With the widespread use of Internet of things (IoT), mobile phones, connected devices and artificial intelligence (AI), recommender systems (RSs) have become a booming technology …
Precise user and item embedding learning is the key to building a successful recommender system. Traditionally, Collaborative Filtering (CF) provides a way to learn user and item …
L Wu, J Li, P Sun, R Hong, Y Ge… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Social recommendation has emerged to leverage social connections among users for predicting users' unknown preferences, which could alleviate the data sparsity issue in …
Abstract Graph Neural Networks have been applied in recommender systems to learn the representation of users and items from a user-item graph. In the state-of-the-art, there are …
P Nitu, J Coelho, P Madiraju - Big Data Mining and Analytics, 2021 - ieeexplore.ieee.org
A travel recommendation system based on social media activity provides a customized place of interest to accommodate user-specific needs and preferences. In general, the user's …
Recommender systems are popular tools used in many applications, such as e-commerce, e- learning, and social networks to help users select their desired items. Collaborative filtering …
B Yi, X Shen, H Liu, Z Zhang, W Zhang… - IEEE Transactions …, 2019 - ieeexplore.ieee.org
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 …
SS Choudhury, SN Mohanty, AK Jagadev - International Journal of …, 2021 - Springer
Recommender system (RS) are a type of suggestion to the information overload problem suffered by user of websites that allow the rating of particular item. The movie RS are one of …
J Feng, Z Xia, X Feng, J Peng - Knowledge-Based Systems, 2021 - Elsevier
The recommender systems aim to predict potential demands of users by analyzing their preferences and provide personalized recommendation services. User preferences can be …