A single pass algorithm for clustering evolving data streams based on swarm intelligence (Articolo in rivista)

Type

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

Label

• A single pass algorithm for clustering evolving data streams based on swarm intelligence (Articolo in rivista) (literal)

Anno

• 2013-01-01T00:00:00+01:00 (literal)

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

• 10.1007/s10618-011-0242-x (literal)

Alternative label

• Forestiero, Agostino and Pizzuti, Clara and Spezzano, Giandomenico (2013)
  A single pass algorithm for clustering evolving data streams based on swarm intelligence
  in Data mining and knowledge discovery
  (literal)

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

• Forestiero, Agostino and Pizzuti, Clara and Spezzano, Giandomenico (literal)

Pagina inizio

• 1 (literal)

Pagina fine

• 26 (literal)

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

• 26 (literal)

Rivista

• Data mining and knowledge discovery (Rivista)

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

• 1 (literal)

Note

• ISI Web of Science (WOS) (literal)

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

• ICAR-CNR (literal)

Titolo

• A single pass algorithm for clustering evolving data streams based on swarm intelligence (literal)

Abstract

• Existing density-based data stream clustering algorithms use a two-phase scheme approach consisting of an online phase, in which raw data is processed to gather summary statistics, and an offline phase that generates the clusters by using the summary data. In this paper we propose a data stream clustering method based on a multi-agent system that uses a decentralized bottom-up self-organizing strategy to group similar data points. Data points are associated with agents and deployed onto a 2D space, to work simultaneously by applying a heuristic strategy based on a bio-inspired model, known as flocking model. Agents move onto the space for a fixed time and, when they encounter other agents into a predefined visibility range, they can decide to form a flock if they are similar. Flocks can join to form swarms of similar groups. This strategy allows to merge the two phases of density-based approaches and thus to avoid the computing demanding offline cluster computation, since a swarm represents a cluster. Experimental results show that the bio-inspired approach can obtain very good results on real and synthetic data sets. (literal)

Prodotto di

• Gestire, Estrarre Conoscenza e Ragionare sui Dati (ICT.P08.002.001) (Modulo)
• Institute for high performance computing and networking (ICAR) (Istituto)
• Sistemi distribuiti e pervasivi intelligenti (ICT.P09.001.001) (Modulo)

Autore CNR

• CLARA PIZZUTI (Unità di personale interno)
• AGOSTINO FORESTIERO (Unità di personale interno)
• GIANDOMENICO SPEZZANO (Unità di personale interno)

Insieme di parole chiave

• Parole chiave di "A single pass algorithm for clustering evolving data streams based on swarm intelligence" (Insieme di parole chiave)

Incoming links:

Prodotto

• Institute for high performance computing and networking (ICAR) (Istituto)
• Sistemi distribuiti e pervasivi intelligenti (ICT.P09.001.001) (Modulo)
• Gestire, Estrarre Conoscenza e Ragionare sui Dati (ICT.P08.002.001) (Modulo)

Autore CNR di

• CLARA PIZZUTI (Unità di personale interno)
• GIANDOMENICO SPEZZANO (Unità di personale interno)
• AGOSTINO FORESTIERO (Unità di personale interno)

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

• Data mining and knowledge discovery (Rivista)

Insieme di parole chiave di

• Parole chiave di "A single pass algorithm for clustering evolving data streams based on swarm intelligence" (Insieme di parole chiave)