請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/55007完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 魏志平 | |
| dc.contributor.author | Pei-Yu Lin | en |
| dc.contributor.author | 林蓓妤 | zh_TW |
| dc.date.accessioned | 2021-06-16T03:44:09Z | - |
| dc.date.available | 2025-12-31 | |
| dc.date.copyright | 2015-02-11 | |
| dc.date.issued | 2015 | |
| dc.date.submitted | 2015-02-09 | |
| dc.identifier.citation | Agrawal, R., & Srikant, R. (2001). On integtaing catalogs. Proceedings of the 10th International Conference on World Wide Web, 603–612.
Albert, M. B., & Avery, D. (1990). Direct validation of citation counts as indicators of industrially important patents. Research Policy, 20(3), 251–259. Bessen, J. (2008). The value of U.S. patents by owner and patent characteristics. Research Policy, 37(5), 932–945. Breiman, L. (1996). Bagging predictors. Machine Learning, 140(24), 123–140. Chang, C.T. (2010). Supporting patent maintenance decision: A data mining approach. Unpublished Master Thesis, Institute of Service Science, National Tsing Hua University. Choksi, J. (1999). The benefits and costs of patent protection. IEEE Canadian Review - Summer, 25–26. Davenport, T. H., DeLong, D. W., & Beers, M. C. (1998). Successful knowledge management projects.Sloan Management Review, 39(2), 43–57. Fall, C. J., Torcsvari, A., Benzineb, K., & Karetka, G. (2003). Automated categorization in the international patent classification. ACM SIGIR Forum, 37(1), 10–25. Griliches, Z. (1998). Patent statistics as economic indicators: A survey. Chapter 13 in R&D and Productivity: The Econometric Evidence, Z. Griliches (ed.), University of Chicago Press,287–343. Hall, B. H., Jaffe, A. B., &Trajtenberg, M. (2001). The NBER patent citations data file: Lessons, insights and methodological tools. NBER Working Paper SeriesNo. 8498. Harhoff, D., Narin, F., Scherer, F. M., & Vopel, K. (1999). Citation frequency and the value of patented inventions. The Review of Economics and Statistics, 81(3), 511–515. Jin, X., Spangler, S., Chen, Y., Cai, K., Ma, R., Zhang, L., Wu, X., & Han, J. (2011). Patent maintenance recommendation with patent information network model. Proceedings of 2011 IEEE 11th International Conference on Data Mining, 280–289. Jun, S., & Uhm, D. (2013). A predictive model for patent registration time using survival analysis. Applied Mathematics & Information Sciences, 7(5), 1819–1823. Lanjouw, J. O., & Schankerman, M. (2004). Patent quality and research productivity: measuring innovation with multiple indicators. The Economic Journal, 114(495), 441–465. Li, X., Chen, H., Zhang, Z., Li, J., & Nunamaker, J. F. (2009). Managing knowledge in light of its evolution process: An empirical study on citation network-based patent classification. Journal of Management Information Systems, 26(1), 129–154. Liu, K., Arthurs, J., Cullen, J., & Alexander, R. (2008). Internal sequential innovations: How does interrelatedness affect patent renewal?,Research Policy, 37(5), 946–953. Nikzad, R. (2011). Survival analysis of patents in canada. The Journal of World Intellectual Property, 14(5), 368–382. Oh, S., Lei, Z., Mitra, P., & Yen, J. (2012). Evaluating and ranking patents using weighted citations. Proceedings of the 12th ACM/IEEE-CS Joint Conference on Digital Libraries, 281–284. Pakes, A. (1986). Patents as options: Some estimates of the value of holding european patent stocks. Econometrica, 54(4), 755–784. Schankerman, M., & Pakes, A. (1985). Estimates of the value of patent rights in European countries during the post-1950 period. NBER Working Paper Series No.1650. Shih, M.J., Liu, D.R., & Hsu, M.L. (2010). Discovering competitive intelligence by mining changes in patent trends. Expert Systems with Applications, 37(4), 2882–2890. Teece, D. J. (1986). Profiting from technological innovation : Implications for integration, collaboration, licensing and public policy. Research Policy, 15(6), 285–305. Jones, T., Norris, M., & Solomon, I. (2002). Strategies for maximizing value from intellectual capital in a technology-driven business. The Licensing Journal, 22(6), 1–6. Thomas, P. (1999). The effect of technological impact upon patent renewal decisions. Technology Analysis & Strategic Management, 11(2), 181–198. Trappey, A. J. C., Hsu, F.C., Trappey, C. V., & Lin, C.I. (2006). Development of a patent document classification and search platform using a back-propagation network. Expert Systems with Applications, 31(4), 755–765. van Zeebroeck, N. (2009). From patent renewals to applications survival: do portfolio management strategies play a role in patent length?, Working Papers CEB, ULB -- Universite Libre de Bruxelles, No. 09-028.RS. Wang, M., Lo, H., Liao, Y., & Lin, P. (2012). Determinants of patent renewal decisions by patent Indicators and social network analysis : The case of the biotech industry in Taiwan and Korea.Proceedings of Technology Management for Emerging Technologies (PICMET), 1060–1065 Yoon, B., & Park, Y. (2004). A text-mining-based patent network: Analytical tool for high-technology trend. The Journal of High Technology Management Research, 15(1), 37–50. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/55007 | - |
| dc.description.abstract | 專利已經成為企業最重要的智慧財產以及知識財產之一，透過法律在一定期間內所賦予的合法排他權利，發明人可以保護自己的創新發明不被他人所抄襲或利用，藉以提升競爭優勢。維護費的繳納可以視為發明人獲得這項保障的方法，但是一個企業或組織內部的專利相當龐大，維護費可能造成研發與製造上的巨額負擔，因此企業傾向維護他們認為較有價值的專利，將資源更有效地分配在有前景的研發上，此時維護決策就變得相當重要且迫切。
本研究預計使用過去研究中認為會影響專利維護的因素，以資料探勘的方式建立專利維護決策支援系統，並且透過分類強化的方法，來提升判斷的準確性。這種預測及支援系統可以協助企業與組織快速的判斷是否該對專利進行維護，增進決策的效率與準確性，同時降低決策成本。此外我們也利用美國專利局資料庫中取得的專利進行實證研究，結果顯示，我們所提出的專利維護決策支援模型表現優於基準模型(未引入分類強化方法之模型)。 | zh_TW |
| dc.description.abstract | Patents have become one of the most important intellectual properties and knowledge assets. With the legal exclusive rights provided by laws for a certain period, inventors can protect their inventions or products from being plagiarized or utilized, promote overall competitiveness, and gain a strategic advantage. Payments of maintenance fee can be regarded as the way inventors acquire such protection continually. However, the large portfolio of patents owned by large companies or organizations may cause heavy financial burden to them. Companies tend to maintain patents with greater value and allocate their resources to promisingtechnologies. In consequence, patent maintenance decisions are essential and urgent.
In this study, we examine factors influencing patent maintenance decisions which are considered significantby previous studies and propose a systematic solution to analyze patents for recommending patent maintenance decisions. Anenhanced classification algorithm is also applied in the study to improve the overall accuracy of our predictions. The patent maintenance decision support system can efficiently and effectivelyhelp companies and organizations determine whether a patent should be maintained while decreasing the decision making costs. In addition, we conduct experiments on the large scale United States Patent and Trademark Office (USPTO) database which contains over millions of granted patents. The empirical evaluation results show that our proposed model outperforms the benchmark model without the use of the enhanced classification algorithm. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T03:44:09Z (GMT). No. of bitstreams: 1 ntu-104-R01725013-1.pdf: 1398043 bytes, checksum: edb3523e11baf9fb28457055ce7a7199 (MD5) Previous issue date: 2015 | en |
| dc.description.tableofcontents | 審定書 I
誌謝 II 中文摘要 III Abstract IV Contents VI List of Tables IX List of Figures X Chapter 1 Introduction 1 1.1 Importance of patents 1 1.2 Maintenance of Patents 4 1.3 Research Motivation and Objectives 7 Chapter 2 Literature Review 12 2.1 Characteristics of Patent Maintenance 12 2.1.1 Economic Perspective 12 2.1.2 Technological Perspective 13 2.2 Related Works on Determining Patent Maintenance Decisions 14 2.3 Models 15 2.3.1 Classification 15 2.3.2 Survival Analysis 16 Chapter 3 Design of Our Patent Maintenance Prediction Technique 17 3.1 Dimensions and Variables 17 3.2 Overall Process of Our Patent Maintenance Prediction Technique 21 3.3 Learning Algorithm 22 3.4 Enhanced Classification Algorithm 24 Chapter 4 Empirical Evaluation 28 4.1 Data Collection 28 4.1.1 Target Industries and Companies 28 4.1.2 Target Patents 29 4.1.3 Maintenance Event Records 30 4.1.4 Variables Extraction 31 4.2 Evaluation Design 33 4.2.1 Benchmark Model 33 4.2.2 Evaluation Criteria 34 4.2.3 Evaluation Procedure 35 4.3 Evaluation Results 35 4.3.1 Initial Prediction Results before Enhancement 35 4.3.2 Effect of Weights on Classification Effectiveness Considering Company and IPC as Source Groups 36 4.3.3 Comparative Evaluation Results 37 4.3.4 Precision of Top and Bottom n% of Testing Patents 40 Chapter 5 In-depth Analysis 43 5.1 Experiment 1: Different Conditions of Company and IPC Source Groupings 43 5.2 Experiment 2: Extension of the Enhanced Model 45 Chapter 6 Conclusion and Future Directions 48 6.1 Conclusion 48 6.2 Future Directions 48 References 51 Appendix 54 | |
| dc.language.iso | en | |
| dc.subject | 資料探勘 | zh_TW |
| dc.subject | 專利智慧 | zh_TW |
| dc.subject | 專利探勘 | zh_TW |
| dc.subject | 分類強化 | zh_TW |
| dc.subject | 專利維護 | zh_TW |
| dc.subject | PatentIntelligence | en |
| dc.subject | Data Mining | en |
| dc.subject | Patent Renewal | en |
| dc.subject | Patent Maintenance | en |
| dc.subject | Enhanced Classification | en |
| dc.subject | PatentMining | en |
| dc.title | 以分類強化方法協助專利維護決策之制定 | zh_TW |
| dc.title | To Renew or Abandon My Patents:An Enhanced Classification Approach for Supporting Patent Maintenance Decisions | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 103-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 林怡伶,吳怡瑾 | |
| dc.subject.keyword | 資料探勘,專利探勘,專利智慧,分類強化,專利維護, | zh_TW |
| dc.subject.keyword | Data Mining,PatentMining,PatentIntelligence,Enhanced Classification,Patent Maintenance,Patent Renewal, | en |
| dc.relation.page | 58 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2015-02-09 | |
| 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-104-1.pdf 未授權公開取用 | 1.37 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。