{"title":"MCOKE: Multi-Cluster Overlapping K-Means Extension Algorithm","authors":"Said Baadel, Fadi Thabtah, Joan Lu","volume":98,"journal":"International Journal of Computer and Information Engineering","pagesStart":427,"pagesEnd":431,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10000529","abstract":"
Clustering involves the partitioning of n objects into k
\r\nclusters. Many clustering algorithms use hard-partitioning techniques
\r\nwhere each object is assigned to one cluster. In this paper we propose
\r\nan overlapping algorithm MCOKE which allows objects to belong to
\r\none or more clusters. The algorithm is different from fuzzy clustering
\r\ntechniques because objects that overlap are assigned a membership
\r\nvalue of 1 (one) as opposed to a fuzzy membership degree. The
\r\nalgorithm is also different from other overlapping algorithms that
\r\nrequire a similarity threshold be defined a priori which can be
\r\ndifficult to determine by novice users.<\/p>\r\n","references":"[1] C.C. Aggarwal, C.K. Reddy. Data Clustering: Algorithms and\r\nApplications. CRC Press, 2014.\r\n[2] A.K. Jain, R.C. Dubes. Algorithms for Clustering Data. Prentice Hall,\r\n1988.\r\n[3] E. Boundaillier, G. Hebrail. Interactive interpretation of hierarchical\r\nclustering. Intell. Data Anal. 1998.\r\n[4] O.A. Abbas. Comparisons between Data Clustering Algorithms. The\r\nInternational Arab Journal of Information Technology, Vol 5. No. 3.\r\n2008.\r\n[5] F. H\u00f6ppner, F. Klawonn, R. Kruse, T. Runkler, Fuzzy Cluster Analysis:\r\nMethods for Classification, Data Analysis and Image Recognition,\r\nWiley, 1999.\r\n[6] B. S. Everitt, S. Landau, M. Leese, \u201cCluster Analysis\u201d, Arnold\r\nPublishers, 2001\r\n[7] A. Jaini. Data Clustering: 50 years beyond k-means. Pattern Recognition\r\nLetters, 31(8): pp. 651-666, 2010.\r\n[8] E.R. Hruschkaet. al. A survey of Evolutionary Algorithms for\r\nClustering. IEEE Trans. Vol. 39, pp. 133-155, 2009.\r\n[9] J. C. Bezdek, Pattern Recognition with Fuzzy Objective Function\r\nAlgorithm, Plenum Press, 1981.\r\n[10] Y. Chen, H. Hu. An overlapping Cluster algorithm to provide nonexhaustive\r\nclustering. Presented at European Journal of Operational\r\nResearch. pp. 762-780, 2006\r\n[11] G. Cleuzious. An extended version of the k-means method for\r\noverlapping clustering. IEEE International Conference on Pattern\r\nRecognition. 2008\r\n[12] K. Bache, M. Lichman. UCI Machine Learning Repository\r\n(http:\/\/archive.ics.uci.edu\/ml). Irvine, CA: University of California,\r\nSchool of Information and Computer Science. 2013\r\n[13] N. Abdelhamid, A. Ayesh, F. Thabtah. Phishing detection based\r\nAssociative Classification data mining. Expert Systems with\r\nApplications Journal. Vol. 41 (13). 2014","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 98, 2015"}