Please wait a minute...
Advanced Search
数据分析与知识发现  2016, Vol. 32 Issue (12): 66-75    DOI: 10.11925/infotech.1003-3513.2016.12.09
  应用论文 本期目录 | 过刊浏览 | 高级检索 |
基于图形数据库的专利语义知识库构建技术研究
翟东升,刘鹤(),张杰,蔡力伟
北京工业大学经济与管理学院 北京 100124
Managing Patent Semantic Knowledge with Graph Database
Dongsheng Zhai,He Liu(),Jie Zhang,Liwei Cai
School of Economics and Management, Beijing University of Technology, Beijing 100124, China
全文: PDF(1725 KB)   HTML ( 38
输出: BibTeX | EndNote (RIS)      
摘要 

目的】针对德温特专利数据设计并实现语义完整、性能良好的专利语义知识库。【应用背景】专利语义知识库用于存储专利数据以及各项数据之间存在的语义关系, 使得人们可以通过语义关系对专利进行检索。【方法】通过分析德温特专利数据所含及其之间的语义关系, 改进基于本体的专利语义表示方法, 提出基于属性图模型的德温特专利图数据模型, 并使用Neo4j图形数据库存储实例化的专利数据。【结果】以云计算技术为例, 构建专利语义知识库, 该知识库保证了语义信息完整, 在较大数据量的情况下, 查询速度可达到传统关系型数据库的5.35倍。【结论】基于图形数据库的专利语义知识库有着信息完整、语义清晰、性能良好等特点, 是一种稳定且高效的专利数据组织与存储方式。

服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
翟东升
刘鹤
张杰
蔡力伟
关键词 专利信息语义关系知识库图形数据库    
Abstract

[Objective]Design and implement a semantic knowledge management system for the Derwent patent data. [Context] The proposed system collects the patent data as well as the semantic relations among them. It could retrieve patent information with semantic relation. [Methods] First, we analyzed the Derwent patent data and the semantic relations among the data. Second, we modified the method of patent semantic representation based on Ontology. Third, we proposed a Derwent patent graph data model based on property graph model. Finally, we used the Neo4j graphic database to store the instantiated patent data. [Results] We built a semantic knowledge management system using cloud computing technology patents. The new system showed stronger semantic integrity and faster retrieval speed than traditional ones. [Conclusions] The proposed patent semantic knowledge management system offers stable and efficient solutions for organizing and storing patent data.

Key wordsPatent information    Semantic relation    Knowledge base    Graph database
收稿日期: 2016-08-09     
引用本文:   
翟东升, 刘鹤, 张杰, 蔡力伟. 基于图形数据库的专利语义知识库构建技术研究[J]. 数据分析与知识发现, 2016, 32(12): 66-75.
Dongsheng Zhai, He Liu, Jie Zhang, Liwei Cai. Managing Patent Semantic Knowledge with Graph Database. Data Analysis and Knowledge Discovery, DOI:10.11925/infotech.1003-3513.2016.12.09.
链接本文:  
http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2016.12.09
[1] Neo4j [EB/OL]. [2015-12-21]..
[2] Studer R, Benjamins V R, Fensel D.Knowledge Engineering: Principles and Methods[J]. Data & Knowledge Engineering, 1998, 25(1-2): 161-197.
[3] Ghoula N, Khelif K, Dieng-Kuntz R.Supporting Patent Mining by Using Ontology-based Semantic Annotations [C]. In: Proceedings of the 2007 IEEE/WIC/ACM International Conference on Web Intelligence. 2007: 435-438.
[4] Giereth M, Koch S, Kompatsiaris Y, et al.A Modular Framework for Ontology-based Representation of Patent Information [C]. In: Proceedings of the 20th Conference on Legal Knowledge and Information Systems, Leiden, the Netherlands. 2007: 49-58.
[5] Taduri S, Lau G T, Law K H, et al.An Ontology to Integrate Multiple Information Domains in the Patent System[C]. In: Proceesings of the 2011 IEEE International Symposium on Technology and Society. IEEE, 2011:1-9.
[6] 翟东升, 张欣琦, 张杰. Derwent专利本体设计与构建[J]. 情报科学, 2013, 31(12): 95-100.
[6] (Zhai Dongsheng, Zhang Xinqi, Zhang Jie.Design and Implementation of Derwent Patent Ontology[J]. Information Science, 2013, 31(12): 95-100.)
[7] Robinson I, Eifrem E, Webber J.Graph Databases[M]. Oreilly Media, 2013.
[8] 王余蓝. 图形数据库NEO4J与关系据库的比较研究[J]. 现代电子技术, 2012, 35(20): 77-79.
[8] (Wang Yulan.Comparison of Graphic Database NEO4J and Relational Database[J]. Modern Electronics Technique, 2012, 35(20): 77-79.)
[9] Elbattah M, Roushdy M, Aref M, et al.Large-scale Ontology Storage and Query Using Graph Database-oriented Approach: The Case of Freebase [C]. In: Proceedings of the 7th International Conference on Intelligent Computing and Information Systems. 2015.
[10] Lampoltshammer T, Wiegand S.Improving the Computational Performance of Ontology-Based Classification Using Graph Databases[J]. Remote Sensing, 2015, 7(7): 9473-9491.
[11] 李佳南, 王曰芬, 颜端武. 馆藏资源语义知识库及服务平台构建探究——以台湾问题为例[J]. 图书馆学研究, 2014(22): 29-35.
[11] (Li Jia’nan, Wang Yuefen, Yan Duanwu.Research on the Construction of the Semantic Knowledge Base of Library Resources and Service Platform — Taking Taiwan as an Example[J]. Research on Library Science, 2014(22): 29-35.)
[12] 王颖, 张智雄, 孙辉, 等. 基于本体的国史知识检索平台构建研究[J]. 图书情报工作, 2015, 59(16): 119-128.
[12] (Wang Ying, Zhang Zhixiong, Sun Hui, et al.Construction of Knowledge Retrieval Platform Based on Historic Ontology of the People’s Republic of China[J]. Library and Information Service, 2015, 59(16): 119-128.)
[13] 张慧, 侯霞, 李宁. 本体存储方法研究[J]. 北京信息科技大学学报:自然科学版, 2016, 31(3): 59-63.
[13] (Zhang Hui, Hou Xia, Li Ning.A Research on Ontology Storage Method[J]. Journal of Beijing Information Science & Technology University, 2016, 31(3): 59-63.)
[14] 本体语言[EB/OL]. [2015-12-21]..
[14] (Ontology Language [EB/OL]. [2015-12-21].. )
[15] 王立轻. 基于本体的互联网专利信息检索技术研究[D]. 北京: 北京工业大学, 2010.
[15] (Wang Liqing.Research on Internet Patent Information Retrieval Technology Based on Ontology [D]. Beijing: Beijing University of Technology, 2010.)
[16] 陶皖, 姚红燕. OWL本体关系数据库存储模式设计[J]. 计算机技术与发展, 2007, 17(2): 111-114.
[16] (Tao Wan, Yao Hongyan.Design of OWL Ontology Storage Schema in Relational Database[J]. Computer Technology and Development, 2007, 17(2): 111-114. )
[17] 翟东升, 禾文汇. 异构专利数据源集成方案设计与实现[J]. 现代图书情报技术, 2010(9): 67-73.
[17] (Zhai Dongsheng, He Wenhui.Design and Implementation of Data Integration over Heterogeneous Patent Sources[J]. New Technology of Library and Information Service, 2010(9): 67-73.)
[18] 翟东升, 李倩, 张杰. 德温特专利信息清洗与标注模型研究[J]. 情报杂志, 2013, 32(8): 150-154.
[18] (Zhai Dongsheng, Li Qian, Zhang Jie.The Research of ETL and Annotation Model Construction of Derwent Patent Information[J]. Journal of Intelligence, 2013, 32(8): 150-154.)
[19] 翟东升, 蔡力伟, 张杰. 基于专利的技术融合创新轨道识别模型研究——以云计算技术为例[J]. 情报学报, 2015, 34(4): 352-360.
[19] (Zhai Dongsheng, Cai Liwei, Zhang Jie.The Study of Patent-based Model for Identifying Technology Fusion Innovation Trajectory Illustrated by the Case of Cloud Computing Technology[J]. Journal of the China Society for Scientific and Technical Information, 2015, 34(4): 352-360.)
[1] 祁瑞华,周俊艺,郭旭,刘彩虹. 基于知识库的图书评论主题抽取研究*[J]. 数据分析与知识发现, 2019, 3(6): 83-91.
[2] 张旺强,祝忠明,李雅梅,卢利农,刘巍. 机构知识库作者名自动消歧框架设计与实践*[J]. 数据分析与知识发现, 2019, 3(6): 92-98.
[3] 吴志强,祝忠明,刘巍,王思丽. CSpace知识分析与可视化功能扩展研究与实践*[J]. 数据分析与知识发现, 2019, 3(3): 112-119.
[4] 吴志强,祝忠明,姚晓娜,王思丽. CSpace机构知识库影音资源支持能力扩展研究与实践*[J]. 数据分析与知识发现, 2017, 1(9): 90-96.
[5] 谢靖,王敬东,吴振新,张智雄,王颖,叶志飞. 科技文献检索系统语义丰富化框架的设计与实践*[J]. 数据分析与知识发现, 2017, 1(4): 84-93.
[6] 陈果,肖璐. 网络社区中的知识元链接体系构建研究*[J]. 数据分析与知识发现, 2017, 1(11): 75-83.
[7] 王思丽,刘巍,祝忠明,吴志强,王金平. 基于CSpace的科技信息可配置化自动监测功能设计与实现*[J]. 数据分析与知识发现, 2017, 1(10): 85-93.
[8] 吴志强,祝忠明,刘巍,张旺强,姚晓娜. 机构知识库三维模型检索与展示技术研究与实践*[J]. 数据分析与知识发现, 2017, 1(1): 73-80.
[9] 李晓瑛,夏光辉,李丹亚. 主题标引文献的语义关系发现研究*[J]. 现代图书情报技术, 2016, 32(7-8): 87-93.
[10] 周鹏程,武川,陆伟. 基于多知识库的短文本实体链接方法研究*——以Wikipedia和Freebase为例[J]. 现代图书情报技术, 2016, 32(6): 1-11.
[11] 张旺强,祝忠明,姚晓娜,刘巍. 基于开放获取论文推送转发服务系统iSwitch的机构知识库内容建设*[J]. 现代图书情报技术, 2016, 32(4): 91-96.
[12] 刘峰,黎建辉,张进,韩芳,刘昂. TeamDR:面向科研团队的数据知识库管理系统*[J]. 现代图书情报技术, 2016, 32(3): 82-89.
[13] 孟园, 王洪伟. 中文评论产品特征与观点抽取方法研究*[J]. 现代图书情报技术, 2016, 32(2): 16-24.
[14] 钱力, 师洪波, 张晓林, 梁娜. 开放获取论文推送转发服务系统iSwitch: 论文分发推送[J]. 现代图书情报技术, 2015, 31(6): 7-12.
[15] 严潮斌, 陈嘉勇, 侯瑞芳, 李玲, 周婕. 查收查引服务支撑需求驱动下的高校机构知识库建设[J]. 现代图书情报技术, 2015, 31(5): 94-100.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
版权所有 © 2015 《数据分析与知识发现》编辑部
地址:北京市海淀区中关村北四环西路33号 邮编:100190
电话/传真:(010)82626611-6626,82624938
E-mail:jishu@mail.las.ac.cn