一种基于命名实体识别增强的对话状态追踪生成方法  

A dialogue state tracking technique enhanced by named entity recognition

作　　者：欧中洪 戴敏江 谭言信 宋美娜[1] OU Zhonghong;DAI Minjiang;TAN Yanxin;SONG Meina(School of Computer Science(National Pilot Software Engineering School),Beijing University of Posts and Telecommunications,Beijing 100876,China)

机构地区：[1]北京邮电大学计算机学院(国家示范性软件学院),北京100876

出　　处：《陕西师范大学学报（自然科学版）》2022年第3期112-120,共9页Journal of Shaanxi Normal University：Natural Science Edition

基　　金：国家重点研发计划专项(2017YFB1400800)。

摘　　要：提出一种基于序列标注同时充分利用本体知识增强命名实体识别能力的端到端方法完成对话状态追踪。一方面通过设计命名实体识别指针,基于序列标注方法对对话历史包含的本体知识信息进行标注,有效利用槽值对本体集增强命名实体识别能力;另一方面利用指针网络,保留新槽值识别的优点。实验结果表明,本文提出的方法相比现有模型在命名实体识别的能力上提升了1.2%,并保留槽值识别可扩展的优点。An end-to-end method based on sequence labeling while making full use of ontology knowledge to enhance the ability of named entity recognition to complete dialogue state tracking is proposed.On the one hand,this method uses a named entity recognition pointer to label the ontology knowledge information contained in the dialogue history based on the sequence labeling method and effectively uses the slot value to enhance the named entity recognition ability of the ontology set.On the other hand,the pointer network is used to retain the ability of the new slot value recognition.The experimental results show that the method proposed in this paper improves the ability of named entity recognition by 1.2%compared with the existing model,and retains the advantages of new slot recognition scalability.

关 键 词：对话状态追踪 指针网络 命名实体识别 深度学习 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]