A growing number of applications in distributed environment involve very large data sets that are inherently distributed among a large number of autonomous sources over a network. The demand to extend data mining technology to such distributed data sets has motivated the development of several approaches to distributed data mining and knowledge discovery, of which only a few make use of agents. We briefly review existing approaches and argue for the potential added value of using agent technology in the domain of knowledge discovery, discussing both issues and benefits. We also propose an approach to distributed data clustering, outline its agent-oriented implementation, and examine potential privacy violating attacks which agents may incur.

J. C. da Silva, M. Klusch, S. Lodi, G. Moro (2006). Privacy-preserving agent-based distributed data clustering. WEB INTELLIGENCE AND AGENT SYSTEMS, 4, 221-238.

Privacy-preserving agent-based distributed data clustering

LODI, STEFANO;MORO, GIANLUCA
2006

Abstract

A growing number of applications in distributed environment involve very large data sets that are inherently distributed among a large number of autonomous sources over a network. The demand to extend data mining technology to such distributed data sets has motivated the development of several approaches to distributed data mining and knowledge discovery, of which only a few make use of agents. We briefly review existing approaches and argue for the potential added value of using agent technology in the domain of knowledge discovery, discussing both issues and benefits. We also propose an approach to distributed data clustering, outline its agent-oriented implementation, and examine potential privacy violating attacks which agents may incur.
2006
J. C. da Silva, M. Klusch, S. Lodi, G. Moro (2006). Privacy-preserving agent-based distributed data clustering. WEB INTELLIGENCE AND AGENT SYSTEMS, 4, 221-238.
J. C. da Silva; M. Klusch; S. Lodi; G. Moro
File in questo prodotto:
Eventuali allegati, non sono esposti

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/29745
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 17
  • ???jsp.display-item.citation.isi??? ND
social impact