The Modeling and Simulation of Data Clustering Algorithms in Data Mining with Big Data

Author:

Chen Weiru12,Oliverio Jared2,Kim Jin Ho3,Shen Jiayue4ORCID

Affiliation:

1. School of Computer and Communication, Lanzhou University of Technology, Lanzhou, Gansu 730050, P. R. China

2. Strome College of Business, Old Dominion University, Norfolk, VA 23508, USA

3. Carlson School of Management, University of Minnesota, Minneapolis, MN 55455, USA

4. College of Engineering, SUNY Polytechnic Institute, Utica, NY 13502, USA

Abstract

Big Data is a popular cutting-edge technology nowadays. Techniques and algorithms are expanding in different areas including engineering, biomedical, and business. Due to the high-volume and complexity of Big Data, it is necessary to conduct data pre-processing methods when data mining. The pre-processing methods include data cleaning, data integration, data reduction, and data transformation. Data clustering is the most important step of data reduction. With data clustering, mining on the reduced data set should be more efficient yet produce quality analytical results. This paper presents the different data clustering methods and related algorithms for data mining with Big Data. Data clustering can increase the efficiency and accuracy of data mining.

Publisher

World Scientific Pub Co Pte Lt

Subject

Management of Technology and Innovation,Strategy and Management,General Engineering,Business and International Management

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