Towards a Dialogue System with Long-term, Episodic Memory

Intelligent personal assistants lack longterm memory. We propose graph databases as a extensible solution to this problem by representing relevant knowledge as entities, properties, and relations between them. We demonstrate through two experiments that our approach lends itself to a system that can improve natural language understanding by updating its knowledge dynamically in a generalizable and interpretable fashion.