In the previous chapters, we studied movement data from several perspectives: the application opportunities, the type of analytical questions, the modeling requirements, and the challenges for mining. Moreover, the complexity of the overall analysis process was pointed out several times. The analytical questions posed by the end user need to be translated into several tasks such as choose analysismethods, prepare the data for application of these methods, apply the methods to the data, and interpret and evaluate the results obtained.

Querying and Reasoning for Spatiotemporal Data Mining

Manco G;Baglioni M;Giannotti F;Renso C
2007

Abstract

In the previous chapters, we studied movement data from several perspectives: the application opportunities, the type of analytical questions, the modeling requirements, and the challenges for mining. Moreover, the complexity of the overall analysis process was pointed out several times. The analytical questions posed by the end user need to be translated into several tasks such as choose analysismethods, prepare the data for application of these methods, apply the methods to the data, and interpret and evaluate the results obtained.
2007
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
978-3-540-75176-2
Spatio temporal data mining
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/97863
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