Formal concept analysis based clustering for blog network visualization

Authors:
Jing Gao;Wei Lai
Affiliations:
Faculty of Information and Communication Technologies, Swinburne University of Technology, Hawthorn Victoria, Australia;Faculty of Information and Communication Technologies, Swinburne University of Technology, Hawthorn Victoria, Australia
Venue:
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications: Part I
Year:
2010

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Abstract

Blog network is growing explosively recently. As a result, the network becomes huge and dynamic. People have an urge to have effective ways to explore and retrieve related information. Blog analysis has been investigated for several years. There are still some improvement space exist. In this paper, we provide a formal concept analysis based clustering visualization to help people find information easily. Especially it is easy for them to find hot topics and their related information. Our approach has several steps such as extracting keywords from individual blog entries, formal concept analysis (FCA) based clustering and user interactions. Compare with other applications, the main difference is using FCA to analysis the content of individual entries so that group similar entries into one community. Experiments results are provided to show the advantages of our approach.