Survey of similarity functions on neighborhood-based collaborative filtering
H Khojamli, J Razmara - Expert Systems with Applications, 2021 - Elsevier
Today, recommender systems play a vital role in the acceleration of searches by internet
users to find what they are interested in. Among the strategies proposed for recommender …
users to find what they are interested in. Among the strategies proposed for recommender …
Knowledge graph self-supervised rationalization for recommendation
In this paper, we introduce a new self-supervised rationalization method, called KGRec, for
knowledge-aware recommender systems. To effectively identify informative knowledge …
knowledge-aware recommender systems. To effectively identify informative knowledge …
A hybrid recommendation system with many-objective evolutionary algorithm
Recommendation system (RS) is a technology that provides accurate recommendations to
users. However, it is not comprehensive to only consider the accuracy of the …
users. However, it is not comprehensive to only consider the accuracy of the …
Collaborative filtering and kNN based recommendation to overcome cold start and sparsity issues: A comparative analysis
Collaborative Filtering (CF) has intrigued several researchers whose goal is to enhance
Recommender System's performance by mitigating their drawbacks. CF's common idea is to …
Recommender System's performance by mitigating their drawbacks. CF's common idea is to …
The effects of controllability and explainability in a social recommender system
CH Tsai, P Brusilovsky - User Modeling and User-Adapted Interaction, 2021 - Springer
In recent years, researchers in the field of recommender systems have explored a range of
advanced interfaces to improve user interactions with recommender systems. Some of the …
advanced interfaces to improve user interactions with recommender systems. Some of the …
A momentum-accelerated Hessian-vector-based latent factor analysis model
Service-oriented applications commonly involve high-dimensional and sparse (HiDS)
interactions among users and service-related entities, eg, user-item interactions from a …
interactions among users and service-related entities, eg, user-item interactions from a …
Recommending based on implicit feedback
Recommender systems have shown to be valuable tools for filtering, ranking, and discovery
in a variety of application domains such as e-commerce, media repositories or document …
in a variety of application domains such as e-commerce, media repositories or document …
New perspectives on gray sheep behavior in E-commerce recommendations
With the exponential rise in the size of data being generated, personalization based on
recommender systems has become an important aspect of digital marketing strategy of E …
recommender systems has become an important aspect of digital marketing strategy of E …
A deep neural network-based collaborative filtering using a matrix factorization with a twofold regularization
A Noulapeu Ngaffo, Z Choukair - Neural computing and applications, 2022 - Springer
In recent years, the ever-growing contents (movies, clothes, books, etc.) accessible and
buyable via the Internet have led to the information overload issue and therefore the item …
buyable via the Internet have led to the information overload issue and therefore the item …
Personalized food recommendation—state of art and review
In the present scenario, people are becoming more health-conscious. There are various
factors like age, gender, and genetic history on which diet matters. The internet is flooded …
factors like age, gender, and genetic history on which diet matters. The internet is flooded …