A survey of recommendation systems: recommendation models, techniques, and application fields
This paper reviews the research trends that link the advanced technical aspects of
recommendation systems that are used in various service areas and the business aspects of …
recommendation systems that are used in various service areas and the business aspects of …
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 …
Insights into relevant knowledge extraction techniques: a comprehensive review
More than 50 million journal papers will have been published by the end of 2019 with 2
million more journal papers published every year. The number of conference papers is even …
million more journal papers published every year. The number of conference papers is even …
Multi-view enhanced graph attention network for session-based music recommendation
Traditional music recommender systems are mainly based on users' interactions, which limit
their performance. Particularly, various kinds of content information, such as metadata and …
their performance. Particularly, various kinds of content information, such as metadata and …
Fog computing architecture for personalized recommendation of banking products
E Hernández-Nieves, G Hernández… - Expert Systems with …, 2020 - Elsevier
In this article, a novel Fog Computing solution is proposed, developed in the area of fintech.
It integrates predictive systems in the process of delivery of personalized customer services …
It integrates predictive systems in the process of delivery of personalized customer services …
Came: Content-and context-aware music embedding for recommendation
Traditional recommendation methods suffer from limited performance, which can be
addressed by incorporating abundant auxiliary/side information. This article focuses on a …
addressed by incorporating abundant auxiliary/side information. This article focuses on a …
Movie recommender system with metaheuristic artificial bee
R Katarya - Neural Computing and Applications, 2018 - Springer
Recommender systems are information retrieval tool that allocates accurate
recommendations to the specific users. Collaborative movie recommender systems support …
recommendations to the specific users. Collaborative movie recommender systems support …
Catering for unique tastes: Targeting grey-sheep users recommender systems through one-class machine learning
R Alabdulrahman, H Viktor - Expert systems with applications, 2021 - Elsevier
In recommendation systems, the grey-sheep problem refers to users with unique
preferences and tastes that make it difficult to develop accurate profiles. That is, the similarity …
preferences and tastes that make it difficult to develop accurate profiles. That is, the similarity …
Attention-aware metapath-based network embedding for HIN based recommendation
Heterogeneous information network (HIN) attracts increasing attention from the communities
of recommender systems. HIN based recommendation methods can help overcome the …
of recommender systems. HIN based recommendation methods can help overcome the …
Collaborative filtering recommendation algorithm integrating time windows and rating predictions
P Zhang, Z Zhang, T Tian, Y Wang - Applied Intelligence, 2019 - Springer
This paper describes a new collaborative filtering recommendation algorithm based on
probability matrix factorization. The proposed algorithm decomposes the rating matrix into …
probability matrix factorization. The proposed algorithm decomposes the rating matrix into …