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A new approach to improve the accuracy of online clustering algorithm based on scatter/gather model

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3 Author(s)
Kian Farsandaj ; Department of Computer Science, Ryerson University, Toronto, ON, M5B 2K3, Canada ; Chen Ding ; Alireza Sadeghian

In cluster analysis process used in data mining which enables extracting interesting data patterns from datasets, accuracy and efficiency are the factors which play a pivotal role. Scatter/Gather is a cluster-based browsing model, and most of previous works on this model focused on efficiency of the clustering algorithm. In this paper we present an algorithm which could improve the accuracy of the online clustering algorithm while still maintain a reasonable level of efficiency. Our experiment proves that the new algorithm is more accurate than the original algorithm.

Published in:

Fuzzy Information Processing Society (NAFIPS), 2010 Annual Meeting of the North American

Date of Conference:

12-14 July 2010