Guiding Topic Flows in the Generative Chatbot by Enhancing the ConceptNet with the Conversation Corpora

Anonymous

Abstract: Human conversations consist of reasonable and natural topic flows, which are observed as the shifts of the mentioned concepts across utterances.Previous chatbots that incorporate the external commonsense knowledge graph prove that modeling the concept shifts can effectively alleviate the dull and uninformative response dilemma.However, there still exists a gap between the concept relations in the natural conversation and those in the external commonsense knowledge graph. Specifically, the concept relations in the external commonsense knowledge graph are not intuitively built from the conversational scenario but the world knowledge, which makes them insufficient for the chatbot construction.To bridge the above gap, we propose the method to supply more concept relations extracted from the conversational corpora and build an enhanced concept graph for the chatbot construction. We then introduce the enhanced graph to the response generation process with a designed network.Experimental results on the Reddit conversation dataset indicate our proposed method significantly outperforms strong baseline systems and achieves new SOTA results.Further analysis individually proves the effectiveness of the enhanced concept graph.

Paper Type: long