Riyam Rwedhi1 and Salam Al-augby2
1,2 Department of Computer Science, Faculty of Computer science and
Mathematics University of Kufa, Iraq
Email: riyamr.alabedi@student.uokufa.edu.iq- salam.alaugby@uokufa.edu.iq
DOI: 10.23918/ICABEP2022p31
Abstract
According to the high increase in research published and the difficulty of obtaining appropriate research attention, the recommendation systems can increase the affordability and availability of these papers, but the results may be inaccurate or there may be delays in recommending them. This is a real problem for researchers that causes a loss of their time and spend extra effort to reach the required research. This research is presented in order to solve this problem by using sentiment analysis, a presented recommendation system for papers is reviewed based on the researcher’s chosen topics or keywords. This research is used to build a future system to help in facilitating the process of searching for papers and giving researchers the relevant papers in the least time and with maximum accuracy. This work suggested that using the hybrid recommendation system may solve the cold start problem (one of the most significant problems in the recommendation system).
Keywords: Recommendation systems (RS), sentiment analysis (SA), scientific papers, hybrid recommender system.
ICABEP2022
4th International Conference on Accounting, Business, Economics and Politics