When dealing with large graphs, such as those that arise in the context of online social networks, a subset of nodes may be labeled. These labels can indicate demographic values, interest, beliefs or other characteristics of the nodes (users). A core problem is to use this information to ex...
As we know, node classification in social networks is an important challenge for understanding the underlying graph with the linkage structure and node features. Compared with the traditional classification problem, we should not only use the node features, but also consider about the relationship ...
Node classification in social networks has been proven to be useful in many real-world applications. The vast majority of existing algorithms focus on unsigned social networks (or social networks with only positive links), while little work exists for signed social networks. It is evident from rec...
Node classification in signed social networks for SDM 2016 by Jiliang Tang et al.
Label-dependent Feature Extraction in Social Networks for Node Classification,程序员大本营,技术文章内容聚合第一站。
Graph Classification: 对整个图进行分类。 Node Clustering: 根据连接性将相似的节点分组。 Link Prediction: 预测缺失的链接。 Influence Maximization: 识别有影响的节点。 Extending Convolutions to Graphs 卷积神经网络在图像中提取特征方面是非常强大的。而图像本身可以看作是一种非常规则的网格状结构的图,其中单个像...
Motivated by the rise of social networks, as well as their applications in fields such as genetics or marketing, the node classification problem is one of the most actively researched topics within network-based machine learning. In contrast to methodologies based on neural networks or relational pr...
According to Burt's structural hole theory31, the structural position of a node in a social network is more important than the corresponding strength of external relationships, since better structural positions have more information, resources, and power. Location advantages in social networks ...
GAT algorithm takes node labels as supervised information and can achieves high node classification accuracy. However in real world, node labels are rare. There are only some citation networks and protein interaction networks that have supervised node label information. The scarcity of node labels ...
In recent years, there have been remarkable advancements in node classification achieved by Graph Neural Networks (GNNs). However, they necessitate abundant high-quality labels to ensure promising performance. In contrast, Large Language Models (LLMs) exhibit impressive zero-shot proficiency on text-...