Neural Approaches to Conversational AI

作者：Jianfeng Gao, Michel Galley, Lihong Li · 发表于：Foundations and Trends® in Information Retrieval · 年份：2019 · DOI：10.1561/1500000074 · 被引用次数：205 · 研究领域：Topic Modeling、Speech and dialogue systems、Advanced Text Analysis Techniques

The present paper surveys neural approaches to conversational AI that have been developed in the last few years. We group conversational systems into three categories: (1) question answering agents, (2) task-oriented dialogue agents, and (3) chatbots. For each category, we present a review of state-of-the-art neural approaches, draw the connection between them and traditional approaches, and discuss the progress that has been made and challenges still being faced, using specific systems and models as case studies.