Zobrazeno 1 - 10
of 689
pro vyhledávání: '"Zhu Yongchun"'
Autor:
Zhang, Yuting, Wu, Yiqing, Han, Ruidong, Sun, Ying, Zhu, Yongchun, Li, Xiang, Lin, Wei, Zhuang, Fuzhen, An, Zhulin, Xu, Yongjun
Recommendation systems, which assist users in discovering their preferred items among numerous options, have served billions of users across various online platforms. Intuitively, users' interactions with items are highly driven by their unchanging i
Externí odkaz:
http://arxiv.org/abs/2407.00912
User preferences follow a dynamic pattern over a day, e.g., at 8 am, a user might prefer to read news, while at 8 pm, they might prefer to watch movies. Time modeling aims to enable recommendation systems to perceive time changes to capture users' dy
Externí odkaz:
http://arxiv.org/abs/2404.19357
Both accuracy and timeliness are key factors in detecting fake news on social media. However, most existing methods encounter an accuracy-timeliness dilemma: Content-only methods guarantee timeliness but perform moderately because of limited availabl
Externí odkaz:
http://arxiv.org/abs/2310.10429
Autor:
Hu, Beizhe, Sheng, Qiang, Cao, Juan, Zhu, Yongchun, Wang, Danding, Wang, Zhengjia, Jin, Zhiwei
Fake news detection has been a critical task for maintaining the health of the online news ecosystem. However, very few existing works consider the temporal shift issue caused by the rapidly-evolving nature of news data in practice, resulting in sign
Externí odkaz:
http://arxiv.org/abs/2306.14728
Autor:
Zhang, Yuting, Wu, Yiqing, Le, Ran, Zhu, Yongchun, Zhuang, Fuzhen, Han, Ruidong, Li, Xiang, Lin, Wei, An, Zhulin, Xu, Yongjun
Takeaway recommender systems, which aim to accurately provide stores that offer foods meeting users' interests, have served billions of users in our daily life. Different from traditional recommendation, takeaway recommendation faces two main challen
Externí odkaz:
http://arxiv.org/abs/2306.04370
Human activity recognition (HAR) is a time series classification task that focuses on identifying the motion patterns from human sensor readings. Adequate data is essential but a major bottleneck for training a generalizable HAR model, which assists
Externí odkaz:
http://arxiv.org/abs/2306.04641
Autor:
Wu, Yiqing, Xie, Ruobing, Zhang, Zhao, Zhu, Yongchun, Zhuang, FuZhen, Zhou, Jie, Xu, Yongjun, He, Qing
Recently, a series of pioneer studies have shown the potency of pre-trained models in sequential recommendation, illuminating the path of building an omniscient unified pre-trained recommendation model for different downstream recommendation tasks. D
Externí odkaz:
http://arxiv.org/abs/2305.03995
Both real and fake news in various domains, such as politics, health, and entertainment are spread via online social media every day, necessitating fake news detection for multiple domains. Among them, fake news in specific domains like politics and
Externí odkaz:
http://arxiv.org/abs/2209.08902
Autor:
Li, Shuokai, Zhu, Yongchun, Xie, Ruobing, Tang, Zhenwei, Zhang, Zhao, Zhuang, Fuzhen, He, Qing, Xiong, Hui
Conversational recommender systems (CRS) aim to capture user's current intentions and provide recommendations through real-time multi-turn conversational interactions. As a human-machine interactive system, it is essential for CRS to improve the user
Externí odkaz:
http://arxiv.org/abs/2207.00814
Autor:
Zhu, Yongchun, Sheng, Qiang, Cao, Juan, Nan, Qiong, Shu, Kai, Wu, Minghui, Wang, Jindong, Zhuang, Fuzhen
The wide spread of fake news is increasingly threatening both individuals and society. Great efforts have been made for automatic fake news detection on a single domain (e.g., politics). However, correlations exist commonly across multiple news domai
Externí odkaz:
http://arxiv.org/abs/2206.12808