基于RNN句子编码器的聊天机器人

Chatterbots Based on RNN Sentence Auto-encoder

人机对话是自然语言处理领域衍生的一项现实应用场景,根据现实获取的大量短文本知识数据,构建单轮短对话式智能应答聊天机器人。本文基于传统的信息检索式聊天机器人,引入循环神经网络(RNN)深度表征交互式知识库中短文本的语义向量,重构表达式语义空间。实验表明该编码向量的方法比传统的利用TF-IDF向量的方法效果更好。

Man-machine dialogue is a realistic application scenario which derived from the field of natural language processing.Based on the large amount of short text knowledge obtained from reality,the man-made short dialogue intelligent response chatterbot is constructed. Based on the traditional information retrieval typed chatterbot,the Recurrent Neural Network（ RNN） is introduced to characterize the semantic vector of short text in the interactive knowledge base and reconstructs the expression semantic space. Experiments show that the effect of the method of using the coding vector is improved compared with the traditional method of using TF-IDF vector.