Evaluating recommender systems: survey and framework
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 …
endeavor: many facets need to be considered in configuring an adequate and effective …
Federated learning in a medical context: a systematic literature review
Data privacy is a very important issue. Especially in fields like medicine, it is paramount to
abide by the existing privacy regulations to preserve patients' anonymity. However, data is …
abide by the existing privacy regulations to preserve patients' anonymity. However, data is …
Designing theory-driven user-centric explainable AI
From healthcare to criminal justice, artificial intelligence (AI) is increasingly supporting high-
consequence human decisions. This has spurred the field of explainable AI (XAI). This …
consequence human decisions. This has spurred the field of explainable AI (XAI). This …
Privacy-aware data fusion and prediction with spatial-temporal context for smart city industrial environment
L Qi, C Hu, X Zhang, MR Khosravi… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
As one of the cyber–physical–social systems that plays a key role in people's daily activities,
a smart city is producing a considerable amount of industrial data associated with …
a smart city is producing a considerable amount of industrial data associated with …
A survey of graph neural networks for social recommender systems
Social recommender systems (SocialRS) simultaneously leverage the user-to-item
interactions as well as the user-to-user social relations for the task of generating item …
interactions as well as the user-to-user social relations for the task of generating item …
Contrastive self-supervised sequential recommendation with robust augmentation
Sequential Recommendationdescribes a set of techniques to model dynamic user behavior
in order to predict future interactions in sequential user data. At their core, such approaches …
in order to predict future interactions in sequential user data. At their core, such approaches …
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 …
Multistakeholder recommendation: Survey and research directions
Recommender systems provide personalized information access to users of Internet
services from social networks to e-commerce to media and entertainment. As is appropriate …
services from social networks to e-commerce to media and entertainment. As is appropriate …
A thematic exploration of digital, social media, and mobile marketing: Research evolution from 2000 to 2015 and an agenda for future inquiry
Over the past 15 years, digital media platforms have revolutionized marketing, offering new
ways to reach, inform, engage, sell to, learn about, and provide service to customers. As a …
ways to reach, inform, engage, sell to, learn about, and provide service to customers. As a …
[LIVRE][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 …