Data Stream Mining Developments and Applications
Jayendra Kumar1, Anitha Raju2

1Mr Jayendra Kumar, Research Scholar, CSE, Koneru lakshmaiah Education Foundation, Vaddeswaram, Guntur Dist,.(A.P) .India.Pin:522502.
2Dr. Anitha Raju, Associate Professor, CSE, Koneru lakshmaiah Education Foundation, Vaddeswaram, Guntur (A.P). India. Pin:522502.
Manuscript received on 02 June 2019 | Revised Manuscript received on 10 June 2019 | Manuscript published on 30 June 2019 | PP: 2698-2702 | Volume-8 Issue-8, June 2019 | Retrieval Number: H7539068819/19©BEIESP
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Abstract: Organizations in multiple domains create diversified data each day. Such data can be processed to improve instantaneous decision-making decisions. However, it is challenging to act on real-time searching and processing large-scale datasets in an online data processing. Selection as the best technology for selecting appropriate data from a large dataset, thereby using upcoming features to make a decision. Though the number of processing data is large the accuracy of the mining counts on the number of instances in a cluster and the security measurers offered to preserve the data. The selection algorithm suggests a variety of approaches in this field to find appropriate algorithms and checks the usage used by the data streaming approach in mining concern. This paper presents a brief review on the developments and applications of data stream mining in current usage.
Keyword: Data stream mining, applications, security measure, Big-data research.
Scope of the Article: Data Mining Methods, Techniques, and Tools.