IRank: A Term-Based Innovation Ranking System for Conferences and Scholars

Authors:
Zhixu Li;Xiaoyong Du;Hongyan Liu;Jun He;Xiaofang Zhou
Affiliations:
Key Labs of Data Engineering and Knowledge Engineering, Ministry of Education, China and School of Information, Renmin University of China, Beijing, China;Key Labs of Data Engineering and Knowledge Engineering, Ministry of Education, China and School of Information, Renmin University of China, Beijing, China;Department of Management Science and Engineering, Tsinghua University, Beijing, China;Key Labs of Data Engineering and Knowledge Engineering, Ministry of Education, China and School of Information, Renmin University of China, Beijing, China;University of Queensland, Australia
Venue:
APWeb/WAIM '09 Proceedings of the Joint International Conferences on Advances in Data and Web Management
Year:
2009

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Abstract

Since the proposition of Journal Impact Factor [1] in 1963, the classical citation-based ranking scheme has been a standard criterion to rank journals and conferences. However, the reference of a paper cannot list all relevant publications and the citation relationships are not always available especially when related to copyright problem. Besides, we cannot evaluate a newly published paper before it is cited by others. Therefore, we propose an alternative method, term-based evaluation scheme which can evaluate publications by terms they use. Then we can rank conferences, journals and scholars accordingly. We think this term-based ranking scheme can be used to evaluate innovation quality for conferences and scholars. To evaluate our scheme and to facilitate its application, we develop an innovation ranking system called IRank to rank conferences and authors in the field of Database Systems . The performance of IRank demonstrates the effectiveness of our scheme.