Title :
A New Concise Representation Method of Generalized Frequent Itemsets
Author :
Yuxing Mao ; Chenghong Zhang ; Hong Ling
Author_Institution :
Sch. of Manage., Fudan Univ., Shanghai, China
Abstract :
Mining generalized frequent item sets is one of important research area in data mining. Because not only the taxonomy data is widely exist, but also the information provided by the generalized frequent item sets is richer and valuable than the traditional frequent item sets. Like the traditional mining, the number of the generalized frequent item set is also very large, which make it difficult to do further analysis. We propose a new method called CGIP-summary, which represent the whole frequent generalized item sets by a set profiles and the profiles used to more concise.
Keywords :
data mining; set theory; CGIP-summary method; closed generalized itemset profile summary; concise representation method; data mining; generalized frequent itemset mining; taxonomy data; Abstracts; Data mining; IP networks; Itemsets; Lattices; Taxonomy; generalized frequent itemset; profile summary; taxnomy;
Conference_Titel :
Computational Science and Engineering (CSE), 2012 IEEE 15th International Conference on
Conference_Location :
Nicosia
Print_ISBN :
978-1-4673-5165-2
Electronic_ISBN :
978-0-7695-4914-9
DOI :
10.1109/ICCSE.2012.21