Event-Enhanced Learning for Knowledge Graph Completion
published: July 10, 2018, recorded: June 2018, views: 644
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Statistical learning of relations between entities is a popular approach to address the problem of missing data in Knowledge Graphs. In this work we study how this learning can be enhanced with background of a special kind: event logs, that are sequences of entities that may occur in the graph. Such background naturally occurs in many important applications. We propose various embedding models that combine entities of a Knowledge Graph and event logs. Our evaluation shows that our approach outperforms state-of-the-art baselines on real-world manufacturing and road traffic Knowledge Graphs, as well as in a controlled scenario that mimics manufacturing processes.
Download slides: eswc2018_ringsquandl_graph_completion_01.pdf (1.7 MB)
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !