研究生: |
陳榮錡 |
---|---|
論文名稱: |
應用專利申請範圍架構和發明元件關係於多模組產品相關專利搜尋 The Study of Searching Relevant Patents of Multi-disciplinary Products Based on Patent Claim Structure |
指導教授: | 林福仁 |
口試委員: | |
學位類別: |
碩士 Master |
系所名稱: |
科技管理學院 - 科技管理研究所 Institute of Technology Management |
論文出版年: | 2008 |
畢業學年度: | 96 |
語文別: | 英文 |
論文頁數: | 65 |
中文關鍵詞: | 專利檢索 、文字探勘 |
相關次數: | 點閱:1 下載:0 |
分享至: |
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
檢索相關專利在現今產品生命週期中扮演非常重要的角色。如果一位產品經理(PM)可以快速且正確無誤地檢索出產品相關專利,他就能有效率地判斷該項產品是否具有競爭優勢,另一方面也可知道,競爭對手產品是否與我們所推產品是否有專利上面的衝突,更重要的是在研發之初進行相關專利檢索可以避免因為侵權訴訟而導致的無形和有形資產損失。但是由於專利不但在數量上快速地成長,也越來越複雜。所以這此研究中我們提供另一種以專利申請範圍的結構為主的方式來協助更精準地檢索龐大的專利資料庫。
目前大部分專利檢索是單純利用關鍵字去搜尋和比對專利,但是這種方式往往會忽略專利發明本身的結構。故此研究利用專利申請範圍的敘述找出發明元件的架構,並用發明元件連線的關係來比對專利的相似程度。所以,我們將以傳統文字探勘技術先建構較可能的且較大潛在相關專利的集合,再利用本篇研究所改進的解析專利申請範圍的技術,再此集合中真正找到最核心且最多最相關的專利文件。
最後本篇研究貢獻在於可減少公司內人員(可能是PM)在開發新產品時,所需花費搜尋專利的負擔,另一方面在資訊科技方面,也提出另外一種新概念於相關專利搜尋。
Nowadays, the search for relevant patents plays an important role in product life cycle. If a product manager can retrieve relevant patents according to his/her criteria for a new product quickly and accurately, s/he will be able to efficiently and effectively judge if the tentative product has the complete feature set, any risks in patent infringement, and its potential in technology competition. However, the increasing number of patents creates the additional efforts in patent search in terms of quantity and complexity. Bewaring the emerging need of prior art retrieval from a large patent database, the main objective of this study is to develop a methodology which can build the claim hierarchy automatically in order to retrieve the most relevant patents for a product with technologies from various disciplines.
Most existing patent retrieval tools use keywords to find relevant patents; however, they ignore the structure of the invention, which mentions in the claim of patent. Thus, this study parses the sentences of a patent claim and finds the structure of the invention. Then, we compare the similarity of the structure of inventions and retrieve the most relevant patents. In order not to ignore potential relevant patents, the proposed relevant patent retrieval method uses keyword-based patent retrieval technique first. Subsequently, the system uses the automated generated claim trees to retrieve the most relevant patents from the patent set retrieved by keywords. Finally, users could adjust the inner and core patent set to decide how much relevant patents retained as the outputs.
The major contribution of this thesis is to decrease the effort for product managers to search relevant patents in product development life cycle. This thesis can serve as a benchmark for researchers to compare with follow-up tech mining techniques.
Allison, J. R., Lemley, M. A., Moore, K. A., & Trunkey, R. D. (2003). Valuable Patents: SSRN.
Ernst, H. (1997). The Use of Patent Data for Technological Forecasting: The Diffusion of CNC-Technology in the Machine Tool Industry: Kluwer Academic Publishers.
Fujii, A. (2007). Enhancing patent retrieval by citation analysis, Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval. Amsterdam, The Netherlands: ACM.
G. Salton, A. Wong, & Yang, C. S. (1975). A vector space model for automatic indexing (Vol. 18, pp. 613-620): ACM.
Gerard, S., & Chris, B. (1987). Term Weighting Approaches in Automatic Text Retrieval: Cornell University.
Gerard, S., & Michael, J. M. (1986). Introduction to Modern Information Retrieval: McGraw-Hill, Inc.
Gregory D. Abowd, & Mynatt, E. D. (2000). Charting past, present, and future research in ubiquitous computing (Vol. 7, pp. 29-58): ACM.
Han, J., & Kamber, M. (2006). Data Mining: Concepts and Techniques: Services Manager Simon Crump.
Hisao Mase, Tadataka Matsubayashi, Yuichi Ogawa, Makoto Iwayama, & Oshio, T. (2005). Proposal of two-stage patent retrieval method considering the claim structure (Vol. 4, pp. 190-206): ACM.
Huang, F. M.(2007). The study of patent prior art retrieval using claim structure and link analysis
Jinxi Xu, & Croft, W. B. (1996). Query expansion using local and global document analysis, Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval. Zurich, Switzerland: ACM.
Kazuaki, K. (2003). Pseudo relevance feedback method based on taylor expansion of retrieval function in NTCIR-3 patent retrieval task, Proceedings of the ACL-2003 workshop on Patent corpus processing - Volume 20: Association for Computational Linguistics.
Kohonen, T. (2001). The Self-Organizing Map: Springer-Verlag, Verlag, Berline, Heidelberg, New York.
Konstantinos Markellos, Katerina Perdikuri, Penelope Markellou, Spiros Sirmakessis, George Mayritsakis, & Tsakalidis, A. (2002). Knowledge discovery in patent databases, Proceedings of the eleventh international conference on Information and knowledge management. McLean, Virginia, USA: ACM Press.
Lai, K.-K., & Wu, S.-J. (2003). Using the patent co-citation approach to establish a new patent classification system: Information Processing and Management.
Larkey, L. S. (1999). A patent search and classification system, Proceedings of the fourth ACM conference on Digital libraries. Berkeley, California, United States: ACM.
Makoto, I., Atsushi, F., Noriko, K., & Yuzo, M. (2003). An empirical study on retrieval models for different document genres: patents and newspaper articles, Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval. Toronto, Canada: ACM Press.
Mark, W. (1995). The computer for the 21st century. In Human-computer interaction: toward the year 2000 (pp. 933-940): Morgan Kaufmann Publishers Inc.
Murphy, O. J. (1990). Nearest Neighbor Pattern Classification Perceptrons: IEEE.
Nagy, G. (1968). State of the Art in Pattern Recognition: IEEE.
Park, C., Park, C., Liu, J., & Chou, P. H. (2005). Eco: an ultra-compact low-power wireless sensor node for real-time motion monitoring
Eco: an ultra-compact low-power wireless sensor node for real-time motion monitoring. Paper presented at the Information Processing in Sensor Networks, 2005. IPSN 2005. Fourth International Symposium on.
Sergey Brin, & Page, L. (1998). The anatomy of a large-scale hypertextual Web search engine, Proceedings of the seventh international conference on World Wide Web 7. Brisbane, Australia: Elsevier Science Publishers B. V.
Sheremetyeva, S. (2003). Natural language analysis of patent claims, Proceedings of the ACL-2003 workshop on Patent corpus processing - Volume 20: Association for Computational Linguistics.
Sheremetyeva S., Nirenburg S., & I., N. (1996). Generating patent claims from interactive input, Proceedings of the 8th international workshop on natural language generation. Hersmonceux, Sussex, UK.
Sung-Shin Lim, Sung-Won Jung, & Kwon, H.-C. (2004). Improving patent retrieval system using ontology. Paper presented at the Industrial Electronics Society, 2004. IECON 2004. 30th Annual Conference of IEEE.
Wartburg, I. v., Teichert Thorsten, & Katja, R. (2005). Inventive progress measured by multi-stage patent citation analysis. Research Policy, 34(10), 1591-1607.
Yiming Yang, & Pedersen, J. O. (1997). A Comparative Study on Feature Selection in Text Categorization, Proceedings of the Fourteenth International Conference on Machine Learning: Morgan Kaufmann Publishers Inc.