Comments (2)
Just like basic sentiment analysis in tweets is counting positive / negative, count the different patterns..
from lexicalcases.
One can use the counts of a set of salient lexical patterns to perform stylometrics. I can look at the literature and see what kinds of patterns are significant in identifying an author, then train a network on those features.
from lexicalcases.
Related Issues (20)
- [LLM][Experiment] Tokenization model using lexical patterns
- WordToken distribution spec
- LexicalMap broken example
- LexicalDispersionPlot should use Tooltip for tick marks when the dataset is large
- Investigate LexicalDispersionSmoothHistogram of LexicalSummary HOT 1
- Remove Sandwich from Symbol registry
- Add Formatting of LexicalPattern for aesthetic labeling HOT 2
- TextType could be TypeToken
- Vector DB Build
- Use FormatLexicalPattern for plot labels
- Broken link to LexicalDispersionPlot from LexicalDispersionSmoothHistorgram SeeAlso
- Old ref pages still exist on paclet page HOT 1
- ToLexicalPattern trimmed whitespace when preserving tokens HOT 2
- Strange match span HOT 2
- May need to invert theme in plots
- LexigramCount counts each element of alternatives HOT 1
- Add automatic label support for plots
- [Asys] looking at synonyms across a text HOT 1
- Improve phrasing for LexicalSummary property description
- Support common NLP statistics
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from lexicalcases.