A visual analytics toolkit for cluster-based classification of mobility data (Articolo in rivista)

Type

• Articolo in rivista (Classe)
• Prodotto della ricerca (Classe)

Label

• A visual analytics toolkit for cluster-based classification of mobility data (Articolo in rivista) (literal)

Anno

• 2009-01-01T00:00:00+01:00 (literal)

Alternative label

• Andrienko G.; Andrienko N.; Rinzivillo S.; Nanni M.; Pedreschi D. (2009)
  A visual analytics toolkit for cluster-based classification of mobility data
  in Lecture notes in computer science
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Andrienko G.; Andrienko N.; Rinzivillo S.; Nanni M.; Pedreschi D. (literal)

Pagina inizio

• 432 (literal)

Pagina fine

• 435 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume

• 5644 (literal)

Rivista

• Lecture notes in computer science (Rivista)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note

• In: SSTD 2009 - Advances in Spatial and Temporal Databases. 11th International Symposium (Aalborg, Denmark, 8-10 July 2009). Proceedings, pp. 432 - 435. Mamoulis N., Seidl Th., Pedersen T.B., Torp K., Assent I. (Lecture Notes in Computer Science, vol. 5644). Springer, 2009. (literal)

Note

• ISI Web of Science (WOS) (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• Fraunhofer IAIS, CNR-ISTI, Pisa, Department of Computer Science, Univ. Pisa (literal)

Titolo

• A visual analytics toolkit for cluster-based classification of mobility data (literal)

Abstract

• In this paper we propose a demo of a Visual Analytics Toolkit to cope with the complexity of analysing a large dataset of moving objects, in a step wise manner.We allow the user to sample a small subset of objects, that can be handled in main memory, and to perform the analysis on this small group by means of a density based clustering algorithm. The GUI is designed in order to exploit and facilitate the human interaction during this phase of the analysis, to select interesting clusters among the candidates. The selected groups are used to build a classifier that can be used to label other objects from the original dataset. The classifier can then be used to efficiently associate all objects in the database to clusters. The tool has been tested using a large set of GPS tracked cars. (literal)

Prodotto di

• Knowledge Discovery and Data Mining (ICT.P08.009.003) (Modulo)
• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)

Autore CNR

• DINO PEDRESCHI (Persona)
• SALVATORE RINZIVILLO (Persona)
• MIRCO NANNI (Unità di personale interno)

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• Parole chiave di "A visual analytics toolkit for cluster-based classification of mobility data" (Insieme di parole chiave)

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Prodotto

• Istituto di scienza e tecnologie dell'informazione \"Alessandro Faedo\" (ISTI) (Istituto)
• Knowledge Discovery and Data Mining (ICT.P08.009.003) (Modulo)

Autore CNR di

• MIRCO NANNI (Unità di personale interno)
• DINO PEDRESCHI (Persona)
• SALVATORE RINZIVILLO (Persona)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi

• Lecture notes in computer science (Rivista)

Insieme di parole chiave di

• Parole chiave di "A visual analytics toolkit for cluster-based classification of mobility data" (Insieme di parole chiave)