Automatic fuzzy ontology generation for semantic help-desk support

Customer service support is an important operation for most multinational manufacturing companies. With the advancement of internet technologies, customer services nowadays are supported through web-based systems. More recently, rapid development of the semantic web and semantic web services has pro...

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Bibliographic Details
Published inIEEE transactions on industrial informatics Vol. 2; no. 3; pp. 155 - 164
Main Authors Thanh Tho Quan, Siu Cheung Hui, Fong, A.C.M.
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 01.08.2006
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Conceptual clustering
Customer satisfaction
Customer service
customer service support
Customer services
Data engineering
fault diagnosis
formal concept analysis
Fuzzy
Fuzzy logic
Fuzzy set theory
Internet
Manufacturing automation
Ontologies
Ontology
ontology generation
Productivity
Queries
Semantic Web
semantic web services
Semantics
Software
Studies
Virtual manufacturing
Web and internet services
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Summary:Customer service support is an important operation for most multinational manufacturing companies. With the advancement of internet technologies, customer services nowadays are supported through web-based systems. More recently, rapid development of the semantic web and semantic web services has prompted us to develop a semantic help-desk for supporting customer services over the semantic web environment, which is presented in this paper. In particular, a fuzzy formal concept analysis (FCA)-based approach is developed for automatic generation of fuzzy machine service ontology that can deal with uncertain information. The proposed automatic fuzzy ontology generation technique consists of the following steps: fuzzy formal concept analysis, fuzzy conceptual clustering, and ontology generation. As such, the supporting machine services provided by the proposed system will potentially improve customer satisfaction in terms of reducing machine down time and increasing productivity. In this paper, an experiment has also been conducted for performance evaluation. The experimental result shows that the proposed approach has attained good performance in terms of both accuracy and efficiency when the queries are associated with appropriate membership values, and a suitable confident threshold is set
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ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2006.873363