Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Adapting Recommender Systems to the New Data Privacy Regulations

View through CrossRef
Recommender systems are key enablers to provide personalization and to make systems be adapted to users' needs. Both, users and content or commercial providers benefit from these techniques. While user profiling is required during the recommendation process, it can also introduce additional threats to the user's privacy. New regulations come into place to palliate the misuse of personal information from companies and public institutions. However, there are no clear rules defined for recommender systems. We find in the literature different proposals to privacy-preserving recommender system, but none of them tackle the compliance with the General Data Protection Regulation (GDPR). In this work we suggest a set of guidelines to assess and implement GDPR compliant recommender systems. Recommender providers shall follow our guidelines to make sure that their systems are not only privacy-preserving, but also GDPR compliant.
Title: Adapting Recommender Systems to the New Data Privacy Regulations
Description:
Recommender systems are key enablers to provide personalization and to make systems be adapted to users' needs.
Both, users and content or commercial providers benefit from these techniques.
While user profiling is required during the recommendation process, it can also introduce additional threats to the user's privacy.
New regulations come into place to palliate the misuse of personal information from companies and public institutions.
However, there are no clear rules defined for recommender systems.
We find in the literature different proposals to privacy-preserving recommender system, but none of them tackle the compliance with the General Data Protection Regulation (GDPR).
In this work we suggest a set of guidelines to assess and implement GDPR compliant recommender systems.
Recommender providers shall follow our guidelines to make sure that their systems are not only privacy-preserving, but also GDPR compliant.

Related Results

Privacy Risk in Recommender Systems
Privacy Risk in Recommender Systems
Nowadays, recommender systems are mostly used in many online applications to filter information and help users in selecting their relevant requirements. It avoids users to become o...
Augmented Differential Privacy Framework for Data Analytics
Augmented Differential Privacy Framework for Data Analytics
Abstract Differential privacy has emerged as a popular privacy framework for providing privacy preserving noisy query answers based on statistical properties of databases. ...
Intelligent healthcare recommender system for advanced healthcare services
Intelligent healthcare recommender system for advanced healthcare services
The introduction of cutting-edge technologies has brought about a lot of changes in the healthcare industry. The application of intelligent recommender systems to improve healthcar...
THE SECURITY AND PRIVACY MEASURING SYSTEM FOR THE INTERNET OF THINGS DEVICES
THE SECURITY AND PRIVACY MEASURING SYSTEM FOR THE INTERNET OF THINGS DEVICES
The purpose of the article: elimination of the gap in existing need in the set of clear and objective security and privacy metrics for the IoT devices users and manufacturers and a...
A novel privacy-preserving matrix factorization recommendation system based on random perturbation
A novel privacy-preserving matrix factorization recommendation system based on random perturbation
 With the popularity of networks and the increasing number of online users, recommender systems have suffered from the privacy leakage of sensitive information. While people enjoy ...
Recommender System for E-Health
Recommender System for E-Health
Introduction; E-healthcare management services can be significantly enhanced through the implementation of recommender systems, as highlighted in various research papers. These sys...
Development of E-Commerce Website Recommender System Using Collaborative Filtering and Deep Learning Techniques
Development of E-Commerce Website Recommender System Using Collaborative Filtering and Deep Learning Techniques
Recommender system or recommendation system is becoming an increasingly important technology on e-commerce websites to help users find products that suit their preferences. However...
Application Status and Prospect of Data Privacy Protection Technology
Application Status and Prospect of Data Privacy Protection Technology
This article aims to explore the current application status and future prospects of data privacy protection technology, analyze the challenges faced by current data privacy, explor...

Back to Top