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dc.contributor.authorPradorn Sureephongen_US
dc.contributor.authorNopasit Chakpitaken_US
dc.contributor.authorYacine Ouzrouteen_US
dc.contributor.authorGilles Neuberten_US
dc.contributor.authorAbdelaziz Bourasen_US
dc.description.abstractAfter the concept of industry cluster was tangibly applied in many countries, SMEs trended to link to each other to maintain their competitiveness in the market. The major key success factors of the cluster are knowledge sharing and collaboration between partners. This knowledge is collected in form of tacit and explicit knowledge from experts and institutions within the cluster. The objective of this study is about enhancing the industry cluster with knowledge management by using knowledge engineering which is one of the most important method for managing knowledge. This work analyzed three well known knowledge engineering methods, i.e. MOKA, SPEDE and CommonKADS, and compare the capability to be implemented in the cluster context. Then, we selected one method and proposed die adapted methodology. At the end of this paper, we validated and demonstrated the proposed methodology with some primary result by using case study of handicraft cluster in Thailand. © Springer-Verlag Berlin Heidelberg 2007.en_US
dc.subjectComputer Scienceen_US
dc.titleKnowledge engineering technique for cluster developmenten_US
dc.typeBook Seriesen_US
article.title.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_US
article.volume4798 LNAIen_US Mai Universityen_US Lumiere Lyon 2en_US
Appears in Collections:CMUL: Journal Articles

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