A systematic literature review of sparsity issues in recommender systems
The tremendous expansion of information available on the web voraciously bombards
users, leaving them unable to make decisions and having no way of stepping back to …
users, leaving them unable to make decisions and having no way of stepping back to …
A deep learning based trust-and tag-aware recommender system
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 …
learning, and social networks to help users select their desired items. Collaborative filtering …
An emotional recommender system for music
Nowadays, recommender systems have become essential to users for finding “what they
need” within large collections of items. Meanwhile, recent studies have demonstrated as …
need” within large collections of items. Meanwhile, recent studies have demonstrated as …
Knowledge graph enhanced neural collaborative recommendation
Existing neural collaborative filtering (NCF) recommendation methods suffer from severe
sparsity problem. Knowledge Graph (KG), which commonly consists of fruitful connected …
sparsity problem. Knowledge Graph (KG), which commonly consists of fruitful connected …
Bilateral knowledge graph enhanced online course recommendation
S Yang, X Cai - Information Systems, 2022 - Elsevier
Recommender system can provide users with items that meet their potential needs in mass
information. Its development provides new ideas and supporting technologies for …
information. Its development provides new ideas and supporting technologies for …
Exploiting relational tag expansion for dynamic user profile in a tag-aware ranking recommender system
Y Pan, Y Huo, J Tang, Y Zeng, B Chen - Information Sciences, 2021 - Elsevier
A tag-aware recommender system (TRS) presents the challenge of tag sparsity in a user
profile. Previous work focuses on expanding similar tags and does not link the tags with …
profile. Previous work focuses on expanding similar tags and does not link the tags with …
Modeling sequential listening behaviors with attentive temporal point process for next and next new music recommendation
Recommender systems, which aim to provide personalized suggestions for users, have
proven to be an effective approach to cope with the information overload problem existing in …
proven to be an effective approach to cope with the information overload problem existing in …
MORec: At the crossroads of context-aware and multi-criteria decision making for online music recommendation
Context-aware recommender systems have received considerable attention from industry
and academic areas. In this paper, we pay heed to the growing interest in integrating context …
and academic areas. In this paper, we pay heed to the growing interest in integrating context …
A novel emotion-aware hybrid music recommendation method using deep neural network
S Wang, C Xu, AS Ding, Z Tang - Electronics, 2021 - mdpi.com
Emotion-aware music recommendations has gained increasing attention in recent years, as
music comes with the ability to regulate human emotions. Exploiting emotional information …
music comes with the ability to regulate human emotions. Exploiting emotional information …
Collaborative Tag-Aware Graph Neural Network for Long-Tail Service Recommendation
Long-tail service recommendation provides an unexpected but reasonable experience for
potential developers when they construct mashups. However, the lack of available …
potential developers when they construct mashups. However, the lack of available …