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An Anonymous Algorithm for Calculating Dissimilarity Metric on Clustering

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DOI: 10.23977/cpcs.2016.11004 | Downloads: 38 | Views: 4449


Sun Yi 1, Li Chi 1


1 Beijing University of Posts and Telecommunications, China

Corresponding Author

Sun Yi


By the research on calculating the dissimilarity metric among tuples with many different attributes based on clustering, this paper improves dissimilarity metric algorithm, which can more accurately reflect the differences between tuples. Besides, in terms of various attribute types ,the value of attribute is divided into multi-category. According to the multi-category, we come to the final dissimilarity metric result through analysis. The experimental results show that this algorithm is able to achieve highly accurate dissimilarity metric results.


dissimilarity metric; multi-category; interval-scaled attribute; binary attribute; nominal attribute; ordinal attribute; proportional-scaled attribute; symmetric binary attribute; asymmetric binary attribute; clustering


Chi, L. and Sun, Y. (2016) An Anonymous Algorithm for Calculating Dissimilarity Metric on Clustering. Computing, Performance and Communication systems (2016) 1: 22-27.


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