Title :
Spatiotemporal Relational Probability Trees: An Introduction
Author :
McGovern, Amy ; Hiers, Nathan C. ; Collier, Matthew ; Gagne, David J., II ; Brown, Rodger A.
Author_Institution :
Univ. of Oklahoma, OK
Abstract :
We introduce spatiotemporal relational probability trees (SRPTs), probability estimation trees for relational data that can vary in both space and time. The SRPT algorithm addresses the exponential increase in search complexity through sampling. We validate the SRPT using a simulated data set and we empirically demonstrate the SRPT algorithm on two real-world data sets.
Keywords :
probability; relational databases; trees (mathematics); probability estimation trees; real-world data sets; spatiotemporal relational probability trees; Data mining; Decision trees; Discrete event simulation; Floods; Logic programming; Sampling methods; Space technology; Spatiotemporal phenomena; Storms; Tornadoes; spatiotemporal; statistical relational data mining;
Conference_Titel :
Data Mining, 2008. ICDM '08. Eighth IEEE International Conference on
Conference_Location :
Pisa
Print_ISBN :
978-0-7695-3502-9
DOI :
10.1109/ICDM.2008.134
