance feedback and to avoid some weaknesses of these approaches. We show that our IR procedure is built on postulates that can be justified analytically and empirically. Additionally, we offer an empirical investigation of the procedure, showing that it is superior to relevance feedback on some dimensions and comparable on other dimensions. The empirical investigation also verifies the conditions under which the use of our IR procedure could be beneficial.