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Frequent spatio-temporal patterns in trajectory data warehouses (Contributo in atti di convegno)

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Frequent spatio-temporal patterns in trajectory data warehouses (Contributo in atti di convegno) (literal)

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Leonardi L.; Orlando S.; Raffaetà A.; Roncato A.; Silvestri C. (2009)
Frequent spatio-temporal patterns in trajectory data warehouses
in ACM Symposium on Applied Computing, Honolulu, Hawaii, USA
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In: SAC 2009 - ACM Symposium on Applied Computing (Honolulu, Hawaii, USA, 9 -12 Marzo 2009). Proceedings, pp. 1433 - 1440. ACM, 2009. (literal)

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ABSTRACT: In this paper we present an approach for storing and aggregating spatio-temporal patterns by using a Trajectory Data Warehouse (TDW). In particular, our aim is to allow the analysts to quickly evaluate frequent patterns mined from trajectories of moving objects occurring in a specific spatial zone and during a given temporal interval. We resort to a TDW, based on a data cube model, having spatial and temporal dimensions, discretized according to a hierarchy of regular grids, and whose facts are sets of trajectories which intersect the spatio-temporal cells of the cube. The idea is to enrich such a TDW with a new measure: frequent patterns obtained from a data-mining process on trajectories. As a consequence these patterns can be analysed by the user at various levels of granularity by means of OLAP queries. The research issues discussed in this paper are (1) the extraction/ mining of the patterns to be stored in each cell, which requires an adequate projection phase of trajec (literal)

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