Link-based methods for bibliometric journal ranking

Pan Su, Qiang Shen

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


The ISI Impact Factor is widely accepted as a possible measurement of academic journal quality. However, much debate has recently surrounded this use, and several complex alternatives have been reported. In this paper, a link-based framework for academic output is proposed, where publications, journals and authors are represented as three sets of nodes in a multi-layered and inter-connected network. Several existing indicators of journal impact are analysed and redefined by the links between the nodes. Furthermore, the indicators are combined and transformed to fused-links between journals, which are further applied to supervised and unsupervised learning methods in order to evaluate impact as well as predict ranks of journals. The link-based framework is explicable and intuitive. The experimental evaluation demonstrates that by applying the proposed fused-links to K-means clustering, the detected clusters are consistent with the ranking of expert reviewers. For journal rank prediction, the accuracy of modified K-nearest-neighbour approaches based on the fused-links is greater than other conventional methods such as the decision tree based approach
Original languageEnglish
Title of host publication Proceedings of the 2012 UK Workshop on Computational Intelligence
PublisherIEEE Press
Number of pages8
ISBN (Print)978-1-4673-4391-6
Publication statusPublished - 2012
Event2012 12th UK Workshop on Computational Intelligence (UKCI) - Edinburgh, United Kingdom of Great Britain and Northern Ireland
Duration: 05 Sept 201207 Sept 2012


Conference2012 12th UK Workshop on Computational Intelligence (UKCI)
Country/TerritoryUnited Kingdom of Great Britain and Northern Ireland
Period05 Sept 201207 Sept 2012


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