Anagani. Bhanu Sree, A. Mary Sowjanya, Andhra University College of Engineering (A), Visakhapatnam, Andhra Pradesh, India.
DOI :01.0401/ijaict.2015.05.08
International Journal of Advanced Information and Communication Technology
Received On :December 12, 2019
Revised On :January 13, 2019
Accepted On :February 15, 2019
Published On :March 05, 2019
Volume 06, Issue 03
Pages : 1040-1044
Abstract
Data mining is an extensively studied field of research area, where most of the work involves knowledge discovery. Data stream is a dynamic research area of data mining. A data stream is an enormous sequence of data elements continuously generated at a fast rate. In data streams, huge amount of data continuously inserted and queried, such data has very large database, for example, consumer click streams and telephone records, bulky sets of web pages, multimedia data, and financial transactions and so on. It raises new problems for the data stream community in terms of how to mine continuous arrival of high speed data items. Many researchers have focused on mining data streams and they proposed many techniques for data stream classification, data stream clustering and finding frequent items from data streams. Data stream clustering techniques are highly helpful to cluster the similar data items in data streams and also to detect the outliers, so they come under cluster based outlier detection. For this purpose we propose a new algorithm which is a combination of both hierarchical and partitioning clustering algorithms. A probabilistic hierarchical clustering algorithm in combination with K-Means and this yields more accurate results than that of those algorithms performed individually. The hybrid approach records good clustering accuracy.
Keywords
Data stream, Data stream clustering, hierarchical clustering algorithm, K-Means.
Cite this article
Anagani. Bhanu Sree, A. Mary Sowjanya, “A Hybrid Clustering Algorithm for Datastreams, ” INTERNATIONAL JOURNAL OF ADVANCED INFORMATION AND COMMUNICATION TECHNOLOGY, pp.1040-1044, March. 2019.
Copyright
© 2019 Anagani. Bhanu Sree, A. Mary Sowjanya. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.