A clustering system for data sequence partitioning |
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| Authors: | Yu-Jie Wang |
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| Affiliation: | 1. Autonomous Control and Information Technology Institute (ACIT), North Carolina A&T State University, 1601 East Market Street, Greensboro, NC 27401, USA;2. United Technologies Research Center (UTRC), East Hartford, CT 06108 USA;1. Department of Computing and Informatics, Bournemouth University, Bournemouth, UK;2. Department of Computing and Informatics, Bournemouth University, UK;1. Department of Building, School of Design and Environment, National University of Singapore, 4 Architecture Drive, Singapore 117566;2. School of Information & Electronic Engineering, Zhejiang Gongshang University, 18 Xuezheng Road, Hangzhou, China, 311300;3. Computer Science Department, School of Science and Engineering, Tulane University, 6823 St. Charles Ave, New Orleans, LA, United States, 70118;1. Tecnologico de Monterrey, School of Engineering and Sciences Av. Carlos Lazo No. 100, Álvaro Obregón, Ciudad de México, 01389, México;2. Tecnologico de Monterrey, School of Engineering and Sciences Av. Eugenio Garza Sada 2501 Sur, Monterrey, N.L., 64849, México;3. Tecnologico de Monterrey, School of Engineering and Sciences Carretera al Lago de Guadalupe Km. 3.5, Atizapán de Zaragoza, Estado de México, C.P. 52926, México;4. Tecnologico de Monterrey, School of Engineering and Sciences Vía Atlixcáyotl No. 2301, Reserva Territorial Atlixcáyotl, Puebla, 72453, México;5. Tecnologico de Monterrey, School of Engineering and Sciences Av. General Ramón Corona No. 2514, Zapopan, Jalisco, 45138, México |
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| Abstract: | In data analyzing, data is often presented as sequences. To partition the data sequences, we propose a sequence clustering system in which a fuzzy compatible relation is employed to show the similarity between any two sequences. Moreover, the max–min transitive closure is applied to transfer the fuzzy compatible relation into a fuzzy equivalence relation. It is found that the data sequences with more similar variations are clustered together by using the proposed clustering system. In that case, the sequences are partitioned easily and quickly into clusters. |
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