A high-performance clustering algorithm based on searched experiences.
Clustering is a traditional data mining problem that has attracted researchers from different disciplines because its solution can be applied to many useful problems in our daily life. Since the era of big data is coming, how to "reduce the computing time" of an "effective clustering algorithm" has...
| Publicado en: | Computers in Human Behavior Vol. 100; pp. 231 - 242 |
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| Autores principales: | , , , , |
| Formato: | Artículo |
| Publicado: |
Elsevier B.V.
Nov2019
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=138100099&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 138100099 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 07475632 JC4 jtl: Computers in Human Behavior issn: 07475632 maglogo: N pubinfo: dt: Nov2019 vid: 100 pid: 2410 pub: Elsevier B.V. artinfo: ui: 138100099 10.1016/j.chb.2018.08.038 ppf: 231 ppct: 11 formats: tig: atl: A high-performance clustering algorithm based on searched experiences. aug: au: Tsai, Chun-Wei Ding, Yong-Chun Liu, Shi-Jui Chiang, Ming-Chao Yang, Chu-Sing affil: Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung 80424, Taiwan, ROC Department of Computer Science and Engineering, National Chung Hsing University, Taichung 40227, Taiwan, ROC Institute of Computer and Communication Engineering, Department of Electrical Engineering, National Cheng Kung University, Tainan 70101, Taiwan, ROC su: Data mining Information retrieval Time Cloud computing sug: subj: Data Processing, Hosting, and Related Services Data mining Information retrieval Time Cloud computing keyword: Big data Clustering Spark Big data Clustering Spark ab: Clustering is a traditional data mining problem that has attracted researchers from different disciplines because its solution can be applied to many useful problems in our daily life. Since the era of big data is coming, how to "reduce the computing time" of an "effective clustering algorithm" has been a promising research issue in recent years. Thus, this paper presents an effective clustering algorithm, by using the so-called searched information to determine later search directions, and then has it implemented on Spark to accelerate its response time for analyzing large-scale datasets. Simulation results show that the proposed algorithm provides a better result than the other clustering algorithms compared in this paper because it is less sensitive to the initial solutions. The simulation results further show that cloud computing platform is capable of enhancing the performance of the proposed algorithm. • This study presents a high-performance clustering algorithm based on searched experiences. • The results show that it is able to find a better result than traditional clustering algorithms. • We apply it to Spark to show its possibility to accelerate the response time on a cloud system. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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