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ORCIDPhilip S. Yu
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- affiliation: University of Illinois at Chicago
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2020 – today
- 2021
[j398]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)- [j397]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) - [j396]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) - [j395]Chunkai Zhang, Zilin Du, Wensheng Gan, Philip S. Yu:
TKUS: Mining top-k high utility sequential patterns. Inf. Sci. 570: 342-359 (2021) - [j394]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) - [j393]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) - [j392]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) - [j391]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) - [j390]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) - [j389]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) - [j388]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) - [j387]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) - [j386]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) - [j385]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) - [j384]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) - [j383]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) - [j382]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) - [j381]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) - [j380]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) - [j379]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) - [j378]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) - [j377]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) - [j376]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) - [j375]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) - [j374]He Li, Hang Yuan, Jianbin Huang, Jiangtao Cui, Xiaoke Ma, Senzhang Wang, Jaesoo Yoo, Philip S. Yu:
Group Reassignment for Dynamic Edge Partitioning. IEEE Trans. Parallel Distributed Syst. 32(10): 2477-2490 (2021) - [c890]Li Sun, Zhongbao Zhang, Jiawei Zhang, Feiyang Wang, Hao Peng, Sen Su, Philip S. Yu:
Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs. AAAI 2021: 4375-4383 - [c889]Ye Liu, Yao Wan, Lifang He, Hao Peng, Philip S. Yu:
KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning. AAAI 2021: 6418-6425 - [c888]Nooshin Mojab, Vahid Noroozi, Abdullah Aleem, Manoj Prabhakar Nallabothula, Joseph Baker, Dimitri T. Azar, Mark Rosenblatt, R. V. Paul Chan, Darvin Yi, Philip S. Yu, Joelle A. Hallak:
I-ODA, Real-world Multi-modal Longitudinal Data for Ophthalmic Applications. HEALTHINF 2021: 566-574 - [c887]Xinyu Wen, Zhaohui Peng, Shanshan Huang, Senzhang Wang, Philip S. Yu:
MISS: A Multi-user Identification Network for Shared-Account Session-Aware Recommendation. DASFAA (3) 2021: 228-243 - [c886]Xiaokang Xu, Zhaohui Peng, Senzhang Wang, Shanshan Huang, Philip S. Yu, Zhenyun Hao, Jian Wang, Xue Wang:
AE-UPCP: Seeking Potential Membership Users by Audience Expansion Combining User Preference with Consumption Pattern. DASFAA (2) 2021: 392-399 - [c885]Ye Liu, Yao Wan, Jianguo Zhang, Wenting Zhao, Philip S. Yu:
Enriching Non-Autoregressive Transformer with Syntactic and Semantic Structures for Neural Machine Translation. EACL 2021: 1235-1244 - [c884]Hsi-Wen Chen, Hong-Han Shuai, De-Nian Yang, Wang-Chien Lee, Chuan Shi, Philip S. Yu, Ming-Syan Chen:
Structure-Aware Parameter-Free Group Query via Heterogeneous Information Network Transformer. ICDE 2021: 2075-2080 - [c883]Congying Xia, Wenpeng Yin, Yihao Feng, Philip S. Yu:
Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and System. NAACL-HLT 2021: 1351-1360 - [c882]Zhongfen Deng, Hao Peng, Dongxiao He, Jianxin Li, Philip S. Yu:
HTCInfoMax: A Global Model for Hierarchical Text Classification via Information Maximization. NAACL-HLT 2021: 3259-3265 - [c881]Zhiwei Liu, Ziwei Fan, Yu Wang, Philip S. Yu:
Augmenting Sequential Recommendation with Pseudo-Prior Items via Reversely Pre-training Transformer. SIGIR 2021: 1608-1612 - [c880]Zheng Liu, Xiaohan Li, Zeyu You, Tao Yang, Wei Fan, Philip S. Yu:
Medical Triage Chatbot Diagnosis Improvement via Multi-relational Hyperbolic Graph Neural Network. SIGIR 2021: 1965-1969 - [c879]Congying Xia, Caiming Xiong, Philip S. Yu:
Pseudo Siamese Network for Few-shot Intent Generation. SIGIR 2021: 2005-2009 - [c878]Yingtong Dou, Kai Shu, Congying Xia, Philip S. Yu, Lichao Sun:
User Preference-aware Fake News Detection. SIGIR 2021: 2051-2055 - [c877]Liangwei Yang, Zhiwei Liu, Yingtong Dou, Jing Ma, Philip S. Yu:
ConsisRec: Enhancing GNN for Social Recommendation via Consistent Neighbor Aggregation. SIGIR 2021: 2141-2145 - [c876]Huidi Chen, Yun Xiong, Yangyong Zhu, Philip S. Yu:
Highly Liquid Temporal Interaction Graph Embeddings. WWW 2021: 1639-1648 - [c875]Shen Wang, Xiaokai Wei, Cícero Nogueira dos Santos, Zhiguo Wang, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang, Philip S. Yu, Isabel F. Cruz:
Mixed-Curvature Multi-Relational Graph Neural Network for Knowledge Graph Completion. WWW 2021: 1761-1771 - [c874]Qingyun Sun, Jianxin Li, Hao Peng, Jia Wu, Yuanxing Ning, Philip S. Yu, Lifang He:
SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism. WWW 2021: 2081-2091 - [c873]Yuwei Cao, Hao Peng, Jia Wu, Yingtong Dou, Jianxin Li, Philip S. Yu:
Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs. WWW 2021: 3383-3395 - [i274]Di Jin, Zhizhi Yu, Pengfei Jiao, Shirui Pan, Philip S. Yu, Weixiong Zhang:
A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning. CoRR abs/2101.01669 (2021) - [i273]Xiaohan Li, Mengqi Zhang, Shu Wu, Zheng Liu, Liang Wang, Philip S. Yu:
Dynamic Graph Collaborative Filtering. CoRR abs/2101.02844 (2021) - [i272]Zheng Liu, Xiaohan Li, Hao Peng, Lifang He, Philip S. Yu:
Heterogeneous Similarity Graph Neural Network on Electronic Health Records. CoRR abs/2101.06800 (2021) - [i271]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. CoRR abs/2101.07425 (2021) - [i270]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. CoRR abs/2101.07437 (2021) - [i269]Qingyun Sun, Hao Peng, Jianxin Li, Jia Wu, Yuanxing Ning, Philip S. Yu, Lifang He:
SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism. CoRR abs/2101.08170 (2021) - [i268]Yuwei Cao, Hao Peng, Jia Wu, Yingtong Dou, Jianxin Li, Philip S. Yu:
Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs. CoRR abs/2101.08747 (2021) - [i267]Ye Liu, Yao Wan, Jianguo Zhang, Wenting Zhao, Philip S. Yu:
Enriching Non-Autoregressive Transformer with Syntactic and SemanticStructures for Neural Machine Translation. CoRR abs/2101.08942 (2021) - [i266]Yixin Liu, Shirui Pan, Ming Jin, Chuan Zhou, Feng Xia, Philip S. Yu:
Graph Self-Supervised Learning: A Survey. CoRR abs/2103.00111 (2021) - [i265]Fanjin Zhang, Jie Tang, Xueyi Liu, Zhenyu Hou, Yuxiao Dong, Jing Zhang, Xiao Liu, Ruobing Xie, Kai Zhuang, Xu Zhang, Leyu Lin, Philip S. Yu:
Understanding WeChat User Preferences and "Wow" Diffusion. CoRR abs/2103.02930 (2021) - [i264]Zi-Yuan Hu, Jin Huang, Zhi-Hong Deng, Chang-Dong Wang, Ling Huang, Jian-Huang Lai, Philip S. Yu:
BCFNet: A Balanced Collaborative Filtering Network with Attention Mechanism. CoRR abs/2103.06105 (2021) - [i263]Yunbo Wang, Haixu Wu, Jianjin Zhang, Zhifeng Gao, Jianmin Wang, Philip S. Yu, Mingsheng Long:
PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning. CoRR abs/2103.09504 (2021) - [i262]Mehrnaz Najafi, Philip S. Yu:
An Introduction to Robust Graph Convolutional Networks. CoRR abs/2103.14807 (2021) - [i261]Chunkai Zhang, Zilin Du, Quanjian Dai, Wensheng Gan, Jian Weng, Philip S. Yu:
TUSQ: Targeted High-Utility Sequence Querying. CoRR abs/2103.16615 (2021) - [i260]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. CoRR abs/2104.00853 (2021) - [i259]Li Sun, Zhongbao Zhang, Jiawei Zhang, Feiyang Wang, Hao Peng, Sen Su, Philip S. Yu:
Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs. CoRR abs/2104.02228 (2021) - [i258]Nooshin Mojab, Vahid Noroozi, Abdullah Aleem, Manoj Prabhakar Nallabothula, Joseph Baker, Dimitri T. Azar, Mark Rosenblatt, R. V. Paul Chan, Darvin Yi, Philip S. Yu, Joelle A. Hallak:
I-ODA, Real-World Multi-modal Longitudinal Data for OphthalmicApplications. CoRR abs/2104.02609 (2021) - [i257]Zhongfen Deng, Hao Peng, Dongxiao He, Jianxin Li, Philip S. Yu:
HTCInfoMax: A Global Model for Hierarchical Text Classification via Information Maximization. CoRR abs/2104.05220 (2021) - [i256]Hao Peng, Ruitong Zhang, Yingtong Dou, Renyu Yang, Jingyi Zhang, Philip S. Yu:
Reinforced Neighborhood Selection Guided Multi-Relational Graph Neural Networks. CoRR abs/2104.07886 (2021) - [i255]Jianxin Li, Hao Peng, Yuwei Cao, Yingtong Dou, Hekai Zhang, Philip S. Yu, Lifang He:
Higher-Order Attribute-Enhancing Heterogeneous Graph Neural Networks. CoRR abs/2104.07892 (2021) - [i254]Congying Xia, Wenpeng Yin, Yihao Feng, Philip S. Yu:
Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and System. CoRR abs/2104.11882 (2021) - [i253]Yingtong Dou, Kai Shu, Congying Xia, Philip S. Yu, Lichao Sun:
User Preference-aware Fake News Detection. CoRR abs/2104.12259 (2021) - [i252]Zhiwei Liu, Ziwei Fan, Yu Wang, Philip S. Yu:
Augmenting Sequential Recommendation with Pseudo-Prior Items via Reversely Pre-training Transformer. CoRR abs/2105.00522 (2021) - [i251]Congying Xia, Caiming Xiong, Philip S. Yu:
Pseudo Siamese Network for Few-shot Intent Generation. CoRR abs/2105.00896 (2021) - [i250]Liangwei Yang, Zhiwei Liu, Yingtong Dou, Jing Ma, Philip S. Yu:
ConsisRec: Enhancing GNN for Social Recommendation via Consistent Neighbor Aggregation. CoRR abs/2105.02254 (2021) - [i249]Mehrnaz Najafi, Lifang He, Philip S. Yu:
Error-Robust Multi-View Clustering: Progress, Challenges and Opportunities. CoRR abs/2105.03058 (2021) - [i248]Gongxu Luo, Jianxin Li, Hao Peng, Carl Yang, Lichao Sun, Philip S. Yu, Lifang He:
Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks. CoRR abs/2105.03178 (2021) - [i247]Shoujin Wang, Liang Hu, Yan Wang, Xiangnan He, Quan Z. Sheng, Mehmet A. Orgun, Longbing Cao, Francesco Ricci, Philip S. Yu:
Graph Learning based Recommender Systems: A Review. CoRR abs/2105.06339 (2021) - [i246]Jianxin Li, Xingcheng Fu, Hao Peng, Senzhang Wang, Shijie Zhu, Qingyun Sun, Philip S. Yu, Lifang He:
A Robust and Generalized Framework for Adversarial Graph Embedding. CoRR abs/2105.10651 (2021) - [i245]Xing Su, Shan Xue, Fanzhen Liu, Jia Wu, Jian Yang, Chuan Zhou, Wenbin Hu, Cécile Paris, Surya Nepal, Di Jin, Quan Z. Sheng, Philip S. Yu:
A Comprehensive Survey on Community Detection with Deep Learning. CoRR abs/2105.12584 (2021) - [i244]Qianren Mao, Xi Li, Hao Peng, Bang Liu, Shu Guo, Jianxin Li, Lihong Wang, Philip S. Yu:
Attend and Select: A Segment Attention based Selection Mechanism for Microblog Hashtag Generation. CoRR abs/2106.03151 (2021) - [i243]Siddharth Bhatia, Mohit Wadhwa, Philip S. Yu, Bryan Hooi:
Sketch-Based Streaming Anomaly Detection in Dynamic Graphs. CoRR abs/2106.04486 (2021) - [i242]Jianguo Zhang, Kazuma Hashimoto, Yao Wan, Ye Liu, Caiming Xiong, Philip S. Yu:
Are Pretrained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection. CoRR abs/2106.04564 (2021) - [i241]Ziwei Fan, Zhiwei Liu, Lei Zheng, Shen Wang, Philip S. Yu:
Modeling Sequences as Distributions with Uncertainty for Sequential Recommendation. CoRR abs/2106.06165 (2021) - [i240]Qian Li, Hao Peng, Jianxin Li, Yuanxing Ning, Lihong Wang, Philip S. Yu, Zheng Wang:
Reinforcement Learning-based Dialogue Guided Event Extraction to Exploit Argument Relations. CoRR abs/2106.12384 (2021) - [i239]Hengrui Zhang, Qitian Wu, Junchi Yan, David Wipf, Philip S. Yu:
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks. CoRR abs/2106.12484 (2021) - [i238]Qiaomin Yi, Ning Yang, Philip S. Yu:
Dual Adversarial Variational Embedding for Robust Recommendation. CoRR abs/2106.15779 (2021) - [i237]Qian Li, Hao Peng, Jianxin Li, Yiming Hei, Rui Sun, Jiawei Sheng, Shu Guo, Lihong Wang, Philip S. Yu:
Deep Learning Schema-based Event Extraction: Literature Review and Current Trends. CoRR abs/2107.02126 (2021) - 2020
- [j373]Yuqing Zhu, Philip S. Yu, Guolei Yi, Mengying Guo, Wenlong Ma, Jianxun Liu, Yungang Bao:
Logless one-phase commit made possible for highly-available datastores. Distributed Parallel Databases 38(1): 101-126 (2020) - [j372]Tianqing Zhu, Ping Xiong, Gang Li, Wanlei Zhou, Philip S. Yu:
Differentially private model publishing in cyber physical systems. Future Gener. Comput. Syst. 108: 1297-1306 (2020) - [j371]Linchuan Xu, Xiaokai Wei, Jiannong Cao, Philip S. Yu:
ICANE: interaction content-aware network embedding via co-embedding of nodes and edges. Int. J. Data Sci. Anal. 9(4): 401-414 (2020) - [j370]Wensheng Gan, Jerry Chun-Wei Lin, Jiexiong Zhang, Han-Chieh Chao, Hamido Fujita, Philip S. Yu:
ProUM: Projection-based utility mining on sequence data. Inf. Sci. 513: 222-240 (2020) - [j369]Hao Peng, Hongfei Wang, Bowen Du, Md. Zakirul Alam Bhuiyan, Hongyuan Ma, Jianwei Liu, Lihong Wang, Zeyu Yang, Linfeng Du, Senzhang Wang, Philip S. Yu:
Spatial temporal incidence dynamic graph neural networks for traffic flow forecasting. Inf. Sci. 521: 277-290 (2020) - [j368]Jianping Cao, Senzhang Wang, Danyan Wen, Zhaohui Peng, Philip S. Yu, Fei-Yue Wang:
Mutual clustering on comparative texts via heterogeneous information networks. Knowl. Inf. Syst. 62(1): 175-202 (2020) - [j367]Xinghua Wang, Zhaohui Peng, Senzhang Wang, Philip S. Yu, Wenjing Fu, Xiaokang Xu, Xiaoguang Hong:
CDLFM: cross-domain recommendation for cold-start users via latent feature mapping. Knowl. Inf. Syst. 62(5): 1723-1750 (2020) - [j366]Tingting Liang, Lifang He, Chun-Ta Lu, Liang Chen, Haochao Ying, Philip S. Yu, Jian Wu:
CAMAR: a broad learning based context-aware recommender for mobile applications. Knowl. Inf. Syst. 62(8): 3291-3319 (2020) - [j365]Tingting Liang, Lei Zheng, Liang Chen, Yao Wan, Philip S. Yu, Jian Wu:
Multi-view factorization machines for mobile app recommendation based on hierarchical attention. Knowl. Based Syst. 187 (2020) - [j364]Yuhui Zhao, Ning Yang, Tao Lin, Philip S. Yu:
Deep Collaborative Embedding for information cascade prediction. Knowl. Based Syst. 193: 105502 (2020) - [j363]Zhi Li, Chaozhuo Li, Liqun Yang, Philip S. Yu, Zhoujun Li:
Mixture distribution modeling for scalable graph-based semi-supervised learning. Knowl. Based Syst. 200: 105974 (2020) - [j362]Chen Li, Xutan Peng, Shanghang Zhang, Hao Peng, Philip S. Yu, Min He, Linfeng Du, Lihong Wang:
Modeling relation paths for knowledge base completion via joint adversarial training. Knowl. Based Syst. 201-202: 105865 (2020) - [j361]Shao-Heng Ko, Hsu-Chao Lai, Hong-Han Shuai, Wang-Chien Lee, Philip S. Yu, De-Nian Yang:
Optimizing Item and Subgroup Configurations for Social-Aware VR Shopping. Proc. VLDB Endow. 13(8): 1275-1289 (2020) - [j360]Wensheng Gan, Jerry Chun-Wei Lin, Han-Chieh Chao, Athanasios V. Vasilakos, Philip S. Yu:
Utility-Driven Data Analytics on Uncertain Data. IEEE Syst. J. 14(3): 4442-4453 (2020) - [j359]Zhongyuan Jiang, Xianyu Chen, Bowen Dong, Junsan Zhang, Jibing Gong, Hui Yan, Zehua Zhang, Jianfeng Ma, Philip S. Yu:
Trajectory-Based Community Detection. IEEE Trans. Circuits Syst. II Express Briefs 67-II(6): 1139-1143 (2020) - [j358]Zhongyuan Jiang, Jing Li, Jianfeng Ma, Philip S. Yu:
Similarity-Based and Sybil Attack Defended Community Detection for Social Networks. IEEE Trans. Circuits Syst. 67-II(12): 3487-3491 (2020) - [j357]Wensheng Gan, Jerry Chun-Wei Lin, Philippe Fournier-Viger, Han-Chieh Chao, Philip S. Yu:
HUOPM: High-Utility Occupancy Pattern Mining. IEEE Trans. Cybern. 50(3): 1195-1208 (2020) - [j356]Dayong Ye, Tianqing Zhu, Wanlei Zhou, Philip S. Yu:
Differentially Private Malicious Agent Avoidance in Multiagent Advising Learning. IEEE Trans. Cybern. 50(10): 4214-4227 (2020) - [j355]Wensheng Gan, Jerry Chun-Wei Lin, Jiexiong Zhang, Philip S. Yu:
Utility Mining across Multi-Sequences with Individualized Thresholds. Trans. Data Sci. 1(2): 8:1-8:29 (2020) - [j354]Changping Wang, Chaokun Wang, Zheng Wang, Xiaojun Ye, Philip S. Yu:
Edge2vec: Edge-based Social Network Embedding. ACM Trans. Knowl. Discov. Data 14(4): 45:1-45:24 (2020) - [j353]Senzhang Wang, Hao Chen, Jiannong Cao, Jiawei Zhang, Philip S. Yu:
Locally Balanced Inductive Matrix Completion for Demand-Supply Inference in Stationless Bike-Sharing Systems. IEEE Trans. Knowl. Data Eng. 32(12): 2374-2388 (2020) - [j352]Linchuan Xu, Jiannong Cao, Xiaokai Wei, Philip S. Yu:
Network Embedding via Coupled Kernelized Multi-Dimensional Array Factorization. IEEE Trans. Knowl. Data Eng. 32(12): 2414-2425 (2020) - [j351]Wensheng Gan, Jerry Chun-Wei Lin, Han-Chieh Chao, Philippe Fournier-Viger, Xuan Wang, Philip S. Yu:
Utility-Driven Mining of Trend Information for Intelligent System. ACM Trans. Manag. Inf. Syst. 11(3): 14:1-14:28 (2020) - [j350]Yongshan Zhang, Jia Wu, Zhihua Cai, Philip S. Yu:
Multi-View Multi-Label Learning With Sparse Feature Selection for Image Annotation. IEEE Trans. Multim. 22(11): 2844-2857 (2020) - [j349]Jiayu Han, Lei Zheng, Yuanbo Xu, Bangzuo Zhang, Fuzhen Zhuang, Philip S. Yu, Wanli Zuo:
Adaptive Deep Modeling of Users and Items Using Side Information for Recommendation. IEEE Trans. Neural Networks Learn. Syst. 31(3): 737-748 (2020) - [j348]Ling Huang, Chang-Dong Wang, Hongyang Chao, Philip S. Yu:
MVStream: Multiview Data Stream Clustering. IEEE Trans. Neural Networks Learn. Syst. 31(9): 3482-3496 (2020) - [j347]Ning Yang, Yuchi Ma, Li Chen, Philip S. Yu:
A meta-feature based unified framework for both cold-start and warm-start explainable recommendations. World Wide Web 23(1): 241-265 (2020) - [j346]Yue Wang, Chenwei Zhang, Shen Wang, Philip S. Yu, Lu Bai, Lixin Cui, Guandong Xu:
Generative temporal link prediction via self-tokenized sequence modeling. World Wide Web 23(4): 2471-2488 (2020) - [j345]Wenhe Yan, Guiling Li, Zongda Wu, Senzhang Wang, Philip S. Yu:
Extracting diverse-shapelets for early classification on time series. World Wide Web 23(6): 3055-3081 (2020) - [c872]He Huang, Shunta Saito, Yuta Kikuchi, Eiichi Matsumoto, Wei Tang, Philip S. Yu:
Addressing Class Imbalance in Scene Graph Parsing by Learning to Contrast and Score. ACCV (6) 2020: 461-477 - [c871]Qingqin Wang, Yun Xiong, Yangyong Zhu, Philip S. Yu:
KASR: Knowledge-Aware Sequential Recommendation. APWeb/WAIM (1) 2020: 493-508 - [c870]Zhiwei Liu, Xiaohan Li, Ziwei Fan, Stephen Guo, Kannan Achan, Philip S. Yu:
Basket Recommendation with Multi-Intent Translation Graph Neural Network. IEEE BigData 2020: 728-737 - [c869]Chen Cui, Ning Yang, Philip S. Yu:
MLANE: Meta-Learning Based Adaptive Network Embedding. IEEE BigData 2020: 904-909 - [c868]Zheng Liu, Xiaohan Li, Hao Peng, Lifang He, Philip S. Yu:
Heterogeneous Similarity Graph Neural Network on Electronic Health Records. IEEE BigData 2020: 1196-1205 - [c867]Shaika Chowdhury, Chenwei Zhang, Philip S. Yu, Yuan Luo:
Med2Meta: Learning Representations of Medical Concepts with Meta-embeddings. HEALTHINF 2020: 369-376 - [c866]He Huang, Wei Tang, Philip S. Yu, Yuanwei Chen, Wenhao Zheng, Qing-Guo Chen:
Multi-label Zero-shot Classification by Learning to Transfer from External Knowledge. BMVC 2020 - [c865]Yingtong Dou, Zhiwei Liu, Li Sun, Yutong Deng, Hao Peng, Philip S. Yu:
Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters. CIKM 2020: 315-324 - [c864]Congying Xia, Chenwei Zhang, Jiawei Zhang, Tingting Liang, Hao Peng, Philip S. Yu:
Low-shot Learning in Natural Language Processing. CogMI 2020: 185-189 - [c863]Tao Zhang, Congying Xia, Chun-Ta Lu, Philip S. Yu:
MZET: Memory Augmented Zero-Shot Fine-grained Named Entity Typing. COLING 2020: 77-87 - [c862]Hu Xu, Lei Shu, Philip S. Yu, Bing Liu:
Understanding Pre-trained BERT for Aspect-based Sentiment Analysis. COLING 2020: 244-250 - [c861]Lichao Sun, Congying Xia, Wenpeng Yin, Tingting Liang, Philip S. Yu, Lifang He:
Mixup-Transformer: Dynamic Data Augmentation for NLP Tasks. COLING 2020: 3436-3440 - [c860]