Selected Publications

 

List of publications from DBLP Server can be found at [ DBLP SangKeun Lee ]

  • [EMNLP] Hyuntae Park, Sooyeon Kim, Jiwon Park, and SangKeun Lee, “MolSC: Leveraging Substituent Contributions to Enhance Fine-grained Molecular Understanding in LLMs”, To appear in Proc. of the 2026 Conference on Empirical Methods in Natural Language Processing (EMNLP), Budapest, Hungary, October 2026.
  • [EMNLP] Sangyun Kim*, Junho Kim*, and SangKeun Lee (* equal contribution), “Chronos: Chronology-Grounded Continued Pre-training for Language Model Adaptation to Materials Science”, To appear in Proc. of the 2026 Conference on Empirical Methods in Natural Language Processing (EMNLP), Budapest, Hungary, October 2026.
  • [ACL] Eojin Jeon and SangKeun Lee, “PICTURE: Enhancing Theory-of-Mind in Large Language Models by Revealing, Not Hiding, Characters’ Lack of Knowledge”, Proc. of Annual Meeting of the Association for Computational Linguistics (ACL), San Diego, USA, July 2026.
  • [ACL(F)] SungHo Kim, Juhyeong Park, Eda Atalay, and SangKeun Lee, “SCRIPT: A Subcharacter Compositional Representation Injection Module for Korean Pre-Trained Language Models”, Findings of the Association for Computational Linguistics: ACL 2026, San Diego, USA, July 2026.
  • [TACL] Yeachan Kim*, Mingyu Lee*, and SangKeun Lee (* equal contribution), “A Survey on Memory-Efficient Fine-Tuning for Large Language Models”, Transactions of the Association for Computational Linguistics, Vol. 14, pp.960-982, June 2026.
  • [ICLR] Gukhyeon Lee*, Yeachan Kim*, and SangKeun Lee (* equal contribution), “KnowProxy: Adapting Large Language Models by Knowledge-guided Proxy”, Proc. of the Fourteenth International Conference on Learning Representations (ICLR), Rio de Janeiro, Brazil, April 2026.
  • [EMNLP] Hyuntae Park*, Yeachan Kim*, and SangKeun Lee (* equal contribution), “Bridging the Gap Between Molecule and Textual Descriptions via Substructure-aware Alignment”, Proc. of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp.23470-23490, Suzhou, China, November 2025.
  • [EMNLP] Junho Kim, Soyeon Bak, Mingyu Lee, Minju Hong, Songha Kim, Tae-Eui Kam, and SangKeun Lee, “Connecting the Knowledge Dots: Retrieval-augmented Knowledge Connection for Commonsense Reasoning”, Proc. of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp.23582–23601, Suzhou, China, November 2025.
  • [EMNLP(F)] Eojin Jeon*, Mingyu Lee*, Sangyun Kim, Junho Kim, Wanzee Cho, Tae-Eui Kam, and SangKeun Lee (* equal contribution), ““Going to a trap house” conveys more fear than “Going to a mall”: Benchmarking Emotion Context Sensitivity for LLMs”, Findings of the Association for Computational Linguistics: EMNLP 2025, pp.14848–14869, Suzhou, China, November 2025.
  • [ACL] SungHo Kim*, Nayeon Kim*, Taehee Jeon, and SangKeun Lee (* equal contribution), “Polishing Every Facet of the GEM: Testing Linguistic Competence of LLMs and Humans in Korean”, Proc. of Annual Meeting of the Association for Computational Linguistics (ACL), pp.9955-9984, Vienna, Austria, July 2025.
  • [ACL] (SAC Highlights Award) Yerim Oh, Jun-Hyung Park, Junho Kim, SungHo Kim, and SangKeun Lee, “Incorporating Domain Knowledge into Materials Tokenization”, Proc. of Annual Meeting of the Association for Computational Linguistics (ACL), pp.9623-9644, Vienna, Austria, July 2025.
  • [ACL] Mingyu Lee, Yeachan Kim, Wing-Lam Mok, and SangKeun Lee, “Curriculum Debiasing: Toward Robust Parameter-Efficient Fine-Tuning Against Dataset Biases”, Proc. of Annual Meeting of the Association for Computational Linguistics (ACL), pp.9524-9540, Vienna, Austria, July 2025.
  • [ACL] Yeachan Kim and SangKeun Lee, “Forward Knows Efficient Backward Path: Saliency-Guided Memory-Efficient Fine-tuning of Large Language Models”, Proc. of Annual Meeting of the Association for Computational Linguistics (ACL), pp.9341-9356, Vienna, Austria, July 2025.
  • [PAKDD] Nayeon Kim*, Eojin Jeon*, Jun-Hyung Park, and SangKeun Lee (* equal contribution), “Handling Korean Out-of-Vocabulary Words with Phoneme Representation Learning”, Proc. of the 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), LNAI 15872, pp.480-491, Sydney, Australia, June 2025.
  • [ESWA] Mingyu Lee, Junho Kim, Jun-Hyung Park, and SangKeun Lee, “Continual Debiasing: A Bias Mitigation Framework for Natural Language Understanding Systems”, Expert Systems With Applications, Vol.271, May 2025.
  • [EMNLP] Jun-Hyung Park, Yeachan Kim, Mingyu Lee, Hyuntae Park, and SangKeun Lee, “MolTRES: Improving Chemical Language Representation Learning for Molecular Property Prediction”, Proc. of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp.14241–14254, Miami, USA, November 2024.
  • [EMNLP] Hojae Lee*, Junho Kim*, and SangKeun Lee (* equal contribution), “Mentor-KD: Making Small Language Models Better Multi-step Reasoners”, Proc. of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp.17643–17658, Miami, USA, November 2024.
  • [EMNLP(F)] Junho Kim*, Yeachan Kim*, Jun-Hyung Park, Yerim Oh, Suho Kim, and SangKeun Lee (* equal contribution), “MELT: Materials-aware Continued Pre-training for Language Model Adaptation to Materials Science”, Findings of the Association for Computational Linguistics: EMNLP 2024, pp.10690–10703, Miami, USA, November 2024.
  • [EMNLP(F)] Hyuntae Park*, Yeachan Kim*, Jun-Hyung Park, and SangKeun Lee (* equal contribution), “Zero-shot Commonsense Reasoning over Machine Imagination”, Findings of the Association for Computational Linguistics: EMNLP 2024, pp.11451–11471, Miami, USA, November 2024.
  • [EMNLP] Jun-Hyung Park*, Hyuntae Park*, Yeachan Kim, Woosang Lim, and SangKeun Lee (* equal contribution), “Moleco: Molecular Contrastive Learning with Chemical Language Models for Molecular Property Prediction” (Industry), Proc. of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp.408–420, Miami, USA, November 2024.
  • [EMNLP] Yeachan Kim, Jun-Hyung Park, SungHo Kim, Juhyeong Park, Sangyun Kim, and SangKeun Lee, “SEED: Semantic Knowledge Transfer for Language Model Adaptation to Materials Science” (Industry), Proc. of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp.421–428, Miami, USA, November 2024.
  • [ACL] Yeachan Kim and SangKeun Lee, “SparseFlow: Accelerating Transformers by Sparsifying Information Flows”, Proc. of Annual Meeting of the Association for Computational Linguistics (ACL), pp.5937-5948, Bangkok, Thailand, August 2024.
  • [ACL] Yeachan Kim*, Junho Kim*, and SangKeun Lee (* equal contribution), “Towards Robust and Generalized Parameter-Efficient Fine-Tuning for Noisy Label Learning”, Proc. of Annual Meeting of the Association for Computational Linguistics (ACL), pp.5922-5936, Bangkok, Thailand, August 2024.
  • [ACL(F)] Jun-Hyung Park, Mingyu Lee, Junho Kim, and SangKeun Lee, “Coconut: Contextualized Commonsense Unified Transformers for Graph-Based Commonsense Augmentation of Language Models”, Findings of the Association for Computational Linguistics: ACL 2024, pp.5815-5830, Bangkok, Thailand, August 2024.
  • [ACL(F)] SungHo Kim*, Juhyeong Park*, Yeachan Kim, and SangKeun Lee (* equal contribution), “KOMBO: Korean Character Representations Based on the Combination Rules of Subcharacters”, Findings of the Association for Computational Linguistics: ACL 2024, pp.5102-5119, Bangkok, Thailand, August 2024.
  • [EMNLP] Jun-Hyung Park*, Hyuntae Park*, Youjin Kang, Eojin Jeon, and SangKeun Lee (* equal contribution), “DIVE: Towards Descriptive and Diverse Visual Commonsense Generation”, Proc. of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp.9677–9695, Singapore, December 2023.
  • [EMNLP] Yeachan Kim, Junho Kim, Jun-Hyung Park, Mingyu Lee, and SangKeun Lee, “Leap-of-Thought: Accelerating Transformers via Dynamic Token Routing”, Proc. of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp.15757–15769, Singapore, December 2023.
  • [EMNLP] Eojin Jeon*, Mingyu Lee*, Juhyeong Park, Yeachan Kim, Wing-Lam Mok, and SangKeun Lee (* equal contribution), “Improving Bias Mitigation through Bias Experts in Natural Language Understanding”, Proc. of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp.11053–11066, Singapore, December 2023.
  • [EMNLP] Joon-Young Choi, Junho Kim, Jun-Hyung Park, Wing-Lam Mok, and SangKeun Lee, “SMoP: Towards Efficient and Effective Prompt Tuning with Sparse Mixture-of-Prompts”, Proc. of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp.14306-14316, Singapore, December 2023.
  • [AACL] Huiju Kim, Youjin Kang, and SangKeun Lee, “Examining a Consistency of Visual Commonsense Reasoning based on Person Grounding”, Proc. of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (IJCNLP-AACL), pp.1026-1039, Bali, Indonesia, November 2023.
  • [ACL(F)] Yeachan Kim*, Junho Kim*, Wing-Lam Mok, Jun-Hyung Park and SangKeun Lee (* equal contribution), “Client-Customized Adaptation for Parameter-Efficient Federated Learning”, Findings of the Association for Computational Linguistics: ACL 2023, pp.1159-1172, Toronto, Canada, July 2023.
  • [EACL(F)] San-Hee Park*, Kang-Min Kim*, O-Joun Lee, Youjin Kang, Jaewon Lee, Su-Min Lee, SangKeun Lee (* equal contribution), ““Why do I feel offended?” – Korean Dataset for Offensive Language Identification”, Findings of the Association for Computational Linguistics: EACL 2023, pp.1112-1123, Dubrovnik, Croatia, May 2023.
  • [AAAI] Jun-Hyung Park, Yeachan Kim, Junho Kim, Joon-Young Choi, and SangKeun Lee, “Dynamic Structure Pruning for Compressing CNNs”, Proc. of the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), pp.9408–9416, Washington DC, USA, February 2023.
  • [EMNLP] Nayeon Kim*, Jun-Hyung Park*, Joon-Young Choi, Eojin Jeon, Youjin Kang, and SangKeun Lee (* equal contribution), “Break it Down into BTS: Basic, Tiniest Subword Units for Korean”, Proc. of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp.7007–7024, Abu Dhabi, UAE, December 2022.
  • [EMNLP] Junho Kim*, Jun-Hyung Park*, Mingyu Lee, Wing-Lam Mok, Joon-Young Choi, and SangKeun Lee (* equal contribution), “Tutoring Helps Students Learn Better: Improving Knowledge Distillation for BERT with Tutor Network”, Proc. of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp.7371–7382, Abu Dhabi, UAE, December 2022.
  • [EMNLP] Mingyu Lee*, Jun-Hyung Park*, Junho Kim, Kang-Min Kim, and SangKeun Lee (* equal contribution), “Efficient Pre-training of Masked Language Model via Concept-based Curriculum Masking”, Proc. of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp.7417–7427, Abu Dhabi, UAE, December 2022.
  • [TECS] Jun-Hyung Park, Kang-Min Kim, and SangKeun Lee , “Quantized Sparse Training: A Unified Trainable Framework for Joint Pruning and Quantization of DNNs”, ACM Transactions on Embedded Computing Systems, Vol.21, Issue.5, Article 60, October 2022.
  • [ACL(F)] Yong-Ho Jung*, Jun-Hyung Park*, Joon-Young Choi, Mingyu Lee, Junho Kim, Kang-Min Kim, and SangKeun Lee (* equal contribution), “Learning from Missing Relations: Contrastive Learning with Commonsense Knowledge Graphs for Commonsense Inference”, Findings of the Association for Computational Linguistics: ACL 2022, pp.1514-1523, Dublin, Ireland, May 2022.
  • [ESWA] Jun-Hyung Park, Byung-Ju Choi, and SangKeun Lee , “Examining the Impact of Adaptive Convolution on Natural Language Understanding”, Expert Systems With Applications, Vol.189, March 2022.
  • [EMNLP] San-Hee Park*, Kang-Min Kim*, Seonhee Cho*, Jun-Hyung Park, Hyuntae Park, Hyuna Kim, Seongwon Chung, and SangKeun Lee (* equal contribution), “KOAS: Korean Text Offensiveness Analysis System” (Demo), Proc. of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp.72-78, Punta Cana, Dominican Republic, November 2021.
  • [EACL] Ohjoon Kwon*, Dohyun Kim*, Soo-Ryeon Lee, Junyoung Choi, and SangKeun Lee (* equal contribution), “Handling Out-of-Vocabulary Problem in Hangeul Word Embeddings”, Proc. of the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL), pp.3213–3221, Kyiv, Ukraine, April 2021.
  • [EMNLP(F)] Kang-Min Kim, Bumsu Hyeon, Yeachan Kim, Jun-Hyung Park, and SangKeun Lee, “Multi-pretraining for Large-scale Text Classification”, Findings of the Association for Computational Linguistics: EMNLP 2020, pp.2041-2050, November 2020.
  • [ACL] Yeachan Kim, Kang-Min Kim, and SangKeun Lee, “Adaptive Compression of Word Embeddings”, Proc. of Annual Meeting of the Association for Computational Linguistics (ACL), pp.3950-3959, Seattle, USA, July 2020.
  • [SAC] Jungho Lee, Byung-Ju Choi, Yeachan Kim, Kang-Min Kim, Woo-Jong Ryu, and SangKeun Lee, “Personalizing Large-scale Text Classification by Modeling Individual Differences”, Proc. of  ACM Symposium on Applied Computing (ACM SAC), pp.900-902, Brno, Czech Republic, April 2020.
  • [BigData] Song-Eun Lee, Kang-Min Kim, Woo-Jong Ryu, Jemin Park, and SangKeun Lee, “From Text Classification to Keyphrase Extraction for Short Text”, Proc. of IEEE International Conference on Big Data (BigData), pp.1137-1142, Los Angeles, USA, December 2019.
  • [NAACL] Byung-Ju Choi, Jun-Hyung Park, and SangKeun Lee, “Adaptive Convolution for Text Classification”, Proc. of Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT), pp.2475-2485, Mineapolis, USA, June 2019.
  • [WWW] Kang-Min Kim, Yeachan Kim, Jungho Lee, Ji-Min Lee, and SangKeun Lee, “From Small-scale to Large-scale Text Classification”, Proc. of International Conference on World Wide Web (WWW), pp.853-862, San Francisco, USA, May 2019.
  • [SAC] Jung-Hyun Lee, Woo-Jong Ryu, Kang-Min Kim, and SangKeun Lee, “MoCA: A Novel Privacy-preserving Contextual Advertising Platform on Mobile Devices”, Proc. of ACM Symposium on Applied Computing (ACM SAC), pp.1208-1215, Limassol, Cyprus, April 2019.
  • [IC] Kang-Min Kim*, Woo-Jong Ryu*, Jun-Hyung Park, and SangKeun Lee (* equal contribution), “meChat: In-device Personal Assistant for Conversational Photo Sharing”, IEEE Internet Computing, Vol.23, Issue.2, pp.23-30, March/April 2019.
  • [COLING] Yeachan Kim, Kang-Min Kim, Ji-Min Lee, and SangKeun Lee, “Learning to Generate Word Representations using Subword Information”, Proc. of the 27th International Conference on Computational Linguistics (COLING), pp.2551-2561, New Mexico, USA, August 2018.
  • [PAKDD] Kang-Min Kim, Aliyeva Dinara, Byung-Ju Choi, and SangKeun Lee, “Incorporating Word Embeddings into Open Directory Project based Large-scale Classification”, Proc. of the 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp.376-388, Melbourne, Australia, June 2018.
  • [KNOSYS] Zolzaya Dashdorj, Stanislav Sobolevsky, SangKeun Lee, and Carlo Ratti, “Deriving Human Activity from Geo-located Data by Ontological and Statistical Reasoning”, Knowledge-Based Systems, Vol.143, pp.225-235, March 2018.
  • [Middleware] So-Jung Park, Jung-Hyun Lee, So-Young Jun, Kang-Min Kim and SangKeun Lee, “MoCA+: Incorporating User Modeling into Mobile Contextual Advertising” (Demo), Proc. of ACM/IFIP/USENIX International Conference on Middleware (Middleware), pp.21-22, Las Vegas, USA, December 2017.
  • [WWWJ] Md. Hijbul Alam, Woo-Jong Ryu, and SangKeun Lee, “Hashtag-based Topic Evolution in Social Media”, World Wide Web Journal, Vol.20, Issue.6, pp.1527-1549, November 2017.
  • [UbiComp] Woo-Jong Ryu, HyeonTaek Oh, and SangKeun Lee, “sigInterface: A Personalized Interface for Intelligent Services” (Poster), Proc. of ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2017): Adjunct, pp.185-188, Hawaii, USA, September 2017.
  • [MobiSys] Jung-Hyun Lee, So-Young Jun, So-Jung Park, Kang-Min Kim and SangKeun Lee, “Mobile Contextual Advertising Platform based on Tiny Text Intelligence” (Demo), Proc. of ACM International Conference on Mobile Systems, Applications and Services (ACM MobiSys), page 181, Niagara Falls, USA, June 2017.
  • [MobiSys] Hyunwoong Bang, Hyunsub Kim and SangKeun Lee, “sigSocial: A Novel Social Media Aggregation Service using a Tiny Text Intelligence” (Demo), Proc. of ACM International Conference on Mobile Systems, Applications and Services (ACM MobiSys), page 184, Niagara Falls, USA, June 2017.
  • [IS] Woo-Jong Ryu, Jung-Hyun Lee, and SangKeun Lee, “Utilizing Verbal Intent in Semantic Contextual Advertising”, IEEE Intelligent Systems, Vol.32, Issue.3, pp.7-13, May/June 2017.
  • [WWW] Woo-Jong Ryu, Jung-Hyun Lee, Kang-Min Kim, and SangKeun Lee, “meCurate: Personalized Curation Service using a Tiny Text Intelligence” (Demo), Proc. of International Conference on World Wide Web (WWW): Companion Volumn, pp.269-272, Perth, Australia, April 2017.
  • [SAC] (Best Paper Award) HaeYong Shin, GeunJae Lee, Woo-Jong Ryu and SangKeun Lee, “Utilizing Wikipedia Knowledge in Open Directory Project-based Text Classification”, Proc. of ACM Symposium on Applied Computing (ACM SAC), pp.309-314, Marrakesh, Morocco, April 2017.
  • [UbiComp] HaeYong Shin, HyeonTaek Oh, Woo-Jong Ryu, and SangKeun Lee, “sigAlbum: An Embedded Photo Service using a Tiny Text Intelligence” (Demo), Proc. of ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2016): Adjunct, pp.373-376, Heidelberg, Germany, September 2016.
  • [INS] Md. Hijbul Alam, Woo-Jong Ryu, and SangKeun Lee, “Joint Multi-grain Topic Sentiment: Modeling Semantic Aspects for Online Reviews”, Information Sciences, Vol.339, pp.206-223, April 2016.
  • [INS] Byung-Gul Ryu, JongWoo Ha, and SangKeun Lee, “XQStream++: Fast Tuple Extraction Algorithm for Streaming XML Data”, Information Sciences, Vol.314, pp.311-326, September 2015.
  • [IC] JongWoo Ha, Jung-Hyun Lee, and SangKeun Lee, “EPE: An Embedded Personalization Engine for Mobile Users”, IEEE Internet Computing, Vol.18, Issue 1, pp.30-37, January/February 2014.
  • [TWEB] Jung-Hyun Lee, JongWoo Ha, Jin-Yong Jung, and SangKeun Lee, “Semantic Contextual Advertising based on the Open Directory Project”, ACM Transactions on the Web, Vol.7, Issue.4, Article 24, October 2013.
  • [ICDM] Md. Hijbul Alam and SangKeun Lee, “Semantic Aspect Discovery for Online Reviews”, Proc. of the IEEE International Conference on Data Mining (IEEE ICDM), pp.816-821, Brussels, Belgium, December 2012.
  • [KAIS] Md. Hijbul Alam, JongWoo Ha, and SangKeun Lee, “Novel Approaches to Crawling Important Pages Early”, Knowledge and Information Systems, Vol.33, No.3, pp.707-734, December 2012.
  • [INS] SangKeun Lee, Byung-Gul Ryu, and Kun-Lung Wu, “Examining the Impact of Data-access Cost on XML Twig Pattern Matching”, Information Sciences, Vol.203, pp.24-43, October 2012.
  • [TMC] Jae-Ho Choi, Kyu-Sun Shim, SangKeun Lee, and Kun-Lung Wu,  “Handling Selfishness in Replica Allocation over a Mobile Ad Hoc Network”, IEEE Transactions on Mobile Computing, Vol.11, No.2, pp.278-291, February 2012.
  • [CIKM] JongWoo Ha, Jung-Hyun Lee, Kyu-Sun Shim, and SangKeun Lee, “EUI: An Embedded Engine for Understanding User Intents from Mobile Devices” (Demo), Proc. of the 19th ACM International Conference on Information and Knowledge Management (ACM CIKM), pp. 1935-1936, Toronto, Canada, October 2010.
  • [TKDE] Hye-Kyeong Ko and SangKeun Lee, “A Binary String Approach for Updates in Dynamic Ordered XML Data”, IEEE Transactions on Knowledge and Data Engineering, Vol.22, No.4, pp.602-607, April 2010.
  • [WIDM] Jung-Jin Lee, Jung-Hyun Lee, JongWoo Ha, and SangKeun Lee, “Novel Web Page Classification Techniques in Contextual Advertising”, Proc. of the 11th ACM International Workshop on Web Information and Data Management (ACM WIDM), pp.39-47, Hong Kong, China, November 2009.
  • [INS] Hye-Kyeong Ko, Min-Jeong Kim, and SangKeun Lee, “On the Efficiency of Secure XML Broadcasting “, Information Sciences, Vol.177, Issue.24, pp.5505-5521, December 2007.
  • [MobiDE] Jae-Ho Choi, Sang-Hyun Park, Myung-Soo Lee, Yon Dohn Chung, and SangKeun Lee, “XIR: Cache Invalidation Strategy for XML Data in Mobile Environments”, Proc. of the 6th International ACM Workshop on Data Engineering for Wireless and Mobile Access (ACM MobiDE), pp.79-82, Beijing, China, June 2007.
  • [TKDE] SangKeun Lee, Chong-Sun Hwang, and Masaru Kitsuregawa, “Efficient, Energy Conserving Transaction Processing in Wireless Data Broadcast”, IEEE Transactions on Knowledge and Data Engineering, Vol.18, No.9, pp.1225-1238, September 2006.
  • [MDM] SangKeun Lee and SungSuk Kim, “Performance Evaluation of a Predeclaration-based Transaction Processing in a Hybrid Data Delivery”, Proc. of the 5th International Conference on Mobile Data Management (IEEE MDM), pp.266-273, Berkeley, USA, January 2004.
  • [TKDE] SangKeun Lee, Chong-Sun Hwang, and Masaru Kitsuregawa, “Using Predeclaration for Efficient Read-only Transaction Processing in Wireless Data Broadcast”, IEEE Transactions on Knowledge and Data Engineering, Vol.15, No.6, pp.1579-1583, November/December 2003.
  • [ICDCS] SangKeun Lee, Masaru Kitsuregawa, and Chong-Sun Hwang, “Using Predeclaration for Efficient Read-only Transaction Processing in Wireless Data Broadcast”, Proc. of the 22nd International Conference on Distributed Computing Systems (IEEE ICDCS), pp.441-442, Vienna, Austria, July 2002.
  • [DAPD] SangKeun Lee, Chong-Sun Hwang, and HeonChang Yu, “Revisiting Transaction Management in Multidatabase Systems”, Distributed and Parallel Databases, Vol.9, No.1, pp.39-65, 2001.
  • [MobiDE] SangKeun Lee, Chong-Sun Hwang, and HeonChang Yu, “Supporting Transactional Cache Consistency in Mobile Database Systems”, Proc. of the 1st International Workshop on Data Engineering for Wireless and Mobile Access (ACM MobiDE), pp.6-13, Seattle, USA, August 1999.
  • [CIKM] SangKeun Lee, Chong-Sun Hwang, and WonGyu Lee, “A Uniform Approach to Global Concurrency Control and Recovery in Multidatabase Environments”, Proc. of the 6th International Conference on Information and Knowledge Management (ACM CIKM), pp.51-58, Las Vegas, USA, November 1997.
  • [CIKM] SangKeun Lee, SoonYoung Jung, and Chong-Sun Hwang, “A New Conflict Relation for Concurrency Control and Recovery in Object-based Databases”, Proc. of the 5th International Conference on Information and Knowledge Management (ACM CIKM), pp.288-295, Maryland, USA, November 1996.

 

International Patents

  • [US Patent] US Patent 11328125, Method and server for text classification using multi-task learning, May 10, 2022
  • [EPO Patent] EPO Patent 2533430, Portable communication terminal for extracting subjects of interest to the user, and a method therefor, March 11, 2020
  • [US Patent] US Patent 10423723, Apparatus and method for extracting semantic topic, September 24, 2019
  • [US Patent] US Patent 10380244, Server and method for providing content based on context information, August 13, 2019
  • [US Patent] US Patent 9323845, Portable communication terminal for extracting subjects of interest to the user, and a method therefor, April 26, 2016
  • [US Patent] US Patent 9152723, Method and apparatus for providing internet service in mobile communication terminal, October 6, 2015
  • [US Patent] US Patent 7457615, Method for processing query effectively in radio data broadcast environment, November 25, 2008
  • [US Patent] US Patent 7136968, System and method for maintaining cache consistency in a wireless communication system, November 14, 2006