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Overview of Concept Drifts Detection Methodology in Data Stream
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Author(s): Shabina Sayed (Jodhpur National University, India), Shoeb Ahemd Ansari (Shri Jagadish Prasad Jabnormal Tibrewala University, India)and Rakesh Poonia (Bikaner Government College of Engineering, India)
Copyright: 2018
Pages: 8
Source title:
Handbook of Research on Pattern Engineering System Development for Big Data Analytics
Source Author(s)/Editor(s): Vivek Tiwari (International Institute of Information Technology, India), Ramjeevan Singh Thakur (Maulana Azad National Institute of Technology, India), Basant Tiwari (Hawassa University, Ethiopia)and Shailendra Gupta (AISECT University, India)
DOI: 10.4018/978-1-5225-3870-7.ch018
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Abstract
Real-time online applications and mobile data generate huge volume of data. There is a need to process this data into compact data structures and extract meaningful information. A number of approaches have been proposed in literature to overcome the issues of data stream mining. This chapter summarizes various issues and application techniques. The chapter is a guideline for research to identify the research issues and select the most appropriate method in order to detect and process novel class.
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