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A computational framework for ontologically storing and ana..:

, In: Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data,

Brost, Randy C. ; McLendon III, William C. ; Parekh, Ojas... - p. 1-10 , 2014

Link: https://dl.acm.org/doi/10.1145/2676536.2676537

RT 
T1 <cTitle>Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data</cTitle>: T1 <Title>A computational framework for ontologically storing and analyzing very large overhead image sets</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-2676537&Exemplar=1&LAN=DE
				
A1 Brost, Randy C.
A1 McLendon III, William C.
A1 Parekh, Ojas
A1 Rintoul, Mark D.
A1 Strip, David R.
A1 Woodbridge, Diane Myung-kyung
PB ACM
YR 2014
K1 geospatial-temporal data analysis
K1 semantic graph
K1 Applied computing
K1 Operations research
K1 Decision analysis
K1 Information systems
K1 Information systems applications
K1 Decision support systems
K1 Information retrieval
K1 Retrieval tasks and goals
K1 Document filtering
K1 Information retrieval query processing
K1 Computing methodologies
K1 Artificial intelligence
K1 Knowledge representation and reasoning
K1 Semantic networks
K1 Information extraction
SP 1
OP 10
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/2676536.2676537
DO https://dl.acm.org/doi/10.1145/2676536.2676537
SF ELIB - SuUB Bremen

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