DocumentCode :
480725
Title :
Using Text Mining to Enrich the Vocabulary of Domain Ontologies
Author :
Speretta, Mirco ; Gauch, Susan
Author_Institution :
CSCE Dept., Univ. of Arkansas, Fayetteville, AR
Volume :
1
fYear :
2008
fDate :
9-12 Dec. 2008
Firstpage :
549
Lastpage :
552
Abstract :
Users organize personal information in various ways. We believe that this process could be expedited and improved by using domain ontologies. The main problem with this idea is the lack of automatic tools that help non-expert users to build and maintain their own ontologies. In this study we report progress in the process of adapting ontologies to better represent a given set of documents centered on a topic of interest. More specifically we investigate automatic approaches to enhance the representation of the concepts within the domain ontology. We show that our approach can enrich the vocabulary of each concept with words mined from the set of small documents provided. The method we propose is based on efficient text mining approaches combined with semantic information from WordNet.
Keywords :
data mining; ontologies (artificial intelligence); domain ontologies; text mining; vocabulary; Intelligent agent; Libraries; Ontologies; Search engines; Statistical distributions; Taxonomy; Text mining; USA Councils; Vocabulary; Web pages; ontology adaptation; text mining; vocabulary enrichment;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence and Intelligent Agent Technology, 2008. WI-IAT '08. IEEE/WIC/ACM International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-0-7695-3496-1
Type :
conf
DOI :
10.1109/WIIAT.2008.288
Filename :
4740507
Link To Document :
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