Automatic Text Categorization
summary
Covers grouping and labeling texts: defines text clustering and text classification with example use cases. Reviews topic modeling methods—generative language models, pLSA, and LDA—and tools for them. Describes applying clustering and automated rubrication to a stream of news texts.
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chapters (13)
- 0:00Introduction
- 2:39Text processing tasks
- 4:26Clustering and classification problems
- 8:25Generative algorithms and bag-of-words
- 13:02Latent Dirichlet allocation
- 16:44LDA in practice
- 24:14Supervised vs unsupervised learning
- 27:04Morphological text analysis
- 31:02Model quality evaluation
- 33:50Engineering implementation aspects
- 36:17Short text handling
- 38:27Technology and library selection
- 40:59Conclusion and Q&A
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