Survey Paper on Clustering of High Dimensional Data Streams

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2017 by IJCTT Journal
Volume-50 Number-1
Year of Publication : 2017
Authors : C Kondaiah, Dr.P.Chandra Sekhar

MLA

C Kondaiah, Dr.P.Chandra Sekhar "Survey Paper on Clustering of High Dimensional Data Streams". International Journal of Computer Trends and Technology (IJCTT) V50(1):63-67, August 2017. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
The data stream problem has been studied extensively in recent years because thecollection of streaming data is very easy. So Clustering of streaming data is essential for classification and decision making. Yet, a lot of stream data is high dimensional in nature. Finding clustering in high dimensional data is a difficult task because of high dimensional data comprises hundreds of attributes.Density-based clustering algorithms treat clusters as the dense regions it’s useful for the clustering of High dimensional data than conventional algorithms. Propose a new, high dimensional, projected data stream clustering method, called HPStream method. The method is implementing by combining a fading cluster structure, and the projection based clustering methodology.

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Keywords
Clustering Data Streams, High Dimensional Data, projected clustering, High Dimensional Data Mining.