帳號:guest(3.85.215.164)          離開系統
字體大小: 字級放大   字級縮小   預設字形  

詳目顯示

以作者查詢圖書館館藏以作者查詢臺灣博碩士以作者查詢全國書目勘誤回報
作者(中):鄭俊彥
作者(英):Cheng, Chun-Yen
論文名稱(中):透過專利文字探勘辨識潛在競爭者之方法:以金融科技產業為例
論文名稱(英):A patent mining methodology of identifying potential competitors: A case study of FinTech industry
指導教授(中):宋皇志
指導教授(英):Sung, Huang-Chih
口試委員:林怡伶
莊弘鈺
口試委員(外文):Lin, Yi-Ling
Chuang, Hung-Yu
學位類別:碩士
校院名稱:國立政治大學
系所名稱:科技管理與智慧財產研究所
出版年:2020
畢業學年度:108
語文別:中文
論文頁數:115
中文關鍵詞:專利分析文字探勘自然語言處理競爭者辨識金融科技
英文關鍵詞:Patent AnalysisText MiningNatural Language ProcessingCompetitor IdentificationFinTech
Doi Url:http://doi.org/10.6814/NCCU202001096
相關次數:
  • 推薦推薦:0
  • 點閱點閱:131
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:8
  • gshot_favorites title msg收藏:0
  現今各行各業皆致力導入新興科技輔助商業發展,使得產業界線逐漸模糊。例如原本受到傳統金融機構長期掌握的金融服務市場,隨著金融科技的蓬勃發展,越來越多科技公司加入競爭,對傳統金融機構造成龐大威脅。倘若企業未能掌握潛在競爭者動向,將可能錯失擬定應對策略的最佳時機,最終導致企業競爭地位下滑。其中潛在競爭的不確定性,是企業不願進行潛在競爭者辨識的主要原因。

  本研究旨在提供一個方法,使企業得以在威脅浮現前預警到可能存在的競爭者。過去研究多將專利方法與文字探勘方法分別應用於競爭者辨識,本研究將結合兩種方法並考量實務可行性,提出以非監督式學習之專利文字探勘方法,協助企業辨識潛在競爭者,從中探求本方法論應用於潛在競爭者辨識的可能性,以及比較本研究採用模型應用於分析專利文本的優劣。本研究以有導入金融科技的傳統金融機構作為案例產業,並由美國百大銀行中挑選專利布局最多的美國銀行 (Bank of America,BOA) 作為標的企業進行測試,從約115萬篇的大量專利中找尋相關的市場與專利競爭威脅。

  本研究之貢獻在於提供一個企業得實際應用之新方法論辨識潛在競爭者。具體而言,研究中透過美國銀行的侵權訴訟評估方法可行性,發現29篇涉及侵權專利有13篇排名於前10%,其中3篇致使美國銀行敗訴的專利均排名於前5%,顯示本辨識方法足以在龐大的專利數據中提升鑑別競爭對手的效率。並以專利相似度排名進行競爭者分析,顯現本方法可以有效找尋有威脅性、多元且具相似專利資源的競爭者。
  Nowadays, all industries have dedicated to introducing new technology to assist their business, further blurring the boundary of industries. For example, the financial service market has long been monopolized by traditional financial institutions. However, with the rapid development of financial technology, technology companies have also entered the very industry, along with a huge competition threat. If the company fails to identify the potential competitors, it may miss the best time to formulate a responsive strategy, which ultimately leads to a decline. Also, the uncertainty of potential competition is the main reason why companies are unwilling to identify their potential competitors.

  The purpose of this study is to provide a methodology for companies to identify potential competitors before threats emerge. In the past research, the patent method and the text mining method were mostly applied to the identification of competitors. However, this study combined the two methods and considered the practical feasibility. Therefore, this research provides the patent text mining with unsupervised learning method to identify potential competitors, explore its feasibility, and compare the advantages between different models applying to analyze patent texts. In this study, traditional financial institutions that have introduced Fintech are been reviewed as case for research, and the Bank of America, which has the largest amount of patents among the top 100 banks in the United States, is selected as the target company for testing.

  The contribution of this study is to provide a new methodology in the field of competitor identification which companies could apply in practice. Specifically, through examining infringement litigation of Bank of America, the study found that 13 of the 29 infringement patents were ranked in the top 10%, and 3 patents that Bank of America is the losing party in infringement litigation were ranked in the top 5%. It shows that this identification method is sufficient to limit the competitive scope in the huge patent data. Lastly, the analysis of competitors based on the ranking of patent similarity shows this methodology can find competitors that are threatening, diverse and have similar patent resources.
第一章 緒論 1
1.1 研究背景 1
1.2 研究動機 3
1.3 研究目的與問題 6
1.4 研究範圍 6

第二章 文獻探討 8
2.1 競爭者辨識之意義 8
2.2 競爭者辨識之方法 10
 2.2.1 非專利與文字探勘之方法 10
 2.2.2 專利方法 12
 2.2.3 文字探勘方法 14
2.3 專利文本之文字探勘方法 16
2.4 銀行業之潛在競爭者問題 21
 2.4.1 金融科技產業概況 21
 2.4.2 銀行業之專利布局 23
2.5 小結 25

第三章 研究方法 27
3.1 研究架構 28
3.2 資料蒐集 33
3.3 模型訓練 35
 3.3.1前處理 35
 3.3.2向量化與模型訓練 36
3.4 模型驗證 42
 3.4.1 第一步驟:資料處理 43
 3.4.2 第二步驟:模型訓練 43
 3.4.3 第三步驟:模型驗證 45
3.5 個案測試 48
 3.5.1 前置步驟 49
 3.5.2 分群階段 49
 3.5.3 排名階段 51

第四章 研究結果 53
4.1 訓練模型驗證 53
 4.1.1 分群任務 53
 4.1.2 排名任務 57
 4.1.3 驗證結果評析 62
4.2 個案測試-Bank of America 63
 4.2.1 專利分群與排名流程 64
 4.2.2 辨識方法之可行性評估 72
 4.2.3 潛在競爭者辨識結果 75

第五章 結論與建議 86
5.1 研究結論 86
5.2 研究限制與建議 88

參考文獻 90

附錄1:模型驗證-分群任務原始數據 100
附錄2:模型驗證-排名任務原始數據 103
附錄3:個案測試-決定分群數原始數據 106
附錄4:個案測試-IPO潛在競爭者原始數據 108
附錄5:個案測試-非IPO潛在競爭者原始數據 112
Abbas, A., Zhang, L., & Khan, S. U. (2014). A literature review on the state-of-the-art in patent analysis. World Patent Information, 37, 3–13.
Abell, D. F. (1980). Defining the business: The starting point of strategic planning. Prentice Hall.
Accenture. (2020). Fintech fundraising grew strongly in most major markets in 2019, accenture analysis finds. Retrieved May 11, 2020, from https://newsroom.accenture.com/news/fintech-fundraising-grew-strongly-in-most-major-markets-in-2019-accenture-analysis-finds.htm
Allahyari, M., Pouriyeh, S., Assefi, M., Safaei, S., Trippe, E. D., Gutierrez, J. B., & Kochut, K. (2017). A brief survey of text mining: Classification, clustering and extraction techniques. ArXiv Preprint ArXiv:1707.02919.
Amarouche, K., Benbrahim, H., & Kassou, I. (2015). Product opinion mining for competitive intelligence. Procedia Computer Science, 73(3), 358-365.
Anica-Popa, I., & Cucui, G. (2009). A framework for enhancing competitive intelligence capabilities using decision support system based on web mining techniques. International Journal of Computers Communications & Control, 4(4), 326–334.
Arner, D. W., Barberis, J., & Buckley, R. P. (2015). The evolution of Fintech: A new post-crisis paradigm. Geo. J. Int’l L., 47, 1271.
Bank Director (2015). 2015 Growth Strategy Survey. August 2015. http://www.bankdirector.com/issues/growth/2015-growth-strategy-survey-arebanks-missing-out-on-millennials/
Bao, S., Li, R., Yu, Y., & Cao, Y. (2008). Competitor mining with the web. IEEE Transactions on Knowledge and Data Engineering, 20(10), 1297–1310.
Bengio, Y., Ducharme, R., Vincent, P., & Jauvin, C. (2003). A neural probabilistic language model. Journal of Machine Learning Research, 3(Feb), 1137–1155.
Bergen, M., & Peteraf, M. A. (2002). Competitor identification and competitor analysis: a broad‐based managerial approach. Managerial and Decision Economics, 23(4‐5), 157–169.
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), 550–562.
Bergmann, I., Möhrle, M. G., Walter, L., Butzke, D., Erdmann, V. A., & Fürste, J. P. (2007). The use of semantic maps for recognition of patent infringements: A case study in biotechnology. Zeitschrift Für Betriebswirtschaft–Special, (4), 69–86.
Blake, C. (2011). Text mining. Annual Review of Information Science and Technology, 45(1), 121–155.
Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent dirichlet allocation. Journal of Machine Learning Research, 3(Jan), 993–1022.
Boyd, B. K., & Fulk, J. (1996). Executive scanning and perceived uncertainty: A multidimensional model. Journal of Management, 22(1), 1–21.
Breitzman, A. (2005). Automated identification of technologically similar organizations. Journal of the American Society for Information Science and Technology, 56(10), 1015–1023.
Breitzman, A. F., & Mogee, M. E. (2002). The many applications of patent analysis. Journal of Information Science, 28(3), 187–205.
Chen, M.-J. (1996). Competitor analysis and interfirm rivalry: Toward a theoretical integration. Academy of Management Review, 21(1), 100–134.
Day, G. S. (1981). Strategic market analysis and definition: an integrated approach. Strategic Management Journal, 2(3), 281–299.
Day, G. S., Massy, W. F., & Shocker, A. D. (1978). The Public Policy Context of the Relevant Market Question. Marketing and the Public Interest, (78-105), 51-67.
Day, G. S., Shocker, A. D., & Srivastava, R. K. (1979). Customer-oriented approaches to identifying product-markets. Journal of marketing, 43(4), 8-19.
DeChernatony, L., Daniels, K., & Johnson, G. (1993). A cognitive perspective on managers’ perceptions of competition. Journal of Marketing Management, 9(4), 373–381.
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), 391–407.
Dietzmann, C., & Alt, R. (2019, July). How IT-Related Financial Innovation Influences Bank Risk-Taking: Results from an Empirical Analysis of Patent Applications. In 2019 IEEE 21st Conference on Business Informatics (CBI) (Vol. 1, pp. 452-461). IEEE.
Domb, E., & Tate, K. (1997). Inventive Principles With Examples’. TRIZ Journal, July.
Ernst, H. (2003). Patent information for strategic technology management. World Patent Information, 25(3), 233–242.
Fong, S. (2012). Framework of competitor analysis by monitoring information on the web. Journal of Emerging Technologies in Web Intelligence, 4(1), 77–83.
Fredrickson, J. W., & Mitchell, T. R. (1984). Strategic decision processes: Comprehensiveness and performance in an industry with an unstable environment. Academy of Management Journal, 27(2), 399–423.
Gerken, J. M., & Moehrle, M. G. (2012). A new instrument for technology monitoring: novelty in patents measured by semantic patent analysis. Scientometrics, 91(3), 645–670.
Geum, Y., Lee, S., Yoon, B., & Park, Y. (2013). Identifying and evaluating strategic partners for collaborative R&D: Index-based approach using patents and publications. Technovation, 33(6–7), 211–224.
Gross, A., & Murthy, D. (2014). Modeling virtual organizations with Latent Dirichlet Allocation: A case for natural language processing. Neural Networks, 58, 38–49.
Gur, F. A., & Greckhamer, T. (2019). Know thy enemy: A review and agenda for research on competitor identification. Journal of Management, 45(5), 2072–2100.
He, C., & Loh, H. T. (2010). Pattern-oriented associative rule-based patent classification. Expert Systems with Applications, 37(3), 2395–2404.
Hinton, G. E. (1986, August). Learning distributed representations of concepts. In Proceedings of the eighth annual conference of the cognitive science society (Vol. 1, p. 12).
Hristidis, V., Ruiz, E., Hernández, A., Farfán, F., & Varadarajan, R. (2010, October). Patentssearcher: a novel portal to search and explore patents. In Proceedings of the 3rd international workshop on Patent information retrieval (pp. 33-38).
Jain, A. K. (2010). Data clustering: 50 years beyond K-means. Pattern Recognition Letters, 31(8), 651–666.
Jaksic, M., & Marinc, M. (2015). The future of banking: The role of information technology. Bancni Vestnik: BANKING SECTOR AT THE CROSSROADS: CHALLENGES FOR THE FUTURE, Forthcoming.
Karvonen, M., & Kässi, T. (2011). Patent analysis for analysing technological convergence. Foresight, 13(5), 34–50.
Kiesler, S., & Sproull, L. (1982). Managerial response to changing environments: Perspectives on problem sensing from social cognition. Administrative science quarterly, 548-570.
Kim, T., Choi, H., & Lee, H. (2016). A study on the research trends in fintech using topic modeling. Journal of the Korea Academia-Industrial Cooperation Society, 17(11), 670–681.
Kim, Y. G., Suh, J. H., & Park, S. C. (2008). Visualization of patent analysis for emerging technology. Expert Systems with Applications, 34(3), 1804–1812.
Kuilman, J., & Li, J. (2006). The organizers’ ecology: An empirical study of foreign banks in Shanghai. Organization Science, 17(3), 385–401.
Lanjouw, J. O., & Schankerman, M. (2001). Characteristics of patent litigation: a window on competition. RAND Journal of Economics, 129–151.
Lanjouw, J. O., & Schankerman, M. A. (1998). Patent suits: do they distort research incentives?
Lappas, T., Valkanas, G., & Gunopulos, D. (2012, August). Efficient and domain-invariant competitor mining. In Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 408-416).
Le, Q., & Mikolov, T. (2014, January). Distributed representations of sentences and documents. In International conference on machine learning (pp. 1188-1196).
Lee, C., Song, B., & Park, Y. (2013). How to assess patent infringement risks: a semantic patent claim analysis using dependency relationships. Technology Analysis & Strategic Management, 25(1), 23–38.
Lee, H. J., & Yang, H. (2015, December). Potential competitor identification and competitor analysis by monitoring patent information. In ISPIM Innovation Symposium (p. 1). The International Society for Professional Innovation Management (ISPIM).
Lee, S., Yoon, B., & Park, Y. (2009). An approach to discovering new technology opportunities: Keyword-based patent map approach. Technovation, 29(6-7), 481–497.
Leong, E. K. F., Ewing, M. T., & Pitt, L. F. (2004). Analysing competitors’ online persuasive themes with text mining. Marketing Intelligence & Planning, 22(2), 187–200.
Lerner, J. (2002). Where does State Street lead? A first look at finance patents, 1971 to 2000. The Journal of Finance, 57(2), 901–930.
Lerner, J., Speen, A., Baker, M., & Leamon, A. (2016). Financial patent quality: Finance patents after State Street. Harvard Business School working paper series# 16-068.
Li, R., Bao, S., Wang, J., Liu, Y., & Yu, Y. (2006, August). Web scale competitor discovery using mutual information. In International Conference on Advanced Data Mining and Applications (pp. 798-808). Springer, Berlin, Heidelberg.
Li, R., Bao, S., Wang, J., Yu, Y., & Cao, Y. (2006, December). Cominer: An effective algorithm for mining competitors from the web. In Sixth International Conference on Data Mining (ICDM'06) (pp. 948-952). IEEE.
Loh, H. T., He, C., & Shen, L. (2006). Automatic classification of patent documents for TRIZ users. World Patent Information, 28(1), 6–13.
Loper, E., & Bird, S. (2002). NLTK: the natural language toolkit. ArXiv Preprint Cs/0205028.
Lu, Y. F., Xu, J. L., & Chen, M. Y. (2019, June). Using Text Mining to Analyze the Financial Patents. In Proceedings of the 9th International Conference on Web Intelligence, Mining and Semantics (pp. 1-7).
Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013). Efficient estimation of word representations in vector space. ArXiv Preprint ArXiv:1301.3781.
Mikolov, T., Sutskever, I., Chen, K., Corrado, G. S., & Dean, J. (2013). Distributed representations of words and phrases and their compositionality. In Advances in neural information processing systems (pp. 3111-3119).
Milliken, F. J. (1987). Three types of perceived uncertainty about the environment: State, effect, and response uncertainty. Academy of Management Review, 12(1), 133–143.
Montgomery, D. B., Moore, M. C., & Urbany, J. E. (2005). Reasoning about competitive reactions: Evidence from executives. Marketing Science, 24(1), 138–149.
Pant, G., & Sheng, O. R. L. (2009). Avoiding the blind spots: Competitor identification using web text and linkage structure. ICIS 2009 Proceedings, 57.
Pant, G., & Sheng, O. R. L. (2015). Web footprints of firms: Using online isomorphism for competitor identification. Information Systems Research, 26(1), 188–209.
Park, H., Yoon, J., & Kim, K. (2011). Identifying patent infringement using SAO based semantic technological similarities. Scientometrics, 90(2), 515–529.
Porac, J. F., & Thomas, H. (1990). Taxonomic mental models in competitor definition. Academy of Management Review, 15(2), 224–240.
Porter, M. E., & Millar, V. E. (1985). How information gives you competitive advantage. Harvard Business Review Reprint Service.
Porter, M. E., & Strategy, C. (1980). Techniques for analyzing industries and competitors. Competitive Strategy. New York: Free.
Ramos, J. (2003, December). Using tf-idf to determine word relevance in document queries. In Proceedings of the first instructional conference on machine learning (Vol. 242, pp. 133-142).
Salton, G. (1971). The SMART system. Retrieval Results and Future Plans.
Samiee, S. (2008). Global marketing effectiveness via alliances and electronic commerce in business-to-business markets. Industrial Marketing Management, 37(1), 3–8.
Scherer, F. M. (1970). Industrial market structure and economic performance.
Schmoch, U. (2008). Concept of a technology classification for country comparisons. Final Report to the World Intellectual Property Organisation (Wipo), WIPO.
Thomas, H., & Pollock, T. (1999). From I‐O economics’ S‐C‐P paradigm through strategic groups to competence‐based competition: reflections on the puzzle of competitive strategy. British Journal of Management, 10(2), 127–140.
Tseng, Y. H., Lin, C. J., & Lin, Y. I. (2007). Text mining techniques for patent analysis. Information Processing & Management, 43(5), 1216–1247.
Williams, R. (2016). Fintech Transforms Competitive Landscape, but Unlikely to Displace Banks’ Central Role. In Moody’s investors service.
Wilson, R. M. (1987). Patent analysis using online databases — II. Competitor activity monitoring. World Patent Information, 9(2), 73–78.
Yoon, B., & Park, Y. (2005). A systematic approach for identifying technology opportunities: Keyword-based morphology analysis. Technological Forecasting and Social Change, 72(2), 145–160.
Yoon, J., & Kim, K. (2012). TrendPerceptor: A property–function based technology intelligence system for identifying technology trends from patents. Expert Systems with Applications, 39(3), 2927–2938.
Yoon, J., Park, H., & Kim, K. (2013). Identifying technological competition trends for R&D planning using dynamic patent maps: SAO-based content analysis. Scientometrics, 94(1), 313–331.
Yu, C., Wang, F., & Brouthers, K. D. (2016). Competitor identification, perceived environmental uncertainty, and firm performance. Canadian Journal of Administrative Sciences/Revue Canadienne Des Sciences de l’Administration, 33(1), 21–35.
Zajac, E. J., & Bazerman, M. H. (1991). Blind spots in industry and competitor analysis: Implications of interfirm (mis) perceptions for strategic decisions. Academy of Management Review, 16(1), 37–56.
Zelenko, D., & Semin, O. (2002). Automatic competitor identification from public information sources. International Journal of Computational Intelligence and Applications, 2(03), 287–294.
Zetsche, D. A., Buckley, R. P., Arner, D. W., & Barberis, J. N. (2017). From FinTech to TechFin: the regulatory challenges of data-driven finance. NYUJL & Bus., 14, 393.
劉高勇、吳金紅與汪會玲 (2014)。基於專利技術關聯的產業競爭格局解析方法研究。情報雜誌,33(8),48–51。
宋皇志 (2017)。人工智慧在專利檢索之應用初探。全國律師月刊雜誌社,21:10期,27–37。
王靜 (2014)。競爭與變革:互聯網金融對傳統銀行業的衝擊。中國流通經濟,28(5),122–126。
 
 
 
 
第一頁 上一頁 下一頁 最後一頁 top
* *