In the healthcare domain, a transformative shift is envisioned towards Healthcare 5.0. It
expands the operational boundaries of Healthcare 4.0 and leverages patient-centric digital …

Multi-criterion decision making (MCDM) methods can derive alternative rankings as
solutions to decision-making problems based on survey or historical data about the …

Factorization Machines (FMs) are a supervised learning approach that enhances the linear
regression model by incorporating the second-order feature interactions. Despite …

Item-to-item collaborative filtering (aka. item-based CF) has been long used for building
recommender systems in industrial settings, owing to its interpretability and efficiency in real …

Abstract Recently, Recurrent Neural Network (RNN) solutions for recommender systems
(RS) are becoming increasingly popular. The insight is that, there exist some intrinsic …

Distributed linguistic representations are powerful tools for modelling the uncertainty and
complexity of preference information in linguistic decision making. To provide a …

Automatic recommendation has become an increasingly relevant problem to industries,
which allows users to discover new items that match their tastes and enables the system to …

Online platforms can be divided into information-oriented and social-oriented domains. The
former refers to forums or E-commerce sites that emphasize user-item interactions, like Trip …

There exist complex patterns behind the decision-making processes of different individuals
across different environments. For instance, in a social recommender system, various user …

Sequential recommendation effectively addresses information overload by modeling users'
temporal and sequential interaction patterns. To overcome the limitations of supervision …