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International Journal of Nonlinear Analysis and Applications، جلد ۱۴، شماره ۱، صفحات ۱۶۴۷-۱۶۵۴

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عنوان انگلیسی User recommendation system based on MIND dataset
چکیده انگلیسی مقاله Nowadays, it's a very significant way for researchers and other individuals to achieve their interests because it provides short solutions to satisfy their demands. Because there are so many pieces of information on the internet, news recommendation systems allow us to filter content and deliver it to the user in proportion to his desires and interests. RSs have three techniques: content-based filtering, collaborative filtering, and hybrid filtering. We will use the MIND dataset with our system, which was collected in 2019, the big challenge in this dataset because there is a lot of ambiguity and complex text processing. In this paper, will present our proposed recommendation system. The core of our system we have used the GloVe algorithm for word embeddings and representation. Besides, the Multi-head Attention Layer calculates the attention of words, to generate a list of recommended news. Finally, we achieve good results more than some other related works in AUC 71.211, MRR 35.72, nDCG@5 38.05, and nDCG@10 44.45.
کلیدواژه‌های انگلیسی مقاله News Recommendation System, Click Behavior, MIND Dataset, MIND-large, GloVe, NRMS

نویسندگان مقاله Niran A. Abdulhussein |
Faculty of Computer Science and Mathematics, University of Kufa, Iraq

Ahmed J Obaid |
Faculty of Computer Science and Mathematics, University of Kufa, Iraq


نشانی اینترنتی https://ijnaa.semnan.ac.ir/article_6857_781730ad637dcec8608c085cafeeda9d.pdf
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