2 papers
cs.IR2022
Towards Employing Recommender Systems for Supporting Data and Algorithm Sharing
Peter Müllner, Stefan Schmerda, Dieter Theiler +2
Data and algorithm sharing is an imperative part of data and AI-driven economies. The efficient sharing of data and algorithms relies on the active interplay between users, data pr…
cs.IR2021
Position Paper on Simulating Privacy Dynamics in Recommender Systems
Peter Müllner, Elisabeth Lex, Dominik Kowald
In this position paper, we discuss the merits of simulating privacy dynamics in recommender systems. We study this issue at hand from two perspectives: Firstly, we present a concep…