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- affiliation: University of Illinois at Chicago
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2020 – today
- 2022
[b5]Chuan Shi, Xiao Wang, Philip S. Yu:
Heterogeneous Graph Representation Learning and Applications. Artificial Intelligence: Foundations, Theory, and Algorithms, Springer 2022, ISBN 978-981-16-6165-5, pp. 1-318- [j445]Mohammed A. Fouad
, Wedad Hussein, Sherine Rady, Philip S. Yu, Tarek F. Gharib:
An Efficient Approach for Mining Reliable High Utility Patterns. IEEE Access 10: 1419-1431 (2022) - [j444]Mohammed A. Fouad, Wedad Hussein, Sherine Rady, Philip S. Yu, Tarek F. Gharib:
An Efficient Approach for Rational Next-Basket Recommendation. IEEE Access 10: 75657-75671 (2022) - [j443]Lefeng Zhang, Tianqing Zhu, Ping Xiong, Wanlei Zhou, Philip S. Yu:
More than Privacy: Adopting Differential Privacy in Game-theoretic Mechanism Design. ACM Comput. Surv. 54(7): 136:1-136:37 (2022) - [j442]Jianguo Chen, Kenli Li, Zhaolei Zhang, Keqin Li, Philip S. Yu:
A Survey on Applications of Artificial Intelligence in Fighting Against COVID-19. ACM Comput. Surv. 54(8): 158:1-158:32 (2022) - [j441]Shirui Pan, Shaoxiong Ji, Di Jin, Feng Xia, Philip S. Yu:
Guest Editorial: Graph-powered machine learning in future-generation computing systems. Future Gener. Comput. Syst. 126: 88-90 (2022) - [j440]Zishuo Cheng, Dayong Ye, Tianqing Zhu, Wanlei Zhou, Philip S. Yu, Congcong Zhu:
Multi-agent reinforcement learning via knowledge transfer with differentially private noise. Int. J. Intell. Syst. 37(1): 799-828 (2022) - [j439]Shuai Gao, Zhongbao Zhang, Sen Su, Philip S. Yu:
REBORN: Transfer learning based social network alignment. Inf. Sci. 589: 265-282 (2022) - [j438]Boyan Wang, Xuegang Hu, Chenwei Zhang, Pei-Pei Li, Philip S. Yu:
Hierarchical GAN-Tree and Bi-Directional Capsules for multi-label image classification. Knowl. Based Syst. 238: 107882 (2022) - [j437]Qian Li, Hao Peng, Jianxin Li, Jia Wu, Yuanxing Ning, Lihong Wang, Philip S. Yu, Zheng Wang:
Reinforcement Learning-Based Dialogue Guided Event Extraction to Exploit Argument Relations. IEEE ACM Trans. Audio Speech Lang. Process. 30: 520-533 (2022) - [j436]Qianren Mao, Jianxin Li, Chenghua Lin, Congwen Chen, Hao Peng, Lihong Wang, Philip S. Yu:
Adaptive Pre-Training and Collaborative Fine-Tuning: A Win-Win Strategy to Improve Review Analysis Tasks. IEEE ACM Trans. Audio Speech Lang. Process. 30: 622-634 (2022) - [j435]Qianren Mao, Jianxin Li, Hao Peng, Shizhu He, Lihong Wang, Philip S. Yu, Zheng Wang:
Fact-Driven Abstractive Summarization by Utilizing Multi-Granular Multi-Relational Knowledge. IEEE ACM Trans. Audio Speech Lang. Process. 30: 1665-1678 (2022) - [j434]Di Jin, Wenjun Wang, Guojie Song, Philip S. Yu, Jiawei Han:
Guest Editorial: Special Issue on Network Structural Modeling and Learning in Big Data. IEEE Trans. Big Data 8(4): 867-868 (2022) - [j433]Hao Peng, Renyu Yang, Zheng Wang, Jianxin Li, Lifang He, Philip S. Yu, Albert Y. Zomaya, Rajiv Ranjan:
Lime: Low-Cost and Incremental Learning for Dynamic Heterogeneous Information Networks. IEEE Trans. Computers 71(3): 628-642 (2022) - [j432]Jie Xu, Zhoujun Li, Feiran Huang, Chaozhuo Li, Philip S. Yu:
Visual Sentiment Analysis With Social Relations-Guided Multiattention Networks. IEEE Trans. Cybern. 52(6): 4472-4484 (2022) - [j431]Shi-Ting Zhong, Ling Huang, Chang-Dong Wang, Jian-Huang Lai, Philip S. Yu:
An Autoencoder Framework With Attention Mechanism for Cross-Domain Recommendation. IEEE Trans. Cybern. 52(6): 5229-5241 (2022) - [j430]Dayong Ye, Tianqing Zhu, Zishuo Cheng, Wanlei Zhou, Philip S. Yu:
Differential Advising in Multiagent Reinforcement Learning. IEEE Trans. Cybern. 52(6): 5508-5521 (2022) - [j429]Chang-Dong Wang, Wei Shi, Ling Huang, Kun-Yu Lin, Dong Huang, Philip S. Yu:
Node Pair Information Preserving Network Embedding Based on Adversarial Networks. IEEE Trans. Cybern. 52(7): 5908-5922 (2022) - [j428]Mansheng Chen, Ling Huang, Chang-Dong Wang, Dong Huang, Philip S. Yu:
Multiview Subspace Clustering With Grouping Effect. IEEE Trans. Cybern. 52(8): 7655-7668 (2022) - [j427]Dayong Ye, Tianqing Zhu, Sheng Shen, Wanlei Zhou, Philip S. Yu:
Differentially Private Multi-Agent Planning for Logistic-Like Problems. IEEE Trans. Dependable Secur. Comput. 19(2): 1212-1226 (2022) - [j426]Qian Li, Hao Peng, Jianxin Li, Congying Xia, Renyu Yang, Lichao Sun, Philip S. Yu, Lifang He:
A Survey on Text Classification: From Traditional to Deep Learning. ACM Trans. Intell. Syst. Technol. 13(2): 31:1-31:41 (2022) - [j425]Senzhang Wang, Meiyue Zhang, Hao Miao, Zhaohui Peng, Philip S. Yu:
Multivariate Correlation-aware Spatio-temporal Graph Convolutional Networks for Multi-scale Traffic Prediction. ACM Trans. Intell. Syst. Technol. 13(3): 38:1-38:22 (2022) - [j424]Chunkai Zhang, Zilin Du, Yuting Yang, Wensheng Gan, Philip S. Yu:
On-Shelf Utility Mining of Sequence Data. ACM Trans. Knowl. Discov. Data 16(2): 21:1-21:31 (2022) - [j423]Jerry Chun-Wei Lin, Youcef Djenouri, Gautam Srivastava, Yuanfa Li, Philip S. Yu:
Scalable Mining of High-Utility Sequential Patterns With Three-Tier MapReduce Model. ACM Trans. Knowl. Discov. Data 16(3): 60:1-60:26 (2022) - [j422]Yali Gao, Xiaoyong Li, Hao Peng, Binxing Fang, Philip S. Yu:
HinCTI: A Cyber Threat Intelligence Modeling and Identification System Based on Heterogeneous Information Network. IEEE Trans. Knowl. Data Eng. 34(2): 708-722 (2022) - [j421]Shengli Sun, Weiping Li, Yimo Wang, Weilong Liao, Philip S. Yu:
Continuous Monitoring of Maximum Clique Over Dynamic Graphs. IEEE Trans. Knowl. Data Eng. 34(4): 1667-1683 (2022) - [j420]Tao Zhang, Tianqing Zhu, Jing Li, Mengde Han, Wanlei Zhou, Philip S. Yu:
Fairness in Semi-Supervised Learning: Unlabeled Data Help to Reduce Discrimination. IEEE Trans. Knowl. Data Eng. 34(4): 1763-1774 (2022) - [j419]Hao Chen, Chenwei Zhang, Jun Li, Philip S. Yu, Ning Jing:
KGGen: A Generative Approach for Incipient Knowledge Graph Population. IEEE Trans. Knowl. Data Eng. 34(5): 2254-2267 (2022) - [j418]Tianqing Zhu, Dayong Ye, Wei Wang, Wanlei Zhou, Philip S. Yu:
More Than Privacy: Applying Differential Privacy in Key Areas of Artificial Intelligence. IEEE Trans. Knowl. Data Eng. 34(6): 2824-2843 (2022) - [j417]Bao-Yu Liu, Ling Huang, Chang-Dong Wang, Jian-Huang Lai, Philip S. Yu:
Multi-View Consensus Proximity Learning for Clustering. IEEE Trans. Knowl. Data Eng. 34(7): 3405-3417 (2022) - [j416]Senzhang Wang, Jiannong Cao, Philip S. Yu:
Deep Learning for Spatio-Temporal Data Mining: A Survey. IEEE Trans. Knowl. Data Eng. 34(8): 3681-3700 (2022) - [j415]Shaoxiong Ji, Shirui Pan, Erik Cambria, Pekka Marttinen, Philip S. Yu:
A Survey on Knowledge Graphs: Representation, Acquisition, and Applications. IEEE Trans. Neural Networks Learn. Syst. 33(2): 494-514 (2022) - [j414]Chen Li, Hao Peng, Jianxin Li, Lichao Sun, Lingjuan Lyu, Lihong Wang, Philip S. Yu, Lifang He:
Joint Stance and Rumor Detection in Hierarchical Heterogeneous Graph. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2530-2542 (2022) - [j413]Shenghao Liu, Bang Wang, Laurence T. Yang, Philip S. Yu:
HNF: Hybrid Neural Filtering Based on Centrality-Aware Random Walk for Personalized Recommendation. IEEE Trans. Netw. Sci. Eng. 9(3): 1056-1066 (2022) - [j412]Hao Peng, Ruitong Zhang, Yingtong Dou, Renyu Yang, Jingyi Zhang, Philip S. Yu:
Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks. ACM Trans. Inf. Syst. 40(4): 69:1-69:46 (2022) - [j411]Xiao Pan, Shili Nie, Haibo Hu, Philip S. Yu, Jingfeng Guo:
Reverse Nearest Neighbor Search in Semantic Trajectories for Location-Based Services. IEEE Trans. Serv. Comput. 15(2): 986-999 (2022) - [j410]Wenhua Wang, Yuqun Zhang, Yulei Sui, Yao Wan, Zhou Zhao, Jian Wu, Philip S. Yu, Guandong Xu:
Reinforcement-Learning-Guided Source Code Summarization Using Hierarchical Attention. IEEE Trans. Software Eng. 48(2): 102-119 (2022) - [c947]Li Sun, Zhongbao Zhang, Junda Ye, Hao Peng, Jiawei Zhang, Sen Su, Philip S. Yu:
A Self-Supervised Mixed-Curvature Graph Neural Network. AAAI 2022: 4146-4155 - [c946]Qingyun Sun, Jianxin Li, Hao Peng, Jia Wu, Xingcheng Fu, Cheng Ji, Philip S. Yu:
Graph Structure Learning with Variational Information Bottleneck. AAAI 2022: 4165-4174 - [c945]Jianguo Zhang, Kazuma Hashimoto, Yao Wan, Zhiwei Liu, Ye Liu, Caiming Xiong, Philip S. Yu:
Are Pre-trained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection. ConvAI@ACL 2022: 12-20 - [c944]Zheng Liu, Xiaohan Li, Philip S. Yu:
Mitigating health disparities in EHR via deconfounder. BCB 2022: 6:1-6:6 - [c943]Yi Xie, Yun Xiong, Yangyong Zhu, Philip S. Yu, Cheng Jin, Qiang Wang, Haihong Li:
Concurrent Transformer for Spatial-Temporal Graph Modeling. DASFAA (3) 2022: 314-321 - [c942]Shu Zhao, Ziwei Du, Jie Chen, Yanping Zhang, Jie Tang, Philip S. Yu:
Hierarchical Representation Learning for Attributed Networks. ICDE 2022: 1497-1498 - [c941]Ya-Wen Teng, Yishuo Shi, De-Nian Yang, Wang-Chien Lee, Philip S. Yu, Ying-Liang Lu, Ming-Syan Chen:
Epidemic Spread Optimization for Disease Containment with NPIs and Vaccination. ICDE 2022: 2845-2858 - [c940]Lu Bai, Yuhang Jiao, Lixin Cui, Luca Rossi, Yue Wang, Philip S. Yu, Edwin R. Hancock:
Learning Graph Convolutional Networks based on Quantum Vertex Information Propagation (Extended Abstract). ICDE 2022: 3132-3133 - [c939]Yao Wan, Yang He, Zhangqian Bi, Jianguo Zhang, Yulei Sui, Hongyu Zhang, Kazuma Hashimoto, Hai Jin, Guandong Xu, Caiming Xiong, Philip S. Yu:
NaturalCC: An Open-Source Toolkit for Code Intelligence. ICSE-Companion 2022: 149-153 - [c938]Yuwei Cao, William Groves, Tanay Kumar Saha, Joel R. Tetreault, Alejandro Jaimes, Hao Peng, Philip S. Yu:
XLTime: A Cross-Lingual Knowledge Transfer Framework for Temporal Expression Extraction. NAACL-HLT (Findings) 2022: 1931-1942 - [c937]Xuming Hu, Zhijiang Guo, Guanyu Wu, Aiwei Liu, Lijie Wen, Philip S. Yu:
CHEF: A Pilot Chinese Dataset for Evidence-Based Fact-Checking. NAACL-HLT 2022: 3362-3376 - [c936]Shuliang Liu, Xuming Hu, Chenwei Zhang, Shuang Li, Lijie Wen, Philip S. Yu:
HiURE: Hierarchical Exemplar Contrastive Learning for Unsupervised Relation Extraction. NAACL-HLT 2022: 5970-5980 - [c935]Zhenyun Hao, Jianing Hao, Zhaohui Peng, Senzhang Wang, Philip S. Yu, Xue Wang, Jian Wang:
Dy-HIEN: Dynamic Evolution based Deep Hierarchical Intention Network for Membership Prediction. WSDM 2022: 363-371 - [c934]Xiaoyun Zhao, Ning Yang, Philip S. Yu:
Multi-Sparse-Domain Collaborative Recommendation via Enhanced Comprehensive Aspect Preference Learning. WSDM 2022: 1452-1460 - [c933]Haoran Yang, Hongxu Chen, Shirui Pan, Lin Li, Philip S. Yu, Guandong Xu:
Dual Space Graph Contrastive Learning. WWW 2022: 1238-1247 - [c932]Ziwei Fan, Zhiwei Liu, Yu Wang, Alice Wang, Zahra Nazari, Lei Zheng, Hao Peng, Philip S. Yu:
Sequential Recommendation via Stochastic Self-Attention. WWW 2022: 2036-2047 - [c931]Liangwei Yang, Zhiwei Liu, Yu Wang, Chen Wang, Ziwei Fan, Philip S. Yu:
Large-scale Personalized Video Game Recommendation via Social-aware Contextualized Graph Neural Network. WWW 2022: 3376-3386 - [i326]Ziwen Du, Ning Yang, Zhonghua Yu, Philip S. Yu:
Learning from Atypical Behavior: Temporary Interest Aware Recommendation Based on Reinforcement Learning. CoRR abs/2201.05970 (2022) - [i325]Xiaoyun Zhao, Ning Yang, Philip S. Yu:
Multi-Sparse-Domain Collaborative Recommendation via Enhanced Comprehensive Aspect Preference Learning. CoRR abs/2201.05973 (2022) - [i324]Ziwei Fan, Zhiwei Liu, Yu Wang, Alice Wang, Zahra Nazari, Lei Zheng, Hao Peng, Philip S. Yu:
Sequential Recommendation via Stochastic Self-Attention. CoRR abs/2201.06035 (2022) - [i323]Haoran Yang, Hongxu Chen, Shirui Pan, Lin Li, Philip S. Yu, Guandong Xu:
Dual Space Graph Contrastive Learning. CoRR abs/2201.07409 (2022) - [i322]Daokun Zhang, Jie Yin, Philip S. Yu:
Link Prediction with Contextualized Self-Supervision. CoRR abs/2201.10069 (2022) - [i321]Liangwei Yang, Zhiwei Liu, Yu Wang, Chen Wang, Ziwei Fan, Philip S. Yu:
Large-scale Personalized Video Game Recommendation via Social-aware Contextualized Graph Neural Network. CoRR abs/2202.03392 (2022) - [i320]Xiaoqin Pan, Xuan Lin, Dongsheng Cao, Xiangxiang Zeng, Philip S. Yu, Lifang He, Ruth Nussinov, Feixiong Cheng:
Deep learning for drug repurposing: methods, databases, and applications. CoRR abs/2202.05145 (2022) - [i319]Xin Zheng, Yixin Liu, Shirui Pan, Miao Zhang, Di Jin, Philip S. Yu:
Graph Neural Networks for Graphs with Heterophily: A Survey. CoRR abs/2202.07082 (2022) - [i318]Wensheng Gan, Guoting Chen, Hongzhi Yin, Philippe Fournier-Viger, Chien-Ming Chen, Philip S. Yu:
Towards Revenue Maximization with Popular and Profitable Products. CoRR abs/2202.13041 (2022) - [i317]Gengsen Huang, Wensheng Gan, Philip S. Yu:
TaSPM: Targeted Sequential Pattern Mining. CoRR abs/2202.13202 (2022) - [i316]Wenting Zhao, Ye Liu, Yao Wan, Philip S. Yu:
Attend, Memorize and Generate: Towards Faithful Table-to-Text Generation in Few Shots. CoRR abs/2203.00732 (2022) - [i315]Zhi-Hong Deng, Chang-Dong Wang, Ling Huang, Jian-Huang Lai, Philip S. Yu:
G3SR: Global Graph Guided Session-based Recommendation. CoRR abs/2203.06467 (2022) - [i314]Xusheng Zhao, Jia Wu, Hao Peng, Amin Beheshti, Jessica Monaghan, David McAlpine, Heivet Hernandez-Perez, Mark Dras, Qiong Dai, Yangyang Li, Philip S. Yu, Lifang He:
Deep Reinforcement Learning Guided Graph Neural Networks for Brain Network Analysis. CoRR abs/2203.10093 (2022) - [i313]Zhiwei Liu, Yongjun Chen, Jia Li, Man Luo, Philip S. Yu, Caiming Xiong:
Improving Contrastive Learning with Model Augmentation. CoRR abs/2203.15508 (2022) - [i312]Tingting Liang, Yixuan Jiang, Congying Xia, Ziqiang Zhao, Yuyu Yin, Philip S. Yu:
Multifaceted Improvements for Conversational Open-Domain Question Answering. CoRR abs/2204.00266 (2022) - [i311]Taotao Cai, Quan Z. Sheng, Xiangyu Song, Jian Yang, Wei Emma Zhang, Jia Wu, Philip S. Yu:
A Survey on Location-Driven Influence Maximization. CoRR abs/2204.08005 (2022) - [i310]Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, George H. Chen, Zhihao Jia, Philip S. Yu:
PyGOD: A Python Library for Graph Outlier Detection. CoRR abs/2204.12095 (2022) - [i309]Yuwei Cao, William Groves, Tanay Kumar Saha, Joel R. Tetreault, Alex Jaimes, Hao Peng, Philip S. Yu:
XLTime: A Cross-Lingual Knowledge Transfer Framework for Temporal Expression Extraction. CoRR abs/2205.01757 (2022) - [i308]Shuliang Liu, Xuming Hu, Chenwei Zhang, Shuang Li, Lijie Wen, Philip S. Yu:
HiURE: Hierarchical Exemplar Contrastive Learning for Unsupervised Relation Extraction. CoRR abs/2205.02225 (2022) - [i307]Jiaqian Ren, Lei Jiang, Hao Peng, Zhiwei Liu, Jia Wu, Philip S. Yu:
Evidential Temporal-aware Graph-based Social Event Detection via Dempster-Shafer Theory. CoRR abs/2205.12179 (2022) - [i306]Shuang Li, Xuming Hu, Li Lin, Aiwei Liu, Lijie Wen, Philip S. Yu:
A Multi-level Supervised Contrastive Learning Framework for Low-Resource Natural Language Inference. CoRR abs/2205.15550 (2022) - [i305]Yizhen Zheng, Shirui Pan, Vincent Cs Lee, Yu Zheng, Philip S. Yu:
Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination. CoRR abs/2206.01535 (2022) - [i304]Wensheng Gan, Gengsen Huang, Jian Weng, Tianlong Gu, Philip S. Yu:
Towards Target Sequential Rules. CoRR abs/2206.04728 (2022) - [i303]Yue Wang, Yao Wan, Lu Bai, Lixin Cui, Zhuo Xu, Ming Li, Philip S. Yu, Edwin R. Hancock:
Collaborative Knowledge Graph Fusion by Exploiting the Open Corpus. CoRR abs/2206.07472 (2022) - [i302]Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu:
Benchmarking Node Outlier Detection on Graphs. CoRR abs/2206.10071 (2022) - [i301]Xuming Hu, Zhijiang Guo, Guanyu Wu, Aiwei Liu, Lijie Wen, Philip S. Yu:
CHEF: A Pilot Chinese Dataset for Evidence-Based Fact-Checking. CoRR abs/2206.11863 (2022) - 2021
- [j409]Jerry Chun-Wei Lin, Philippe Fournier-Viger, Vincent S. Tseng, Philip S. Yu:
IEEE Access Special Section Editorial: Utility-Pattern Mining: Theoretical Analytics and Applications. IEEE Access 9: 16604-16607 (2021) - [j408]Xiaobin Rui, Fanrong Meng, Yahui Chai, Zhixiao Wang, Philip S. Yu:
Dismantling Networks by Skeleton Extraction and Greedy Tree Breaking. IEEE Access 9: 84922-84931 (2021) - [j407]Guixiang Ma, Nesreen K. Ahmed, Theodore L. Willke, Philip S. Yu:
Deep graph similarity learning: a survey. Data Min. Knowl. Discov. 35(3): 688-725 (2021) - [j406]Longbing Cao, Qiang Yang, Philip S. Yu:
Data science and AI in FinTech: an overview. Int. J. Data Sci. Anal. 12(2): 81-99 (2021) - [j405]Erik Cambria, Shaoxiong Ji, Shirui Pan, Philip S. Yu:
Knowledge graph representation and reasoning. Neurocomputing 461: 494-496 (2021) - [j404]Chunkai Zhang, Zilin Du, Wensheng Gan, Philip S. Yu:
TKUS: Mining top-k high utility sequential patterns. Inf. Sci. 570: 342-359 (2021) - [j403]Tie Li, Gang Kou, Yi Peng, Philip S. Yu:
A fast diagonal distance metric learning approach for large-scale datasets. Inf. Sci. 571: 225-245 (2021) - [j402]Boyan Wang, Xuegang Hu, Pei-Pei Li, Philip S. Yu:
Cognitive structure learning model for hierarchical multi-label text classification. Knowl. Based Syst. 218: 106876 (2021) - [j401]Zhixiao Wang, Chengcheng Sun, Xiaobin Rui, Philip S. Yu, Lichao Sun:
Localization of multiple diffusion sources based on overlapping community detection. Knowl. Based Syst. 226: 106613 (2021) - [j400]Lixin Cui, Lu Bai, Yue Wang, Philip S. Yu, Edwin R. Hancock:
Fused lasso for feature selection using structural information. Pattern Recognit. 119: 108058 (2021) - [j399]Jianguo Chen, Kenli Li, Keqin Li, Philip S. Yu, Zeng Zeng:
Dynamic Bicycle Dispatching of Dockless Public Bicycle-sharing Systems Using Multi-objective Reinforcement Learning. ACM Trans. Cyber Phys. Syst. 5(4): 34:1-34:24 (2021) - [j398]Xianyu Chen, Zhongyuan Jiang, Hui Li, Jianfeng Ma, Philip S. Yu:
Community Hiding by Link Perturbation in Social Networks. IEEE Trans. Comput. Soc. Syst. 8(3): 704-715 (2021) - [j397]Wensheng Gan, Jerry Chun-Wei Lin, Jiexiong Zhang, Philippe Fournier-Viger, Han-Chieh Chao, Philip S. Yu:
Fast Utility Mining on Sequence Data. IEEE Trans. Cybern. 51(2): 487-500 (2021) - [j396]Bao-Yu Liu, Ling Huang, Chang-Dong Wang, Suohai Fan, Philip S. Yu:
Adaptively Weighted Multiview Proximity Learning for Clustering. IEEE Trans. Cybern. 51(3): 1571-1585 (2021) - [j395]Wensheng Gan, Guoting Chen, Hongzhi Yin, Philippe Fournier-Viger, Chien-Ming Chen, Philip S. Yu:
Towards Revenue Maximization with Popular and Profitable Products. Trans. Data Sci. 2(4): 42:1-42:21 (2021) - [j394]Jie Xu, Zhoujun Li, Feiran Huang, Chaozhuo Li, Philip S. Yu:
Social Image Sentiment Analysis by Exploiting Multimodal Content and Heterogeneous Relations. IEEE Trans. Ind. Informatics 17(4): 2974-2982 (2021) - [j393]Jianguo Chen, Kenli Li, Keqin Li, Philip S. Yu, Zeng Zeng:
Dynamic Planning of Bicycle Stations in Dockless Public Bicycle-sharing System Using Gated Graph Neural Network. ACM Trans. Intell. Syst. Technol. 12(2): 25:1-25:22 (2021) - [j392]Zhenchang Xia, Jia Wu, Libing Wu, Yanjiao Chen, Jian Yang, Philip S. Yu:
A Comprehensive Survey of the Key Technologies and Challenges Surrounding Vehicular Ad Hoc Networks. ACM Trans. Intell. Syst. Technol. 12(4): 37:1-37:30 (2021) - [j391]Yu Huang, Josh Jia-Ching Ying, Philip S. Yu, Vincent S. Tseng:
Dynamic Graph Mining for Multi-weight Multi-destination Route Planning with Deadlines Constraints. ACM Trans. Knowl. Discov. Data 15(1): 3:1-3:32 (2021) - [j390]Wensheng Gan, Jerry Chun-Wei Lin, Jiexiong Zhang, Hongzhi Yin, Philippe Fournier-Viger, Han-Chieh Chao, Philip S. Yu:
Utility Mining Across Multi-Dimensional Sequences. ACM Trans. Knowl. Discov. Data 15(5): 82:1-82:24 (2021) - [j389]Hao Peng, Jianxin Li, Yangqiu Song, Renyu Yang, Rajiv Ranjan, Philip S. Yu, Lifang He:
Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks. ACM Trans. Knowl. Discov. Data 15(5): 89:1-89:33 (2021) - [j388]Wensheng Gan, Jerry Chun-Wei Lin, Philippe Fournier-Viger, Han-Chieh Chao, Vincent S. Tseng, Philip S. Yu:
A Survey of Utility-Oriented Pattern Mining. IEEE Trans. Knowl. Data Eng. 33(4): 1306-1327 (2021) - [j387]Chuan Shi, Xiaotian Han, Li Song, Xiao Wang, Senzhang Wang, Junping Du, Philip S. Yu:
Deep Collaborative Filtering with Multi-Aspect Information in Heterogeneous Networks. IEEE Trans. Knowl. Data Eng. 33(4): 1413-1425 (2021) - [j386]Jianguo Chen, Philip S. Yu:
A Domain Adaptive Density Clustering Algorithm for Data With Varying Density Distribution. IEEE Trans. Knowl. Data Eng. 33(6): 2310-2321 (2021) - [j385]Mingtao Lei, Xi Zhang, Lingyang Chu, Zhefeng Wang, Philip S. Yu, Binxing Fang:
Finding Route Hotspots in Large Labeled Networks. IEEE Trans. Knowl. Data Eng. 33(6): 2479-2492 (2021) - [j384]Hao Peng, Jianxin Li, Senzhang Wang, Lihong Wang, Qiran Gong, Renyu Yang, Bo Li, Philip S. Yu, Lifang He:
Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification. IEEE Trans. Knowl. Data Eng. 33(6): 2505-2519 (2021) - [j383]Linchuan Xu, Jing Wang, Lifang He, Jiannong Cao, Xiaokai Wei, Philip S. Yu, Kenji Yamanishi:
MixSp: A Framework for Embedding Heterogeneous Information Networks With Arbitrary Number of Node and Edge Types. IEEE Trans. Knowl. Data Eng. 33(6): 2627-2639 (2021) - [j382]Zheng Wang, Xiaojun Ye, Chaokun Wang, Jian Cui, Philip S. Yu:
Network Embedding With Completely-Imbalanced Labels. IEEE Trans. Knowl. Data Eng. 33(11): 3634-3647 (2021) - [j381]Lichao Sun, Bokai Cao, Ji Wang, Witawas Srisa-an, Philip S. Yu, Alex D. Leow, Stephen Checkoway:
Kollector: Detecting Fraudulent Activities on Mobile Devices Using Deep Learning. IEEE Trans. Mob. Comput. 20(4): 1465-1476 (2021) - [j380]Youcef Djenouri, Jerry Chun-Wei Lin, Kjetil Nørvåg, Heri Ramampiaro, Philip S. Yu:
Exploring Decomposition for Solving Pattern Mining Problems. ACM Trans. Manag. Inf. Syst. 12(2): 15:1-15:36 (2021) - [j379]Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, Philip S. Yu:
A Comprehensive Survey on Graph Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 32(1): 4-24 (2021) - [j378]Chang-Dong Wang, Mansheng Chen, Ling Huang, Jian-Huang Lai, Philip S. Yu:
Smoothness Regularized Multiview Subspace Clustering With Kernel Learning. IEEE Trans. Neural Networks Learn. Syst. 32(11): 5047-5060 (2021) - [j377]Shaoxu Song, Fei Gao, Aoqian Zhang, Jianmin Wang, Philip S. Yu:
Stream Data Cleaning under Speed and Acceleration Constraints. ACM Trans. Database Syst. 46(3): 10:1-10:44 (2021) - [j376]Wensheng Gan, Jerry Chun-Wei Lin, Philippe Fournier-Viger, Han-Chieh Chao, Philip S. Yu:
Beyond Frequency: Utility Mining with Varied Item-specific Minimum Utility. ACM Trans. Internet Techn. 21(1): 3:1-3:32 (2021) - [j375]He Li, Hang Yuan, Jianbin Huang, Jiangtao Cui