Ir al contenido (pulsa Retorno)

Universitat Politècnica de Catalunya

    • Català
    • Castellano
    • English
    • LoginRegisterLog in (no UPC users)
  • mailContact Us
  • world English 
    • Català
    • Castellano
    • English
  • userLogin   
      LoginRegisterLog in (no UPC users)

UPCommons. Global access to UPC knowledge

57.066 UPC E-Prints
You are here:
View Item 
  •   DSpace Home
  • E-prints
  • Grups de recerca
  • DMAG - Grup d'Aplicacions Multimèdia Distribuïdes
  • Reports de recerca
  • View Item
  •   DSpace Home
  • E-prints
  • Grups de recerca
  • DMAG - Grup d'Aplicacions Multimèdia Distribuïdes
  • Reports de recerca
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Parameter determination of ONN (Ordered Neural Networks)

Thumbnail
View/Open
onn.tr.pdf (342,7Kb)
Share:
 
  View Usage Statistics
Cita com:
hdl:2117/12712

Show full item record
Pont Tuset, Jordi
Medrano Gracia, Pau
Nin Guerrero, JordiMés informació
Larriba Pey, JosepMés informacióMés informacióMés informació
Muntés Mulero, Víctor
Document typeResearch report
Defense date2007
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
The need for data privacy motivates the development of new methods that allow to protect data minimizing the disclosure risk without losing information. In this paper, we propose a new protection method for numerical data called Ordered Neural Networks (ONN) method. ONN presents a new way to protect data based on the use of Artificial Neural Networks (ANN). ONN combines the use of ANN with a new strategy for preprocessing data consisting in the vectorization, sorting and partitioning of all the values in the attributes to be protected in the data set. We also present an statistical analysis that allows to understand the most important parameters affecting the quality of our method, and we show that it is possible to find a good configuration for these parameters. Finally, we compare our method to the best methods presented in the literature, using data provided by the US Census Bureau. Our experiments show that ONN outperforms the previous methods proposed in the literature, proving that the use of ANNs in these situations is convenient to protect the data efficiently without losing the statistical properties of the set.
CitationPont, J. [et al.]. "Parameter determination of ONN (Ordered Neural Networks)". 2007. 
URIhttp://hdl.handle.net/2117/12712
URL other repositoryhttp://personals.ac.upc.edu/nin/papers/onn.tr.pdf
Collections
  • DMAG - Grup d'Aplicacions Multimèdia Distribuïdes - Reports de recerca [3]
  • Departament de Teoria del Senyal i Comunicacions - Reports de recerca [185]
  • Departament d'Arquitectura de Computadors - Reports de recerca [175]
  • DAMA-UPC - Data Management Group de la Universitat Politècnica de Catalunya - Reports de recerca [2]
Share:
 
  View Usage Statistics

Show full item record

FilesDescriptionSizeFormatView
onn.tr.pdf342,7KbPDFView/Open

Browse

This CollectionBy Issue DateAuthorsOther contributionsTitlesSubjectsThis repositoryCommunities & CollectionsBy Issue DateAuthorsOther contributionsTitlesSubjects

© UPC Obrir en finestra nova . Servei de Biblioteques, Publicacions i Arxius

info.biblioteques@upc.edu

  • About This Repository
  • Contact Us
  • Send Feedback
  • Inici de la pàgina