2024

  • Youchan Park and In-Young Ko, “Multi-Temporal-Scale Event Detection and Clustering in IoT Systems”, To appear in Internet of Things, Elsevier (SCIE)
  • Arogya Kharel, Kyeongdeok Baek, and In-Young Ko, “Effective Model Replacement for Solving Objective Mismatches in Pre-trained Model Compositions”, To appear in Proceedings of the 31st Asia-Pacific Software Engineering Conference (APSEC 2024), December 3-6, 2024, Chongqing, China
  • Sven Casteleyn, Tommi Mikkonen, Alberto García Simón, In-Young Ko, Giuseppe Loseto (Eds.), Current Trends in Web Engineering, ICWE 2023 International Workshops, BECS, SWEET and WALS, Alicante, Spain, June 6–9, 2023, Revised Selected Papers, Communications in Computer and Information Science 1898, Springer 2024 (ISBN 978-3-031-50384-9)
  • Dae-Young Park, “Graph-theoretical Approach to Enhance Accuracy of Financial Fraud Detection Using Synthetic Tabular Data Generation”, In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM 2024), October 21-25, 2024, Boise, Idaho, USA [PhD Symposium Paper, Acceptance rate: 26%]
  • Dae-Young Park and In-Young Ko, “Graph-based Tabular Data Synthesis Model for More Effective Financial Application”, In Proceedings of the IJCAI-24 Workshop on Recommender Systems in Finance (Fin-RecSys), August 4, 2024, Jeju, Korea [Workshop Paper]
  • Eunchan Park, Kyeongdeok Baek, and In-Young Ko, “HiDRA: A Hierarchical Decentralized Reactive Autoscaler for Spatio-temporal Bursts of Load”, In Proceedings of the 2024 IEEE International Conference on Web Services (ICWS 2024), July 7-13, 2024, Shenzhen, China [Work-in-progress Paper]
  • Xiangchi Song, Zhaoyan Wang, Kyeongdeok Baek, and In-Young Ko, “EPFLU: Efficient Peer-to-peer Federated Learning for Personalized User Models in Edge-Cloud Environments”, 4th International Workshop on Big data driven Edge Cloud Services (BECS 2024) Co-located with the 24th International Conference on Web Engineering (ICWE 2024), June 17-20, 2024, Tampere, Finland [Workshop Paper]
  • Dae-Young Park and In-Young Ko, “An Empirical Study of Utility and Disclosure Risk for Tabular Data Synthesis Models: In-Depth Analysis and Interesting Findings”, In Proceedings of the 2024 IEEE International Conference on Big Data and Smart Computing (BigComp 2024), January 18 – 21, 2024, Bangkok, Thailand [Best Paper Award]

2023

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2005

  • Hwayoun Lee, Ho-Jin Choi, and In-Young Ko, A Semantically-Based Software Component Selection Mechanism for Intelligent Service Robots, The 4th Mexican International Conference on Artificial Intelligence (MICAI2005), A. Gelbukh, A. de Albornoz, and H. Terashima (Eds.), Lecture Notes in Artificial Intelligence (LNAI), 2005, Springer-Verlag. [SCIE]
  • Hyung-Min Koo, and In-Young Ko, “A Repository Framework for Self-Growing Robot Software”, In Proceedings of 12th Asia-Pacific Software Engineering Conference (APSEC’2005), Taiwan, December 2005. [Acceptance rate: 29%]
  • Soo-Yong Park, In-Young Ko, and Hyeong-Soo Chang, “Toward Self-adaptive Robot Software: A Framework and Approach”, The 2005 US – Korea Conference on Science, Technology and Entrepreneurship, August 11-13, 2005, University of California, Irvine (UCI), Irvine, California, USA.

2004

  • Hyun-Chong Kim, Ho-Jin Choi, and In-Young Ko, “An Architectural Model to Support Adaptive Software Systems for Sensor Networks”, In Proceedings of the 1st Asia-Pacific Workshop on Software Architectures and Component Technologies (APSEC’04), November 2004, Busan, Korea.
  • In-Young Ko, and Robert Neches, Composing Web Services for Large-Scale Tasks, IEEE Internet Computing, Vol. 7, Issue 5, pp. 52–59, 2003. DOI: 10.1109/MIC.2003.1232518. [SCIE]
  • Hyun-Chong Kim, Ho-Jin Choi, and In-Young Ko, “Architecture-based Adaptive Software Systems for Sensor Networks”, In Proceedings of the ACIS International Conference on Computer and Information Science, pp. 99-104, August 2004, Los Angeles, USA.

~ 2003: