How to combine term clumping and technology roadmapping for newly emerging science & technology competitive intelligence: “problem & solution” pattern based semantic TRIZ tool and case study

Scientometrics

Volumn 101, Issue 2, 2014, Pages 1375-1389

  Zhang, Yi ^a   Zhou, Xiao ^a   Porter, Alan L ^b,c   Vicente Gomila, Jose M ^d  

^a BEIJING INSTITUTE OF TECHNOLOGY   (China)

^b GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^c Search Technology Inc   (United States)

^d UNIVERSITAT POLITÈCNICA DE VALÈNCIA   (Spain)

Author keywords

DSSCs; Semantic TRIZ; Technology roadmapping; Text mining

Indexed keywords

EID: 84894610601     PISSN: 01389130     EISSN: 15882861     Source Type: Journal    
DOI: 10.1007/s11192-014-1262-2     Document Type: Article

References (31)

1. Blackburn, T. D., Mazzuchi, T. A., & Sarkani, S. (2012). Using a TRIZ framework for system engineering trade studies. Systems Engineering,15(3), 355–367.
2. Blei, D. (2012). Probabilistic topic models. Communications of the ACM,55(4), 77–84.
3. Blei, D., Ng, A., & Jordan, M. (2003). Latent Dirichlet allocation. Journal of Machine Learning Research,3, 993–1022.
4. Cascini, G., Fantechi, A., & Spinicci, E. (2004). Natural language processing of patents and technical documentation. In Document Analysis Systems VI (pp. 508–520).
5. Choi, S., Yoon, J., Kim, K., Lee, J., & Kim, C. (2011). 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.
6. Goldfire Innovator, http://inventionmachine.com/products-and-services/innovation-software/goldfire-innovator/. Accessed January 1, 2013.
7. Kerr, C., Mortara, L., Phaal, R., & Probert, D. (2006). A conceptual model for technology intelligence. International Journal of Technology Intelligence and Planning,2(1), 73–93.
8. Kim, Y., Tian, Y., Jeong, Y., Ryu, J., & Myaeng, S. (2009). Automatic discovery of technology trends from patent text. Proceedings of the 2009 ACM symposium on Applied Computing, Hawaii, USA.
9. Kostoff, R. N., Boylan, R., & Simons, G. R. (2004). Disruptive technology roadmaps. Technological Forecasting and Social Change,71, 141–159.
10. Moehrle, M. G. (2005). How combinations of TRIZ tools are used in companies—Results of a cluster analysis. R&D Management,35(3), 285–296.
11. Moehrle, M. G., 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.
12. Nakagawa, T. (2001). Introduction to TRIZ: A technological philosophy for creative problem solving. The 23rd Annual Symposium of Japan Creativity Society, Tokyo, Japan.
13. Newman, N. C., Porter, A. L., Newman, D., Courseault-Trumbach, C., & Bolan, D. (2012). Comparing methods to extract technical content for technological intelligence, Proceedings of Portland International Conference on Management of Engineering and Technology, Vancouver, Canada.
14. 2films. Nature,353(6346), 737–740.
15. Porter, A. L., & Cunningham, S. W. (2005). Tech mining: Exploiting new technologies for competitive advantage. New York: Wiley.
16. Porter, A. L., & Detampel, M. J. (1995). Technology opportunity analysis. Technological Forecasting and Social Change,49, 237–255.
17. Rantanen, K., & Domb, E. (2008). Simplified TRIZ: New problem solving applications for engineers and manufacturing professionals (2nd ed.). New York: Auerbach Publications.
18. Rizzi, C. (2011). TRIZ and intelligence property management. Research in Interactive Design,3, 123–128.
19. Savransky, S. D. (2000). Engineering of creativity (Introduction to TRIZ Methodology of Inventive Problem Solving). Florida: CRC Press LLC.
20. Shahbazpour, M., & Seidel, R. (2007). Strategic manufacturing system and process innovation through elimination of trade-offs. International Journal of Computer Integrated Manufacturing,20(5), 413–422.
21. Stephen, R. L. (2002). A conceptual design tool for engineer: An amalgamation of theory of constraints, theory of inventive problem solving and logic. Virginia: Old Dominion University.
22. Trumbach, C., & Payne, D. (2007). Identifying synonymous concepts in preparation for technology mining. Journal of Information Science,33(6), 660–677.
23. VantagePoint, www.theVantagePoint.com. Accessed January 1, 2013.
24. Verbitsky, M. (2004). Semantic TRIZ.triz-journal.com. http://www.triz-journal.com/archives/2004/. Accessed January 18, 2013.
25. Walsh, S. T. (2004). Roadmapping a disruptive technology: A case study—the emerging microsystems and top-down nanosystems industry. Technological Forecasting and Social Change,71, 161–185.
26. Walsh, S. T., & Linton, J. (2000). Infrastructure for emerging markets based on discontinuous innovations. Engineering Management Journal,12(2), 23–31.
27. Yoon, J., & Kim, K. (2012). Trend perceptor: A property—function based technology intelligence system for identifying technology trends from patents. Expert Systems with Applications,39, 2927–2938.
28. Zhang, Y., Guo, Y., Wang, X., Zhu, D., & Porter, A. L. (2013a). A hybrid visualization model for technology roadmapping: bibliometrics, qualitative methodology, and empirical study. Technology Analysis & Strategic Management,25(6), 707–724.
29. Zhang, Y., Zhou, X., Porter, A. L., & Vicente-Gomila, J. M. (2013b). Triple helix innovation in China’s dye-sensitized solar cell industry: Hybrid Methods with semantic TRIZ and technology roadmapping. Scientometrics. doi:10.1007/s11192-013-1090-9.
30. Zhang, Y., Porter, A. L., Hu, Z., Guo, Y., & Newman, N. C. (2014). “Term Clumping” for technical intelligence: A case study on dye-sensitized solar cells. Technological Forecasting & Social Change. doi:10.1016/j.techfore.2013.12.019.
31. Zhu, D., & Porter, A. L. (2002). Automated extraction and visualization of information for technological intelligence and forecasting. Technological Forecasting and Social Change,69, 495–506.