Back to Search Start Over

A Problem Oriented Approach to Data Mining in Distributed Spatio-temporal Database.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Rangan, C. Pandu
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Shi, Yong
van Albada, Geert Dick
Dongarra, Jack
Sloot, Peter M. A.
Zhou Huang
Source :
Computational Science: ICCS 2007 (9783540725879); 2007, p653-660, 8p
Publication Year :
2007

Abstract

Recently, a fast increment of spatio-temporal data volume has been achieved and more importantly the data might distribute everywhere. So, there is a need for spatio-temporal data mining systems that are able to support such distributed spatio-temporal query and analysis operations. Distributed spatio-temporal data mining technologies were discussed in this paper. After discussing the process of spatio-temporal data mining in distributed environment, one actual DSTDMS (Distributed Spatio-Temporal Data Mining System) was designed and then implemented. The system is based on data model of sequent snapshot and accomplished through spatio-temporal extension on PostgreSQL. Various spatio-temporal analyses and mining queries could be carried out in the system through simple SQL statements. By using the system, effective mining of distributed spatio-temporal data were achieved. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540725879
Database :
Complementary Index
Journal :
Computational Science: ICCS 2007 (9783540725879)
Publication Type :
Book
Accession number :
33155314
Full Text :
https://doi.org/10.1007/978-3-540-72588-6_111