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Hinneburg, A. and Keim, D. (1998) An Efficient Approach to Clustering in Large Multimedia Databases with Noise. Proceeding 4th International Conference on Knowledge Discovery & Data Mining, 58-65.

has been cited by the following article:

• TITLE: D-IMPACT: A Data Preprocessing Algorithm to Improve the Performance of Clustering

  AUTHORS: Vu Anh Tran, Osamu Hirose, Thammakorn Saethang, Lan Anh T. Nguyen, Xuan Tho Dang, Tu Kien T. Le, Duc Luu Ngo, Gavrilov Sergey, Mamoru Kubo, Yoichi Yamada, Kenji Satou

  KEYWORDS: Attraction, Clustering, Data Preprocessing, Density, Shrinking

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.7 No.8, July 8, 2014

  ABSTRACT: In this study, we propose a data preprocessing algorithm called D-IMPACT inspired by the IMPACT clustering algorithm. D-IMPACT iteratively moves data points based on attraction and density to detect and remove noise and outliers, and separate clusters. Our experimental results on two-dimensional datasets and practical datasets show that this algorithm can produce new datasets such that the performance of the clustering algorithm is improved.