DocumentCode :
2757803
Title :
Restructuring Ontologies through Knowledge Discovery
Author :
Henshaw, Sylvia M. ; El-Masri, Ala´a ; Sage, Philip A.
Author_Institution :
Dept. of Comput. Sci., George Mason Univ., Fairfax, VA
fYear :
2008
fDate :
21-24 July 2008
Firstpage :
441
Lastpage :
444
Abstract :
In this work, we describe an approach for maintaining self-adapting personalized ontologies. We motivate this work with the observation that users are often interested in only small parts of larger domain ontologies; however, we also observe that users are frequently unaware of concepts that may be of interest given their past preferences. As such, we suggest that personalized ontologies should be continuously specialized and generalized to represent only those concepts that have proven to be of value to the user.
Keywords :
data mining; ontologies (artificial intelligence); semantic Web; knowledge discovery; ontology restructuring; self-adapting personalized ontology; Collaborative work; Computer science; Data mining; History; Information filtering; Information filters; Ontologies; Semantic Web; USA Councils; Web mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
E-Commerce Technology and the Fifth IEEE Conference on Enterprise Computing, E-Commerce and E-Services, 2008 10th IEEE Conference on
Conference_Location :
Washington, DC
Print_ISBN :
978-0-7695-3340-7
Type :
conf
DOI :
10.1109/CECandEEE.2008.147
Filename :
4785104
Link To Document :
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