A Recommendation System for Finding Experts in Online Scientific Communities
Publish Year: 1399
Type: Journal paper
Language: English
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Document National Code:
JR_JADM-8-4_011
Index date: 10 May 2021
A Recommendation System for Finding Experts in Online Scientific Communities abstract
Online scientific communities are bases that publish books, journals, and scientific papers, and help promote knowledge. The researchers use search engines to find the given information including scientific papers, an expert to collaborate with, and the publication venue, but in many cases due to search by keywords and lack of attention to the content, they do not achieve the desired results at the early stages. Online scientific communities can increase the system efficiency to respond to their users utilizing a customized search. In this paper, using a dataset including bibliographic information of user’s publication, the publication venues, and other published papers provided as a way to find an expert in a particular context where experts are recommended to a user according to his records and preferences. In this way, a user request to find an expert is presented with keywords that represent a certain expertise and the system output will be a certain number of ranked suggestions for a specific user. Each suggestion is the name of an expert who has been identified appropriate to collaborate with the user. In evaluation using IEEE database, the proposed method reached an accuracy of 71.50 percent that seems to be an acceptable result.
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A Recommendation System for Finding Experts in Online Scientific Communities authors
S. Javadi
Department of Computer Engineering, University of Guilan, Rasht, Iran.
R. Safa
Department of Computer Engineering, University of Guilan, Rasht, Iran.
M. Azizi
Department of Computer Engineering, University of Guilan, Rasht, Iran.
Seyed A. Mirroshandel
Department of Computer Engineering, University of Guilan, Rasht, Iran.
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