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Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2950701
Abstract: Due to the explosive growth of image data, image annotation has been one of the most popular research directions in computer vision. It has been widely used in image retrieval, image analysis and understanding. Because…
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Keywords:
tri factorization;
image annotation;
annotation;
image ... See more keywords
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Published in 2023 at "IEEE Transactions on Knowledge and Data Engineering"
DOI: 10.1109/tkde.2022.3145489
Abstract: As a novel paradigm for data mining and dimensionality reduction, Non-negative Matrix Tri-Factorization (NMTF) has attracted much attention due to its notable performance and elegant mathematical derivation, and it has been applied to a plethora…
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Keywords:
data clustering;
text data;
matrix tri;
non negative ... See more keywords
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Published in 2017 at "BioData Mining"
DOI: 10.1186/s13040-017-0160-6
Abstract: BackgroundMatrix 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. Matrix factorization learns a latent data…
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Keywords:
matrix tri;
factorization;
matrix;
tri factorization ... See more keywords
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Published in 2023 at "Mathematical Biosciences and Engineering"
DOI: 10.3934/mbe.2023556
Abstract: Non-negative matrix factorization (NMF) has been widely used in machine learning and data mining fields. As an extension of NMF, non-negative matrix tri-factorization (NMTF) provides more degrees of freedom than NMF. However, standard NMTF algorithm…
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Keywords:
tri factorization;
matrix tri;
non negative;
negative matrix ... See more keywords