Ontology-Based Group Pattern Discovery Systems for Mining Multiple Data Sources

Funding: 2005: $55,000
2006: $55,000
2007: $55,000

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

Start year: 2005

Summary: Pattern discovery from multiple data sources (MDS) is about finding patterns from different data sources. It becomes one of the crucial techniques because of globalization, e-commerce and online collaboration between organizations. This project will develop group pattern discovery systems for identifying useful patterns from MDSs based on local-pattern-analysis for attacking the MDS problem, mainly including a logical system for information enhancing, a logical system for solving conflictions, and a pattern discovery system. Our innovative method will lead to greatly reducing search cost and generating many more useful patterns. This project will deliver an ontology-based hybrid system for mining MDSs.

Publications:

Qin, Y & Zhang, S 2008, 'Empirical likelihood confidence intervals for differences between two datasets with missing data', Pattern Recognition Letters, vol. 29, no. 6, pp. 803-812.
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Zhang, S, Huang, Z, Zhang, J & Zhu, X 2008, 'Mining follow-up correlation patterns from time-related databases', Knowledge and Information Systems, vol. 14, no. 1, pp. 81-100.
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Zhang, S, Wu, X, Zhang, C & Lu, J 2008, 'Computing the minimum-support for mining frequent patterns', Knowledge and Information Systems, vol. 15, no. 2, pp. 233-257.
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Zhang, S, Zhang, J, Zhu, X, Qin, Y & Zhang, C 2008, 'Missing Value Imputation Based on Data Clustering', Lecture Notes in Computer Science, vol. 4750, no. 2008, pp. 128-138.
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Qin, Y, Zhang, S, Zhu, X, Zhang, J & Zhang, C 2007, 'Semi-parametric optimization for missing data imputation', Applied Intelligence, vol. 27, no. 1, pp. 79-88.
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Yan, X, Zhang, S & Zhang, C 2007, 'ON DATA STRUCTURES FOR ASSOCIATION RULE DISCOVERY', Applied Artificial Intelligence, vol. 21, no. 2, pp. 57-79.
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Zhang, S, Zhang, J & Zhang, C 2007, 'EDUA: An efficient algorithm for dynamic database mining', Information Sciences, vol. 177, no. 13, pp. 2756-2767.
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Zhang, S, Wang, R & Guo, Y 1970, 'Knowledge Science, Engineering and Management', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), International Conference on Knowledge Science, Engineering and Management, Springer Berlin Heidelberg, Guilin, China, pp. 612-624.
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Keywords: Data mining, Quality knowledge management, Model Logics, Knowledge discovery in databases, Pattern discovery, Multiple data sources,

FOR Codes: Information Storage, Retrieval and Management, Database Management, Other Artificial Intelligence, Application tools and system utilities, Information processing services, Application packages, Records and Information Management (excl. Business Records and Information Management), Artificial Intelligence and Image Processing not elsewhere classified, Information Processing Services (incl. Data Entry and Capture), Recordkeeping informatics, Graphics, augmented reality and games not elsewhere classified, Database systems, Information systems, technologies and services not elsewhere classified

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.