A recommender system is employed to accurately recommend items, which are expected to
attract the user's attention. The over-emphasis on the accuracy of the recommendations can …

Serendipitous recommendations have emerged as a compelling approach to deliver users
with unexpected yet valuable information, contributing to heightened user satisfaction and …

Recommendation serendipity is being increasingly recognized as being equally important
as the other beyond-accuracy objectives (such as novelty and diversity), in eliminating the …

Programmatic advertising is a nascent and rapidly growing information technology
phenomenon that reacts to, and impacts upon, consumers and their behavior. Despite its …

Unemployment constitutes one of the major problems in develo** countries, with factors
such as unavailable skills and the proliferation of unskilled workers being cited as main …

Serendipity is a notion that means an unexpected but valuable discovery. Due to its elusive
and subjective nature, serendipity is difficult to study even with today's advances in machine …

Most recommender systems suggest items that are popular among all users and similar to
items a user usually consumes. As a result, the user receives recommendations that she/he …

Most of the available recommender systems focus on the accuracy of recommendations. As
a result, their recommendations are often popular and very close to user preferences, which …

Every day we interact with machine learning systems offering individualized predictions for
our entertainment, social connections, purchases, or health. These involve several …

We study a model of user decision-making in the context of recommender systems via
numerical simulation. Our model provides an explanation for the findings of Nguyen, et. al …