DocumentCode :
2727814
Title :
Automatic Taxonomy Extraction Using Google and Term Dependency
Author :
Makrehchi, Masoud ; Kamel, Mohamed S.
fYear :
2007
fDate :
2-5 Nov. 2007
Firstpage :
321
Lastpage :
325
Abstract :
An automatic taxonomy extraction algorithm is proposed. Given a set of terms or terminology related to a subject domain, the proposed approach uses Google page count to estimate the dependency links between the terms. A taxonomic link is an asymmetric relation between two concepts. In order to extract these directed links, neither mutual information nor normalized Google distance can be employed. Using the new measure of information theoretic inclusion index, term dependency matrix, which represents the pair-wise dependencies, is obtained. Next, using a proposed algorithm, the dependency matrix is converted into an adjacency matrix, representing the taxonomy tree. In order to evaluate the performance of the proposed approach, it is applied to several domains for taxonomy extraction.
Keywords :
Data mining; Databases; Information systems; Machine intelligence; Matrix converters; Ontologies; Pattern analysis; Semantic Web; Taxonomy; Terminology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence, IEEE/WIC/ACM International Conference on
Conference_Location :
Fremont, CA
Print_ISBN :
978-0-7695-3026-0
Type :
conf
DOI :
10.1109/WI.2007.37
Filename :
4427111
Link To Document :
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