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ORCIDCharu C. Aggarwal
Charu Aggarwal 0001
Person information
- affiliation: IBM T. J. Watson Research Center, Yorktown, NY, USA
- affiliation: Indian Institute of Technology Kanpur, Department of Computer Science and Engineering, India
Other persons with the same name
- Charu Aggarwal 0002 — University of Delhi, Department of Computer Science, India
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2020 – today
- 2025
[j114]Zahra Zamanzadeh Darban, Geoffrey I. Webb, Shirui Pan, Charu Aggarwal, Mahsa Salehi:
Deep Learning for Time Series Anomaly Detection: A Survey. ACM Comput. Surv. 57(1): 15:1-15:42 (2025)- [j113]Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Shan Xue, Chuan Zhou, Charu Aggarwal, Hao Peng, Wenbin Hu, Edwin R. Hancock, Pietro Liò:
State of the Art and Potentialities of Graph-level Learning. ACM Comput. Surv. 57(2): 28:1-28:40 (2025) - [j112]Zahra Zamanzadeh Darban
, Geoffrey I. Webb, Shirui Pan, Charu C. Aggarwal, Mahsa Salehi:
CARLA: Self-supervised contrastive representation learning for time series anomaly detection. Pattern Recognit. 157: 110874 (2025) - 2024
- [j111]Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Lingfei Wu, Charu Aggarwal, Chang-Tien Lu:
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural Networks. ACM Comput. Surv. 56(5): 126:1-126:42 (2024) - [j110]Ke Sun, Feng Xia, Jiaying Liu, Bo Xu, Vidya Saikrishna, Charu C. Aggarwal:
Attributed Graph Force Learning. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4502-4515 (2024) - [j109]Ciyuan Peng, Tao Tang, Qiuyang Yin, Xiaomei Bai, Suryani Lim, Charu C. Aggarwal:
Physics-Informed Explainable Continual Learning on Graphs. IEEE Trans. Neural Networks Learn. Syst. 35(9): 11761-11772 (2024) - [c254]Yuying Zhao, Yu Wang, Yi Zhang, Pamela J. Wisniewski, Charu C. Aggarwal, Tyler Derr:
Leveraging Opposite Gender Interaction Ratio as a Path towards Fairness in Online Dating Recommendations Based on User Sexual Orientation. AAAI 2024: 22547-22555 - [c253]Charu C. Aggarwal:
Ensembles for Outlier Detection and Evaluation. CIKM 2024: 1 - [c252]Pengfei He, Han Xu, Jie Ren, Yingqian Cui, Shenglai Zeng, Hui Liu, Charu C. Aggarwal, Jiliang Tang:
Sharpness-Aware Data Poisoning Attack. ICLR 2024 - [c251]Teng Xiao, Huaisheng Zhu, Zhiwei Zhang, Zhimeng Guo, Charu C. Aggarwal, Suhang Wang, Vasant G. Honavar:
Efficient Contrastive Learning for Fast and Accurate Inference on Graphs. ICML 2024 - [c250]Long Vu, Peter Kirchner, Charu C. Aggarwal, Horst Samulowitz:
Instance-Level Metalearning for Outlier Detection. IJCAI 2024: 2379-2387 - [c249]Wangyang Ying, Dongjie Wang, Xuanming Hu, Yuanchun Zhou, Charu C. Aggarwal, Yanjie Fu:
Unsupervised Generative Feature Transformation via Graph Contrastive Pre-training and Multi-objective Fine-tuning. KDD 2024: 3966-3976 - [c248]Saket Sathe, Charu Aggarwal, Horst Samulowitz, Deepak S. Turaga:
Feature-Engineered Random Forests. SDM 2024: 100-108 - [i61]Hongliang Chi, Wei Jin, Charu Aggarwal, Yao Ma:
Precedence-Constrained Winter Value for Effective Graph Data Valuation. CoRR abs/2402.01943 (2024) - [i60]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) - [i59]Yuying Zhao, Yu Wang, Yi Zhang, Pamela J. Wisniewski, Charu C. Aggarwal, Tyler Derr:
Leveraging Opposite Gender Interaction Ratio as a Path towards Fairness in Online Dating Recommendations Based on User Sexual Orientation. CoRR abs/2402.12541 (2024) - [i58]Zaitian Wang, Pengfei Wang, Kunpeng Liu, Pengyang Wang, Yanjie Fu, Chang-Tien Lu, Charu C. Aggarwal, Jian Pei, Yuanchun Zhou:
A Comprehensive Survey on Data Augmentation. CoRR abs/2405.09591 (2024) - [i57]Wangyang Ying, Dongjie Wang, Xuanming Hu, Yuanchun Zhou, Charu C. Aggarwal, Yanjie Fu:
Unsupervised Generative Feature Transformation via Graph Contrastive Pre-training and Multi-objective Fine-tuning. CoRR abs/2405.16879 (2024) - [i56]Xueqi Cheng, Yu Wang, Yunchao Liu, Yuying Zhao, Charu C. Aggarwal, Tyler Derr:
Edge Classification on Graphs: New Directions in Topological Imbalance. CoRR abs/2406.11685 (2024) - [i55]Hezhe Qiao, Hanghang Tong, Bo An, Irwin King, Charu C. Aggarwal, Guansong Pang:
Deep Graph Anomaly Detection: A Survey and New Perspectives. CoRR abs/2409.09957 (2024) - [i54]Sharmishtha Dutta, Alex Gittens, Mohammed J. Zaki, Charu C. Aggarwal:
Replacing Paths with Connection-Biased Attention for Knowledge Graph Completion. CoRR abs/2410.00876 (2024) - 2023
- [j108]Falih Gozi Febrinanto, Feng Xia, Kristen Moore, Chandra Thapa, Charu Aggarwal:
Graph Lifelong Learning: A Survey. IEEE Comput. Intell. Mag. 18(1): 32-51 (2023) - [j107]Jaykumar Kakkad, Jaspal Jannu, Kartik Sharma, Charu Aggarwal, Sourav Medya:
A Survey on Explainability of Graph Neural Networks. IEEE Data Eng. Bull. 46(2): 35-63 (2023) - [j106]Yiqi Wang, Yao Ma, Wei Jin, Chaozhuo Li, Charu Aggarwal, Jiliang Tang:
Customized Graph Nerual Networks. IEEE Data Eng. Bull. 46(2): 108-125 (2023) - [j105]Feng Xia, Leman Akoglu, Charu Aggarwal, Huan Liu:
Deep Anomaly Analytics: Advancing the Frontier of Anomaly Detection. IEEE Intell. Syst. 38(2): 32-35 (2023) - [j104]Jing Ren, Feng Xia, Ivan Lee, Azadeh Noori Hoshyar, Charu C. Aggarwal:
Graph Learning for Anomaly Analytics: Algorithms, Applications, and Challenges. ACM Trans. Intell. Syst. Technol. 14(2): 28:1-28:29 (2023) - [j103]Kunpeng Liu, Yanjie Fu, Le Wu, Xiaolin Li, Charu Aggarwal, Hui Xiong:
Automated Feature Selection: A Reinforcement Learning Perspective. IEEE Trans. Knowl. Data Eng. 35(3): 2272-2284 (2023) - [j102]Jianxin Li, Lifang He, Hao Peng, Peng Cui, Charu C. Aggarwal, Philip S. Yu:
Guest Editorial Introduction to the Special Issue on Anomaly Detection in Emerging Data-Driven Applications: Theory, Algorithms, and Applications. IEEE Trans. Knowl. Data Eng. 35(12): 11982-11983 (2023) - [c247]Harry Shomer, Yao Ma, Juanhui Li, Bo Wu, Charu C. Aggarwal, Jiliang Tang:
Distance-Based Propagation for Efficient Knowledge Graph Reasoning. EMNLP 2023: 14692-14707 - [c246]Wenqi Fan, Han Xu, Wei Jin, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Qing Li, Jiliang Tang, Jianping Wang, Charu C. Aggarwal:
Jointly Attacking Graph Neural Network and its Explanations. ICDE 2023: 654-667 - [c245]Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu C. Aggarwal, Jiliang Tang:
Towards Label Position Bias in Graph Neural Networks. NeurIPS 2023 - [i53]Zhenyu Yang, Ge Zhang, Jia Wu, Jian Yang, Quan Z. Sheng, Shan Xue, Chuan Zhou, Charu C. Aggarwal, Hao Peng, Wenbin Hu, Edwin R. Hancock, Pietro Liò:
A Comprehensive Survey of Graph-level Learning. CoRR abs/2301.05860 (2023) - [i52]Zitai Qiu, Jia Wu, Jian Yang, Xing Su, Charu C. Aggarwal:
Heterogeneous Social Event Detection via Hyperbolic Graph Representations. CoRR abs/2302.10362 (2023) - [i51]Zhimeng Guo, Teng Xiao, Charu Aggarwal, Hui Liu, Suhang Wang:
Counterfactual Learning on Graphs: A Survey. CoRR abs/2304.01391 (2023) - [i50]Pengfei He, Han Xu, Jie Ren, Yingqian Cui, Hui Liu, Charu C. Aggarwal, Jiliang Tang:
Sharpness-Aware Data Poisoning Attack. CoRR abs/2305.14851 (2023) - [i49]Haoyu Han, Xiaorui Liu, Feng Shi, MohamadAli Torkamani, Charu C. Aggarwal, Jiliang Tang:
Towards Label Position Bias in Graph Neural Networks. CoRR abs/2305.15822 (2023) - [i48]Jaykumar Kakkad, Jaspal Jannu, Kartik Sharma, Charu C. Aggarwal, Sourav Medya:
A Survey on Explainability of Graph Neural Networks. CoRR abs/2306.01958 (2023) - [i47]Zhichao Hou, Xitong Zhang, Wei Wang, Charu C. Aggarwal, Xiaorui Liu:
Can Directed Graph Neural Networks be Adversarially Robust? CoRR abs/2306.02002 (2023) - [i46]Yuying Zhao, Yu Wang, Yunchao Liu, Xueqi Cheng, Charu C. Aggarwal, Tyler Derr:
Fairness and Diversity in Recommender Systems: A Survey. CoRR abs/2307.04644 (2023) - [i45]Harry Shomer, Yao Ma, Juanhui Li, Bo Wu, Charu C. Aggarwal, Jiliang Tang:
Distance-Based Propagation for Efficient Knowledge Graph Reasoning. CoRR abs/2311.01024 (2023) - 2022
- [b10]Charu C. Aggarwal:
Machine Learning for Text, Second Edition. Springer 2022, ISBN 978-3-030-96622-5, pp. 1-532 - [j101]Zhiqiang Hu, Roy Ka-Wei Lee, Charu C. Aggarwal, Aston Zhang:
Text Style Transfer: A Review and Experimental Evaluation. SIGKDD Explor. 24(1): 14-45 (2022) - [j100]Charu C. Aggarwal:
An Interview with Dr. Charu Aggarwal, Winner of ACM SIGKDD 2022 Service Award. SIGKDD Explor. 24(2): 3-4 (2022) - [j99]Nurendra Choudhary, Charu C. Aggarwal, Karthik Subbian, Chandan K. Reddy:
Self-supervised Short-text Modeling through Auxiliary Context Generation. ACM Trans. Intell. Syst. Technol. 13(3): 51:1-51:21 (2022) - [j98]Charu C. Aggarwal:
Communication from the Editor-in-Chief: State of the ACM Transactions on Knowledge Discovery from Data. ACM Trans. Knowl. Discov. Data 16(2): 21e:1-21e:2 (2022) - [j97]Guansong Pang, Charu Aggarwal, Chunhua Shen, Nicu Sebe:
Editorial Deep Learning for Anomaly Detection. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2282-2286 (2022) - [c244]Fanzhen Liu, Xiaoxiao Ma, Jia Wu, Jian Yang, Shan Xue, Amin Beheshti, Chuan Zhou, Hao Peng, Quan Z. Sheng, Charu C. Aggarwal:
DAGAD: Data Augmentation for Graph Anomaly Detection. ICDM 2022: 259-268 - [c243]Wei Jin, Xiaorui Liu, Yao Ma, Charu C. Aggarwal, Jiliang Tang:
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective. KDD 2022: 709-719 - [c242]Ge Zhang, Zhenyu Yang, Jia Wu, Jian Yang, Shan Xue, Hao Peng, Jianlin Su, Chuan Zhou, Quan Z. Sheng, Leman Akoglu, Charu C. Aggarwal:
Dual-discriminative Graph Neural Network for Imbalanced Graph-level Anomaly Detection. NeurIPS 2022 - [c241]Shoujin Wang, Qi Zhang, Liang Hu, Xiuzhen Zhang, Yan Wang, Charu Aggarwal:
Sequential/Session-based Recommendations: Challenges, Approaches, Applications and Opportunities. SIGIR 2022: 3425-3428 - [c240]Nidhi Rastogi, Sharmishtha Dutta, Alex Gittens, Mohammed J. Zaki, Charu C. Aggarwal:
TINKER: A framework for Open source Cyberthreat Intelligence. TrustCom 2022: 1569-1574 - [c239]Feng Xia, Renaud Lambiotte, Charu Aggarwal:
GraphLearning'22: 1st International Workshop on Graph Learning. WWW (Companion Volume) 2022: 1004-1005 - [i44]Falih Gozi Febrinanto, Feng Xia, Kristen Moore, Chandra Thapa, Charu Aggarwal:
Graph Lifelong Learning: A Survey. CoRR abs/2202.10688 (2022) - [i43]Shoujin Wang, Qi Zhang, Liang Hu, Xiuzhen Zhang, Yan Wang, Charu Aggarwal:
Sequential/Session-based Recommendations: Challenges, Approaches, Applications and Opportunities. CoRR abs/2205.10759 (2022) - [i42]Ge Zhang, Jia Wu, Jian Yang, Shan Xue, Wenbin Hu, Chuan Zhou, Hao Peng, Quan Z. Sheng, Charu Aggarwal:
Graph-level Neural Networks: Current Progress and Future Directions. CoRR abs/2205.15555 (2022) - [i41]Wei Jin, Xiaorui Liu, Yao Ma, Charu C. Aggarwal, Jiliang Tang:
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective. CoRR abs/2206.07743 (2022) - [i40]Shijie Zhou, Zhimeng Guo, Charu C. Aggarwal, Xiang Zhang, Suhang Wang:
Link Prediction on Heterophilic Graphs via Disentangled Representation Learning. CoRR abs/2208.01820 (2022) - [i39]Djallel Bouneffouf, Charu C. Aggarwal:
Survey on Applications of Neurosymbolic Artificial Intelligence. CoRR abs/2209.12618 (2022) - [i38]Fanzhen Liu, Xiaoxiao Ma, Jia Wu, Jian Yang, Shan Xue, Amin Beheshti, Chuan Zhou, Hao Peng, Quan Z. Sheng, Charu C. Aggarwal:
DAGAD: Data Augmentation for Graph Anomaly Detection. CoRR abs/2210.09766 (2022) - [i37]Zahra Zamanzadeh Darban, Geoffrey I. Webb, Shirui Pan, Charu C. Aggarwal, Mahsa Salehi:
Deep Learning for Time Series Anomaly Detection: A Survey. CoRR abs/2211.05244 (2022) - [i36]Jing Ren, Feng Xia, Azadeh Noori Hoshyar, Charu C. Aggarwal:
Graph Learning for Anomaly Analytics: Algorithms, Applications, and Challenges. CoRR abs/2212.05532 (2022) - 2021
- [b9]Charu C. Aggarwal:
Artificial Intelligence - A Textbook. Springer 2021, ISBN 978-3-030-72356-9, pp. 1-483 - [j96]Liang Duan, Shuai Ma, Charu Aggarwal, Saket Sathe:
Improving spectral clustering with deep embedding, cluster estimation and metric learning. Knowl. Inf. Syst. 63(3): 675-694 (2021) - [j95]Debmalya Mandal, Sourav Medya, Brian Uzzi, Charu Aggarwal:
MetaLearning with Graph Neural Networks: Methods and Applications. SIGKDD Explor. 23(2): 13-22 (2021) - [j94]Pengyang Wang, Xiaolin Li, Yu Zheng, Charu Aggarwal, Yanjie Fu:
Spatiotemporal Representation Learning for Driving Behavior Analysis: A Joint Perspective of Peer and Temporal Dependencies. IEEE Trans. Knowl. Data Eng. 33(2): 728-741 (2021) - [j93]Yuxiang Ren, Charu C. Aggarwal, Jiawei Zhang:
ActiveIter: Meta Diagram Based Active Learning in Social Networks Alignment. IEEE Trans. Knowl. Data Eng. 33(5): 1848-1860 (2021) - [c238]Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu C. Aggarwal, Jiliang Tang:
Graph Feature Gating Networks. CIKM 2021: 813-822 - [c237]Enyan Dai, Charu Aggarwal, Suhang Wang:
NRGNN: Learning a Label Noise Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs. KDD 2021: 227-236 - [c236]Guansong Pang, Charu C. Aggarwal:
Toward Explainable Deep Anomaly Detection. KDD 2021: 4056-4057 - [c235]Zhiqiang Hu, Roy Ka-Wei Lee, Charu C. Aggarwal:
Syntax Matters! Syntax-Controlled in Text Style Transfer. RANLP 2021: 566-575 - [c234]Charu C. Aggarwal, Yao Li, Philip S. Yu:
Signature-Based Anomaly Detection in Networks. SDM 2021: 109-117 - [c233]Guansong Pang, Longbing Cao, Charu Aggarwal:
Deep Learning for Anomaly Detection: Challenges, Methods, and Opportunities. WSDM 2021: 1127-1130 - [i35]Nidhi Rastogi, Sharmishtha Dutta, Mohammed J. Zaki, Alex Gittens, Charu C. Aggarwal:
TINKER: A framework for Open source Cyberthreat Intelligence. CoRR abs/2102.05571 (2021) - [i34]Debmalya Mandal, Sourav Medya, Brian Uzzi, Charu Aggarwal:
Meta-Learning with Graph Neural Networks: Methods and Applications. CoRR abs/2103.00137 (2021) - [i33]Yang Gao, Yi-Fan Li, Yu Lin, Charu C. Aggarwal, Latifur Khan:
SetConv: A New Approach for Learning from Imbalanced Data. CoRR abs/2104.06313 (2021) - [i32]Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu C. Aggarwal, Jiliang Tang:
Graph Feature Gating Networks. CoRR abs/2105.04493 (2021) - [i31]Enyan Dai, Charu C. Aggarwal, Suhang Wang:
NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs. CoRR abs/2106.04714 (2021) - [i30]Zhiqian Chen, Fanglan Chen, Lei Zhang, Taoran Ji, Kaiqun Fu, Liang Zhao, Feng Chen, Lingfei Wu, Charu C. Aggarwal, Chang-Tien Lu:
Bridging the Gap between Spatial and Spectral Domains: A Theoretical Framework for Graph Neural Networks. CoRR abs/2107.10234 (2021) - [i29]Wenqi Fan, Wei Jin, Xiaorui Liu, Han Xu, Xianfeng Tang, Suhang Wang, Qing Li, Jiliang Tang, Jianping Wang, Charu C. Aggarwal:
Jointly Attacking Graph Neural Network and its Explanations. CoRR abs/2108.03388 (2021) - [i28]Zhiqiang Hu, Roy Ka-Wei Lee, Charu C. Aggarwal:
Syntax Matters! Syntax-Controlled in Text Style Transfer. CoRR abs/2108.05869 (2021) - [i27]Yu Wang, Charu Aggarwal, Tyler Derr:
Distance-wise Prototypical Graph Neural Network in Node Imbalance Classification. CoRR abs/2110.12035 (2021) - 2020
- [b8]Charu C. Aggarwal:
Linear Algebra and Optimization for Machine Learning - A Textbook. Springer 2020, ISBN 978-3-030-40343-0, pp. 1-495 - [j92]Charu Aggarwal:
An Interview with Dr. Charu Aggarwal, SIGKDD Innovation Award Winner. SIGKDD Explor. 22(1): 1-3 (2020) - [j91]Wei Jin, Yaxin Li, Han Xu, Yiqi Wang, Shuiwang Ji, Charu Aggarwal, Jiliang Tang:
Adversarial Attacks and Defenses on Graphs. SIGKDD Explor. 22(2): 19-34 (2020) - [c232]Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Charu C. Aggarwal, Prasenjit Mitra, Suhang Wang:
Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values. AAAI 2020: 5956-5963 - [c231]Djallel Bouneffouf, Irina Rish, Charu C. Aggarwal:
Survey on Applications of Multi-Armed and Contextual Bandits. CEC 2020: 1-8 - [c230]Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Yiqi Wang, Jiliang Tang, Charu C. Aggarwal, Prasenjit Mitra, Suhang Wang:
Investigating and Mitigating Degree-Related Biases in Graph Convoltuional Networks. CIKM 2020: 1435-1444 - [c229]Yang Gao, Yi-Fan Li, Yu Lin, Charu C. Aggarwal, Latifur Khan:
SetConv: A New Approach for Learning from Imbalanced Data. EMNLP (1) 2020: 1284-1294 - [c228]Juan-Hui Li, Yao Ma, Yiqi Wang, Charu C. Aggarwal, Chang-Dong Wang, Jiliang Tang:
Graph Pooling with Representativeness. ICDM 2020: 302-311 - [c227]Djallel Bouneffouf, Charu C. Aggarwal, Thanh Hoang, Udayan Khurana, Horst Samulowitz, Beat Buesser, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander G. Gray:
Survey on Automated End-to-End Data Science? IJCNN 2020: 1-9 - [c226]Charu C. Aggarwal, Yao Li, Philip S. Yu:
On Supervised Change Detection in Graph Streams. SDM 2020: 289-297 - [c225]Tyler Derr, Yao Ma, Wenqi Fan, Xiaorui Liu, Charu C. Aggarwal, Jiliang Tang:
Epidemic Graph Convolutional Network. WSDM 2020: 160-168 - [i26]Yiqi Wang, Yao Ma, Charu C. Aggarwal, Jiliang Tang:
Non-IID Graph Neural Networks. CoRR abs/2005.12386 (2020) - [i25]Nidhi Rastogi, Sharmishtha Dutta, Mohammed J. Zaki, Alex Gittens, Charu C. Aggarwal:
MALOnt: An Ontology for Malware Threat Intelligence. CoRR abs/2006.11446 (2020) - [i24]Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Yiqi Wang, Jiliang Tang, Charu C. Aggarwal, Prasenjit Mitra, Suhang Wang:
Graph Convolutional Networks against Degree-Related Biases. CoRR abs/2006.15643 (2020) - [i23]Zhiqiang Hu, Roy Ka-Wei Lee, Charu C. Aggarwal:
Text Style Transfer: A Review and Experiment Evaluation. CoRR abs/2010.12742 (2020)
2010 – 2019
- 2019
- [j90]Michele Dallachiesa, Charu C. Aggarwal, Themis Palpanas:
Improving Classification Quality in Uncertain Graphs. ACM J. Data Inf. Qual. 11(1): 3:1-3:20 (2019) - [c224]Bowen Dong, Charu C. Aggarwal, Philip S. Yu:
The Link Regression Problem in Graph Streams. IEEE BigData 2019: 1088-1095 - [c223]Suhang Wang, Charu C. Aggarwal, Huan Liu:
Beyond word2vec: Distance-graph Tensor Factorization for Word and Document Embeddings. CIKM 2019: 1041-1050 - [c222]Kemilly Dearo Garcia, Elaine Ribeiro de Faria, Cláudio Rebelo de Sá, João Mendes-Moreira, Charu C. Aggarwal, André C. P. L. F. de Carvalho, Joost N. Kok:
Ensemble Clustering for Novelty Detection in Data Streams. DS 2019: 460-470 - [c221]Yuxiang Ren, Charu C. Aggarwal, Jiawei Zhang:
Meta Diagram Based Active Social Networks Alignment. ICDE 2019: 1690-1693 - [c220]Liang Duan, Charu C. Aggarwal, Shuai Ma, Saket Sathe:
Improving Spectral Clustering with Deep Embedding and Cluster Estimation. ICDM 2019: 170-179 - [c219]Karthik S. Gurumoorthy, Amit Dhurandhar, Guillermo A. Cecchi, Charu C. Aggarwal:
Efficient Data Representation by Selecting Prototypes with Importance Weights. ICDM 2019: 260-269 - [c218]Wenchao Yu, Wei Cheng, Charu C. Aggarwal, Bo Zong, Haifeng Chen, Wei Wang:
Self-Attentive Attributed Network Embedding Through Adversarial Learning. ICDM 2019: 758-767 - [c217]Saket Sathe, Charu C. Aggarwal:
Nearest Neighbor Classifiers Versus Random Forests and Support Vector Machines. ICDM 2019: 1300-1305 - [c216]Bowen Dong, Charu C. Aggarwal, Philip S. Yu:
Transfer Learning for Network Classification. IJCNN 2019: 1-8 - [c215]Lingfei Wu, Ian En-Hsu Yen, Siyu Huo, Liang Zhao, Kun Xu, Liang Ma, Shouling Ji, Charu C. Aggarwal:
Efficient Global String Kernel with Random Features: Beyond Counting Substructures. KDD 2019: 520-528 - [c214]Yao Ma, Suhang Wang, Charu C. Aggarwal, Jiliang Tang:
Graph Convolutional Networks with EigenPooling. KDD 2019: 723-731 - [c213]Lingfei Wu, Ian En-Hsu Yen, Zhen Zhang, Kun Xu, Liang Zhao, Xi Peng, Yinglong Xia, Charu C. Aggarwal:
Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding. KDD 2019: 1418-1428 - [c212]Yao Ma, Suhang Wang, Charu C. Aggarwal, Dawei Yin, Jiliang Tang:
Multi-dimensional Graph Convolutional Networks. SDM 2019: 657-665 - [i22]Yuxiang Ren, Charu C. Aggarwal, Jiawei Zhang:
Meta Diagram based Active Social Networks Alignment. CoRR abs/1902.04220 (2019) - [i21]Yao Ma, Suhang Wang, Charu C. Aggarwal, Jiliang Tang:
Graph Convolutional Networks with EigenPooling. CoRR abs/1904.13107 (2019) - [i20]Charu C. Aggarwal, Djallel Bouneffouf, Horst Samulowitz, Beat Buesser, Thanh Hoang, Udayan Khurana, Sijia Liu, Tejaswini Pedapati, Parikshit Ram, Ambrish Rawat, Martin Wistuba, Alexander G. Gray:
How can AI Automate End-to-End Data Science? CoRR abs/1910.14436 (2019) - [i19]Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Charu C. Aggarwal, Prasenjit Mitra, Suhang Wang:
Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values. CoRR abs/1911.10273 (2019) - [i18]Lingfei Wu, Ian En-Hsu Yen, Zhen Zhang, Kun Xu, Liang Zhao, Xi Peng, Yinglong Xia, Charu C. Aggarwal:
Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding. CoRR abs/1911.11119 (2019) - [i17]Lingfei Wu, Ian En-Hsu Yen, Siyu Huo, Liang Zhao, Kun Xu, Liang Ma, Shouling Ji, Charu C. Aggarwal:
Efficient Global String Kernel with Random Features: Beyond Counting Substructures. CoRR abs/1911.11121 (2019) - 2018
- [b7]Charu C. Aggarwal:
Neural Networks and Deep Learning - A Textbook. Springer 2018, ISBN 978-3-319-94462-3, pp. 1-497 - [j89]Saket Sathe, Charu C. Aggarwal:
Subspace histograms for outlier detection in linear time. Knowl. Inf. Syst. 56(3): 691-715 (2018) - [j88]Suhang Wang, Charu C. Aggarwal, Huan Liu:
Random-Forest-Inspired Neural Networks. ACM Trans. Intell. Syst. Technol. 9(6): 69:1-69:25 (2018) - [j87]Xindong Wu, Charu C. Aggarwal:
Editorial: TKDD Special Issue on Interactive Data Exploration and Analytics. ACM Trans. Knowl. Discov. Data 12(1): 1:1 (2018) - [c211]Tyler Derr, Charu C. Aggarwal, Jiliang Tang:
Signed Network Modeling Based on Structural Balance Theory. CIKM 2018: 557-566 - [c210]Swarup Chandra, Ahsanul Haque, Hemeng Tao, Jie Liu, Latifur Khan, Charu C. Aggarwal:
Ensemble Direct Density Ratio Estimation for Multistream Classification. ICDE 2018: 1364-1367 - [c209]Pengyang Wang, Yanjie Fu, Jiawei Zhang, Pengfei Wang, Yu Zheng, Charu C. Aggarwal:
You Are How You Drive: Peer and Temporal-Aware Representation Learning for Driving Behavior Analysis. KDD 2018: 2457-2466 - [c208]Lingfei Wu, Pin-Yu Chen, Ian En-Hsu Yen, Fangli Xu, Yinglong Xia, Charu C. Aggarwal:
Scalable Spectral Clustering Using Random Binning Features. KDD 2018: 2506-2515 - [c207]Wenchao Yu, Cheng Zheng, Wei Cheng, Charu C. Aggarwal, Dongjin Song, Bo Zong, Haifeng Chen, Wei Wang:
Learning Deep Network Representations with Adversarially Regularized Autoencoders. KDD 2018: 2663-2671 - [c206]Wenchao Yu, Wei Cheng, Charu C. Aggarwal, Kai Zhang, Haifeng Chen, Wei Wang:
NetWalk: A Flexible Deep Embedding Approach for Anomaly Detection in Dynamic Networks. KDD 2018: 2672-2681 - [c205]Muchen Wu, Charu C. Aggarwal, Zhou Yu, Ananthram Swami, Prasant Mohapatra:
Exploiting Knowledge Across Distinct Domains: Learning Event Details from Network Logs. MILCOM 2018: 1-9 - [c204]Ana Paula Appel, Renato Luiz de Freitas Cunha, Charu C. Aggarwal, Marcela Megumi Terakado:
Temporally Evolving Community Detection and Prediction in Content-Centric Networks. ECML/PKDD (2) 2018: 3-18 - [c203]Pengyang Wang, Jiawei Zhang, Guannan Liu, Yanjie Fu, Charu C. Aggarwal:
Ensemble-Spotting: Ranking Urban Vibrancy via POI Embedding with Multi-view Spatial Graphs. SDM 2018: 351-359 - [c202]Wenchao Yu, Charu C. Aggarwal, Wei Wang:
Modeling Co-Evolution Across Multiple Networks. SDM 2018: 675-683 - [c201]Charu C. Aggarwal:
Extracting Real-Time Insights from Graphs and Social Streams. SIGIR 2018: 1339 - [e16]Xindong Wu, Yew-Soon Ong, Charu C. Aggarwal, Huanhuan Chen:
2018 IEEE International Conference on Big Knowledge, ICBK 2018, Singapore, November 17-18, 2018. IEEE Computer Society 2018, ISBN 978-1-5386-9125-0 [contents] - [r9]Charu C. Aggarwal:
Classification in Streams. Encyclopedia of Database Systems (2nd ed.) 2018 - [r8]Charu C. Aggarwal:
Counterterrorism, Social Network Analysis in. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - [r7]Charu C. Aggarwal:
Privacy in Social Networks, Current and Future Research Trends on. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - [i16]Lingfei Wu, Pin-Yu Chen, Ian En-Hsu Yen, Fangli Xu, Yinglong Xia, Charu C. Aggarwal:
Scalable Spectral Clustering Using Random Binning Features. CoRR abs/1805.11048 (2018) - [i15]Ana Paula Appel, Renato Luiz de Freitas Cunha, Charu C. Aggarwal, Marcela Megumi Terakado:
Temporally Evolving Community Detection and Prediction in Content-Centric Networks. CoRR abs/1807.06560 (2018) - [i14]Yao Ma, Suhang Wang, Charu C. Aggarwal, Dawei Yin, Jiliang Tang:
Multi-dimensional Graph Convolutional Networks. CoRR abs/1808.06099 (2018) - 2017
- [b6]Charu C. Aggarwal, Saket Sathe:
Outlier Ensembles - An Introduction. Springer 2017, ISBN 978-3-319-54764-0, pp. 1-276 - [j86]Charu C. Aggarwal, Amotz Bar-Noy, Simon Shamoun:
On sensor selection in linked information networks. Comput. Networks 126: 100-113 (2017) - [j85]Karthik Subbian, Charu C. Aggarwal:
Mining Social Streams: Models and Applications. IEEE Data Eng. Bull. 40(3): 100-109 (2017) - [j84]Weike Pan, Qiang Yang, Charu C. Aggarwal, Christoph Koch:
Big Data. IEEE Intell. Syst. 32(2): 7-8 (2017) - [j83]Guo-Jun Qi, Wei Liu, Charu C. Aggarwal, Thomas S. Huang:
Joint Intermodal and Intramodal Label Transfers for Extremely Rare or Unseen Classes. IEEE Trans. Pattern Anal. Mach. Intell. 39(7): 1360-1373 (2017) - [j82]Arijit Khan, Charu C. Aggarwal:
Toward query-friendly compression of rapid graph streams. Soc. Netw. Anal. Min. 7(1): 23:1-23:19 (2017) - [j81]Jingdong Wang, Guo-Jun Qi, Nicu Sebe, Charu C. Aggarwal:
Guest Editorial: Big Media Data: Understanding, Search, and Mining. IEEE Trans. Big Data 3(1): 36 (2017) - [j80]Charu C. Aggarwal:
Introduction to Special Issue on the Best Papers from KDD 2016. ACM Trans. Knowl. Discov. Data 11(4): 39:1-39:3 (2017) - [j79]Liang Duan, Shuai Ma, Charu C. Aggarwal, Tiejun Ma, Jinpeng Huai:
An Ensemble Approach to Link Prediction. IEEE Trans. Knowl. Data Eng. 29(11): 2402-2416 (2017) - [c200]Jiawei Zhang, Philip S. Yu, Charu C. Aggarwal, Limeng Cui:
Real Time Social Attitude Expression Prediction. BigData Congress 2017: 472-479 - [c199]Suhang Wang, Charu C. Aggarwal, Jiliang Tang, Huan Liu:
Attributed Signed Network Embedding. CIKM 2017: 137-146 - [c198]Mengxiao Zhu, Charu C. Aggarwal, Shuai Ma, Hui Zhang, Jinpeng Huai:
Outlier Detection in Sparse Data with Factorization Machines. CIKM 2017: 817-826 - [c197]Jiawei Zhang, Charu C. Aggarwal, Philip S. Yu:
Rumor Initiator Detection in Infected Signed Networks. ICDCS 2017: 1900-1909 - [c196]Ahsanul Haque, Swarup Chandra, Latifur Khan, Kevin W. Hamlen, Charu C. Aggarwal:
Efficient Multistream Classification Using Direct Density Ratio Estimation. ICDE 2017: 155-158 - [c195]Charu C. Aggarwal, Yao Li, Philip S. Yu, Yuchen Zhao:
On Edge Classification in Networks with Structure and Content. ICDE 2017: 187-190 - [c194]Xinyue Liu, Yuanfang Song, Charu C. Aggarwal, Yao Zhang, Xiangnan Kong:
BiCycle: Item Recommendation with Life Cycles. ICDM 2017: 297-306 - [c193]Saket Sathe, Charu C. Aggarwal, Xiangnan Kong, Xinyue Liu:
Kernel-Based Feature Extraction for Collaborative Filtering. ICDM 2017: 1057-1062 - [c192]Wenchao Yu, Wei Cheng, Charu C. Aggarwal, Haifeng Chen, Wei Wang:
Link Prediction with Spatial and Temporal Consistency in Dynamic Networks. IJCAI 2017: 3343-3349 - [c191]Md. Tanvir Al Amin, Charu C. Aggarwal, Shuochao Yao, Tarek F. Abdelzaher, Lance M. Kaplan:
Unveiling polarization in social networks: A matrix factorization approach. INFOCOM 2017: 1-9 - [c190]Yanjie Fu, Guannan Liu, Mingfei Teng, Charu C. Aggarwal:
Unsupervised P2P Rental Recommendations via Integer Programming. KDD 2017: 165-173 - [c189]Saket Sathe, Charu C. Aggarwal:
Similarity Forests. KDD 2017: 395-403 - [c188]Suhang Wang, Charu C. Aggarwal, Huan Liu:
Randomized Feature Engineering as a Fast and Accurate Alternative to Kernel Methods. KDD 2017: 485-494 - [c187]Pengfei Wang, Yanjie Fu, Guannan Liu, Wenqing Hu, Charu C. Aggarwal:
Human Mobility Synchronization and Trip Purpose Detection with Mixture of Hawkes Processes. KDD 2017: 495-503 - [c186]Yanjie Fu, Charu C. Aggarwal, Srinivasan Parthasarathy, Deepak S. Turaga, Hui Xiong:
REMIX: Automated Exploration for Interactive Outlier Detection. KDD 2017: 827-835 - [c185]Liheng Zhang, Charu C. Aggarwal, Guo-Jun Qi:
Stock Price Prediction via Discovering Multi-Frequency Trading Patterns. KDD 2017: 2141-2149 - [c184]Suhang Wang, Charu C. Aggarwal, Huan Liu:
Using a Random Forest to Inspire a Neural Network and Improving on It. SDM 2017: 1-9 - [c183]Jinghui Chen, Saket Sathe, Charu C. Aggarwal, Deepak S. Turaga:
Outlier Detection with Autoencoder Ensembles. SDM 2017: 90-98 - [c182]Suhang Wang, Jiliang Tang, Charu C. Aggarwal, Yi Chang, Huan Liu:
Signed Network Embedding in Social Media. SDM 2017: 327-335 - [c181]Ramakrishnan Kannan, Hyenkyun Woo, Charu C. Aggarwal, Haesun Park:
Outlier Detection for Text Data. SDM 2017: 489-497 - [c180]Suhang Wang, Yilin Wang, Jiliang Tang, Charu C. Aggarwal, Suhas Ranganath, Huan Liu:
Exploiting Hierarchical Structures for Unsupervised Feature Selection. SDM 2017: 507-515 - [c179]Wenchao Yu, Charu C. Aggarwal, Wei Wang:
Temporally Factorized Network Modeling for Evolutionary Network Analysis. WSDM 2017: 455-464 - [r6]Charu C. Aggarwal:
Graph Clustering. Encyclopedia of Machine Learning and Data Mining 2017: 570-579 - [i13]Ramakrishnan Kannan, Hyenkyun Woo, Charu C. Aggarwal, Haesun Park:
Outlier Detection for Text Data : An Extended Version. CoRR abs/1701.01325 (2017) - [i12]Guo-Jun Qi, Wei Liu, Charu C. Aggarwal, Thomas S. Huang:
Joint Intermodal and Intramodal Label Transfers for Extremely Rare or Unseen Classes. CoRR abs/1703.07519 (2017) - [i11]Yanjie Fu, Charu C. Aggarwal, Srinivasan Parthasarathy, Deepak S. Turaga, Hui Xiong:
REMIX: Automated Exploration for Interactive Outlier Detection. CoRR abs/1705.05986 (2017) - [i10]Tyler Derr, Charu C. Aggarwal, Jiliang Tang:
Signed Network Modeling Based on Structural Balance Theory. CoRR abs/1710.09485 (2017) - 2016
- [b5]Charu C. Aggarwal:
Recommender Systems - The Textbook. Springer 2016, ISBN 978-3-319-29657-9, pp. 1-498 - [j78]Jiliang Tang, Yi Chang, Charu C. Aggarwal, Huan Liu:
A Survey of Signed Network Mining in Social Media. ACM Comput. Surv. 49(3): 42:1-42:37 (2016) - [j77]Peng Cui, Huan Liu, Charu C. Aggarwal, Fei Wang:
Online Behavioral Analysis and Modeling [Guest Editorial]. IEEE Intell. Syst. 31(1): 2-4 (2016) - [j76]Peng Cui, Huan Liu, Charu C. Aggarwal, Fei Wang:
Uncovering and Predicting Human Behaviors. IEEE Intell. Syst. 31(2): 77-88 (2016) - [j75]Shiyu Chang, Guo-Jun Qi, Yingzhen Yang, Charu C. Aggarwal, Jiayu Zhou, Meng Wang, Thomas S. Huang:
Large-scale supervised similarity learning in networks. Knowl. Inf. Syst. 48(3): 707-740 (2016) - [j74]Hessam Zakerzadeh, Charu C. Aggarwal, Ken Barker:
Managing dimensionality in data privacy anonymization. Knowl. Inf. Syst. 49(1): 341-373 (2016) - [j73]Jingdong Wang, Guo-Jun Qi, Nicu Sebe, Charu C. Aggarwal:
Guest Editorial: Big Media Data: Understanding, Search, and Mining. IEEE Trans. Big Data 2(1): 31 (2016) - [j72]Karthik Subbian, Charu C. Aggarwal, Jaideep Srivastava:
Mining Influencers Using Information Flows in Social Streams. ACM Trans. Knowl. Discov. Data 10(3): 26:1-26:28 (2016) - [j71]Tahseen Al-Khateeb, Mohammad M. Masud, Khaled Al-Naami, Sadi Evren Seker, Ahmad M. Mustafa, Latifur Khan, Zouheir Trabelsi, Charu C. Aggarwal, Jiawei Han:
Recurring and Novel Class Detection Using Class-Based Ensemble for Evolving Data Stream. IEEE Trans. Knowl. Data Eng. 28(10): 2752-2764 (2016) - [c178]Arijit Khan, Charu C. Aggarwal:
Query-friendly compression of graph streams. ASONAM 2016: 130-137 - [c177]Ahsanul Haque, Zhuoyi Wang, Swarup Chandra, Yupeng Gao, Latifur Khan, Charu C. Aggarwal:
Sampling-based distributed Kernel mean matching using spark. IEEE BigData 2016: 462-471 - [c176]Suhang Wang, Jiliang Tang, Charu C. Aggarwal, Huan Liu:
Linked Document Embedding for Classification. CIKM 2016: 115-124 - [c175]Swarup Chandra, Ahsanul Haque, Latifur Khan, Charu C. Aggarwal:
An Adaptive Framework for Multistream Classification. CIKM 2016: 1181-1190 - [c174]Karthik Subbian, Charu C. Aggarwal, Kshiteesh Hegde:
Recommendations For Streaming Data. CIKM 2016: 2185-2190 - [c173]Renjun Hu, Charu C. Aggarwal, Shuai Ma, Jinpeng Huai:
An embedding approach to anomaly detection. ICDE 2016: 385-396 - [c172]Ahsanul Haque, Latifur Khan, Michael Baron, Bhavani Thuraisingham, Charu C. Aggarwal:
Efficient handling of concept drift and concept evolution over Stream Data. ICDE 2016: 481-492 - [c171]Peixiang Zhao, Charu C. Aggarwal, Gewen He:
Link prediction in graph streams. ICDE 2016: 553-564 - [c170]Charu C. Aggarwal, Gewen He, Peixiang Zhao:
Edge classification in networks. ICDE 2016: 1038-1049 - [c169]Jose Cadena, Anil Kumar S. Vullikanti, Charu C. Aggarwal:
On Dense Subgraphs in Signed Network Streams. ICDM 2016: 51-60 - [c168]Saket Sathe, Charu C. Aggarwal:
Subspace Outlier Detection in Linear Time with Randomized Hashing. ICDM 2016: 459-468 - [c167]Swarup Chandra, Ahsanul Haque, Latifur Khan, Charu C. Aggarwal:
Efficient Sampling-Based Kernel Mean Matching. ICDM 2016: 811-816 - [c166]Shuochao Yao, Md. Tanvir Al Amin, Lu Su, Shaohan Hu, Shen Li, Shiguang Wang, Yiran Zhao, Tarek F. Abdelzaher, Lance M. Kaplan, Charu C. Aggarwal, Aylin Yener:
Recursive Ground Truth Estimator for Social Data Streams. IPSN 2016: 14:1-14:12 - [c165]Jiawei Zhang, Qianyi Zhan, Lifang He, Charu C. Aggarwal, Philip S. Yu:
Trust Hole Identification in Signed Networks. ECML/PKDD (1) 2016: 697-713 - [c164]Jiliang Tang, Charu C. Aggarwal, Huan Liu:
Node Classification in Signed Social Networks. SDM 2016: 54-62 - [c163]Saket Sathe, Charu C. Aggarwal:
LODES: Local Density Meets Spectral Outlier Detection. SDM 2016: 171-179 - [c162]Xinyue Liu, Charu C. Aggarwal, Yufeng Li, Xiangnan Kong, Xinyuan Sun, Saket Sathe:
Kernelized Matrix Factorization for Collaborative Filtering. SDM 2016: 378-386 - [c161]Liang Duan, Charu C. Aggarwal, Shuai Ma, Renjun Hu, Jinpeng Huai:
Scaling up Link Prediction with Ensembles. WSDM 2016: 367-376 - [c160]Zhaoming Wu, Charu C. Aggarwal, Jimeng Sun:
The Troll-Trust Model for Ranking in Signed Networks. WSDM 2016: 447-456 - [c159]Karthik Subbian, Charu C. Aggarwal, Jaideep Srivastava:
Querying and Tracking Influencers in Social Streams. WSDM 2016: 493-502 - [c158]Jiliang Tang, Charu C. Aggarwal, Huan Liu:
Recommendations in Signed Social Networks. WWW 2016: 31-40 - [e15]Balaji Krishnapuram, Mohak Shah, Alexander J. Smola, Charu C. Aggarwal, Dou Shen, Rajeev Rastogi:
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA, August 13-17, 2016. ACM 2016, ISBN 978-1-4503-4232-2 [contents] - 2015
- [b4]Charu C. Aggarwal:
Data Mining - The Textbook. Springer 2015, ISBN 978-3-319-14141-1, pp. 1-693 - [j70]Charu C. Aggarwal, Yao Li, Philip S. Yu:
On the anonymizability of graphs. Knowl. Inf. Syst. 45(3): 571-588 (2015) - [j69]Charu C. Aggarwal, Saket Sathe:
Theoretical Foundations and Algorithms for Outlier Ensembles. SIGKDD Explor. 17(1): 24-47 (2015) - [j68]Jingdong Wang, Guo-Jun Qi, Nicu Sebe, Charu C. Aggarwal:
Guest Editorial: Big Media Data: Understanding, Search, and Mining. IEEE Trans. Big Data 1(3): 82-83 (2015) - [j67]Jingdong Wang, Guo-Jun Qi, Nicu Sebe, Charu C. Aggarwal:
Guest Editorial: Big Media Data: Understanding, Search, and Mining (Part 2). IEEE Trans. Big Data 1(4): 151 (2015) - [j66]Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang:
Breaking the Barrier to Transferring Link Information across Networks. IEEE Trans. Knowl. Data Eng. 27(7): 1741-1753 (2015) - [c157]Hessam Zakerzadeh, Charu C. Aggarwal, Ken Barker:
Big Graph Privacy. EDBT/ICDT Workshops 2015: 255-262 - [c156]Charu C. Aggarwal, Philip S. Yu:
On historical diagnosis of sensor streams. ICDE 2015: 185-194 - [c155]Wei Feng, Chao Zhang, Wei Zhang, Jiawei Han, Jianyong Wang, Charu C. Aggarwal, Jianbin Huang:
STREAMCUBE: Hierarchical spatio-temporal hashtag clustering for event exploration over the Twitter stream. ICDE 2015: 1561-1572 - [c154]Shiyu Chang, Wei Han, Jiliang Tang, Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang:
Heterogeneous Network Embedding via Deep Architectures. KDD 2015: 119-128 - [c153]Guo-Jun Qi, Charu C. Aggarwal, Deepak S. Turaga, Daby M. Sow, Phil Anno:
State-Driven Dynamic Sensor Selection and Prediction with State-Stacked Sparseness. KDD 2015: 945-954 - [c152]Jialu Liu, Chi Wang, Jing Gao, Quanquan Gu, Charu C. Aggarwal, Lance M. Kaplan, Jiawei Han:
GIN: A Clustering Model for Capturing Dual Heterogeneity in Networked Data. SDM 2015: 388-396 - [c151]Karthik Subbian, Charu C. Aggarwal, Jaideep Srivastava, Vipin Kumar:
Rare Class Detection in Networks. SDM 2015: 406-414 - [c150]Min-Hsuan Tsai, Charu C. Aggarwal, Thomas S. Huang:
Towards Classification of Social Streams. SDM 2015: 649-657 - [c149]Hessam Zakerzadeh, Charu C. Aggarwal, Ken Barker:
Privacy-preserving big data publishing. SSDBM 2015: 26:1-26:11 - [c148]Jiliang Tang, Shiyu Chang, Charu C. Aggarwal, Huan Liu:
Negative Link Prediction in Social Media. WSDM 2015: 87-96 - [c147]Jialu Liu, Charu C. Aggarwal, Jiawei Han:
On Integrating Network and Community Discovery. WSDM 2015: 117-126 - [p44]Chandan K. Reddy, Charu C. Aggarwal:
An Introduction to Healthcare Data Analytics. Healthcare Data Analytics 2015: 1-18 - [e14]Chandan K. Reddy, Charu C. Aggarwal:
Healthcare Data Analytics. Chapman and Hall/CRC 2015, ISBN 978-1-4822-3211-0 [contents] - [e13]James Bailey, Alistair Moffat, Charu C. Aggarwal, Maarten de Rijke, Ravi Kumar, Vanessa Murdock, Timos K. Sellis, Jeffrey Xu Yu:
Proceedings of the 24th ACM International Conference on Information and Knowledge Management, CIKM 2015, Melbourne, VIC, Australia, October 19 - 23, 2015. ACM 2015, ISBN 978-1-4503-3794-6 [contents] - [e12]Charu C. Aggarwal, Zhi-Hua Zhou, Alexander Tuzhilin, Hui Xiong, Xindong Wu:
2015 IEEE International Conference on Data Mining, ICDM 2015, Atlantic City, NJ, USA, November 14-17, 2015. IEEE Computer Society 2015, ISBN 978-1-4673-9504-5 [contents] - [i9]Jiliang Tang, Yi Chang, Charu C. Aggarwal, Huan Liu:
A Survey of Signed Network Mining in Social Media. CoRR abs/1511.07569 (2015) - [i8]Mohammad Hosseini, Nooreddin Naghibolhosseini, Amotz Barnoy, Peter Terlecky, Hengchang Liu, Shaohan Hu, Shiguang Wang, Md. Tanvir Al Amin, Lu Su, Dong Wang, Ramesh Govindan, Raghu K. Ganti, Mudhakar Srivatsa, Charu C. Aggarwal, Tarek F. Abdelzaher, Siyu Gu, Chenji Pan:
Joint Source Selection and Data Extrapolation in Social Sensing for Disaster Response. CoRR abs/1512.00500 (2015) - 2014
- [b3]Manish Gupta, Jing Gao, Charu C. Aggarwal, Jiawei Han:
Outlier Detection for Temporal Data. Synthesis Lectures on Data Mining and Knowledge Discovery, Morgan & Claypool Publishers 2014, ISBN 978-3-031-00777-4 - [j65]Charu C. Aggarwal, Karthik Subbian:
Evolutionary Network Analysis: A Survey. ACM Comput. Surv. 47(1): 10:1-10:36 (2014) - [j64]Charu C. Aggarwal, Yan Xie, Philip S. Yu:
A framework for dynamic link prediction in heterogeneous networks. Stat. Anal. Data Min. 7(1): 14-33 (2014) - [j63]Charu C. Aggarwal, Yuchen Zhao, Philip S. Yu:
On the Use of Side Information for Mining Text Data. IEEE Trans. Knowl. Data Eng. 26(6): 1415-1429 (2014) - [j62]Manish Gupta, Jing Gao, Charu C. Aggarwal, Jiawei Han:
Outlier Detection for Temporal Data: A Survey. IEEE Trans. Knowl. Data Eng. 26(9): 2250-2267 (2014) - [c146]Ahsanul Haque, Swarup Chandra, Latifur Khan, Charu C. Aggarwal:
Distributed Adaptive Importance Sampling on graphical models using MapReduce. IEEE BigData 2014: 597-602 - [c145]Tyler Clemons, S. M. Faisal, Shirish Tatikonda, Charu C. Aggarwal, Srinivasan Parthasarathy:
One, Two, Hash! Counting Hash Tables for Flash Devices. CODS 2014: 1-10 - [c144]Siyu Gu, Chenji Pan, Hengchang Liu, Shen Li, Shaohan Hu, Lu Su, Shiguang Wang, Dong Wang, Md. Tanvir Al Amin, Ramesh Govindan, Charu C. Aggarwal, Raghu K. Ganti, Mudhakar Srivatsa, Amotz Barnoy, Peter Terlecky, Tarek F. Abdelzaher:
Data Extrapolation in Social Sensing for Disaster Response. DCOSS 2014: 119-126 - [c143]Charu C. Aggarwal, Philip S. Yu:
A Condensation Approach to Privacy Preserving Data Mining. EDBT 2014: 607 - [c142]Shiyu Chang, Guo-Jun Qi, Charu C. Aggarwal, Jiayu Zhou, Meng Wang, Thomas S. Huang:
Factorized Similarity Learning in Networks. ICDM 2014: 60-69 - [c141]Shiyu Chang, Charu C. Aggarwal, Thomas S. Huang:
Learning Local Semantic Distances with Limited Supervision. ICDM 2014: 70-79 - [c140]Swarup Chandra, Justin Sahs, Latifur Khan, Bhavani Thuraisingham, Charu C. Aggarwal:
Stream Mining Using Statistical Relational Learning. ICDM 2014: 743-748 - [c139]Dong Wang, Md. Tanvir Al Amin, Shen Li, Tarek F. Abdelzaher, Lance M. Kaplan, Siyu Gu, Chenji Pan, Hengchang Liu, Charu C. Aggarwal, Raghu K. Ganti, Xinlei Wang, Prasant Mohapatra, Boleslaw K. Szymanski, Hieu Khac Le:
Using humans as sensors: an estimation-theoretic perspective. IPSN 2014: 35-46 - [c138]Charu C. Aggarwal:
The setwise stream classification problem. KDD 2014: 432-441 - [c137]Karthik Subbian, Chidananda Sridhar, Charu C. Aggarwal, Jaideep Srivastava:
Scalable Information Flow Mining in Networks. ECML/PKDD (3) 2014: 130-146 - [c136]Hessam Zakerzadeh, Charu C. Aggarwal, Ken Barker:
Towards Breaking the Curse of Dimensionality for High-Dimensional Privacy. SDM 2014: 731-739 - [c135]Michele Dallachiesa, Charu C. Aggarwal, Themis Palpanas:
Node classification in uncertain graphs. SSDBM 2014: 32:1-32:4 - [c134]Min-Hsuan Tsai, Charu C. Aggarwal, Thomas S. Huang:
Ranking in heterogeneous social media. WSDM 2014: 613-622 - [p43]Charu C. Aggarwal:
An Introduction to Data Classification. Data Classification: Algorithms and Applications 2014: 1-36 - [p42]Charu C. Aggarwal:
Instance-Based Learning: A Survey. Data Classification: Algorithms and Applications 2014: 157-186 - [p41]Charu C. Aggarwal:
A Survey of Stream Classification Algorithms. Data Classification: Algorithms and Applications 2014: 245-274 - [p40]Charu C. Aggarwal, ChengXiang Zhai:
Text Classification. Data Classification: Algorithms and Applications 2014: 287-336 - [p39]Charu C. Aggarwal:
Rare Class Learning. Data Classification: Algorithms and Applications 2014: 445-468 - [p38]Charu C. Aggarwal, Xiangnan Kong, Quanquan Gu, Jiawei Han, Philip S. Yu:
Active Learning: A Survey. Data Classification: Algorithms and Applications 2014: 571-606 - [p37]Charu C. Aggarwal:
Educational and Software Resources for Data Classification. Data Classification: Algorithms and Applications 2014: 657-666 - [p36]Charu C. Aggarwal:
An Introduction to Frequent Pattern Mining. Frequent Pattern Mining 2014: 1-17 - [p35]Charu C. Aggarwal, Mansurul Bhuiyan, Mohammad Al Hasan:
Frequent Pattern Mining Algorithms: A Survey. Frequent Pattern Mining 2014: 19-64 - [p34]Charu C. Aggarwal:
Applications of Frequent Pattern Mining. Frequent Pattern Mining 2014: 443-467 - [e11]Charu C. Aggarwal, Chandan K. Reddy:
Data Clustering: Algorithms and Applications. CRC Press 2014, ISBN 978-1-46-655821-2 [contents] - [e10]Charu C. Aggarwal:
Data Classification: Algorithms and Applications. CRC Press 2014, ISBN 978-1-4665-8674-1 [contents] - [e9]Charu C. Aggarwal, Jiawei Han:
Frequent Pattern Mining. Springer 2014, ISBN 978-3-319-07820-5 [contents] - [e8]Jimmy Lin, Jian Pei, Xiaohua Hu, Wo Chang, Raghunath Nambiar, Charu C. Aggarwal, Nick Cercone, Vasant G. Honavar, Jun Huan, Bamshad Mobasher, Saumyadipta Pyne:
2014 IEEE International Conference on Big Data (IEEE BigData 2014), Washington, DC, USA, October 27-30, 2014. IEEE Computer Society 2014, ISBN 978-1-4799-5665-4 [contents] - [r5]Charu C. Aggarwal:
Counterterrorism, Social Network Analysis In. Encyclopedia of Social Network Analysis and Mining 2014: 285-289 - [r4]Charu C. Aggarwal:
Privacy in Social Networks, Current and Future Research Trends on. Encyclopedia of Social Network Analysis and Mining 2014: 1335-1339 - [i7]Hessam Zakerzadeh, Charu C. Aggarwal, Ken Barker:
Towards Breaking the Curse of Dimensionality for High-Dimensional Privacy: An Extended Version. CoRR abs/1401.1174 (2014) - [i6]Michele Dallachiesa, Charu C. Aggarwal, Themis Palpanas:
Node Classification in Uncertain Graphs. CoRR abs/1405.5829 (2014) - [i5]Jiliang Tang, Shiyu Chang, Charu C. Aggarwal, Huan Liu:
Negative Link Prediction in Social Media. CoRR abs/1412.2723 (2014) - 2013
- [b2]Charu C. Aggarwal:
Outlier Analysis. Springer 2013, ISBN 978-1-4614-6395-5 - [j61]Dong Wang, Lance M. Kaplan, Tarek F. Abdelzaher, Charu C. Aggarwal:
On Credibility Estimation Tradeoffs in Assured Social Sensing. IEEE J. Sel. Areas Commun. 31(6): 1026-1037 (2013) - [j60]Charu C. Aggarwal, Peixiang Zhao:
Towards graphical models for text processing. Knowl. Inf. Syst. 36(1): 1-21 (2013) - [j59]Arijit Khan, Yinghui Wu, Charu C. Aggarwal, Xifeng Yan:
NeMa: Fast Graph Search with Label Similarity. Proc. VLDB Endow. 6(3): 181-192 (2013) - [j58]Charu C. Aggarwal:
Mining text and social streams: a review. SIGKDD Explor. 15(2): 9-19 (2013) - [j57]Mohammad M. Masud, Qing Chen, Latifur Khan, Charu C. Aggarwal, Jing Gao, Jiawei Han, Ashok Srivastava, Nikunj C. Oza:
Classification and Adaptive Novel Class Detection of Feature-Evolving Data Streams. IEEE Trans. Knowl. Data Eng. 25(7): 1484-1497 (2013) - [j56]Charu C. Aggarwal:
On the Analytical Properties of High-Dimensional Randomization. IEEE Trans. Knowl. Data Eng. 25(7): 1628-1642 (2013) - [c133]Quanquan Gu, Charu C. Aggarwal, Jiawei Han:
Unsupervised Link Selection in Networks. AISTATS 2013: 298-306 - [c132]Tyler Clemons, S. M. Faisal, Shirish Tatikonda, Charu C. Aggarwal, Srinivasan Parthasarathy:
Hash in a flash: Hash tables for flash devices. IEEE BigData 2013: 7-14 - [c131]Karthik Subbian, Charu C. Aggarwal, Jaideep Srivastava:
Content-centric flow mining for influence analysis in social streams. CIKM 2013: 841-846 - [c130]Dong Wang, Tarek F. Abdelzaher, Lance M. Kaplan, Charu C. Aggarwal:
Recursive Fact-Finding: A Streaming Approach to Truth Estimation in Crowdsourcing Applications. ICDCS 2013: 530-539 - [c129]Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang:
Link prediction across networks by biased cross-network sampling. ICDE 2013: 793-804 - [c128]Weiren Yu, Charu C. Aggarwal, Shuai Ma, Haixun Wang:
On Anomalous Hotspot Discovery in Graph Streams. ICDM 2013: 1271-1276 - [c127]Quanquan Gu, Charu C. Aggarwal, Jialu Liu, Jiawei Han:
Selective sampling on graphs for classification. KDD 2013: 131-139 - [c126]Karthik Subbian, Charu C. Aggarwal, Jaideep Srivastava, Philip S. Yu:
Community Detection with Prior Knowledge. SDM 2013: 405-413 - [c125]Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang:
Online community detection in social sensing. WSDM 2013: 617-626 - [c124]Guo-Jun Qi, Charu C. Aggarwal, Jiawei Han, Thomas S. Huang:
Mining collective intelligence in diverse groups. WWW 2013: 1041-1052 - [p33]Charu C. Aggarwal:
An Introduction to Cluster Analysis. Data Clustering: Algorithms and Applications 2013: 1-28 - [p32]Charu C. Aggarwal:
A Survey of Stream Clustering Algorithms. Data Clustering: Algorithms and Applications 2013: 231-258 - [p31]Dimitrios Kotsakos, Goce Trajcevski, Dimitrios Gunopulos, Charu C. Aggarwal:
Time-Series Data Clustering. Data Clustering: Algorithms and Applications 2013: 357-380 - [p30]Charu C. Aggarwal:
A Survey of Uncertain Data Clustering Algorithms. Data Clustering: Algorithms and Applications 2013: 457-482 - [p29]Charu C. Aggarwal, Chandan K. Reddy:
Educational and Software Resources for Data Clustering. Data Clustering: Algorithms and Applications 2013: 607-616 - [p28]Charu C. Aggarwal:
An Introduction to Sensor Data Analytics. Managing and Mining Sensor Data 2013: 1-8 - [p27]Charu C. Aggarwal:
Mining Sensor Data Streams. Managing and Mining Sensor Data 2013: 143-171 - [p26]Charu C. Aggarwal, Tarek F. Abdelzaher:
Social Sensing. Managing and Mining Sensor Data 2013: 237-297 - [p25]Charu C. Aggarwal, Jiawei Han:
A Survey of RFID Data Processing. Managing and Mining Sensor Data 2013: 349-382 - [p24]Charu C. Aggarwal, Naveen Ashish, Amit P. Sheth:
The Internet of Things: A Survey from the Data-Centric Perspective. Managing and Mining Sensor Data 2013: 383-428 - [e7]Charu C. Aggarwal:
Managing and Mining Sensor Data. Springer 2013, ISBN 978-1-4614-6308-5 [contents] - 2012
- [j55]Fei Wang, Hanghang Tong, Philip S. Yu, Charu C. Aggarwal:
Guest editorial: special issue on data mining technologies for computational social science. Data Min. Knowl. Discov. 25(3): 415-419 (2012) - [j54]Charu C. Aggarwal, Philip S. Yu:
On the network effect in Web 2.0 applications. Electron. Commer. Res. Appl. 11(2): 142-151 (2012) - [j53]Charu C. Aggarwal:
A segment-based framework for modeling and mining data streams. Knowl. Inf. Syst. 30(1): 1-29 (2012) - [j52]Guo-Jun Qi, Charu C. Aggarwal, Qi Tian, Heng Ji, Thomas S. Huang:
Exploring Context and Content Links in Social Media: A Latent Space Method. IEEE Trans. Pattern Anal. Mach. Intell. 34(5): 850-862 (2012) - [j51]Yizhou Sun, Charu C. Aggarwal, Jiawei Han:
Relation Strength-Aware Clustering of Heterogeneous Information Networks with Incomplete Attributes. Proc. VLDB Endow. 5(5): 394-405 (2012) - [j50]Charu C. Aggarwal, Nan Li:
On supervised mining of dynamic content-based networks. Stat. Anal. Data Min. 5(1): 16-34 (2012) - [j49]Charu C. Aggarwal:
Outlier ensembles: position paper. SIGKDD Explor. 14(2): 49-58 (2012) - [j48]Charu C. Aggarwal:
On the equivalence of PLSI and projected clustering. SIGMOD Rec. 41(4): 45-50 (2012) - [c123]Charu C. Aggarwal, Wangqun Lin, Philip S. Yu:
Searching by corpus with fingerprints. EDBT 2012: 348-359 - [c122]Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang:
Community Detection with Edge Content in Social Media Networks. ICDE 2012: 534-545 - [c121]Charu C. Aggarwal, Yuchen Zhao, Philip S. Yu:
On Text Clustering with Side Information. ICDE 2012: 894-904 - [c120]Tahseen Al-Khateeb, Mohammad M. Masud, Latifur Khan, Charu C. Aggarwal, Jiawei Han, Bhavani Thuraisingham:
Stream Classification with Recurring and Novel Class Detection Using Class-Based Ensemble. ICDM 2012: 31-40 - [c119]Lin Liu, Ruoming Jin, Charu C. Aggarwal, Yelong Shen:
Reliable Clustering on Uncertain Graphs. ICDM 2012: 459-468 - [c118]Charu C. Aggarwal:
The Multi-Set Stream Clustering Problem. SDM 2012: 59-69 - [c117]Charu C. Aggarwal, Yan Xie, Philip S. Yu:
On Dynamic Link Inference in Heterogeneous Networks. SDM 2012: 415-426 - [c116]Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang:
Transfer Learning of Distance Metrics by Cross-Domain Metric Sampling across Heterogeneous Spaces. SDM 2012: 528-539 - [c115]Charu C. Aggarwal, Karthik Subbian:
Event Detection in Social Streams. SDM 2012: 624-635 - [c114]Charu C. Aggarwal, Shuyang Lin, Philip S. Yu:
On Influential Node Discovery in Dynamic Social Networks. SDM 2012: 636-647 - [c113]Dong Wang, Lance M. Kaplan, Tarek F. Abdelzaher, Charu C. Aggarwal:
On scalability and robustness limitations of real and asymptotic confidence bounds in social sensing. SECON 2012: 506-514 - [c112]Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang:
On clustering heterogeneous social media objects with outlier links. WSDM 2012: 553-562 - [c111]Yizhou Sun, Jiawei Han, Charu C. Aggarwal, Nitesh V. Chawla:
When will it happen?: relationship prediction in heterogeneous information networks. WSDM 2012: 663-672 - [p23]Charu C. Aggarwal:
From Combinatorial Optimization to Data Mining. Journeys to Data Mining 2012: 27-42 - [p22]Charu C. Aggarwal, ChengXiang Zhai:
An Introduction to Text Mining. Mining Text Data 2012: 1-10 - [p21]Charu C. Aggarwal, ChengXiang Zhai:
A Survey of Text Clustering Algorithms. Mining Text Data 2012: 77-128 - [p20]Charu C. Aggarwal, ChengXiang Zhai:
A Survey of Text Classification Algorithms. Mining Text Data 2012: 163-222 - [p19]Charu C. Aggarwal:
Mining Text Streams. Mining Text Data 2012: 297-321 - [e6]Charu C. Aggarwal, ChengXiang Zhai:
Mining Text Data. Springer 2012, ISBN 978-1-4419-8462-3 [contents] - [i4]Yizhou Sun, Charu C. Aggarwal, Jiawei Han:
Relation Strength-Aware Clustering of Heterogeneous Information Networks with Incomplete Attributes. CoRR abs/1201.6563 (2012) - [i3]Guo-Jun Qi, Charu C. Aggarwal, Pierre Moulin, Thomas S. Huang:
Learning from Collective Intelligence in Groups. CoRR abs/1210.0954 (2012) - [i2]Tyler Clemons, S. M. Faisal, Shirish Tatikonda, Charu C. Aggarwal, Srinivasan Parthasarathy:
Hash in a Flash: Hash Tables for Solid State Devices. CoRR abs/1211.4521 (2012) - 2011
- [j47]Peixiang Zhao, Charu C. Aggarwal, Min Wang:
gSketch: On Query Estimation in Graph Streams. Proc. VLDB Endow. 5(3): 193-204 (2011) - [c110]Manish Gupta, Charu C. Aggarwal, Jiawei Han, Yizhou Sun:
Evolutionary Clustering and Analysis of Bibliographic Networks. ASONAM 2011: 63-70 - [c109]Yizhou Sun, Rick Barber, Manish Gupta, Charu C. Aggarwal, Jiawei Han:
Co-author Relationship Prediction in Heterogeneous Bibliographic Networks. ASONAM 2011: 121-128 - [c108]Guo-Jun Qi, Charu C. Aggarwal, Yong Rui, Qi Tian, Shiyu Chang, Thomas S. Huang:
Towards cross-category knowledge propagation for learning visual concepts. CVPR 2011: 897-904 - [c107]Charu C. Aggarwal, Amotz Bar-Noy, Simon Shamoun:
On sensor selection in linked information networks. DCOSS 2011: 1-8 - [c106]Dong Wang, Hossein Ahmadi, Tarek F. Abdelzaher, Harshavardhan Chenji, Radu Stoleru, Charu C. Aggarwal:
Optimizing quality-of-information in cost-sensitive sensor data fusion. DCOSS 2011: 1-8 - [c105]Dong Wang, Tarek F. Abdelzaher, Hossein Ahmadi, Jeff Pasternack, Dan Roth, Manish Gupta, Jiawei Han, Omid Fatemieh, Hieu Khac Le, Charu C. Aggarwal:
On Bayesian interpretation of fact-finding in information networks. FUSION 2011: 1-8 - [c104]Charu C. Aggarwal, Yuchen Zhao, Philip S. Yu:
Outlier detection in graph streams. ICDE 2011: 399-409 - [c103]Charu C. Aggarwal, Haixun Wang:
On dimensionality reduction of massive graphs for indexing and retrieval. ICDE 2011: 1091-1102 - [c102]Charu C. Aggarwal, Yao Li, Philip S. Yu:
On the Hardness of Graph Anonymization. ICDM 2011: 1002-1007 - [c101]Mohammad M. Masud, Tahseen Al-Khateeb, Latifur Khan, Charu C. Aggarwal, Jing Gao, Jiawei Han, Bhavani Thuraisingham:
Detecting Recurring and Novel Classes in Concept-Drifting Data Streams. ICDM 2011: 1176-1181 - [c100]Ruoming Jin, Lin Liu, Charu C. Aggarwal:
Discovering highly reliable subgraphs in uncertain graphs. KDD 2011: 992-1000 - [c99]Charu C. Aggarwal, Yan Xie, Philip S. Yu:
On dynamic data-driven selection of sensor streams. KDD 2011: 1226-1234 - [c98]Charu C. Aggarwal, Nan Li:
On Node Classification in Dynamic Content-based Networks. SDM 2011: 355-366 - [c97]Charu C. Aggarwal, Yan Xie, Philip S. Yu:
Towards Community Detection in Locally Heterogeneous Networks. SDM 2011: 391-402 - [c96]Charu C. Aggarwal, Arijit Khan, Xifeng Yan:
On Flow Authority Discovery in Social Networks. SDM 2011: 522-533 - [c95]Charu C. Aggarwal:
On Classification of Graph Streams. SDM 2011: 652-663 - [c94]Chun Li, Charu C. Aggarwal, Jianyong Wang:
On Anonymization of Multi-graphs. SDM 2011: 711-722 - [c93]Manish Gupta, Charu C. Aggarwal, Jiawei Han:
Finding Top-k Shortest Path Distance Changes in an Evolutionary Network. SSTD 2011: 130-148 - [c92]Guojun Qi, Charu C. Aggarwal, Thomas S. Huang:
Towards semantic knowledge propagation from text corpus to web images. WWW 2011: 297-306 - [p18]Charu C. Aggarwal:
An Introduction to Social Network Data Analytics. Social Network Data Analytics 2011: 1-15 - [p17]Charu C. Aggarwal, Haixun Wang:
Text Mining in Social Networks. Social Network Data Analytics 2011: 353-378 - [p16]Charu C. Aggarwal, Tarek F. Abdelzaher:
Integrating Sensors and Social Networks. Social Network Data Analytics 2011: 379-412 - [e5]Charu C. Aggarwal:
Social Network Data Analytics. Springer 2011, ISBN 978-1-4419-8461-6 [contents] - [r3]Charu C. Aggarwal:
Data Mining (Privacy in). Encyclopedia of Cryptography and Security (2nd Ed.) 2011: 303-306 - [i1]Peixiang Zhao, Charu C. Aggarwal, Min Wang:
gSketch: On Query Estimation in Graph Streams. CoRR abs/1111.7167 (2011) - 2010
- [j46]Charu C. Aggarwal, Chen Chen, Jiawei Han:
The Inverse Classification Problem. J. Comput. Sci. Technol. 25(3): 458-468 (2010) - [j45]Charu C. Aggarwal, Philip S. Yu:
On clustering massive text and categorical data streams. Knowl. Inf. Syst. 24(2): 171-196 (2010) - [j44]Charu C. Aggarwal, Yao Li, Philip S. Yu, Ruoming Jin:
On Dense Pattern Mining in Graph Streams. Proc. VLDB Endow. 3(1): 975-984 (2010) - [j43]Charu C. Aggarwal, Yuchen Zhao, Philip S. Yu:
A framework for clustering massive graph streams. Stat. Anal. Data Min. 3(6): 399-416 (2010) - [c91]Yuchen Zhao, Charu C. Aggarwal, Philip S. Yu:
On wavelet decomposition of uncertain time series data sets. CIKM 2010: 129-138 - [c90]Mohammad M. Masud, Qing Chen, Latifur Khan, Charu C. Aggarwal, Jing Gao, Jiawei Han, Bhavani Thuraisingham:
Addressing Concept-Evolution in Concept-Drifting Data Streams. ICDM 2010: 929-934 - [c89]Charu C. Aggarwal:
On Multidimensional Sharpening of Uncertain Data. SDM 2010: 373-384 - [c88]Charu C. Aggarwal, Yuchen Zhao, Philip S. Yu:
On Clustering Graph Streams. SDM 2010: 478-489 - [c87]Charu C. Aggarwal:
The Generalized Dimensionality Reduction Problem. SDM 2010: 607-618 - [c86]Charu C. Aggarwal, Philip S. Yu:
On Classification of High-Cardinality Data Streams. SDM 2010: 802-813 - [c85]Charu C. Aggarwal, Peixiang Zhao:
Graphical models for text: a new paradigm for text representation and processing. SIGIR 2010: 899-900 - [p15]Charu C. Aggarwal:
Data Streams: An Overview and Scientific Applications. Scientific Data Mining and Knowledge Discovery 2010: 377-397 - [p14]Charu C. Aggarwal, Haixun Wang:
An Introduction to Graph Data. Managing and Mining Graph Data 2010: 1-11 - [p13]Charu C. Aggarwal, Haixun Wang:
Graph Data Management and Mining: A Survey of Algorithms and Applications. Managing and Mining Graph Data 2010: 13-68 - [p12]Haixun Wang, Charu C. Aggarwal:
A Survey of Algorithms for Keyword Search on Graph Data. Managing and Mining Graph Data 2010: 249-273 - [p11]Charu C. Aggarwal, Haixun Wang:
A Survey of Clustering Algorithms for Graph Data. Managing and Mining Graph Data 2010: 275-301 - [p10]Victor E. Lee, Ning Ruan, Ruoming Jin, Charu C. Aggarwal:
A Survey of Algorithms for Dense Subgraph Discovery. Managing and Mining Graph Data 2010: 303-336 - [e4]Charu C. Aggarwal, Haixun Wang:
Managing and Mining Graph Data. Advances in Database Systems 40, Springer 2010, ISBN 978-1-4419-6044-3 [contents] - [r2]Charu C. Aggarwal:
Graph Clustering. Encyclopedia of Machine Learning 2010: 459-467
2000 – 2009
- 2009
- [b1]Charu C. Aggarwal:
Managing and Mining Uncertain Data. Advances in Database Systems 35, Kluwer 2009, ISBN 978-0-387-09689-6, pp. 1-41 - [j42]Jianyong Wang, Yuzhou Zhang, Lizhu Zhou, George Karypis, Charu C. Aggarwal:
CONTOUR: an efficient algorithm for discovering discriminating subsequences. Data Min. Knowl. Discov. 18(1): 1-29 (2009) - [j41]Charu C. Aggarwal:
On classification and segmentation of massive audio data streams. Knowl. Inf. Syst. 20(2): 137-156 (2009) - [j40]Charu C. Aggarwal, Yan Xie, Philip S. Yu:
GConnect: A Connectivity Index for Massive Disk-resident Graphs. Proc. VLDB Endow. 2(1): 862-873 (2009) - [j39]Charu C. Aggarwal, Philip S. Yu:
A Survey of Uncertain Data Algorithms and Applications. IEEE Trans. Knowl. Data Eng. 21(5): 609-623 (2009) - [c84]Charu C. Aggarwal:
A Framework for Clustering Massive-Domain Data Streams. ICDE 2009: 102-113 - [c83]Dina Thomas, Rajesh Bordawekar, Charu C. Aggarwal, Philip S. Yu:
On Efficient Query Processing of Stream Counts on the Cell Processor. ICDE 2009: 748-759 - [c82]Charu C. Aggarwal:
On High Dimensional Projected Clustering of Uncertain Data Streams. ICDE 2009: 1152-1154 - [c81]Charu C. Aggarwal, Yan Li, Jianyong Wang, Jing Wang:
Frequent pattern mining with uncertain data. KDD 2009: 29-38 - [c80]Charu C. Aggarwal:
On Segment-Based Stream Modeling and Its Applications. SDM 2009: 721-732 - [c79]Charu C. Aggarwal, Philip S. Yu:
Online Auctions: There Can Be Only One. CEC 2009: 176-181 - [r1]Charu C. Aggarwal:
Classification in Streams. Encyclopedia of Database Systems 2009: 340-341 - 2008
- [j38]Charu C. Aggarwal, Philip S. Yu:
A framework for condensation-based anonymization of string data. Data Min. Knowl. Discov. 16(3): 251-275 (2008) - [j37]Charu C. Aggarwal, Philip S. Yu:
On static and dynamic methods for condensation-based privacy-preserving data mining. ACM Trans. Database Syst. 33(1): 2:1-2:39 (2008) - [c78]Charu C. Aggarwal, Philip S. Yu:
A Framework for Clustering Uncertain Data Streams. ICDE 2008: 150-159 - [c77]Charu C. Aggarwal:
On Unifying Privacy and Uncertain Data Models. ICDE 2008: 386-395 - [c76]Charu C. Aggarwal, Philip S. Yu:
LOCUST: An Online Analytical Processing Framework for High Dimensional Classification of Data Streams. ICDE 2008: 426-435 - [c75]Charu C. Aggarwal, Philip S. Yu:
On High Dimensional Indexing of Uncertain Data. ICDE 2008: 1460-1461 - [c74]Charu C. Aggarwal, Philip S. Yu:
Outlier Detection with Uncertain Data. SDM 2008: 483-493 - [c73]Charu C. Aggarwal, Philip S. Yu:
On Indexing High Demensional Data with Uncertainty. SDM 2008: 621-631 - [p9]Charu C. Aggarwal, Philip S. Yu:
Privacy-Preserving Data Mining: A Survey. Handbook of Database Security 2008: 431-460 - [p8]Charu C. Aggarwal, Philip S. Yu:
An Introduction to Privacy-Preserving Data Mining. Privacy-Preserving Data Mining 2008: 1-9 - [p7]Charu C. Aggarwal, Philip S. Yu:
A General Survey of Privacy-Preserving Data Mining Models and Algorithms. Privacy-Preserving Data Mining 2008: 11-52 - [p6]Charu C. Aggarwal, Philip S. Yu:
A Survey of Randomization Methods for Privacy-Preserving Data Mining. Privacy-Preserving Data Mining 2008: 137-156 - [p5]Charu C. Aggarwal:
Privacy and the Dimensionality Curse. Privacy-Preserving Data Mining 2008: 433-460 - [e3]Charu C. Aggarwal, Philip S. Yu:
Privacy-Preserving Data Mining - Models and Algorithms. Advances in Database Systems 34, Springer 2008, ISBN 978-0-387-70991-8 [contents] - 2007
- [j36]Charu C. Aggarwal:
Toward Exploratory Test-Instance-Centered Diagnosis in High-Dimensional Classification. IEEE Trans. Knowl. Data Eng. 19(8): 1001-1015 (2007) - [c72]Charu C. Aggarwal:
On Randomization, Public Information and the Curse of Dimensionality. ICDE 2007: 136-145 - [c71]Charu C. Aggarwal:
On Density Based Transforms for Uncertain Data Mining. ICDE 2007: 866-875 - [c70]Charu C. Aggarwal, Philip S. Yu:
On string classification in data streams. KDD 2007: 36-45 - [c69]Charu C. Aggarwal, Na Ta, Jianyong Wang, Jianhua Feng, Mohammed Javeed Zaki:
Xproj: a framework for projected structural clustering of xml documents. KDD 2007: 46-55 - [c68]Charu C. Aggarwal:
A framework for classification and segmentation of massive audio data streams. KDD 2007: 1013-1017 - [c67]Charu C. Aggarwal, Philip S. Yu:
On Privacy-Preservation of Text and Sparse Binary Data with Sketches. SDM 2007: 57-67 - [c66]Charu C. Aggarwal:
On Point Sampling Versus Space Sampling for Dimensionality Reduction. SDM 2007: 192-203 - [c65]Charu C. Aggarwal, Philip S. Yu:
On Anonymization of String Data. SDM 2007: 419-424 - [c64]Jianyong Wang, Yuzhou Zhang, Lizhu Zhou, George Karypis, Charu C. Aggarwal:
Discriminating Subsequence Discovery for Sequence Clustering. SDM 2007: 605-610 - [c63]Kun-Lung Wu, Philip S. Yu, Bugra Gedik, Kirsten Hildrum, Charu C. Aggarwal, Eric Bouillet, Wei Fan, David George, Xiaohui Gu, Gang Luo, Haixun Wang:
Challenges and Experience in Prototyping a Multi-Modal Stream Analytic and Monitoring Application on System S. VLDB 2007: 1185-1196 - [p4]Charu C. Aggarwal:
An Introduction to Data Streams. Data Streams - Models and Algorithms 2007: 1-8 - [p3]Charu C. Aggarwal, Jiawei Han, Jianyong Wang, Philip S. Yu:
On Clustering Massive Data Streams: A Summarization Paradigm. Data Streams - Models and Algorithms 2007: 9-38 - [p2]Charu C. Aggarwal:
A Survey of Change Diagnosis Algorithms in Evolving Data Streams. Data Streams - Models and Algorithms 2007: 85-102 - [p1]Charu C. Aggarwal, Philip S. Yu:
A Survey of Synopsis Construction in Data Streams. Data Streams - Models and Algorithms 2007: 169-207 - [e2]Charu C. Aggarwal:
Data Streams - Models and Algorithms. Advances in Database Systems 31, Springer 2007, ISBN 978-0-387-28759-1 [contents] - 2006
- [j35]Charu C. Aggarwal:
On the use of Human-Computer Interaction for Projected Nearest Neighbor Search. Data Min. Knowl. Discov. 13(1): 89-117 (2006) - [j34]Mohammed Javeed Zaki, Charu C. Aggarwal:
XRules: An effective algorithm for structural classification of XML data. Mach. Learn. 62(1-2): 137-170 (2006) - [j33]Charu C. Aggarwal, Jiawei Han, Jianyong Wang, Philip S. Yu:
A Framework for On-Demand Classification of Evolving Data Streams. IEEE Trans. Knowl. Data Eng. 18(5): 577-589 (2006) - [c62]Charu C. Aggarwal:
On Futuristic Query Processing in Data Streams. EDBT 2006: 41-58 - [c61]Charu C. Aggarwal, Chen Chen, Jiawei Han:
On the Inverse Classification Problem and its Applications. ICDE 2006: 111 - [c60]Charu C. Aggarwal, Jian Pei, Bo Zhang:
On privacy preservation against adversarial data mining. KDD 2006: 510-516 - [c59]Charu C. Aggarwal:
On Temporal Evolution in Data Streams. PKDD 2006: 1 - [c58]Charu C. Aggarwal:
Representation is Everything: Towards Efficient and Adaptable Similarity Measures for Biological Data. SDM 2006: 210-221 - [c57]Charu C. Aggarwal:
A Framework for Local Supervised Dimensionality Reduction of High Dimensional Data. SDM 2006: 360-371 - [c56]Charu C. Aggarwal, Philip S. Yu:
A Framework for Clustering Massive Text and Categorical Data Streams. SDM 2006: 479-483 - [c55]Charu C. Aggarwal:
On Biased Reservoir Sampling in the Presence of Stream Evolution. VLDB 2006: 607-618 - 2005
- [j32]Charu C. Aggarwal, Paul S. Bradley:
On the Use of Wavelet Decomposition for String Classification. Data Min. Knowl. Discov. 10(2): 117-139 (2005) - [j31]Charu C. Aggarwal, Jiawei Han, Jianyong Wang, Philip S. Yu:
On High Dimensional Projected Clustering of Data Streams. Data Min. Knowl. Discov. 10(3): 251-273 (2005) - [j30]Charu C. Aggarwal:
On Change Diagnosis in Evolving Data Streams. IEEE Trans. Knowl. Data Eng. 17(5): 587-600 (2005) - [j29]Charu C. Aggarwal, Philip S. Yu:
An effective and efficient algorithm for high-dimensional outlier detection. VLDB J. 14(2): 211-221 (2005) - [c54]Charu C. Aggarwal, David P. Olshefski, Debanjan Saha, Zon-Yin Shae, Philip S. Yu:
CSR: Speaker Recognition from Compressed VoIP Packet Stream. ICME 2005: 970-973 - [c53]Charu C. Aggarwal, Philip S. Yu:
On Clustering Techniques for Change Diagnosis in Data Streams. WEBKDD 2005: 139-157 - [c52]Charu C. Aggarwal:
Towards exploratory test instance specific algorithms for high dimensional classification. KDD 2005: 526-531 - [c51]Charu C. Aggarwal, Philip S. Yu:
Online Analysis of Community Evolution in Data Streams. SDM 2005: 56-67 - [c50]Charu C. Aggarwal:
On Abnormality Detection in Spuriously Populated Data Streams. SDM 2005: 80-91 - [c49]Charu C. Aggarwal, Philip S. Yu:
On Variable Constraints in Privacy Preserving Data Mining. SDM 2005: 115-125 - [c48]Charu C. Aggarwal:
On k-Anonymity and the Curse of Dimensionality. VLDB 2005: 901-909 - 2004
- [j28]Charu C. Aggarwal:
On Leveraging User Access Patterns for Topic Specific Crawling. Data Min. Knowl. Discov. 9(2): 123-145 (2004) - [j27]Charu C. Aggarwal, Stephen C. Gates, Philip S. Yu:
On Using Partial Supervision for Text Categorization. IEEE Trans. Knowl. Data Eng. 16(2): 245-255 (2004) - [j26]Charu C. Aggarwal:
A Human-Computer Interactive Method for Projected Clustering. IEEE Trans. Knowl. Data Eng. 16(4): 448-460 (2004) - [j25]Charu C. Aggarwal:
An Efficient Subspace Sampling Framework for High-Dimensional Data Reduction, Selectivity Estimation, and Nearest-Neighbor Search. IEEE Trans. Knowl. Data Eng. 16(10): 1247-1262 (2004) - [c47]Charu C. Aggarwal, Philip S. Yu:
A Condensation Approach to Privacy Preserving Data Mining. EDBT 2004: 183-199 - [c46]Charu C. Aggarwal, Jiawei Han, Jianyong Wang, Philip S. Yu:
On demand classification of data streams. KDD 2004: 503-508 - [c45]Charu C. Aggarwal, Jiawei Han, Jianyong Wang, Philip S. Yu:
A Framework for Projected Clustering of High Dimensional Data Streams. VLDB 2004: 852-863 - 2003
- [j24]Srinivasan Parthasarathy, Charu C. Aggarwal:
On the Use of Conceptual Reconstruction for Mining Massively Incomplete Data Sets. IEEE Trans. Knowl. Data Eng. 15(6): 1512-1521 (2003) - [c44]Chung-Sheng Li, Charu C. Aggarwal, Murray Campbell, Yuan-Chi Chang, Gregory Glass, Vijay S. Iyengar, Mahesh Joshi, Ching-Yung Lin, Milind R. Naphade, John R. Smith, Belle L. Tseng, Min Wang, Kun-Lung Wu, Philip S. Yu:
Epi-SPIRE: a system for environmental and public health activity monitoring. ICME 2003: 713-716 - [c43]Charu C. Aggarwal:
Towards systematic design of distance functions for data mining applications. KDD 2003: 9-18 - [c42]Mohammed Javeed Zaki, Charu C. Aggarwal:
XRules: an effective structural classifier for XML data. KDD 2003: 316-325 - [c41]Charu C. Aggarwal, Dakshi Agrawal:
On nearest neighbor indexing of nonlinear trajectories. PODS 2003: 252-259 - [c40]Charu C. Aggarwal:
A Framework for Change Diagnosis of Data Streams. SIGMOD Conference 2003: 575-586 - [c39]Charu C. Aggarwal, Jiawei Han, Jianyong Wang, Philip S. Yu:
A Framework for Clustering Evolving Data Streams. VLDB 2003: 81-92 - [e1]Mohammed Javeed Zaki, Charu C. Aggarwal:
Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery, DMKD 2003, San Diego, California, USA, June 13, 2003. ACM 2003 [contents] - 2002
- [j23]Charu C. Aggarwal, Joel L. Wolf, Philip S. Yu:
Adaptive Piggybacking Schemes for Video-On-Demand Systems. Multim. Tools Appl. 16(3): 231-250 (2002) - [j22]Charu C. Aggarwal, James B. Orlin:
On multiroute maximum flows in networks. Networks 39(1): 43-52 (2002) - [j21]Charu C. Aggarwal:
Towards Effective and Interpretable Data Mining by Visual Interaction. SIGKDD Explor. 3(2): 11-22 (2002) - [j20]Charu C. Aggarwal, Cecilia Magdalena Procopiuc, Philip S. Yu:
Finding Localized Associations in Market Basket Data. IEEE Trans. Knowl. Data Eng. 14(1): 51-62 (2002) - [j19]Charu C. Aggarwal, Philip S. Yu:
Redefining Clustering for High-Dimensional Applications. IEEE Trans. Knowl. Data Eng. 14(2): 210-225 (2002) - [j18]Charu C. Aggarwal, Zheng Sun, Philip S. Yu:
Fast Algorithms for Online Generation of Profile Association Rules. IEEE Trans. Knowl. Data Eng. 14(5): 1017-1028 (2002) - [c38]Charu C. Aggarwal:
An Intuitive Framework for Understanding Changes in Evolving Data Streams. ICDE 2002: 261 - [c37]Charu C. Aggarwal:
Towards Meaningful High-Dimensional Nearest Neighbor Search by Human-Computer Interaction. ICDE 2002: 593-604 - [c36]Charu C. Aggarwal:
On effective classification of strings with wavelets. KDD 2002: 163-172 - [c35]Charu C. Aggarwal:
Collaborative crawling: mining user experiences for topical resource discovery. KDD 2002: 423-428 - [c34]Charu C. Aggarwal:
Hierarchical subspace sampling: a unified framework for high dimensional data reduction, selectivity estimation and nearest neighbor search. SIGMOD Conference 2002: 452-463 - [c33]Charu C. Aggarwal, Philip S. Yu:
An Automated System for Web Portal Personalization. VLDB 2002: 1031-1040 - 2001
- [j17]Ramesh C. Agarwal, Charu C. Aggarwal, V. V. V. Prasad:
A Tree Projection Algorithm for Generation of Frequent Item Sets. J. Parallel Distributed Comput. 61(3): 350-371 (2001) - [j16]Charu C. Aggarwal:
Towards Long Pattern Generation in Dense Databases. SIGKDD Explor. 3(1): 20-26 (2001) - [j15]Charu C. Aggarwal:
Re-designing Distance Functions and Distance-Based Applications for High Dimensional Data. SIGMOD Rec. 30(1): 13-18 (2001) - [j14]Charu C. Aggarwal, Joel L. Wolf, Philip S. Yu:
The Maximum Factor Queue Length Batching Scheme for Video-on-Demand Systems. IEEE Trans. Computers 50(2): 97-110 (2001) - [j13]Charu C. Aggarwal, Philip S. Yu:
A New Approach to Online Generation of Association Rules. IEEE Trans. Knowl. Data Eng. 13(4): 527-540 (2001) - [j12]Charu C. Aggarwal, Philip S. Yu:
Mining Associations with the Collective Strength Approach. IEEE Trans. Knowl. Data Eng. 13(6): 863-873 (2001) - [j11]Charu C. Aggarwal, Fatima Al-Garawi, Philip S. Yu:
On the design of a learning crawler for topical resource discovery. ACM Trans. Inf. Syst. 19(3): 286-309 (2001) - [c32]Sang-Wook Kim, Charu C. Aggarwal, Philip S. Yu:
Effective Nearest Neighbor Indexing with the Euclidean Metric. CIKM 2001: 9-16 - [c31]Charu C. Aggarwal, Philip S. Yu:
On Effective Conceptual Indexing and Similarity Search in Text Data. ICDM 2001: 3-10 - [c30]Charu C. Aggarwal, Alexander Hinneburg, Daniel A. Keim:
On the Surprising Behavior of Distance Metrics in High Dimensional Spaces. ICDT 2001: 420-434 - [c29]Charu C. Aggarwal:
A human-computer cooperative system for effective high dimensional clustering. KDD 2001: 221-226 - [c28]Charu C. Aggarwal, Srinivasan Parthasarathy:
Mining massively incomplete data sets by conceptual reconstruction. KDD 2001: 227-232 - [c27]Charu C. Aggarwal:
On the Effects of Dimensionality Reduction on High Dimensional Similarity Search. PODS 2001 - [c26]Dakshi Agrawal, Charu C. Aggarwal:
On the Design and Quantification of Privacy Preserving Data Mining Algorithms. PODS 2001 - [c25]Charu C. Aggarwal, Philip S. Yu:
Outlier Detection for High Dimensional Data. SIGMOD Conference 2001: 37-46 - [c24]Kun-Lung Wu, Charu C. Aggarwal, Philip S. Yu:
Personalization with Dynamic Profiler. WECWIS 2001: 12-20 - [c23]Charu C. Aggarwal, Fatima Al-Garawi, Philip S. Yu:
Intelligent crawling on the World Wide Web with arbitrary predicates. WWW 2001: 96-105 - 2000
- [j10]Charu C. Aggarwal, Philip S. Yu:
Data Mining Techniques for Personalization. IEEE Data Eng. Bull. 23(1): 4-9 (2000) - [j9]Kenneth A. Ross, Charu C. Aggarwal, Alfons Kemper, Sunita Sarawagi, S. Sudarshan, Mihalis Yannakakis:
Reminiscences on Influential Papers. SIGMOD Rec. 29(3): 52-54 (2000) - [c22]Charu C. Aggarwal, Joel L. Wolf, Kun-Lung Wu, Philip S. Yu:
The Intelligent Recommendation Analyzer. ICDCS Workshop of Knowledge Discovery and Data Mining in the World-Wide Web 2000: F67-F72 - [c21]Ramesh C. Agarwal, Charu C. Aggarwal, V. V. V. Prasad:
Depth first generation of long patterns. KDD 2000: 108-118 - [c20]Charu C. Aggarwal, Philip S. Yu:
The IGrid index: reversing the dimensionality curse for similarity indexing in high dimensional space. KDD 2000: 119-129 - [c19]Charu C. Aggarwal, Philip S. Yu:
Finding Generalized Projected Clusters In High Dimensional Spaces. SIGMOD Conference 2000: 70-81 - [c18]Alexander Hinneburg, Charu C. Aggarwal, Daniel A. Keim:
What Is the Nearest Neighbor in High Dimensional Spaces? VLDB 2000: 506-515
1990 – 1999
- 1999
- [j8]Charu C. Aggarwal, Joel L. Wolf, Philip S. Yu, Marina A. Epelman:
Using Unbalanced Trees for Indexing Multidimensional Objects. Knowl. Inf. Syst. 1(3): 157-192 (1999) - [j7]Charu C. Aggarwal, Joel L. Wolf, Philip S. Yu:
Design and Analysis of Permutation-Based Pyramid Broadcasting. Multim. Syst. 7(6): 439-448 (1999) - [j6]Charu C. Aggarwal, Joel L. Wolf, Philip S. Yu:
Caching on the World Wide Web. IEEE Trans. Knowl. Data Eng. 11(1): 95-107 (1999) - [c17]Charu C. Aggarwal, Joel L. Wolf, Kun-Lung Wu, Philip S. Yu:
Horting Hatches an Egg: A New Graph-Theoretic Approach to Collaborative Filtering. KDD 1999: 201-212 - [c16]Charu C. Aggarwal, Stephen C. Gates, Philip S. Yu:
On the Merits of Building Categorization Systems by Supervised Clustering. KDD 1999: 352-356 - [c15]Charu C. Aggarwal, Mark S. Squillante, Joel L. Wolf, Philip S. Yu, Jay Sethuraman:
Optimizing Profits in the Broadcast Delivery of Multimedia Products. Multimedia Information Systems 1999: 88-95 - [c14]Charu C. Aggarwal, Philip S. Yu:
Data Mining Techniques for Associations, Clustering and Classification. PAKDD 1999: 13-23 - [c13]Charu C. Aggarwal, Philip S. Yu:
On Text Mining Techniques for Personalization. RSFDGrC 1999: 12-18 - [c12]Charu C. Aggarwal, Cecilia Magdalena Procopiuc, Joel L. Wolf, Philip S. Yu, Jong Soo Park:
Fast Algorithms for Projected Clustering. SIGMOD Conference 1999: 61-72 - [c11]Charu C. Aggarwal, Joel L. Wolf, Philip S. Yu:
A New Method for Similarity Indexing of Market Basket Data. SIGMOD Conference 1999: 407-418 - 1998
- [j5]Charu C. Aggarwal, Philip S. Yu:
Mining Large Itemsets for Association Rules. IEEE Data Eng. Bull. 21(1): 23-31 (1998) - [j4]Charu C. Aggarwal, Joel L. Wolf, Philip S. Yu:
Optimization issues in multimedia systems. Int. J. Intell. Syst. 13(12): 1113-1135 (1998) - [j3]Charu C. Aggarwal, Ravindra K. Ahuja, Jianxiu Hao, James B. Orlin:
Diagnosing infeasibilities in network flow problems. Math. Program. 81: 263-280 (1998) - [c10]Charu C. Aggarwal, Zheng Sun, Philip S. Yu:
Online Algorithms for Finding Profile Association Rules. CIKM 1998: 86-95 - [c9]Charu C. Aggarwal, Philip S. Yu:
Online Generation of Association Rules. ICDE 1998: 402-411 - [c8]Charu C. Aggarwal, Joel L. Wolf, Philip S. Yu:
A Framework for the Optimizing of WWW Advertising. Trends in Distributed Systems for Electronic Commerce 1998: 1-10 - [c7]Charu C. Aggarwal, Zheng Sun, Philip S. Yu:
Online Generation of Profile Association Rules. KDD 1998: 129-133 - [c6]Charu C. Aggarwal, Philip S. Yu:
A New Framework For Itemset Generation. PODS 1998: 18-24 - 1997
- [j2]Charu C. Aggarwal, James B. Orlin, Ray P. Tai:
Optimized Crossover for the Independent Set Problem. Oper. Res. 45(2): 226-234 (1997) - [c5]Charu C. Aggarwal, Philip S. Yu:
On Disk Caching of Web Objects in Proxy Servers. CIKM 1997: 238-245 - [c4]Charu C. Aggarwal, Joel L. Wolf, Philip S. Yu, Marina A. Epelman:
The S-Tree: An Efficient Index for Multidimensional Objects. SSD 1997: 350-373 - 1996
- [c3]Charu C. Aggarwal, Joel L. Wolf, Philip S. Yu:
A Permutation-Based Pyramid Broadcasting Scheme for Video-on-Demand Systems. ICMCS 1996: 118-126 - [c2]Charu C. Aggarwal, Joel L. Wolf, Philip S. Yu:
On Optimal Batching Policies for Video-on-Demand Storage Servers. ICMCS 1996: 253-258 - [c1]Charu C. Aggarwal, Joel L. Wolf, Philip S. Yu:
On Optimal Piggyback Merging Policies for Video-on-Demand Systems. SIGMETRICS 1996: 200-209 - 1995
- [j1]Charu C. Aggarwal, N. Jain, P. Gupta:
An Efficient Selection Algorithm on the Pyramid. Inf. Process. Lett. 53(1): 37-47 (1995)
Coauthor Index
Guo-Jun Qi
aka: Guojun Qi
aka: Guojun Qi
[j102] [c234] [c226] [c224] [c216] [c200] [c197] [c195] [c165] [j70] [c156] [j64] [j63] [c143] [p38] [c126] [j55] [j54] [c123] [c121] [c117] [c114] [c104] [c102] [c99] [c97] [j45] [j44] [j43] [c91] [c88] [c86] [j40] [j39] [c83] [c79] [j38] [j37] [c78] [c76] [c75] [c74] [c73] [p9] [p8] [p7] [p6] [e3] [c70] [c67] [c65] [c63] [p3] [p1] [j33] [c56] [j31] [j29] [c54] [c53] [c51] [c49] [j27] [c47] [c46] [c45] [c44] [c39] [j23] [j20] [j19] [j18] [c33] [j14] [j13] [j12] [j11] [c32] [c31] [c25] [c24] [c23] [j10] [c22] [c20] [c19] [j8] [j7] [j6] [c17] [c16] [c15] [c14] [c13] [c12] [c11] [j5] [j4] [c10] [c9] [c8] [c7] [c6] [c5] [c4] [c3] [c2] [c1]
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