[1]左敏,徐泽龙,张青川,等.基于双维度中文语义分析的食品领域知识库问答[J].郑州大学学报(工学版),2020,41(03):8-13.[doi:10.13705/j.issn.1671-6833.2020.02.003]
　Zuo Min,Xu Zelong,Zhang Qingchuan,et al.A question answering model over food domain knowledge base from two-dimensional Chinese semantic analysis[J].Journal of Zhengzhou University (Engineering Science),2020,41(03):8-13.[doi:10.13705/j.issn.1671-6833.2020.02.003]
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基于双维度中文语义分析的食品领域知识库问答()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
41
期数:
2020年03期
页码:
8-13
栏目:
出版日期:
2020-07-29

文章信息/Info

Title:
A question answering model over food domain knowledge base from two-dimensional Chinese semantic analysis
作者:
左敏; 徐泽龙; 张青川; 毕铭文
北京工商大学农产品食品安全追溯技术及应用国家工程实验室
Author(s):
Zuo Min; Xu Zelong; Zhang Qingchuan; Bi inscription
National Engineering Laboratory for Food Safety Traceability Technology and Application of Agricultural Products, Beijing Technology and Business University
关键词:
自然语言处理' target="_blank" rel="external">">自然语言处理; 知识库; 问答系统; 实体识别; 关系抽取; 
Keywords:
National Engineering Laboratory for Food Safety Traceability Technology and Application of Agricultural Products;  Beijing Technology and Business University
DOI:
10.13705/j.issn.1671-6833.2020.02.003
文献标志码:
A
摘要:
基于知识库的简单问答是自然语言处理中的一个研究热点，也是实际生活中应用最广泛的一种情况.然而在研究中文方面基于知识库问答的过程中，存在诸如不同处理过程间的错误传播，难以从关系名称表达不明确的问句中抽取关系等问题.本文在自主构建的食品领域知识库以及食品领域问答语料库的基础上，从中文词义和中文字义两个语义角度出发，利用两个维度进行实体链接，并且采用长短时记忆网络进行语义向量建模来抽取关系，提出一种基于双维度的中文语义分析的食品领域知识库问答模型.实验结果表明，本文提出的模型在中文食品领域知识库问答上能达到85.66%的准确率.
Abstract:
Simple Question Answering over Knowledge Bases (KB-QA) is a hot topic in Natural Language Processing (NLP) research, and it is also the most widely used case in real life. However, in the process of researching Chinese KB-QA, there are still many technical challenges such as extracting relations from questions which relation names are ambiguous, also have problems such as error propagation between different processes. Based on the self-built food domain knowledge base (FD-KB) and the food field corpus, this paper starts from the two semantic perspectives of Chinese characters and Chinese words to extract relations and mitigate the error propagation. Contrast experimental results show, the model of two-dimensional Chinese semantic analysis that proposed here can get the accuracy of 85.66%.

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更新日期/Last Update: 2020-07-28