Abstract
Visual data mining is one of important approach of data mining techniques. Most of them are based on computer graphic techniques but few of them exploit image-processing techniques. This paper proposes an image processing method, named RNAM (resemble neighborhood averaging method), to facilitate visual data mining, which is used to post-process the data mining result-image and help users to discover significant features and useful patterns effectively. The experiments show that the method is intuitive, easily-understanding and effectiveness. It provides a new approach for visual data mining.
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Foundation item: Supported by the National Natural Science Foundation of China (60173051), the Teaching and Research Award Program for Outstanding Young Teachers in Higher Education Institutions of Ministry of Education of China, and Liaoning Province Higher Education Research Foundation (20040206).
Biography: REN Young-Gong(1972-), male, Ph. D. candidate, Associate professor, research direction: visual data mining and image processing, etc.
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Yong-gong, R., Ge, Y. Image post-processing method for visual data mining. Wuhan Univ. J. Nat. Sci. 11, 15–20 (2006). https://doi.org/10.1007/BF02831696
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DOI: https://doi.org/10.1007/BF02831696