Title :
Mining Up-to-Date Knowledge Based on Tree Structures
Author :
Lin, Chun-Wei ; Hong, Tzung-Pei ; Lu, Wen-Hsiang
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
Abstract :
In the past, the up-to-date patterns is proposed to mine the frequent itemsets within its corresponding lifetime. This hybrid method is based on the Apriori-like approach, which requests high computational cost and memory requirement. In this paper, the up-to-date pattern tree (UDP tree) is proposed to keep the up-to-date patterns in a tree structure. The experimental results show that the proposed approach has a better performance than the level-wise up-to-date algorithm.
Keywords :
data mining; Apriori-like approach; frequent itemsets; tree structures; up-to-date knowledge mining; Association rules; Computational efficiency; Computer science; Data mining; Frequency; Itemsets; Knowledge engineering; Pattern recognition; Transaction databases; Tree data structures; FP-tree; UDP-tree; data mining; temporal data mining; up-to-date pattern;
Conference_Titel :
Soft Computing and Pattern Recognition, 2009. SOCPAR '09. International Conference of
Conference_Location :
Malacca
Print_ISBN :
978-1-4244-5330-6
Electronic_ISBN :
978-0-7695-3879-2
DOI :
10.1109/SoCPaR.2009.36
