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Fuzzy Transfer Learning for Prediction in Data-Shortage and Rapidly-Changing Environments

Funding: 2014: $134,000
2015: $120,000
2016: $140,000

Project Member(s): Lu, J., Zhang, G.

Funding or Partner Organisation: University of Alberta
Australian Research Council (ARC Discovery Projects)

Start year: 2014

Summary: Collecting sufficient up-to-date data to train a learning model for data analysis and prediction is difficult and expensive. This project will develop a Fuzzy Transfer Learning methodology, using Information Granularity theory, that exploits data with different features and/or distributions available in other, similar systems, to provide accurate learning-based prediction for current problems. It will establish a new research direction, Fuzzy Transfer Learning for Prediction, and the outcomes will enable Government and industry to better use past experience to make more accurate predictions and decisions. Highly significant benefits will also accrue in the data analytics, business intelligence and decision making research fields.

Publications:

Hao, P, Zhang, G, Martinez, L & Lu, J 2019, 'Regularizing Knowledge Transfer in Recommendation With Tag-Inferred Correlation', IEEE Transactions on Cybernetics.
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Wang, G, Zhang, G, Choi, KS & Lu, J 2019, 'Deep Additive Least Squares Support Vector Machines for Classification With Model Transfer', IEEE Transactions on Systems Man and Cybernetics: Systems, vol. 49, no. 7, pp. 1527-1540.
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Zuo, H, Lu, J, Zhang, G & Pedrycz, W 2019, 'Fuzzy Rule-Based Domain Adaptation in Homogeneous and Heterogeneous Spaces', IEEE Transactions on Fuzzy Systems, vol. 27, no. 2, pp. 348-361.
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Xuan, J, Lu, J, Zhang, G, Xu, RYD & Luo, X 2018, 'Doubly Nonparametric Sparse Nonnegative Matrix Factorization Based on Dependent Indian Buffet Processes', IEEE Transactions on Neural Networks and Learning Systems, pp. 1835-1849.
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Chen, H, Zhang, G, Zhu, D & Lu, J 2017, 'Topic-based technological forecasting based on patent data: A case study of Australian patents from 2000 to 2014', Technological Forecasting and Social Change, vol. 119, no. June 2017, pp. 39-52.
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Han, J, Lu, J & Zhang, G 2017, 'Tri-level decision-making for decentralized vendor-managed inventory', Information Sciences, vol. 421, pp. 85-103.
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Lu, J, Xuan, J, Zhang, G, Xu, YD & Luo, X 2017, 'Bayesian Nonparametric Relational Topic Model through Dependent Gamma Processes', IEEE Transactions on Knowledge and Data Engineering, vol. 29, no. 7, pp. 1357-1369.
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Mao, M, Lu, J, Zhang, G & Zhang, J 2017, 'Multirelational Social Recommendations via Multigraph Ranking', IEEE Transactions on Cybernetics, vol. 47, no. 12, pp. 4049-4061.
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Ramezani, F, Lu, J, Taheri, J & Zomaya, AY 2017, 'A Multi-Objective Load Balancing System for Cloud Environments', The Computer Journal, vol. 60, no. 9, pp. 1316-1337.
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Xuan, J, Lu, J, Zhang, G, Xu, RYD & Luo, X 2017, 'A Bayesian nonparametric model for multi-label learning', MACHINE LEARNING, vol. 106, no. 11, pp. 1787-1815.
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Xuan, J, Luo, X, Lu, J & Zhang, G 2017, 'Explicitly and implicitly exploiting the hierarchical structure for mining website interests on news events', INFORMATION SCIENCES, vol. 420, pp. 263-277.
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Yang, C, Zhu, D, Wang, X, Zhang, Y, Zhang, G & Lu, J 2017, 'Requirement-oriented core technological components’ identification based on SAO analysis', Scientometrics, vol. 112, no. 3, pp. 1229-1248.
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Zhang, Y, Qian, Y, Huang, Y, Guo, Y, Zhang, G & Lu, J 2017, 'An entropy-based indicator system for measuring the potential of patents in technological innovation: rejecting moderation', Scientometrics, vol. 111, no. 3, pp. 1925-1946.
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Zuo, H, Zhang, G, Pedrycz, W, Behbood, V & Lu, J 2017, 'Fuzzy Regression Transfer Learning in Takagi-Sugeno Fuzzy Models', IEEE Transactions on Fuzzy Systems, vol. 25, no. 6, pp. 1795-1807.
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Liu, F, Zhang, G & Lu, J 2017, 'Heterogeneous unsupervised domain adaptation based on fuzzy feature fusion', IEEE International Conference on Fuzzy Systems, IEEE International Conference on Fuzzy Systems, IEEE, Naples, Italy, pp. 1-6.
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Wang, G, Zhang, G, Choi, KS, Lam, KM & Lu, J 2017, 'An output-based knowledge transfer approach and its application in bladder cancer prediction', Proceedings of the International Joint Conference on Neural Networks, International Joint Conference on Neural Networks, IEEE, Anchorage, AK, USA, pp. 356-363.
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Yin, R, Li, K, Zhang, G & Lu, J 2017, 'Detecting overlapping protein complexes in dynamic protein-protein interaction networks by developing a fuzzy clustering algorithm', IEEE International Conference on Fuzzy Systems, IEEE International Conference on Fuzzy Systems, IEEE, Naples, Italy.
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Zuo, H, Zhang, G, Lu, J & Pedrycz, W 2017, 'Fuzzy Rule-based Transfer Learning for Label Space Adaptation', 2017 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE), IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), IEEE, Naples, ITALY.

Jialin, H, Guangquan, Z, Yaoguang, H & Jie, L 2016, 'A solution to bi/tri-level programming problems using particle swarm optimization', INFORMATION SCIENCES, vol. 370, pp. 519-537.
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Lu, J, Han, J, Hu, Y & Zhang, G 2016, 'Multilevel decision-making: A survey', INFORMATION SCIENCES, vol. 346, pp. 463-487.
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Luo, X, Xuan, J, Lu, J & Zhang, G 2016, 'Measuring the Semantic Uncertainty of News Events for Evolution Potential Estimation', ACM TRANSACTIONS ON INFORMATION SYSTEMS, vol. 34, no. 4.
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Pratama, M, Lu, J & Zhang, G 2016, 'Evolving Type-2 Fuzzy Classifier', IEEE TRANSACTIONS ON FUZZY SYSTEMS, vol. 24, no. 3, pp. 574-589.
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Pratama, M, Lu, J, Anavatti, S, Lughofer, E & Lim, C-P 2016, 'An incremental meta-cognitive-based scaffolding fuzzy neural network', NEUROCOMPUTING, vol. 171, pp. 89-105.
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Xuan, J, Luo, X, Zhang, G, Lu, J & Xu, Z 2016, 'Uncertainty Analysis for the Keyword System of Web Events', IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, vol. 46, no. 6, pp. 829-842.
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Zhang, Y, Shang, L, Huang, L, Porter, A, Zhu, D, Zhang, G & Lu, J 2016, 'A hybrid similarity measure method for patent portfolio analysis', Journal of Informetrics, vol. 10, no. 4, pp. 1108-1130.

Zhang, Y, Zhang, G, Chen, H, Porter, AL, Zhu, D & Lu, J 2016, 'Topic analysis and forecasting for science, technology and innovation: Methodology with a case study focusing on big data research', Technological Forecasting and Social Change, vol. 105, pp. 179-191.
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Gu, F, Zhang, G, Lu, J & Lin, CT 2016, 'Concept drift detection based on equal density estimation', Proceedings of the International Joint Conference on Neural Networks, IEEE International Joint Conference on Neural Networks, IEEE, Vancouver, Canada, pp. 24-30.
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Hao, P, Zhang, G & Lu, J 2016, 'Enhancing Cross Domain Recommendation with Domain Dependent Tags', 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), IEEE International Conference on Fuzzy Systems, IEEE, Vancouver, CANADA, pp. 1266-1273.
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Liu, A, Zhang, G, Lu, J, Lu, N & Lin, CT 2016, 'An online competence-based concept drift detection algorithm', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Australasian Joint Conference on Artificial Intelligence, Springer, Hobart, TAS, Australia, pp. 416-428.
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Ramezani, F, Naderpour, M & Lu, J 2016, 'A multi-objective optimization model for virtual machine mapping in cloud data centres', 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), IEEE International Conference on Fuzzy Systems, IEEE, Vancouver, BC, Canada, pp. 1259-1265.
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Zhang, T, Gu, M, Zhang, G & Lu, J 2016, 'A fast load pattern extraction approach based on dimension reduction and sampling', 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016, IEEE International Conference on Fuzzy Systems, IEEE, Vancouver, BC, Canada, pp. 1253-1258.
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Behbood, V, Lu, J, Zhang, G & Pedrycz, W 2015, 'Multi-Step Fuzzy Bridged Refinement Domain Adaptation Algorithm and Its Application to Bank Failure Prediction', IEEE Transactions on Fuzzy Systems, vol. 23, no. 6, pp. 1917-1935.
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Lu, J, Behbood, V, Hao, P, Zuo, H, Xue, S & Zhang, G 2015, 'Transfer Learning using Computational Intelligence: A Survey', Knowledge-Based Systems, vol. 80, pp. 14-23.
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Pratama, M, Anavatti, SG & Lu, J 2015, 'Recurrent Classifier Based on an Incremental Metacognitive-Based Scaffolding Algorithm', IEEE TRANSACTIONS ON FUZZY SYSTEMS, vol. 23, no. 6, pp. 2048-2066.
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Ramezani, F, Lu, J, Taheri, J & Hussain, FK 2015, 'Evolutionary algorithm-based multi-objective task scheduling optimization model in cloud environments', WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, vol. 18, no. 6, pp. 1737-1757.
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Xuan, J, Lu, J, Zhang, G & Luo, X 2015, 'Topic Model for Graph Mining', IEEE Transactions on Cybernetics, vol. 45, no. 2, pp. 2792-2803.
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Chen, H, Zhang, G, Lu, J & Zhu, D 2015, 'A Fuzzy Approach for Measuring Development of Topics in Patents Using Latent Dirichlet Allocation', 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2015), IEEE International Conference on Fuzzy Systems, IEEE, Istanbul, Turkey, pp. 1-7.
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Chen, H, Zhang, YI, Zhang, G, Zhu, D & Lu, J 2015, 'Modeling Technological Topic Changes in Patent Claims', Proceeding of 2015 Portland International Conference on Management of Engineering and Technology (PICMET), Portland International Center for Management of Engineering and Technology Conference, IEEE, Portland, USA, pp. 2049-2059.
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Ramezani, F, Naderpour, M & Lu, J 2015, 'Handling Uncertainty in Cloud Resource Management Using Fuzzy Bayesian Networks', Proceedings of the 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), IEEE International Conference on Fuzzy Systems, IEEE, Istanbul, Turkey.
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Xuan, J, Lu, J, Zhang, G, Xu, RYD & Luo, X 2015, 'Infinite author topic model based on mixed gamma-negative binomial process', Proceedings - IEEE International Conference on Data Mining, ICDM, IEEE International Conference on Data Mining, IEEE, Atlantic City, USA, pp. 489-498.
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Xue, S, Lu, J, Zhang, G & Xiong, L 2015, 'Heterogeneous feature space based task selection machine for unsupervised transfer learning', Proceedings - The 2015 10th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2015, International Conference on Intelligent Systems and Knowledge Engineering, IEEE, Taipei Taiwan, pp. 46-51.
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Xue, S, Lu, J, Zhang, G & Xiong, L 2015, 'SEIR immune strategy for instance weighted Naive bayes classification', Neural Information Processing (LNCS), International Conference on Neural Information Processing, Springer, Istanbul, Turkey, pp. 283-292.
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Keywords: Fuzzy Systems and Granularity,Intelligent Systems,Transfer Learning

FOR Codes: Neural, Evolutionary and Fuzzy Computation, Information Processing Services (incl. Data Entry and Capture), Expert Systems, Application Software Packages (excl. Computer Games), Decision Support and Group Support Systems, Computer Software and Services not elsewhere classified