The ongoing rapid expansion of the Word Wide Web (WWW) greatly increases the
information of effective transmission from heterogeneous individuals to various systems …

Cross domain recommender systems (CDRS) can assist recommendations in a target
domain based on knowledge learned from a source domain. CDRS consists of three …

Automatic multimedia learning resources recommendation has become an increasingly
relevant problem: it allows students to discover new learning resources that match their …

Both explicit and implicit feedbacks can reflect user opinions on items, which are essential
for learning user preferences in recommendation. However, most current recommendation …

The recommender systems aim to predict potential demands of users by analyzing their
preferences and provide personalized recommendation services. User preferences can be …

Intelligent recommendation technology has been playing an increasingly important role in
various industry applications such as e-commerce product promotion and Internet …

Personalized recommendation for online service systems aims to predict potential demand
by analysing user preference. User preference can be inferred from heterogeneous implicit …

Recommender systems (RSs) have been employed for many real-world applications
including search engines, social networks, and information retrieval systems as powerful …

Neural-based multi-task learning (MTL) has gained significant improvement, and it has been
successfully applied to recommendation system (RS). Recent deep MTL methods for RS (eg …

Group recommendation plays a significant role in today's social media systems, where users
form social groups to receive multimedia content together and interact with each other …