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
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;
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
DOI :
10.1109/CCDC.2008.4597754
