Title :
Maintaining Pre-large FUSP Trees for Record Deletion
Author :
Hong, Tzung-Pei ; Chen, Hsin-Yi ; Lin, Chun-Wei ; Li, Sheng-Tun
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Univ. of Kaohsiung, Kaohsiung, Taiwan
fDate :
June 30 2009-July 2 2009
Abstract :
In the past, a pre-large fast-updated sequential pattern tree (pre-large FUSP tree) structure was proposed to effectively handle newly inserted customer sequences for data mining. Since data deletion also commonly occurs in real applications, in this paper, we thus propose a maintenance algorithm for pre-large FUSP trees when records are deleted from the mined database. Pre-large sequences act like buffers and are used to reduce the movement of sequences directly from large to small and vice-versa when records are deleted. Experimental results also show that the proposed pre-large FUSP-tree maintenance algorithm for record deletion has a good performance when compared to the batch maintenance algorithm.
Keywords :
data mining; tree data structures; FUSP tree structure; data mining; fast-updated sequential pattern tree; maintenance algorithm; record deletion; Algorithm design and analysis; Association rules; Computer science; Data engineering; Data mining; Databases; Information management; Itemsets; Maintenance engineering; Tree data structures; FUSP tree; data mining; large sequences; prelarge sequences;
Conference_Titel :
New Trends in Information and Service Science, 2009. NISS '09. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-0-7695-3687-3
DOI :
10.1109/NISS.2009.194