Objective and Subjective Algorithms for Grouping Association Rules

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Third IEEE International Conference on Data Mining (ICDM'03)

Melbourne, Florida

November 19-November 22

ISBN: 0-7695-1978-4

	ASCII Text	x
	Aijun An, Shakil Khan, Xiangji Huang, "Objective and Subjective Algorithms for Grouping Association Rules," Data Mining, IEEE International Conference on, pp. 477, Third IEEE International Conference on Data Mining (ICDM'03), 2003.

	BibTex	x
	@article{ 10.1109/ICDM.2003.1250956, author = {Aijun An and Shakil Khan and Xiangji Huang}, title = {Objective and Subjective Algorithms for Grouping Association Rules}, journal ={Data Mining, IEEE International Conference on}, volume = {0}, year = {2003}, isbn = {0-7695-1978-4}, pages = {477}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2003.1250956}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Data Mining, IEEE International Conference on TI - Objective and Subjective Algorithms for Grouping Association Rules SN - 0-7695-1978-4 SP EP A1 - Aijun An, A1 - Shakil Khan, A1 - Xiangji Huang, PY - 2003 KW - null VL - 0 JA - Data Mining, IEEE International Conference on ER -

Aijun An, York University, Toronto

Shakil Khan, York University, Toronto

Xiangji Huang, York University, Toronto

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDM.2003.1250956

We propose two algorithms for grouping and summarizing association rules. The first algorithm recursively groups rules according to the structure of the rules and generates a tree of clusters as a result. The second algorithm groups the rules according to the semantic distance between the rules by making use of an autometically tagged semantic tree-structured network of items. We provide a case study in which the proposed algorithms are evaluated. The results show that our grouping methods are effective and produce good grouping results.

Citation:

Aijun An, Shakil Khan, Xiangji Huang, "Objective and Subjective Algorithms for Grouping Association Rules," icdm, pp.477, Third IEEE International Conference on Data Mining (ICDM'03), 2003

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