[1]杨 阳,盛胜利,奚雪峰.基于知识图谱的多轮对话技术研究综述[J].计算机技术与发展,2023,33(04):27-33.[doi:10. 3969 / j. issn. 1673-629X. 2023. 04. 004]
　YANG Yang,SHENG Sheng-li,XI Xue-feng.Recovery of Multi-turn Dialogue Based on Knowledge Graph[J].,2023,33(04):27-33.[doi:10. 3969 / j. issn. 1673-629X. 2023. 04. 004]
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基于知识图谱的多轮对话技术研究综述()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
33
期数:
2023年04期
页码:
27-33
栏目:
综述
出版日期:
2023-04-10

文章信息/Info

Title:
Recovery of Multi-turn Dialogue Based on Knowledge Graph
文章编号:
1673-629X(2023)04-0027-07
作者:
杨 阳1; 2 ; 盛胜利3 ; 奚雪峰1; 2
1. 苏州科技大学 电子与信息工程学院,江苏 苏州 215009;
2. 苏州市虚拟现实智能交互及应用重点实验室(苏州科技大学),江苏 苏州 215009;
3. 数据分析实验室(德州理工大学),德克萨斯州 拉伯克市 79409
Author(s):
YANG Yang1; 2 ; SHENG Sheng-li3 ; XI Xue-feng1; 2
1. School of Electronic and Information Engineering,Suzhou University of Science and Technology,Suzhou 215009,China;
2. Suzhou Key Laboratory of Virtual Reality Intelligent Interaction and Application Technology,Suzhou University of Science and Technology,Suzhou 215009,China;
3. Data Analytics Lab,Soochow University ( Texas Tech University) ,Lubbock 79409,USA
关键词:
知识图谱; 多轮对话; 人机交互; 自然语言处理; 对话系统
Keywords:
knowledge graph; multi-turn dialogue; human-computer interaction; natural language processing; dialogue system
分类号:
TP18
DOI:
10. 3969 / j. issn. 1673-629X. 2023. 04. 004
摘要:
随着自然语言技术的不断进步与发展,人机交互取得了跨越式的进步。 然而,目前人机交互系统往往都是用户与机器双方在特定的应用场景下设计完成的,在开放域下进行难度较大的多轮对话效果差强人意。 而知识图谱作为实现对话系统的重要工具之一,其被证明在多轮对话任务中是有效的。 该文从基于知识图谱的多轮对话技术总结了多轮对话中使用的相关技术,其中基于知识图谱的多轮对话模型包括 TransE、TransH、TransR 和 TransD 等,以及涉及到基于知识图谱的多轮对话相关数据集及评价标准。 最后提出了基于知识图谱的多轮对话技术当前面临的挑战并进行了总结。
Abstract:
With the continuous progress and development of natural language technology,human-computer interaction has made a greatprogress. However,at present,human-computer interaction systems are often designed by both users and machines in specific applicationscenarios,and the effect of difficult multi-turn dialogue in open domain is not satisfactory. As one of the important tools to implement dialogue system,knowledge graph has been proved to be effective in multi - turn dialogue tasks. We summarize the related technologiesused in multi-turn dialogue from the multi-turn dialogue technology based on knowledge graph. The multi-turn dialogue model basedon knowledge graph includes TransE,TransH,TransR and TransD,as well as the related data sets and evaluation standards of multi-turndialogue based on knowledge graph. Finally, we put forward the current challenges of multi - turn dialogue technology based onknowledge graph and make a summary.

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更新日期/Last Update: 2023-04-10