Mining Multiple Information Sources through Collaborative and Comparative Analysis

Funding: 2010: $115,000
2011: $110,000
2012: $110,000

Project Member(s): Zhang, C.

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

Start year: 2010

Summary: Mining multiple information sources can provide rich knowledge which is difficult to discover by mining single data source. Comparing and collaborating multi-source data for mining are critical. This project aims to systematically investigate the theoretical foundations and practical solutions for mining multiple information sources, with the objective of delivering a unified multi-source collaborative and comparative mining framework. The expected outcomes are: (1) establishing the theoretical foundations for this emerging data mining research area, (2) benefiting key application areas, such as bioinformatics, business intelligence, and security informatics, and (3) helping maintain Australia's leading role in data mining research.

Publications:

Bin Li, Xingquan Zhu, Ruijiang Li & Chengqi Zhang 2015, 'Rating Knowledge Sharing in Cross-Domain Collaborative Filtering', IEEE Transactions on Cybernetics, vol. 45, no. 5, pp. 1068-1082.
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Fang, M, Yin, J, Zhu, X & Zhang, C 2015, 'TrGraph: Cross-Network Transfer Learning via Common Signature Subgraphs', IEEE Transactions on Knowledge and Data Engineering, vol. 27, no. 9, pp. 2536-2549.
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Wang, H, Zhang, P, Tsang, I, Chen, L & Zhang, C 1970, 'Defragging Subgraph Features for Graph Classification', Proceedings of the 24th ACM International on Conference on Information and Knowledge Management, CIKM'15: 24th ACM International Conference on Information and Knowledge Management, ACM, Melbourne, VIC, Australia, pp. 1687-1690.
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Fu, Y, Zhu, X & Li, B 2013, 'A survey on instance selection for active learning', Knowledge and Information Systems, vol. 35, no. 2, pp. 249-283.
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Li, B, Chen, L, Zhu, X & Zhang, C 2013, 'Noisy but non-malicious user detection in social recommender systems', World Wide Web, vol. 16, no. 5-6, pp. 677-699.
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Long, G, Chen, L, Zhu, X & Zhang, C 1970, 'TCSST', Proceedings of the 21st ACM international conference on Information and knowledge management, CIKM'12: 21st ACM International Conference on Information and Knowledge Management, ACM, Maui, Hawaii, USA, pp. 764-772.
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Zhu, Z, Zhu, X, Ye, Y, Guo, Y-F & Xue, X 1970, 'Parallel proximal support vector machine for high-dimensional pattern classification', Proceedings of the 21st ACM international conference on Information and knowledge management, CIKM'12: 21st ACM International Conference on Information and Knowledge Management, ACM, Hawaii, USA, pp. 2351-2354.
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He, D, Zhu, X & Wu, X 2011, 'MINING APPROXIMATE REPEATING PATTERNS FROM SEQUENCE DATA WITH GAP CONSTRAINTS', Computational Intelligence, vol. 27, no. 3, pp. 336-362.
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Zhang, P, Zhu, X, Shi, Y, Guo, L & Wu, X 2011, 'Robust ensemble learning for mining noisy data streams', Decision Support Systems, vol. 50, no. 2, pp. 469-479.
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Zhu, X, Li, B, Wu, X, He, D & Zhang, C 2011, 'CLAP: Collaborative pattern mining for distributed information systems', Decision Support Systems, vol. 52, no. 1, pp. 40-51.
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Liang, G, Zhu, X & Zhang, C 1970, 'An empirical study of bagging predictors for different learning algorithms', Proceedings of the National Conference on Artificial Intelligence, National Conference of the American Association for Artificial Intelligence, AAAI Press, San Francisco, California, US, pp. 1802-1803.

Keywords: Multiple Information Sources; Heterogeneous Data Collections; Data Mining; Multiple Source Collaborative mining; Multiple Source Comparative Mining;

FOR Codes: Information Systems, Computer Time Leasing, Sharing and Renting Services, Information Processing Services (incl. Data Entry and Capture), Library and Information Studies, Library and information studies , Information systems, technologies and services not elsewhere classified