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

fYear

2012

fDate

10-15 June 2012

Firstpage

1

Lastpage

5

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on

Conference_Location

Brisbane, QLD

ISSN

1098-7584

Print_ISBN

978-1-4673-1507-4

Electronic_ISBN

1098-7584

Type

conf

DOI

10.1109/FUZZ-IEEE.2012.6251351

Filename

6251351