Non-negative matrix factorization temporal topic models and clinical text data identify COVID-19 pandemic effects on primary healthcare and community health in Toronto, Canada.
Christopher MeaneyMichael D. EscobarRahim MoineddinTherese A. StukelSumeet KaliaBabak AliarzadehTao ChenBraden O'NeillMichelle GreiverPublished in: J. Biomed. Informatics (2022)
Keyphrases
- topic models
- text data
- negative matrix factorization
- text documents
- document clustering
- text mining
- topic modeling
- probabilistic latent semantic analysis
- latent dirichlet allocation
- text classification
- probabilistic model
- latent topics
- principal component analysis
- natural language processing
- matrix factorization
- generative model
- sparse representation
- document collections
- information extraction
- high dimensional
- data mining
- text categorization
- clustering method
- structured data
- named entities
- wordnet
- vector space model
- keywords
- co occurrence
- collaborative filtering
- knowledge representation
- machine learning