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ORCIDJae-Gil Lee 0001
Person information
- affiliation: Korea Advanced Institute of Science and Technology (KAIST), Data Mining Lab, Daejeon, Korea
Other persons with the same name
- Jae-Gil Lee (aka: Jae-gil Lee, Jae Gil Lee) — disambiguation page
- Jae-Gil Lee 0002
![[0000-0001-7376-4480]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0001-7376-4480")
(aka: Jae-gil Lee 0002) — Hallym University, Media School, South Korea (and 1 more) - Jae-Gil Lee 0003 — Hongik University, School of Electronic and Electrical Engineering, Seoul, South Korea
- Jae-Gil Lee 0004 — Korea Electronics Technology Institute, Bucheon, South Korea (and 1 more)
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2020 – today
- 2024
[c68]Doyoung Kim, Dongmin Park, Yooju Shin, Jihwan Bang, Hwanjun Song, Jae-Gil Lee:
Adaptive Shortcut Debiasing for Online Continual Learning. AAAI 2024: 13122-13131- [c67]Hwanjun Song, Minseok Kim, Jae-Gil Lee:
Toward Robustness in Multi-Label Classification: A Data Augmentation Strategy against Imbalance and Noise. AAAI 2024: 21592-21601 - [c66]Jihwan Bang, Sumyeong Ahn, Jae-Gil Lee:
Active Prompt Learning in Vision Language Models. CVPR 2024: 26994-27004 - [c65]Doyoung Kim, Susik Yoon, Dongmin Park, Youngjun Lee, Hwanjun Song, Jihwan Bang, Jae-Gil Lee:
One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning. ICML 2024 - [c64]Minyoung Bae, Yooju Shin, Youngeun Nam, Youngseop Lee, Jae-Gil Lee:
Semi-Supervised Learning for Time Series Collected at a Low Sampling Rate. KDD 2024: 59-70 - [c63]Youngeun Nam, Susik Yoon, Yooju Shin, Minyoung Bae, Hwanjun Song, Jae-Gil Lee, Byung Suk Lee:
Breaking the Time-Frequency Granularity Discrepancy in Time-Series Anomaly Detection. WWW 2024: 4204-4215 - [e6]Makoto Onizuka, Jae-Gil Lee, Yongxin Tong, Chuan Xiao, Yoshiharu Ishikawa, Sihem Amer-Yahia, H. V. Jagadish, Kejing Lu:
Database Systems for Advanced Applications - 29th International Conference, DASFAA 2024, Gifu, Japan, July 2-5, 2024, Proceedings, Part I. Lecture Notes in Computer Science 14850, Springer 2024, ISBN 978-981-97-5551-6 [contents] - [e5]Makoto Onizuka, Jae-Gil Lee, Yongxin Tong, Chuan Xiao, Yoshiharu Ishikawa, Sihem Amer-Yahia, H. V. Jagadish, Kejing Lu:
Database Systems for Advanced Applications - 29th International Conference, DASFAA 2024, Gifu, Japan, July 2-5, 2024, Proceedings, Part IV. Lecture Notes in Computer Science 14853, Springer 2024, ISBN 978-981-97-5561-5 [contents] - [e4]Makoto Onizuka, Jae-Gil Lee, Yongxin Tong, Chuan Xiao, Yoshiharu Ishikawa, Sihem Amer-Yahia, H. V. Jagadish, Kejing Lu:
Database Systems for Advanced Applications - 29th International Conference, DASFAA 2024, Gifu, Japan, July 2-5, 2024, Proceedings, Part VI. Lecture Notes in Computer Science 14855, Springer 2024, ISBN 978-981-97-5571-4 [contents] - [e3]Makoto Onizuka, Jae-Gil Lee, Yongxin Tong, Chuan Xiao, Yoshiharu Ishikawa, Sihem Amer-Yahia, H. V. Jagadish, Kejing Lu:
Database Systems for Advanced Applications - 29th International Conference, DASFAA 2024, Gifu, Japan, July 2-5, 2024, Proceedings, Part VII. Lecture Notes in Computer Science 14856, Springer 2024, ISBN 978-981-97-5574-5 [contents] - [i21]Patara Trirat, Yooju Shin, Junhyeok Kang, Youngeun Nam, Jihye Na, Minyoung Bae, Joeun Kim, Byunghyun Kim, Jae-Gil Lee:
Universal Time-Series Representation Learning: A Survey. CoRR abs/2401.03717 (2024) - [i20]Byunghyun Kim, Jae-Gil Lee:
Continuous-Time Linear Positional Embedding for Irregular Time Series Forecasting. CoRR abs/2409.20092 (2024) - 2023
- [j39]Patara Trirat, Susik Yoon, Jae-Gil Lee:
MG-TAR: Multi-View Graph Convolutional Networks for Traffic Accident Risk Prediction. IEEE Trans. Intell. Transp. Syst. 24(4): 3779-3794 (2023) - [j38]Hwanjun Song, Minseok Kim, Dongmin Park, Yooju Shin, Jae-Gil Lee:
Learning From Noisy Labels With Deep Neural Networks: A Survey. IEEE Trans. Neural Networks Learn. Syst. 34(11): 8135-8153 (2023) - [j37]Steven Euijong Whang, Yuji Roh, Hwanjun Song, Jae-Gil Lee:
Data collection and quality challenges in deep learning: a data-centric AI perspective. VLDB J. 32(4): 791-813 (2023) - [c62]Patara Trirat, Youngeun Nam, Taeyoon Kim, Jae-Gil Lee:
AnoViz: A Visual Inspection Tool of Anomalies in Multivariate Time Series. AAAI 2023: 16488-16490 - [c61]Hyangsuk Min, Jae-Gil Lee:
Temporal Convolutional Network-Based Time-Series Segmentation. BigComp 2023: 269-276 - [c60]Yooju Shin, Susik Yoon, Hwanjun Song, Dongmin Park, Byunghyun Kim, Jae-Gil Lee, Byung Suk Lee:
Context Consistency Regularization for Label Sparsity in Time Series. ICML 2023: 31579-31595 - [c59]Dongmin Park, Seola Choi, Doyoung Kim, Hwanjun Song, Jae-Gil Lee:
Robust Data Pruning under Label Noise via Maximizing Re-labeling Accuracy. NeurIPS 2023 - [c58]Youngeun Nam, Patara Trirat, Taeyoon Kim, Youngseop Lee, Jae-Gil Lee:
Context-Aware Deep Time-Series Decomposition for Anomaly Detection in Businesses. ECML/PKDD (6) 2023: 330-345 - [i19]Dongmin Park, Seola Choi, Doyoung Kim, Hwanjun Song, Jae-Gil Lee:
Robust Data Pruning under Label Noise via Maximizing Re-labeling Accuracy. CoRR abs/2311.01002 (2023) - [i18]Jihwan Bang, Sumyeong Ahn, Jae-Gil Lee:
Active Prompt Learning in Vision Language Models. CoRR abs/2311.11178 (2023) - [i17]Doyoung Kim, Susik Yoon, Dongmin Park, Youngjun Lee, Hwanjun Song, Jihwan Bang, Jae-Gil Lee:
One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning. CoRR abs/2311.12048 (2023) - [i16]Hwanjun Song, Minseok Kim, Jae-Gil Lee:
Toward Robustness in Multi-label Classification: A Data Augmentation Strategy against Imbalance and Noise. CoRR abs/2312.07087 (2023) - [i15]Doyoung Kim, Dongmin Park, Yooju Shin, Jihwan Bang, Hwanjun Song, Jae-Gil Lee:
Adaptive Shortcut Debiasing for Online Continual Learning. CoRR abs/2312.08677 (2023) - 2022
- [j36]Kyu-Young Whang, Jae-Gil Lee, Hyo-Sang Lim, Inju Na:
A Bird's Eye View of the 4th Industrial Revolution Technologies. IEEE Data Eng. Bull. 45(3): 4-16 (2022) - [c57]Minseok Kim, Hwanjun Song, Yooju Shin, Dongmin Park, Kijung Shin, Jae-Gil Lee:
Meta-Learning for Online Update of Recommender Systems. AAAI 2022: 4065-4074 - [c56]Doyoung Kim, Hyangsuk Min, Youngeun Nam, Hwanjun Song, Susik Yoon, Minseok Kim, Jae-Gil Lee:
COVID-EENet: Predicting Fine-Grained Impact of COVID-19 on Local Economies. AAAI 2022: 11971-11981 - [c55]Dongmin Park, Junhyeok Kang, Hwanjun Song, Susik Yoon, Jae-Gil Lee:
Multi-view POI-level Cellular Trajectory Reconstruction for Digital Contact Tracing of Infectious Diseases. ICDM 2022: 1137-1142 - [c54]Yooju Shin, Susik Yoon, Sundong Kim, Hwanjun Song, Jae-Gil Lee, Byung Suk Lee:
Coherence-based Label Propagation over Time Series for Accelerated Active Learning. ICLR 2022 - [c53]Susik Yoon, Youngjun Lee, Jae-Gil Lee, Byung Suk Lee:
Adaptive Model Pooling for Online Deep Anomaly Detection from a Complex Evolving Data Stream. KDD 2022: 2347-2357 - [c52]Dongmin Park, Yooju Shin, Jihwan Bang, Youngjun Lee, Hwanjun Song, Jae-Gil Lee:
Meta-Query-Net: Resolving Purity-Informativeness Dilemma in Open-set Active Learning. NeurIPS 2022 - [i14]Minseok Kim, Hwanjun Song, Yooju Shin, Dongmin Park, Kijung Shin, Jae-Gil Lee:
Meta-Learning for Online Update of Recommender Systems. CoRR abs/2203.10354 (2022) - [i13]Susik Yoon, Youngjun Lee, Jae-Gil Lee, Byung Suk Lee:
Adaptive Model Pooling for Online Deep Anomaly Detection from a Complex Evolving Data Stream. CoRR abs/2206.04792 (2022) - [i12]Dongmin Park, Yooju Shin, Jihwan Bang, Youngjun Lee, Hwanjun Song, Jae-Gil Lee:
Meta-Query-Net: Resolving Purity-Informativeness Dilemma in Open-set Active Learning. CoRR abs/2210.07805 (2022) - 2021
- [c51]Minseok Kim, Hwanjun Song, Doyoung Kim, Kijung Shin, Jae-Gil Lee:
PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation. AAAI 2021: 4164-4171 - [c50]Hwanjun Song, Eunyoung Kim, Varun Jampani, Deqing Sun, Jae-Gil Lee, Ming-Hsuan Yang:
Exploiting Scene Depth for Object Detection with Multimodal Transformers. BMVC 2021: 265 - [c49]Hwanjun Song, Minseok Kim, Dongmin Park, Yooju Shin, Jae-Gil Lee:
Robust Learning by Self-Transition for Handling Noisy Labels. KDD 2021: 1490-1500 - [c48]Jae-Gil Lee, Yuji Roh, Hwanjun Song, Steven Euijong Whang:
Machine Learning Robustness, Fairness, and their Convergence. KDD 2021: 4046-4047 - [c47]Dongmin Park, Hwanjun Song, Minseok Kim, Jae-Gil Lee:
Task-Agnostic Undesirable Feature Deactivation Using Out-of-Distribution Data. NeurIPS 2021: 4040-4052 - [c46]Susik Yoon, Yooju Shin, Jae-Gil Lee, Byung Suk Lee:
Multiple Dynamic Outlier-Detection from a Data Stream by Exploiting Duality of Data and Queries. SIGMOD Conference 2021: 2063-2075 - [c45]Patara Trirat, Jae-Gil Lee:
DF-TAR: A Deep Fusion Network for Citywide Traffic Accident Risk Prediction with Dangerous Driving Behavior. WWW 2021: 1146-1156 - [i11]Steven Euijong Whang, Yuji Roh, Hwanjun Song, Jae-Gil Lee:
Data Collection and Quality Challenges in Deep Learning: A Data-Centric AI Perspective. CoRR abs/2112.06409 (2021) - 2020
- [j35]S. K. Hong, Jae-Gil Lee:
DTranNER: biomedical named entity recognition with deep learning-based label-label transition model. BMC Bioinform. 21(1): 53 (2020) - [j34]Narae Cha, Auk Kim, Cheul Young Park, Soowon Kang, Mingyu Park, Jae-Gil Lee, Sangsu Lee, Uichin Lee:
Hello There! Is Now a Good Time to Talk?: Opportune Moments for Proactive Interactions with Smart Speakers. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 4(3): 74:1-74:28 (2020) - [j33]Sundong Kim, Jae-Gil Lee:
A systematic framework of predicting customer revisit with in-store sensors. Knowl. Inf. Syst. 62(3): 1005-1035 (2020) - [j32]Hwanjun Song, Sundong Kim, Minseok Kim, Jae-Gil Lee:
Ada-boundary: accelerating DNN training via adaptive boundary batch selection. Mach. Learn. 109(9-10): 1837-1853 (2020) - [j31]Gwangseon Jang, Jin-Woo Lee, Jae-Gil Lee, Yunxin Liu:
Distributed fine-tuning of CNNs for image retrieval on multiple mobile devices. Pervasive Mob. Comput. 64: 101134 (2020) - [j30]Steven Whang, Jae-Gil Lee:
Data Collection and Quality Challenges for Deep Learning. Proc. VLDB Endow. 13(12): 3429-3432 (2020) - [j29]Jungeun Kim, Jae-Gil Lee, Byung Suk Lee, Jiajun Liu:
Geosocial Co-Clustering: A Novel Framework for Geosocial Community Detection. ACM Trans. Intell. Syst. Technol. 11(4): 45:1-45:26 (2020) - [j28]Minseo Kang, Jae-Gil Lee:
Effect of garbage collection in iterative algorithms on Spark: an experimental analysis. J. Supercomput. 76(9): 7204-7218 (2020) - [j27]Jae-Gil Lee, Donghwan Bae, Sansung Kim, Jungeun Kim, Mun Yong Yi:
An effective approach to enhancing a focused crawler using Google. J. Supercomput. 76(10): 8175-8192 (2020) - [c44]Hwanjun Song, Minseok Kim, Sundong Kim, Jae-Gil Lee:
Carpe Diem, Seize the Samples Uncertain "at the Moment" for Adaptive Batch Selection. CIKM 2020: 1385-1394 - [c43]Susik Yoon, Jae-Gil Lee, Byung Suk Lee:
Ultrafast Local Outlier Detection from a Data Stream with Stationary Region Skipping. KDD 2020: 1181-1191 - [c42]Minseok Kim, Junhyeok Kang, Doyoung Kim, Hwanjun Song, Hyangsuk Min, Youngeun Nam, Dongmin Park, Jae-Gil Lee:
Hi-COVIDNet: Deep Learning Approach to Predict Inbound COVID-19 Patients and Case Study in South Korea. KDD 2020: 3466-3473 - [c41]Sundong Kim, Hwanjun Song, Sejin Kim, Beomyoung Kim, Jae-Gil Lee:
Revisit Prediction by Deep Survival Analysis. PAKDD (2) 2020: 514-526 - [c40]Dongmin Park, Hwanjun Song, Minseok Kim, Jae-Gil Lee:
TRAP: Two-level Regularized Autoencoder-based Embedding for Power-law Distributed Data. WWW 2020: 1615-1624 - [i10]Hwanjun Song, Minseok Kim, Dongmin Park, Jae-Gil Lee:
Learning from Noisy Labels with Deep Neural Networks: A Survey. CoRR abs/2007.08199 (2020) - [i9]Jin-Woo Lee, Jaehoon Oh, Sungsu Lim, Se-Young Yun, Jae-Gil Lee:
TornadoAggregate: Accurate and Scalable Federated Learning via the Ring-Based Architecture. CoRR abs/2012.03214 (2020) - [i8]Hwanjun Song, Minseok Kim, Dongmin Park, Jae-Gil Lee:
Two-Phase Learning for Overcoming Noisy Labels. CoRR abs/2012.04337 (2020) - [i7]Jin-Woo Lee, Jaehoon Oh, Yooju Shin, Jae-Gil Lee, Se-Young Yoon:
Accurate and Fast Federated Learning via IID and Communication-Aware Grouping. CoRR abs/2012.04857 (2020)
2010 – 2019
- 2019
- [j26]Jin-Woo Lee, Gwangseon Jang, Hohyun Jung, Jae-Gil Lee, Uichin Lee:
Maximizing MapReduce job speed and reliability in the mobile cloud by optimizing task allocation. Pervasive Mob. Comput. 60 (2019) - [j25]Susik Yoon, Jae-Gil Lee, Byung Suk Lee:
NETS: Extremely Fast Outlier Detection from a Data Stream via Set-Based Processing. Proc. VLDB Endow. 12(11): 1303-1315 (2019) - [j24]Jungeun Kim, Sungsu Lim, Jae-Gil Lee, Byung Suk Lee:
LinkBlackHole**: Robust Overlapping Community Detection Using Link Embedding. IEEE Trans. Knowl. Data Eng. 31(11): 2138-2150 (2019) - [c39]Yooju Shin, Susik Yoon, Patara Trirat, Jae-Gil Lee:
CEP-Wizard: Automatic Deployment of Distributed Complex Event Processing. ICDE 2019: 2004-2007 - [c38]Jungeun Kim, Sungsu Lim, Jae-Gil Lee, Byung Suk Lee:
LinkBlackHole*: Robust Overlapping Community Detection Using Link Embedding (Extended Abstract). ICDE 2019: 2123-2124 - [c37]Hwanjun Song, Minseok Kim, Jae-Gil Lee:
SELFIE: Refurbishing Unclean Samples for Robust Deep Learning. ICML 2019: 5907-5915 - [i6]Dongmin Park, Susik Yoon, Hwanjun Song, Jae-Gil Lee:
MLAT: Metric Learning for kNN in Streaming Time Series. CoRR abs/1910.10368 (2019) - [i5]Hwanjun Song, Minseok Kim, Sundong Kim, Jae-Gil Lee:
Carpe Diem, Seize the Samples Uncertain "At the Moment" for Adaptive Batch Selection. CoRR abs/1911.08050 (2019) - [i4]Hwanjun Song, Minseok Kim, Dongmin Park, Jae-Gil Lee:
Prestopping: How Does Early Stopping Help Generalization against Label Noise? CoRR abs/1911.08059 (2019) - 2018
- [j23]Longbing Cao, Jae-Gil Lee, Xuemin Lin:
Introduction to the special issue on Data Science in Asia (with PAKDD'2017). Int. J. Data Sci. Anal. 6(4): 271-272 (2018) - [c36]Jaehoon Oh, Injung Lee, Yeon Seonwoo, Simin Sung, Ilbong Kwon, Jae-Gil Lee:
TED Talk Recommender Using Speech Transcripts. ASONAM 2018: 598-600 - [c35]Sundong Kim, Jae-Gil Lee:
Utilizing In-store Sensors for Revisit Prediction. ICDM 2018: 217-226 - [c34]Hwanjun Song, Jae-Gil Lee:
RP-DBSCAN: A Superfast Parallel DBSCAN Algorithm Based on Random Partitioning. SIGMOD Conference 2018: 1173-1187 - [i3]Younghun Song, Jae-Gil Lee:
Augmenting Recurrent Neural Networks with High-Order User-Contextual Preference for Session-Based Recommendation. CoRR abs/1805.02983 (2018) - [i2]Jaehoon Oh, Injung Lee, Yeon Seonwoo, Simin Sung, Ilbong Kwon, Jae-Gil Lee:
TED Talk Recommender Using Speech Transcripts. CoRR abs/1809.05350 (2018) - 2017
- [j22]Minseo Kang, Jae-Gil Lee:
An experimental analysis of limitations of MapReduce for iterative algorithms on Spark. Clust. Comput. 20(4): 3593-3604 (2017) - [j21]Seongchan Kim, Jae-Gil Lee, Mun Yong Yi:
Developing information quality assessment framework of presentation slides. J. Inf. Sci. 43(6): 742-768 (2017) - [j20]Bum-Soo Kim, Yang-Sae Moon, Jae-Gil Lee:
Boundary image matching supporting partial denoising using time-series matching techniques. Multim. Tools Appl. 76(6): 8471-8496 (2017) - [j19]Jungeun Kim, Jae-Gil Lee, Sungsu Lim:
Differential Flattening: A Novel Framework for Community Detection in Multi-Layer Graphs. ACM Trans. Intell. Syst. Technol. 8(2): 27:1-27:23 (2017) - [c33]Hyun Gook Kang, Minseo Kang, Jae-Gil Lee:
Efficient fall detection based on event pattern matching in image streams. BigComp 2017: 51-58 - [c32]Hwanjun Song, Jae-Gil Lee, Wook-Shin Han:
PAMAE: Parallel k-Medoids Clustering with High Accuracy and Efficiency. KDD 2017: 1087-1096 - [e2]Jinho Kim, Kyuseok Shim, Longbing Cao, Jae-Gil Lee, Xuemin Lin, Yang-Sae Moon:
Advances in Knowledge Discovery and Data Mining - 21st Pacific-Asia Conference, PAKDD 2017, Jeju, South Korea, May 23-26, 2017, Proceedings, Part I. Lecture Notes in Computer Science 10234, 2017, ISBN 978-3-319-57453-0 [contents] - [e1]Jinho Kim, Kyuseok Shim, Longbing Cao, Jae-Gil Lee, Xuemin Lin, Yang-Sae Moon:
Advances in Knowledge Discovery and Data Mining - 21st Pacific-Asia Conference, PAKDD 2017, Jeju, South Korea, May 23-26, 2017, Proceedings, Part II. Lecture Notes in Computer Science 10235, 2017, ISBN 978-3-319-57528-5 [contents] - 2016
- [j18]Seunghyeon Moon, Jae-Gil Lee, Minseo Kang, Minsoo Choy, Jin-Woo Lee:
Parallel community detection on large graphs with MapReduce and GraphChi. Data Knowl. Eng. 104: 17-31 (2016) - [j17]Jiajun Liu, Kun Zhao, Philipp Sommer, Shuo Shang, Brano Kusy, Jae-Gil Lee, Raja Jurdak:
A Novel Framework for Online Amnesic Trajectory Compression in Resource-Constrained Environments. IEEE Trans. Knowl. Data Eng. 28(11): 2827-2841 (2016) - [c31]Haejoon Lee, Minseo Kang, Sun-Bum Youn, Jae-Gil Lee, YongChul Kwon:
An Experimental Comparison of Iterative MapReduce Frameworks. CIKM 2016: 2089-2094 - [c30]Ilyeop Yi, Jae-Gil Lee, Kyu-Young Whang:
APAM: Adaptive Eager-Lazy Hybrid Evaluation of Event Patterns for Low Latency. CIKM 2016: 2275-2280 - [c29]Minseo Kang, Jae-Gil Lee:
A comparative analysis of iterative MapReduce systems. EDB 2016: 61-64 - [c28]Minsoo Choy, Daehoon Kim, Jae-Gil Lee, Heeyoung Kim, Hiroshi Motoda:
Looking back on the current day: interruptibility prediction using daily behavioral features. UbiComp 2016: 1004-1015 - [c27]Daehoon Kim, Jae-Gil Lee, Byung Suk Lee:
Topical influence modeling via topic-level interests and interactions on social curation services. ICDE 2016: 13-24 - [c26]Sungsu Lim, Junghoon Kim, Jae-Gil Lee:
BlackHole: Robust community detection inspired by graph drawing. ICDE 2016: 25-36 - [c25]Sang-Jun Yea, Sejin Kim, John-Michaël To, Jae-Gil Lee:
SentiWorld: Understanding Emotions between Countries Based on Tweets. ICWSM 2016: 762-763 - [i1]Jiajun Liu, Kun Zhao, Philipp Sommer, Shuo Shang, Brano Kusy, Jae-Gil Lee, Raja Jurdak:
A Novel Framework for Online Amnesic Trajectory Compression in Resource-constrained Environments. CoRR abs/1605.02337 (2016) - 2015
- [j16]Jae-Gil Lee, Minseo Kang:
Geospatial Big Data: Challenges and Opportunities. Big Data Res. 2(2): 74-81 (2015) - [j15]Jungeun Kim, Jae-Gil Lee:
Community Detection in Multi-Layer Graphs: A Survey. SIGMOD Rec. 44(3): 37-48 (2015) - [j14]Jae-Gil Lee, Jiawei Han, Xiaolei Li:
A Unifying Framework of Mining Trajectory Patterns of Various Temporal Tightness. IEEE Trans. Knowl. Data Eng. 27(6): 1478-1490 (2015) - [j13]Kyu-Young Whang, Jae-Gil Lee, Min-Jae Lee, Wook-Shin Han, Min-Soo Kim, Jun-Sung Kim:
DB-IR integration using tight-coupling in the Odysseus DBMS. World Wide Web 18(3): 491-520 (2015) - [c24]Jungeun Kim, Minseo Kang, Sungsu Lim, Jae-Gil Lee:
Triangle counting in networks using a multi-level branching technique. BigComp 2015: 47-50 - [c23]Jin-Woo Lee, Joohyun Kim, Uichin Lee, Jae-Gil Lee:
SocialKeyboard: Proofreading Everyday Writings in Mobile Phones. CHI Extended Abstracts 2015: 1591-1596 - 2014
- [j12]Jae-Gil Lee, Gopi K. Attaluri, Ronald Barber, Naresh Chainani, Oliver Draese, Frederick Ho, Stratos Idreos, Min-Soo Kim, Sam Lightstone, Guy M. Lohman, Konstantinos Morfonios, Keshava Murthy, Ippokratis Pandis, Lin Qiao, Vijayshankar Raman, Vincent Kulandai Samy, Richard Sidle, Knut Stolze, Liping Zhang:
Joins on Encoded and Partitioned Data. Proc. VLDB Endow. 7(13): 1355-1366 (2014) - [c22]Seunghyeon Moon, Jae-Gil Lee, Minseo Kang:
Scalable community detection from networks by computing edge betweenness on MapReduce. BigComp 2014: 145-148 - [c21]Seongchan Kim, Wonchul Jung, Keejun Han, Jae-Gil Lee, Mun Yong Yi:
Quality-Based Automatic Classification for Presentation Slides. ECIR 2014: 638-643 - [c20]Sungsu Lim, Seungwoo Ryu, Sejeong Kwon, Kyomin Jung, Jae-Gil Lee:
LinkSCAN*: Overlapping community detection using the link-space transformation. ICDE 2014: 292-303 - [c19]Minsoo Choy, Jae-Gil Lee, Gahgene Gweon, Daehoon Kim:
Glaucus: Exploiting the Wisdom of Crowds for Location-Based Queries in Mobile Environments. ICWSM 2014 - 2013
- [c18]Keejun Han, Mun Yong Yi, Gahgene Gweon, Jae-Gil Lee:
Understanding the Difficulty Factors for Learning Materials: A Qualitative Study. AIED 2013: 615-618 - [c17]Jeungmin Oh, Daehoon Kim, Uichin Lee, Jae-Gil Lee, Junehwa Song:
Facilitating developer-user interactions with mobile app review digests. CHI Extended Abstracts 2013: 1809-1814 - [c16]Juyup Sung, Jae-Gil Lee, Uichin Lee:
Booming Up the Long Tails: Discovering Potentially Contributive Users in Community-Based Question Answering Services. ICWSM 2013 - [c15]Juyup Sung, Seunghyeon Moon, Jae-Gil Lee:
The Influence in Twitter: Are They Really Influenced? BSI@PAKDD/BSIC@IJCAI 2013: 95-105 - 2012
- [j11]Ronald Barber, Peter Bendel, Marco Czech, Oliver Draese, Frederick Ho, Namik Hrle, Stratos Idreos, Min-Soo Kim, Oliver Koeth, Jae-Gil Lee, Tianchao Tim Li, Guy M. Lohman, Konstantinos Morfonios, René Müller, Keshava Murthy, Ippokratis Pandis, Lin Qiao, Vijayshankar Raman, Richard Sidle, Knut Stolze, Sandor Szabo:
Business Analytics in (a) Blink. IEEE Data Eng. Bull. 35(1): 9-14 (2012) - [c14]Seulki Lee, Minsam Ko, Keejun Han, Jae-Gil Lee:
On Finding Fine-Granularity User Communities by Profile Decomposition. ASONAM 2012: 631-639 - 2011
- [j10]Zhenhui Li, Jiawei Han, Ming Ji, Lu-An Tang, Yintao Yu, Bolin Ding, Jae-Gil Lee, Roland Kays:
MoveMine: Mining moving object data for discovery of animal movement patterns. ACM Trans. Intell. Syst. Technol. 2(4): 37:1-37:32 (2011) - [j9]