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

Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Systematic analysis of artificial intelligence in the era of industry 4.0;Journal of Management Analytics;2023-01-02

2. Research on application software operation fault diagnosis method based on big data mining;2022 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS);2022-03

3. Technological Innovation Research;Journal of Global Information Management;2021-11

4. Euclidean distance stratified random sampling based clustering model for big data mining;Computational and Mathematical Methods;2021-10-26

5. Stratified linear systematic sampling based clustering approach for detection of financial risk group by mining of big data;International Journal of System Assurance Engineering and Management;2021-10-19

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3