DocumentCode
2561630
Title
An integrated updating Algorithm for mining maximal frequent patterns
Author
Yang Jun-rui ; Zhang Tie-jun ; Liu Nan-yan
Author_Institution
Dept. of Comput. Sci., Xi´an Univ. of Sci. & Technol., Xi´an
fYear
2008
fDate
2-4 July 2008
Firstpage
2396
Lastpage
2400
Abstract
The problem of mining maximal frequent patterns plays an essential role in mining association rules. In order to discover more useful maximal frequent patterns, users may adjust the minimum support while database changes. Therefore, we present a novel algorithm IUMFPA that makes use of improved FP-Tree structure and bit object for data expression. It can also utilize the former FP-Tree and the mined results sufficiently. The experimental results indicate that IUMFPA performs efficiently.
Keywords
data mining; tree data structures; IUMFPA; data mining; improved frequent pattern tree structure; integrated updating algorithm; maximal frequent patterns; mining association rules; Association rules; Data mining; Databases; Association Rule; Data Mining; Integrated Updating; Maximal Frequent Pattern;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference, 2008. CCDC 2008. Chinese
Conference_Location
Yantai, Shandong
Print_ISBN
978-1-4244-1733-9
Electronic_ISBN
978-1-4244-1734-6
Type
conf
DOI
10.1109/CCDC.2008.4597754
Filename
4597754
Link To Document