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http://dx.doi.org/10.7232/JKIIE.2017.43.1.039

User Needs-Based Technology Opportunities in Heterogeneous Fields Using Opinion Mining and Patent Analysis  

Jang, Hyejin (Department of Industrial and System Engineering, Dongguk University)
Roh, Taeyeoun (Department of Industrial and System Engineering, Dongguk University)
Yoon, Byungun (Department of Industrial and System Engineering, Dongguk University)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.43, no.1, 2017 , pp. 39-48 More about this Journal
Abstract
In a digital economy, users actively express their needs in many ways. Thus, many researchers analyze what users need and whether they are satisfied or not through opinion mining. In addition, they begin to find technology opportunities in heterogeneous technology fields. But they did not connect users' opinion to technology development process, only focused on natural language processing or marketing or manufacturing area. Also, heterogeneous technology fields are focused on fusion technology. Thus, this study suggests a novel approach that is based on sentimental value and can be applied to exploring technology opportunities in heterogeneous fields. Sentimental value is calculated from users' opinion through sLDA. The heterogeneous technology opportunity is explored by patent analysis. This research contributes to suggesting a hybrid methodology through patent and users' opinion. In addition, it can provide managerial efficiency by suggesting base data onto decision making.
Keywords
Opinion Mining; Supervised LDA; Technology Opportunity; Heterogeneous Technology; Patent Analysis;
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Times Cited By KSCI : 7  (Citation Analysis)
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1 Singh, V. K., Piryani, R., Udding, A., and Waila, P. (2013), Sentiment analysis of movie reviews : A new feature-based heuristic for aspect-level sentiment classification, Automation, Computing, Communication, Control and Compressed Sensing (iMac4s).
2 Thorleuchter, D., Poel, D. V., and Prinzie, A. (2012), Analyzing existing customers' websites to improve the customer acquisition process as well as the profitability prediction in B-to-B marketing, Expert systems with applications, 39(3), 2597-2605.   DOI
3 Wu, M., Wang, L., Li, M., and Long, H. (2014), An approach of product usability evaluation based on Web mining in feature fatigue analysis, Computers and Industrial Engineering, 75, 230-238.   DOI
4 Yun, J.-H. (2011), Patent Information Analysis : Tools for Systematic R&D Planning, Industrial Engineering Magazine, 18(3), 23-28.
5 Kwon, J.-D. (2012), An actual proof study on selecting key patents based on patent index, Hansung University, Seoul, Korea.
6 Lee, C., Kang, B., and Shin, J. (2015), Novelty-focused patent mapping for technology opportunity analysis, Technological Forecasting and Social Change, 90(B), 355-365.   DOI
7 Lee, H.-J. (2005), Analysis of science and technology information necessary for research and development (R&D), Patent 21, 60, 33-39.
8 Lee, T. Y. (2009), Automatically learning user needs from online reviews for new product design, AMCIS 2009 Proceedings, 22.
9 Lee, T. Y., Li, S., and Wei, R. (2008), Needs-centric searching and ranking based on customer reviews, 2008 10th IEEE Conference on ECommerce Technology and the Fifth IEEE Conference on Enterprise Computing.
10 Lee, W. S. and Sohn, S. Y. (2015), Topic model analysis of research trend on spatial big data, Journal of Korean Institute of Industrial Engineers, 41(1), 64-73.   DOI
11 Lim, C., Yun, D., Park, I., Park, G., Koh, S., and Yoon, B. (2015), Exploring Prospective Research Areas in UI/UX through the Analysis of Patents, Korean Management Science Review, 32(4), 1-18.   DOI
12 Liu, B. (2012), Sentiment analysis and opinion mining, Synthesis Lectures on Human Language Technologies, 5(1), 1-167.   DOI
13 Min, H.-J. and Park, J. C. (2012), Identifying helpful reviews based on customer's mentions about experiences, Expert Systems with Applications, 39(15), 11830-11838.   DOI
14 Liu, Y., Huang, X., An, A., and Yu, X. (2008), Modeling and predicting the helpfulness of online reviews, 2008 Eighth IEEE International Conference on Data Mining.
15 Liu, Y., Jin, J., Ji, P., Harding, J. A., and Fung, R. Y. (2013), Identifying helpful online reviews : a product designer's perspective, Computer-Aided Design, 45(2), 180-194.   DOI
16 Mcauliffe, J. D. and Blei, D. M. (2008), Supervised topic models, Advances in Neural Information Processing Systems, 121-128.
17 No, H. J., An, Y., and Park, Y. (2015), A structured approach to explore knowledge flows through technology-based business methods by integrating patent citation analysis and text mining, Technological Forecasting and Social Change, 97, 181-192.   DOI
18 No, H. J. and Park, Y. (2010), Trajectory patterns of technology fusion: Trend analysis and taxonomical grouping in nanobiotechnology. Technological Forecasting and Social Change, 77(1), 63-75.   DOI
19 Paradigms, T. and Trajectories, T. (1982), A Suggested Interpretation of the Determinants and Directions of Technical Change, Research Policy, 11, 147-162.   DOI
20 Park, J. and Song, M. (2013), A study on the Research Trends in Library and Information Science in Korea using Topic Modeling, Journal of the Korean Society for Information Management, 30(1), 7-32.   DOI
21 Huang, L., Shang, L., Wang, K., Porter, A. L., and Zhang, Y. (2015), Identifying target for technology mergers and acquisitions using patent information and semantic analysis, 2015 Portland International Conference on Management of Engineering and Technology (PICMET).
22 Jeong, B. and Lee, H. (2016), Research Topics in Industrial Engineering 2001-2015, Journal of Korean Institute of Industrial Engineers, 42(6), 421-431.   DOI
23 Jeong, E. S., Kim, Y. G., Lee, S. C., Kim, Y. T., and Cxhang, Y. B. (2014), Identifying Emerging Free Technologies by PCT Patent Analysis, The Journal of the Korea Institute of Electronic Communication Sciences, 9(1), 111-122.   DOI
24 Jin, S. A., Heo, G. E., Jeong, Y. K., and Song, M. (2013), Topic-Network based Topic Shift Detection on Twitter, Journal of the Korean Society for Information Management, 30(1), 285-302.   DOI
25 Jo, C. Y., Lee, Y. M., Sin, H. J., and Park, H. J. (2005), Validation of claim as patent analysis indicator, Patent 21, 64, 14-21.
26 Kim, M., Park, Y., and Yoon, J. (2016), Generating patent development maps for technology monitoring using semantic patent-topic analysis, Computers and Industrial Engineering, 98, 289-299.   DOI
27 Kim, J. and Lee, S. (2016), Issues for Technology-Humanities Convertgence : Patent Keyword Analysis, Journal of Korean Institute of Industrial Engineers, 42(3), 231-240.   DOI
28 KISTI (2012), Design and construction of a knowledge base for technology opportunity discovery, Daejun.
29 Ko, N., Yoon, J., and Seo, W. (2014), Analyzing interdisciplinarity of technology fusion using knowledge flows of patents, Expert Systems with Applications, 41(4), 1955-1963.   DOI
30 An, J., Kim, K., Noh, H., and Lee, S. (2016), Identifying Converging Technologies in the ICT Industry : Analysis of Patents Published by Incumbents and Entrants, Journal of Korean Institute of Industrial Engineers, 42(3), 209-221.   DOI
31 Ghazizadeh, M., McDonald, A. D., and Lee. J. D. (2014), Text mining to decipher free-response consumer complaints insights from the NHTSA vehicle owner's complaint database, Human Factors : The Journal of the Human Factors and Ergonomics Society, 56(6), 1189-1203.   DOI
32 Bin, H., Lucheng, H., Feifei, W., and Hong, M. (2015), Assessment of the Connectivity between Technologies Based on Patent Co-classification, Beijing, China.
33 Blei, D. M., Ng, A. Y., and Jordan M. I. (2003), Latent dirichlet allocation, Journal of machine Learning research, 3, 993-1022.
34 Choi, C., Kim, S., and Park, Y. (2007), A patent-based cross impact analysis for quantitative estimation of technological impact : The case of information and communication technology, Technological Forecasting and Social Change, 74(8), 1296-1314.   DOI
35 Ghiassi, M., Skinner, J., and Zimbra, D. (2013), Twitter brand sentiment analysis : A hybrid system using n-gram analysis and dynamic artificial neural network, Expert Systems with Applications, 40(16), 6266-6282.   DOI
36 Griffiths, T. L. and Steyvers, M. (2004), Finding scientific topics, Proceedings of the National academy of Sciences, 101(suppl 1), 5228-5235.
37 Penalver-Martinez, I., Garcia-Sanchez, F., Rodriguez-Garcia, M. A., Moreano, V., Fraga, A., and Sanchez-Cervantes, J. L. (2014), Featurebased opinion mining through ontologies, Expert Systems with Applications, 41(13), 5995-6008.   DOI