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| Question Comprehension and Answer Organization for Scientific Education of Epidemics |
Cheng Zijia,Chen Chong( ) |
| School of Government, Beijing Normal University, Beijing 100875, China |
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Abstract [Objective] This study constructs a KGQA system based on the knowledge graph of epidemics, which improves the comprehension of user questions and organization of answers, aiming to effectively disseminate professional knowledge to the public. [Methods] First, we summarized users’ information needs based on multiple health information systems. Then, we combined the AC algorithm with BERT model to understand user queries and map the elements of questions to structured query statements. Third, we retrieved answers from the pre-constructed epidemic knowledge graph. Finally, we organized the answers with Flask framework and a variety of JS packages, which improved the front end interaction and presentation. [Results] The average accuracy of our new Q&A system was more than 90% and the proposed method is practical for specific domains. [Limitations] The knowledge of epidemic diseases was retrieved from the public dataset of AMiner platform and the Q&A coverage as well as the question types should to be expanded. [Conclusions] The proposed model optimizes the semantics of the question comprehension, as well as the organization of answers, which helps the public understand the professional knowledge effectively.
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Received: 21 September 2021
Published: 14 April 2022
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| Fund:National Social Science Fund of China(21BTQ065) |
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Corresponding Authors:
Chen Chong,ORCID：0000-0002-9704-1575
E-mail: chenchong@bnu.edu.cn
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| [1] |
欧阳学平. 论医学院校在医学科普宣传教育中作用之发挥[J]. 高校保健医学研究与实践, 2006, 3(1):61-62.
|
| [1] |
( Ouyang Xueping. On the Role of Medical Schools in the Publicity and Education of Medical Science[J]. Health Medicine Research and Practice in Higher Institutions, 2006, 3(1):61-62.)
|
| [2] |
孙素芬, 罗长寿, 魏清凤. Web农业实用技术自动问答系统设计实现[J]. 现代图书情报技术, 2009(7/8):70-74.
|
| [2] |
( Sun Sufen, Luo Changshou, Wei Qingfeng. Design and Implementation of Automatic Question-Answering System about Agricultural Operative Technology Based on Web[J]. New Technology of Library and Information Service, 2009(7/8):70-74.)
|
| [3] |
郑实福, 刘挺, 秦兵, 等. 自动问答综述[J]. 中文信息学报, 2002, 16(6):46-52.
|
| [3] |
( Zheng Shifu, Liu Ting, Qin Bing, et al. Overview of Question-Answering[J]. Journal of Chinese Information Processing, 2002, 16(6):46-52.)
|
| [4] |
阮彤, 王梦婕, 王昊奋, 等. 垂直知识图谱的构建与应用研究[J]. 知识管理论坛, 2016, 1(3):226-234.
|
| [4] |
( Ruan Tong, Wang Mengjie, Wang Haofen, et al. Research on the Construction and Application of Vertical Knowledge Graphs[J]. Knowledge Management Forum, 2016, 1(3):226-234.)
|
| [5] |
Bollacker K, Evans C, Paritosh P, et al. Freebase: A Collaboratively Created Graph Database for Structuring Human Knowledge[C]// Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data. ACM, 2008: 1247-1250.
|
| [6] |
Auer S, Bizer C, Kobilarov G, et al. DBpedia: A Nucleus for a Web of Open Data[C]// Proceedings of the 6th International Semantic Web and 2nd Asian Semantic Web Conference. 2007: 722-735.
|
| [7] |
付雷杰, 曹岩, 白瑀, 等. 国内垂直领域知识图谱发展现状与展望[J]. 计算机应用研究, 2021, 38(11):3201-3214.
|
| [7] |
( Fu Leijie, Cao Yan, Bai Yu, et al. Development Status and Prospect of Vertical Domain Knowledge Graph in China[J]. Application Research of Computers, 2021, 38(11):3201-3214.)
|
| [8] |
Singhal A. Introducing the Knowledge Graph, Things, Not Strings[EB/OL]. (2012-12-04). http://googleblog.blogspot.be/2012/05/introducing-knowledeg-graph-thingsnot.html.
|
| [9] |
Hashemi H B, Asiaee A, Kraft R. Query Intent Detection Using Convolutional Neural Networks[C]// Proceedings of International Conference on Web Search and Data Mining, Workshop on Query Understanding. 2016.
|
| [10] |
Reddy S, Täckström O, Collins M, et al. Transforming Dependency Structures to Logical Forms for Semantic Parsing[J]. Transactions of the Association for Computational Linguistics, 2016, 4:127-140.
doi: 10.1162/tacl_a_00088
|
| [11] |
Chen L H, Liang J Q, Xie C H, et al. Short Text Entity Linking with Fine-Grained Topics[C]// Proceedings of the 27th ACM International Conference on Information and Knowledge Management. 2018: 457-466.
|
| [12] |
马满福, 刘元喆, 李勇, 等. 基于LCN的医疗知识问答模型[J]. 西南大学学报(自然科学版), 2020, 42(10):25-36.
|
| [12] |
( Ma Manfu, Liu Yuanzhe, Li Yong, et al. An LCN-Based Medical Knowledge Base Question Answering Model[J]. Journal of Southwest University (Natural Science Edition), 2020, 42(10):25-36.)
|
| [13] |
曹明宇, 李青青, 杨志豪, 等. 基于知识图谱的原发性肝癌知识问答系统[J]. 中文信息学报, 2019, 33(6):88-93.
|
| [13] |
( Cao Mingyu, Li Qingqing, Yang Zhihao, et al. A Question Answering System for Primary Liver Cancer Based on Knowledge Graph[J]. Journal of Chinese Information Processing, 2019, 33(6):88-93.)
|
| [14] |
Haffner P, Tur G, Wright J H. Optimizing SVMs for Complex Call Classification[C]// Proceedings of 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing. 2003.
|
| [15] |
陈曙东, 欧阳小叶. 命名实体识别技术综述[J]. 无线电通信技术, 2020, 46(3):251-260.
|
| [15] |
( Chen Shudong, Ouyang Xiaoye. Overview of Named Entity Recognition Technology[J]. Radio Communications Technology, 2020, 46(3):251-260.)
|
| [16] |
陈永杰, 吾守尔·斯拉木, 于清. 一种基于Aho-Corasick算法改进的多模式匹配算法[J]. 现代电子技术, 2019, 42(4):89-93.
|
| [16] |
( Chen Yongjie, Wushour Silamu, Yu Qing. An Improved Multi-Pattern Matching Algorithm Based on Aho-Corasick Algorithm[J]. Modern Electronics Technique, 2019, 42(4):89-93.)
|
| [17] |
Huang Z H, Xu W, Yu K . Bidirectional LSTM-CRF Models for Sequence Tagging[OL]. arXiv Preprint, arXiv: 1508.01991.
|
| [18] |
Sakor A, Mulang I O, Singh K, et al. Old is Gold: Linguistic Driven Approach for Entity and Relation Linking of Short Text[C]// Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2019: 2336-2346.
|
| [19] |
Lei K, Zhang B, Liu Y, et al. A Knowledge Graph Based Solution for Entity Discovery and Linking in Open-Domain Questions[C]// Proceedings of the 2nd International Conference on Smart Computing and Communication. 2018: 181-190.
|
| [20] |
李贺, 刘嘉宇, 李世钰, 等. 基于疾病知识图谱的自动问答系统优化研究[J]. 数据分析与知识发现, 2021, 5(5):115-126.
|
| [20] |
( Li He, Liu Jiayu, Li Shiyu, et al. Optimizing Automatic Question Answering System Based on Disease Knowledge Graph[J]. Data Analysis and Knowledge Discovery, 2021, 5(5):115-126.)
|
| [21] |
刘思琴, 冯胥睿瑞. 基于BERT的文本情感分析[J]. 信息安全研究, 2020, 6(3):220-227.
|
| [21] |
( Liu Siqin, Feng Xuruirui. Text Sentiment Analysis Based on BERT[J]. Journal of Information Security Research, 2020, 6(3):220-227.)
|
| [22] |
董佳琳, 张宇航, 徐永康, 等. 基于知识图谱的新冠疫情智能问答系统[J]. 信息技术与信息化, 2021(6):258-261.
|
| [22] |
( Dong Jialin, Zhang Yuhang, Xu Yongkang, et al. Covid-19 Intelligent Question Answering System Based on Knowledge Graph[J]. Information Technology and Informatization, 2021(6):258-261.)
|
| [23] |
Bordes A, Chopra S, Weston J. Question Answering with Subgraph Embeddings[OL]. arXiv Preprint, arXiv:1406.3676.
|
| [24] |
Yih W T, Chang M W, He X D, et al. Semantic Parsing via Staged Query Graph Generation: Question Answering with Knowledge Base[C]// Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 2015: 1321-1331.
|
| [25] |
Davis F D. User Acceptance of Information Technology: System Characteristics, User Perceptions, and Behavioral Impacts[J]. International Journal of Man-Machine Studies, 1993, 38(3):475-487.
doi: 10.1006/imms.1993.1022
|
| [26] |
刘紫琪, 白旭, 程子佳, 等. 面向科技人才信息问答的查询需求及答案组织研究[J]. 文献与数据学报, 2021, 3(1):30-44.
|
| [26] |
( Liu Ziqi, Bai Xu, Cheng Zijia, et al. Study on Query Needs and Answer Organization of Scientific and Technological Talents Information Q&A[J]. Journal of Library and Data, 2021, 3(1):30-44.)
|
| [27] |
Wei J W, Zou K. EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks[OL]. arXiv Preprint, arXiv: 1901.11196
|
| [28] |
陈璟浩, 曾桢, 李纲. 基于知识图谱的“一带一路”投资问答系统构建[J]. 图书情报工作, 2020, 64(12):95-105.
|
| [28] |
( Chen Jinghao, Zeng Zhen, Li Gang. A Question Answering System for “The Belt and Road” Investment Based on Knowledge Graph[J]. Library and Information Service, 2020, 64(12):95-105.)
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