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ORCIDJingrui He
何京芮
Person information
- affiliation: University of Illinois at Urbana-Champaign, IL, USA
- affiliation: Arizona State University, AZ, USA
- affiliation (Ph.D., 2010): Carnegie Mellon University, PA, USA
- affiliation (former): Tsinghua University, China
- unicode name: 何京芮
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2020 – today
- 2022
[j26]Dongming Han, Jiacheng Pan, Rusheng Pan, Dawei Zhou, Nan Cao, Jingrui He, Mingliang Xu, Wei Chen:
iNet: visual analysis of irregular transition in multivariate dynamic networks. Frontiers Comput. Sci. 16(2): 162701 (2022)- [j25]Yang Shi
, Yuyin Liu, Hanghang Tong, Jingrui He, Gang Yan, Nan Cao:
Visual Analytics of Anomalous User Behaviors: A Survey. IEEE Trans. Big Data 8(2): 377-396 (2022) - [c112]Dawei Zhou, Lecheng Zheng, Dongqi Fu, Jiawei Han, Jingrui He:
MentorGNN: Deriving Curriculum for Pre-Training GNNs. CIKM 2022: 2721-2731 - [c111]Yao Zhou, Jun Wu, Haixun Wang, Jingrui He:
Adversarial Robustness through Bias Variance Decomposition: A New Perspective for Federated Learning. CIKM 2022: 2753-2762 - [c110]Dongqi Fu, Yikun Ban, Hanghang Tong, Ross Maciejewski, Jingrui He:
DISCO: Comprehensive and Explainable Disinformation Detection. CIKM 2022: 4848-4852 - [c109]Jian Kang, Shuaicheng Zhang, Bo Li, Jingrui He, Jian Pei, Dawei Zhou:
TrustLOG: The First Workshop on Trustworthy Learning on Graphs. CIKM 2022: 5169-5170 - [c108]Ziwei Wu, Jingrui He:
Fairness-aware Model-agnostic Positive and Unlabeled Learning. FAccT 2022: 1698-1708 - [c107]Yikun Ban, Yuchen Yan, Arindam Banerjee, Jingrui He:
EE-Net: Exploitation-Exploration Neural Networks in Contextual Bandits. ICLR 2022 - [c106]Jun Wu, Jingrui He:
A Unified Meta-Learning Framework for Dynamic Transfer Learning. IJCAI 2022: 3573-3579 - [c105]Dongqi Fu, Liri Fang, Ross Maciejewski, Vetle I. Torvik, Jingrui He:
Meta-Learned Metrics over Multi-Evolution Temporal Graphs. KDD 2022: 367-377 - [c104]Yunzhe Qi, Yikun Ban, Jingrui He:
Neural Bandit with Arm Group Graph. KDD 2022: 1379-1389 - [c103]Tianxin Wei, Jingrui He:
Comprehensive Fair Meta-learned Recommender System. KDD 2022: 1989-1999 - [c102]Jun Wu, Jingrui He:
Domain Adaptation with Dynamic Open-Set Targets. KDD 2022: 2039-2049 - [c101]Lecheng Zheng, Jinjun Xiong, Yada Zhu, Jingrui He:
Contrastive Learning with Complex Heterogeneity. KDD 2022: 2594-2604 - [i37]Jun Wu, Elizabeth A. Ainsworth, Sheng Wang, Kaiyu Guan, Jingrui He:
Adaptive Transfer Learning for Plant Phenotyping. CoRR abs/2201.05261 (2022) - [i36]Haonan Wang, Ziwei Wu, Jingrui He:
Training Fair Deep Neural Networks by Balancing Influence. CoRR abs/2201.05759 (2022) - [i35]Yikun Ban, Yunzhe Qi, Tianxin Wei, Jingrui He:
Neural Collaborative Filtering Bandits via Meta Learning. CoRR abs/2201.13395 (2022) - [i34]Dongqi Fu, Yikun Ban, Hanghang Tong, Ross Maciejewski, Jingrui He:
DISCO: Comprehensive and Explainable Disinformation Detection. CoRR abs/2203.04928 (2022) - [i33]Yunzhe Qi, Yikun Ban, Jingrui He:
Neural Bandit with Arm Group Graph. CoRR abs/2206.03644 (2022) - [i32]Tianxin Wei, Jingrui He:
Comprehensive Fair Meta-learned Recommender System. CoRR abs/2206.04789 (2022) - [i31]Ziwei Wu, Jingrui He:
Fairness-aware Model-agnostic Positive and Unlabeled Learning. CoRR abs/2206.09346 (2022) - [i30]Dongqi Fu, Jingrui He, Hanghang Tong, Ross Maciejewski:
Privacy-preserving Graph Analytics: Secure Generation and Federated Learning. CoRR abs/2207.00048 (2022) - [i29]Jun Wu, Jingrui He:
A Unified Meta-Learning Framework for Dynamic Transfer Learning. CoRR abs/2207.01784 (2022) - [i28]Dawei Zhou, Lecheng Zheng, Dongqi Fu, Jiawei Han, Jingrui He:
MentorGNN: Deriving Curriculum for Pre-Training GNNs. CoRR abs/2208.09905 (2022) - [i27]Wenxuan Bao, Jingrui He:
BOBA: Byzantine-Robust Federated Learning with Label Skewness. CoRR abs/2208.12932 (2022) - [i26]Yikun Ban, Yuheng Zhang, Hanghang Tong, Arindam Banerjee, Jingrui He:
Improved Algorithms for Neural Active Learning. CoRR abs/2210.00423 (2022) - [i25]Tianxin Wei, Yuning You, Tianlong Chen, Yang Shen, Jingrui He, Zhangyang Wang:
Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative. CoRR abs/2210.03801 (2022) - [i24]Jun Wu, Jingrui He, Elizabeth A. Ainsworth:
Non-IID Transfer Learning on Graphs. CoRR abs/2212.08174 (2022) - 2021
- [j24]Xu Liu, Congzhe Su, Amey Barapatre, Xiaoting Zhao, Diane Hu, Chu-Cheng Hsieh, Jingrui He:
Interpretable Attribute-based Action-aware Bandits for Within-Session Personalization in E-commerce. IEEE Data Eng. Bull. 44(2): 65-80 (2021) - [j23]Dawei Zhou, Si Zhang, Mehmet Yigit Yildirim, Scott Alcorn, Hanghang Tong, Hasan Davulcu, Jingrui He:
High-Order Structure Exploration on Massive Graphs: A Local Graph Clustering Perspective. ACM Trans. Knowl. Discov. Data 15(2): 18:1-18:26 (2021) - [j22]Yuxin Ma, Arlen Fan, Jingrui He, Arun Reddy Nelakurthi, Ross Maciejewski:
A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning Processes. IEEE Trans. Vis. Comput. Graph. 27(2): 1385-1395 (2021) - [c100]Jianbo Li, Lecheng Zheng, Yada Zhu, Jingrui He:
Outlier Impact Characterization for Time Series Data. AAAI 2021: 11595-11603 - [c99]Yikun Ban, Jingrui He, Curtiss B. Cook:
Multi-facet Contextual Bandits: A Neural Network Perspective. KDD 2021: 35-45 - [c98]Jun Wu, Jingrui He:
Indirect Invisible Poisoning Attacks on Domain Adaptation. KDD 2021: 1852-1862 - [c97]Yao Zhou, Jianpeng Xu, Jun Wu, Zeinab Taghavi Nasrabadi, Evren Körpeoglu, Kannan Achan, Jingrui He:
PURE: Positive-Unlabeled Recommendation with Generative Adversarial Network. KDD 2021: 2409-2419 - [c96]Dongqi Fu, Jingrui He:
SDG: A Simplified and Dynamic Graph Neural Network. SIGIR 2021: 2273-2277 - [c95]Haonan Wang, Chang Zhou, Carl Yang, Hongxia Yang, Jingrui He:
Controllable Gradient Item Retrieval. WWW 2021: 768-777 - [c94]Lecheng Zheng, Yu Cheng, Hongxia Yang, Nan Cao, Jingrui He:
Deep Co-Attention Network for Multi-View Subspace Learning. WWW 2021: 1528-1539 - [c93]Yikun Ban, Jingrui He:
Local Clustering in Contextual Multi-Armed Bandits. WWW 2021: 2335-2346 - [i23]Lecheng Zheng, Yu Cheng, Hongxia Yang, Nan Cao, Jingrui He:
Deep Co-Attention Network for Multi-View Subspace Learning. CoRR abs/2102.07751 (2021) - [i22]Yikun Ban, Jingrui He:
Local Clustering in Contextual Multi-Armed Bandits. CoRR abs/2103.00063 (2021) - [i21]Lecheng Zheng, Yada Zhu, Jingrui He, Jinjun Xiong:
Heterogeneous Contrastive Learning. CoRR abs/2105.09401 (2021) - [i20]Haonan Wang, Chang Zhou, Carl Yang, Hongxia Yang, Jingrui He:
Controllable Gradient Item Retrieval. CoRR abs/2106.00062 (2021) - [i19]Yikun Ban, Jingrui He, Curtiss B. Cook:
Multi-facet Contextual Bandits: A Neural Network Perspective. CoRR abs/2106.03039 (2021) - [i18]Dongqi Fu, Jingrui He:
DPPIN: A Biological Dataset of Dynamic Protein-Protein Interaction Networks. CoRR abs/2107.02168 (2021) - [i17]Yikun Ban, Jingrui He:
Convolutional Neural Bandit: Provable Algorithm for Visual-aware Advertising. CoRR abs/2107.07438 (2021) - [i16]Yikun Ban, Yuchen Yan, Arindam Banerjee, Jingrui He:
EE-Net: Exploitation-Exploration Neural Networks in Contextual Bandits. CoRR abs/2110.03177 (2021) - [i15]Haonan Wang, Wei Huang, Andrew Margenot, Hanghang Tong, Jingrui He:
Deep Active Learning by Leveraging Training Dynamics. CoRR abs/2110.08611 (2021) - [i14]Lecheng Zheng, Dongqi Fu, Jingrui He:
Tackling Oversmoothing of GNNs with Contrastive Learning. CoRR abs/2110.13798 (2021) - [i13]Yao Zhou, Haonan Wang, Jingrui He, Haixun Wang:
From Intrinsic to Counterfactual: On the Explainability of Contextualized Recommender Systems. CoRR abs/2110.14844 (2021) - 2020
- [j21]Jiacheng Pan, Dongming Han, Fangzhou Guo, Dawei Zhou, Nan Cao, Jingrui He, Mingliang Xu, Wei Chen:
RCAnalyzer: visual analytics of rare categories in dynamic networks. Frontiers Inf. Technol. Electron. Eng. 21(4): 491-506 (2020) - [j20]Pei Yang, Qi Tan, Jingrui He:
Complex heterogeneity learning: A theoretical and empirical study. Pattern Recognit. 107: 107519 (2020) - [c92]Zhining Liu, Dawei Zhou, Yada Zhu, Jinjie Gu, Jingrui He:
Towards Fine-Grained Temporal Network Representation via Time-Reinforced Random Walk. AAAI 2020: 4973-4980 - [c91]Shane Roach, Connie Ni, Alexei Kopylov, Tsai-Ching Lu, Jiejun Xu, Si Zhang, Boxin Du, Dawei Zhou, Jun Wu, Lihui Liu, Yuchen Yan, Jingrui He, Hanghang Tong:
CANON: Complex Analytics of Network of Networks for Modeling Adversarial Activities. IEEE BigData 2020: 1634-1643 - [c90]Dongqi Fu, Zhe Xu, Bo Li, Hanghang Tong, Jingrui He:
A View-Adversarial Framework for Multi-View Network Embedding. CIKM 2020: 2025-2028 - [c89]Jian Kang, Jingrui He, Ross Maciejewski, Hanghang Tong:
InFoRM: Individual Fairness on Graph Mining. KDD 2020: 379-389 - [c88]Dongqi Fu, Dawei Zhou, Jingrui He:
Local Motif Clustering on Time-Evolving Graphs. KDD 2020: 390-400 - [c87]Dawei Zhou, Lecheng Zheng, Jiawei Han, Jingrui He:
A Data-Driven Graph Generative Model for Temporal Interaction Networks. KDD 2020: 401-411 - [c86]Yikun Ban, Jingrui He:
Generic Outlier Detection in Multi-Armed Bandit. KDD 2020: 913-923 - [c85]Yao Zhou, Arun Reddy Nelakurthi, Ross Maciejewski, Wei Fan, Jingrui He:
Crowd Teaching with Imperfect Labels. WWW 2020: 110-121 - [c84]Dawei Zhou, Lecheng Zheng, Yada Zhu, Jianbo Li, Jingrui He:
Domain Adaptive Multi-Modality Neural Attention Network for Financial Forecasting. WWW 2020: 2230-2240 - [i12]Jun Wu, Jingrui He:
Continuous Transfer Learning with Label-informed Distribution Alignment. CoRR abs/2006.03230 (2020) - [i11]Yikun Ban, Jingrui He:
Generic Outlier Detection in Multi-Armed Bandit. CoRR abs/2007.07293 (2020) - [i10]Yuxin Ma, Arlen Fan, Jingrui He, Arun Reddy Nelakurthi, Ross Maciejewski:
A Visual Analytics Framework for Explaining and Diagnosing Transfer Learning Processes. CoRR abs/2009.06876 (2020) - [i9]Yao Zhou, Jun Wu, Jingrui He:
Robust Decentralized Learning for Neural Networks. CoRR abs/2009.09026 (2020) - [i8]Yao Zhou, Jianpeng Xu, Jun Wu, Zeinab Taghavi Nasrabadi, Evren Körpeoglu, Kannan Achan, Jingrui He:
GAN-based Recommendation with Positive-Unlabeled Sampling. CoRR abs/2012.06901 (2020)
2010 – 2019
- 2019
- [j19]Dawei Zhou, Lecheng Zheng, Jiejun Xu, Jingrui He:
Misc-GAN: A Multi-scale Generative Model for Graphs. Frontiers Big Data 2: 3 (2019) - [j18]Chieh-Yang Huang, Hanghang Tong, Jingrui He, Ross Maciejewski:
Location Prediction for Tweets. Frontiers Big Data 2: 5 (2019) - [j17]Yao Zhou, Lei Ying, Jingrui He:
Multi-task Crowdsourcing via an Optimization Framework. ACM Trans. Knowl. Discov. Data 13(3): 27:1-27:26 (2019) - [c83]Jun Wu, Jingrui He:
Scalable Manifold-Regularized Attributed Network Embedding via Maximum Mean Discrepancy. CIKM 2019: 2101-2104 - [c82]Zhining Liu, Dawei Zhou, Jingrui He:
Towards Explainable Representation of Time-Evolving Graphs via Spatial-Temporal Graph Attention Networks. CIKM 2019: 2137-2140 - [c81]Xu Liu, Jingrui He, Sam Duddy, Liz O'Sullivan:
Convolution-Consistent Collective Matrix Completion. CIKM 2019: 2209-2212 - [c80]Pei Yang, Qi Tan, Jieping Ye, Hanghang Tong, Jingrui He:
Deep Multi-Task Learning with Adversarial-and-Cooperative Nets. IJCAI 2019: 4078-4084 - [c79]Jun Wu, Jingrui He, Jiejun Xu:
DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification. KDD 2019: 406-415 - [c78]Pei Yang, Qi Tan, Hanghang Tong, Jingrui He:
Task-Adversarial Co-Generative Nets. KDD 2019: 1596-1604 - [c77]Dawei Zhou, Jingrui He:
Gold Panning from the Mess: Rare Category Exploration, Exposition, Representation, and Interpretation. KDD 2019: 3213-3214 - [c76]Yao Zhou, Fenglong Ma, Jing Gao, Jingrui He:
Optimizing the Wisdom of the Crowd: Inference, Learning, and Teaching. KDD 2019: 3231-3232 - [c75]Lecheng Zheng, Yu Cheng, Jingrui He:
Deep Multimodality Model for Multi-task Multi-view Learning. SDM 2019: 10-18 - [i7]Lecheng Zheng, Yu Cheng, Jingrui He:
Deep Multimodality Model for Multi-task Multi-view Learning. CoRR abs/1901.08723 (2019) - [i6]Yang Shi, Yuyin Liu, Hanghang Tong, Jingrui He, Gang Yan, Nan Cao:
Visual Analytics of Anomalous User Behaviors: A Survey. CoRR abs/1905.06720 (2019) - [i5]Jun Wu, Jingrui He, Jiejun Xu:
DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification. CoRR abs/1906.02319 (2019) - [i4]Yikun Ban, Yuchen Zhou, Jingrui He, Xu Cheng, Jiangfang Yi:
Coalesced TLB to Exploit Diverse Contiguity of Memory Mapping. CoRR abs/1908.08774 (2019) - 2018
- [j16]Shuo Feng, Derong Shen, Tiezheng Nie, Yue Kou, Jingrui He, Ge Yu:
Inferring Anchor Links Based on Social Network Structure. IEEE Access 6: 17340-17353 (2018) - [j15]Pei Yang, Qi Tan, Yada Zhu, Jingrui He:
Heterogeneous representation learning with separable structured sparsity regularization. Knowl. Inf. Syst. 55(3): 671-694 (2018) - [j14]Qi Tan, Pei Yang, Jingrui He:
Feature co-shrinking for co-clustering. Pattern Recognit. 77: 12-19 (2018) - [j13]Pei Yang, Qi Tan, Jingrui He:
Function-on-Function Regression with Mode-Sparsity Regularization. ACM Trans. Knowl. Discov. Data 12(3): 36:1-36:23 (2018) - [j12]Hanfei Lin, Siyuan Gao, David Gotz, Fan Du, Jingrui He, Nan Cao:
RCLens: Interactive Rare Category Exploration and Identification. IEEE Trans. Vis. Comput. Graph. 24(7): 2223-2237 (2018) - [c74]Arun Reddy Nelakurthi, Ross Maciejewski, Jingrui He:
Source Free Domain Adaptation Using an Off-the-Shelf Classifier. IEEE BigData 2018: 140-145 - [c73]Jun Wu, Jingrui He, Yongming Liu:
ImVerde: Vertex-Diminished Random Walk for Learning Imbalanced Network Representation. IEEE BigData 2018: 871-880 - [c72]Dawei Zhou, Jingrui He, Hasan Davulcu, Ross Maciejewski:
Motif-Preserving Dynamic Local Graph Cut. IEEE BigData 2018: 1156-1161 - [c71]Yada Zhu, Jianbo Li, Jingrui He, Brian Leo Quanz, Ajay A. Deshpande:
A Local Algorithm for Product Return Prediction in E-Commerce. IJCAI 2018: 3718-3724 - [c70]Jianbo Li, Jingrui He, Yada Zhu:
E-tail Product Return Prediction via Hypergraph-based Local Graph Cut. KDD 2018: 519-527 - [c69]Dawei Zhou, Jingrui He, Hongxia Yang, Wei Fan:
SPARC: Self-Paced Network Representation for Few-Shot Rare Category Characterization. KDD 2018: 2807-2816 - [c68]Yao Zhou, Arun Reddy Nelakurthi, Jingrui He:
Unlearn What You Have Learned: Adaptive Crowd Teaching with Exponentially Decayed Memory Learners. KDD 2018: 2817-2826 - [c67]Pengfei Jiang, Weina Wang, Yao Zhou, Jingrui He, Lei Ying:
A Winners-Take-All Incentive Mechanism for Crowd-Powered Systems. NetEcon@SIGMETRICS 2018: 3:1-3:6 - [c66]Jiejun Xu, Hanghang Tong, Tsai-Ching Lu, Jingrui He, Nadya Bliss:
GTA3 2018: Workshop on Graph Techniques for Adversarial Activity Analytics. WSDM 2018: 803 - [e2]Naoki Abe, Huan Liu, Calton Pu, Xiaohua Hu, Nesreen K. Ahmed, Mu Qiao, Yang Song, Donald Kossmann, Bing Liu, Kisung Lee, Jiliang Tang, Jingrui He, Jeffrey S. Saltz:
IEEE International Conference on Big Data (IEEE BigData 2018), Seattle, WA, USA, December 10-13, 2018. IEEE 2018, ISBN 978-1-5386-5035-6 [contents] - [r2]Yada Zhu, Jingrui He:
Social Phishing. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - [i3]Yao Zhou, Arun Reddy Nelakurthi, Jingrui He:
Unlearn What You Have Learned: Adaptive Crowd Teaching with Exponentially Decayed Memory Learners. CoRR abs/1804.06481 (2018) - [i2]Jun Wu, Jingrui He, Yongming Liu:
ImVerde: Vertex-Diminished Random Walk for Learning Network Representation from Imbalanced Data. CoRR abs/1804.09222 (2018) - [i1]Yao Zhou, Jingrui He:
Optimizing the Wisdom of the Crowd: Inference, Learning, and Teaching. CoRR abs/1806.09018 (2018) - 2017
- [j11]Dawei Zhou, Arun Karthikeyan, Kangyang Wang, Nan Cao, Jingrui He:
Discovering rare categories from graph streams. Data Min. Knowl. Discov. 31(2): 400-423 (2017) - [j10]Chen Chen, Jingrui He, Nadya Bliss, Hanghang Tong:
Towards Optimal Connectivity on Multi-Layered Networks. IEEE Trans. Knowl. Data Eng. 29(10): 2332-2346 (2017) - [c65]Arun Reddy Nelakurthi, Jingrui He:
Finding Cut from the Same Cloth: Cross Network Link Recommendation via Joint Matrix Factorization. AAAI 2017: 1467-1473 - [c64]Jianbo Li, Jingrui He, Yada Zhu:
HiMuV: Hierarchical Framework for Modeling Multi-modality Multi-resolution Data. ICDM 2017: 267-276 - [c63]Yao Zhou, Jingrui He:
A Randomized Approach for Crowdsourcing in the Presence of Multiple Views. ICDM 2017: 685-694 - [c62]Jingrui He:
Learning from Data Heterogeneity: Algorithms and Applications. IJCAI 2017: 5126-5130 - [c61]Dawei Zhou, Si Zhang, Mehmet Yigit Yildirim, Scott Alcorn, Hanghang Tong, Hasan Davulcu, Jingrui He:
A Local Algorithm for Structure-Preserving Graph Cut. KDD 2017: 655-664 - [c60]Pei Yang, Qi Tan, Jingrui He:
Multi-task Function-on-function Regression with Co-grouping Structured Sparsity. KDD 2017: 1255-1264 - [c59]Hongxia Yang, Yada Zhu, Jingrui He:
Local Algorithm for User Action Prediction Towards Display Ads. KDD 2017: 2091-2099 - [c58]Arun Reddy Nelakurthi, Hanghang Tong, Ross Maciejewski, Nadya Bliss, Jingrui He:
User-guided Cross-domain Sentiment Classification. SDM 2017: 471-479 - [c57]Si Zhang, Dawei Zhou, Mehmet Yigit Yildirim, Scott Alcorn, Jingrui He, Hasan Davulcu, Hanghang Tong:
HiDDen: Hierarchical Dense Subgraph Detection with Application to Financial Fraud Detection. SDM 2017: 570-578 - [c56]Yao Zhou, Lei Ying, Jingrui He:
MultiC2: an Optimization Framework for Learning from Task and Worker Dual Heterogeneity. SDM 2017: 579-587 - [c55]Yada Zhu, Jianbo Li, Jingrui He:
Learning from Multi-Modality Multi-Resolution Data: an Optimization Approach. SDM 2017: 714-722 - 2016
- [j9]Pei Yang, Hongxia Yang, Haoda Fu, Dawei Zhou, Jieping Ye, Theodoros Lappas, Jingrui He:
Jointly Modeling Label and Feature Heterogeneity in Medical Informatics. ACM Trans. Knowl. Discov. Data 10(4): 39:1-39:25 (2016) - [j8]Yada Zhu, Jingrui He:
Co-Clustering Structural Temporal Data with Applications to Semiconductor Manufacturing. ACM Trans. Knowl. Discov. Data 10(4): 43:1-43:18 (2016) - [j7]Pei Yang, Hasan Davulcu, Yada Zhu, Jingrui He:
A Generalized Hierarchical Multi-Latent Space Model for Heterogeneous Learning. IEEE Trans. Knowl. Data Eng. 28(12): 3154-3168 (2016) - [c54]Pei Yang, Jingrui He:
Heterogeneous Representation Learning with Structured Sparsity Regularization. ICDM 2016: 539-548 - [c53]Dawei Zhou, Jingrui He, Yu Cao, Jae-sun Seo:
Bi-Level Rare Temporal Pattern Detection. ICDM 2016: 719-728 - [c52]