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Ji-Yoon Kim and Chae-Kwan Lim
The electronic publication market is growing along with the electronic commerce market. Electronic publishing companies use recommendation systems to increase sales to recommend various services to consumers. However, due to data sparsity, the recommenda...
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Wenkai Ni, Yanhui Du, Xingbang Ma and Haibin Lv
One of the five types of Internet information service recommendation technologies is the personalized recommendation algorithm, and knowledge graphs are frequently used in these algorithms. RippleNet is a personalized recommendation model based on knowle...
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Xinhua Wang, Yuchen Wang, Lei Guo, Liancheng Xu, Baozhong Gao, Fangai Liu and Wei Li
Digital library as one of the most important ways in helping students acquire professional knowledge and improve their professional level has gained great attention in recent years. However, its large collection (especially the book resources) hinders st...
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Zhen Tian, Lamei Pan, Pu Yin and Rui Wang
The emergence of the recommendation system has effectively alleviated the information overload problem. However, traditional recommendation systems either ignore the rich attribute information of users and items, such as the user?s social-demographic fea...
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Mingxuan Sun, Fei Li and Jian Zhang
Collaborative filtering (CF) approaches, which provide recommendations based on ratings or purchase history, perform well for users and items with sufficient interactions. However, CF approaches suffer from the cold-start problem for users and items with...
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