Abstract

Techniques for automatic query expansion have been extensively studied in information retrieval research as a means of addressing the word mismatch between queries and documents. These techniques can 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. Both types of techniques have advantages and limitations. In this paper we propose a new technique, called local context analysis, which combines the advantages of a global technique called Phrasefinder and a local technique known as local feedback. Experiments on a number of collections, both English and non-English, show that local context analysis offers more effective and consistent retrieval results.

Citations