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.
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:||Schools > No Research Centre|
|Publisher:||Springer Berlin / Heidelberg|
|Series Name:||Lecture Notes in Computer Science|
|Depositing User:||Users 29196 not found.|
|Date Deposited:||14 Aug 2012 13:07|
|Last Modified:||30 Nov 2015 23:59|
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