使用螢光粉之可見光發光二極體（phosphor-converted white LEDs）是固態照明領域中，最具環保價值的科技產品之一。本論文結合期刊論文與專利文件的引用觀點，輔以引用網路分析（citation network analysis）的角度，找出使用螢光粉之可見光發光二極體的發展脈絡，並以視覺化的方式呈現該技術領域之演化，以提供產官學界一個簡單而清楚的系統性概觀，以加速了解特定科技之發展。在本論文中，首先將分別從ISI Web of Science（WOS）與美國專利文件庫（USPTO）等公開資料庫中擷取相關文獻資料（包括學術論文與專利文件）。藉由這些文獻資料的引用關係，分別建立初步的引用網路。接下來將採用主路徑分析（main-path analysis）技術，分別針對使用螢光粉白光發光二極體技術在學術論文與專利文件的文獻，提供一個主要路徑，以挑選出該領域發展史中最具關鍵性之學術論文與專利文件。最後，吾人以「雙主路徑分析」（dual main-path analysis）的方式呈現該技術領域之科學連結性，以勾勒出使用螢光粉白光發光二極體技術的發展與演進。

Phosphor-converted white LEDs have become one of the most environment-friendly solid-state lighting products. This study offers a “phosphor-converted visible LEDs” development scenario from a perspective different from previous studies. In this thesis, we conduct data retrieval of academic papers and patent documents from ISI Web of Science (WOS) and USPTO database, respectively. Directional networks are constructed based on citation relationships among academic papers and patent publications to visualize the citation patterns. Main-path analyses are further conducted to trace the main knowledge flow through citation data, from which some papers and patents are found to have stronger impacts. Finally, a dual main-path approach is used to visualize the science-technology linkage, by which we measure how influential the scientific frontier is upon the related technological discipline. Dual main-path analysis is based on the citation relation between the paper main path and the patent main path, both of which are constructed respectively by key actors connected by directional arrows and are linked from papers to patents. Our findings could provide policy makers, especially those dealing with government-level research projects, and research group leaders with an intellectual basis for evaluating academic papers and forecasting possible opportunities for the industry.

[1] 李季達，”21世紀白光LED照明分析”，PIDA光電協進會，pp. 27-34，2000。
[2] Schubert E. F., Light-Emitting Diodes, Cambridge University Press, 2006.
[3] Steigerwald D.A., Bhat J.C., Collins D., Fletcher R.M., Holcomb M.O., Ludowise M.J., Martin P.S., Rudaz S.L., “Illumination with solid state lighting technology,” IEEE Journal of Selected Topics in Quantum Electronics, vol. 8, pp. 310–320, 2002.
[4] Chhajed S., Xi Y., Li Y.L., Gessmann T., Schubert, E.F., “Influence of junction temperature on chromaticity and color-rendering properties of trichromatic white-light sources based on light-emitting diodes,” Journal of Applied Physics, vol. 97, pp. 054506–054508, 2005.
[5] Pimputkar S., Speck J. S., DenBaars S. P., Nakamura S., “Prospects for LED lighting,” Nature Photonics, vol. 3, pp. 180–182, 2009.
[6] 黃翊軒，本體論為基之智慧型專利文件分類方法論研究，國立清華大學碩士論文，2007。
[7] Grossman D., Frieder O., Holmes D., Roberts D., “Integrating Structured Data and Text: a Relational Approach,” Journal of the American Society for Information Science, vol. 48, pp. 122–132, 1997.
[8] Raghavan V.V., Wong S.K.M., “A Critical Analysis of Vector Space Model for Information Retrieval,” Journal of the American Society for Information Science, vol. 37, pp. 279–287, 1986.
[9] McCallum A., Nigam K., “A Comparison of Event Models for Naive Bayes Text Classification,” Proceedings, AAAI’98 workshop on learning for text categorization, Madison, Wisconsin, July 26-30, pp. 41–48, 1998.
[10] Nigam K., Maccallum A.K., Thrun S., Mitchell T., “Text Classification from Labeled and Unlabeled Cocuments using EM,” Machine Learning Journal, pp. 103–134, 2000.
[11] Tam V., Sangtoso A., Setiono R., “A Comparative Study of Centroid-based, Neighborhood-based and Statistical Approaches, for Effective Document Categorization,” Proceedings, 16th International Conference on Pattern Recognition, no. 4, pp. 235–238, 2002.
[12] Chiang J., Chen Y., “Hierarchical Fuzzy-knn Networks for News Documents Categorization,” Proceedings, the 10th IEEE International Conference on Fuzzy System, no. 2, pp. 720–723, 2001.
[13] Lam W., Han Y., “Automatic Textual Document Categorization based on Generalized Instance Sets and a Metamodel,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, pp. 628–633, 2003.
[14] Svingen B., “Using Genetic Programming for Document Classification,” Proceedings, The Eleventh International Florida Artificial Intelligence Reseach Society Conference, Sanibel Island, Florida, May 18–20, pp. 63–67, 1998.
[15] Zhihang C., Chengwen N., Yi L., “Neural Network Approaches for Text Document Categorization,” 2006 International Joint Conference on Neural Networks, Sheraton Vancouver Wall Centre Hotel, Vancouver, BC, Canada, July 16–21, 2006.
[16] Massey, L., “On the Quality ART1 Text Clustering,” Neural Networks, vol. 16, pp. 771–778, 2003.
[17] Lam W., Ruiz M.E., Srinivasan P., “Automatic Text Categorization and its Applications to Text Retrieval,” IEEE Transactions on Knowledge Data Engineering, vol. 11, pp. 865–879, 1999.
[18] Jennifer F., “Neural Networks and Document Classification,” Canadian Conference on Electrical and Computer Engineering, Canada, 1993.
[19] Karras D.A., Mertzios B.G., “A Robust Meaning Extraction Methodology using Supervised Neural Networks,” Proceedings, Australian Joint Conference on Artificial Intelligence, Canberra, Australia. December 2–6, pp. 498–510, 2002.
[20] Trappey A.J.C., Lin S.C.I., Wang C.L., “Using Neural Network Categorization Method to Develop an Innovative Knowledge Management Technology for Patent Document Classification,” Proceeding, The 9th International Conference on Computer Supported Cooperative Work in Design, Coventry, United Kingdom, May 24–26, pp. 830–835, 2005.
[21] Parasuraman A., “Reflections on contributing to a discipline through research and writing,” Journal of the Academy of Marketing Science, vol. 31, pp. 314–318, 2003.
[22] Dosi G., “Technological paradigms and technological trajectories”, Research Policy, vol. 11, pp. 147–162, 1982.
[23] Stuart T. E., Podolny J. M., “Local Search and the Evolution of Technological Capabilities,” Strategic Management Journal, vol. 17, pp. 21–38, 1996.
[24] Meyer M., “Does science push technology? Patents citing scientific literature,” Research Policy, vol. 29, pp. 409–434, 2000.
[25] Yoon B., Park Y., “A text-mining-based patent network: analytical tool for high-technology trend,” Journal of High Technology Management Research, vol. 15, pp. 37–50, 2004.
[26] 李沛錞、蘇信寧，以專利引用網絡分析探討技術發展之動態演化，科技管理學刊，第十四卷第三期，pp. 65–107, 2009。
[27] Hall B. H., Jaffe A. B., Trajtenberg M., “Market value and patent citations: a first look,” National bureau of economic research, Working paper no. W7741, 2000.
[28] Narin F., “Patent bibliometrics,” Scientometrics, vol. 30, pp. 147–155, 1994.
[29] Frances M., Ginski J. M., “Citation patterns of the cardiovascular serial literature,” Journal of the American Society for Information Science, vol. 23, pp.172–175, 1972.
[30] Garfield E., “Is citation analysis a legitimate evaluation tool?,” Scientometrics, vol. 1, pp. 359–375, 1979.
[31] Wasserman S., Galaskiewicz J., Advances in Social Network Analysis：Research in the Social and Behavioral Sciences, Sage Publications Inc., 1994.
[32] Wellman B., Berkowitz S. D., Introduction: studying social structures: A network approach, Cambridge University Press, 1988.
[33] Marsden P., Campbell K.E., “Measuring tie strength,” Social Forces, vol. 63, pp. 482–501, 1984.
[34] Freeman L. C., “Centrality in Social Networks: Conceptual Clarification,” Social Networks, vol. 1, pp. 215–239, 1979.
[35] Bonacich P., “Factoring and weighting approaches to clique identification,” Journal of Mathematical Sociology 2: pp. 113–120, 1972.
[36] Langville A., Meyer C., Google's PageRank and Beyond: The Science of Search Engine Rankings. Princeton University Press, 2006.
[37] Scott, J., Social Network Analysis: A Handbook. Sage, London., 1991.
[38] Newman M.E.J., “Fast algorithm for detecting community structure in networks,” Physical Review E, vol. 69, 066133, 2004.
[39] Newman M.E.J., Girvan M., “Finding and evaluating community structure in networks,” Physical Review E, vol. 69, 026113, 2004.
[40] Kajikawa Y., Yoshikawa J., Takeda Y., Matsushima K., “Tracking emerging technologies in energy research: Toward a roadmap for sustainable energy,” Technological Forecasting & Social Change, vol. 75, pp. 771–782, 2008.
[41] Kajikawa Y., Takeda Y., “Citation network analysis of organic LEDs,” Technological Forecasting & Social Change, vol. 76, pp. 1115–1123, 2009.
[42] Shibata N., Kajikawa Y., Sakata I., “Extracting the commercialization gap between science and technology — Case study of a solar cell,” Technological Forecasting & Social Change, vol. 77, pp. 1147–1155, 2010.
[43] Garfield E., Sher I. H., Torpie R. J., The use of citation data in writing the history of science, Philadelphia, Institute for Scientific Information, 1964.
[44] Hummon N. P., Doreian P., “Connectivity in a citation network: The development of DNA theory,” Social Networks, vol. 11, pp. 39–63, 1989.
[45] Yin L., Kretschmer H., Hanneman R. A., Liu Z., “The evolution of a citation network topology: The development of the journal Scientometrics,” Proceedings of the International Workshop on Webometrics, informetrics, and scientometrics & Seventh COLLNET Meeting, France, pp. 92–113, 2006.
[46] Verspagen B., “Mapping technological trajectories as patent citation networks: A study on the history of fuel cell research,” Advances in Complex Systems, vol. 10, pp. 93–115, 2007.
[47] Mina A., Ramlogan R., Tampubolon G., Metcalfe J. S., “Mapping evolutionary trajectories: Applications to the growth and transformation of medical knowledge,” Research Policy, vol. 36, pp. 789–806, 2007.
[48] Roberto F., Alessandro N., Bart V., “Mapping technological trajectories as patent citation networks. An application to data communication standards,” Economics of Innovation and New Technology, vol. 18, pp. 311–336, 2009.
[49] Liu J. S., Lu Y. Y., Lu W. M., Lin J. Y., “Data Envelopment Analysis 1978-2010: A Citation-Based Literature Survey,” Omega-The International Journal of Management Science, 10.1016/j.omega.2010.12.006, 2012.
[50] 曾佑強，磷酸鋰鐵電池未來發展趨勢－學術論文之主路徑分析，國立台灣科技大學碩士論文，2011。
[51] Batagelj V., “Efficient algorithms for citation network analysis,” University of Ljubljana, Institute of Mathematics, Physics and Mechanics, Preprint series, vol. 41, pp. 897, 2003.
[52] Batagelj V., Mrvar A., “Pajek - program for large network analysis,” Connections, vol. 21, pp. 47–57, 1998.
[53] Meyer M., “Tracing knowledge flows in innovation systems,” Scientometrics, vol. 54, pp. 193-212, 2002.
[54] Boyack K.W., Klavans R., “Measuring science-technology interaction using rare inventor-author names,” Journal of Informetrics, vol. 2, pp. 173–182, 2008.
[55] Narin F., Noma E., “Is technology becoming science?,” Scientometrics, vol. 7, pp. 369–381, 1985.