隨著全球化的競爭與科技的快速發展，各國對智慧財產權的保護越來越重視，專利是紀錄智慧財產權的一種形式，富含重要科技發展成果。對於組織而言，為了瞭解特定新興科技領域的相關議題並且應用於新產品的開發過程，都必須事先參考專利上現有的技術。藉由專利知識累積技術新知，啟發新的創意靈感，同時避免使用與現有專利衝突的技術，減少法律的糾紛。
然而，隨著科技的快速發展，存在的專利的數量越來越多，使用者在查詢與取得所需要的專利時時常面臨查詢結果過多，形成資訊過載的問題。專利因為具有特殊的法律議題，在搜尋的過程中遺漏任何一篇重要的專利都會造成決策者誤判。因此，提供使用者更全面性與更有效率的方式取得所需要的專利便顯得非常重要。近年來，以知識管理的方法提供使用者更有效率與更全面性的方式取得所需資訊變的十分熱門。主題地圖具有能節省使用者瀏覽的時間並可以提升在查詢過程中得到更多重要文件的特性。
本研究建構以科技為主題的主題地圖，為了擷取出每篇專利所談論的科技元素作為主題地圖的主題關鍵字來源，本研究利用樣板學習法的方法進行科技主題的擷取，並進一步利用Bootstrapping的方法自動學習更多用於擷取科技主題的樣板。在實驗的過程中，本研究發現以Bootstrapping的方式進行樣版的學習能夠有效的學習到需要的樣版並能擷取被視為科技元素的項目，同時利用主題地圖富含充分的知識資訊，能幫助使用者取得所需專利。

With the global competition and the development of technology, each country takes more and more emphases on the protection of intellectual property. Patents are one of forms which people record their intellectual property, and comprise a plurality of research results. By reading patents, one can know some special issue of a new technology domain. In R&D process, collecting patents can accumulated technical knowledge, inspire new creative inspiration, avoid conflict with existing patents, and reduce legal disputes.
However, existing patents have causing the issue of information overloading when users want to search for some needed patents. Patents have its own legal issue, omitting any important patent will cause decision-makers to make wrong decisions. Therefore, providing users with more comprehensive and more efficient way of acquiring necessary patents has become very important.
Constructing knowledge map to help users of information retrieval has become very popular. Topic map is a kind of knowledge map that save time when browsing and enhance query quality. Bootstrapping is a machine learning technique that use a little seed human assigned, and automatically learn information we need from data. Before constructing topic map, we use bootstrapping to train patterns and use these patterns to extract technology elements in patents as keywords of topics. In this study, we provide a method to construct topic map to help user save their time in browsing and get more needed patent while searching. The experimental result showed that learning patterns via bootstrapping could help in recognizing technology elements that a patent used. We also show that the constructed topic map helped user to find patent they needed.

Agichtein, E., & Gravano, L. (2000). Snowball: extracting relations from large plain-text collections. Paper presented at the Proceedings of the fifth ACM conference on Digital libraries, San Antonio, Texas, United States.
Al-Rajebah, N. I., & Al-Khalifa, H. S. (2010). Semantic Relationship Extraction and Ontology Building using Wikipedia: A Comprehensive Survey. International Journal of Computer Applications, 12(3), 6-12.
Blackman, M. (1995). Provision of patent information: a national patent office perspective. World Patent Information, 17(2), 115-123. doi: 10.1016/0172-2190(95)00012-o
Brank, J., Grobelnik, M., & Mladenić, D. (2005). A survey of ontology evaluation techniques. Paper presented at the In Proceedings of the Conference on Data Mining and Data Warehouses (SiKDD 2005).
Brin, S. (1999). Extracting Patterns and Relations from the World Wide Web. Paper presented at the Selected papers from the International Workshop on The World Wide Web and Databases.
Cetintas, S., & Si, L. (2012). Effective Query Generation and Postprocessing Strategies for Prior Art Patent Search. Journal of the American Society for Information Science and Technology, 63(3), 512-527. doi: 10.1002/asi.21708
Chan, L. M. (2005). Library Of Congress Subject Headings: Principles And Application: Libraries Unlimited, Incorporated.
Chen, Y.-L., & Chiu, Y.-T. (2011). An IPC-based vector space model for patent retrieval. Information Processing & Management, 47(3), 309-322. doi: 10.1016/j.ipm.2010.06.001
Ciravegna, F., & Petrelli, D. (2001). User Involvement in customizing Adaptive Information Extraction from Texts: Position Paper Proceedings of the IJCAI01 Workshop on Adaptive Text Extraction and Mining.
Dörre, J., Gerstl, P., & Seiffert, R. (1999). Text mining: finding nuggets in mountains of textual data. Paper presented at the Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining.
Ellouze, N., Ahmed, M. B., & Metais, E. (2008). Overview of Topic Map Construction Approaches. Paper presented at the Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops.
Ellouze, N., Lammari, N., & Metais, E. (2012). CITOM: An incremental construction of multilingual topic maps. Data & Knowledge Engineering, 74, 46-62. doi: 10.1016/j.datak.2012.02.002
Ernst, H. (2003). Patent information for strategic technology management. World Patent Information, 25(3), 233-242. doi: 10.1016/s0172-2190(03)00077-2
Etzioni, O., Banko, M., Soderland, S., & Weld, D. S. (2008). Open information extraction from the web. Communication of ACM, 51(12), 68-74. doi: 10.1145/1409360.1409378
Etzioni, O., Cafarella, M., Downey, D., Kok, S., Popescu, A.-M., Shaked, T., . . . Yates, A. (2004). Web-scale information extraction in knowitall: (preliminary results). Paper presented at the Proceedings of the 13th international conference on World Wide Web, New York, NY, USA.
Fall, C. J., Törcsvári, A., Benzineb, K., & Karetka, G. (2003). Automated categorization in the international patent classification. SIGIR Forum, 37(1), 10-25. doi: 10.1145/945546.945547
Hearst, M. A. (1992). Automatic acquisition of hyponyms from large text corpora. Paper presented at the Proceedings of the 14th conference on Computational linguistics - Volume 2, Nantes, France.
Kang, I.-S., Na, S.-H., Kim, J., & Lee, J.-H. (2007). Cluster-based patent retrieval. Information Processing & Management, 43(5), 1173-1182. doi: 10.1016/j.ipm.2006.11.006
Kim, J.-H., & Choi, K.-S. (2007). Patent document categorization based on semantic structural information. Information Processing & Management, 43(5), 1200-1215. doi: 10.1016/j.ipm.2007.02.002
Kim, W., Jeong, O.-R., & Lee, S.-W. (2010). On social Web sites. Information Systems, 35(2), 215-236. doi: 10.1016/j.is.2009.08.003
Klein, D., & Manning, C. D. (2003a). Accurate unlexicalized parsing. Paper presented at the Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1, Sapporo, Japan.
Klein, D., & Manning, C. D. (2003b). Fast Exact Inference with a Factored Model for Natural Language Parsing. Paper presented at the Advances in Neural Information Processing Systems.
Krovetz, R. T. (2000). Viewing morphology as an inference process. Artificial Intelligence, 118(1-2), 277-294. doi: 10.1016/s0004-3702(99)00101-0
Lai, H. C., & Yang, T. C. (2000). A system architecture for intelligent browsing on the Web. Decision Support Systems, 28(3), 219-239. doi: 10.1016/s0167-9236(99)00087-1
Lee, C., Jeon, J., & Park, Y. (2011). Monitoring trends of technological changes based on the dynamic patent lattice: A modified formal concept analysis approach. Technological Forecasting and Social Change, 78(4), 690-702. doi: 10.1016/j.techfore.2010.11.010
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. doi: 10.1016/j.technovation.2008.10.006
Ma, Z. Z., & Yu, K. H. (2010). Research paradigms of contemporary knowledge management studies: 1998-2007. Journal of Knowledge Management, 14(2), 175-189. doi: Doi 10.1108/13673271011032337
Mitchell, T. M. (1997). Machine Learning. New York: McGraw-Hill, Inc.
Mukherjea, S., Bamba, B., & Kankar, P. (2005). Information retrieval and knowledge discovery utilizing a biomedical patent Semantic Web. IEEE Transactions on Knowledge and Data Engineering, 17(8), 1099-1110. doi: 10.1109/tkde.2005.130
Nanba, H. (2007). Query Expansion using an Automatically Constructed Thesaurus. Paper presented at the Proceedings of NTCIR-6 Workshop Meeting, Tokyo, Japan.
Nanba, H., Kondo, T., & Takezawa, T. (2010a). Automatic creation of a technical trend map from research papers and patents. Paper presented at the Proceedings of the 3rd international workshop on Patent information retrieval, Toronto, ON, Canada.
Nanba, H., Fujii, A., Iwayama, M., & Hashimoto, T. (2010b). Overview of the Patent Mining Task at the NTCIR-8 Workshop. Paper presented at the Proceedings of NTCIR-8 Workshop Meeting, Tokyo, Japan.
Nunnally, J. C. (1978). Psychometric theory ( 2nd ed.): McGraw-Hill, NewYork
Ong, T. H., Chen, H. C., Sung, W. K., & Zhu, B. (2005). Newsmap: a knowledge map for online news. Decision Support Systems, 39(4), 583-597. doi: 10.1016/j.dss.2004.03.008
Paice, C. D. (1990). Another stemmer. SIGIR Forum, 24(3), 56-61. doi: 10.1145/101306.101310
Pepper, S. (2002). The TAO of Topic Map Retrieved 09/28, 2012, from http://www.ontopia.net/topicmaps/materials/tao.html#d0e632
Porter, M. F. (1980). An algorithm for suffix stripping. Program-Automated Library and Information Systems, 14(3), 130-137. doi: 10.1108/eb046814
Roda, G., Tait, J., Piroi, F., & Zenz, V. (2010). CLEF-IP 2009: Retrieval Experiments in the Intellectual Property Domain Multilingual Information Access Evaluation I. Text Retrieval Experiments. In C. Peters, G. Di Nunzio, M. Kurimo, T. Mandl, D. Mostefa, A. Peñas & G. Roda (Eds.), (Vol. 6241, pp. 385-409): Springer Berlin / Heidelberg.
Rosso, P., Correa, S., & Buscaldi, D. (2011). Passage retrieval in legal texts. Journal of Logic and Algebraic Programming, 80(3-5), 139-153. doi: 10.1016/j.jlap.2011.02.001
Salton, G., Wong, A., & Yang, C. S. (1975). A vector space model for automatic indexing. Communications of the ACM, 18(11), 613-620. doi: 10.1145/361219.361220
Santoso, H. A., Haw, S. C., & Abdul-Mehdi, Z. T. (2011). Ontology extraction from relational database: Concept hierarchy as background knowledge. Knowledge-Based Systems, 24(3), 457-464. doi: DOI 10.1016/j.knosys.2010.11.003
Segev, A., & Sheng, Q. Z. (2012). Bootstrapping Ontologies for Web Services. IEEE Transactions on Services Computing, 5(1), 33-44. doi: 10.1109/tsc.2010.51
Tao, X., Li, Y., & Zhong, N. (2011). A Personalized Ontology Model for Web Information Gathering. IEEE Transactions on Knowledge and Data Engineering, 23(4), 496-511. doi: 10.1109/tkde.2010.145
Thurow, L. C. (1999). Building Wealth: The New Rules For Individuals, Companies and Nations In A Knowledge-Based Economy: HarperCollins Publishers.
Trappey, A. J. C., & Trappey, C. V. (2008). An R&D knowledge management method for patent document summarization. Industrial Management & Data Systems, 108(1-2), 245-257. doi: 10.1108/02635570810847608
Tseng, Y.-H., Lin, C.-J., & Lin, Y.-I. (2007). Text mining techniques for patent analysis. Information Processing & Management, 43(5), 1216-1247. doi: 10.1016/j.ipm.2006.11.011
Tseng, Y.-H., Wang, Y.-M., Lin, Y.-I., Lin, C.-J., & Juang, D.-W. (2007). Patent surrogate extraction and evaluation in the context of patent mapping. Journal of Information Science, 33(6), 718-736. doi: 10.1177/0165551507077406
Wang, H. C., Chen, Y. H., Kao, H. Y., & Tsai, S. J. (2011). Inference of transcriptional regulatory network by bootstrapping patterns. Bioinformatics, 27(10), 1422-1428. doi: 10.1093/bioinformatics/btr155
Wikipedia. (2012). United States Patent and Trademark Office Retrieved 09/23, 2012, from http://en.wikipedia.org/wiki/United_States_Patent_and_Trademark_Office
Wu, D., Lee, W. S., Ye, N., & Chieu, H. L. (2009). Domain adaptive bootstrapping for named entity recognition. Paper presented at the Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3, Singapore.
Wu, Y. J., & Dunaway, D. J. (2013). Creating a large topic map by integrating Wandora and Ontopia. Library Hi Tech, 31(1), 64-75. doi: 10.1108/07378831311303930
Yang, S. Y., & Soo, V. W. (2012). Extract conceptual graphs from plain texts in patent claims. Engineering Applications of Artificial Intelligence, 25(4), 874-887. doi: 10.1016/j.engappai.2011.11.006
Yi, M. (2008). Information organization and retrieval using a Topic Maps-based ontology: Results of a task-based evaluation. Journal of the American Society for Information Science and Technology, 59(12), 1898-1911. doi: 10.1002/asi.20899
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. doi: 10.1016/j.techfore.2004.08.011
Yoon, B. U., Yoon, C. B., & Park, Y. T. (2002). On the development and application of a self-organizing feature map-based patent map. R & D Management, 32(4), 291-300. doi: 10.1111/1467-9310.00261