Open AccessData Stream Clustering for Big Data Sets: A comparative Analysis
Author(s) -
Ankit Kumar Dubey,
Rajendra Gupta,
Sanjay Mishra
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1099/1/012030
Subject(s) - big data , cluster analysis , computer science , task (project management) , data science , data stream mining , reservation , data stream , data mining , artificial intelligence , engineering , computer network , telecommunications , systems engineering
The world is growing rapidly with constantly increasing the data. There are innumerable people around the world who use different types of applications, whether it is for reservation, marketing, shopping or knowledge in the form of text, image, audio and video. Only data is being generated everywhere and this growing data which is large and high dimensional is in nature is generally known as “big data”. For the organizations, it is a big task to cluster streaming big data successfully. In this paper, we are presenting a survey of data stream clustering algorithms applied over big data and big datasets. The paper shows the comparative analysis of all the studied methods and also review the evolution and progression of data stream clustering algorithm for big datasets. The paper also analyses the proposed and implemented algorithms in recent years.