Privacy, Security, and Trust in KDD [electronic resource] : 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.

Contributor(s): Bonchi, Francesco [editor.] | Ferrari, Elena [editor.] | Malin, Bradley [editor.] | Saygin, Yücel [editor.] | SpringerLink (Online service)Material type: TextTextSeries: Lecture Notes in Computer Science ; 4890Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008Description: online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783540784784Subject(s): Computer science | Computer Communication Networks | Data mining | Information systems | Computers -- Law and legislation | Information Systems | Computer Science | Information Systems Applications (incl.Internet) | Data Mining and Knowledge Discovery | Computer Communication Networks | Computers and Society | Legal Aspects of Computing | Management of Computing and Information SystemsAdditional physical formats: Printed edition:: No titleDDC classification: 005.7 LOC classification: QA76.76.A65Online resources: Click here to access online
Contents:
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.
In: Springer eBooks
Item type: E-BOOKS
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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.

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