Recommended Readings:
- J. Z. Pan, An Introduction to Knowledge Graphs, Tutorial at the BIAS2021 summer school, 2021.
- F. Baader, I. Horrocks, C. Lutz, and U. Sattler: An Introduction to Description Logic. Cambridge University Press 2017.
- J. Z. Pan, G. Vetere, J. M. Gómez-Pérez, H. Wu (Eds.): Exploiting Linked Data and Knowledge Graphs in Large Organisations. Springer 2017.
- R. Brachman and H. Levesque: Knowledge Representation and Reasoning. Morgan Kaufmann 2014.
- M. Nickel, K. Murphy, V. Tresp, and E. Gabrilovich: A Review of Relational Machine Learning for Knowledge Graphs. Proceedings of the IEEE, Volume 104. 2015.
- D. Ruffinelli, S. Broscheit, and R. Gemulla: You CAN Teach an Old Dog New Tricks! On Training Knowledge Graph Embeddings. ICLR 2020
- W. Hamilton: Graph Representation Learning Book (Chapter 1: Node Embeddings). Morgan & Claypool 2020
- I. Goodfellow, Y. Bengio, and A. Courville: Deep Learning (Chapter 5: Machine Learning Basics; Chapter 7: Regularization for Deep Learning; Chapter 8: Optimization for Training Deep Models; Chapter 15: Representation Learning). MIT Press 2016.
Optional Readings:
- J. Z. Pan, S. Staab, U. Aßmann, J. Ebert, Y. Zhao (Eds.): Ontology-Driven Software Development. Springer 2013.
Additional Links:
- Google & KG: Introducing the Knowledge Graph: things, not strings. What Is the Google Knowledge Graph & How Does It Work?
- Meta & KG: Knowledge Graph Metadata: What Facebook really knows about you?
- Microsoft & KG: Overview of Microsoft Graph Microsoft Academic Knowledge Graph (MAKG)
- Amazon & KG: Knowledge Graphs on AWS Using knowledge graphs to streamline COVID-19 research
- IBM & KG: Use cases of Knowledge Graphs