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Ontology Matching Techniques: A 3-Tier Classification Framework, Nelson K. Y. Leung, Seung Hwan Kang, Sim Kim Lau, Joshua Fan
Ontology Matching Techniques: A 3-Tier Classification Framework, Nelson K. Y. Leung, Seung Hwan Kang, Sim Kim Lau, Joshua Fan
Faculty of Informatics - Papers (Archive)
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Clustering, Classification And Explanatory Rules From Harmonic Monitoring Data, Ali Asheibi, David A. Stirling, Danny Sutanto, D A. Robinson
Clustering, Classification And Explanatory Rules From Harmonic Monitoring Data, Ali Asheibi, David A. Stirling, Danny Sutanto, D A. Robinson
Faculty of Informatics - Papers (Archive)
A method based on the successful AutoClass (Cheeseman & Stutz, 1996) and the Snob research programs (Wallace & Dowe, 1994); (Baxter & Wallace, 1996) has been chosen for our research work on harmonic classification. The method utilizes mixture models (McLachlan, 1992) as a representation of the formulated clusters. This research is principally based on the formation of such mixture models (typically based on Gaussian distributions) through a Minimum Message Length (MML) encoding scheme (Wallace & Boulton, 1968). During the formation of such mixture models the various derivative tools (algorithms) allow for the automated selection of the number of clusters and …