DocumentCode
3462031
Title
Taxonomy Ontology Searching Method Based on Fuzzy Clustering
Author
Yangyao, Zhao ; Shengchun, Deng ; Nianbin, Wang
Author_Institution
Coll. of Comput. Sci. & Technol., Harbin Eng. Univ., Harbin, China
fYear
2009
fDate
21-22 April 2009
Firstpage
311
Lastpage
315
Abstract
Following with the rapid development of e-commerce Websites and on-line business, how to aggregate and unify information from millions of on-line ontologies becomes an important searching field. In order to solve this problem among taxonomy ontologies, this paper proposed a searching method based on fuzzy clustering. The similarity among different conceptions can be well calculated by fuzzy clustering. Getting the queries from users, this method can both give the final searching answers according to the similarity and arrange these answers in special order which can be defined by users or system designers. During the discussion, an instance which used this method in sports clothes selling Websites was given out. What is more, a propositional answer method which can reveal the relationship among the answers was described. In conclusion, fuzzy clustering method can work well in analyzing concept similarity among e-commerce Websites.
Keywords
Web sites; electronic commerce; fuzzy set theory; ontologies (artificial intelligence); pattern clustering; query processing; e-commerce Websites; fuzzy clustering method; on-line business; system designer; taxonomy ontology searching method; Aggregates; Application software; Clustering methods; Computer science; Educational institutions; Electronic commerce; Fuzzy systems; Humans; Ontologies; Taxonomy; E-commerce; Ontology; conception; fuzzy clustering; similarity;
fLanguage
English
Publisher
ieee
Conference_Titel
Interoperability for Enterprise Software and Applications China, 2009. IESA '09. International Conference on
Conference_Location
Beijing
Print_ISBN
978-0-7695-3652-1
Type
conf
DOI
10.1109/I-ESA.2009.17
Filename
5260797
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