With the emergence of various information access systems exhibiting increasing complexity,
there is a critical need for sound and scalable means of automatic evaluation. To address …

This article presents the first, systematic analysis of the ethical challenges posed by
recommender systems through a literature review. The article identifies six areas of concern …

User preferences are a crucial input needed by recommender systems to determine relevant
items. In single-shot recommendation scenarios such as content-based filtering and …

Trust in a Recommender System (RS) is crucial for its overall success. However, it remains
underexplored whether users trust personal recommendation sources (ie other humans) …

Recommendation system (RS) is a technology that provides accurate recommendations to
users. However, it is not comprehensive to only consider the accuracy of the …

Personalized recommender systems have become indispensable in today's online world.
Most of today's recommendation algorithms are data-driven and based on behavioral data …

Recommender systems (RS) are on the rise in many domains. While they offer great
promises, they also raise concerns: lack of transparency, reduction of diversity, little to no …

Decision making is the cognitive process of identifying and choosing alternatives based on
preferences, beliefs, and degree of importance given by the decision maker to objects or …

In this paper, we present a strategy to provide users with explainable cross-domain
recommendations (CDR) that exploits large language models (LLMs). Generally speaking …

How much trust a user places in a recommender is crucial to the uptake of the
recommendations. Although prior work established various factors that build and sustain …