A survey on conversational recommender systems
Recommender systems are software applications that help users to find items of interest in
situations of information overload. Current research often assumes a one-shot interaction …
situations of information overload. Current research often assumes a one-shot interaction …
Recommender systems in the healthcare domain: state-of-the-art and research issues
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 …
hinders users from finding helpful information for their well-being improvement. Besides, the …
Explainable recommendation: A survey and new perspectives
Y Zhang, X Chen - Foundations and Trends® in Information …, 2020 - nowpublishers.com
Explainable recommendation attempts to develop models that generate not only high-quality
recommendations but also intuitive explanations. The explanations may either be post-hoc …
recommendations but also intuitive explanations. The explanations may either be post-hoc …
Recommender systems leveraging multimedia content
Recommender systems have become a popular and effective means to manage the ever-
increasing amount of multimedia content available today and to help users discover …
increasing amount of multimedia content available today and to help users discover …
A review on deep learning for recommender systems: challenges and remedies
Recommender systems are effective tools of information filtering that are prevalent due to
increasing access to the Internet, personalization trends, and changing habits of computer …
increasing access to the Internet, personalization trends, and changing habits of computer …
[图书][B] Recommender systems
CC Aggarwal - 2016 - Springer
“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 …
though he cannot at once reveal himself because of his enormous size.”–Albert Einstein The …
The movielens datasets: History and context
FM Harper, JA Konstan - Acm transactions on interactive intelligent …, 2015 - dl.acm.org
The MovieLens datasets are widely used in education, research, and industry. They are
downloaded hundreds of thousands of times each year, reflecting their use in popular press …
downloaded hundreds of thousands of times each year, reflecting their use in popular press …
Social data: Biases, methodological pitfalls, and ethical boundaries
Social data in digital form—including user-generated content, expressed or implicit relations
between people, and behavioral traces—are at the core of popular applications and …
between people, and behavioral traces—are at the core of popular applications and …
Collaborative metric learning
Metric learning algorithms produce distance metrics that capture the important relationships
among data. In this work, we study the connection between metric learning and collaborative …
among data. In this work, we study the connection between metric learning and collaborative …
Diversity, serendipity, novelty, and coverage: a survey and empirical analysis of beyond-accuracy objectives in recommender systems
M Kaminskas, D Bridge - ACM Transactions on Interactive Intelligent …, 2016 - dl.acm.org
What makes a good recommendation or good list of recommendations? Research into
recommender systems has traditionally focused on accuracy, in particular how closely the …
recommender systems has traditionally focused on accuracy, in particular how closely the …