关键词: 意图识别, 自然语言处理, 深度学习, 分类

Abstract: How to understand a user’s intention according to the context in multi-round chatting robots is a key and difficult issue. Most existing questions-understanding methods are for a single sentence, and focus on the understanding of a sentence structure. It is an urgent problem to be solved that how to identify the current user’s intention according to the context instead of analyzing each single round individually, which can make the dialogue have fine-grained understanding ability in a continuous context. In order to solve the above problems, this paper presents a method of multi-intention classification of natural language questions based on deep learning. The user intents include 13 categories, such as chatting, music, news, arithmetic, catering, booking, weather, service categories and so on. Firstly, this paper uses the technology of natural language processing to process and analyze multi-round dialogues, identifies the key words therein, and then constructs the dichotomous and multi-category deep learning model to learn contexts by using the deep learning method and the hierarchical classification technology, they are both used to identify user’s intention. Experiments show that the accuracy rate of user intention recognition with constructed deep learning model is 94.81% and 93.49% respectively. Therefore, the proposed method can basically solve the problem of understanding a user’s intention with natural question language.

Key words: intent identification, natural language processing, deep learning, classification