数据库驱动的对话机器人技术实现

Research on Database-driven Chatbot

世界上很多高价值的数据信息储存在关系数据库中,访问这些数据需要掌握专门的结构化查询语言(SQL),普通人很难直接使用。基于对现有对话机器人存在的问题和相关关键技术的梳理,本文融合了数据仓库、数据同步、数据库查询、消息推送、自然语言理解及语音识别等相关技术及产品,设计了数据库驱动的对话机器人。方案可以实现用户理解、消息推送、事实数据查询和分析数据查询四个功能,使得用户能够快速地获取信息。本文提出的数据库驱动的对话机器人具有较强的泛化性和可扩展性。

Many high-value data in the world are stored in relational databases.Access to these data requires a special Structured Query Language(SQL),which is difficult for ordinary people to use directly.Aiming at problems of the existing chatbot,this paper proposes to design database-driven chatbots by integrating related technologies and products,such as data warehouse,data synchronization,database query,message push,natural language understanding and speech recognition.The solution realizes four functions:user understanding,message push,fact-data query and analysis-data query,so that users can quickly obtain information.Database-driven chatbots proposed in this paper has a capability of strong generalization and scalability that enable chatbots to work with data-driven conversations.