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Data Mining Clustering Technique in Data Streams – A Survey

S. Vijayarani, P. Sathya


A data stream is a continuous, real time, ordered sequence of items. It is impossible to control the order in which items arrives. Real time surveillances system, telecommunication system, sensor network, financial applications are some of the examples of the data stream systems. These types of streams produced millions or billions of updates every hour. These data must be processed to extract the information in a meaningful way. As data stored in a database and data warehouse are processed by using some mining algorithm. Data mining is an extraction of interesting pattern or knowledge from huge amount of data. In this paper, we will study how the data mining techniques are used in data streams as well as the clustering problem for data stream applications. To partition the data sets into one or more groups of similar objects is known as clustering.


Clustering, Data Mining, Data Streams,

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