Case Studies and Outcomes 11.1

Industry


Real world, business-focused success stories of how knowledge graphs, ontologies, and AI have been applied to address business needs.  The track will focus on return on investment and value to organizations.

Time: 
Thursday, April 23, 2020 - 14:30 to 16:00

Talks

Integrating Language Models and Knowledge Graphs for Enterprise Data Management

Identification of entities and the relations between them is a difficult task for traditional pattern-based matching or machine learning approaches; these techniques rapidly overfit training datasets and struggle to transfer to other contexts or domains. Utilizing outside knowledge, such as facts contained in a knowledge base or ontology, seems to be a solution to the lack of transferability. However, integrating unstructured text data and language models with highly structured resources such as knowledge bases is a challenging research problem.