A Clustering Method Based on Linguistic Similarity Matrices
Fan Zhi-ping · Systems Engineering · 2004
With respect to clustering analysis problems with the linguistic similarity matrices provided by multiple experts, a new net-making clustering analysis method is proposed. In this paper, firstly, the clustering analysis problem with linguistic similarity matrices is described, and the two-tuple linguistic concept and its operator developed in recent years are (introduced.) Secondly, based on the approach to two-tuple linguistic processing, linguistic similarity matrices given by (experts) are transformed into the form of two-tuple linguistic, and the two-tuple linguistic aggregation operator is used to (aggregate) the linguistic similarity matrix given by each expert into the group one. Then, according to the basic ideas of (traditional) net-making clustering method, the calculation steps of the clustering analysis method with linguistic similarity (matrices) is developed. Finally, a numerical example is used to illustrate the method proposed in this paper.