Modeling and Efficient Mining of Intentional Knowledge of Outliers

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Seventh International Database Engineering and Applications Symposium (IDEAS'03)

Hong Kong, SAR

July 16-July 18

ISBN: 0-7695-1981-4

	ASCII Text	x
	Zhixiang Chen, Jian Tang, Ada Wai-Chee Fu, "Modeling and Efficient Mining of Intentional Knowledge of Outliers," Database Engineering and Applications Symposium, International, pp. 44, Seventh International Database Engineering and Applications Symposium (IDEAS'03), 2003.

	BibTex	x
	@article{ 10.1109/IDEAS.2003.1214910, author = {Zhixiang Chen and Jian Tang and Ada Wai-Chee Fu}, title = {Modeling and Efficient Mining of Intentional Knowledge of Outliers}, journal ={Database Engineering and Applications Symposium, International}, volume = {0}, year = {2003}, issn = {1098-8068}, pages = {44}, doi = {http://doi.ieeecomputersociety.org/10.1109/IDEAS.2003.1214910}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Database Engineering and Applications Symposium, International TI - Modeling and Efficient Mining of Intentional Knowledge of Outliers SN - 1098-8068 SP EP A1 - Zhixiang Chen, A1 - Jian Tang, A1 - Ada Wai-Chee Fu, PY - 2003 KW - outlier detection KW - knowledge sets KW - categorical similarity KW - behavioral similarity KW - outliered patterns VL - 0 JA - Database Engineering and Applications Symposium, International ER -

Zhixiang Chen, University of Texas-Pan American

Jian Tang, Chinese University of Hong Kong

Ada Wai-Chee Fu, Chinese University of Hong Kong

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IDEAS.2003.1214910

In this paper, we study in a general setting the notion of outliered patterns as intentional knowledge of outliers and algorithms to mine those patterns. Our contributions consist of a model for de.ning outliered patterns with the help of categorical and behavioral similarities of outliers, and efficient algorithms for mining knowledge sets of distance-based outliers and outliered patterns. Our algorithms require only very limited domain knowledge, and no classified information. We also present an empirical study to show the feasibility of our algorithms.

Index Terms:

outlier detection, knowledge sets, categorical similarity, behavioral similarity, outliered patterns

Citation:

Zhixiang Chen, Jian Tang, Ada Wai-Chee Fu, "Modeling and Efficient Mining of Intentional Knowledge of Outliers," ideas, pp.44, Seventh International Database Engineering and Applications Symposium (IDEAS'03), 2003

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