检索式聊天机器人技术综述

With the rapid progress of natural language processing techniques and the massive accessible conversational data on Internet,non-tasked oriented dialogue systems,also referred to as Chatbots,have achieved great success,and drawn attention from both academia and industry.Currently,there are two lines in chatbots research,retrieval-based chatbots and generation-based chatbots.Due to the fluent responses and low latency,retrieval-based chatbots is a common method in practice.This paperfirst briefly introduces the research background, basic structure and component modules of retrieval-based chatbots,and then illustrates the constraints of the response selection module and related data set in details.Subsequently,we summarize recent popular techniques for response selection problem,including:statistic method,representation-based neural network method,interaction-based neural network method,and pre-training-based method.Finally,we pose the challenges of chatbots and outline promising directions as future work.