Abstract
This paper suggests a method for Subject–Action–Object (SAO) network analysis of patents for technology trends identification by using the concept of function. The proposed method solves the shortcoming of the keyword-based approach to identification of technology trends, i.e., that it cannot represent how technologies are used or for what purpose. The concept of function provides information on how a technology is used and how it interacts with other technologies; the keyword-based approach does not provide such information. The proposed method uses an SAO model and represents “key concept” instead of “key word”. We present a procedure that formulates an SAO network by using SAO models extracted from patent documents, and a method that applies actor network theory to analyze technology implications of the SAO network. To demonstrate the effectiveness of the SAO network this paper presents a case study of patents related to Polymer Electrolyte Membrane technology in Proton Exchange Membrane Fuel Cells.
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References
Altshuller, G. S. (1984). Creativity as an exact science: the theory of the solution of inventive problems (Studies in cybernetics). New York: Gordon and Breach Science Publishers.
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. doi:10.1111/j.1467-9310.2008.00533.x.
Bhattacharya, S., & Basu, P. (1998). Mapping a research area at the micro level using co-word analysis. Scientometrics, 43(3), 359–372. doi:10.1007/bf02457404.
Bock, R. D., & Husain, S. Z. (1950). An adaptation of Holzinger’s B-coefficients for the analysis of sociometric data. Sociometry, 13(2), 146–153.
Bollobas, B. (1984). Graph theory and combinatorics. London: Academic Press.
Burt, R., & Schott, T. (1991). STRUCTURE. A general purpose network analysis program providing sociometric indices, cliques, structural and role equivalence, density tables, contagion, autonomy, power and equilibria in multiple network systems. Version 4.2. New York: Center for the Social Sciences, Columbia University.
Callon, M., Courtial, J.-P., & Laville, F. (1991). Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemistry. Scientometrics, 22(1), 155–205. doi:10.1007/bf02019280.
Callon, M., Courtial, J.-P., Turner, W. A., & Bauin, S. (1983). From translations to problematic networks: An introduction to co-word analysis. Social Science Information, 22(2), 191–235. doi:10.1177/053901883022002003.
Carrington, P. J. (2005). Models and methods in social network analysis (Structural analysis in the social sciences, 27 [i.e. 28]). Cambridge [u.a.]: Cambridge University Press.
Cascini, G., Fantechi, A., & Spinicci, E. (2004a). Natural language processing of patents and technical documentation. In 11th international conference PAM 2010, Zurich, Switzerland, April 7–9 (Vol. 3163, pp. 508–520).
Cascini, G., Fantechi, A., & Spinicci, E. (2004b). Natural language processing of patents and technical documentation. In Document Analysis Systems VI (pp. 508–520).
Cascini, G., Fantechi, A., & Spinicci, E. (2004c). Natural language processing of patents and technical documentation. In S. Marinai, & A. Dengel (Eds.), Document analysis systems VI (Vol. 3163, pp. 89–92). Lecture Notes in Computer Science. Berlin: Springer.
Cascini, G., & Russo, D. (2006). Computer-aided analysis of patents and search for TRIZ contradictions. International Journal of Product Development, 4, 52–67. doi:10.1504/ijpd.2007.011533.
Cascini, G., & Zini, M. (2008). Measuring patent similarity by comparing inventions functional trees. In International federation for information processing 20th world computer congress, Milano, Italy, September 7–10 (pp. 31–42).
Charniak, E., Carroll, G., Adcock, J., Cassandra, A., Gotoh, Y., Katz, J., et al. (1996). Taggers for parsers. Artificial Intelligence, 85(1–2), 45–57. doi:10.1016/0004-3702(95)00108-5.
Chen, L., Tokuda, N., & Adachi, H. (2003). A patent document retrieval system addressing both semantic and syntactic properties. Paper presented at the proceedings of the ACL-2003 workshop on Patent corpus processing—Vol. 20, Sapporo, Japan.
Choi, S., Lim, J., Yoon, J., & Kim, K. (2010). Patent function network analysis: A function based approach for analyzing patent information. In Y. Hosni, & T. Khalil (Eds.), 19th International conference for the international association of management of technology, Cairo, Egypt, March 8–11.
Dewulf, S. (2006). Directed Variation® systematic innovation in the established companies. In Conference on entrepreneurship and innovation, Maribor, Slovenia, March 30–31 2006, Citeseer.
Diestel, R. (2005). Graph theory. Berlin: Springer.
Hanneman, R., & Riddle, M. (2005). Introduction to social network methods. CA: University of California Riverside.
Hood, W., & Wilson, C. (2001). The literature of bibliometrics, scientometrics, and informetrics. Scientometrics, 52(2), 291–314. doi:10.1023/A:1017919924342.
Hopcroft, J., & Tarjan, R. (1973). Algorithm 447: efficient algorithms for graph manipulation. Communications of the ACM, 16(6), 372–378. doi:10.1145/362248.362272.
Kim, H., Choi, S., Jeong, C., & Kim, K. (2010). Cause-and-effect function analysis. In Management of innovation and technology (ICMIT), 2010 IEEE international conference on, 2–5 June 2010 (pp. 518–523).
KIPO (2006). Patent Map Repoart: Proton exchange membrane fuel cell Korea Intellectual Property Office.
Kostoff, R. (1998). The use and misuse of citation analysis in research evaluation. Scientometrics, 43(1), 27–43.
Law, J., & Hassard, J. (1999). Actor network theory and after. Malden: Blackwell.
Lee, W. (2008). How to identify emerging research fields using scientometrics: An example in the field of Information Security. Scientometrics, 76(3), 503–525. doi:10.1007/s11192-007-1898-2.
Lee, B., & Jeong, Y.-I. (2008). Mapping Korea’s national R&D domain of robot technology by using the co-word analysis. Scientometrics, 77(1), 3–19. doi:10.1007/s11192-007-1819-4.
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. doi:10.1111/j.1467-9310.2008.00509.x.
Lee, B., & Sounai, A. (2008). Polymer Electrolyte Membrane for fuel cell and membrane-electrode assembly and fuel cell including the same. United States Cheil Industries Inc. (Gumi-si, KR).
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.
Liang, Y., Tan, R., & Ma, J. (2008). Patent analysis with text mining for TRIZ. In Management of innovation and technology, 2008. ICMIT 2008. 4th IEEE international conference on, 21–24 Sept. 2008 (pp. 1147–1151).
Liang, Y., Gan, D., Guo, Y., & Zhang, P. (2009a). Computer-aided analysis of patents for product technology maturity forecasting. In R. Tan, G. Cao, & N. León (Eds.), Growth and development of computer-aided innovation (Vol. 304, pp. 295–303. Boston: IFIP Advances in Information and Communication Technology, Springer.
Liang, Y., Tan, R., Wang, C., & Li, Z. (2009b). Computer-aided classification of patents oriented to TRIZ. In Industrial engineering and engineering management, 2009. IEEM 2009. IEEE international conference on, 8–11 Dec. 2009 (pp. 2389–2393).
Linton, C. F. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41.
Liu, H. (2004). MontyLingua: An end-to-end natural language processor with common sense. http://web.media.mit.edu/~hugo/montylingua/. Accessed 15 Jan 2009.
Liu, H., & Singh, P. (2004). ConceptNet—A practical commonsense reasoning tool-kit. BT Technology Journal, 22(4), 211–226. doi:10.1023/B:BTTJ.0000047600.45421.6d.
Mehta, V., & Cooper, J. S. (2003). Review and analysis of PEM fuel cell design and manufacturing. Journal of Power Sources, 114(1), 32–53. doi:10.1016/s0378-7753(02)00542-6.
Miller, G. A. (1995). WordNet: A lexical database for English. Communications of the ACM, 38(11), 39–41. doi:10.1145/219717.219748.
Moehrle, M. (2010). Measures for textual patent similarities: a guided way to select appropriate approaches. Scientometrics, 85(1), 95–109. doi:10.1007/s11192-010-0243-3.
Moehrle, M., Walter, L., Geritz, A., & Müller, S. (2005). Patent-based inventor profiles as a basis for human resource decisions in research and development. R&D Management, 35(5), 513–524. doi:10.1111/j.1467-9310.2005.00408.x.
Mokken, R. J. (1979). Cliques, clubs and clans. Quality & Quantity, 13(2), 161–173. doi:10.1007/bf00139635.
Neff, M., & Corley, E. (2009). 35 years and 160,000 articles: A bibliometric exploration of the evolution of ecology. Scientometrics, 80(3), 657–682. doi:10.1007/s11192-008-2099-3.
Ohniwa, R., Hibino, A., & Takeyasu, K. (2010). Trends in research foci in life science fields over the last 30 years monitored by emerging topics. Scientometrics, 85(1), 111–127. doi:10.1007/s11192-010-0252-2.
Salamatov, Y., & Souchkov, V. (1999). TRIZ: The right solution at the right time: A guide to innovative problem solving. Hattem: Insytec.
Savransky, S. D. (2000). Engineering of creativity: Introduction to TRIZ methodology of inventive problem solving. London: CRC Press.
Sternitzke, C., & Bergmann, I. (2009). Similarity measures for document mapping: A comparative study on the level of an individual scientist. Scientometrics, 78(1), 113–130. doi:10.1007/s11192-007-1961-z.
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.
Tsourikov, V. M., Batchilo, L. S., & Sovpel, I. V. (2000). Document semantic analysis/selection with knowledge creativity capability utilizing subject-action-object (SAO) structures. Google Patents.
Verhaegen, P. A., D’Hondt, J., Vertommen, J., Dewulf, S., & Duflou, J. R. (2009). Relating properties and functions from patents to TRIZ trends. CIRP Journal of Manufacturing Science and Technology, 1(3), 126–130. doi:10.1016/j.cirpj.2008.09.010.
Yoon, J., Choi, S., & Kim, K. (2011). Invention property-function network analysis of patents: A case of silicon-based thin film solar cells. Scientometrics, 86(3), 687–703. doi:10.1007/s11192-010-0303-8.
Yoon, B., & Park, Y. (2004). A text-mining-based patent network: Analytical tool for high-technology trend. The Journal of High Technology Management Research, 15(1), 37–50. doi:10.1016/j.hitech.2003.09.003.
Acknowledgments
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2009-0088379).
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Choi, S., Yoon, J., Kim, K. et al. SAO network analysis of patents for technology trends identification: a case study of polymer electrolyte membrane technology in proton exchange membrane fuel cells. Scientometrics 88, 863–883 (2011). https://doi.org/10.1007/s11192-011-0420-z
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DOI: https://doi.org/10.1007/s11192-011-0420-z
Keywords
- Technology Subject-Action-Object (SAO)
- Function
- Patent mining
- Patent analysis
- Technology trends analysis
- Co-word analysis
- Actor network theory