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1
Lee, Y. & Geum, Y. (2023) Identifying patterns of mergers and acquisitions in startup: An empirical analysis using Crunchbase data
Lee, Y., Geum, Y.
IEEE Access, 2023
2
Kim, J., Kim, H., & Geum, Y. (2023) How to succeed in the market? Predicting startup success using a machine learning approach
Kim, J., Kim, H., Geum, Y.
Technological Forecasting and Social Change, 2023
3
Han, J., Jeon, B. & Geum, Y. (2022) Link Prediction Revisited: New Approach for Anticipating New Innovation Chances Using Technology Convergence
Han, J., Jeon, B., Geum, Y.
IEEE Transactions on Engineering Management, 2022
4
Park, M. & Geum, Y. (2022) Two-stage technology opportunity discovery for firm-level decision making: GCN-based link-prediction approach
Park, M., Geum, Y.
Technological Forecasting and Social Change, 2022
5
Han, M. & Geum, Y. (2022) Problem-oriented CBR: Finding potential problems from lead user communities
Han, M., Geum, Y.
Expert Systems with Applications, 2022
6
Ha, S., & Geum, Y. (2022). Identifying new innovative services using M&A data: An integrated approach of data-driven morphological analysis.
Ha, S., Geum, Y.
Technological Forecasting and Social Change, 2022
7
Kim, J. & Geum, Y. (2021) How to develop data-driven technology roadmaps: The integration of topic modeling and link prediction
Kim, J., Geum, Y.
Technological Forecasting and Social Change, 2021
8
Park, M. & Geum, Y. (2021) On the data-driven generation of new service idea: Integrated approach of morphological analysis and text mining
Park, M., Geum, Y.
Service Business, 2021
9
Kim, J., Jeon, W. & Geum, Y. (2021) Industry Convergence for Start-Up Businesses: Dynamic Trend Analysis Using Merger and Acquisition Information
Kim, J., Jeon, W., Geum, Y.
IEEE Transactions on Engineering Management, 2021
10
Kim, M. & Geum, Y. (2020) Predicting patent transactions using patent-based machine learning techniques
Kim, M., Geum, Y.
IEEE Access, 2020
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