Knowledge Graphs are becoming a key technology for large-scale information processing systems containing massive collections of interrelated facts. Specifically, Knowledge Graphs provide the means for development of the newest data methods for data management, data fusion, data merging, and graph optimization and modeling, serving as a source of high quality data and a base for web-scale information integration.
The 2nd International Workshop on Machine Learning and Knowledge Graphs aims to be a meeting point for researchers and practitioners working on the latest advances in the intersection of machine learning technologies and knowledge graphs. Therefore, we welcome submissions of novel research that brings together the two topics of Machine Learning (ML) and Knowledge Graphs (KGs) either applying ML models for semantic data management structures (like KGs or ontologies), or by presenting newly assembled Knowledge Graphs that support the task of Machine Learning for certain application domains. Examples areas are Business Analytics, Customer Relationship Management, Fault Detection, Industry 4.0, or Social Networking.