TELKOMNIKA (Telecommunication Computing Electronics and Control)
Vol 17, No 2: April 2019

Data stream mining techniques: a review

Eiman Alothali (United Arab Emirates University)
Hany Alashwal (United Arab Emirates University)
Saad Harous (United Arab Emirates University)



Article Info

Publish Date
01 Apr 2019

Abstract

A plethora of infinite data is generated from the Internet and other information sources. Analyzing this massive data in real-time and extracting valuable knowledge using different mining applications platforms have been an area for research and industry as well. However, data stream mining has different challenges making it different from traditional data mining. Recently, many studies have addressed the concerns on massive data mining problems and proposed several techniques that produce impressive results. In this paper, we review real time clustering and classification mining techniques for data stream. We analyze the characteristics of data stream mining and discuss the challenges and research issues of data steam mining. Finally, we present some of the platforms for data stream mining.

Copyrights © 2019






Journal Info

Abbrev

TELKOMNIKA

Publisher

Subject

Computer Science & IT

Description

Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of ...