Work

Enhancing Privacy in Recommender Systems through Differential Privacy Techniques

Year: 2024

Type: conference-paper

Abstract: Recommender systems have become essential tools for addressing information overload in the digital age. However, the collection and usage of user data for personalized recommendations raise significant privacy concerns. This research focuses on enhancing privacy in recommender systems through the application of differential privacy techniques, particularly in the domain of privacy-preserving data publishing.

Source: ACM Conference on Recommender Systems (RecSys)

DOI: 10.1145/3640457.3688019

Author: Angela Di Fazio

Institution: Polytechnic University of Bari

Language: English

Topic: Privacy-Preserving Technologies in Data

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W4403222288

FWCI: 2.058

Cites: 41

Cited by: 7

Related to: 10