We present a framework for a declarative approach to spatio-temporal reasoning on geographical data, based on the constraint logical language STACLP, which offers deductive and inductive capabilities. It can be exploited for a deductive rule-based approach to represent domain knowledge on data. Furthermore it is well suited to model trajectories of moving objects, which can be analysed by using inductive techniques, like clustering, in order to find common movement patterns. A sketch of a case study on behavioral ecology is presented.

Deductive and inductive reasoning on spatio temporal data

Nanni M;Renso C;Turini F
2004

Abstract

We present a framework for a declarative approach to spatio-temporal reasoning on geographical data, based on the constraint logical language STACLP, which offers deductive and inductive capabilities. It can be exploited for a deductive rule-based approach to represent domain knowledge on data. Furthermore it is well suited to model trajectories of moving objects, which can be analysed by using inductive techniques, like clustering, in order to find common movement patterns. A sketch of a case study on behavioral ecology is presented.
2004
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
978-3-540-25560-4
Spatio temporal reasoning
Data mining
GIS
Declarative programming
Constraint programming
Clustering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/37320
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