Adaptive support vector clustering for multi-relational data mining

Authors:
Ping Ling;Chun-Guang Zhou
Affiliations:
College of Computer Science, Jilin University, Key Laboratory of Symbol Computation, and Knowledge Engineering of the Ministry of Education, Changchun, China;College of Computer Science, Jilin University, Key Laboratory of Symbol Computation, and Knowledge Engineering of the Ministry of Education, Changchun, China
Venue:
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Year:
2006

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Abstract

A novel self Adaptive Support Vector Clustering algorithm (ASVC) is proposed in this paper to cluster dataset with diverse dispersions. And a Kernel function is defined to measure affinity between multi-relational data. Task of clustering multi-relational data is addressed by integrating the designed Kernel into ASVC. Experimental results indicate that the designed Kernel can capture structured features well and ASVC is of fine performance.