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Mining Regular Patterns in Data Streams Using Vertical Format
G. Vijay Kumar, M. Sreedevi, NVS Pavan Kumar
Pages - 142 - 149     |    Revised - 15-03-2012     |    Published - 16-04-2012
Volume - 6   Issue - 2    |    Publication Date - April 2012  Table of Contents
regular patterns, data streams, vertical database
The increasing prominence of data streams has been lead to the study of online mining in order to capture interesting trends, patterns and exceptions. Recently, temporal regularity in occurrence behavior of a pattern was treated as an emerging area in several online applications like network traffic, sensor networks, e-business and stock market analysis etc. A pattern is said to be regular in a data stream, if its occurrence behavior is not more than the user given regularity threshold. Although there has been some efforts done in finding regular patterns over stream data, no such method has been developed yet by using vertical data format. Therefore, in this paper we develop a new method called VDSRP-method to generate the complete set of regular patterns over a data stream at a user given regularity threshold. Our experimental results show that highly efficiency in terms of execution and memory consumption.
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Mr. G. Vijay Kumar
- India
Mr. M. Sreedevi
- India
Dr. NVS Pavan Kumar
- India

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