Graph data mining in recommendation is currently a research topic attracts more and more attentions from industry and academic fields. In this half-day tutorial, we will present some key graph data mining methods and its applications in recommendation. We hope to find out the directions for the ...
2018. Graph Convolutional Neural Networks for Web-Scale Recommender Systems. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 974–983. ^abcJianing Sun, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Xiuqiang He, Chen Ma, and Mark ...
我个人觉得Text-Attributed-Graph会是一个比较有潜力的课题。相比于Data Mining & Recommender Systems上一些非常成熟的topic,目前在TAG上的研究还没到井喷式的阶段,还是能有比较多的工作可以展开。 TAG同时包含了图结构信息和文本信息,如何充分利用语言模型与图模型,实现更具表达力的节点表征,是一个挑战。已有工作G2P2...
In: Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining, pp 353–362. https://doi.org/10.1145/2939672.29396 Chen CM, Wang CJ, Tsai MF, Yang YH (2019) Collaborative similarity embedding for recommender systems. In: The world wide web conference, ...
Her research interests include graph neural networks, graph representation learning, graph data mining, recommender systems, etc. Lixin Cui received the Ph.D. degree from the University of Hong Kong, HKSAR, China, and both the B.Sc. and M.Sc. degrees from Tianjin University, Tianjin, China....
However, the huge amount of data also brings the problem of information overload, making it difficult for users to quickly find the content they are interested in. Therefore, recommender systems have become an important research topic in the field of information technology, which can be viewed ...
2022. "Graph Neural Networks in Recommender Systems: A Survey." ACM Computing Surveys 55 (5): 1–37. doi:10.1145/3535101. Wu, Yuankai, and Huachun Tan. 2016. "Short-term Traffic Flow Forecasting with Spatial-Temporal Correlation in a Hybrid Deep Learning Framework." arXiv preprint arXiv:...
As a result, graph learning5 is quickly standing out in many real-world applications such as the prediction of chemical properties of molecules for drug discovery6, recommender systems of social networks7 and combinatorial optimization for design automation8. In the era of Big Data and the ...
degree in Center for Research on Intelligent Perception and Computing (CRIPAC) at National Laboratory of Pattern Recognition (NLPR), Institute of Automation, Chinese Academy of Sciences (CASIA), Beijing, China. His research interests include data mining, machine learning, recommender systems, and ...
Graph neural networks in recommender systems: a survey ACM Computing Surveys, 55 (5) (2022), pp. 1-37 Google Scholar Xie, Lv et al., 2022 Xie Y., Lv S., Qian Y., Wen C., Liang J. Active and semi-supervised graph neural networks for graph classification IEEE Transactions on Big ...