OWA-aggregated fuzzy similarity relations for journal ranking

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

7 Citations (SciVal)

Abstract

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.
Original languageEnglish
Title of host publicationProceedings of the 22nd International Conference on Fuzzy Systems
PublisherIEEE Press
Pages1-7
Number of pages7
ISBN (Print)978-1-4799-0020-6
DOIs
Publication statusPublished - 2013
EventFuzzy Systems - Hyderabad, Hyderabad, India
Duration: 07 Jul 201310 Jul 2013
Conference number: 22

Conference

ConferenceFuzzy Systems
Abbreviated titleFUZZ-IEEE-2013
Country/TerritoryIndia
CityHyderabad
Period07 Jul 201310 Jul 2013

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