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: | Schools > No Research Centre |
| Publisher: | Springer Berlin / Heidelberg |
| Refereed: | No |
| Series Name: | Lecture Notes in Computer Science |
| ISBN: | 9783-540738701 |
| Depositing User: | Users 29196 not found. |
| Date Deposited: | 14 Aug 2012 13:07 |
| Last Modified: | 27 Aug 2021 22:58 |
| URI: | http://usir.salford.ac.uk/id/eprint/23122 |
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