在技術快速變遷與創新的年代，企業渴望完整應變產業環境之需求與競爭者的發展，進而推導出未來產品與技術的部署，希冀結合技術面與專利面的綜合競爭力，來拓展企業的科技革新。而技術藍圖（Technology Roadmap）是未來產品與企業策略的結合，技術探勘（Technology mining） 是找出技術在相關文獻、期刊、雜誌與專業網站論壇中的資訊連結，是過去技術累積與未來技術發展之模型，結合兩者即可掌握產品、技術與專利架構，亦可進一步當成企業或研發機構內部技術規劃之參考。雖然技術藍圖是判斷技術趨勢的重要依據，但過去少有研究探勘技術資訊、進而追縱技術趨勢定義技術藍圖。因此，本研究擬發展整合技術探勘之決策分析架
構，以多屬性決策分析(MADM)建立數據驅動技術藍圖，希冀未來可以將技術藍圖與專利地圖相互結合，作為企業擬定未來產品與專利布局方向之總計畫。因此，本研究擬先以專家意見作為技術關鍵字之確認，並從所有資源中找出關鍵字間的關聯，再結合約略集合理論(Rough Set)得出不同層次關鍵字間的影響關係，最後帶入決策實驗室分析法(DEMATEL)找出技術間的影響程度，進而發展出技術策略藍圖，其整合市場、產品及技術相關資訊，可作為企業之研發策略、產品創新與技術的開發方向。實證研究將以有望顛覆產業未來的潛力技術─無人機為例，分析本架構之可行性。透過本研究之進程，可以得出起落裝置、無線通訊與地理區域和全球定位系統將會是未來無人機發展的三大重點技術。研究結果可供企業即時掌握競爭者與領導廠商之技術發展方向，並做為訂定未來研發策略之依據。

In the generation of rapid change in technology, enterprise eager to completely strain the demand of industry environment and the development of competitor, and then deduce the deployment of products and technology in future, aspiring to combine with the comprehensive competitiveness of the technology and the patent to expand the technological innovation. The technology roadmap is an integration of future products and business strategy. Technology mining is an analytical procedure to find out the technology in the link of relevant literature, journals, and professional platform, it is previous technology accumulation and future technology development model, combining both of them can predominate the products, patent and technology architecture, and also be taken a deeper reference to internal technology planning by companies and research institutions. Although the technology roadmap is an important basis for judging the trend of technology, there was few research about mining information and tracking technology trends to construct the technology roadmap. Therefore, this study intends to develop the integration of technology mining and decision analysis framework, with Multiple Attribute Decision Making (MADM) to build data-driven technology roadmap, hope combining technology roadmap and patent map for the enterprise to develop future products and direction of the patent portfolio in the future. Therefore, this study employs the expert’s opinion to confirm the technical key and utilizes mining technology to find out the correlation between the keywords from all sources, and combines with Dominance Based Rough Set Approach (DRSA) checking at different levels of relationships, finally introduces the Decision Making Trial and Evaluation Laboratory (DEMATEL) to find out the influence degree of technology and derives the technology roadmap. It will integrate market, product and technology-related information, and used as the developing direction for enterprise technology strategy. In this research, we will analyze unmanned aerial vehicle(UAV) which is expected to subvert the future industry. Through the research process, it can be concluded that landing gear, wireless communication and geographical area and global positioning system will be the three key technologies for future UAV development. The results can be used in the enterprise to grasp the technical development direction of the competitors and the leaders and as the basis for the future research and development strategy.

Agrawal, R., Imieliński, T., & Swami, A. (1993). Mining association rules between sets of items in large databases. Paper presented at the Acm sigmod record.
Becker, H. A., & Sanders, K. (2006). Innovations in meta-analysis and social impact analysis relevant for tech mining. Technological Forecasting and Social Change, 73(8), 966-980.
Bommer, M., & Jalajas, D. S. (2004). Innovation sources of large and small technology-based firms. IEEE Transactions on engineering management, 51(1), 13-18.
Bray, O. H., & Garcia, M. L. (1997). Technology roadmapping: the integration of strategic and technology planning for competitiveness. Paper presented at the Proceedings of the Portland International Conference on Management of Engineering and Technology (PICMET).
Daim, T. U., & Oliver, T. (2008). Implementing technology roadmap process in the energy services sector: A case study of a government agency. Technological Forecasting and Social Change, 75(5), 687-720.
Geum, Y., Lee, H., Lee, Y., & Park, Y. (2015). Development of data-driven technology roadmap considering dependency: An ARM-based technology roadmapping. Technological Forecasting and Social Change, 91, 264-279.
Gopalakrishnan, S., & Bierly, P. E. (2006). The impact of firm size and age on knowledge strategies during product development: A study of the drug delivery industry. IEEE Transactions on engineering management, 53(1), 3-16.
Guo, Y., Zhou, X., Porter, A. L., & Robinson, D. K. (2015). Tech mining to generate indicators of future national technological competitiveness: Nano-Enhanced Drug Delivery (NEDD) in the US and China. Technological Forecasting and Social Change, 97, 168-180.
Han, J., Pei, J., & Kamber, M. (2011). Data mining: concepts and techniques: Elsevier.
Hinchberger, B. (2004). Clearing the data smog. Paper presented at the International Trade Forum.
Holmes, C., & Ferrill, M. (2005). The application of operation and technology roadmapping to aid Singaporean SMEs identify and select emerging technologies. Technological Forecasting and Social Change, 72(3), 349-357.
Huang, Z., Lu, X., & Duan, H. (2011). Mining association rules to support resource allocation in business process management. Expert Systems with Applications, 38(8), 9483-9490.
Julien, P.-A., Andriambeloson, E., & Ramangalahy, C. (2004). Networks, weak signals and technological innovations among SMEs in the land-based transportation equipment sector. Entrepreneurship & Regional Development, 16(4), 251-269.
Kostoff, R. N., & Schaller, R. R. (2001). Science and technology roadmaps. IEEE Transactions on engineering management, 48(2), 132-143.
Kotsiantis, S., & Kanellopoulos, D. (2006). Association rules mining: A recent overview. GESTS International Transactions on Computer Science and Engineering, 32(1), 71-82.
Lee, S., Lee, S., Seol, H., & Park, Y. (2008). Using patent information for designing new product and technology: keyword based technology roadmapping. R&d Management, 38(2), 169-188.
Lee, S., & Park, Y. (2005). Customization of technology roadmaps according to roadmapping purposes: Overall process and detailed modules. Technological Forecasting and Social Change, 72(5), 567-583.
Liu, D.-R., & Shih, Y.-Y. (2005). Integrating AHP and data mining for product recommendation based on customer lifetime value. Information & Management, 42(3), 387-400.
Manufacturing, U. o. C. I. f. (2001). T-plan: the fast start to technology roadmapping: planning your route to success: University of Cambridge.
Parra-López, E., Bulchand-Gidumal, J., Gutiérrez-Taño, D., & Díaz-Armas, R. (2011). Intentions to use social media in organizing and taking vacation trips. Computers in human behavior, 27(2), 640-654.
Porter, A. L. (2009). Tech mining for future-oriented technology analyses. Text Mining.
Porter, A. L., & Cunningham, S. W. (2004). Tech mining: exploiting new technologies for competitive advantage (Vol. 29): John Wiley & Sons.
Robinson, D. K., Huang, L., Guo, Y., & Porter, A. L. (2013). Forecasting Innovation Pathways (FIP) for new and emerging science and technologies. Technological Forecasting and Social Change, 80(2), 267-285.
Swanson, D. R. (1987). Two medical literatures that are logically but not bibliographically connected. Journal of the American Society for Information Science, 38(4), 228.
Tanabe, K., & Watanabe, C. (2005). Sources of small and medium enterprises excellent business performance in a service oriented economy. Journal of Services Research, 5(1), 5.
Trumbach, C. C., & Payne, D. (2007). Identifying synonymous concepts in preparation for technology mining. Journal of Information Science, 33(6), 660-677.
Trumbach, C. C., Payne, D., & Kongthon, A. (2006). Technology mining for small firms: Knowledge prospecting for competitive advantage. Technological Forecasting and Social Change, 73(8), 937-949.
Tzeng, G.-H., Chiang, C.-H., & Li, C.-W. (2007). Evaluating intertwined effects in e-learning programs: A novel hybrid MCDM model based on factor analysis and DEMATEL. Expert Systems with Applications, 32(4), 1028-1044.
Watts, R., Courseault, C., & Kapplin, S. (2001). Identifying unique information using principal component decomposition. Management of technology: the key to prosperity in the third millennium. Elsevier Science, Pergamon.
Watts, R. J., & Porter, A. L. (1997). Innovation forecasting. Technological Forecasting and Social Change, 56(1), 25-47.
Watts, R. J., Porter, A. L., & Courseault, C. (1999). Functional analysis: deriving systems knowledge from bibliographic information resources. Information Knowledge Systems Management, 1(1), 45-61.
Yoon, B., Phaal, R., & Probert, D. (2008). Morphology analysis for technology roadmapping: application of text mining. R&d Management, 38(1), 51-68.
Yoon, B., Phaal, R., & Probert, D. (2008). Structuring technological information for technology roadmapping: data mining approach. AIKED, 8, 417-422.