[Purpose/significance] This paper establishes an ontology-based knowledeg organization model of the supply and demand (S&D) information association for patent technology, for promoting the effective matchmaking of patent R&D and industrial demands.[Method/process] From the perspective of the contents and the workflows of patent technology S&D information, this paper designs a patent technology S&D information association framework, and describes its structure and application process. Taking the field of variable agricultural machinery as a case study, based on the theory of semantic TRIZ and structured ontology construction method, this paper builds the domain knowledge ontology, patent technology supply ontology and patent technology demand ontology, and designs the matchmaking-task solving model, and formalization representation of the matchmaking-task solving of patent technology S&D information.[Result/conclusion] This paper proposes a new ontology-based knowledge organization program for the matchmaking-task solving of patent S&D information. The case study validates the feasibility and validity of the integrated application of ontology, semantic TRIZ, formalize-representation method. The results make significant progress in research methodology, and provide a theoretical model and experimental prototype for the further research.
Zhang Xian
,
Hu Zhenyin
,
Ru Lijie
,
Xu Haiyun
,
Xiao Guohua
,
Fang Shu
. Knowledge Organization Framework for the Association of Patent Technology Supply and Demand Information[J]. Library and Information Service, 2016
, 60(8)
: 118
-125
.
DOI: 10.13266/j.issn.0252-3116.2016.08.015
[1] 毛昊.我国专利实施和产业化的理论与政策研究[J].研究与发展管理,2015(4):100-109.
[2] 郭强.基于区域产业集群的专利信息服务平台建设研究[J].科技进步与对策,2013,30(20):59-62.
[3] DELGADOET J. Franz公司培训资料[EB/OL]. (2002)[2016-01-03]. http://agraph.franz.com/allegrograph/.
[4] GHOULA N, KHELIF K, DIENG-KUNTZ R. Supporting patent mining by using ontology-based semantic annotations[C]//Proceedings of the International Conference on Web Intelligence. Fremont:IEEE, 2007:435-438.
[5] 陶然.基于本体的专利情报发现体系研究[J].图书与情报,2007(4):23-27.
[6] 胡正银.基于本体的语义标注技术在专利分析中的应用研究[R].成都:中国科学院成都文献情报中心,2010.
[7] 俞春阳.基于专利本体的产品创新设计技术研究[D].杭州:浙江大学, 2007.
[8] 张太华.机电产品知识模块本体的集成及应用研究[D].杭州:浙江大学, 2009.
[9] 谷俊.冶金行业专利本体的构建研究[J].情报杂志, 2012,31(3):157-162.
[10] VERBITSKY M. Semantic TRIZ[EB/OL]. (2004)[2014-09-10]. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.115.1907&rep=rep1&type=pdf.
[11] ZHANG Y, PORTER A L, HU Z Y, et al."Term clumping" for technical intelligence:a case study on dye-sensitized solar cells[J]. The forecasting and social change, 2014,85(6):26-39.
[12] ZHANG Y, PORTER A L, GUO Y, et al. Discovering emerging technology trends:with TRIZ and technology roadmapping[EB/OL].[2014-08-04].http://www.gtmconference.org/abstracts/session1-TRIZ_and_TRM-Zhang.pdf.
[13] IHS INC. Optimize Decision-making across the product lifecycle[EB/OL].[2014-12-10]. http://inventionmachine.com/Portals/56687/docs/OptimizingDecisionMakingAcrosstheProductLifecycle_WhitePaper_InventionMachine.pdf.
[14] CREAX INC. Accelerate your R&D-process with CREAX CreationSuite.[EB/OL]. (2012)[2014-12-10]. http://www.creationsuite.com/Content/CREAX%20CreationSuite%20folder.pdf.
[15] MUKHERJEA S, BAMBA B, KANKAR P. Information retrieval and knowledge discovery utilizing a biomedical patent semantic Web[J]. Knowledge & data engineering IEEE transactions on, 2005, 17(8):1099-1110.
[16] KIM H B, HYEOK Y J, KIM K S. Semantic SAO network of patents for reusability of inventive knowledge[C]//Proceedings of the international conference on management of innovation and technology.Sanur:IEEE, 2012:510-515.
[17] 刘翔,李彦,李文等.构建支持产品创新设计的专利知识库[J]. 机械设计与研究, 2010, 26(6):7-11,26.
[18] 梁浩.面向创新设计的语义知识表示方法的研究与应用[D].哈尔滨:东北林业大学, 2014.
[19] 肖琬蓉,施韶亭,张龙等. 基于产业的知识服务平台构建研究——以甘肃省支柱产业知识服务平台建设为例[J].甘肃科技, 2012, 28(22):45-48.
[20] 国家科技图书文献中心. 科技知识组织体系共享服务系统.[EB/OL]. (2014)[2015-10-12]. http://stkos.las.ac.cn/.
[21] 胡正银. 基于个性化语义TRIZ的专利技术挖掘研究[D].北京:中国科学院大学, 2015.
[22] GHOULA N, KHELIF K, DIENG-KUNTZ R. Supporting Patent Mining by using Ontology-based Semantic Annotations[C]//Proceedings of IEEE/WIC/ACM International Conference on Web Intelligence. Fremont:IEEE, 2007:435-438.
[23] KIM Y, TIAN Y, JEONG Y, et al. Automatic discovery of technology trends from patent text[C]//Proceedings of the 2009 ACM symposium on applied computing. Honolulu:ACM, 2009:1480-1487.
[24] 陈颖, 张晓林.专利中技术词和功效词识别方法研究[J].现代图书情报技术,2011(12):24-30.
[25] 梁田,胡正银,程欣等.基于知识分类体系的专利检索系统[J]. 情报理论与实践, 2012, 35(4):99-102.
[26] 陈颖,李芳,任强等.药品专利技术解决方案的结构及描述模式[J].中华医学图书情报杂志, 2013,22(8):6-12.
[27] 陈树清.基于向量空间模型的文本分类研究与应用[D]. 广州:广东工业大学, 2010.
[28] BLEI D M, NG A Y, JORDAN M I. Latent dirichlet allocation[J]. Journal of machine learning research, 2003,3(5):993-1022.
