Title :
Incremental multiple fuzzy frequent pattern tree
Author :
Hong, Tzung-Pei ; Lin, Chun-Wei ; Lin, Tsung-Ching ; Wang, Shyue-Liang
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Univ. of Kaohsiung, Kaohsiung, Taiwan
Abstract :
In the past, the multiple fuzzy frequent pattern tree (MFFP tree) was proposed for extracting multiple fuzzy frequent itemsets from quantitative transactions. It kept the multiple transformed fuzzy regions of an item to form the multiple fuzzy frequent itemsets. In this paper, an incremental algorithm is proposed for efficiently mining multiple fuzzy frequent itemsets based on the FUP concepts and the MFFP-tree structure. Experimental results show that the proposed incremental algorithm runs faster than the batch one.
Keywords :
data mining; fuzzy set theory; FUP concepts; MFFP tree; MFFP-tree structure; incremental algorithm; incremental multiple fuzzy frequent pattern tree; multiple fuzzy frequent itemset extraction; multiple fuzzy frequent itemset mining; multiple fuzzy frequent itemsets; multiple transformed fuzzy regions; quantitative transactions; Algorithm design and analysis; Association rules; Educational institutions; Heuristic algorithms; Itemsets; data mining; dynamic database; fuzzy set; incremetnal mining; transaction insertion;
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1507-4
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZ-IEEE.2012.6251351
