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Assessing the Performance of Compression Based Clustering for Text Mining

Author

Listed:
  • Alexandra CERNIAN

    (“Politehnica” University of Bucharest)

  • Dorin CARSTOIU

    (“Politehnica” University of Bucharest)

  • Adriana OLTEANU

    (“Politehnica” University of Bucharest)

  • Valentin SGARCIU

    (“Politehnica” University of Bucharest)

Abstract

The nature of the human brain is to find patterns in whatever surrounds us. Thus, we are all developing models of our personal universe. In an extended form, a constant preoccupation of philosophers has been to model the universe. Clustering is one of the most useful tools in the data mining process for discovering groups and identifying patterns in the underlying data. This paper addresses the compression based clustering approach and focuses on validating this method in the context of text mining. The idea is supported by the evidence that compression algorithms provide a good evaluation of the informational content. In this context, we developed an integrated clustering platform, called EasyClustering, which incorporates 3 compressors, 4 distance metrics and 3 clustering algorithms. The experimental validation presented in this paper focuses on clustering text documents based on informational content.

Suggested Citation

  • Alexandra CERNIAN & Dorin CARSTOIU & Adriana OLTEANU & Valentin SGARCIU, 2016. "Assessing the Performance of Compression Based Clustering for Text Mining," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(2), pages 197-210.
    • Handle: RePEc:cys:ecocyb:v:50:y:2016:i:2:p:197-210
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    References listed on IDEAS

    as
    1. Lian Duan & Lida Xu & Ying Liu & Jun Lee, 2009. "Cluster-based outlier detection," Annals of Operations Research, Springer, vol. 168(1), pages 151-168, April.
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    More about this item

    Keywords

    clustering; compression; text mining; EasyClustering; FScore.;
    All these keywords.

    JEL classification:

    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

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