AOG-ags Algorithms and Applications
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- Wang L., Lu J., Lu J., Yip J. (2007) AOG-ags Algorithms and Applications. In: Alhajj R., Gao H., Li J., Li X., Zaïane O.R. (eds) Advanced Data Mining and Applications. ADMA 2007. Lecture Notes in Computer Science, vol 4632. Springer, Berlin, Heidelberg
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.
KeywordsAttribute-oriented generalization (AOG) Concept hierarchy trees Attributes’ generalization sequences (AGS) Equivalence partition trees Interestingness of AGS
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