An improved parallel algorithm for sequence mining

Author

She, Chundong ; Tang, Jian ; Li, Lei ; Wang, Hongbing ; Fan, Zhihua

Author_Institution

Inst. of Software, Chinese Acad. of Sci., Beijing, China

Volume

4

fYear

2005

fDate

2005

Firstpage

1692

Abstract

It is more and more important in data mining field to finding the frequent sequences in a large database. The paper briefly introduces the basic concept of frequent sequence mining and presents the data parallel formulation and task parallel formulation of tree-projection based algorithm. Moreover, the on-line LPT algorithm is used to successfully solve the problem of imbalance for the task parallel formulation. Our experiment shows that these algorithms are capable of achieving good speedups. However, the task parallel formulation is more scalable than the data parallel one.

Keywords

data mining; parallel algorithms; trees (mathematics); very large databases; data mining; data parallel formulation; frequent sequence mining; large database; online LPT algorithm; parallel algorithm; task parallel formulation; tree-projection based algorithm; Concurrent computing; Data mining; Databases; Distributed computing; Frequency; Parallel algorithms; Parallel processing; Partitioning algorithms; Sequences; Web pages;

fLanguage

English

Publisher

ieee

Conference_Titel

Mechatronics and Automation, 2005 IEEE International Conference

Conference_Location

Niagara Falls, Ont., Canada

Print_ISBN

0-7803-9044-X

Type

conf

DOI

10.1109/ICMA.2005.1626812

Filename

1626812