An Earthquake Sequential Pattern Mining Algorithm Based on General Constraint

Author

Wu, Shaochun ; Fang, Minfu ; Li, Yinyin ; Zhang, Bofeng

Author_Institution

Sch. of Comput. Eng. & Sci., Shanghai Univ. Shanghai, Shanghai

fYear

2008

fDate

18-21 Nov. 2008

Firstpage

1878

Lastpage

1883

Abstract

In recent years, time series data mining has already been an important branch of data mining. In this paper, an improved sequential pattern mining algorithm PBGC ( sequential pattern mining algorithm based on general constraint) is presented, in which seismic knowledge is used as general constraint to restrict the sequential patterns, and eventually enhances the suitability and the value of the result. Its application is to discover general earthquake sequence from earthquake catalogue data and to study the similarity of earthquake sequence.

Keywords

data mining; earthquakes; geophysics computing; seismology; sequences; time series; earthquake sequential pattern mining algorithm; general constraint; seismic knowledge; time series data mining; Data mining; Earthquake engineering; History; Itemsets; Large-scale systems; Pattern matching; Seismology; Sequential analysis; Test pattern generators; Time factors; General Constraint; data mining; earthquake sequence; sequential pattern; time series;

fLanguage

English

Publisher

ieee

Conference_Titel

Young Computer Scientists, 2008. ICYCS 2008. The 9th International Conference for

Conference_Location

Hunan

Print_ISBN

978-0-7695-3398-8

Electronic_ISBN

978-0-7695-3398-8

Type

conf

DOI

10.1109/ICYCS.2008.55

Filename

4709260