期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2014
卷号：5
期号：4
页码：9-11
语种：English
出版社：Ayushmaan Technologies
摘要：Fuzzy clustering algorithms let configurations to belong to all clusters with different degrees of membership. A novel fuzzy clustering algorithm that works on relational input data; i.e., data in the arrangement of a square matrix of pairwise resemblances among data objects. The algorithm uses a graph representation of the data and functions in an Expectation-Maximization framework in which the graph centrality of an entity in the graph is interpreted as a possibility. Results of relating the algorithm to sentence clustering errands determine that the algorithm is capable of categorizing coinciding clusters of semantically related sentences and that it is consequently of latent use in a variety of text mining tasks.
关键词：Hierarchical Fuzzy Relational Clustering;Fuzzification Degree; Hard Clustering;Soft Clustering
