Automating the assignment of submitted manuscripts to reviewers
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
An algorithm for automated rating of reviewers
Proceedings of the 1st ACM/IEEE-CS joint conference on Digital libraries
Mining for proposal reviewers: lessons learned at the national science foundation
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Measuring credibility of users in an e-learning environment
Proceedings of the 16th international conference on World Wide Web
Technical paper recommendation: a study in combining multiple information sources
Journal of Artificial Intelligence Research
Learning to recommend with trust and distrust relationships
Proceedings of the third ACM conference on Recommender systems
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In this paper, we propose a novel approach called, Reviewers Authority Testing and Evaluation (RATE), to improve the effectiveness of a manuscript review process. In the proposed RATE approach, we define a RATE model to express a manuscript review process mathematically. We then design a RATE algorithm to rank the authority of each reviewer in the RATE model and consequently calculate the quality score for each manuscript. The experimental results demonstrate that the performance of the RATE algorithm is superior to existing approaches. Furthermore, the experiments on testing algorithm's parameter settings also demonstrate that the proposed RATE algorithm behaves effectively and stably.