[1]高凤宁,高祥涛,曹 帅,等.面向智能搜索应用的水利知识图谱构建[J].江苏水利,2021,(10):59-64.
 GAO Fengning,GAO Xiangtao,CAO Shuai,et al.Construction of water conservancy knowledge graph for intelligent search application[J].JIANGSU WATER RESOURCES,2021,(10):59-64.
点击复制

面向智能搜索应用的水利知识图谱构建()
分享到:

《江苏水利》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2021年10期
页码:
59-64
栏目:
水利信息化
出版日期:
2021-12-15

文章信息/Info

Title:
Construction of water conservancy knowledge graph for intelligent search application
文章编号:
1007-7839(2021)10-0059-06
作者:
高凤宁1高祥涛2曹 帅2朱向荣1司存友2胡 伟1
(1.南京大学 计算机科学与技术系,江苏 南京 210023; 2.江苏省水文水资源勘测局,江苏 南京 210029)
Author(s):
GAO Fengning1GAO Xiangtao2CAO Shuai2ZHU Xiangrong1SI Cunyou2HU Wei1
(1.Department of Computer Science and Technology,Nanjing University,Nanjing 210023,China; 2.Jiangsu Hydrology and Water Resources Survey Bureau,Nanjing 210029,China)
关键词:
水利知识图谱 知识融合 词嵌入 语义搜索
Keywords:
water conservancy knowledge graph knowledge fusion word embedding semantic search
分类号:
TM734
文献标志码:
B
摘要:
在水利知识图谱的基础上,结合字符串相似度以及word2vec生成的词嵌入的余弦相似度,设计了关联属性的语义查询算法,实现了异构水利知识的融合。在网页端搭建了一个智能搜索应用,通过用户实验,验证了基于水利知识图谱的智能搜索应用可以降低水利领域从业人员的数据获取难度,增强对水利领域相关知识的理解。
Abstract:
On the basis of water conservancy knowledge graph,combined with the string similarity and the cosine similarity of word embedding generated by word2vec,semantic query algorithm of associated attributes was designed to achieve the integration of heterogeneous water conservancy knowledge. After building an intelligent search application on the web,user experiments verified that the intelligent search application based on the water conservancy knowledge graph could reduce the difficulty of data acquisition for practitioners in the water conservancy field and enhance the understanding of relevant knowledge in the water conservancy field.

参考文献/References:

[1] 葛召华,张中坤,李博. 基于知识图谱的水利数据垂直搜索应用[J]. 山东水利,2018(5):1-2.
[2] 王鑫,邹磊,王朝坤. 知识图谱数据管理研究综述[J]. 软件学报,2019(7):2139-2174.
[3] BERNERSLEE T,HENDLER J,LASSILA O. The Semantic Web,Scientific American[J]. Scientific American,2001,284(5):34-43.
[4] LEHMANN J,ISELE R,JAKOB M,et al. DBpedia–a large-scale,multilingual knowledge base extracted from wikipedia[J]. Semantic web,2015,6(2):167-195.
[5] MAHDISOLTANI F,BIEGA J,SUCHANEK F.YAGO3:a knowledge base from multilingual wikipedias[C]. Seventh Biennial Conference on Innovative Data Systems Research,2015.
[6] VRANDECIC D,KRTOETZSCH M.Wikidata:A free collaborative knowledgebase[J]. Communications of the ACM,2014,57(10):78-85.
[7] DA N B,GUHA R V.RDF Vocabulary Description Language 1.0:RDF Schema[R/OL].(2003-12-15)[2014-02-10]. http://www.w3.org/TR/rdf-schema/.
[8] 贾存鑫,胡伟,柏文阳,等. SMap:基于语义的关系数据库模式与OWL本体间映射方法[J]. 计算机研究与发展,2012,49(10):2241-2250.
[9] BIZER C. D2R MAP-a database to RDF mapping language[C]//ACM,The 12th Internanonal World Wide Web. Budapest,2003.
[10] Prud'Hommeaux E,Seaborne A. SPARQL Query Language for RDF[S]. 2008.
[11] HUANG J,HU W,BAO Z,et al. Crowdsourced Collective Entity Resolution with Relational Match Propagation[C]. ICDE,2020.
[12] MIKOLOV T,CHEN K,CORRADO G,et al. Efficient estimation of word representations in vector space[J]. arXiv,2013.
[13] CHENG G,LIU D,QU Y. Fast algorithms for semantic association search and pattern mining[J]. IEEE Transactions on Knowledge and Data Engineering,2019(99):1-1.
[14] JOHN BROOKE.SUS:a retrospective[J]. Journal of Usability Studies,2013,8(2):29-40.

备注/Memo

备注/Memo:
收稿日期:2021-05-24
基金项目:江苏省水利科技项目(2019046)
作者简介:高凤宁(1997—),男,硕士研究生,研究方向为知识融合。E-mail:ngao.nju@gmail.com
通信作者:胡伟(1982—),男,副教授,博士,主要从事知识图谱研究。E-mail:whu@nju.edu.cn
更新日期/Last Update: 2021-11-17