Publications

International Journal Paper

1. Jang, K., Choi, J., Lee, H. S., & Kim, B.* (2025) A novel similarity-based recommendation for identifying potential customers in new markets using an inter-firm transaction network. Technological Forecasting & Social Change, 216, 124151.

2. Bose, A., & Kim, B.* (2025). A novel similarity score for link prediction approach using financial transaction networks and firms’ attribute. IEEE Access, 13, 52051 - 52068. 

3. Bose, A., & Kim, B.* (2025). Graph-based approach for industrial market segmentation using financial transaction network structure and firm’s attribute. IEEE Access, 13, 16394 - 16412.

4. Choi, J., Kim, B.*, & Lee, H. S. (2024). Competitor identification with memory in a dynamic financial transaction network. Annals of Operations Research, 341, 349-374. 

5. Zubair, I. M., Lee, Y. S., & Kim, B.* (2024). A new permutation-based method for ranking and selecting group features in multiclass classification. Applied Sciences, 14(8), 3156.

6. Yoon, J., Bose, A., Park, H., Lee, J., Kim, B.* (2023). A novel methodology for estimating technology value and importance of factors in market‑based approach. Systems, 11, 439, 1-25.

7. Ayat, M., Kim, B., & Kang, C. W.* (2023). A new data mining-based framework to predict the success of private participation in infrastructure projects. International Journal of Construction Management, 23(13), 2151-2159.

8. Zubair, I. M., & Kim, B.* (2022) A group feature ranking and selection method based on dimension reduction technique in high-dimensional data. IEEE Access, 10, 125136-125147.

9. Choi, M., Yoo, S.-H., Lee, J., Choi, J., &  Kim, B.* (2022). A modified gamma/Gompertz/NBD model for estimating technology lifetime. Scientometrics, 127, 5731-5751.

10. Choi, J., Tosyali, A., Kim, B.*, Lee, H. S., & Jeong, M. K. (2022). A novel method for identifying competitors using a financial transaction network. IEEE Transactions on Engineering Management, 69(4), 845-860.

11. Kim, B., Jeong, Y. S.*, & Jeong, M. K. (2021). New multivariate kernel density estimator for uncertain data classification. Annals of Operations Research, 303, 413-431.

12. Tosyali, A., Choi, J., Kim, B.*, Lee, H., & Jeong, M. K.* (2021). A dynamic graph-based approach to ranking firms for identifying key players using inter-firm transactions. Annals of Operations Research, 303, 5-27.

13. Choi, J., Kim, B.*, Han, C. H., Hahn, H., Park, H., Yoo, J., & Jeong, M. K. (2021). Methodology for assessing the contribution of knowledge services during the new product development process to business performance. Expert Systems with Applications, 167, 113860.

14. Sardar, S. K., Sarkar, B., & Kim, B*. (2021). Integrating machine learning, radio frequency identification, and consignment policy for reducing unreliability in smart supply chain management. Processes, 9(2), 247.

15. Kim, B., Jeong, Y. S., Tong, S. H., & Jeong, M. K.* (2020). A generalised uncertain decision tree for defect classification of multiple wafer maps. International Journal of Production Research, 58(9), 2805-2821.

16. Lee, J., Kim, B., & Ahn, S.* (2019). Maintenance optimization for repairable deteriorating systems under imperfect preventive maintenance. Mathematics, 7(8), 716.

17. Choi, J., Kim, B., Jeong, Y., Han, H., Yoo, J., & Jeong, M. K.* (2017). Data mining-based variable assessment methodology for evaluating the contribution of characteristics of knowledge services of a public research institute to business performance of firms. Expert Systems with Applications, 84, 37–48.

18. Kim, B., Gazzola, G., Lee, J. M., Kim, Coh, B. Y., & Jeong, M. K.* (2017). Two phase edge outlier detection model for technology opportunity discovery. Scientometrics, 113(1), 1-16.

19. Kim, B., Jeong, Y. S., Tong, S. H., Chang, I. K., & Jeong, M. K.* (2016). Step-down spatial randomness test for detecting abnormalities in DRAM wafers with multiple spatial maps. IEEE Transactions on Semiconductor Manufacturing, 29(1), 57-65.

20. Rodriguez, A., Tosyali, A., Kim, B., Choi, J., Lee, J. M., Coh, B. Y., & Jeong, M. K.* (2016). Patent clustering and outlier ranking methodologies for attributed patent citation networks for technology opportunity discovery. IEEE Transactions on Engineering Management, 63(4), 426-437.

21. Zhao, K., Xie, Y., Tsui, K. L., Wei, Q., Huang, W., Jiang, W., ... & Li, L. (2015). System informatics: from methodology to applications. IEEE Intelligent Systems, 30(6), 12-29.

22. Rodriguez, A., Kim, B., Turkoz, M., Lee, J. M., Coh, B. Y., & Jeong, M. K.* (2015). New multi-stage similarity measure for calculation of pairwise patent similarity in a patent citation network. Scientometrics, 103(2), 565-581.

23. Yoo, S. H., Kim, B., & Jeong, M. K.* (2015). Modelling of technology lifetime based on patent citation data and segmentation. Journal of the Operational Research Society, 66(3), 450-462.

24. Rodriguez, A., Kim, B., Lee, J. M., Coh, B. Y., & Jeong, M. K.* (2015). Graph kernel based measure for evaluating the influence of patents in a patent citation network. Expert Systems with Applications, 42(3), 1479-1486.

25. Kim, B., Jeong, Y.S.*, Tong, S.H., Chang, I.K. & Jeong, M.K. (2015). A regularized singular value decomposition-based approach for failure pattern classification on fail bit map in a DRAM wafer. IEEE Transactions on Semiconductor Manufacturing, 28(1), pp.41-49.

26. Kim, B., Gazzola, G., Lee, J.M., Kim, D., Kim, K. & Jeong, M.K.* (2014). Inter-cluster connectivity analysis for technology opportunity discovery. Scientometrics, 98(3), pp.1811-1825.

*  Corresponding author

Domestic Journal Paper

1. 최이수, 윤주호, 김병훈* (2023). 패턴 불균형에 강건한 자가 지도학습을 활용한 웨이퍼 불량 패턴 클러스터링 방법 제안. 대한산업공학회지, 49(4), 330-343.

2. 송창용, 정영선, 김병훈*. (2022). Multi class data description 기반의 웨이퍼 빈 맵 불량 패턴 분류 및 신규 불량 패턴 검출방법. 대한산업공학회지, 48 (3), 298-309 

3. 윤주호, 추병하, & 김병훈*. (2021). 기계학습을 기반으로 한 자외선 경화형 도장의 부착성 불량 위험수준 정량화. 대한산업공학회지, 47(4), 406-413.

4. 성태응, 이종택, 김병훈, 전승표, & 박현우. (2017). 실물옵션 기반 기술가치 평가모델 정교화와 변동성 유효구간에 관한 연구. 기술혁신학회지, 20(3), 732-753.

* 교신저자

International Conference  Paper

1. Joo, T., Kang, D., & Kim, B. (2020). Regularizing activations in neural networks via distribution matching with the Wasserstein metric. International Conference on Learning Representation, 1-13.

Patent

1. 딥러닝 기반의 가치 평가 방법 및 그 장치. (2019.01). 등록번호: 1019360290000.

2. 유사기업 선정 기반의 시장 규모 및 예상 매출액 추정 장치 및 방법. (2018.04). 등록번호: 1018507530000.