How’s your experience? A blockchain-based framework for cookie sharing enabling adversarial diversity

February 22nd, 2022

Online recommender systems (RSs) are an integral element of the web used by around 4 billion people world wide. The ultimate goal of these systems is to help users find content, such as articles, videos, products, social media posts, etc. depending on the respective web service, that is in some form appealing or relevant to them.

Thesis Type
  • Master
Michael Kretschmer
Proposal on
02/11/2021 2:00 pm
Proposal room
Presentation on
31/05/2022 1:00 pm
Presentation room
Seminar room I5 6202
Ralf Klamma
Stefan Decker
Alexander Neumann

This is especially helpful and partially required considering the sheer amount of content on the web.
Although RSs are ubiquitous online, the attitudes expressed towards them and the knowledge of them varies greatly among their users.
While the vast majority of users seems to appreciate RSs at least to some extent, some researchers have expressed concerns that personalized recommendations narrow the exposure to diverse content which may have negative side effects.
Thus, we study diversity in recommender systems in this work by developing a system which grants users direct control over the content recommendations they receive.