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Granule mining and its application for network traffic characterization

Liu, Bin, Li, Yuefeng, & Wang, Kewen (2012) Granule mining and its application for network traffic characterization. In Watada, Junzo, Watanabe, Toyohide, & Philips-Wren, Gloria (Eds.) Intelligent Decision Technologies : Proceedings of the 4th International Conference on Intelligent Decision Technologies, Springer-Verlag , Nagaragawa Convention Center, Gifu, Japan, pp. 333-343.

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Abstract

Decision table and decision rules play an important role in rough set based data analysis, which compress databases into granules and describe the associations between granules. Granule mining was also proposed to interpret decision rules in terms of association rules and multi-tier structure. In this paper, we further extend granule mining to describe the relationships between granules not only by traditional support and confidence, but by diversity and condition diversity as well. Diversity measures how diverse of a granule associated with the other ganules, it provides a kind of novel knowledge in databases. Some experiments are conducted to test the proposed new concepts for describing the characteristics of a real network traffic data collection. The results show that the proposed concepts are promising.

Impact and interest:

1 citations in Scopus
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2 citations in Web of Science®

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ID Code: 52693
Item Type: Conference Paper
Keywords: Granule mining, Artificial intelligence, Diversity, Computational intelligence
DOI: 10.1007/978-3-642-29920-9_34
ISBN: 9783642299193
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 Springer
Deposited On: 25 Jul 2012 10:34
Last Modified: 27 Jul 2013 11:48

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