Please wait a minute...
New Technology of Library and Information Service  2015, Vol. 31 Issue (7-8): 131-138    DOI: 10.11925/infotech.1003-3513.2015.07.17
Current Issue | Archive | Adv Search |
The Study of Patent Data Warehouse-based Technical Efficiency Map Mining Method——Taking 3D Printing Technology as an Example
Zhai Dongsheng, Cai Liwei, Zhang Jie, Feng Xiuzhen
School of Economics and Management, Beijing University of Technology, Beijing 100124, China
Download: PDF(762 KB)   HTML  
Export: BibTeX | EndNote (RIS)      
Abstract  

[Objective] In order to achieve the micro drilling analysis of technical efficiency map and the recognition of specific patent involved in technical efficiency map. [Methods] This paper proposes a Patent Data Warehouse-based technical efficiency map mining method, which achieves the construction and multidimensional analysis of technical efficiency map by cleaning patent structured information and extracting feature words of unstructured information, combined with the Data Warehouse. [Results] The experiment results show that this method can achieve the objective fastly. [Limitations] However, if the amount of patent data is large, the star model used may reduce efficiency. And the patent feature extraction can't be automated. [Conclusions] This proposed method provides a new way for constructing and mining technical efficiency map.

Received: 17 March 2015      Published: 25 August 2015
:  TP391  

Cite this article:

Zhai Dongsheng, Cai Liwei, Zhang Jie, Feng Xiuzhen. The Study of Patent Data Warehouse-based Technical Efficiency Map Mining Method——Taking 3D Printing Technology as an Example. New Technology of Library and Information Service, 2015, 31(7-8): 131-138.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2015.07.17     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2015/V31/I7-8/131

[1] 杨春亮. 基于模糊逻辑的专利数据层次分类研究 [D]. 天津: 天津大学, 2008. (Yang Chunliang. Study on Hierarchical Text Categorization of Patent Data Based on Fuzzy Logistic [D]. Tianjin: Tianjin University, 2008.)
[2] 陈颖, 张晓林. 基于特征度和词汇模型的专利技术功效矩阵结构生成研究[J]. 现代图书情报技术, 2012(2): 53-59. (Chen Ying, Zhang Xiaolin. Research of Patent Technology- Effect Matrix Construction Based on Feature Degree and Lexical Model [J]. New Technology of Library and Information Service, 2012 (2): 53-59.)
[3] 唐桂军. 商业智能在企业信息管理系统中的应用研究[D]. 镇江: 江苏科技大学, 2009. (Tang Guijun. Application and Research of Business Intelligence in Industry Management Information System [D]. Zhenjiang: Jiangsu University of Science and Technology, 2009.)
[4] 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. (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.)
[5] 翟东升, 袁昕. 面向主题的专利分析系统[J]. 情报杂志, 2012, 31(6): 168-172. (Zhai Dongsheng, Yuan Xin. Subject-oriented Analysis of Patent System [J]. Journal of Intelligence, 2012, 31(6): 168-172.)
[6] 杨忠. 专利信息可视化分析系统构建研究[D]. 湘潭: 湘潭大学, 2013. (Yang Zhong. Research on Building Visual Analysis System of Patent Information [D]. Xiangtan: Xiangtan University, 2013.)
[7] 郭杰. 基于专利数据仓库理论的四川3D打印产业发展研究[D]. 成都: 西华大学, 2014. (Guo Jie. Development of the Sichuan-based 3D Printing Industry Patent Data Warehouse Theory [D]. Chengdu: Xihua University, 2014.)
[8] 王圣顺. 专利文件之专利技术特性及功能知识分析法 [D].台北: 台湾科技大学, 2006. (Wang Shengshun. Patent Technology Characterize and Function Knowledge Analysis of Patent Document [D]. Taipei: The Taiwan University of Science and Technology, 2006.)
[9] Tseng Y H, Wang Y M, Juang D W, et al. Text Mining for Patent Map Analysis [C]. In: Proceedings of IACIS Pacific 2005 Conference, 2005.
[10] Kim Y G, Suh J H, Park S C. Visualization of Patent Analysis for Emerging Technology [J]. Expert Systems with Applications, 2008, 34(3): 1804-1812.
[11] 罗立国. 基于专利信息服务平台的专利地图研究[D]. 武汉: 华中科技大学, 2009. (Luo Liguo. Patent Map Study Based on Patent Information Service Platform [D]. Wuhan: Huazhong University of Science and Technology, 2009.)
[12] Nanba H, Fujii A, Iwayama M, et al. Overview of the Patent Mining Task at the NTCIR-7 Workshop [C]. In: Proceedings of NTCIR-7 Workshop Meeting, Tokyo, Japan. 2008.
[13] 陈颖, 张晓林. 专利技术功效矩阵构建词汇模型研究[J]. 情报科学, 2012, 30(11): 1704-1708. (Chen Ying, Zhang Xiaolin. Research on Lexical Model of Construction of Patent Technology-Effect Matrix [J]. Information Science, 2012, 30 (11): 1704-1708.)
[14] 翟东升, 陈晨, 张杰, 等. 专利信息的技术功效与应用图挖掘研究[J]. 现代图书情报技术, 2012 (7-8): 96-102. (Zhai Dongsheng, Chen Chen, Zhang Jie, et al. The Mining Research of Technical Efficiency and Application Map of Patent Information [J]. New Technology of Library and Information Service, 2012 (7-8): 96-102.)
[15] Cheng T Y, Wang M T. The Patent-Classification Technology/Function Matrix-A Systematic Method for Design Around [J]. Journal of Intellectual Property Rights, 2013, 18(2): 158-167.
[16] 霍翠婷, 蒋勇青, 凌锋, 等. 日本FI/F-term分类体系在专利技术/功效矩阵中的应用研究[J]. 情报杂志, 2013, 32(11): 140-144. (Huo Cuiting, Jiang Yongqing, Ling Feng, et al. Application Study on Patent Technology/Function Matrix Based on Japanese Classification System (FI/F-term) [J]. Journal of Information, 2013, 32(11): 140-144.)
[17] 王丽, 张冬荣, 张晓辉, 等. 利用主题自动标引生成技术功效矩阵[J]. 现代图书情报技术, 2013(5): 80-86. (Wang Li, Zhang Dongrong, Zhang Xiaohui, et al. Realization of Technology/Effect Maps Generating Based on Subject Automatic Indexing [J]. New Technology of Library and Information Service, 2013 (5): 80-86.)
[18] Derwent Innovations IndexSM [DB/OL]. [2015-01-21]. http:// www.thomsonscientific.com.cn/Productsservices/diimedia/.
[19] 李倩. 基于专利的新兴技术弱信号识别方法研究[D]. 北京: 北京工业大学, 2014. (Li Qian. The Research of the Emerging Technology Weak Signal Recognition Based on Patent [D]. Beijing: Beijing University of Technology, 2014.)
[20] GATE [EB/OL]. [2015-01-21]. https://gate.ac.uk/.

[1] Xiaofeng Li,Jing Ma,Chi Li,Hengmin Zhu. Identifying Commodity Names Based on XGBoost Model[J]. 数据分析与知识发现, 2019, 3(7): 34-41.
[2] Zhongxi You,Weina Hua,Xuelian Pan. Matching Book Reviews and Essential Sentiment Lexicons with Chinese Word Segmenters[J]. 数据分析与知识发现, 2019, 3(7): 23-33.
[3] Peng Guan,Yuefen Wang,Zhu Fu. Analyzing Topic Semantic Evolution with LDA: Case Study of Lithium Ion Batteries[J]. 数据分析与知识发现, 2019, 3(7): 61-72.
[4] Jiahui Hu,An Fang,Wanqing Zhao,Chenliu Yang,Huiling Ren. Annotating Chinese E-Medical Record for Knowledge Discovery[J]. 数据分析与知识发现, 2019, 3(7): 123-132.
[5] Beibei Kong,Jing Xie,Li Qian,Zhijun Chang,Zhenxin Wu. Methodology and Tools to Enrich Sci-Tech Big Data[J]. 数据分析与知识发现, 2019, 3(7): 113-122.
[6] Fan Xuexue, Wang Zhirong, Xu Wu, Liang Yin, Ma Xiaohu. Research on Semantic Similarity Estimation Algorithm of Medical Terminology Based on Medical Ontology[J]. 现代图书情报技术, 2015, 31(12): 57-64.
[7] Ren Haiying, Yu Liting. A Multi-strategy Method for Word Sense Disambiguation Based on Wikipedia[J]. 现代图书情报技术, 2015, 31(11): 18-25.
[8] Du Kun, Liu Huailiang, Guo Lujie. Study on the Modified Method of Feature Weighting with Complex Networks[J]. 现代图书情报技术, 2015, 31(11): 26-32.
[9] Ye Chuan, Ma Jing. Research on Topic Discovery Algoritm of Multimedia Microblog Comments Information[J]. 现代图书情报技术, 2015, 31(11): 51-59.
[10] Xie Xiaqing, Wu Xu. Application of Visualization Technology for “Classic Reading” Platform[J]. 现代图书情报技术, 2015, 31(11): 96-103.
[11] He Yu, Lv Xueqiang, Xu Liping. A Chinese Term Extraction System in New Energy Vehicles Domain[J]. 现代图书情报技术, 2015, 31(10): 88-94.
[12] Du Siqi, Li Honglian, Lv Xueqiang. Research of Chinese Chunk Parsing in Application of the Product Feature Extraction[J]. 现代图书情报技术, 2015, 31(9): 26-30.
[13] Xu Deshan, Li Hui, Zhang Yunliang. A Method of Keywords Annotation Based on Linked Triples[J]. 现代图书情报技术, 2015, 31(9): 31-37.
[14] Dun Wenjie, Sun Yigang, Zhu Xianzhong. Design and Realization of Multimedia Document Structure of Internet TV[J]. 现代图书情报技术, 2015, 31(9): 82-89.
[15] Chen Shiqin, Li Wenjiang. Application of WebSocket in Library Mobile Information Service[J]. 现代图书情报技术, 2015, 31(9): 90-96.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn