Big data is a rapidly growing field, and new developments are constantly emerging to
address various challenges. One such development is the use of federated learning for …

Machine unlearning (MU) is gaining increasing attention due to the need to remove or
modify predictions made by machine learning (ML) models. While training models have …

User-based KNN recommender systems (UserKNN) utilize the rating data of a target user'sk
nearest neighbors in the recommendation process. This, however, increases the privacy risk …

Increased use of collaborative technologies and agile teamwork models has led to a greater
need for temporary teams. Unfortunately, they lack the normal team formation processes that …

Recommendation and search systems have already become indispensable means of
helping web users identify the most relevant information/services in the era of information …

The principle of data minimization aims to reduce the amount of data collected, processed or
retained to minimize the potential for misuse, unauthorized access, or data breaches …

Using 286 research papers collected from Web of Science, ScienceDirect, SpringerLink,
arXiv, and Google Scholar databases, a systematic review methodology was adopted to …

Flesteparten av dagens digitale tjenester benytter en eller annen form for et
anbefalingssystem. En stor ulempe med disse anbefalingssystemene er at de baserer seg …

The principle of data minimization aims to reduce the amount of data collected, processed or
retained to minimize the potential for misuse, unauthorized access, or data breaches …