PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Ortale R., Pelekis N., Ritacco E., Trasarti R., Costa G., Giannotti F., Manco G., Renso C., Theodoridis Y. Towards progressive querying and mining movement data. Technical report, 2008.
 
 
Abstract
(English)
In this work we propose a research foundation for uniformly querying both movement data and patterns extracted from movement data. Our proposal is based on a formal framework, called 2W Model, that defines the knowledge discovery execution process as a progressive combination of mining and querying operators. Furthermore, a query language is proposed that extends SQL in two respects, namely a pattern definition operator and the capability to uniformly manipulate both raw data and unveiled patterns. The resulting Moving-Object data mining query language is implemented in DAEDALUS, an innovative computational engine serving as a query execution layer on top of the Hermes Moving Object Database. A qualitative evaluation of the whole system by means of a concrete case study is presented.
Subject data mining query language
spatio-temporal database
data mining
H.2.8 Database Applications. Data mining


Icona documento 1) Download Document PDF


Icona documento Open access Icona documento Restricted Icona documento Private

 


Per ulteriori informazioni, contattare: Librarian http://puma.isti.cnr.it

Valid HTML 4.0 Transitional