Method evidence record
Multimodal NMF Topic Model
Multimodal NMF Topic Model extends Non-negative Matrix Factorization to simultaneously discover latent topics across multiple data modalities — such as text and images — by enforcing shared or aligned low-rank factor matrices. It uncovers coherent, interpretable topics that jointly explain patterns in both textual and visual (or other) feature spaces.
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Multimodal Non-negative Matrix Factorization Topic Model
Taxonomic method record · ml-model / deep-learning
- Cai, D., He, X., Han, J., & Huang, T. S. (2011). Graph regularized NMF. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(8), 1548–1560. · URL
- Non-negative matrix factorization. Wikipedia. · URL
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