Conference Paper Assignment Using a Combined Greedy/Evolutionary Algorithm

This paper presents a method that combines a greedy and an evolutionary algorithm to assign papers submitted to a conference to reviewers. The evolutionary algorithm tries to maximize match between the referee expertise and the paper topics, with the constraints that no referee should get more paper...

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Hauptverfasser: Merelo-Guervós, Juan Julián, Castillo-Valdivieso, Pedro
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description This paper presents a method that combines a greedy and an evolutionary algorithm to assign papers submitted to a conference to reviewers. The evolutionary algorithm tries to maximize match between the referee expertise and the paper topics, with the constraints that no referee should get more papers than a preset maximum and no paper should get less reviewers than an established minimum, taking into account also incompatibilities and conflicts of interest. A previous version of the method presented on this paper was tested in another conference obtaining not only a good match, but also a high satisfaction of referees with the papers they have been assigned; the current version has been also applied on that conference data, and to the conference where this paper has been submitted; results were obtained in a short time, and yielded a good match between reviewers and papers assigned to them, better than a greedy algorithm. The paper finishes with some conclusions and reflections on how the whole submission and refereeing process should be conducted.
doi_str_mv 10.1007/978-3-540-30217-9_61
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Computer arithmetics</topic><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Average Match</topic><topic>Computer science; control theory; systems</topic><topic>Evolutionary Algorithm</topic><topic>Exact sciences and technology</topic><topic>Greedy Algorithm</topic><topic>Learning and adaptive systems</topic><topic>Soft Constraint</topic><topic>Theoretical computing</topic><topic>Tournament Size</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Merelo-Guervós, Juan Julián</creatorcontrib><creatorcontrib>Castillo-Valdivieso, Pedro</creatorcontrib><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Merelo-Guervós, Juan Julián</au><au>Castillo-Valdivieso, Pedro</au><au>Smith, Jim</au><au>Lozano, José A.</au><au>Burke, Edmund K.</au><au>Schwefel, Hans-Paul</au><au>Rowe, Jonathan E.</au><au>Yao, Xin</au><au>Merelo-Guervós, Juan Julián</au><au>Bullinaria, John A.</au><au>Tiňo, Peter</au><au>Kabán, Ata</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Conference Paper Assignment Using a Combined Greedy/Evolutionary Algorithm</atitle><btitle>Lecture notes in computer science</btitle><date>2004</date><risdate>2004</risdate><spage>602</spage><epage>611</epage><pages>602-611</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>9783540230922</isbn><isbn>3540230920</isbn><eisbn>3540302174</eisbn><eisbn>9783540302179</eisbn><abstract>This paper presents a method that combines a greedy and an evolutionary algorithm to assign papers submitted to a conference to reviewers. The evolutionary algorithm tries to maximize match between the referee expertise and the paper topics, with the constraints that no referee should get more papers than a preset maximum and no paper should get less reviewers than an established minimum, taking into account also incompatibilities and conflicts of interest. A previous version of the method presented on this paper was tested in another conference obtaining not only a good match, but also a high satisfaction of referees with the papers they have been assigned; the current version has been also applied on that conference data, and to the conference where this paper has been submitted; results were obtained in a short time, and yielded a good match between reviewers and papers assigned to them, better than a greedy algorithm. 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identifier ISSN: 0302-9743
ispartof Lecture notes in computer science, 2004, p.602-611
issn 0302-9743
1611-3349
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subjects Algorithmics. Computability. Computer arithmetics
Applied sciences
Artificial intelligence
Average Match
Computer science
control theory
systems
Evolutionary Algorithm
Exact sciences and technology
Greedy Algorithm
Learning and adaptive systems
Soft Constraint
Theoretical computing
Tournament Size
title Conference Paper Assignment Using a Combined Greedy/Evolutionary Algorithm
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