The comprehensive evaluation of the performance of a recommender system is a complex
endeavor: many facets need to be considered in configuring an adequate and effective …

Recommender systems (RSs) have become an inseparable part of our everyday lives. They
help us find our favorite items to purchase, our friends on social networks, and our favorite …

How big data and machine learning encode discrimination and create agitated clusters of
comforting rage. In Discriminating Data, Wendy Hui Kyong Chun reveals how polarization is …

Recommendation foundation model utilizes large language models (LLM) for
recommendation by converting recommendation tasks into natural language tasks. It …

Nowadays, a vast amount of clinical data scattered across different sites on the Internet
hinders users from finding helpful information for their well-being improvement. Besides, the …

In this paper, we introduce SciANN, a Python package for scientific computing and physics-
informed deep learning using artificial neural networks. SciANN uses the widely used deep …

With the growing volume of online information, recommender systems have been an
effective strategy to overcome information overload. The utility of recommender systems …

“Nature shows us only the tail of the lion. But I do not doubt that the lion belongs to it even
though he cannot at once reveal himself because of his enormous size.”–Albert Einstein The …

Research about recommender systems emerges over the last decade and comprises
valuable services to increase different companies' revenue. While most existing …

Recommender systems (RSs) are software tools and techniques that provide suggestions
for items that are most likely of interest to a particular user. In this introductory chapter, we …