Interpretation of association rules with multi-tier granule mining

Wu, Jingtong (2014) Interpretation of association rules with multi-tier granule mining. PhD thesis, Queensland University of Technology.


This study was a step forward to improve the performance for discovering useful knowledge – especially, association rules in this study – in databases. The thesis proposed an approach to use granules instead of patterns to represent knowledge implicitly contained in relational databases; and multi-tier structure to interpret association rules in terms of granules. Association mappings were proposed for the construction of multi-tier structure. With these tools, association rules can be quickly assessed and meaningless association rules can be justified according to the association mappings. The experimental results indicated that the proposed approach is promising.

Impact and interest:

4 citations in Web of Science®
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92 since deposited on 30 May 2014
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ID Code: 71455
Item Type: QUT Thesis (PhD)
Supervisor: Li, Yuefeng & Bruza, Peter
Keywords: Data mining, Association rule mining, Granule mining, Decision rules, Rough sets
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Institution: Queensland University of Technology
Deposited On: 30 May 2014 02:15
Last Modified: 09 Sep 2015 05:45

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