Case Studies and Outcomes 1.1


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.

Wednesday, April 22, 2020 - 10:30 to 12:15


Explainable Reasoning over Knowledge Graphs for Recommendation and Reasoning

Incorporating knowledge graphs into recommender systems has attracted increasing attention in recent years. By exploring the interlinks within a knowledge graph, the connectivity between users and items can be discovered as paths, which provide rich and complementary information to user-item interactions. Such connectivity not only reveals the semantics of entities and relations, but also helps to comprehend a user’s interest.

“Answer Adjacent” in “Three” Clicks: Applying Semantic Technologies to JPL’s Structured and Unstructured Flight Project Data

At the Jet Propulsion Laboratory, finding experience and expertise is critical to mission success but is often a challenge. Job titles, official institution roles, and even work assignment data isn’t easily analyzed and cannot tell a complete story about specific experience. Records produced during a flight project’s lifecycle can hold the answers, but searching and finding the right information usually requires knowing the right person who knows the right data system to query and how to query it. Finding the person with a specific expertise may take weeks.