Semantic query expansion combining association rules with ontologies and information retrieval techniques

Min Song, Il Yeol Song, Xiaohua Hu, Robert Allen

Research output: Contribution to journalConference article

10 Citations (Scopus)

Abstract

Query expansion techniques are used to find the desired set of query terms to improve retrieval performance. One of the limitations with the query expansion techniques is that a query is often expanded only by the linguistic features of terms. This paper presents a novel semantic query expansion technique that combines association rules with ontologies and information retrieval techniques. We propose to use the association rule discovery to find good candidate terms to improve the retrieval performance. These candidate terms are automatically derived from collections and added to the original query. Our method is differentiated from others in that 1) it utilizes the semantics as well as linguistic properties of unstructured text corpus and 2) it makes use of contextual properties of important terms discovered by association rules. Experiments conducted on a subset of TREC collections give quite encouraging results. We achieve from 15.49% to 20.98% improvement in term of P@20 with TREC5 ad hoc queries.

Original languageEnglish
Pages (from-to)326-335
Number of pages10
JournalLecture Notes in Computer Science
Volume3589
Publication statusPublished - 2005 Oct 24
Event7th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2005 - Copenhagen, Denmark
Duration: 2005 Aug 222005 Aug 26

Fingerprint

Query Expansion
Association rules
Association Rules
Information retrieval
Information Retrieval
Ontology
Semantics
Linguistics
Term
Query
Retrieval
Experiments
Subset
Experiment

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

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abstract = "Query expansion techniques are used to find the desired set of query terms to improve retrieval performance. One of the limitations with the query expansion techniques is that a query is often expanded only by the linguistic features of terms. This paper presents a novel semantic query expansion technique that combines association rules with ontologies and information retrieval techniques. We propose to use the association rule discovery to find good candidate terms to improve the retrieval performance. These candidate terms are automatically derived from collections and added to the original query. Our method is differentiated from others in that 1) it utilizes the semantics as well as linguistic properties of unstructured text corpus and 2) it makes use of contextual properties of important terms discovered by association rules. Experiments conducted on a subset of TREC collections give quite encouraging results. We achieve from 15.49{\%} to 20.98{\%} improvement in term of P@20 with TREC5 ad hoc queries.",
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Semantic query expansion combining association rules with ontologies and information retrieval techniques. / Song, Min; Song, Il Yeol; Hu, Xiaohua; Allen, Robert.

In: Lecture Notes in Computer Science, Vol. 3589, 24.10.2005, p. 326-335.

Research output: Contribution to journalConference article

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