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Namyong Park
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Estimating node importance in knowledge graphs using graph neural networks
N Park, A Kan, XL Dong, T Zhao, C Faloutsos
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019
1342019
Scalable tucker factorization for sparse tensors-algorithms and discoveries
S Oh, N Park, S Lee, U Kang
2018 IEEE 34th International Conference on Data Engineering (ICDE), 1120-1131, 2018
672018
Bepi: Fast and memory-efficient method for billion-scale random walk with restart
J Jung, N Park, S Lee, U Kang
Proceedings of the 2017 ACM International Conference on Management of Data …, 2017
592017
EvoKG: Jointly Modeling Event Time and Network Structure for Reasoning over Temporal Knowledge Graphs
N Park, F Liu, P Mehta, D Cristofor, C Faloutsos, Y Dong
Proceedings of the Fifteenth ACM International Conference on Web Search and …, 2022
462022
Bigtensor: Mining billion-scale tensor made easy
N Park, B Jeon, J Lee, U Kang
Proceedings of the 25th ACM International on Conference on Information and …, 2016
462016
Predicting acute kidney injury in cancer patients using heterogeneous and irregular data
N Park, E Kang, M Park, H Lee, HG Kang, HJ Yoon, U Kang
PloS one 13 (7), e0199839, 2018
352018
High-performance tucker factorization on heterogeneous platforms
S Oh, N Park, JG Jang, L Sael, U Kang
IEEE Transactions on Parallel and Distributed Systems 30 (10), 2237-2248, 2019
282019
MultiImport: Inferring Node Importance in a Knowledge Graph from Multiple Input Signals
N Park, A Kan, XL Dong, T Zhao, C Faloutsos
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
262020
CGC: Contrastive Graph Clustering for Community Detection and Tracking
N Park, R Rossi, E Koh, IA Burhanuddin, S Kim, F Du, N Ahmed, ...
Proceedings of the ACM Web Conference 2022, 1115-1126, 2022
252022
Acute kidney injury predicts all‐cause mortality in patients with cancer
E Kang, M Park, PG Park, N Park, Y Jung, U Kang, HG Kang, DK Kim, ...
Cancer medicine 8 (6), 2740-2750, 2019
252019
Fast and scalable distributed boolean tensor factorization
N Park, S Oh, U Kang
2017 IEEE 33rd International Conference on Data Engineering (ICDE), 1071-1082, 2017
222017
Fast and scalable method for distributed boolean tensor factorization
N Park, S Oh, U Kang
The VLDB Journal 28 (4), 549-574, 2019
192019
INFOSHIELD: Generalizable Information-Theoretic Human-Trafficking Detection
MC Lee, C Vajiac, A Kulshrestha, S Levy, N Park, C Jones, R Rabbany, ...
2021 IEEE 37th International Conference on Data Engineering (ICDE), 1116–1127, 2021
182021
Evolving the best known approximation to the q function
DN Phong, NX Hoai, RI McKay, C Siriteanu, NQ Uy, N Park
Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012
162012
Dropout Prediction over Weeks in MOOCs by Learning Representations of Clicks and Videos
B Jeon, N Park
arXiv preprint arXiv:2002.01955, 2020
122020
Partition aware connected component computation in distributed systems
HM Park, N Park, SH Myaeng, U Kang
2016 IEEE 16th International Conference on Data Mining (ICDM), 420-429, 2016
112016
Dropout Prediction over Weeks in MOOCs via Interpretable Multi-Layer Representation Learning
B Jeon, N Park, S Bang
arXiv preprint arXiv:2002.01598, 2020
102020
MetaGL: Evaluation-Free Selection of Graph Learning Models via Meta-Learning
N Park, RA Rossi, N Ahmed, C Faloutsos
International Conference on Learning Representations, 2023
9*2023
PACC: Large scale connected component computation on Hadoop and Spark
HM Park, N Park, SH Myaeng, U Kang
PLOS ONE 15 (3), e0229936, 2020
72020
Improvement of complex and refractory ecological models: Riverine water quality modelling using evolutionary computation
MH Kim, N Park, RIB McKay, H Shin, YG Lee, KS Jeong, DK Kim
Ecological modelling 291, 205-217, 2014
72014
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Articles 1–20