Title :
Anytime mining for multiuser applications
Author :
Zhang, Shichao ; Zhang, Chengqi
Author_Institution :
Fac. of Inf. Technol., Univ. of Technol., Sydney, NSW, Australia
fDate :
7/1/2002 12:00:00 AM
Abstract :
Database systems have been designed to serve multi-users in real-world applications. There are essential differences between mono- and multi-user applications when a database is very large. Therefore, this paper presents an "anytime" framework for mining very large databases which are shared by multi-users. Anytime mining is designed to generate approximate results such that these results can be accessed at any time while the system is autonomously mining a database.
Keywords :
data mining; database theory; probability; very large databases; anytime mining; association rule; data mining; instance selection; multiuser application; probability; very large databases; Australia; Computational efficiency; Data mining; Databases; Delay; Helium; Information technology; Itemsets; Mathematics; Sampling methods;
Journal_Title :
Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on
DOI :
10.1109/TSMCA.2002.804793
