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Modelling and Discovering Complex Interaction Relations Hidden in Group Behaviours in Businesses, Online and Social Communities

Funding: 2013: $120,000
2014: $120,000
2015: $120,000

Project Member(s): Cao, L.

Funding or Partner Organisation: University of Illinois at Chicago
Maastricht University (Maastricht University, Netherlands)
Australian Research Council (ARC Discovery Projects)

Start year: 2013

Summary: Complex interactions and relations hidden in groups form a major driver of exceptional behaviours and their dynamics in wide businesses, online and social communities. The inadequacy of related techniques for modelling and discovering complex relations in behaviour analysis and data mining limits the instant detection and effective intervention on suspicious group behaviours. This project will invent effective theories and algorithms for representing and learning diverse behavior interaction relations, their influence and evolution in large groups. The outcomes will advance complex relation learning and behaviour analysis, deepen the understanding of group events and activities, and safeguard businesses, online and social communities.

Publications:

Dong, X, Gong, Y & Cao, L 2018, 'F-NSP+: A fast negative sequential patterns mining method with self-adaptive data storage', Pattern Recognition, vol. 84, pp. 13-27.
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Cao, L 2017, 'Data science: A comprehensive overview', ACM Computing Surveys, vol. 50, no. 3.
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Hu, L, Cao, L, Cao, J, Gu, Z, Xu, G & Wang, J 2017, 'Improving the Quality of Recommendations for Users and Items in the Tail of Distribution', ACM Transactions on Information Systems, vol. 35, no. 3.
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Cao, L 2016, 'Data Science: Nature and Pitfalls', IEEE INTELLIGENT SYSTEMS, vol. 31, no. 5, pp. 66-75.

Cao, L, Dong, XJ & Zheng, Z 2016, 'E-NSP: Efficient negative sequential pattern mining', Artificial Intelligence, vol. 235, pp. 156-182.
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Li, F, Xu, G & Cao, L 2016, 'Two-level matrix factorization for recommender systems', Neural Computing and Applications, vol. 27, no. 8, pp. 2267-2278.
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Shen, B, Cao, L, Yao, M & Gao, Y 2016, 'Mining preferred navigation patterns by consolidating both selection and time preferences', World Wide Web.
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Pang, G, Cao, L & Chen, L 2016, 'Outlier detection in complex categorical data by modelling the feature value couplings', Proceedings of the 25th International Joint Conference on Artificial Intelligence, International Joint Conference on Artificial Intelligence (IJCAI), AAAI Press, New York.
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Pang, G, Cao, L, Chen, L & Liu, H 2016, 'Unsupervised Feature Selection for Outlier Detection by Modelling Hierarchical Value-Feature Couplings', Proceedings - IEEE International Conference on Data Mining, ICDM, IEEE International Conference on Data Mining, IEEE, Barcelona.
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Deng, Z, Cao, L, Jiang, Y & Wang, S 2015, 'Minimax Probability TSK Fuzzy System Classifier: A More Transparent and Highly Interpretable Classification Model', IEEE TRANSACTIONS ON FUZZY SYSTEMS, vol. 23, no. 4, pp. 813-826.
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Fan, X & Cao, L 2015, 'A convergence theorem for graph shift-type algorithms', Pattern Recognition, vol. 48, no. 8, pp. 2751-2760.
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Fan, X, Cao, L & Xu, RYD 2015, 'Dynamic Infinite Mixed-Membership Stochastic Blockmodel', IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, vol. 26, no. 9, pp. 2072-2085.
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Li, F, Xu, G & Cao, L 2015, 'Coupled Matrix Factorization within Non-IID Context', Proceedings, Part II, 19th Pacific-Asia Conference, PAKDD 2015, Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer, Ho Chi Minh City, Vietnam, pp. 707-719.
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Cao, L 2014, 'Non-IIDness Learning in Behavioral and Social Data', The Computer Journal, vol. 57, no. 9, pp. 1358-1370.
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Deng, Z, Choi, K-S, Cao, L & Wang, S 2014, 'T2FELA: Type-2 Fuzzy Extreme Learning Algorithm for Fast Training of Interval Type-2 TSK Fuzzy Logic System', IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, vol. 25, no. 4, pp. 664-676.
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Liu, B, Xiao, Y, Yu, PS, Cao, L, Zhang, Y & Hao, Z 2014, 'Uncertain One-Class Learning and Concept Summarization Learning on Uncertain Data Streams', IEEE Transactions on Knowledge and Data Engineering, vol. 26, no. 2, pp. 468-484.
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Liu, B, Xiao, Y, Yu, PS, Hao, Z & Cao, L 2014, 'An efficient orientation distance–based discriminative feature extraction method for multi-classification', Knowledge and Information Systems, vol. 39, no. 2, pp. 409-433.
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Liu, B, Xiao, YS, Yu, PS, Hao, ZF & Cao, LB 2014, 'An Efficient Approach for Outlier Detection with Imperfect Data Labels', IEEE Transactions on Knowledge and Data Engineering, vol. 26, no. 7, pp. 1602-1616.
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Xiao, Y, Liu, B, Hao, Z & Cao, L 2014, 'A K-Farthest-Neighbor-based approach for support vector data description', Applied Intelligence, vol. 41, no. 1, pp. 196-211.
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Xiao, YS, Liu, B, Hao, ZF & Cao, LB 2014, 'A Similarity-Based Classification Framework for Multiple-Instance Learning', IEEE Transactions on Cybernetics, vol. 44, no. 4, pp. 500-515.
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Wang, C, Cao, L & Miao, B 2013, 'Optimal feature selection for sparse linear discriminant analysis and its applications in gene expression data', Computational Statistics and Data Analysis, vol. 66, pp. 140-149.
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Wang, C, Yang, J, Miao, B & Cao, L 2013, 'Identity tests for high dimensional data using RMT', Journal of Multivariate Analysis, vol. 118, pp. 128-137.
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Zhou, J, Cao, L & Yang, N 2013, 'On the convergence of some possibilistic clustering algorithms', Fuzzy Optimization and Decision Making, vol. 12, no. 4, pp. 415-432.
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Li, F, Xu, G, Cao, L, Fan, X & Niu, Z 2013, 'CGMF: Coupled Group-Based Matrix Factorization for Recommender System', Lecture Notes in Computer Science, International Conference on Web Information Systems Engineering, Springer, Nanjing, China, pp. 289-298.
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Li, W, Cao, L, Zhao, D, Cui, X & Yang, J 2013, 'CRNN: Integrating classification rules into neural network', The 2013 International Joint Conference on Neural Networks, IJCNN 2013, Dallas, TX, USA, August 4-9, 2013, IEEE International Joint Conference on Neural Networks, IEEE, Dallas, TX, USA, pp. 1-8.
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Liu, B, Xiao, Y, Yu, P, Cao, L & Hao, Z 2013, 'Robust Textual Data Streams Mining Based on Continuous Transfer Learning', Proceedings of the 13th SIAM International Conference on Data Mining, SIAM International Conference on Data Mining, SIAM, Austin, Texas, USA, pp. 731-739.
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Wei, W, Li, J, Cao, L, Sun, J, Liu, C & Li, M 2013, 'Optimal Allocation of High Dimensional Assets through Canonical Vines', Advances in Knowledge Discovery and Data Mining: 17th Pacific-Asia Conference, PAKDD 2013, Gold Coast, Australia, April 14-17, 2013, Proceedings, Part I, Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer, Gold Coast, Australia, pp. 366-377.
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Yu, Y, Wang, C, Gao, Y, Cao, L & Chen, X 2013, 'A Coupled Clustering Approach for Items Recommendation', Lecture Notes in Computer Science, Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer, Gold Coast, Australia, pp. 365-376.
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Keywords: Data mining,Behavior analysis

FOR Codes: Pattern Recognition and Data Mining, Application Tools and System Utilities, Simulation and Modelling, Information Processing Services (incl. Data Entry and Capture)