Dskreg: Differentiable sampling on knowledge graph for recommendation with relational gnn
In the information explosion era, recommender systems (RSs) are widely studied and
applied to discover user-preferred information. A RS performs poorly when suffering from the …
applied to discover user-preferred information. A RS performs poorly when suffering from the …
Large-scale personalized video game recommendation via social-aware contextualized graph neural network
Because of the large number of online games available nowadays, online game
recommender systems are necessary for users and online game platforms. The former can …
recommender systems are necessary for users and online game platforms. The former can …
Finding core labels for maximizing generalization of graph neural networks
Graph neural networks (GNNs) have become a popular approach for semi-supervised graph
representation learning. GNNs research has generally focused on improving …
representation learning. GNNs research has generally focused on improving …
A graph is more than its nodes: Towards structured uncertainty-aware learning on graphs
Current graph neural networks (GNNs) that tackle node classification on graphs tend to only
focus on nodewise scores and are solely evaluated by nodewise metrics. This limits …
focus on nodewise scores and are solely evaluated by nodewise metrics. This limits …
Enhancement economic system based-graph neural network in stock classification
Y Xu, Y Zhang - IEEE Access, 2023 - ieeexplore.ieee.org
As a result of the integration of the stock industry into the entire international economic
system, stock companies publish hundreds of prospectuses every second. The ability to …
system, stock companies publish hundreds of prospectuses every second. The ability to …
Accelerating Sparse Graph Neural Networks with Tensor Core Optimization
KW Wu - arXiv preprint arXiv:2412.12218, 2024 - arxiv.org
Graph neural networks (GNNs) have seen extensive application in domains such as social
networks, bioinformatics, and recommendation systems. However, the irregularity and …
networks, bioinformatics, and recommendation systems. However, the irregularity and …
结合项目属性协作信号减少无关邻域的推荐.
赵文涛， 薛赛丽， 刘甜甜 - Journal of Computer Engineering …, 2024 - search.ebscohost.com
在推荐系统中, 知识图谱(knowledge graph, KG) 作为辅助信息, 提高了算法的性能以及可解释
性. 但在聚合多跳邻居时, 它通常把所有的实体信息加以聚合并传播. KG 中不是所有的信息都有 …
性. 但在聚合多跳邻居时, 它通常把所有的实体信息加以聚合并传播. KG 中不是所有的信息都有 …
Behavior Mining for Recommendation
Y Wang - 2024 - search.proquest.com
In the era of information explosion, recommender systems are crucial for mitigating user
information overload by filtering out irrelevant information and suggesting preferred items or …
information overload by filtering out irrelevant information and suggesting preferred items or …