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Cited by 3 publications
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References 28 publications
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“…Indeed, Giannoukos et al (2010) proposed a ranking of the most suitable reviewers for each author by means of artificial neural networks. In order to train the model, the reviewers' feedback usefulness serve as outputs from the network while inputs are built on the basis of a combination of the authors and reviewers profiles.…”
Section: Optimization Of Learner Matching In Pamentioning
confidence: 99%
“…Indeed, Giannoukos et al (2010) proposed a ranking of the most suitable reviewers for each author by means of artificial neural networks. In order to train the model, the reviewers' feedback usefulness serve as outputs from the network while inputs are built on the basis of a combination of the authors and reviewers profiles.…”
Section: Optimization Of Learner Matching In Pamentioning
confidence: 99%
“…Giannoukos, et al focus on peer-matching to improve feedback [8]. Their process involves assigning three to five reviewers based on criteria like proficiency, strictness, usefulness, and willingness to review.…”
Section: Improving Helpfulness By Matchingmentioning
confidence: 99%