TY - JOUR ID - 1860 TI - A Recommendation System for Finding Experts in Online Scientific Communities JO - Journal of AI and Data Mining JA - JADM LA - en SN - 2322-5211 AU - Javadi, S. AU - Safa, R. AU - Azizi, M. AU - Mirroshandel, Seyed A. AD - Department of Computer Engineering, University of Guilan, Rasht, Iran. Y1 - 2020 PY - 2020 VL - 8 IS - 4 SP - 573 EP - 584 KW - Big Scholarly Data KW - Online Scientific Communities KW - Recommender Systems KW - Expert Finding Systems KW - IEEE DO - 10.22044/jadm.2020.9087.2045 N2 - 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. UR - https://jad.shahroodut.ac.ir/article_1860.html L1 - https://jad.shahroodut.ac.ir/article_1860_f98865a0e9bc7bd6497434f7c37ec13f.pdf ER -