Proceedings of the 11th international conference on World Wide Web
Toward alternative metrics of journal impact: a comparison of download and citation data
Information Processing and Management: an International Journal - Special issue: Infometrics
Co-authorship networks in the digital library research community
Information Processing and Management: an International Journal - Special issue: Infometrics
Citation analysis of database publications
ACM SIGMOD Record
Bibliometric impact measures leveraging topic analysis
Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries
Using citations for ranking in digital libraries
Proceedings of the 6th ACM/IEEE-CS joint conference on Digital libraries
Learning to assess the quality of scientific conferences: a case study in computer science
Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
Yet another paper ranking algorithm advocating recent publications
Proceedings of the 19th international conference on World wide web
ECDL'09 Proceedings of the 13th European conference on Research and advanced technology for digital libraries
Analysis of computer science communities based on DBLP
ECDL'10 Proceedings of the 14th European conference on Research and advanced technology for digital libraries
A decade of database research publications: a look inside
Scientometrics
Local computation of PageRank: the ranking side
Proceedings of the 20th ACM international conference on Information and knowledge management
Constructing seminal paper genealogy
Proceedings of the 20th ACM international conference on Information and knowledge management
ICADL'11 Proceedings of the 13th international conference on Asia-pacific digital libraries: for cultural heritage, knowledge dissemination, and future creation
Comparing paper ranking algorithms
Proceedings of the South African Institute for Computer Scientists and Information Technologists Conference
Towards an effective and unbiased ranking of scientific literature through mutual reinforcement
Proceedings of the 21st ACM international conference on Information and knowledge management
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Ranking of publication venues is often closely related with important issues such as evaluating the contributions of individual scholars/research groups, or subscription decision making. The development of large-scale digital libraries and the availability of various meta data provide the possibility of building new measures more efficiently and accurately. In this work, we propose two novel measures for ranking the impacts of academic venues an easy-to-implement seed-based measure that does not use citation analysis, and a realistic browsing-based measure that takes an article reader's behavior into account. Both measures are computationally efficient yet mimic the results of the widely accepted Impact Factor. In particular, our proposal exploits the fact that: (1)in most disciplines, there are "top" venues that most people agree on; and (2) articles that appeared in good venues are more likely to be viewed by readers. Our proposed measures are extensively evaluated on a test case of the Database research community using two real bibliography data sets - ACM and DBLP. Finally, ranks of venues by our proposed measures are compared against the Impact Factor using the Spearman's rank correlation coefficient, and their positive rank order relationship is proved with a statistical significance test.