Supporting web query expansion efficiently using multi-granularity indexing and query processing

Wen Syan Li, Divyakant Agrawal

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

The problem of word mismatch in information retrieval (IR) occurs because users often use different words to describe concepts in their queries than authors use to describe the same concepts in their documents. Query expansion is used to deal with the mismatch between author and user vocabularies. To support query expansion, indices on words related by lexical semantics and syntactical co-occurrence need to be maintained. Two issues become paramount in supporting query expansion: the size of index tables and the query processing overhead. In this paper, we propose to use the notion of multi-granularity for more efficient indexing and query processing while the same degrees of precision and recall are maintained. We also describes extensions of this technique to handle: (1) query relaxation to handle words with multiple senses and with other semantic relationships; (2) progressive processing of queries with top N results and (3) progressive processing of queries with specification of the importance of each keyword.

Original languageEnglish
Pages (from-to)239-257
Number of pages19
JournalData and Knowledge Engineering
Volume35
Issue number3
DOIs
Publication statusPublished - 1 Dec 2000
Externally publishedYes

Fingerprint

Query processing
Semantics
Processing
Information retrieval
Specifications
Query expansion
Indexing
Query
World Wide Web
Mismatch

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Supporting web query expansion efficiently using multi-granularity indexing and query processing. / Li, Wen Syan; Agrawal, Divyakant.

In: Data and Knowledge Engineering, Vol. 35, No. 3, 01.12.2000, p. 239-257.

Research output: Contribution to journalArticle

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