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OWA aggregation of fuzzy similarity relations for journal ranking

Fuzzy similarity relations form the basis for many developments and applications of fuzzy systems. Measures of fuzzy similarity have been proposed in the literature for comparing objects. In this paper, aggregated fuzzy relations are generated between academic journals to compare their performance with respect to different journal impact indicators. In particular, various indicators may be employed to construct several distinctive fuzzy similarity relations, which may be subsequently combined via the use of the Ordered Weighted Average (OWA) operator. This proposed aggregated measure preserves reflexivity and symmetry, with T-transitivity conditionally preserved if appropriate weighting vectors are selected. Different similarity measures and weighting vectors are compared for the task of journal clustering, in an effort to estimate the ranking of academic journals. The results of experimental evaluation demonstrate that by using OWA-aggregated relations, simple techniques such as C-means can perform well in terms of standard accuracy and within-1 accuracy. The proposed method also exhibits the advantages of being more intuitive and interpretable.