论文标题
基于规则的对话系统中的终身知识学习
Lifelong Knowledge Learning in Rule-based Dialogue Systems
论文作者
论文摘要
当前聊天机器人或对话系统的主要弱点之一是，他们在部署后在对话中没有在线学习。这是一个重大的机会丧失。显然，每个人类用户都对可能对他人有用的世界有很多知识。如果聊天机器人可以在聊天期间向用户学习，它将大大扩展其知识库并更好地为用户服务。本文建议在基于规则的聊天机器人中构建这样的学习能力，以便它可以在与用户聊天时不断获取新知识。这项工作很有用，因为许多现实生活中部署的聊天机器人都是基于规则的。
One of the main weaknesses of current chatbots or dialogue systems is that they do not learn online during conversations after they are deployed. This is a major loss of opportunity. Clearly, each human user has a great deal of knowledge about the world that may be useful to others. If a chatbot can learn from their users during chatting, it will greatly expand its knowledge base and serve its users better. This paper proposes to build such a learning capability in a rule-based chatbot so that it can continuously acquire new knowledge in its chatting with users. This work is useful because many real-life deployed chatbots are rule-based.
