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2020 , Vol. 64 >Issue 12: 95 - 105

DOI: https://doi.org/10.13266/j.issn.0252-3116.2020.12.011

A Question Answering System for “the Belt and Road” Investment Based on Knowledge Graph

  • Chen Jinghao ,
  • Zeng Zhen ,
  • Li Gang
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  • 1. School of Public Policy and Management, Guangxi University, Nanning 530004;
    2. School of Information, Guizhou University of Finance and Economics, Guiyang 550025;
    3. Center for the Studies of Information Resources of Wuhan University, Wuhan 430072

Received date: 2020-01-04

  Revised date: 2020-04-12

  Online published: 2020-06-20

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Abstract

[Purpose/significance] The question answering system for "the Belt and Road" investment has important research and application significance. It can effectively integrate information from multiple sources and provide user with fast, accurate and high-quality "the Belt and Road" investment information.[Method/process] Firstly, the information which related to the "the Belt and Road" investment was collected, processed and integrated. and then, under the guidance of experts, the "the Belt and Road" investment knowledge graph was constructed. On this basis, the functions of each part of question answering system were realized, including:question preprocessing, question classification, question template matching and answer query.[Result/conclusion] The result shows that, this system can effectively answer questions about "the Belt and Road" investment.

Key words： question answering system; knowledge graph; the Belt and Road; system construction

Cite this article

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 . DOI: 10.13266/j.issn.0252-3116.2020.12.011

References

[1] 邢厚媛."一带一路"战略下的投资促进研究[R].北京:商务部投资促进事务局,2017:2.
[2] 王雨萧,于佳欣. 我国对"一带一路"沿线国家直接投资超900亿美元[EB/OL].[2019-04-19].https://www.yidaiyilu.gov.cn/xwzx/gnxw/86349.htm.
[3] 郭天翼,彭敏,伊穆兰,等.自然语言处理领域中的自动问答研究进展[J].武汉大学学报(理学版),2019,65(5):417-426.
[4] 黄恒琪,于娟,廖晓,等.知识图谱研究综述[J].计算机系统应用,2019,28(6):1-12.
[5] BRILL E, LIN J, BANKO M, et al. Data-intensive question answering[C]//Trec. Tenth Text Retrieval conference. Gaithersburg:NIST,2001, 56:90.
[6] 王东升,王卫民,王石,等.面向限定领域问答系统的自然语言理解方法综述[J].计算机科学,2017,44(8):1-8,41.
[7] LOPEZ V, MIRIAM F, MOTTA E, et al. Poweraqua:supporting users in querying and exploring the semantic web[J]. Semantic web, 2011, 3(3):249-265.
[8] BORIS K, GREGORY M, GARY B, et al. The start natural language question answering system[EB/OL].[2019-09-10].http://start.csail.mit.edu.
[9] ZHENG Z. Answerbus question answering system[C]//Proceedings of the second international conference on human language technology research. San Francisco:Morgan Kaufmann Publishers Inc., 2002:399-404.
[10] FERRUCCI D, LEAVS A, BAGCHI S, et al. Watson:beyond jeopardy![J]. Artificial intelligence, 2013, 199(200):93-105.
[11] GREEN J R, BERT F, CHOMSKY C, et al. Baseball:an automatic question answerer[C]//Proceedings of the western joint computer conference. New York:IRE-AIEE-ACM, 1961:219-224.
[12] WOODS W A, KAPLAN R. Lunar rocks in natural English:explorations in natural language question answering[J]. Linguistic structures processing, 1977, 5(1):521-569.
[13] WILENSKY R, CHIN DN, LURIA M, et al. The berkeley UNIX consultant project[J]. Artificial intelligence review, 2000, 14(1/2):43-88.
[14] VARGAS-VERA M, LYTRAS M D. AQUA:A closed-domain question answering system[J]. Information systems management, 2010, 27(3):217-225.
[15] ABACHA A B, ZWEIGENBAUM P. MEANS:a medical question-answering system combining NLP techniques and semantic web technologies[J]. Information processing & management, 2015, 51(5):570-594.
[16] ASIAEE A H, MINNING T, DOSHI P, et al. A framework for ontology-based question answering with application to parasite immunology[J]. Journal of biomedical semantics, 2015, 6(1):1-31.
[17] XIE X,SONG W,LIU L,et al.Research and implementation of automatic question answering system based on ontology[C]//2015 27th chinese control and decision conference(CCDC).Piscataway:IEEE, 2015.
[18] ABDI A, IDRIS N, Ahmad Z. QAPD:an ontology-based question answering system in the physics domain[J]. Soft computing, 2018, 22(1):213-230.
[19] AGARWAL A, SACHDEVA N, YADAV R K, et al. EDUQA:Educational domain question answering system using conceptual network mapping[C]//ICASSP 2019-2019 IEEE international conference on acoustics, speech and signal processing (ICASSP). Piscataway:IEEE, 2019:8137-8141.
[20] 马晨浩.基于甲状腺知识图谱的自动问答系统的设计与实现[J].智能计算机与应用,2018,8(3):102-107.
[21] 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.
[22] 杜泽宇,杨燕,贺樑.基于中文知识图谱的电商领域问答系统[J].计算机应用与软件,2017,34(5):153-159.
[23] 陆伟,戚越,胡潇戈,等.图书馆自动问答系统的设计与实现[J].情报工程, 2019,5(2):5-16.
[24] 刘峤,李杨,段宏,等.知识图谱构建技术综述[J].计算机研究与发展, 2016,53(3):582-600.
[25] UNGER C, BUHMANN L, LEHMANN J, et al. Template-based question answering over RDF data[C]//Proceedings of the 21st international conference on world wide web. Lyon:ACM, 2012:639-648.
[26] 王继民,王若佳,曾兰馨,等.1996-2015年"一带一路"沿线国家科研合作网络的演化分析[J].图书情报工作,2017,61(16):76-83.
[27] 张旭,孙玉伟,成颖.不同特征对文本聚类效果的比较研究——以新闻文本为例[J/OL].情报理论与实践:1-13.[2019-10-19]. http://kns.cnki.net/kcms/detail/11.1762.G3.20190903.1330.006.html.
[28] 唐明,朱磊,邹显春.基于Word2Vec的一种文档向量表示[J].计算机科学, 2016,43(6):214-217,269.
[29] 高森. 农业问答系统中问题分类和相似度计算的研究[D].合肥:中国科学技术大学,2018:32.
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