Jan 31, 2022 · In this paper, we propose a method, namely Guided Semi-Supervised Non-negative Matrix Factorization (GSSNMF), that performs both classification ...
In this paper, we propose a novel method, namely Guided Semi-Supervised Non-negative Matrix Factorization (GSSNMF), that performs both classification and topic ...
Apr 27, 2022 · In this paper, we propose a novel method, namely Guided Semi-Supervised Non-negative Matrix Factorization (GSSNMF), that performs both ...
Jan 31, 2022 · The results show that our proposed method improves both classification accuracy and topic coherence in comparison to past methods like Semi- ...
May 1, 2022 · In this paper, we propose a novel method, namely Guided Semi-Supervised Non-negative Matrix Factorization (GSSNMF), that performs both classification and topic ...
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Is Non-Negative Matrix Factorization supervised or unsupervised?
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Aug 30, 2019 · In this article, we propose a semi-supervised non-negative matrix factorization (NMF) model by means of elegantly modeling the label ...
In this paper, we design an effective Self-Supervised Semi-Supervised Nonnegative Matrix Factorization (S 4 NMF) in a semi-supervised clustering setting.
Our proposed method, which we refer to as Guided NMF, makes use of seed word (or generally seed-feature) supervi- sion and exploits a model based upon SSNMF. We ...
Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, notably in bioinformatics ...
We propose an NMF-based model, Guided NMF, which incorporates seed topic supervision to guide learned topics towards meaningful and coherent sets of features.