EDSC: Efficient document subspace clustering technique for high-dimensional data

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Radhika, K.R. and Pushpa, C.N. and Thriveni, J. and Venugopal, K.R. (2016) EDSC: Efficient document subspace clustering technique for high-dimensional data. In: 2016 International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT), 11-13 March 2016, Bangalore.

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Official URL: https://doi.org/10.1109/ICCTICT.2016.7514582

Abstract

With the advancement in the pervasive technology, there is a spontaneous rise in the size of the data. Such data are generated from various forms of resources right from individual to organization level. Due to the characteristics of unstructured or semi-structuredness in data representation, the existing data analytics approaches are not directly applicable which leads to curse of dimensionality problem. Hence, this paper presents an Efficient Document Subspace Clustering (EDSC) technique for high-dimensional data that contributes to the existing system with respect to identification by eliminating the redundant data. The discrete segmentation of data points are used to explicitly expose the dimensionality of hidden subspaces in the clusters. The outcome of the proposed system was compared with existing system to find the effective document clustering process for high-dimensional data. The processing time of EDSC for subspace clustering is reduced by 50% as compared to the existing system.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Cluster Analysis, High-Dimensional Data,Subspace Clustering.
Subjects: Faculty of Engineering > Computer Science & Information Science Engineering
Divisions: University Visvesvarayya College of Engineering > Department of Computer Science and Information Science Engineering
Depositing User: Ms. Deepa M Kolli
Date Deposited: 20 Oct 2016 06:33
Last Modified: 20 Oct 2016 06:33
URI: http://eprints-bangaloreuniversity.in/id/eprint/6623

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