Ontology-Based K-Means Clustering Algorithm Analysis

Qing Ju Guo; Wen Tian Ji; Sheng Zhong

doi:10.4028/www.scientific.net/AMM.380-384.1290

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 380-384Ontology-Based K-Means Clustering Algorithm...

Ontology-Based K-Means Clustering Algorithm Analysis

Abstract:

Lots of research findings have been made from home and abroad on clustering algorithm in recent years. In view of the traditional partition clustering method K-means algorithm, this paper, after analyzing its advantages and disadvantages, combines it with ontology-based data set to establish a semantic web model. It improves the existing clustering algorithm in various constraint conditions with the aim of demonstrating that the improved algorithm has better efficiency and accuracy under semantic web.

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Periodical:

Applied Mechanics and Materials (Volumes 380-384)

Pages:

1290-1293

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.380-384.1290

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Online since:

August 2013

Authors:

Qing Ju Guo, Wen Tian Ji, Sheng Zhong

Keywords:

Clustering Algorithm, Data, Improvement, K-Means Algorithm, Semantic Web

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