MuDi-Stream: A multi density clustering algorithm for evolving data stream

Amini, A. and Saboohi, H. and Herawan, T. and Teh, Y.W. (2016) MuDi-Stream: A multi density clustering algorithm for evolving data stream. Journal of Network and Computer Applications, 59. pp. 370-385. ISSN 1084-8045, DOI

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Density-based method has emerged as a worthwhile class for clustering data streams. Recently, a number of density-based algorithms have been developed for clustering data streams. However, existing density-based data stream clustering algorithms are not without problem. There is a dramatic decrease in the quality of clustering when there is a range in density of data. In this paper, a new method, called the MuDi-Stream, is developed. It is an online-offline algorithm with four main components. In the online phase, it keeps summary information about evolving multi-density data stream in the form of core mini-clusters. The offline phase generates the final clusters using an adapted density-based clustering algorithm. The grid-based method is used as an outlier buffer to handle both noises and multi-density data and yet is used to reduce the merging time of clustering. The algorithm is evaluated on various synthetic and real-world datasets using different quality metrics and further, scalability results are compared. The experimental results show that the proposed method in this study improves clustering quality in multi-density environments.

Item Type: Article
Funders: University of Malaya: UMRG vote no. RP002F-13ICT , Ministry of Higher Education: High Impact Research (HIR) Grant, University of Malaya, no. UM.C/625/HIR/MOHE/SC/13/2
Uncontrolled Keywords: Evolving data streams; Multi-density clusters; Core mini-clusters; Density grid
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Computer Science & Information Technology
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 16 Nov 2017 02:46
Last Modified: 16 Nov 2017 02:46

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