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Proceedings Paper

A review of contrast pattern based data mining
Author(s): Shiwei Zhu; Meilong Ju; Junfeng Yu; Binlei Cai; Aiping Wang
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Paper Abstract

Contrast pattern based data mining is concerned with the mining of patterns and models that contrast two or more datasets. Contrast patterns can describe similarities or differences between the datasets. They represent strong contrast knowledge and have been shown to be very successful for constructing accurate and robust clusters and classifiers. The increasing use of contrast pattern data mining has initiated a great deal of research and development attempts in the field of data mining. A comprehensive revision on the existing contrast pattern based data mining research is given in this paper. They are generally categorized into background and representation, definitions and mining algorithms, contrast pattern based classification, clustering, and other applications, the research trends in future. The primary of this paper is to server as a glossary for interested researchers to have an overall picture on the current contrast based data mining development and identify their potential research direction to future investigation.

Paper Details

Date Published: 6 July 2015
PDF: 10 pages
Proc. SPIE 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015), 96311U (6 July 2015); doi: 10.1117/12.2197326
Show Author Affiliations
Shiwei Zhu, Shandong Academy of Sciences (China)
Meilong Ju, Shandong Academy of Sciences (China)
Junfeng Yu, Shandong Academy of Sciences (China)
Binlei Cai, Shandong Academy of Sciences (China)
Aiping Wang, Shandong Academy of Sciences (China)


Published in SPIE Proceedings Vol. 9631:
Seventh International Conference on Digital Image Processing (ICDIP 2015)
Charles M. Falco; Xudong Jiang, Editor(s)

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