Affiliation of Author(s):School of Reliability and Systems Engineering, Beihang University, Beijing, China

Journal:IEEE Transactions on Neural Networks and Learning Systems

Key Words:Clustering by fast search (CFS), clusters adjustment, incremental clustering, large data, multiplere

Abstract:With the prevailing development of Cyber-physicalsocial systems and Internet of Things, large-scale data have been collected consistently. Mining large data effectively and efficiently becomes increasingly important to promote the development and improve the service quality of these applications. Clustering, a popular data mining technique, aims to identify underlying patterns hidden in the data. Most clustering methods assume the static data, thus they are unfavorable for analyzing large, unbalanced dynamic data. In this paper, to address this concern, we focus on incremental clustering by ext

Co-author:Z. Chen,Liang Zou,Z. Jane Wang

First Author:L. Zhao

Indexed by:Development research

Correspondence Author:Y. Yang

First-Level Discipline:Control Science and Engineering

Document Type:J

Page Number:1-11

ISSN No.:21622388 2162237X

Translation or Not:no

CN No.:null

Date of Publication:2018-07-25

Included Journals:SCI

Links to published journals:https://doi-org-443.e.buaa.edu.cn/10.1109/TNNLS.2018.2851979

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