Simultaneous Visualization of Documents, Words and Topics by Tensor Self-Organizing Map and Non-negative Matrix Factorization.
Kazuki NoguchiTakuro IshidaTetsuo FurukawaPublished in: SCIS/ISIS (2020)
Keyphrases
- self organizing maps
- negative matrix factorization
- document clustering
- text documents
- tensor factorization
- latent topics
- document representation
- keywords
- topic models
- text mining
- k means
- text corpora
- text categorization
- neural network
- information retrieval
- information extraction
- document collections
- principal component analysis
- input data
- latent dirichlet allocation
- text classification
- wordnet
- topic modeling
- bag of words
- matrix factorization
- growing self organizing map
- som neural network
- named entities
- spectral clustering
- vector space model
- pattern recognition
- sparse representation
- unsupervised learning
- dimensionality reduction
- information retrieval systems
- computer vision
- probabilistic latent semantic analysis
- data mining
- clustering algorithm
- high dimensional
- latent semantic indexing
- active learning
- nearest neighbor