Matt Gardner: Feature Generation from Knowledge Graphs

Matt Gardner: Feature Generation from Knowledge Graphs Abstract: A lot of attention has recently been given to the creation of large knowledge bases that contain millions of facts about people, things, and places in the world. In this talk I present methods for using these knowledge bases to generate features for machine learning models. These methods view the knowledge base as a graph which can be traversed to find potentially predictive information. I show how these methods can be applied to models of knowledge base completion, relation extraction, and question answering.