A compact review of progress and prospects of deep learning in drug discovery
H Li, L Zou, JAH Kowah, D He, Z Liu, X Ding… - Journal of Molecular …, 2023 - Springer
Background Drug discovery processes, such as new drug development, drug synergy, and
drug repurposing, consume significant yearly resources. Computer-aided drug discovery …
drug repurposing, consume significant yearly resources. Computer-aided drug discovery …
A Survey on Recommendation Methods Based on Social Relationships
R Chen, K Pang, M Huang, H Liang, S Zhang, L Zhang… - Electronics, 2023 - mdpi.com
With the rapid development of online social networks recently, more and more online users
have participated in social network activities and rich social relationships are formed …
have participated in social network activities and rich social relationships are formed …
Mitigating sensitive data exposure with adversarial learning for fairness recommendation systems
Fairness is an important research problem for recommendation systems, and unfair
recommendation methods can lead to discrimination against users. Gender is a kind of …
recommendation methods can lead to discrimination against users. Gender is a kind of …
Hashing-based semantic relevance attributed knowledge graph embedding enhancement for deep probabilistic recommendation
Abstract Knowledge graph embedding (KGE) is effectively exploited in providing precise
and accurate recommendations from many perspectives in different application scenarios …
and accurate recommendations from many perspectives in different application scenarios …
CupMar: A deep learning model for personalized news recommendation based on contextual user-profile and multi-aspect article representation
In modern days, making recommendation for news articles poses a great challenge due to
vast amount of online information. However, providing personalized recommendations from …
vast amount of online information. However, providing personalized recommendations from …
KG2Lib: knowledge-graph-based convolutional network for third-party library recommendation
In the process of software system evolution, software users constantly put forward a large
number of expectations. For these expectations, software developers usually use the …
number of expectations. For these expectations, software developers usually use the …
SoURA: a user-reliability-aware social recommendation system based on graph neural network
Exploiting user trust information for developing a recommendation system has gained
increasing research interest in recent years. Due to the exchange of opinions about items …
increasing research interest in recent years. Due to the exchange of opinions about items …
Cognitive name-face association through context-aware graph neural network
The extraction of valuable insights from unstructured content has attracted much attention in
the last decades. Main results lie in the area of text mining, while the understanding of …
the last decades. Main results lie in the area of text mining, while the understanding of …
图神经网络推荐系统综述.
吴静， 谢辉， 姜火文 - … of Frontiers of Computer Science & …, 2022 - search.ebscohost.com
推荐系统(RS) 因信息冗杂繁多而诞生. 由于数据形式的多样化, 复杂化以及数据信息量稀疏性,
传统的推荐系统已经不能很好地解决目前的问题. 图神经网络(GNN) 能从图中对边和节点数据 …
传统的推荐系统已经不能很好地解决目前的问题. 图神经网络(GNN) 能从图中对边和节点数据 …
A multi-intent-aware recommendation algorithm based on interactive graph convolutional networks
J Zhang, H Gao, S Xiao, J Zhu, J Wang - Complex & Intelligent Systems, 2024 - Springer
In recent years, graph neural networks (GNNs) have been widely applied in recommender
systems. However, existing recommendation algorithms based on GNNs still face …
systems. However, existing recommendation algorithms based on GNNs still face …