UMP Institutional Repository

A Review on Data Stream Classification

A. A., Haneen and Noraziah, Ahmad and Mohd Helmy, Abd Wahab (2018) A Review on Data Stream Classification. In: Journal of Physics: Conference Series, 1st International Conference on Big Data and Cloud Computing (ICoBiC) 2017, 25-27 November 2017 , Kuching, Sarawak, Malaysia. pp. 1-8., 1018 (012019). ISSN 1742-6596

Available under License Creative Commons Attribution.

Download (856kB) | Preview


At this present time, the significance of data streams cannot be denied as many researchers have placed their focus on the research areas of databases, statistics, and computer science. In fact, data streams refer to some data points sequences that are found in order with the potential to be non-binding, which is generated from the process of generating information in a manner that is not stationary. As such the typical tasks of searching data have been linked to streams of data that are inclusive of clustering, classification, and repeated mining of pattern. This paper presents several data stream clustering approaches, which are based on density, besides attempting to comprehend the function of the related algorithms; both semi-supervised and active learning, along with reviews of a number of recent studies.

Item Type: Conference or Workshop Item (Lecture)
Uncontrolled Keywords: Clustering, Data Mining, Data Streams, Computational Intelligence
Subjects: Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: PM Dr. Noraziah Ahmad
Date Deposited: 30 Oct 2019 08:34
Last Modified: 30 Oct 2019 08:34
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item