請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/61006完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 魏志平(Chih-Ping Wei) | |
| dc.contributor.author | Hong-Ieng Hoi | en |
| dc.contributor.author | 許鴻英 | zh_TW |
| dc.date.accessioned | 2021-06-16T10:41:01Z | - |
| dc.date.available | 2018-07-31 | |
| dc.date.copyright | 2013-08-20 | |
| dc.date.issued | 2013 | |
| dc.date.submitted | 2013-08-13 | |
| dc.identifier.citation | Bianchi, M., Campodall’Orto S. C., Frattini F., & Vercesi, P. (2010) Enabling open innovation in small and medium-sized enterprises: how to find alternative applications for your technologies. R&D Management, 40(4), pp. 414-431.
Bergmann, I., Butzke, D., Walter, L., Fuerste, J. P., Moehrle, M. G., & Erdmann, V. A. (2008). Evaluating the risk of patent infringement by means of semantic patent analysis: the case of DNA chips. R&d Management, 38(5), pp. 550-562. Collan, M., and Heikkila, M. (2011) Enhancing patent valuation with the pay-off method. Journal of Intellectual Property Rights, 16, pp. 377-384. Chesbrough H. (2013) Innovation: The new imperative for creating and profiting from technology. Boston: Harvard University Press. Choi, S., Yoon, J., Kim, K., Lee, J. Y., & Kim, C. H. (2011) SAO network analysis of patents for technology trends identification: a case study of polymer electrolyte membrane technology in proton exchange membrane fuel cells. Scientometrics, 88(2) , pp. 863-883. Deerwester, S., Dumais, S. T., Furnas, G. W., Landauer, T. K., & Harshman, R. (1990) Indexing by latent semantic analysis. Journal of the American Society for Information Science, 41(6), pp. 391-407. Dewulf, S. (2006) Directed variation: Variation of properties for new or improved function product DNA, A base for ‘connect and develop’. Proceedings of the ETRIA TRIZ Future Conference, Kortrijk, Belgium. Glaser, M. & Miecznik, B. (2009) TRIZ for reverse inventing in market research: a case study from WITTENSTEIN AG, identifying new areas of application of a core technology. Creativity and Innovation Management, 18(2), pp. 90-100. Harris, C., Arens, R. & Srinivasan, P. (2010) Comparison of IPC and USPC classification systems in patent prior art searches. Proceeding of the 3nd international workshop on patent information retrieval, pp. 27-32. ACM. Jeon, J., Lee, C. & Park, Y. (2011) How to use patent information to search potential technology partners in open innovation. Journal of Intellectual Property Rights, 16, pp. 385-393. Kimbrough, S. O., MacMillan, I. & Ranieri, J. (2007). U.S. Patent No. 7,257,568. Lee, S., Park, G., Yoon, B. & Park, J., (2010) Openinnovation in SMEs – An Intermediated Network Model. Research Policy, 29, pp. 290–300. Lichtenthaler, U. (2008) Opening up strategic technology planning: extended roadmaps and functional markets. Management Decision, 46(1), pp. 77-91. Loh H. T., He C., & Shen L. (2006) Automatic classification of patent documents for TRIZ users. World Patent Information, 28(1), pp. 6-13. De Marneffe, M. C., MacCartney, B., & Manning, C. D. (2006). Generating typed dependency parses from phrase structure parses. In Proceedings of LREC (6), pp. 449-454. Mann, D. (2002) Assessing the accuracy of the contradiction matrix for recent mechanical inventions. TRIZ Journal. Moehrle, M. G., Walter, L., Geritz, A., & Muller, S. (2005). Patent‐based inventor profiles as a basis for human resource decisions in research and development. R&D Management, 35(5), pp. 513-524. Moehrle, M. G. (2005) What is TRIZ? From conceptual basics to a framework for research. Creativity and innovation management, 14(1), pp. 3-13. Ngassa, A., Bachelet, R., & Truchot, P. (2003) How to turn an invention into an innovation? An approach based on a reverse use of TRIZ. Proceedings of 12th International Conference on Management of Technology (IAMOT), Nancy, France. Ovtcharova, J. & Marinov, M. (2008). Function based identification of affected components in cross-domain engineering. In B. Rachev & A. Smrikarov (eds.), CompSysTech (p./pp. 21), : ACM. ISBN: 978-954-9641-52-3. Park, H., Yoon, J., & Kim, K. (2013) Using function-based patent analysis to identify potential application areas of technology for technology transfer. Expert Systems with Applications, 40(13), pp. 5260–5265. Park, H., Kim, K., Choi, S., & Yoon, J. (2012) A Patent intelligence system for strategic technology planning. Expert Systems with Applications, 40(7), pp. 2373-2390. She, T. W. (2012) A text mining approach to identifying cross-sectoral applications. Department of Information Management College of Management, National Taiwan University Master Thesis. Umeda, Y., & Tomiyama, T. (1997) Functional reasoning in design. IEEE expert, 12(2), pp. 42-48. Verhaegen, P. A., D’hondt, J., Vertommen, J., Dewulf, S., & Duflou, J. R. (2009) Interrelating products through properties via patent analysis. Proceedings of the 18th CIRP Design Conference, pp. 252–257. Miller, G. A. (1995). WordNet: a lexical database for English. Communications of the ACM, 38(11), pp. 39-41. Wu, Z., & Palmer, M. (1994) Verb semantics and lexical selection. In 32nd Annual Meeting of the Association for Computational Linguistics, pp. 133-138. Yoon, J., & Kim, K. (2011). An automated method for identifying TRIZ evolution trends from patents. Expert Systems with Applications, 38(12), pp. 15540-15548. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/61006 | - |
| dc.description.abstract | 「跨業應用」是指和企業核心領域完全不同的應用。找出專利的跨業應用可以幫助企業持續創新而獲得更多利潤並且提升競爭力。但是要找出專利可以跨業應用的領域是一件很困難的項目，因為要尋找跨業應用的專家必須熟悉各個領域的技術、公司也需要投入大量的時間和金錢去做研發。
因此在這次研究中，我們將提出以功能分析為基礎的自動化系統Automatic Recommendation of Patent Cross-sectoral Application (ACROSS) 為企業有效率地找出專利的跨業應用領域。對於要尋找跨業應用的專利，ACROSS會找出和此專利不相同的應用領域來進行分析，如果某一應用領域的大部分專利和此專利在功能上是很相似的，這應用領域將有可能成為ACROSS推薦給此專利的跨業應用。最後的評估結果證明我們的系統是有足夠能力找出專利的跨業應用。 | zh_TW |
| dc.description.abstract | Cross-sectoral application is applying technology to completely different industries from firm’s own business activities. Identifying cross-sectoral applications of patents can help firms to keep innovations to market for gaining profit and enhancing competitive advantage. However, it is a difficult task to discovery other domains which need this patent for improving its capacity or business efficiency. Moreover, identification of cross-sectoral applications for a patent only relies on the experts having abundant experiences in these different technical domains, and this process is usually time-consuming. So, in this study, we developed an automatic function-based recommendation system, called Automatic Recommendation of Patent Cross-sectoral Application (ACROSS), to discovery cross-sectoral applications for a given focal patent. The main idea of ACROSS is to consider application areas which are different from the ones of the focal patent and in which most patents have similar function with the focal patent as cross-sectoral applications. Therefore, we may recommend these cross-sectoral applications for the focal patent. The evaluation result suggests the proposed approach performs well in discovering cross-sectoral application. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T10:41:01Z (GMT). No. of bitstreams: 1 ntu-102-R00725027-1.pdf: 1037508 bytes, checksum: 7ee6b4a61a0acb7e35cf5cb03f1d53c7 (MD5) Previous issue date: 2013 | en |
| dc.description.tableofcontents | 誌謝 i
中文摘要 ii ABSTRACT iii CONTENTS iv LIST OF FIGURES vi LIST OF TABLES vii Chapter 1 Introduction 1 1.1 Background 1 1.2 Research Motivation 2 1.3 Research Objective 4 Chapter 2 Literature Review 5 2.1 Property-based Identification 5 2.2 TRIZ-based Identification 6 2.3 Function-based Identification 9 Chapter 3 Design of Proposed ACROSS System 11 3.1 System overview 11 3.2 AO Structure Extraction 13 3.2.1 Stanford Parser for Syntactic Analysis 13 3.2.2 The process of AO Structure Extraction 14 3.3 AO Structure Selection 17 3.3.1 Dictionary-based of AO structure selection 17 3.3.2 Statistics-based of AO Structure Selection 19 3.4 Semantic Similarity Assessment and Similar Prior Patents Retrieval 20 3.4.1 Semantic Similarity Assessment 20 3.4.2 Similar Prior Patents Retrieval 23 3.5 Candidates Generation for Cross-sectoral Application 24 3.6 Candidates Scoring and Ranking 24 Chapter 4 Experimental Evaluation 26 4.1 Ground Truth of Cross-sectoral Applications 26 4.2 Data Collection 27 4.3 Evaluation Criterion 28 4.4 Benchmark 29 4.5 Parameter Tuning Experiments 29 4.6 Evaluation Results of Our Proposed System 32 4.7 Effect of Candidates Scoring on Effectiveness of Cross-sectoral Application Identification 35 4.8 Effect of Different Approach for Semantic Similarity Assessment on Effectiveness of Cross-sectoral Application Identification 37 Chapter 5 Conclusion and Future Work 40 REFERENCE 42 LIST OF FIGURES Fig. 1 The Processes of TRIZ 7 Fig. 2 Overall Process of Our Proposed ACROS System 12 Fig. 3 The Process for Extracting AO Structures in a Sentence 16 Fig. 4 Effects of Number of Retrieved Prior Patents (k) and Number of LSA Reduced Dimension (m) for Dictionary-based AO Structure Selection Approach 30 Fig. 5 Effects of Number of LSA Reduced Dimension (m) and Number of Selected AO Structures (w) for Statistics-based AO Structures Selection Approach 31 Fig. 6 The Result of Identification of All Cross-sectoral Applications 33 Fig. 7 The Result of Identification of Surprising Cross-sectoral Applications 35 Fig. 8 Evaluation Results of Different Candidate Scoring Methods 36 Fig. 9 Evaluation Result of Different Methods to Assess Similarity between Two Actions and between Two Objects 39 | |
| dc.language.iso | en | |
| dc.subject | 跨業授權 | zh_TW |
| dc.subject | 跨業應用 | zh_TW |
| dc.subject | 專利分析 | zh_TW |
| dc.subject | 功能分析 | zh_TW |
| dc.subject | cross-sectoral applications | en |
| dc.subject | cross-sectoral out-licensing | en |
| dc.subject | patent analysis | en |
| dc.subject | functional analysis | en |
| dc.title | 利用功能分析方法找出專利的跨業應用 | zh_TW |
| dc.title | A Function-based Approach to Identifying Cross-sectoral Applications for Patents | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 101-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 胡雅涵(Ya-Han Hu),楊錦生(Chin-Sheng Yang) | |
| dc.subject.keyword | 跨業應用,跨業授權,專利分析,功能分析, | zh_TW |
| dc.subject.keyword | cross-sectoral applications,cross-sectoral out-licensing,patent analysis,functional analysis, | en |
| dc.relation.page | 44 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2013-08-13 | |
| dc.contributor.author-college | 管理學院 | zh_TW |
| dc.contributor.author-dept | 資訊管理學研究所 | zh_TW |
| 顯示於系所單位： | 資訊管理學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-102-1.pdf 未授權公開取用 | 1.01 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。