Wang, L, Lu, J, Yip, YJ and Lu, J 2007, 'AOG-ags algorithms and applications' , in: Advanced Data Mining and Applications , Lecture Notes in Computer Science, 4632 , Springer Berlin / Heidelberg, pp. 323-334.

Full text not available from this repository.

Abstract

The attribute-oriented generalization (AOG for short) method is one of the most important data mining methods. In this paper, a reasonable approach of AOG (AOG-ags, attribute-oriented generalization based on attributes? generalization sequence), which expands the traditional AOG method efficiently, is proposed. By introducing equivalence partition trees, an optimization algorithm of the AOG-ags is devised. Defining interestingness of attributes? generalization sequences, the selection problem of attributes? generalization sequences is solved. Extensive experimental results show that the AOG-ags are useful and efficient. Particularly, by using the AOG-ags algorithm in a plant distributing dataset, some distributing rules for the species of plants in an area are found interesting.

Item Type:	Book Section
Additional Information:	From the The Third International Conference on Advanced Data Mining and Applications, Harbin, China, August 6-8, 2007
Themes:	Media, Digital Technology and the Creative Economy
Schools:	Colleges and Schools > College of Science & Technology Strategic Leadership Team
Publisher:	Springer Berlin / Heidelberg
Refereed:	No
ISBN:	9783-540738701
Depositing User:	Users 29196 not found.
Date Deposited:	14 Aug 2012 14:07
Last Modified:	17 Aug 2012 14:57
URI:	http://usir.salford.ac.uk/id/eprint/23122

Actions (login required)

Edit record (repository staff only)