InforLorV4, Main, Curation, bibRecord, 004535

Privacy Concerns when Modeling Users in Collaborative Filtering Recommender Systems

Identifieur interne : 004535 ( Main/Curation ); précédent : 004534; suivant : 004536

Privacy Concerns when Modeling Users in Collaborative Filtering Recommender Systems

Auteurs : Sylvain Castagnos [France] ; Anne Boyer [France]

Source :

RBID : Hal:inria-00171806

English descriptors

mix :
- Collaborative Filtering, Information Search and Retrieval, Information Systems, Privacy Laws, Privacy Rights, User Characteristics, User Characteristics., User Modeling.

Abstract

This chapter investigates ways to deal with privacy rules when modeling preferences of users in recommender systems based on collaborative filtering. It argues that it is possible to find a good compromise between quality of predictions and protection of personal data. Thus, it proposes a methodology that fulfills with strictest privacy laws for both centralized and distributed architectures. The authors hope that their attempts to provide an unified vision of privacy rules through the related works and a generic privacy-enhancing procedure will help researchers and practitioners to better take into account the ethical and juridical constraints as regards privacy protection when designing information systems.

Url:

https://hal.inria.fr/inria-00171806

Links toward previous steps (curation, corpus...)

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Links to Exploration step

Hal:inria-00171806

Le document en format XML

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<front><div type="abstract" xml:lang="en">This chapter investigates ways to deal with privacy rules when modeling preferences of users in recommender systems based on collaborative filtering. It argues that it is possible to find a good compromise between quality of predictions and protection of personal data. Thus, it proposes a methodology that fulfills with strictest privacy laws for both centralized and distributed architectures. The authors hope that their attempts to provide an unified vision of privacy rules through the related works and a generic privacy-enhancing procedure will help researchers and practitioners to better take into account the ethical and juridical constraints as regards privacy protection when designing information systems.</div>
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Privacy Concerns when Modeling Users in Collaborative Filtering Recommender Systems

Privacy Concerns when Modeling Users in Collaborative Filtering Recommender Systems

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