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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creator | Merelo-Guervós, Juan Julián Castillo-Valdivieso, Pedro |
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 |
format | Conference Proceeding |
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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.</description><identifier>ISSN: 0302-9743</identifier><identifier>ISBN: 9783540230922</identifier><identifier>ISBN: 3540230920</identifier><identifier>EISSN: 1611-3349</identifier><identifier>EISBN: 3540302174</identifier><identifier>EISBN: 9783540302179</identifier><identifier>DOI: 10.1007/978-3-540-30217-9_61</identifier><language>eng</language><publisher>Berlin, Heidelberg: Springer Berlin Heidelberg</publisher><subject>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</subject><ispartof>Lecture notes in computer science, 2004, p.602-611</ispartof><rights>Springer-Verlag Berlin Heidelberg 2004</rights><rights>2004 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c279t-9ed89249c54ce6b013fca353ee40db0fc470f3b445f2d244533a371f7114b3c93</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/978-3-540-30217-9_61$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/978-3-540-30217-9_61$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>309,310,775,776,780,785,786,789,4035,4036,27904,38234,41421,42490</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=16176975$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><contributor>Smith, Jim</contributor><contributor>Lozano, José A.</contributor><contributor>Burke, Edmund K.</contributor><contributor>Schwefel, Hans-Paul</contributor><contributor>Rowe, Jonathan E.</contributor><contributor>Yao, Xin</contributor><contributor>Merelo-Guervós, Juan Julián</contributor><contributor>Bullinaria, John A.</contributor><contributor>Tiňo, Peter</contributor><contributor>Kabán, Ata</contributor><creatorcontrib>Merelo-Guervós, Juan Julián</creatorcontrib><creatorcontrib>Castillo-Valdivieso, Pedro</creatorcontrib><title>Conference Paper Assignment Using a Combined Greedy/Evolutionary Algorithm</title><title>Lecture notes in computer science</title><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.</description><subject>Algorithmics. Computability. Computer arithmetics</subject><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Average Match</subject><subject>Computer science; control theory; systems</subject><subject>Evolutionary Algorithm</subject><subject>Exact sciences and technology</subject><subject>Greedy Algorithm</subject><subject>Learning and adaptive systems</subject><subject>Soft Constraint</subject><subject>Theoretical computing</subject><subject>Tournament Size</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>9783540230922</isbn><isbn>3540230920</isbn><isbn>3540302174</isbn><isbn>9783540302179</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2004</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNotkM1OwzAQhM2fRCl9Aw65cDS1vU5cH6uoFFAlONCz5Th2CCROZQekvj1OYS8jzcyuVh9Cd5Q8UELEUooVBpxzgoEwKrBUBT1DN5Cck8HP0YwWlGIALi_QIvWnjAGRjF2i2dTCUnC4RosYP0matCXzfIZeysE7G6w3NnvTBxuydYxt43vrx2wfW99kOiuHvmq9rbNtsLY-Ljc_Q_c9toPX4Zitu2YI7fjR36Irp7toF_86R_vHzXv5hHev2-dyvcOGCTliaeuVZFyanBtbVISCMxpysJaTuiLOcEEcVJznjtUsCYAGQZ2glFdgJMzR_d_dg45Gdy5ob9qoDqHt0z8qgRCFFHnqsb9eTJFvbFDVMHxFRYmaqKpESYFKnNQJopqowi-9ZWT1</recordid><startdate>2004</startdate><enddate>2004</enddate><creator>Merelo-Guervós, Juan Julián</creator><creator>Castillo-Valdivieso, Pedro</creator><general>Springer Berlin Heidelberg</general><general>Springer</general><scope>IQODW</scope></search><sort><creationdate>2004</creationdate><title>Conference Paper Assignment Using a Combined Greedy/Evolutionary Algorithm</title><author>Merelo-Guervós, Juan Julián ; Castillo-Valdivieso, Pedro</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c279t-9ed89249c54ce6b013fca353ee40db0fc470f3b445f2d244533a371f7114b3c93</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2004</creationdate><topic>Algorithmics. Computability. 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. The paper finishes with some conclusions and reflections on how the whole submission and refereeing process should be conducted.</abstract><cop>Berlin, Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/978-3-540-30217-9_61</doi><tpages>10</tpages></addata></record> |
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identifier | ISSN: 0302-9743 |
ispartof | Lecture notes in computer science, 2004, p.602-611 |
issn | 0302-9743 1611-3349 |
language | eng |
recordid | cdi_pascalfrancis_primary_16176975 |
source | Springer Books |
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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