Twin labeled LDA: a supervised topic model for document classification.
Wei WangBing GuoYan ShenHan YangYaosen ChenXinhua SuoPublished in: Appl. Intell. (2020)
Keyphrases
- document classification
- topic models
- text documents
- latent dirichlet allocation
- text mining
- supervised topic models
- supervised learning
- topic modeling
- text classification
- latent topics
- probabilistic model
- semi supervised
- document clustering
- text categorization
- unsupervised learning
- news articles
- generative model
- co occurrence
- gibbs sampling
- variational inference
- training set
- topic discovery
- classification algorithm
- training data
- learning algorithm
- latent variables
- text analysis
- markov networks
- data mining
- information retrieval
- statistical topic models
- web documents
- active learning
- feature selection
- unlabeled data
- image representation
- image classification
- text classifiers
- information extraction
- knowledge discovery
- lda model
- data analysis
- search engine