Incorporating Relevant Knowledge in Context Modeling and Response Generation [article]

Yanran Li and Wenjie Li and Ziqiang Cao and Chengyao Chen
2018 arXiv   pre-print
To sustain engaging conversation, it is critical for chatbots to make good use of relevant knowledge. Equipped with a knowledge base, chatbots are able to extract conversation-related attributes and entities to facilitate context modeling and response generation. In this work, we distinguish the uses of attribute and entity and incorporate them into the encoder-decoder architecture in different manners. Based on the augmented architecture, our chatbot, namely Mike, is able to generate responses
more » ... by referring to proper entities from the collected knowledge. To validate the proposed approach, we build a movie conversation corpus on which the proposed approach significantly outperforms other four knowledge-grounded models.
arXiv:1811.03729v1 fatcat:xefjcsi7yfdojpyyuiv2xftdi4