Results 11 to 20 of about 1,983,602 (251)
International Journal of Cognitive Computing in Engineering, 2020 Matrix factorization is a popular method in recommendation system. However, the quality of recommendation algorithm based on matrix decomposition is greatly affected by the sparsity of rating data.
Jing Wang, Lei Liu
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Boolean Matrix Factorization via Nonnegative Auxiliary Optimization
IEEE Access, 2021 A novel approach to Boolean matrix factorization (BMF) is presented. Instead of solving the BMF problem directly, this approach solves a nonnegative optimization problem with an additional constraint over an auxiliary matrix whose Boolean structure is ...
Duc P. Truong +3 more
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Improved Matrix Factorization Algorithm Using Social Information for Recommendation [PDF]
Jisuanji gongcheng, 2021 The recommendation models using matrix factorization have high accuracy and scalability, and they are preferred by most researchers in building a recommendation system that integrates social information.However, in the process of factorization, the ...
JIA Junjie, LIU Pengtao, CHEN Wanghu
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Weighted Nonnegative Matrix Factorization for Image Inpainting and Clustering
International Journal of Computational Intelligence Systems, 2020 Conventional nonnegative matrix factorization and its variants cannot separate the noise data space into a clean space and learn an effective low-dimensional subspace from Salt and Pepper noise or Contiguous Occlusion.
Xiangguang Dai +3 more
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Scalable non-negative matrix tri-factorization
BioData Mining, 2017 Background Matrix factorization is a well established pattern discovery tool that has seen numerous applications in biomedical data analytics, such as gene expression co-clustering, patient stratification, and gene-disease association mining.
Andrej Čopar +2 more
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Robust Probabilistic Matrix Tri-factorization
Jisuanji kexue yu tansuo, 2020 Matrix factorization is a commonly-used data analysis tool in computer vision, machine learning and data mining. In recent years, the probabilistic models of matrix factorization have become the focus of attention.
SHI Jiarong, CHEN Jiaojiao
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Directional clustering through matrix factorization [PDF]
, 2016 This paper deals with a clustering problem where feature vectors are clustered depending on the angle between feature vectors, that is, feature vectors are grouped together if they point roughly in the same direction.
Blumensath, Thomas
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BMC Bioinformatics, 2023 Background Identifying drug–target interactions (DTIs) plays a key role in drug development. Traditional wet experiments to identify DTIs are costly and time consuming. Effective computational methods to predict DTIs are useful to speed up the process of
Junjun Zhang, Minzhu Xie
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Co-sparse Non-negative Matrix Factorization
Frontiers in Neuroscience, 2022 Non-negative matrix factorization, which decomposes the input non-negative matrix into product of two non-negative matrices, has been widely used in the neuroimaging field due to its flexible interpretability with non-negativity property.
Fan Wu +3 more
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Fredholm factorization of Wiener-Hopf scalar and matrix kernels [PDF]
, 2007 A general theory to factorize the Wiener-Hopf (W-H) kernel using Fredholm Integral Equations (FIE) of the second kind is presented. This technique, hereafter called Fredholm factorization, factorizes the W-H kernel using simple numerical quadrature.
V. Daniele +3 more
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