Articolo in rivista, 2006, ENG, 10.1007/s10844-006-9953-7

Time-focused clustering of trajectories of moving objects

Nanni M.; Pedreschi D.

CNR-ISTI, Pisa, Italy; Dipartimento di Informatica - Università di Pisa, Pisa, Italy

Spatio-temporal, geo-referenced datasets are growing rapidly, and will be more in the near future, due to both technological and social/commercial reasons. From the data mining viewpoint, spatio-temporal trajectory data introduce new dimensions and, correspondingly, novel issues in performing the analysis tasks. In this paper, we consider the clustering problem applied to the trajectory data domain. In particular, we propose an adaptation of a density-based clustering algorithm to trajectory data based on a simple notion of distance between trajectories. Then, a set of experiments on synthesized data is performed in order to test the algorithm and to compare it with other standard clustering approaches. Finally, a new approach to the trajectory clustering problem, called temporal focussing, is sketched, having the aim of exploiting the intrinsic semantics of the temporal dimension to improve the quality of trajectory clustering.

Journal of intelligent information systems 27 (3), pp. 267–289

Keywords

OPTICS, Spatio-temporal data mining, Trajectory clustering

CNR authors

Nanni Mirco

CNR institutes

ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"

ID: 182243

Year: 2006

Type: Articolo in rivista

Creation: 2012-04-26 18:36:27.000

Last update: 2023-07-17 16:16:29.000

CNR authors

External IDs

CNR OAI-PMH: oai:it.cnr:prodotti:182243

DOI: 10.1007/s10844-006-9953-7

Scopus: 2-s2.0-37849187329

ISI Web of Science (WOS): 000243498200005