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ORCIDLongbing Cao
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- affiliation: University of Technology Sydney, Australia
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2020 – today
- 2025
[j177]Zhilin Zhao
, Longbing Cao, Philip S. Yu:
Out-of-distribution detection by regaining lost clues. Artif. Intell. 339: 104275 (2025)- [j176]Longbing Cao, Qing Liu:
COVID-19 Modeling: A Review. ACM Comput. Surv. 57(1): 10:1-10:42 (2025) - [j175]Zhi-Lin Zhao, Longbing Cao, Chang-Dong Wang:
Gray Learning From Non-IID Data With Out-of-Distribution Samples. IEEE Trans. Neural Networks Learn. Syst. 36(1): 1396-1409 (2025) - [j174]Zhangkai Wu, Longbing Cao, Lei Qi:
eVAE: Evolutionary Variational Autoencoder. IEEE Trans. Neural Networks Learn. Syst. 36(2): 3288-3299 (2025) - [j173]Hui He, Qi Zhang, Kun Yi, Kaize Shi, Zhendong Niu, Longbing Cao:
Distributional Drift Adaptation With Temporal Conditional Variational Autoencoder for Multivariate Time Series Forecasting. IEEE Trans. Neural Networks Learn. Syst. 36(4): 7287-7301 (2025) - [c202]Jianbo Zheng, Chao Yang, Tairui Zhang, Longbing Cao, Bin Jiang, Xuhui Fan, Xiao-Ming Wu, Xianxun Zhu:
Dynamic Spectral Graph Anomaly Detection. AAAI 2025: 13410-13418 - [c201]Zhilin Zhao, Longbing Cao, Yuan-Yu Wan:
Mixture of Online and Offline Experts for Non-Stationary Time Series. AAAI 2025: 22867-22874 - [c200]Zhangkai Wu, Xuhui Fan, Longbing Cao:
ProgDiffusion: Progressively Self-encoding Diffusion Models. KDD (1) 2025: 1633-1644 - [i75]Zhangkai Wu, Xuhui Fan, Hongyu Wu, Longbing Cao:
TraFlow: Trajectory Distillation on Pre-Trained Rectified Flow. CoRR abs/2502.16972 (2025) - 2024
- [b3]Longbing Cao:
Global COVID-19 Research and Modeling - A Historical Record, 1. Springer 2024, ISBN 978-981-99-9914-9, pp. 1-342 - [j172]Longbing Cao:
Ai4tech: X-AI enabling X-Tech with human-like, generative, decentralized, humanoid and metaverse AI. Int. J. Data Sci. Anal. 18(3): 219-238 (2024) - [j171]Zhi-Lin Zhao, Longbing Cao:
Weighting non-IID batches for out-of-distribution detection. Mach. Learn. 113(10): 7371-7391 (2024) - [j170]Hui He, Qi Zhang, Shoujin Wang, Kun Yi, Zhendong Niu, Longbing Cao:
Learning Informative Representation for Fairness-Aware Multivariate Time-Series Forecasting: A Group-Based Perspective. IEEE Trans. Knowl. Data Eng. 36(6): 2504-2516 (2024) - [j169]Wei Wang, Longbing Cao:
Explicit and Implicit Pattern Relation Analysis for Discovering Actionable Negative Sequences. IEEE Trans. Neural Networks Learn. Syst. 35(4): 5183-5197 (2024) - [j168]Zhi-Lin Zhao, Longbing Cao, Kun-Yu Lin:
Out-of-Distribution Detection by Cross-Class Vicinity Distribution of In-Distribution Data. IEEE Trans. Neural Networks Learn. Syst. 35(10): 13777-13788 (2024) - [j167]Jia Xu, Longbing Cao:
Copula Variational LSTM for High-Dimensional Cross-Market Multivariate Dependence Modeling. IEEE Trans. Neural Networks Learn. Syst. 35(11): 16233-16247 (2024) - [j166]Yawen Zheng, Xiaojie Zhao, Li Yao, Longbing Cao:
Deep Multidilation Temporal and Spatial Dependence Modeling in Stereoscopic 3-D EEG for Visual Discomfort Assessment. IEEE Trans. Syst. Man Cybern. Syst. 54(4): 2125-2136 (2024) - [c199]An Lao, Qi Zhang, Chongyang Shi, Longbing Cao, Kun Yi, Liang Hu, Duoqian Miao:
Frequency Spectrum Is More Effective for Multimodal Representation and Fusion: A Multimodal Spectrum Rumor Detector. AAAI 2024: 18426-18434 - [c198]Chengkun He, Xiangmin Zhou, Chen Wang, Longbing Cao, Jie Shao, Zahir Tari:
Influence-Aware Group Recommendation for Social Media Propagation. ICDM 2024: 705-710 - [c197]Zhilin Zhao, Longbing Cao, Xuhui Fan, Wei-Shi Zheng:
Revealing Distribution Discrepancy by Sampling Transfer in Unlabeled Data. NeurIPS 2024 - [c196]Runze Yang, Longbing Cao, Jie Yang, Jianxun Li:
Rethinking Fourier Transform from A Basis Functions Perspective for Long-term Time Series Forecasting. NeurIPS 2024 - [i74]Zhangkai Wu, Longbing Cao, Qi Zhang, Junxian Zhou, Hui Chen:
Weakly Augmented Variational Autoencoder in Time Series Anomaly Detection. CoRR abs/2401.03341 (2024) - [i73]Jianing He, Qi Zhang, Weiping Ding, Duoqian Miao, Jun Zhao, Liang Hu, Longbing Cao:
DE3-BERT: Distance-Enhanced Early Exiting for BERT based on Prototypical Networks. CoRR abs/2402.05948 (2024) - [i72]Jin Li, Shoujin Wang, Qi Zhang, Longbing Cao, Fang Chen, Xiuzhen Zhang, Dietmar Jannach, Charu C. Aggarwal:
Causal Learning for Trustworthy Recommender Systems: A Survey. CoRR abs/2402.08241 (2024) - [i71]Hui Chen, Hengyu Liu, Zhangkai Wu, Xuhui Fan, Longbing Cao:
FedSI: Federated Subnetwork Inference for Efficient Uncertainty Quantification. CoRR abs/2404.15657 (2024) - [i70]Zhangkai Wu, Xuhui Fan, Jin Li, Zhilin Zhao, Hui Chen, Longbing Cao:
ParamReL: Learning Parameter Space Representation via Progressively Encoding Bayesian Flow Networks. CoRR abs/2405.15268 (2024) - [i69]Longbing Cao:
AI Robots and Humanoid AI: Review, Perspectives and Directions. CoRR abs/2405.15775 (2024) - [i68]Hui He, Qi Zhang, Kun Yi, Xiaojun Xue, Shoujin Wang, Liang Hu, Longbing Cao:
Robust Multivariate Time Series Forecasting against Intra- and Inter-Series Transitional Shift. CoRR abs/2407.13194 (2024) - [i67]Jiaxing Miao, Liang Hu, Qi Zhang, Longbing Cao:
Graph Memory Learning: Imitating Lifelong Remembering and Forgetting of Brain Networks. CoRR abs/2407.19183 (2024) - [i66]Manqing Dong, Hao Huang, Longbing Cao:
Can LLMs Serve As Time Series Anomaly Detectors? CoRR abs/2408.03475 (2024) - [i65]Jiwei Guan, Tianyu Ding, Longbing Cao, Lei Pan, Chen Wang, Xi Zheng:
Probing the Robustness of Vision-Language Pretrained Models: A Multimodal Adversarial Attack Approach. CoRR abs/2408.13461 (2024) - [i64]Hui Chen, Hengyu Liu, Yaqiong Li, Xuhui Fan, Zhilin Zhao, Feng Zhou, Christopher John Quinn, Longbing Cao:
Federated Neural Nonparametric Point Processes. CoRR abs/2410.05637 (2024) - [i63]Peizhen Li, Longbing Cao, Xiao-Ming Wu, Xiaohan Yu, Runze Yang:
UGotMe: An Embodied System for Affective Human-Robot Interaction. CoRR abs/2410.18373 (2024) - [i62]Hui Chen, Xuhui Fan, Hengyu Liu, Longbing Cao:
Marked Temporal Bayesian Flow Point Processes. CoRR abs/2410.19512 (2024) - 2023
- [j165]Qinfen Wang, Geng Chen, Xuting Jin, Siyuan Ren, Gang Wang, Longbing Cao, Yong Xia:
BiT-MAC: Mortality prediction by bidirectional time and multi-feature attention coupled network on multivariate irregular time series. Comput. Biol. Medicine 155: 106586 (2023) - [j164]Longbing Cao:
AI in Finance: Challenges, Techniques, and Opportunities. ACM Comput. Surv. 55(3): 64:1-64:38 (2023) - [j163]Longbing Cao:
Trans-AI/DS: transformative, transdisciplinary and translational artificial intelligence and data science. Int. J. Data Sci. Anal. 15(2): 119-132 (2023) - [j162]Longbing Cao:
AI and data science for smart emergency, crisis and disaster resilience. Int. J. Data Sci. Anal. 15(3): 231-246 (2023) - [j161]Zhi-Lin Zhao, Longbing Cao, Kun-Yu Lin:
Revealing the Distributional Vulnerability of Discriminators by Implicit Generators. IEEE Trans. Pattern Anal. Mach. Intell. 45(7): 8888-8901 (2023) - [j160]Zhilin Zhao, Longbing Cao, Kun-Yu Lin:
Supervision Adaptation Balancing In-Distribution Generalization and Out-of-Distribution Detection. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 15743-15758 (2023) - [j159]Shoujin Wang, Yan Wang, Liang Hu, Xiuzhen Zhang, Qi Zhang, Quan Z. Sheng, Mehmet A. Orgun, Longbing Cao, Defu Lian:
Modeling User Demand Evolution for Next-Basket Prediction. IEEE Trans. Knowl. Data Eng. 35(11): 11585-11598 (2023) - [j158]Zhilin Zhao, Longbing Cao:
Dual Representation Learning for Out-of-distribution Detection. Trans. Mach. Learn. Res. 2023 (2023) - [j157]Ping Qiu, Yongshun Gong, Yuhai Zhao, Longbing Cao, Chengqi Zhang, Xiangjun Dong:
An Efficient Method for Modeling Nonoccurring Behaviors by Negative Sequential Patterns With Loose Constraints. IEEE Trans. Neural Networks Learn. Syst. 34(4): 1864-1878 (2023) - [c195]Yang Yang, Zhilin Zhao, Longbing Cao:
Deep Spectral Copula Mechanisms Modeling Coupled and Volatile Multivariate Time Series. DSAA 2023: 1-10 - [c194]Matthew Lai, Longbing Cao, Haiyan Lu, Quang Ha, Li Li, Md. Jahangir Hossain, Paul J. Kennedy:
An Unsupervised Hierarchical Clustering Approach to Improve Hopfield Retrieval Accuracy. IJCNN 2023: 1-8 - [c193]Yang Yang, Longbing Cao:
MTSNet: Deep Probabilistic Cross-multivariate Time Series Modeling with External Factors for COVID-19. IJCNN 2023: 1-10 - [c192]Zhilin Zhao, Longbing Cao:
R-divergence for Estimating Model-oriented Distribution Discrepancy. NeurIPS 2023 - [c191]Kun Yi, Qi Zhang, Wei Fan, Hui He, Liang Hu, Pengyang Wang, Ning An, Longbing Cao, Zhendong Niu:
FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective. NeurIPS 2023 - [c190]Kun Yi, Qi Zhang, Wei Fan, Shoujin Wang, Pengyang Wang, Hui He, Ning An, Defu Lian, Longbing Cao, Zhendong Niu:
Frequency-domain MLPs are More Effective Learners in Time Series Forecasting. NeurIPS 2023 - [i61]Zhangkai Wu, Longbing Cao, Lei Qi:
eVAE: Evolutionary Variational Autoencoder. CoRR abs/2301.00011 (2023) - [i60]Hui He, Qi Zhang, Shoujin Wang, Kun Yi, Zhendong Niu, Longbing Cao:
Learning Informative Representation for Fairness-aware Multivariate Time-series Forecasting: A Group-based Perspective. CoRR abs/2301.11535 (2023) - [i59]Yu Dong, Jie Liang, Longbing Cao, Daniel R. Catchpoole:
ClinicLens: Visual Analytics for Exploring and Optimizing the Testing Capacity of Clinics given Uncertainty. CoRR abs/2303.13558 (2023) - [i58]Longbing Cao, Hui Chen, Xuhui Fan, João Gama, Yew-Soon Ong, Vipin Kumar:
Bayesian Federated Learning: A Survey. CoRR abs/2304.13267 (2023) - [i57]Jia Xu, Longbing Cao:
Copula Variational LSTM for High-dimensional Cross-market Multivariate Dependence Modeling. CoRR abs/2305.08778 (2023) - [i56]Zhangkai Wu, Longbing Cao:
C2VAE: Gaussian Copula-based VAE Differing Disentangled from Coupled Representations with Contrastive Posterior. CoRR abs/2309.13303 (2023) - [i55]Hui Chen, Hengyu Liu, Longbing Cao, Tiancheng Zhang:
Bayesian Personalized Federated Learning with Shared and Personalized Uncertainty Representations. CoRR abs/2309.15499 (2023) - [i54]Zhilin Zhao, Longbing Cao:
R-divergence for Estimating Model-oriented Distribution Discrepancy. CoRR abs/2310.01109 (2023) - [i53]Kun Yi, Qi Zhang, Wei Fan, Shoujin Wang, Pengyang Wang, Hui He, Defu Lian, Ning An, Longbing Cao, Zhendong Niu:
Frequency-domain MLPs are More Effective Learners in Time Series Forecasting. CoRR abs/2311.06184 (2023) - [i52]Kun Yi, Qi Zhang, Wei Fan, Hui He, Liang Hu, Pengyang Wang, Ning An, Longbing Cao, Zhendong Niu:
FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective. CoRR abs/2311.06190 (2023) - [i51]Zhilin Zhao, Longbing Cao, Yixuan Zhang:
Out-of-Distribution Knowledge Distillation via Confidence Amendment. CoRR abs/2311.07975 (2023) - [i50]An Lao, Qi Zhang, Chongyang Shi, Longbing Cao, Kun Yi, Liang Hu, Duoqian Miao:
Frequency Spectrum is More Effective for Multimodal Representation and Fusion: A Multimodal Spectrum Rumor Detector. CoRR abs/2312.11023 (2023) - 2022
- [j156]Guansong Pang, Chunhua Shen, Longbing Cao, Anton van den Hengel:
Deep Learning for Anomaly Detection: A Review. ACM Comput. Surv. 54(2): 38:1-38:38 (2022) - [j155]Shoujin Wang, Longbing Cao, Yan Wang, Quan Z. Sheng, Mehmet A. Orgun, Defu Lian:
A Survey on Session-based Recommender Systems. ACM Comput. Surv. 54(7): 154:1-154:38 (2022) - [j154]Longbing Cao:
AI Science and Engineering: A New Field. IEEE Intell. Syst. 37(1): 3-13 (2022) - [j153]Longbing Cao:
AI Science and Engineering. IEEE Intell. Syst. 37(1): 14-15 (2022) - [j152]Longbing Cao:
A New Age of AI: Features and Futures. IEEE Intell. Syst. 37(1): 25-37 (2022) - [j151]Longbing Cao:
AI in Combating the COVID-19 Pandemic. IEEE Intell. Syst. 37(2): 3-13 (2022) - [j150]Longbing Cao:
Non-IID Federated Learning. IEEE Intell. Syst. 37(2): 14-15 (2022) - [j149]Longbing Cao:
Deep Learning Applications. IEEE Intell. Syst. 37(3): 3-5 (2022) - [j148]Longbing Cao:
Decentralized AI: Edge Intelligence and Smart Blockchain, Metaverse, Web3, and DeSci. IEEE Intell. Syst. 37(3): 6-19 (2022) - [j147]Longbing Cao:
Non-IID Learning. IEEE Intell. Syst. 37(4): 3-4 (2022) - [j146]Longbing Cao:
Beyond i.i.d.: Non-IID Thinking, Informatics, and Learning. IEEE Intell. Syst. 37(4): 5-17 (2022) - [j145]Xuan Li, Peijun Ye, Juanjuan Li, Zhongmin Liu, Longbing Cao, Fei-Yue Wang:
From Features Engineering to Scenarios Engineering for Trustworthy AI: I&I, C&C, and V&V. IEEE Intell. Syst. 37(4): 18-26 (2022) - [j144]Longbing Cao:
AutoAI: Autonomous AI. IEEE Intell. Syst. 37(5): 3-5 (2022) - [j143]Longbing Cao:
Beyond AutoML: Mindful and Actionable AI and AutoAI With Mind and Action. IEEE Intell. Syst. 37(5): 6-18 (2022) - [j142]Siyuan Ren, Bin Guo, Ke Li, Qianru Wang, Zhiwen Yu, Longbing Cao:
CoupledMUTS: Coupled Multivariate Utility Time-Series Representation and Prediction. IEEE Internet Things J. 9(22): 22972-22982 (2022) - [j141]Chengzhang Zhu, Longbing Cao, Jianping Yin:
Unsupervised Heterogeneous Coupling Learning for Categorical Representation. IEEE Trans. Pattern Anal. Mach. Intell. 44(1): 533-549 (2022) - [j140]Siyuan Ren, Bin Guo, Longbing Cao, Ke Li, Jiaqi Liu, Zhiwen Yu:
DeepExpress: Heterogeneous and Coupled Sequence Modeling for Express Delivery Prediction. ACM Trans. Intell. Syst. Technol. 13(6): 89:1-89:22 (2022) - [j139]Jing Huang, Kun Luo, Longbing Cao, Yuanqiao Wen, Shuyuan Zhong:
Learning Multiaspect Traffic Couplings by Multirelational Graph Attention Networks for Traffic Prediction. IEEE Trans. Intell. Transp. Syst. 23(11): 20681-20695 (2022) - [j138]Jinjin Guo, Longbing Cao, Zhiguo Gong:
Recurrent Coupled Topic Modeling over Sequential Documents. ACM Trans. Knowl. Discov. Data 16(1): 8:1-8:32 (2022) - [j137]Qi Zhang, Longbing Cao, Chongyang Shi, Zhendong Niu:
Neural Time-Aware Sequential Recommendation by Jointly Modeling Preference Dynamics and Explicit Feature Couplings. IEEE Trans. Neural Networks Learn. Syst. 33(10): 5125-5137 (2022) - [c189]Wei Liu, Kexin Xie, Linsey Pang, James Bailey, Longbing Cao, Yuxi Zhang:
Deep Learning for Search and Recommendation. CIKM 2022: 5171-5172 - [c188]Mohammad Fahim Arefin, Chowdhury Farhan Ahmed, Redwan Ahmed Rizvee, Carson K. Leung, Longbing Cao:
Mining Contextual Item Similarity without Concept Hierarchy. IMCOM 2022: 1-8 - [c187]Qi Zhang, Liang Hu, Longbing Cao, Chongyang Shi, Shoujin Wang, Dora D. Liu:
A Probabilistic Code Balance Constraint with Compactness and Informativeness Enhancement for Deep Supervised Hashing. IJCAI 2022: 1651-1657 - [c186]Longbing Cao, Philip S. Yu, Zhilin Zhao:
Shallow and Deep Non-IID Learning on Complex Data. KDD 2022: 4774-4775 - [c185]Guansong Pang, Jundong Li, Anton van den Hengel, Longbing Cao, Thomas G. Dietterich:
ANDEA: Anomaly and Novelty Detection, Explanation, and Accommodation. KDD 2022: 4892-4893 - [i49]Zhilin Zhao, Longbing Cao, Yuan-Yu Wan:
Coupling Online-Offline Learning for Multi-distributional Data Streams. CoRR abs/2202.05996 (2022) - [i48]Wei Wang, Longbing Cao:
Explicit and Implicit Pattern Relation Analysis for Discovering Actionable Negative Sequences. CoRR abs/2204.03571 (2022) - [i47]Zhilin Zhao, Longbing Cao, Chang-Dong Wang:
Gray Learning from Non-IID Data with Out-of-distribution Samples. CoRR abs/2206.09375 (2022) - [i46]Zhilin Zhao, Longbing Cao, Kun-Yu Lin:
Supervision Adaptation Balances In-Distribution Generalization and Out-of-Distribution Detection. CoRR abs/2206.09380 (2022) - [i45]Zhilin Zhao, Longbing Cao, Kun-Yu Lin:
Out-of-distribution Detection by Cross-class Vicinity Distribution of In-distribution Data. CoRR abs/2206.09385 (2022) - [i44]Zhilin Zhao, Longbing Cao:
Label and Distribution-discriminative Dual Representation Learning for Out-of-Distribution Detection. CoRR abs/2206.09387 (2022) - [i43]Qi Zhang, Liang Hu, Chongyang Shi, Ke Liu, Longbing Cao:
Supervised Deep Hashing for High-dimensional and Heterogeneous Case-based Reasoning. CoRR abs/2206.14523 (2022) - [i42]Hui He, Qi Zhang, Kun Yi, Kaize Shi, Zhendong Niu, Longbing Cao:
Distributional Drift Adaptation with Temporal Conditional Variational Autoencoder for Multivariate Time Series Forecasting. CoRR abs/2209.00654 (2022) - [i41]Kun Yi, Qi Zhang, Liang Hu, Hui He, Ning An, Longbing Cao, Zhendong Niu:
Edge-Varying Fourier Graph Networks for Multivariate Time Series Forecasting. CoRR abs/2210.03093 (2022) - [i40]Rui Yu, Yifeng Li, Wenpeng Lu, Longbing Cao:
Tri-Attention: Explicit Context-Aware Attention Mechanism for Natural Language Processing. CoRR abs/2211.02899 (2022) - 2021
- [j136]Guansong Pang, Longbing Cao, Ling Chen:
Homophily outlier detection in non-IID categorical data. Data Min. Knowl. Discov. 35(4): 1163-1224 (2021) - [j135]Shufeng Hao, Chongyang Shi, Longbing Cao, Zhendong Niu, Ping Guo:
Learning deep relevance couplings for ad-hoc document retrieval. Expert Syst. Appl. 183: 115335 (2021) - [j134]Can Wang, Fosca Giannotti, Longbing Cao:
Learning Complex Couplings and Interactions. IEEE Intell. Syst. 36(1): 3-5 (2021) - [j133]Qing Liu, Trong Dinh Thac Do, Longbing Cao:
Answer Keyword Generation for Community Question Answering by Multiaspect Gamma-Poisson Matrix Completion. IEEE Intell. Syst. 36(4): 35-47 (2021) - [j132]Shoujin Wang, Longbing Cao, Liang Hu, Shlomo Berkovsky, Xiaoshui Huang, Lin Xiao, Wenpeng Lu:
Hierarchical Attentive Transaction Embedding With Intra- and Inter-Transaction Dependencies for Next-Item Recommendation. IEEE Intell. Syst. 36(4): 56-64 (2021) - [j131]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) - [j130]Jinjin Guo, Zhiguo Gong, Longbing Cao:
dhCM: Dynamic and Hierarchical Event Categorization and Discovery for Social Media Stream. ACM Trans. Intell. Syst. Technol. 12(5): 57:1-57:25 (2021) - [j129]Wei Wang, Longbing Cao:
VM-NSP: Vertical Negative Sequential Pattern Mining with Loose Negative Element Constraints. ACM Trans. Inf. Syst. 39(2): 22:1-22:27 (2021) - [j128]Wei Wang, Longbing Cao:
Interactive Sequential Basket Recommendation by Learning Basket Couplings and Positive/Negative Feedback. ACM Trans. Inf. Syst. 39(3): 24:1-24:26 (2021) - [c184]Guifeng Wang, Longbing Cao, Hongke Zhao, Qi Liu, Enhong Chen:
Coupling Macro-Sector-Micro Financial Indicators for Learning Stock Representations with Less Uncertainty. AAAI 2021: 4418-4426 - [c183]Qi Zhang, Longbing Cao, Chongyang Shi, Liang Hu:
Tripartite Collaborative Filtering with Observability and Selection for Debiasing Rating Estimation on Missing-Not-at-Random Data. AAAI 2021: 4671-4678 - [c182]Tianfu Zhang, Heyan Huang, Chong Feng, Longbing Cao:
Self-supervised Bilingual Syntactic Alignment for Neural Machine Translation. AAAI 2021: 14454-14462 - [c181]Qinfen Wang, Siyuan Ren, Yong Xia, Longbing Cao:
BiCMTS: Bidirectional Coupled Multivariate Learning of Irregular Time Series with Missing Values. CIKM 2021: 3493-3497 - [c180]Tianfu Zhang, Heyan Huang, Chong Feng, Longbing Cao:
Enlivening Redundant Heads in Multi-head Self-attention for Machine Translation. EMNLP (1) 2021: 3238-3248 - [c179]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. IJCAI 2021: 4644-4652 - [c178]Guansong Pang, Anton van den Hengel, Chunhua Shen, Longbing Cao:
Toward Deep Supervised Anomaly Detection: Reinforcement Learning from Partially Labeled Anomaly Data. KDD 2021: 1298-1308 - [c177]Guansong Pang, Jundong Li, Anton van den Hengel, Longbing Cao, Thomas G. Dietterich:
Anomaly and Novelty Detection, Explanation, and Accommodation (ANDEA). KDD 2021: 4145-4146 - [c176]Guansong Pang, Longbing Cao, Charu Aggarwal:
Deep Learning for Anomaly Detection: Challenges, Methods, and Opportunities. WSDM 2021: 1127-1130 - [i39]Guansong Pang, Longbing Cao, Ling Chen:
Homophily Outlier Detection in Non-IID Categorical Data. CoRR abs/2103.11516 (2021) - [i38]Longbing Cao, Qing Liu, Wenfeng Hou:
COVID-19 Modeling: A Review. CoRR abs/2104.12556 (2021) - [i37]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) - [i36]Jinjin Guo, Longbing Cao, Zhiguo Gong:
Recurrent Coupled Topic Modeling over Sequential Documents. CoRR abs/2106.13732 (2021) - [i35]Longbing Cao:
AI in Finance: Challenges, Techniques and Opportunities. CoRR abs/2107.09051 (2021) - [i34]Siyuan Ren, Bin Guo, Longbing Cao, Ke Li, Jiaqi Liu, Zhiwen Yu:
DeepExpress: Heterogeneous and Coupled Sequence Modeling for Express Delivery Prediction. CoRR abs/2108.08170 (2021) - [i33]Longbing Cao, Chengzhang Zhu:
Personalized next-best action recommendation with multi-party interaction learning for automated decision-making. CoRR abs/2108.08846 (2021) - [i32]Zhilin Zhao, Longbing Cao, Kun-Yu Lin:
Revealing Distributional Vulnerability of Explicit Discriminators by Implicit Generators. CoRR abs/2108.09976 (2021) - [i31]Qing Liu, Longbing Cao:
Modeling COVID-19 uncertainties evolving over time and density-dependent social reinforcement and asymptomatic infections. CoRR abs/2108.10029 (2021) - [i30]Longbing Cao, Chengzhang Zhu:
Table2Vec: Automated Universal Representation Learning to Encode All-round Data DNA for Benchmarkable and Explainable Enterprise Data Science. CoRR abs/2112.01830 (2021) - 2020
- [j127]Longbing Cao, Marley M. B. R. Vellasco:
IEEE DSAA-The IEEE Flagship Conference in Data Science [Society Briefs]. IEEE Comput. Intell. Mag. 15(3): 9-11 (2020) - [j126]Longbing Cao, George Yuan, Tim Leung, Wei Zhang:
Special Issue on AI and FinTech: The Challenge Ahead. IEEE Intell. Syst. 35(2): 3-6 (2020) - [j125]Longbing Cao, George Yuan, Tim Leung, Wei Zhang:
Special Issue on AI and FinTech: The Challenge Ahead. IEEE Intell. Syst. 35(3): 3-6 (2020) - [j124]Shoujin Wang, Gabriella Pasi, Liang Hu, Longbing Cao:
The Era of Intelligent Recommendation: Editorial on Intelligent Recommendation with Advanced AI and Learning. IEEE Intell. Syst. 35(5): 3-6 (2020) - [j123]Xiangjun Dong, Yongshun Gong, Longbing Cao:
e-RNSP: An Efficient Method for Mining Repetition Negative Sequential Patterns. IEEE Trans. Cybern. 50(5): 2084-2096 (2020) - [j122]Guansong Pang, Longbing Cao:
Heterogeneous Univariate Outlier Ensembles in Multidimensional Data. ACM Trans. Knowl. Discov. Data 14(6): 68:1-68:27 (2020) - [j121]Shoujin Wang, Longbing Cao:
Inferring Implicit Rules by Learning Explicit and Hidden Item Dependency. IEEE Trans. Syst. Man Cybern. Syst. 50(3): 935-946 (2020) - [c175]Songlei Jian, Liang Hu, Longbing Cao, Kai Lu:
Representation Learning with Multiple Lipschitz-Constrained Alignments on Partially-Labeled Cross-Domain Data. AAAI 2020: 4320-4327 - [c174]Shoujin Wang, Liang Hu, Yan Wang, Quan Z. Sheng, Mehmet A. Orgun, Longbing Cao:
Intention Nets: Psychology-Inspired User Choice Behavior Modeling for Next-Basket Prediction. AAAI 2020: 6259-6266 - [c173]Chengzhang Zhu, Qi Zhang, Longbing Cao, Arman Abrahamyan:
Mix2Vec: Unsupervised Mixed Data Representation. DSAA 2020: 118-127 - [c172]Shoujin Wang, Liang Hu, Yan Wang, Quan Z. Sheng, Mehmet A. Orgun, Longbing Cao:
Intention2Basket: A Neural Intention-driven Approach for Dynamic Next-basket Planning. IJCAI 2020: 2333-2339 - [c171]Longxiang Shi, Shijian Li, Qian Zheng, Longbing Cao, Long Yang, Gang Pan:
Maximum Entropy Reinforcement Learning with Evolution Strategies. IJCNN 2020: 1-8 - [e24]Geoffrey I. Webb, Zhongfei Zhang, Vincent S. Tseng, Graham Williams, Michalis Vlachos, Longbing Cao:
7th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2020, Sydney, Australia, October 6-9, 2020. IEEE 2020, ISBN 978-1-7281-8206-3 [contents] - [i29]Shoujin Wang, Liang Hu, Yan Wang, Longbing Cao, Quan Z. Sheng, Mehmet A. Orgun:
Sequential Recommender Systems: Challenges, Progress and Prospects. CoRR abs/2001.04830 (2020) - [i28]Shoujin Wang, Liang Hu, Yan Wang, Xiangnan He, Quan Z. Sheng, Mehmet A. Orgun, Longbing Cao, Nan Wang, Francesco Ricci, Philip S. Yu:
Graph Learning Approaches to Recommender Systems: A Review. CoRR abs/2004.11718 (2020) - [i27]Shoujin Wang, Longbing Cao, Liang Hu, Shlomo Berkovsky, Xiaoshui Huang, Lin Xiao, Wenpeng Lu:
Jointly Modeling Intra- and Inter-transaction Dependencies with Hierarchical Attentive Transaction Embeddings for Next-item Recommendation. CoRR abs/2006.04530 (2020) - [i26]Longbing Cao:
Data Science: Nature and Pitfalls. CoRR abs/2006.16964 (2020) - [i25]Longbing Cao:
Data Science: Challenges and Directions. CoRR abs/2006.16966 (2020) - [i24]Guansong Pang, Chunhua Shen, Longbing Cao, Anton van den Hengel:
Deep Learning for Anomaly Detection: A Review. CoRR abs/2007.02500 (2020) - [i23]Longbing Cao:
Data Science: A Comprehensive Overview. CoRR abs/2007.03606 (2020) - [i22]Longbing Cao:
Non-IID Recommender Systems: A Review and Framework of Recommendation Paradigm Shifting. CoRR abs/2007.07217 (2020) - [i21]Chengzhang Zhu, Longbing Cao, Jianping Yin:
Unsupervised Heterogeneous Coupling Learning for Categorical Representation. CoRR abs/2007.10720 (2020) - [i20]Longbing Cao:
AI in FinTech: A Research Agenda. CoRR abs/2007.12681 (2020) - [i19]Longbing Cao:
Coupling Learning of Complex Interactions. CoRR abs/2007.13534 (2020) - [i18]Longbing Cao:
In-Depth Behavior Understanding and Use: The Behavior Informatics Approach. CoRR abs/2007.15516 (2020) - [i17]Feng Xia, Haifeng Liu, Ivan Lee, Longbing Cao:
Scientific Article Recommendation: Exploiting Common Author Relations and Historical Preferences. CoRR abs/2008.04652 (2020) - [i16]Guansong Pang, Anton van den Hengel, Chunhua Shen, Longbing Cao:
Deep Reinforcement Learning for Unknown Anomaly Detection. CoRR abs/2009.06847 (2020)
2010 – 2019
- 2019
- [j120]Bin Guo, Yi Ouyang, Tong Guo, Longbing Cao, Zhiwen Yu:
Enhancing Mobile App User Understanding and Marketing With Heterogeneous Crowdsourced Data: A Review. IEEE Access 7: 68557-68571 (2019) - [j119]Liang Hu, Qingkui Chen, Longbing Cao, Songlei Jian, Haiyan Zhao, Jian Cao:
Evolving Coauthorship Modeling and Prediction via Time-Aware Paired Choice Analysis. IEEE Access 7: 98639-98651 (2019) - [j118]Wei Wang, Longbing Cao:
Negative Sequence Analysis: A Review. ACM Comput. Surv. 52(2): 32:1-32:39 (2019) - [j117]Shufeng Hao, Chongyang Shi, Zhendong Niu, Longbing Cao:
Modeling positive and negative feedback for improving document retrieval. Expert Syst. Appl. 120: 253-261 (2019) - [j116]Longbing Cao:
Data Science: Profession and Education. IEEE Intell. Syst. 34(5): 35-44 (2019) - [j115]Qi Zhang, Chongyang Shi, Zhendong Niu, Longbing Cao:
HCBC: A Hierarchical Case-Based Classifier Integrated with Conceptual Clustering. IEEE Trans. Knowl. Data Eng. 31(1): 152-165 (2019) - [j114]Songlei Jian, Guansong Pang, Longbing Cao, Kai Lu, Hang Gao:
CURE: Flexible Categorical Data Representation by Hierarchical Coupling Learning. IEEE Trans. Knowl. Data Eng. 31(5): 853-866 (2019) - [j113]Xiangjun Dong, Ping Qiu, Jinhu Lü, Longbing Cao, Tiantian Xu:
Mining Top- ${k}$ Useful Negative Sequential Patterns via Learning. IEEE Trans. Neural Networks Learn. Syst. 30(9): 2764-2778 (2019) - [c170]Peng Xu, Zhaohong Deng, Kup-Sze Choi, Longbing Cao, Shitong Wang:
Multi-View Information-Theoretic Co-Clustering for Co-Occurrence Data. AAAI 2019: 379-386 - [c169]Songlei Jian, Liang Hu, Longbing Cao, Kai Lu, Hang Gao:
Evolutionarily Learning Multi-Aspect Interactions and Influences from Network Structure and Node Content. AAAI 2019: 598-605 - [c168]Liang Hu, Songlei Jian, Longbing Cao, Zhiping Gu, Qingkui Chen, Artak Amirbekyan:
HERS: Modeling Influential Contexts with Heterogeneous Relations for Sparse and Cold-Start Recommendation. AAAI 2019: 3830-3837 - [c167]Longxiang Shi, Shijian Li, Longbing Cao, Long Yang, Gang Pan:
TBQ(σ): Improving Efficiency of Trace Utilization for Off-Policy Reinforcement Learning. AAMAS 2019: 1025-1032 - [c166]Shoujin Wang, Liang Hu, Yan Wang, Quan Z. Sheng, Mehmet A. Orgun, Longbing Cao:
Modeling Multi-Purpose Sessions for Next-Item Recommendations via Mixture-Channel Purpose Routing Networks. IJCAI 2019: 3771-3777 - [c165]Shoujin Wang, Liang Hu, Yan Wang, Longbing Cao, Quan Z. Sheng, Mehmet A. Orgun:
Sequential Recommender Systems: Challenges, Progress and Prospects. IJCAI 2019: 6332-6338 - [i15]Shoujin Wang, Longbing Cao, Yan Wang:
A Survey on Session-based Recommender Systems. CoRR abs/1902.04864 (2019) - [i14]Longxiang Shi, Shijian Li, Longbing Cao, Long Yang, Gang Pan:
TBQ(σ): Improving Efficiency of Trace Utilization for Off-Policy Reinforcement Learning. CoRR abs/1905.07237 (2019) - [i13]Peng Xu, Zhaohong Deng, Kup-Sze Choi, Longbing Cao, Shitong Wang:
Multi-view Information-theoretic Co-clustering for Co-occurrence Data. CoRR abs/1905.10594 (2019) - 2018
- [j112]Shufeng Hao, Chongyang Shi, Zhendong Niu, Longbing Cao:
Concept coupling learning for improving concept lattice-based document retrieval. Eng. Appl. Artif. Intell. 69: 65-75 (2018) - [j111]Fanrong Meng, Xiaobin Rui, Zhixiao Wang, Yan Xing, Longbing Cao:
Coupled Node Similarity Learning for Community Detection in Attributed Networks. Entropy 20(6): 471 (2018) - [j110]Liang Hu, Qingkui Chen, Haiyan Zhao, Songlei Jian, Longbing Cao, Jian Cao:
Neural Cross-Session Filtering: Next-Item Prediction Under Intra- and Inter-Session Context. IEEE Intell. Syst. 33(6): 57-67 (2018) - [j109]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) - [j108]Yi Ouyang, Bin Guo, Tong Guo, Longbing Cao, Zhiwen Yu:
Modeling and Forecasting the Popularity Evolution of Mobile Apps: A Multivariate Hawkes Process Approach. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2(4): 182:1-182:23 (2018) - [j107]Lizhen Wang, Xuguang Bao, Hongmei Chen, Longbing Cao:
Effective lossless condensed representation and discovery of spatial co-location patterns. Inf. Sci. 436-437: 197-213 (2018) - [j106]Zhaohong Deng, Junyong Chen, Te Zhang, Longbing Cao, Shitong Wang:
Generalized Hidden-Mapping Minimax Probability Machine for the training and reliability learning of several classical intelligent models. Inf. Sci. 436-437: 302-319 (2018) - [j105]Xiangjun Dong, Yongshun Gong, Longbing Cao:
F-NSP+: A fast negative sequential patterns mining method with self-adaptive data storage. Pattern Recognit. 84: 13-27 (2018) - [j104]Yonggang Huang, Longbing Cao, Jun Zhang, Lei Pan, Yuying Liu:
Exploring Feature Coupling and Model Coupling for Image Source Identification. IEEE Trans. Inf. Forensics Secur. 13(12): 3108-3121 (2018) - [j103]Can Wang, Chi-Hung Chi, Zhong She, Longbing Cao, Bela Stantic:
Coupled Clustering Ensemble by Exploring Data Interdependence. ACM Trans. Knowl. Discov. Data 12(6): 63:1-63:38 (2018) - [j102]Chengzhang Zhu, Longbing Cao, Qiang Liu, Jianping Yin, Vipin Kumar:
Heterogeneous Metric Learning of Categorical Data with Hierarchical Couplings. IEEE Trans. Knowl. Data Eng. 30(7): 1254-1267 (2018) - [j101]Songlei Jian, Longbing Cao, Kai Lu, Hang Gao:
Unsupervised Coupled Metric Similarity for Non-IID Categorical Data. IEEE Trans. Knowl. Data Eng. 30(9): 1810-1823 (2018) - [j100]Defu Lian, Kai Zheng, Yong Ge, Longbing Cao, Enhong Chen, Xing Xie:
GeoMF++: Scalable Location Recommendation via Joint Geographical Modeling and Matrix Factorization. ACM Trans. Inf. Syst. 36(3): 33:1-33:29 (2018) - [c164]Shoujin Wang, Liang Hu, Longbing Cao, Xiaoshui Huang, Defu Lian, Wei Liu:
Attention-Based Transactional Context Embedding for Next-Item Recommendation. AAAI 2018: 2532-2539 - [c163]Trong Dinh Thac Do, Longbing Cao:
Coupled Poisson Factorization Integrated With User/Item Metadata for Modeling Popular and Sparse Ratings in Scalable Recommendation. AAAI 2018: 2918-2925 - [c162]Songlei Jian, Liang Hu, Longbing Cao, Kai Lu:
Metric-Based Auto-Instructor for Learning Mixed Data Representation. AAAI 2018: 3318-3325 - [c161]Guansong Pang, Longbing Cao, Ling Chen, Defu Lian, Huan Liu:
Sparse Modeling-Based Sequential Ensemble Learning for Effective Outlier Detection in High-Dimensional Numeric Data. AAAI 2018: 3892-3899 - [c160]Lizhen Wang, Xuguang Bao, Longbing Cao:
Interactive Probabilistic Post-Mining of User-Preferred Spatial Co-Location Patterns. ICDE 2018: 1256-1259 - [c159]Xingyu Chen, Fanghui Liu, Enmei Tu, Longbing Cao, Jie Yang:
Deep-PUMR: Deep Positive and Unlabeled Learning with Manifold Regularization. ICONIP (1) 2018: 12-20 - [c158]Liang Hu, Songlei Jian, Longbing Cao, Qingkui Chen:
Interpretable Recommendation via Attraction Modeling: Learning Multilevel Attractiveness over Multimodal Movie Contents. IJCAI 2018: 3400-3406 - [c157]Quangui Zhang, Longbing Cao, Chengzhang Zhu, Zhiqiang Li, Jinguang Sun:
CoupledCF: Learning Explicit and Implicit User-item Couplings in Recommendation for Deep Collaborative Filtering. IJCAI 2018: 3662-3668 - [c156]Trong Dinh Thac Do, Longbing Cao:
Metadata-dependent Infinite Poisson Factorization for Efficiently Modelling Sparse and Large Matrices in Recommendation. IJCAI 2018: 5010-5016 - [c155]Defu Lian, Kai Zheng, Vincent W. Zheng, Yong Ge, Longbing Cao, Ivor W. Tsang, Xing Xie:
High-order Proximity Preserving Information Network Hashing. KDD 2018: 1744-1753 - [c154]Guansong Pang, Longbing Cao, Ling Chen, Huan Liu:
Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection. KDD 2018: 2041-2050 - [c153]Trong Dinh Thac Do, Longbing Cao:
Gamma-Poisson Dynamic Matrix Factorization Embedded with Metadata Influence. NeurIPS 2018: 5829-5840 - [c152]Jia Xu, Longbing Cao:
Vine Copula-Based Asymmetry and Tail Dependence Modeling. PAKDD (1) 2018: 285-297 - [c151]Liying Zhang, Longbing Cao, Sheng Luo, Lei Gu, Yijin Chen, Yuanfeng Lian:
Coupled Collective Matrix Factorization. SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2018: 1023-1030 - [i12]Guansong Pang, Longbing Cao, Ling Chen, Huan Liu:
Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection. CoRR abs/1806.04808 (2018) - 2017
- [j99]Yunzhi Jiang, Pohsiang Tsai, Wei-Chang Yeh, Longbing Cao:
A honey-bee-mating based algorithm for multilevel image segmentation using Bayesian theorem. Appl. Soft Comput. 52: 1181-1190 (2017) - [j98]Longbing Cao:
Data science: challenges and directions. Commun. ACM 60(8): 59-68 (2017) - [j97]Longbing Cao:
Data Science: A Comprehensive Overview. ACM Comput. Surv. 50(3): 43:1-43:42 (2017) - [j96]Tingting Zhai, Yang Gao, Hao Wang, Longbing Cao:
Classification of high-dimensional evolving data streams via a resource-efficient online ensemble. Data Min. Knowl. Discov. 31(5): 1242-1265 (2017) - [j95]Shameek Ghosh, Jinyan Li, Longbing Cao, Kotagiri Ramamohanarao:
Septic shock prediction for ICU patients via coupled HMM walking on sequential contrast patterns. J. Biomed. Informatics 66: 19-31 (2017) - [j94]Xiangfu Meng, Longbing Cao, Xiaoyan Zhang, Jingyu Shao:
Top-k coupled keyword recommendation for relational keyword queries. Knowl. Inf. Syst. 50(3): 883-916 (2017) - [j93]Bo Liu, Yanshan Xiao, Longbing Cao:
SVM-based multi-state-mapping approach for multi-class classification. Knowl. Based Syst. 129: 79-96 (2017) - [j92]Xuhui Fan, Richard Yi Da Xu, Longbing Cao, Yin Song:
Learning Nonparametric Relational Models by Conjugately Incorporating Node Information in a Network. IEEE Trans. Cybern. 47(3): 589-599 (2017) - [j91]Liang Hu, Longbing Cao, Jian Cao, Zhiping Gu, Guandong Xu, Jie Wang:
Improving the Quality of Recommendations for Users and Items in the Tail of Distribution. ACM Trans. Inf. Syst. 35(3): 25:1-25:37 (2017) - [j90]Xiangmin Zhou, Lei Chen, Yanchun Zhang, Dong Qin, Longbing Cao, Guangyan Huang, Chen Wang:
Enhancing online video recommendation using social user interactions. VLDB J. 26(5): 637-656 (2017) - [c150]Yinghuan Shi, Wenbin Li, Yang Gao, Longbing Cao, Dinggang Shen:
Beyond IID: Learning to Combine Non-IID Metrics for Vision Tasks. AAAI 2017: 1524-1531 - [c149]Guansong Pang, Hongzuo Xu, Longbing Cao, Wentao Zhao:
Selective Value Coupling Learning for Detecting Outliers in High-Dimensional Categorical Data. CIKM 2017: 807-816 - [c148]Jia Xu, Wei Wei, Longbing Cao:
Copula-Based High Dimensional Cross-Market Dependence Modeling. DSAA 2017: 734-743 - [c147]Liang Hu, Longbing Cao, Shoujin Wang, Guandong Xu, Jian Cao, Zhiping Gu:
Diversifying Personalized Recommendation with User-session Context. IJCAI 2017: 1858-1864 - [c146]Songlei Jian, Longbing Cao, Guansong Pang, Kai Lu, Hang Gao:
Embedding-based Representation of Categorical Data by Hierarchical Value Coupling Learning. IJCAI 2017: 1937-1943 - [c145]Guansong Pang, Longbing Cao, Ling Chen, Huan Liu:
Learning Homophily Couplings from Non-IID Data for Joint Feature Selection and Noise-Resilient Outlier Detection. IJCAI 2017: 2585-2591 - [c144]Longbing Cao:
Behavior Informatics to Discover Behavior Insight for Active and Tailored Client Management. KDD 2017: 15-16 - [c143]Defu Lian, Rui Liu, Yong Ge, Kai Zheng, Xing Xie, Longbing Cao:
Discrete Content-aware Matrix Factorization. KDD 2017: 325-334 - [c142]Shoujin Wang, Liang Hu, Longbing Cao:
Perceiving the Next Choice with Comprehensive Transaction Embeddings for Online Recommendation. ECML/PKDD (2) 2017: 285-302 - [e23]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] - [e22]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
- [j89]Longbing Cao, Xiangjun Dong, Zhigang Zheng:
e-NSP: Efficient negative sequential pattern mining. Artif. Intell. 235: 156-182 (2016) - [j88]Éric Gaussier, Longbing Cao:
Conference Report on 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA'2015) [Conference Reports]. IEEE Comput. Intell. Mag. 11(1): 13-14 (2016) - [j87]Longbing Cao:
Data Science: Nature and Pitfalls. IEEE Intell. Syst. 31(5): 66-75 (2016) - [j86]Longbing Cao:
Data science and analytics: a new era. Int. J. Data Sci. Anal. 1(1): 1-2 (2016) - [j85]Dong Li, Xianmang He, Longbing Cao, Huahui Chen:
Permutation anonymization. J. Intell. Inf. Syst. 47(3): 427-445 (2016) - [j84]Fangfang Li, Guandong Xu, Longbing Cao:
Two-level matrix factorization for recommender systems. Neural Comput. Appl. 27(8): 2267-2278 (2016) - [j83]Feng Xia, Haifeng Liu, Ivan Lee, Longbing Cao:
Scientific Article Recommendation: Exploiting Common Author Relations and Historical Preferences. IEEE Trans. Big Data 2(2): 101-112 (2016) - [j82]Liang Hu, Longbing Cao, Jian Cao, Zhiping Gu, Guandong Xu, Dingyu Yang:
Learning Informative Priors from Heterogeneous Domains to Improve Recommendation in Cold-Start User Domains. ACM Trans. Inf. Syst. 35(2): 13:1-13:37 (2016) - [j81]Zhigang Zheng, Wei Wei, Chunming Liu, Wei Cao, Longbing Cao, Maninder Bhatia:
An effective contrast sequential pattern mining approach to taxpayer behavior analysis. World Wide Web 19(4): 633-651 (2016) - [j80]Bin Shen, Longbing Cao, Min Yao, Yunjun Gao:
Mining preferred navigation patterns by consolidating both selection and time preferences. World Wide Web 19(5): 979-1007 (2016) - [c141]Karnam Dileep Kumar, Krishna Reddy Polepalli, Pailla Balakrishna Reddy, Longbing Cao:
Improving the Performance of Collaborative Filtering with Category-Specific Neighborhood. ACIIDS (2) 2016: 201-210 - [c140]Guansong Pang, Longbing Cao, Ling Chen, Huan Liu:
Unsupervised Feature Selection for Outlier Detection by Modelling Hierarchical Value-Feature Couplings. ICDM 2016: 410-419 - [c139]Xuhui Fan, Richard Yi Da Xu, Longbing Cao:
Copula Mixed-Membership Stochastic Blockmodel. IJCAI 2016: 1462-1468 - [c138]Guansong Pang, Longbing Cao, Ling Chen:
Outlier Detection in Complex Categorical Data by Modeling the Feature Value Couplings. IJCAI 2016: 1902-1908 - [c137]Shoujin Wang, Wei Liu, Jia Wu, Longbing Cao, Qinxue Meng, Paul J. Kennedy:
Training deep neural networks on imbalanced data sets. IJCNN 2016: 4368-4374 - 2015
- [b2]Longbing Cao:
Metasynthetic Computing and Engineering of Complex Systems. Advanced Information and Knowledge Processing, Springer 2015, ISBN 978-1-4471-6550-7, pp. 1-341 - [j79]Anna Fariha, Chowdhury Farhan Ahmed, Carson K. Leung, Md. Samiullah, Suraiya Pervin, Longbing Cao:
A new framework for mining frequent interaction patterns from meeting databases. Eng. Appl. Artif. Intell. 45: 103-118 (2015) - [j78]Wei Cao, Longbing Cao:
Financial Crisis Forecasting via Coupled Market State Analysis. IEEE Intell. Syst. 30(2): 18-25 (2015) - [j77]Longbing Cao, Philip S. Yu, Vipin Kumar:
Nonoccurring Behavior Analytics: A New Area. IEEE Intell. Syst. 30(6): 4-11 (2015) - [j76]Longbing Cao:
Coupling learning of complex interactions. Inf. Process. Manag. 51(2): 167-186 (2015) - [j75]Xiaodong Yue, Longbing Cao, Duoqian Miao, Yufei Chen, B. Xu:
Multi-view attribute reduction model for traffic bottleneck analysis. Knowl. Based Syst. 86: 1-10 (2015) - [j74]Xuhui Fan, Longbing Cao:
A convergence theorem for graph shift-type algorithms. Pattern Recognit. 48(8): 2751-2760 (2015) - [j73]Yunzhi Jiang, Pohsiang Tsai, Zhifeng Hao, Longbing Cao:
Automatic multilevel thresholding for image segmentation using stratified sampling and Tabu Search. Soft Comput. 19(9): 2605-2617 (2015) - [j72]Weiwei Liu, Zhi-Hong Deng, Longbing Cao, Xiaoran Xu, He Liu, Xiuwen Gong:
Mining Top K Spread Sources for a Specific Topic and a Given Node. IEEE Trans. Cybern. 45(11): 2472-2483 (2015) - [j71]Zhaohong Deng, Longbing Cao, Yizhang Jiang, Shitong Wang:
Minimax Probability TSK Fuzzy System Classifier: A More Transparent and Highly Interpretable Classification Model. IEEE Trans. Fuzzy Syst. 23(4): 813-826 (2015) - [j70]Philippe Fournier-Viger, Cheng-Wei Wu, Vincent S. Tseng, Longbing Cao, Roger Nkambou:
Mining Partially-Ordered Sequential Rules Common to Multiple Sequences. IEEE Trans. Knowl. Data Eng. 27(8): 2203-2216 (2015) - [j69]Can Wang, Xiangjun Dong, Fei Zhou, Longbing Cao, Chi-Hung Chi:
Coupled Attribute Similarity Learning on Categorical Data. IEEE Trans. Neural Networks Learn. Syst. 26(4): 781-797 (2015) - [j68]Xuhui Fan, Longbing Cao, Richard Yi Da Xu:
Dynamic Infinite Mixed-Membership Stochastic Blockmodel. IEEE Trans. Neural Networks Learn. Syst. 26(9): 2072-2085 (2015) - [j67]Wanqi Yang, Yang Gao, Yinghuan Shi, Longbing Cao:
MRM-Lasso: A Sparse Multiview Feature Selection Method via Low-Rank Analysis. IEEE Trans. Neural Networks Learn. Syst. 26(11): 2801-2815 (2015) - [j66]Can Wang, Longbing Cao, Chi-Hung Chi:
Formalization and Verification of Group Behavior Interactions. IEEE Trans. Syst. Man Cybern. Syst. 45(8): 1109-1124 (2015) - [c136]Wei Cao, Liang Hu, Longbing Cao:
Deep Modeling Complex Couplings within Financial Markets. AAAI 2015: 2518-2524 - [c135]Xinxin Jiang, Wei Liu, Longbing Cao, Guodong Long:
Coupled Collaborative Filtering for Context-aware Recommendation. AAAI 2015: 4172-4173 - [c134]Jingyu Shao, Junfu Yin, Wei Liu, Longbing Cao:
Actionable Combined High Utility Itemset Mining. AAAI 2015: 4206-4207 - [c133]Xiaodong Yue, Longbing Cao, Yufei Chen, Bin Xu:
Multi-View Actionable Patterns for Managing Traffic Bottleneck. AAAI Workshop: AI for Transportation 2015 - [c132]Wei Cao, Yves Demazeau, Longbing Cao, Weidong Zhu:
Financial crisis and global market couplings. DSAA 2015: 1-10 - [c131]Qianqian Chen, Liang Hu, Jia Xu, Wei Liu, Longbing Cao:
Document similarity analysis via involving both explicit and implicit semantic couplings. DSAA 2015: 1-10 - [c130]Jingyu Shao, Junfu Yin, Wei Liu, Longbing Cao:
Mining actionable combined patterns of high utility and frequency. DSAA 2015: 1-10 - [c129]Marco Rossetti, Fabio Stella, Longbing Cao, Markus Zanker:
Analysing User Reviews in Tourism with Topic Models. ENTER 2015: 47-58 - [c128]Chunming Liu, Longbing Cao:
A Coupled k-Nearest Neighbor Algorithm for Multi-label Classification. PAKDD (1) 2015: 176-187 - [c127]Fangfang Li, Guandong Xu, Longbing Cao:
Coupled Matrix Factorization Within Non-IID Context. PAKDD (2) 2015: 707-719 - [c126]Bin Fu, Guandong Xu, Longbing Cao, Zhihai Wang, Zhiang Wu:
Coupling Multiple Views of Relations for Recommendation. PAKDD (2) 2015: 732-743 - [c125]Xiangmin Zhou, Lei Chen, Yanchun Zhang, Longbing Cao, Guangyan Huang, Chen Wang:
Online Video Recommendation in Sharing Community. SIGMOD Conference 2015: 1645-1656 - [e21]Longbing Cao, Yifeng Zeng, Bo An, Andreas L. Symeonidis, Vladimir Gorodetsky, Frans Coenen, Philip S. Yu:
Agents and Data Mining Interaction - 10th International Workshop, ADMI 2014, Paris, France, May 5-9, 2014, Revised Selected Papers. Lecture Notes in Computer Science 9145, Springer 2015, ISBN 978-3-319-20229-7 [contents] - [e20]Longbing Cao, Chengqi Zhang, Thorsten Joachims, Geoffrey I. Webb, Dragos D. Margineantu, Graham Williams:
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Sydney, NSW, Australia, August 10-13, 2015. ACM 2015, ISBN 978-1-4503-3664-2 [contents] - [i11]Fangfang Li, Guandong Xu, Longbing Cao:
CSAL: Self-adaptive Labeling based Clustering Integrating Supervised Learning on Unlabeled Data. CoRR abs/1502.05111 (2015) - [i10]Fangfang Li, Yanchang Zhao, Klaus Felsche, Guandong Xu, Longbing Cao:
Coupling Analysis Between Twitter and Call Centre. CoRR abs/1509.02238 (2015) - 2014
- [j65]Yanshan Xiao, Bo Liu, Zhifeng Hao, Longbing Cao:
A K-Farthest-Neighbor-based approach for support vector data description. Appl. Intell. 41(1): 196-211 (2014) - [j64]Wanqi Yang, Yang Gao, Longbing Cao, Ming Yang, Yinghuan Shi:
mPadal: a joint local-and-global multi-view feature selection method for activity recognition. Appl. Intell. 41(3): 776-790 (2014) - [j63]Lin Zhu, Longbing Cao, Jie Yang, Jingsheng Lei:
Evolving soft subspace clustering. Appl. Soft Comput. 14: 210-228 (2014) - [j62]Longbing Cao:
Non-IIDness Learning in Behavioral and Social Data. Comput. J. 57(9): 1358-1370 (2014) - [j61]Longbing Cao, Thorsten Joachims, Can Wang, Éric Gaussier, Jinjiu Li, Yuming Ou, Dan Luo, Reza Zafarani, Huan Liu, Guandong Xu, Zhiang Wu, Gabriella Pasi, Ya Zhang, Xiaokang Yang, Hongyuan Zha, Edoardo Serra, V. S. Subrahmanian:
Behavior Informatics: A New Perspective. IEEE Intell. Syst. 29(4): 62-80 (2014) - [j60]Enmei Tu, Longbing Cao, Jie Yang, Nikola K. Kasabov:
A novel graph-based k-means for nonlinear manifold clustering and representative selection. Neurocomputing 143: 109-122 (2014) - [j59]Bo Liu, Yanshan Xiao, Philip S. Yu, Zhifeng Hao, Longbing Cao:
An efficient orientation distance-based discriminative feature extraction method for multi-classification. Knowl. Inf. Syst. 39(2): 409-433 (2014) - [j58]Cheng Wang, Tiejun Tong, Longbing Cao, Baiqi Miao:
Non-parametric shrinkage mean estimation for quadratic loss functions with unknown covariance matrices. J. Multivar. Anal. 125: 222-232 (2014) - [j57]Xiaodong Yue, Duoqian Miao, Longbing Cao, Qiang Wu, Yufei Chen:
An efficient color quantization based on generic roughness measure. Pattern Recognit. 47(4): 1777-1789 (2014) - [j56]Bin Fu, Zhihai Wang, Guandong Xu, Longbing Cao:
Multi-label learning based on iterative label propagation over graph. Pattern Recognit. Lett. 42: 85-90 (2014) - [j55]Mu Li, Jinjiu Li, Yuming Ou, Ya Zhang, Dan Luo, Maninder Bahtia, Longbing Cao:
Coupled K-Nearest Centroid Classification for Non-iid Data. Trans. Comput. Collect. Intell. 15: 89-100 (2014) - [j54]Hui-Dong Liu, Ming Yang, Yang Gao, Longbing Cao:
Fast Local Histogram Specification. IEEE Trans. Circuits Syst. Video Technol. 24(11): 1833-1843 (2014) - [j53]Yanshan Xiao, Bo Liu, Zhifeng Hao, Longbing Cao:
A Similarity-Based Classification Framework for Multiple-Instance Learning. IEEE Trans. Cybern. 44(4): 500-515 (2014) - [j52]Bo Liu, Yanshan Xiao, Philip S. Yu, Longbing Cao, Yun Zhang, Zhifeng Hao:
Uncertain One-Class Learning and Concept Summarization Learning on Uncertain Data Streams. IEEE Trans. Knowl. Data Eng. 26(2): 468-484 (2014) - [j51]Bo Liu, Yanshan Xiao, Philip S. Yu, Zhifeng Hao, Longbing Cao:
An Efficient Approach for Outlier Detection with Imperfect Data Labels. IEEE Trans. Knowl. Data Eng. 26(7): 1602-1616 (2014) - [j50]Zhe Xu, Ya Zhang, Longbing Cao:
Social Image Analysis From a Non-IID Perspective. IEEE Trans. Multim. 16(7): 1986-1998 (2014) - [j49]Zhaohong Deng, Kup-Sze Choi, Longbing Cao, Shitong Wang:
T2FELA: Type-2 Fuzzy Extreme Learning Algorithm for Fast Training of Interval Type-2 TSK Fuzzy Logic System. IEEE Trans. Neural Networks Learn. Syst. 25(4): 664-676 (2014) - [c124]Liang Hu, Jian Cao, Guandong Xu, Longbing Cao, Zhiping Gu, Wei Cao:
Deep Modeling of Group Preferences for Group-Based Recommendation. AAAI 2014: 1861-1867 - [c123]Mu Li, Jinjiu Li, Yuming Ou, Longbing Cao:
A Coupled Similarity Kernel for Pairwise Support Vector Machine. ADMI 2014: 114-123 - [c122]Xiangfu Meng, Longbing Cao, Jingyu Shao:
Semantic Approximate Keyword Query Based on Keyword and Query Coupling Relationship Analysis. CIKM 2014: 529-538 - [c121]Philip S. Yu, Masaru Kitsuregawa, Hiroshi Motoda, Bart Goethals, Minyi Guo, Longbing Cao, George Karypis, Irwin King, Wei Wang:
Welcome from DSAA 2014 chairs. DSAA 2014: 9-10 - [c120]Zhaohong Deng, Yizhang Jiang, Longbing Cao, Shitong Wang:
Knowledge-leverage based TSK fuzzy system with improved knowledge transfer. FUZZ-IEEE 2014: 178-185 - [c119]Liang Hu, Wei Cao, Jian Cao, Guandong Xu, Longbing Cao, Zhiping Gu:
Bayesian Heteroskedastic Choice Modeling on Non-identically Distributed Linkages. ICDM 2014: 851-856 - [c118]Chunming Liu, Longbing Cao, Philip S. Yu:
Coupled fuzzy k-nearest neighbors classification of imbalanced non-IID categorical data. IJCNN 2014: 1122-1129 - [c117]Chunming Liu, Longbing Cao, Philip S. Yu:
A hybrid coupled k-nearest neighbor algorithm on imbalance data. IJCNN 2014: 2011-2018 - [c116]Wei Wei, Junfu Yin, Jinyan Li, Longbing Cao:
Modeling Asymmetry and Tail Dependence among Multiple Variables by Using Partial Regular Vine. SDM 2014: 776-784 - [c115]Fangfang Li, Guandong Xu, Longbing Cao:
Coupled Item-Based Matrix Factorization. WISE (1) 2014: 1-14 - [e19]Longbing Cao, Yifeng Zeng, Andreas L. Symeonidis, Vladimir Gorodetsky, Jörg P. Müller, Philip S. Yu:
Agents and Data Mining Interaction - 9th International Workshop, ADMI 2013, Saint Paul, MN, USA, May 6-7, 2013, Revised Selected Papers. Lecture Notes in Computer Science 8316, Springer 2014, ISBN 978-3-642-55191-8 [contents] - [i9]Fangfang Li, Guandong Xu, Longbing Cao, Xiaozhong Fan, Zhendong Niu:
CMF: Coupled Matrix Factorization for Recommender Systems. CoRR abs/1404.7467 (2014) - [i8]Fangfang Li, Guandong Xu, Longbing Cao:
Coupled Item-based Matrix Factorization. CoRR abs/1405.6223 (2014) - 2013
- [j48]Cheng Wang, Longbing Cao, Baiqi Miao:
Optimal feature selection for sparse linear discriminant analysis and its applications in gene expression data. Comput. Stat. Data Anal. 66: 140-149 (2013) - [j47]Wanqi Yang, Yang Gao, Longbing Cao:
TRASMIL: A local anomaly detection framework based on trajectory segmentation and multi-instance learning. Comput. Vis. Image Underst. 117(10): 1273-1286 (2013) - [j46]Jian Zhou, Longbing Cao, Nan Yang:
On the convergence of some possibilistic clustering algorithms. Fuzzy Optim. Decis. Mak. 12(4): 415-432 (2013) - [j45]Dong Yu, Priyadarsi Nanda, Longbing Cao, Xiangjian He:
TCTM: an evaluation framework for architecture design on wireless sensor networks. Int. J. Sens. Networks 14(3): 168-177 (2013) - [j44]Bo Liu, Yanshan Xiao, Longbing Cao, Zhifeng Hao, Feiqi Deng:
SVDD-based outlier detection on uncertain data. Knowl. Inf. Syst. 34(3): 597-618 (2013) - [j43]Longbing Cao, Philip S. Yu, Hiroshi Motoda, Graham J. Williams:
Special issue on behavior computing. Knowl. Inf. Syst. 37(2): 245-249 (2013) - [j42]Cheng Wang, Jing Yang, Baiqi Miao, Longbing Cao:
Identity tests for high dimensional data using RMT. J. Multivar. Anal. 118: 128-137 (2013) - [j41]Frank Jiang, Daoyi Dong, Longbing Cao, Michael R. Frater:
Agent-Based Self-Adaptable Context-Aware Network Vulnerability Assessment. IEEE Trans. Netw. Serv. Manag. 10(3): 255-270 (2013) - [j40]Longbing Cao:
Combined mining: Analyzing object and pattern relations for discovering and constructing complex yet actionable patterns. WIREs Data Mining Knowl. Discov. 3(2): 140-155 (2013) - [j39]Wei Wei, Jinjiu Li, Longbing Cao, Yuming Ou, Jiahang Chen:
Effective detection of sophisticated online banking fraud on extremely imbalanced data. World Wide Web 16(4): 449-475 (2013) - [c114]Mu Li, Jinjiu Li, Yuming Ou, Ya Zhang, Dan Luo, Maninder Bahtia, Longbing Cao:
Learning Heterogeneous Coupling Relationships Between Non-IID Terms. ADMI 2013: 79-91 - [c113]Wei Li, Dazhe Zhao, Jinzhu Yang, Longbing Cao:
An approach of hierarchical concept clustering on Medical Short Text corpus. BMEI 2013: 509-518 - [c112]Xing Wang, Ji Chen, Longbing Cao, Xiangfu Meng:
The Foundation of Fuzzy Rule Interchange in the Semantic Web. Web Intelligence/IAT Workshops 2013: 280-281 - [c111]Can Wang, Zhong She, Longbing Cao:
Coupled clustering ensemble: Incorporating coupling relationships both between base clusterings and objects. ICDE 2013: 374-385 - [c110]Bin Fu, Guandong Xu, Zhihai Wang, Longbing Cao:
Leveraging Supervised Label Dependency Propagation for Multi-label Learning. ICDM 2013: 1061-1066 - [c109]Junfu Yin, Zhigang Zheng, Longbing Cao, Yin Song, Wei Wei:
Efficiently Mining Top-K High Utility Sequential Patterns. ICDM 2013: 1259-1264 - [c108]Can Wang, Zhong She, Longbing Cao:
Coupled Attribute Analysis on Numerical Data. IJCAI 2013: 1736-1742 - [c107]Liang Hu, Jian Cao, Guandong Xu, Jie Wang, Zhiping Gu, Longbing Cao:
Cross-Domain Collaborative Filtering via Bilinear Multilevel Analysis. IJCAI 2013: 2626-2632 - [c106]Wei Cao, Longbing Cao, Yin Song:
Coupled market behavior based financial crisis detection. IJCNN 2013: 1-8 - [c105]Xin Cheng, Duoqian Miao, Can Wang, Longbing Cao:
Coupled term-term relation analysis for document clustering. IJCNN 2013: 1-8 - [c104]Wei Li, Longbing Cao, Dazhe Zhao, Xia Cui, Jinzhu Yang:
CRNN: Integrating classification rules into neural network. IJCNN 2013: 1-8 - [c103]Yin Song, Longbing Cao, Junfu Yin, Cheng Wang:
Extracting discriminative features for identifying abnormal sequences in one-class mode. IJCNN 2013: 1-8 - [c102]Anna Fariha, Chowdhury Farhan Ahmed, Carson Kai-Sang Leung, S. M. Abdullah, Longbing Cao:
Mining Frequent Patterns from Human Interactions in Meetings Using Directed Acyclic Graphs. PAKDD (1) 2013: 38-49 - [c101]Yonghong Yu, Can Wang, Yang Gao, Longbing Cao, Xixi Chen:
A Coupled Clustering Approach for Items Recommendation. PAKDD (2) 2013: 365-376 - [c100]Wei Wei, Jinyan Li, Longbing Cao, Jingguang Sun, Chunming Liu, Mu Li:
Optimal Allocation of High Dimensional Assets through Canonical Vines. PAKDD (1) 2013: 366-377 - [c99]Yonghong Yu, Can Wang, Yang Gao, Longbing Cao, Qianqian Chen:
Erratum: A Coupled Clustering Approach for Items Recommendation. PAKDD (2) 2013 - [c98]Yin Song, Jian Zhang, Longbing Cao, Morgan Sangeux:
On Discovering the Correlated Relationship between Static and Dynamic Data in Clinical Gait Analysis. ECML/PKDD (3) 2013: 563-578 - [c97]Longbing Cao, Jinjiu Li, Can Wang, Philip S. Yu:
Efficient Selection of Globally Optimal Rules on Large Imbalanced Data Based on Rule Coverage Relationship Analysis. SDM 2013: 216-224 - [c96]Longbing Cao, Zhifeng Hao, Bo Liu, Yanshan Xiao, Philip S. Yu:
Robust Textual Data Streams Mining Based on Continuous Transfer Learning. SDM 2013: 731-739 - [c95]Fangfang Li, Guandong Xu, Longbing Cao, Xiaozhong Fan, Zhendong Niu:
CGMF: Coupled Group-Based Matrix Factorization for Recommender System. WISE (1) 2013: 189-198 - [c94]Liang Hu, Jian Cao, Guandong Xu, Longbing Cao, Zhiping Gu, Can Zhu:
Personalized recommendation via cross-domain triadic factorization. WWW 2013: 595-606 - [e18]Hiroshi Motoda, Zhaohui Wu, Longbing Cao, Osmar R. Zaïane, Min Yao, Wei Wang:
Advanced Data Mining and Applications, 9th International Conference, ADMA 2013, Hangzhou, China, December 14-16, 2013, Proceedings, Part I. Lecture Notes in Computer Science 8346, Springer 2013, ISBN 978-3-642-53913-8 [contents] - [e17]Hiroshi Motoda, Zhaohui Wu, Longbing Cao, Osmar R. Zaïane, Min Yao, Wei Wang:
Advanced Data Mining and Applications - 9th International Conference, ADMA 2013, Hangzhou, China, December 14-16, 2013, Proceedings, Part II. Lecture Notes in Computer Science 8347, Springer 2013, ISBN 978-3-642-53916-9 [contents] - [e16]Longbing Cao, Yifeng Zeng, Andreas L. Symeonidis, Vladimir Gorodetsky, Philip S. Yu, Munindar P. Singh:
Agents and Data Mining Interaction - 8th International Workshop, ADMI 2012, Valencia, Spain, June 4-5, 2012, Revised Selected Papers. Lecture Notes in Computer Science 7607, Springer 2013, ISBN 978-3-642-36287-3 [contents] - [e15]Jian Pei, Vincent S. Tseng, Longbing Cao, Hiroshi Motoda, Guandong Xu:
Advances in Knowledge Discovery and Data Mining, 17th Pacific-Asia Conference, PAKDD 2013, Gold Coast, Australia, April 14-17, 2013, Proceedings, Part I. Lecture Notes in Computer Science 7818, Springer 2013, ISBN 978-3-642-37452-4 [contents] - [e14]Jian Pei, Vincent S. Tseng, Longbing Cao, Hiroshi Motoda, Guandong Xu:
Advances in Knowledge Discovery and Data Mining, 17th Pacific-Asia Conference, PAKDD 2013, Gold Coast, Australia, April 14-17, 2013, Proceedings, Part II. Lecture Notes in Computer Science 7819, Springer 2013, ISBN 978-3-642-37455-5 [contents] - [e13]Jiuyong Li, Longbing Cao, Can Wang, Kay Chen Tan, Bo Liu, Jian Pei, Vincent S. Tseng:
Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2013 International Workshops: DMApps, DANTH, QIMIE, BDM, CDA, CloudSD, Gold Coast, QLD, Australia, April 14-17, 2013, Revised Selected Papers. Lecture Notes in Computer Science 7867, Springer 2013, ISBN 978-3-642-40318-7 [contents] - [e12]Longbing Cao, Hiroshi Motoda, Jaideep Srivastava, Ee-Peng Lim, Irwin King, Philip S. Yu, Wolfgang Nejdl, Guandong Xu, Gang Li, Ya Zhang:
Behavior and Social Computing, International Workshop on Behavior and Social Informatics, BSI 2013, Gold Coast, QLD, Australia, April 14-17, 2013 and International Workshop on Behavior and Social Informatics and Computing, BSIC 2013, Beijing, China, August 3-9, 2013, Revised Selected Papers. Lecture Notes in Computer Science 8178, Springer 2013, ISBN 978-3-319-04047-9 [contents] - [i7]Yin Song, Longbing Cao, Xuhui Fan, Wei Cao, Jian Zhang:
Characterizing A Database of Sequential Behaviors with Latent Dirichlet Hidden Markov Models. CoRR abs/1305.5734 (2013) - [i6]Xuhui Fan, Longbing Cao, Richard Yi Da Xu:
Copula Mixed-Membership Stochastic Blockmodel for Intra-Subgroup Correlations. CoRR abs/1306.2733 (2013) - [i5]Xuhui Fan, Longbing Cao, Richard Yi Da Xu:
Dynamic Infinite Mixed-Membership Stochastic Blockmodel. CoRR abs/1306.2999 (2013) - [i4]Xuhui Fan, Longbing Cao:
A Convergence Theorem for the Graph Shift-type Algorithms. CoRR abs/1306.3002 (2013) - [i3]Xuhui Fan, Yiling Zeng, Longbing Cao:
Non-parametric Power-law Data Clustering. CoRR abs/1306.3003 (2013) - [i2]Xuhui Fan, Richard Yi Da Xu, Longbing Cao, Yin Song:
Learning Hidden Structures with Relational Models by Adequately Involving Rich Information in A Network. CoRR abs/1310.1545 (2013) - 2012
- [b1]Longbing Cao, Philip S. Yu:
Behavior Computing - Modeling, Analysis, Mining and Decision. Springer 2012, ISBN 978-1-4471-2968-4, pp. I-XVI, 1-374 - [j38]Longbing Cao, Gerhard Weiss, Philip S. Yu:
A brief introduction to agent mining. Auton. Agents Multi Agent Syst. 25(3): 419-424 (2012) - [j37]Zhenhua Li, Ying He, Longbing Cao, Limsoon Wong, Jinyan Li:
Conservation of water molecules in protein binding interfaces. Int. J. Bioinform. Res. Appl. 8(3/4): 228-244 (2012) - [j36]Gabor Melli, Xindong Wu, Paul Beinat, Francesco Bonchi, Longbing Cao, Rong Duan, Christos Faloutsos, Rayid Ghani, Brendan Kitts, Bart Goethals, Geoffrey J. McLachlan, Jian Pei, Ashok Srivastava, Osmar R. Zaïane:
Top-10 Data Mining Case Studies. Int. J. Inf. Technol. Decis. Mak. 11(2): 389-400 (2012) - [j35]Longbing Cao, Yuming Ou, Philip S. Yu:
Coupled Behavior Analysis with Applications. IEEE Trans. Knowl. Data Eng. 24(8): 1378-1392 (2012) - [j34]Longbing Cao:
Social Security and Social Welfare Data Mining: An Overview. IEEE Trans. Syst. Man Cybern. Part C 42(6): 837-853 (2012) - [j33]Longbing Cao:
Actionable knowledge discovery and delivery. WIREs Data Mining Knowl. Discov. 2(2): 149-163 (2012) - [c93]Xuhui Fan, Longbing Cao:
A Theoretical Framework of the Graph Shift Algorithm. AAAI 2012: 2419-2420 - [c92]Zhong She, Can Wang, Longbing Cao:
CCE: A Coupled Framework of Clustering Ensembles. AAAI 2012: 2455-2456 - [c91]Wei Cao, Cheng Wang, Longbing Cao:
Trading Strategy Based Portfolio Selection for Actionable Trading Agents. ADMI 2012: 191-202 - [c90]Yunzhi Jiang, Pohsiang Tsai, Zhifeng Hao, Longbing Cao:
A novel auto-parameters selection process for image segmentation. IEEE Congress on Evolutionary Computation 2012: 1-7 - [c89]Lin Zhu, Longbing Cao, Jie Yang:
Multiobjective evolutionary algorithm-based soft subspace clustering. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c88]Xuhui Fan, Lin Zhu, Longbing Cao, Xia Cui, Yew-Soon Ong:
Maximum margin clustering on evolutionary data. CIKM 2012: 625-634 - [c87]Wei Wei, Xuhui Fan, Jinyan Li, Longbing Cao:
Model the complex dependence structures of financial variables by using canonical vine. CIKM 2012: 1382-1391 - [c86]Yin Song, Longbing Cao:
Graph-based coupled behavior analysis: A case study on detecting collaborative manipulations in stock markets. IJCNN 2012: 1-8 - [c85]Junfu Yin, Zhigang Zheng, Longbing Cao:
USpan: an efficient algorithm for mining high utility sequential patterns. KDD 2012: 660-668 - [c84]Yin Song, Longbing Cao, Xindong Wu, Gang Wei, Wu Ye, Wei Ding:
Coupled behavior analysis for capturing coupling relationships in group-based market manipulations. KDD 2012: 976-984 - [c83]Can Wang, Mingchun Wang, Zhong She, Longbing Cao:
CD: A Coupled Discretization Algorithm. PAKDD (2) 2012: 407-418 - [e11]Longbing Cao, Ana L. C. Bazzan, Andreas L. Symeonidis, Vladimir Gorodetsky, Gerhard Weiss, Philip S. Yu:
Agents and Data Mining Interaction - 7th International Workshop on Agents and Data Mining Interation, ADMI 2011, Taipei, Taiwan, May 2-6, 2011, Revised Selected Papers. Lecture Notes in Computer Science 7103, Springer 2012, ISBN 978-3-642-27608-8 [contents] - [e10]Longbing Cao, Joshua Zhexue Huang, James Bailey, Yun Sing Koh, Jun Luo:
New Frontiers in Applied Data Mining - PAKDD 2011 International Workshops, Shenzhen, China, May 24-27, 2011, Revised Selected Papers. Lecture Notes in Computer Science 7104, Springer 2012, ISBN 978-3-642-28319-2 [contents] - 2011
- [j32]Tao Yang, Vojislav Kecman, Longbing Cao, Chengqi Zhang, Joshua Zhexue Huang:
Margin-based ensemble classifier for protein fold recognition. Expert Syst. Appl. 38(10): 12348-12355 (2011) - [j31]Longbing Cao, Huaifeng Zhang, Yanchang Zhao, Dan Luo, Chengqi Zhang:
Combined Mining: Discovering Informative Knowledge in Complex Data. IEEE Trans. Syst. Man Cybern. Part B 41(3): 699-712 (2011) - [c82]Chayapol Moemeng, Can Wang, Longbing Cao:
Obtaining an Optimal MAS Configuration for Agent-Enhanced Mining Using Constraint Optimization. ADMI 2011: 46-57 - [c81]Xiangjun Dong, Zhigang Zheng, Longbing Cao, Yanchang Zhao, Chengqi Zhang, Jinjiu Li, Wei Wei, Yuming Ou:
e-NSP: efficient negative sequential pattern mining based on identified positive patterns without database rescanning. CIKM 2011: 825-830 - [c80]Can Wang, Longbing Cao, Mingchun Wang, Jinjiu Li, Wei Wei, Yuming Ou:
Coupled nominal similarity in unsupervised learning. CIKM 2011: 973-978 - [c79]Lin Zhu, Longbing Cao, Jie Yang:
Soft subspace clustering with competitive agglomeration. FUZZ-IEEE 2011: 691-698 - [c78]Yanshan Xiao, Bo Liu, Jie Yin, Longbing Cao, Chengqi Zhang, Zhifeng Hao:
Similarity-Based Approach for Positive and Unlabeled Learning. IJCAI 2011: 1577-1582 - [c77]Bo Liu, Yanshan Xiao, Longbing Cao, Philip S. Yu:
One-Class-Based Uncertain Data Stream Learning. SDM 2011: 992-1003 - [e9]Olivier Boissier, Jeffrey Bradshaw, Longbing Cao, Klaus Fischer, Mohand-Said Hacid:
Proceedings of the 2011 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2011, Campus Scientifique de la Doua, Lyon, France, August 22-27, 2011. IEEE Computer Society 2011 [contents] - [e8]Joshua Zhexue Huang, Longbing Cao, Jaideep Srivastava:
Advances in Knowledge Discovery and Data Mining - 15th Pacific-Asia Conference, PAKDD 2011, Shenzhen, China, May 24-27, 2011, Proceedings, Part I. Lecture Notes in Computer Science 6634, Springer 2011, ISBN 978-3-642-20840-9 [contents] - [e7]Joshua Zhexue Huang, Longbing Cao, Jaideep Srivastava:
Advances in Knowledge Discovery and Data Mining - 15th Pacific-Asia Conference, PAKDD 2011, Shenzhen, China, May 24-27, 2011, Proceedings, Part II. Lecture Notes in Computer Science 6635, Springer 2011, ISBN 978-3-642-20846-1 [contents] - 2010
- [j30]Yanshan Xiao, Bo Liu, Dan Luo, Longbing Cao, Feiqi Deng, Zhifeng Hao:
Multi-agent system for customer relationship management with SVMs tool. Int. J. Intell. Inf. Database Syst. 4(2): 121-136 (2010) - [j29]Longbing Cao:
In-depth behavior understanding and use: The behavior informatics approach. Inf. Sci. 180(17): 3067-3085 (2010) - [j28]Longbing Cao:
Domain-Driven Data Mining: Challenges and Prospects. IEEE Trans. Knowl. Data Eng. 22(6): 755-769 (2010) - [j27]Longbing Cao, Yanchang Zhao, Huaifeng Zhang, Dan Luo, Chengqi Zhang, Eun K. Park:
Flexible Frameworks for Actionable Knowledge Discovery. IEEE Trans. Knowl. Data Eng. 22(9): 1299-1312 (2010) - [c76]Chayapol Moemeng, Xinhua Zhu, Longbing Cao:
Integrating Workflow into Agent-Based Distributed Data Mining Systems. ADMI 2010: 4-15 - [c75]Bo Liu, Yanshan Xiao, Longbing Cao, Philip S. Yu:
Orientation distance-based discriminative feature extraction for multi-class classification. CIKM 2010: 909-918 - [c74]Yanshan Xiao, Bo Liu, Longbing Cao:
K-farthest-neighbors-based concept boundary determination for support vector data description. CIKM 2010: 1701-1704 - [c73]Bo Liu, Jie Yin, Yanshan Xiao, Longbing Cao, Philip S. Yu:
Exploiting Local Data Uncertainty to Boost Global Outlier Detection. ICDM 2010: 304-313 - [c72]Yanshan Xiao, Bo Liu, Longbing Cao, Jie Yin, Xindong Wu:
SMILE: A Similarity-Based Approach for Multiple Instance Learning. ICDM 2010: 589-598 - [c71]Yanchang Zhao, Hans Bohlscheid, Shanshan Wu, Longbing Cao:
Less Effort, More Outcomes: Optimising Debt Recovery with Decision Trees. ICDM Workshops 2010: 655-660 - [c70]Bo Liu, Yanshan Xiao, Longbing Cao, Philip S. Yu:
Vote-Based LELC for Positive and Unlabeled Textual Data Streams. ICDM Workshops 2010: 951-958 - [c69]Chayapol Moemeng, Xinhua Zhu, Longbing Cao, Jiahang Chen:
i-Analyst: An Agent-Based Distributed Data Mining Platform. ICDM Workshops 2010: 1404-1406 - [c68]Jia-Yi Feng, Mingchun Wang, Can Wang, Longbing Cao:
Enhanced co-occurrence distances for categorical data in unsupervised learning. ICMLC 2010: 2071-2078 - [c67]Tao Yang, Vojislav Kecman, Longbing Cao, Chengqi Zhang:
Testing Adaptive Local Hyperplane for multi-class classification by double cross-validation. IJCNN 2010: 1-5 - [c66]Longbing Cao, Yuming Ou, Philip S. Yu, Gang Wei:
Detecting abnormal coupled sequences and sequence changes in group-based manipulative trading behaviors. KDD 2010: 85-94 - [c65]Tao Yang, Vojislav Kecman, Longbing Cao, Chengqi Zhang:
Combining Support Vector Machines and the t-statistic for Gene Selection in DNA Microarray Data Analysis. PAKDD (2) 2010: 55-62 - [c64]Tao Yang, Longbing Cao, Chengqi Zhang:
A Novel Prototype Reduction Method for the K-Nearest Neighbor Algorithm with K >= 1. PAKDD (2) 2010: 89-100 - [c63]Zhigang Zheng, Yanchang Zhao, Ziye Zuo, Longbing Cao:
An Efficient GA-Based Algorithm for Mining Negative Sequential Patterns. PAKDD (1) 2010: 262-273 - [c62]Yong Yang, Longbing Cao, Li Liu:
Time-Sensitive Feature Mining for Temporal Sequence Classification. PRICAI 2010: 315-326 - [e6]Longbing Cao, Yong Feng, Jiang Zhong:
Advanced Data Mining and Applications - 6th International Conference, ADMA 2010, Chongqing, China, November 19-21, 2010, Proceedings, Part I. Lecture Notes in Computer Science 6440, Springer 2010, ISBN 978-3-642-17315-8 [contents] - [e5]Longbing Cao, Jiang Zhong, Yong Feng:
Advanced Data Mining and Applications - 6th International Conference, ADMA 2010, Chongqing, China, November 19-21, 2010, Proceedings, Part II. Lecture Notes in Computer Science 6441, Springer 2010, ISBN 978-3-642-17312-7 [contents] - [e4]Longbing Cao, Ana L. C. Bazzan, Vladimir Gorodetsky, Pericles A. Mitkas, Gerhard Weiss, Philip S. Yu:
Agents and Data Mining Interaction, 6th International Workshop on Agents and Data Mining Interaction, ADMI 2010, Toronto, ON, Canada, May 11, 2010, Revised Selected Papers. Lecture Notes in Computer Science 5980, Springer 2010, ISBN 978-3-642-15419-5 [contents]
2000 – 2009
- 2009
- [j26]Longbing Cao, Philip S. Yu:
Behavior Informatics: An Informatics Perspective for Behavior Studies. IEEE Intell. Informatics Bull. 10(1): 6-11 (2009) - [j25]Yuming Ou, Longbing Cao, Chengqi Zhang:
Adaptive Anomaly Detection of Coupled Activity Sequences. IEEE Intell. Informatics Bull. 10(1): 12-16 (2009) - [j24]Longbing Cao, Vladimir Gorodetsky, Pericles A. Mitkas:
Guest Editors' Introduction: Agents and Data Mining. IEEE Intell. Syst. 24(3): 14-15 (2009) - [j23]Longbing Cao, Vladimir Gorodetsky, Pericles A. Mitkas:
Agent Mining: The Synergy of Agents and Data Mining. IEEE Intell. Syst. 24(3): 64-72 (2009) - [j22]Huaifeng Zhang, Yanchang Zhao, Longbing Cao, Chengqi Zhang, Hans Bohlscheid:
Customer Activity Sequence Classification for Debt Prevention in Social Security. J. Comput. Sci. Technol. 24(6): 1000-1009 (2009) - [j21]Longbing Cao, Tony He:
Developing actionable trading agents. Knowl. Inf. Syst. 18(2): 183-198 (2009) - [j20]Pohsiang Tsai, Longbing Cao, Tom Hintz, Tony Jan:
A bi-modal face recognition framework integrating facial expression with facial appearance. Pattern Recognit. Lett. 30(12): 1096-1109 (2009) - [j19]Longbing Cao, Ruwei Dai, Mengchu Zhou:
Metasynthesis: M-Space, M-Interaction, and M-Computing for Open Complex Giant Systems. IEEE Trans. Syst. Man Cybern. Part A 39(5): 1007-1021 (2009) - [c61]Longbing Cao:
Data Mining in Financial Markets. ADMA 2009: 4 - [c60]Longbing Cao, Dan Luo, Chengqi Zhang:
Ubiquitous Intelligence in Agent Mining. ADMI 2009: 23-35 - [c59]Zhigang Zheng, Yanchang Zhao, Ziye Zuo, Longbing Cao:
Negative-GSP: An Efficient Method for Mining Negative Sequential Patterns. AusDM 2009: 63-68 - [c58]Tiong-Thye Goh, Siddhartha Bose, Wee Keong Ng, Longbing Cao, Vincent C. S. Lee:
Editorial to the Proceedings of mobile technologies in enterprise computing systems workshop (MTECS 2009). EDOCW 2009: 138-139 - [c57]Yanshan Xiao, Bo Liu, Longbing Cao, Xindong Wu, Chengqi Zhang, Zhifeng Hao, Fengzhao Yang, Jie Cao:
Multi-sphere Support Vector Data Description for Outliers Detection on Multi-distribution Data. ICDM Workshops 2009: 82-87 - [c56]Gang Zhao, Yun Xiong, Longbing Cao, Dan Luo, Xuchun Su, Yangyong Zhu:
A Cost-Effective LSH Filter for Fast Pairwise Mining. ICDM 2009: 1088-1093 - [c55]Shanshan Wu, Yanchang Zhao, Huaifeng Zhang, Chengqi Zhang, Longbing Cao, Hans Bohlscheid:
Debt Detection in Social Security by Adaptive Sequence Classification. KSEM 2009: 192-203 - [c54]Yanchang Zhao, Huaifeng Zhang, Longbing Cao, Chengqi Zhang, Hans Bohlscheid:
Mining Both Positive and Negative Impact-Oriented Sequential Rules from Transactional Data. PAKDD 2009: 656-663 - [c53]Yanchang Zhao, Huaifeng Zhang, Shanshan Wu, Jian Pei, Longbing Cao, Chengqi Zhang, Hans Bohlscheid:
Debt Detection in Social Security by Sequence Classification Using Both Positive and Negative Patterns. ECML/PKDD (2) 2009: 648-663 - [c52]Pohsiang Tsai, Tich Phuoc Tran, Longbing Cao:
Expression-invariant Facial Identification. SMC 2009: 5151-5155 - [p1]Longbing Cao:
Introduction to Agent Mining Interaction and Integration. Data Mining and Multi-agent Integration 2009: 3-36 - [e3]Longbing Cao:
Data Mining and Multi-agent Integration. Springer 2009, ISBN 978-1-4419-0521-5 [contents] - [e2]Longbing Cao, Vladimir Gorodetsky, Jiming Liu, Gerhard Weiss, Philip S. Yu:
Agents and Data Mining Interaction, 4th International Workshop, ADMI 2009, Budapest, Hungary, May 10-15, 2009, Revised Selected Papers. Lecture Notes in Computer Science 5680, Springer 2009, ISBN 978-3-642-03602-6 [contents] - [i1]Tich Phuoc Tran, Longbing Cao, Dat Tran, Cuong Duc Nguyen:
Novel Intrusion Detection using Probabilistic Neural Network and Adaptive Boosting. CoRR abs/0911.0485 (2009) - 2008
- [j18]Longbing Cao, David Taniar:
Book Review: Computational Methods of Feature Selection. IEEE Intell. Informatics Bull. 9(1): 39-40 (2008) - [j17]Yanshan Xiao, Bo Liu, Longbing Cao:
A Chinese question classification using one-vs-one method as a learning tool. Int. J. Intell. Inf. Database Syst. 2(4): 446-459 (2008) - [j16]Li Lin, Longbing Cao:
Mining in-depth patterns in stock market. Int. J. Intell. Syst. Technol. Appl. 4(3/4): 225-238 (2008) - [j15]Wanli Chen, Longbing Cao, Zhe Qin:
An integrated investment decision-support framework analysing and synthesising multidimensional market dynamics. Int. J. Intell. Syst. Technol. Appl. 4(3/4): 239-253 (2008) - [j14]Longbing Cao, Yanchang Zhao, Chengqi Zhang, Huaifeng Zhang:
Activity Mining: from Activities to Actions. Int. J. Inf. Technol. Decis. Mak. 7(2): 259-273 (2008) - [j13]Longbing Cao:
Integrating Agent, Service and Organizational Computing. Int. J. Softw. Eng. Knowl. Eng. 18(5): 573-596 (2008) - [j12]Longbing Cao, Ngoc Thanh Nguyen:
Knowledge Processing in Intelligent Systems. J. Univers. Comput. Sci. 14(14): 2255 (2008) - [j11]Longbing Cao, Ngoc Thanh Nguyen:
Intelligence Metasynthesis and Knowledge Processing in Intelligent Systems. J. Univers. Comput. Sci. 14(14): 2256-2262 (2008) - [j10]Longbing Cao, Yuming Ou:
Market Microstructure Patterns Powering Trading and Surveillance Agents. J. Univers. Comput. Sci. 14(14): 2288-2308 (2008) - [j9]Longbing Cao, Yanchang Zhao, Chengqi Zhang:
Mining Impact-Targeted Activity Patterns in Imbalanced Data. IEEE Trans. Knowl. Data Eng. 20(8): 1053-1066 (2008) - [j8]Longbing Cao, Chengqi Zhang, MengChu Zhou:
Engineering Open Complex Agent Systems: A Case Study. IEEE Trans. Syst. Man Cybern. Part C 38(4): 483-496 (2008) - [c51]Yanchang Zhao, Huaifeng Zhang, Longbing Cao, Chengqi Zhang, Hans Bohlscheid:
Combined Pattern Mining: From Learned Rules to Actionable Knowledge. Australasian Conference on Artificial Intelligence 2008: 393-403 - [c50]Longbing Cao, Ruwei Dai, Vladimir I. Gorodetski:
Message from the EOCS-MCP 2008 Workshop Organizers. COMPSAC 2008: 859 - [c49]Longbing Cao, Ruwei Dai, Vladimir I. Gorodetski:
EOCS-MCP 2008 Workshop Organization. COMPSAC 2008: 860-861 - [c48]Longbing Cao:
Metasynthetic Computing for Solving Open Complex Problems. COMPSAC 2008: 896-901 - [c47]Peerapol Moemeng, Longbing Cao, Chengqi Zhang:
F-TRADE 3.0: An Agent-Based Integrated Framework for Data Mining Experiments. Web Intelligence/IAT Workshops 2008: 612-615 - [c46]Chao Luo, Yanchang Zhao, Longbing Cao, Yuming Ou, Chengqi Zhang:
Exception Mining on Multiple Time Series in Stock Market. Web Intelligence/IAT Workshops 2008: 690-693 - [c45]Longbing Cao:
Domain Driven Data Mining (D3M). ICDM Workshops 2008: 74-76 - [c44]Longbing Cao:
Behavior Informatics and Analytics: Let Behavior Talk. ICDM Workshops 2008: 87-96 - [c43]Bo Liu, Longbing Cao, Philip S. Yu, Chengqi Zhang:
Multi-Space-Mapped SVMs for Multi-class Classification. ICDM 2008: 911-916 - [c42]Xuekan Qiu, Shuqiang Jiang, Huiying Liu, Qingming Huang, Longbing Cao:
Spatial-temporal attention analysis for home video. ICME 2008: 1517-1520 - [c41]Yanshan Xiao, Bo Liu, Dan Luo, Longbing Cao:
Multi-agent System for Custom Relationship Management with SVMs Tool. KES-AMSTA 2008: 333-340 - [c40]Longbing Cao, Dan Luo, Yanshan Xiao, Zhigang Zheng:
Agent Collaboration for Multiple Trading Strategy Integration. KES-AMSTA 2008: 361-370 - [c39]Huaifeng Zhang, Yanchang Zhao, Longbing Cao, Chengqi Zhang:
Combined Association Rule Mining. PAKDD 2008: 1069-1074 - [c38]Yuming Ou, Longbing Cao, Chao Luo, Chengqi Zhang:
Domain-Driven Local Exceptional Pattern Mining for Detecting Stock Price Manipulation. PRICAI 2008: 849-858 - [c37]Chao Luo, Yanchang Zhao, Longbing Cao, Yuming Ou, Li Liu:
Outlier Mining on Multiple Time Series Data in Stock Market. PRICAI 2008: 1010-1015 - [c36]Yanchang Zhao, Huaifeng Zhang, Longbing Cao, Chengqi Zhang, Hans Bohlscheid:
Efficient Mining of Event-Oriented Negative Sequential Rules. Web Intelligence 2008: 336-342 - [c35]Yuming Ou, Longbing Cao, Chao Luo, Li Liu:
Mining Exceptional Activity Patterns in Microstructure Data. Web Intelligence 2008: 884-887 - 2007
- [j7]Longbing Cao, Chengqi Zhang, Qiang Yang, David A. Bell, Michail Vlachos, Bahar Taneri, Eamonn J. Keogh, Philip S. Yu, Ning Zhong, Mafruz Zaman Ashrafi, David Taniar, Eugene Dubossarsky, Warwick Graco:
Domain-Driven, Actionable Knowledge Discovery. IEEE Intell. Syst. 22(4): 78-88 (2007) - [j6]Longbing Cao, Dan Luo, Chengqi Zhang:
Knowledge actionability: satisfying technical and business interestingness. Int. J. Bus. Intell. Data Min. 2(4): 496-514 (2007) - [j5]Longbing Cao, Chengqi Zhang:
The Evolution of KDD: towards Domain-Driven Data Mining. Int. J. Pattern Recognit. Artif. Intell. 21(4): 677-692 (2007) - [j4]Longbing Cao, Chengqi Zhang, Yanchang Zhao, Philip S. Yu, Graham Williams:
DDDM2007: Domain Driven Data Mining. SIGKDD Explor. 9(2): 84-86 (2007) - [c34]Longbing Cao, Chao Luo, Chengqi Zhang:
Agent-Mining Interaction: An Emerging Area. AIS-ADM 2007: 60-73 - [c33]Longbing Cao, Chengqi Zhang:
F-trade: an agent-mining symbiont for financial services. AAMAS 2007: 262 - [c32]Huaifeng Zhang, Yanchang Zhao, Longbing Cao, Chengqi Zhang:
Class Association Rule Mining with Multiple Imbalanced Attributes. Australian Conference on Artificial Intelligence 2007: 827-831 - [c31]Longbing Cao, Chao Luo, Chengqi Zhang:
Developing Actionable Trading Strategies for Trading Agents. IAT 2007: 72-75 - [c30]Longbing Cao:
Multi-strategy Integration for Actionable Trading Agents. Web Intelligence/IAT Workshops 2007: 487-490 - [c29]Yuming Ou, Longbing Cao, Ting Yu, Chengqi Zhang:
Detecting Turning Points of Trading Price and Return Volatility for Market Surveillance Agents. Web Intelligence/IAT Workshops 2007: 491-494 - [c28]Dan Luo, Longbing Cao, Jiarui Ni, Li Liu:
Building Agent Service Oriented Multi-Agent Systems. KES-AMSTA 2007: 11-20 - [c27]Jiarui Ni, Longbing Cao, Chengqi Zhang:
Evolutionary Optimization of Trading Strategies. DMBiz@PAKDD 2007: 11-24 - [c26]Longbing Cao, Yanchang Zhao, Fernando Figueiredo, Yuming Ou, Dan Luo:
Mining High Impact Exceptional Behavior Patterns. PAKDD Workshops 2007: 56-63 - [c25]Dan Luo, Longbing Cao, Chao Luo, Chengqi Zhang, Weiyuan Wang:
Towards Business Interestingness in Actionable Knowledge Discovery. DMBiz@PAKDD 2007: 99-109 - [e1]Vladimir Gorodetsky, Chengqi Zhang, Victor A. Skormin, Longbing Cao:
Autonomous Intelligent Systems: Multi-Agents and Data Mining, Second International Workshop, AIS-ADM 2007, St. Petersburg, Russia, June 3-5, 2007, Proceedings. Lecture Notes in Computer Science 4476, Springer 2007, ISBN 978-3-540-72838-2 [contents] - 2006
- [j3]Longbing Cao, Chengqi Zhang:
Domain-Driven Data Mining: A Practical Methodology. Int. J. Data Warehous. Min. 2(4): 49-65 (2006) - [j2]Longbing Cao, Chengqi Zhang, Jiming Liu:
Ontology-based integration of business intelligence. Web Intell. Agent Syst. 4(3): 313-325 (2006) - [c24]Longbing Cao:
Activity Mining: Challenges and Prospects. ADMA 2006: 582-593 - [c23]Chengqi Zhang, Longbing Cao:
Domain-Driven Data Mining: Methodologies and Applications. AMT 2006: 13-16 - [c22]Jiarui Ni, Longbing Cao, Chengqi Zhang:
Agent Services-Oriented Architectural Design of a Framework for Artificial Stock Markets. AMT 2006: 396-399 - [c21]Longbing Cao, Jiarui Ni, Dan Luo:
Ontological Engineering in Data Warehousing. APWeb 2006: 923-929 - [c20]Yanchang Zhao, Longbing Cao, Yvonne Morrow, Yuming Ou, Jiarui Ni, Chengqi Zhang:
Discovering Debtor Patterns of Centrelink Customers. AusDM 2006: 135-144 - [c19]Longbing Cao, Chao Luo, Jiarui Ni, Dan Luo, Chengqi Zhang:
Stock Data Mining through Fuzzy Genetic Algorithms. JCIS 2006 - [c18]Longbing Cao, Chengqi Zhang:
Domain-Driven Actionable Knowledge Discovery in the Real World. PAKDD 2006: 821-830 - [c17]Longbing Cao, Dan Luo, Chengqi Zhang:
Fuzzy Genetic Algorithms for Pairs Mining. PRICAI 2006: 711-720 - [c16]Longbing Cao, Chengqi Zhang, Dan Luo, Ruwei Dai:
Intelligence Metasynthesis in Building Business Intelligence Systems. WImBI 2006: 454-470 - 2005
- [c15]Chengqi Zhang, Zili Zhang, Longbing Cao:
Agents and Data Mining: Mutual Enhancement by Integration. AIS-ADM 2005: 50-61 - [c14]Li Lin, Longbing Cao, Chengqi Zhang:
The Fish-eye Visualization of Foreign Currency Exchange Data Streams. APVIS 2005: 91-96 - [c13]Li Lin, Longbing Cao, Chengqi Zhang:
The Visualization of Large Database in Stock Market. Databases and Applications 2005: 163-166 - [c12]Li Lin, Longbing Cao, Chengqi Zhang:
Genetic Algorithms for Robust Optimization in Financial Applications. Computational Intelligence 2005: 387-391 - [c11]Longbing Cao, Chengqi Zhang, Jiarui Ni:
Agent Services-Orinted Architectural Design of Open Complex Agent Systems. IAT 2005: 120-123 - 2004
- [c10]Longbing Cao, Jiarui Ni, Jiaqi Wang, Chengqi Zhang:
Agent Services-Driven Plug-and-Play in F-TRADE. Australian Conference on Artificial Intelligence 2004: 917-922 - [c9]Longbing Cao, Dan Luo, Chao Luo, Li Liu:
Ontology Transformation in Multiple Domains. Australian Conference on Artificial Intelligence 2004: 985-990 - [c8]Longbing Cao, Chengqi Zhang, Dan Luo, Wanli Chen, Neda Zamani:
Integrative Early Requirements Analysis for Agent-Based Systems. HIS 2004: 118-123 - [c7]Longbing Cao, Jiaqi Wang, Li Lin, Chengqi Zhang:
Agent Services-Based Infrastructure for Online Assessment of Trading Strategies. IAT 2004: 345-348 - [c6]Longbing Cao, Chao Luo, Dan Luo, Li Liu:
Ontology Services-Based Information Integration in Mining Telecom Business Intelligence. PRICAI 2004: 85-94 - [c5]Longbing Cao, Chao Luo, Dan Luo, Chengqi Zhang:
Integration of Business Intelligence Based on Three-Level Ontology Services. Web Intelligence 2004: 17-23 - 2003
- [j1]Longbing Cao, Ruwei Dai:
Agent-Oriented Metasynthetic Engineering for Decision Making. Int. J. Inf. Technol. Decis. Mak. 2(2): 197-215 (2003) - [c4]Longbing Cao, Dan Luo, Chao Luo, Chengqi Zhang:
Systematic Engineering in Designing Architecture of Telecommunications Business Intelligence System. HIS 2003: 1084-1093 - [c3]Chunsheng Li, Chengqi Zhang, Longbing Cao:
Theoretical Evaluation of Ring-Based Architectural Model for Middle Agents in Agent-Based System. ISMIS 2003: 603-607 - [c2]Longbing Cao, Chunsheng Li, Chengqi Zhang, Ruwei Dai:
Open Giant Intelligent Information Systems and Its Agent-Oriented Analysis and Design. SEKE 2003: 85-89 - [c1]Longbing Cao, Chunsheng Li, Chengqi Zhang, Ruwei Dai:
Open Giant Intelligent Information Systems and Its Multiagent-Oriented System Design. Software Engineering Research and Practice 2003: 816-822
Coauthor Index
[j157] [e20] [j32] [j31] [c81] [c78] [j27] [c67] [c65] [c64] [j25] [j22] [c60] [c57] [c55] [c54] [c53] [j14] [j9] [j8] [c51] [c47] [c46] [c43] [c39] [c38] [c36] [j7] [j6] [j5] [j4] [c34] [c33] [c32] [c31] [c29] [c27] [c25] [e1] [j3] [j2] [c23] [c22] [c20] [c19] [c18] [c17] [c16] [c15] [c14] [c13] [c12] [c11] [c10] [c8] [c7] [c5] [c4] [c3] [c2] [c1]
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