Maximal tree clustering method based on dyadic semantic information processing
Fan Zhi-ping · Systems engineering and electronics · 2006
With respect to multiple attribute clustering analysis problems with linguistic assessment information,a new maximal tree clustering analysis method is proposed.In the method,based on the traditional ideas of maximal tree clustering method,the dyadic semantic representation is used to process the linguistic assessment information,and the clustering objects are classified.The method has the characteristics of clear conception,simple calculation steps and exact information processing.Finally,a numerical example is given to illustrate the applicability of the proposed clustering method.