ACM Computing Surveys· 2012Q1· Review
A Survey of Automatic Query Expansion in Information Retrieval
- 1,096citations
- Q1SCImago
- 2012year
Short summary
Automatic Query Expansion (AQE) significantly improves information retrieval effectiveness by augmenting user queries with semantically similar terms, addressing the gap between keyword queries and user information needs.
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Key points
- Information retrieval systems struggle because keyword queries often fail to represent the user's true information need.
- Automatic Query Expansion (AQE) augments original queries with terms of similar meaning to improve search effectiveness.
- Recent AQE approaches exhibit scientific and experimental maturity, particularly in laboratory settings like TREC.
- This survey offers a unified view of diverse AQE methods, comparing their principles, techniques, and data sources.
AI-generated from the title and abstract; the full text is not read.
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)?
The authors' abstract, as published at the source. ACM Computing Surveys, 2012 · DOI ↗
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Field: Signal Processing
Signal ProcessingComputer Science