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An Improved Clustering Algorithm Using Fuzzy Relation for the Performance Evaluation of Humanistic Systems
Author(s) -
Beg Ismat,
Rashid Tabasam
Publication year - 2014
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.21689
Subject(s) - transitive closure , cluster analysis , partition (number theory) , computer science , fuzzy clustering , fuzzy logic , algorithm , data mining , mathematics , artificial intelligence , discrete mathematics , combinatorics
A hierarchical structure is proposed for the performance evaluation of vague, complicated humanistic systems. An improved fuzzy clustering algorithm is developed to produce several partition trees with different levels and clusters according to different triangular norm compositions. Additionally, a fuzzy clustering algorithm is given to produce a partition tree without using the transitive closure composition. The usefulness of the proposed algorithm is illustrated by an example of actual academic data.