Interestingness, Peculiarity, and Multi-database Mining

San Jose, California November 29-December 02

DOI Bookmark:

http://doi.ieeecomputersociety.org/10.1109/ICDM.2001.989566

First IEEE International Conference o ...

	This Article
	PURCHASE ARTICLE: $19 PDF HTML IEEE Xplore Subscribers
	Share
	Email this Article to a friend
	Bibliographic References
	ASCII Text BibTex RefWorks Procite/RefMan/Endnote
	Add to:
	Digg Furl Spurl Blink Simpy Google Del.icio.us Y!MyWeb
	Search
	Similar Articles Articles by Ning Zhong Articles by Y.Y. Yao Articles by Muneaki Ohshima Articles by Setsuo Ohsuga

	ASCII Text	x
	Ning Zhong, Y.Y. Yao, Muneaki Ohshima, Setsuo Ohsuga, "Interestingness, Peculiarity, and Multi-database Mining," Data Mining, IEEE International Conference on, pp. 566, First IEEE International Conference on Data Mining (ICDM'01), 2001.

	BibTex	x
	@article{ 10.1109/ICDM.2001.989566, author = {Ning Zhong and Y.Y. Yao and Muneaki Ohshima and Setsuo Ohsuga}, title = {Interestingness, Peculiarity, and Multi-database Mining}, journal ={Data Mining, IEEE International Conference on}, volume = {0}, year = {2001}, isbn = {0-7695-1119-8}, pages = {566}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2001.989566}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Data Mining, IEEE International Conference on TI - Interestingness, Peculiarity, and Multi-database Mining SN - 0-7695-1119-8 SP EP A1 - Ning Zhong, A1 - Y.Y. Yao, A1 - Muneaki Ohshima, A1 - Setsuo Ohsuga, PY - 2001 VL - 0 JA - Data Mining, IEEE International Conference on ER -

In order to discover new, surprising, interesting patterns hidden in data, peculiarity oriented mining and multi-database mining are required. In the paper, we introduce peculiarity rules as new class of rules, which can be discovered from relatively low number of peculiar data by searching the relevance among the peculiar data. We give formal interpretation and comparison of three classes of rules: association rules, exception rules, and peculiarity rules, as well as describe how to mine more interesting peculiarity rules in multiple databases.

Citation:

Ning Zhong, Y.Y. Yao, Muneaki Ohshima, Setsuo Ohsuga, "Interestingness, Peculiarity, and Multi-database Mining," icdm, pp.566, First IEEE International Conference on Data Mining (ICDM'01), 2001

Peer Review Notice | Give Us Feedback

Usage of this product signifies your acceptance of the Terms of Use.