Many real-world datasets come in the form of graphs. These datasets include social networks, biological networks, knowledge graphs, the World Wide Web, and many more. Having a comprehensive understanding of these networks is essential to truly understand many important applications.
This course introduces the fundamental concepts and tools used in modeling large-scale graphs and knowledge graphs. You will learn a spectrum of techniques used to build applications that use graphs and knowledge graphs. These techniques range from traditional data analysis and mining methods to the emerging deep learning and embedding approaches.
From Graph to Knowledge Graph – Algorithms and Applications
This course may be unavailable.
Overview
Syllabus
- Module 1: Introduction and Overview
- Module 2: Graph Properties and Applications
- Module 3: Graph Representation Learning
- Module 4: Knowledge Graph Fundamentals and Construction
- Module 5: Knowledge Graph Inference and Applications
Taught by
Yuxiao Dong, Iris Shen and Hao Ma
