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Privacy, Security, and Trust in KDD : First ACM SIGKDD International Workshop, PinKDD 2007, San Jose, CA, USA, August 12, 2007, Revised Selected Papers / edited by Francesco Bonchi, Elena Ferrari, Bradley Malin, Yücel Saygin.

Por: Colaborador(es): Tipo de material: TextoTextoSeries Lecture Notes in Computer Science ; 4890Editor: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008Descripción: recurso en líneaTipo de contenido:
  • texto
Tipo de medio:
  • computadora
Tipo de portador:
  • recurso en línea
ISBN:
  • 9783540784784
Formatos físicos adicionales: Edición impresa:: Sin títuloClasificación LoC:
  • QA76.76.A65
Recursos en línea:
Contenidos:
Invited Paper -- An Ad Omnia Approach to Defining and Achieving Private Data Analysis -- Contributed Papers -- Phoenix: Privacy Preserving Biclustering on Horizontally Partitioned Data -- Allowing Privacy Protection Algorithms to Jump Out of Local Optimums: An Ordered Greed Framework -- Probabilistic Anonymity -- Website Privacy Preservation for Query Log Publishing -- Privacy-Preserving Data Mining through Knowledge Model Sharing -- Privacy-Preserving Sharing of Horizontally-Distributed Private Data for Constructing Accurate Classifiers -- Towards Privacy-Preserving Model Selection -- Preserving the Privacy of Sensitive Relationships in Graph Data.
Resumen: This book constitutes the thoroughly refereed post-workshop proceedings of the First International Workshop on Privacy, Security, and Trust in KDD, PinKDD 2007, held in San Jose, CA, USA, in August 2007 in conjunction with the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2007. The 8 revised full papers presented together with 1 keynote lecture were carefully reviewed and selected from numerous submissions. The papers address all prevailing topics concerning privacy, security, and trust aspects of data mining and knowledge discovery. Special focus is put on applied domains such as healthcare, ubiquitous computing, and location-based services.
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Invited Paper -- An Ad Omnia Approach to Defining and Achieving Private Data Analysis -- Contributed Papers -- Phoenix: Privacy Preserving Biclustering on Horizontally Partitioned Data -- Allowing Privacy Protection Algorithms to Jump Out of Local Optimums: An Ordered Greed Framework -- Probabilistic Anonymity -- Website Privacy Preservation for Query Log Publishing -- Privacy-Preserving Data Mining through Knowledge Model Sharing -- Privacy-Preserving Sharing of Horizontally-Distributed Private Data for Constructing Accurate Classifiers -- Towards Privacy-Preserving Model Selection -- Preserving the Privacy of Sensitive Relationships in Graph Data.

This book constitutes the thoroughly refereed post-workshop proceedings of the First International Workshop on Privacy, Security, and Trust in KDD, PinKDD 2007, held in San Jose, CA, USA, in August 2007 in conjunction with the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2007. The 8 revised full papers presented together with 1 keynote lecture were carefully reviewed and selected from numerous submissions. The papers address all prevailing topics concerning privacy, security, and trust aspects of data mining and knowledge discovery. Special focus is put on applied domains such as healthcare, ubiquitous computing, and location-based services.

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