Information retrieval by constrained spreading activation in semantic networks
Information Processing and Management: an International Journal - Artificial Intelligence and Information Retrieval
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
When is the classroom assignment problem hard?
Operations Research - Supplement
Recommending and evaluating choices in a virtual community of use
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
The k-cardinality assignment problem
GO-II Meeting Proceedings of the second international colloquium on Graphs and optimization
Recommendation as classification: using social and content-based information in recommendation
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Jester 2.0 (poster abstract): evaluation of an new linear time collaborative filtering algorithm
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Web-collaborative filtering: recommending music by crawling the Web
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
The journal review process: a manifesto for change
Communications of the AIS
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
The Assignment Problem with Seniority and Job Priority Constraints
Operations Research
Optimal Allocation of Proposals to Reviewers to Facilitate Effective Ranking
Management Science
A Paper Recommendation Mechanism for the Research Support System Papits
DEEC '05 Proceedings of the International Workshop on Data Engineering Issues in E-Commerce
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
A Hybrid Knowledge and Model Approach for Reviewer Assignment
HICSS '07 Proceedings of the 40th Annual Hawaii International Conference on System Sciences
An algorithm to determine peer-reviewers
Proceedings of the 17th ACM conference on Information and knowledge management
Technical paper recommendation: a study in combining multiple information sources
Journal of Artificial Intelligence Research
Challenge: how IJCAI 1999 can prove the value of AI by using AI
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Probabilistic latent semantic analysis
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Citation recommendation without author supervision
Proceedings of the fourth ACM international conference on Web search and data mining
ELIxIR: Expertise Learning and Identification x Information Retrieval
International Journal of Information Systems and Social Change
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Research into Reviewer Assignment Problem (RAP) is still in its early stage but there is great world-wide interest, as the foregoing process of peer-review which is the brickwork of science authentication. The RAP approach can be divided into three phases: identifying assignment procedure, computing the matching degree between manuscripts and reviewers, and optimizing the assignment so as to achieve the given objectives. Methodologies for addressing the above three phases have been developed from a variety of research disciplines, including information retrieval, artificial intelligent, operations research, etc. This survey is not only to cover variations of RAP that have appeared in the literature, but also to identify the practical challenge and current progress for developing intelligent RAP systems.