Improving the effectiveness of information retrieval with local context analysis

Techniques for automatic query expansion have been extensively studied in information research as a means of addressing the word mismatch between queries and documents. These techniques can be categorized as either global or local. While global techniques rely on analysis of a whole collection to di...

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Bibliographic Details
Published in:ACM transactions on information systems 2000-01, Vol.18 (1), p.79-112
Main Authors: Xu, Jinxi, Croft, W. Bruce
Format: Article
Language:English
Subjects:
Information retrieval
Information retrieval query processing
Information systems
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Summary:Techniques for automatic query expansion have been extensively studied in information research as a means of addressing the word mismatch between queries and documents. These techniques can be categorized as either global or local. While global techniques rely on analysis of a whole collection to discover word relationships, local techniques emphasize analysis of the top-ranked documents retrieved for a query. While local techniques have shown to be more effective that global techniques in general, existing local techniques are not robust and can seriously hurt retrieved when few of the retrieval documents are relevant. We propose a new technique, called local context analysis, which selects expansion terms based on cooccurrence with the query terms within the top-ranked documents. Experiments on a number of collections, both English and non-English, show that local context analysis offers more effective and consistent retrieval results.
ISSN:1046-8188
1558-2868
DOI:10.1145/333135.333138