A comparative study of automated reviewer assignment methods

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dc.contributor.advisor Konstantinidis, Stavros
dc.creator Young, Joshua Peter
dc.date.accessioned 2013-09-19T18:56:01Z
dc.date.available 2013-09-19T18:56:01Z
dc.date.issued 2012
dc.identifier.other QA76.9 T48 Y68 2012
dc.identifier.uri http://library2.smu.ca/xmlui/handle/01/25211
dc.description vii, 75 leaves : ill. ; 29 cm.
dc.description Includes abstract.
dc.description Includes bibliographical references (leaves 55-60).
dc.description.abstract The reviewer assignment problem is the problem of determining suitable reviewers for papers submitted to journals or conferences. Automated solutions to this problem have used standard information retrieval methods such as the vector space model and latent semantic indexing. In this work we introduce two new methods. One method assigns reviewers using compression approximated information distance. This method approximates the Kolmogorov complexity of papers using their size when compressed by a compression program, and then approximates the relatedness of the papers using an information distance equation. This method performs better than standard information retrieval methods. The second method assigns reviewers using Google desktop a more advanced information retrieval system. The method searches for key terms from a paper needing reviewers in a set of papers written by possible reviewers and uses the search results as votes for reviewers. This method is relatively simple and is very effective for assigning reviewers. en_CA
dc.language.iso en en_CA
dc.publisher Halifax, N.S. : Saint Mary's University
dc.subject.lcc QA76.9.T48
dc.subject.lcsh Text processing (Computer science)
dc.subject.lcsh Information retrieval
dc.subject.lcsh Algorithms
dc.subject.lcsh Research -- Evaluation
dc.subject.lcsh Peer review
dc.title A comparative study of automated reviewer assignment methods en_CA
dc.type Text en_CA
thesis.degree.name Master of Science in Applied Science
thesis.degree.level Masters
thesis.degree.discipline Mathematics and Computing Science
thesis.degree.grantor Saint Mary's University (Halifax, N.S.)


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