The Improvement of K-Medoids Clustering Algorithm under Semantic Web

Wen Tian Ji; Qing Ju Guo; Sheng Zhong

doi:10.4028/www.scientific.net/AMM.380-384.1286

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 380-384The Improvement of K-Medoids Clustering Algorithm...

The Improvement of K-Medoids Clustering Algorithm under Semantic Web

Abstract:

K-medoids clustering algorithm is an efficient algorithm in classifying cluster categories. Based on algorithm analysis, this paper first improves the selection of K center point and then sets up a web model of ontology data set object with the aim of demonstrating through experiment evaluation that the improved algorithm can greatly enhance the accuracy of clustering results under semantic web.

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Periodical:

Applied Mechanics and Materials (Volumes 380-384)

Pages:

1286-1289

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.380-384.1286

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Online since:

August 2013

Authors:

Wen Tian Ji, Qing Ju Guo, Sheng Zhong

Keywords:

K-Mediods Clustering Algorithm, Ontology Data Set Object, Semantic Web Model

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