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A Clustering Algorithm Based on the Text Feature Matrix of Domain-Ontology

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4 Author(s)
Gong Guangming ; Sch. of Bus., Hunan Univ., Changsha, China ; Jiang Yanhui ; Wang Wei ; Zhou Shuangwen

The text feature matrix of domain-ontology has the following three characteristics: high-dimension, sparse and independence of dimensions. Independence means that text implications of dimensions are different from each other. Many clustering algorithms take into account the characteristics of high-dimension and sparse, but ignore the impact of independence. And the artificial interference in parameters can often affect our clustering results. In this paper, we propose a new clustering algorithm by enriching connotation of similarity and minimizing the influence of subjective parameters. The experimental results verify the validity of our algorithm.

Published in:

Intelligent System Design and Engineering Applications (ISDEA), 2013 Third International Conference on

Date of Conference:

16-18 Jan. 2013

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