Integration of association rules and ontologies for semantic query expansion

被引:57
作者
Song, Min
Song, Il-Yeol
Hu, Xiaohua
Allen, Robert B.
机构
[1] New Jersey Inst Technol, Dept Informat Syst, Newark, NJ 07102 USA
[2] Drexel Univ, Coll Informat Sci & Technol, Philadelphia, PA 19104 USA
基金
美国国家科学基金会;
关键词
association rules; digital libraries; knowledge discovery; ontologies; semantic query expansion;
D O I
10.1016/j.datak.2006.10.010
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We propose a novel semantic query expansion technique that combines association rules with ontologies and Natural Language Processing techniques. Our technique is different from others in that (1) it utilizes the explicit semantics as well as other linguistic properties of unstructured text corpus, (2) it makes use of contextual properties of important terms discovered by association rules, and (3) ontology entries are added to the query by disambiguating word senses. Using TREC ad hoc queries we achieve from 13.41% to 32.39% improvement for P@20 and from 8.39% to 14.22% for the F-measure. (c) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:63 / 75
页数:13
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