An Efficient Clustering Sentence-Level Text Using a Novel Hierarchical Fuzzy Relational Clustering Algorithm

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Provided by: International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE)
Topic: Big Data
Format: PDF
In comparison with hard and soft clustering methods, in which a pattern belongs to a single cluster, fuzzy clustering algorithms allow patterns to belong to all clusters with differing degrees of membership. In Existing a novel fuzzy clustering algorithm that operates on relational input data; i.e., data in the form of a square matrix of pair-wise similarities between data objects. However, the major disadvantage of the Fuzzy Relational Eigenvector Centrality-based Clustering Algorithm (FRECCA) is its time complexity.
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