An overview of recommendation techniques and their applications in healthcare
With the increasing amount of information on the internet, recommendation system (RS) has
been utilized in a variety of fields as an efficient tool to overcome information overload. In …
been utilized in a variety of fields as an efficient tool to overcome information overload. In …
A survey of community detection in complex networks using nonnegative matrix factorization
Community detection is one of the popular research topics in the field of complex networks
analysis. It aims to identify communities, represented as cohesive subgroups or clusters …
analysis. It aims to identify communities, represented as cohesive subgroups or clusters …
Fast and accurate non-negative latent factor analysis of high-dimensional and sparse matrices in recommender systems
A fast non-negative latent factor (FNLF) model for a high-dimensional and sparse (HiDS)
matrix adopts a Single Latent Factor-dependent, Non-negative, Multiplicative and …
matrix adopts a Single Latent Factor-dependent, Non-negative, Multiplicative and …
Temporal pattern-aware QoS prediction via biased non-negative latent factorization of tensors
Quality-of-service (QoS) data vary over time, making it vital to capture the temporal patterns
hidden in such dynamic data for predicting missing ones with high accuracy. However …
hidden in such dynamic data for predicting missing ones with high accuracy. However …
A survey of collaborative filtering-based recommender systems: From traditional methods to hybrid methods based on social networks
R Chen, Q Hua, YS Chang, B Wang, L Zhang… - IEEE …, 2018 - ieeexplore.ieee.org
In the era of big data, recommender system (RS) has become an effective information
filtering tool that alleviates information overload for Web users. Collaborative filtering (CF) …
filtering tool that alleviates information overload for Web users. Collaborative filtering (CF) …
Diversified regularization enhanced training for effective manipulator calibration
Recently, robot arms have become an irreplaceable production tool, which play an important
role in the industrial production. It is necessary to ensure the absolute positioning accuracy …
role in the industrial production. It is necessary to ensure the absolute positioning accuracy …
Elliot: A comprehensive and rigorous framework for reproducible recommender systems evaluation
Recommender Systems have shown to be an effective way to alleviate the over-choice
problem and provide accurate and tailored recommendations. However, the impressive …
problem and provide accurate and tailored recommendations. However, the impressive …
Robust latent factor analysis for precise representation of high-dimensional and sparse data
High-dimensional and sparse (HiDS) matrices commonly arise in various industrial
applications, eg, recommender systems (RSs), social networks, and wireless sensor …
applications, eg, recommender systems (RSs), social networks, and wireless sensor …
A deep latent factor model for high-dimensional and sparse matrices in recommender systems
Recommender systems (RSs) commonly adopt a user-item rating matrix to describe users'
preferences on items. With users and items exploding, such a matrix is usually high …
preferences on items. With users and items exploding, such a matrix is usually high …
Advancing non-negative latent factorization of tensors with diversified regularization schemes
Dynamic relationships are frequently encountered in big data and services computing-
related applications, like dynamic data of user-side QoS in Web services. They are modeled …
related applications, like dynamic data of user-side QoS in Web services. They are modeled …