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pro vyhledávání: '"Fu, Hao-Ming"'
Publikováno v:
RecSys 2020: Proceedings of the 14th ACM Conference on Recommender Systems, Pages 498 to 502
In the one-class recommendation problem, it's required to make recommendations basing on users' implicit feedback, which is inferred from their action and inaction. Existing works obtain representations of users and items by encoding positive and neg
Externí odkaz:
http://arxiv.org/abs/2401.10316
Autor:
Fu, Hao-Ming, Cheng, Pu-Jen
Publikováno v:
SIGIR 2019: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, Pages 1105 to 1108
Document representation is the core of many NLP tasks on machine understanding. A general representation learned in an unsupervised manner reserves generality and can be used for various applications. In practice, sentiment analysis (SA) has been a c
Externí odkaz:
http://arxiv.org/abs/2401.06210
Collaborative filtering (CF) is one of the most successful and fundamental techniques in recommendation systems. In recent years, Graph Neural Network (GNN)-based CF models, such as NGCF [31], LightGCN [10] and GTN [9] have achieved tremendous succes
Externí odkaz:
http://arxiv.org/abs/2203.15789