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Zhaoxuan Liu and Wenjie Luo
In recommendation models, bias can distort the distribution of user-generated data, leading to inaccurate representation of user preferences. Failure to filter out biased data can result in significant learning errors, ultimately reducing the accuracy of...
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Wei Chen, Yihao Zhang, Yantuan Xian and Yonghua Wen
Tremendous academic articles face serious information overload problems while supporting literature searches. Finding a research article in a relevant domain that meets researchers? requirements is challenging. Hence, different paper recommendation model...
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Zhuoming Xu, Hanlin Liu, Jian Li, Qianqian Zhang and Yan Tang
Knowledge graph-based recommendation methods are a hot research topic in the field of recommender systems in recent years. As a mainstream knowledge graph-based recommendation method, the propagation-based recommendation method captures users? potential ...
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Wenchao Li, Xin Liu, Chenggang Yan, Guiguang Ding, Yaoqi Sun and Jiyong Zhang
The rapidly growing location-based social network (LBSN) has become a promising platform for studying users? mobility patterns. Many online applications can be built based on such studies, among which, recommending locations is of particular interest. Pr...
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