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A Survey of Automatic Query Expansion in Information Retrieval

Published:01 January 2012Publication History
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Abstract

The relative ineffectiveness of information retrieval systems is largely caused by the inaccuracy with which a query formed by a few keywords models the actual user information need. One well known method to overcome this limitation is automatic query expansion (AQE), whereby the user’s original query is augmented by new features with a similar meaning. AQE has a long history in the information retrieval community but it is only in the last years that it has reached a level of scientific and experimental maturity, especially in laboratory settings such as TREC. This survey presents a unified view of a large number of recent approaches to AQE that leverage various data sources and employ very different principles and techniques. The following questions are addressed. Why is query expansion so important to improve search effectiveness? What are the main steps involved in the design and implementation of an AQE component? What approaches to AQE are available and how do they compare? Which issues must still be resolved before AQE becomes a standard component of large operational information retrieval systems (e.g., search engines)?

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            cover image ACM Computing Surveys
            ACM Computing Surveys  Volume 44, Issue 1
            January 2012
            181 pages
            ISSN:0360-0300
            EISSN:1557-7341
            DOI:10.1145/2071389
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            • Published: 1 January 2012
            • Accepted: 1 March 2010
            • Revised: 1 February 2010
            • Received: 1 November 2009
            Published in csur Volume 44, Issue 1

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