Mining and Learning on Graphs Workshop at KDD 2023

Neil Shah, Shobeir Fakhraei, Da Zheng, Bahare Fatemi, Leman Akoglu
Event MLG @ KDD 2023
Research Areas Graph Machine Learning

There is a great deal of interest in analyzing data that is best represented as a graph. Examples include the WWW, social networks, biological networks, communication networks, transportation networks, energy grids, and many others. These graphs are typically multi-modal, multi-relational and dynamic. In the era of big data, the importance of being able to effectively mine and learn from such data is growing, as more and more structured and semi-structured data is becoming available. The workshop serves as a forum for researchers from a variety of fields working on mining and learning from graphs to share and discuss their latest findings.