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Releases: andrewtavis/kwx

kwx 1.0.0

28 Dec 15:01
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kwx 0.1.8

29 Apr 11:59
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Changes include:

  • Support has been added for gensim 3.8.x and 4.x
  • Dependencies in requirement and environment files are now condensed
  • An alert for users when the corpus size is to small for the number of topics was added
  • An import error for pyLDAvis was fixed

kwx 0.1.7.3

30 Mar 06:34
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Changes include:

  • Switching over to an src structure
  • Removing the lda_bert method because its dependencies were causing breaks
  • Code quality is now checked with Codacy
  • Extensive code formatting to improve quality and style
  • Bug fixes and a more explicit use of exceptions
  • More extensive contributing guidelines
  • Tests now use random seeds and are thus more robust

kwx 0.1.5

15 Mar 13:49
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Changes include:

  • Keyword extraction and selection are now disjointed so that modeling doesn't occur again to get new keywords

  • Keyword extraction and cleaning are now fully disjointed processes

  • kwargs for sentence-transformers BERT, LDA, and TFIDF can now be passed

  • The cleaning process is verbose and uses multiprocessing

  • The user has greater control over the cleaning process

  • Reformatting of the code to make the process more clear

kwx 0.1.0

17 Feb 21:24
0a3d6f1
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First stable release of kwx

Changes include:

  • Full documentation of the package

  • Virtual environment files

  • Bug fixes

  • Extensive testing of all modules with GH Actions and Codecov

  • Code of conduct and contribution guidelines

kwx 0.0.2.2

31 Jan 13:25
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The minimum viable product of kwx:

  • Users are able to extract keywords using the following methods

    • Most frequent words
    • TFIDF words unique to one corpus when compared to others
    • Latent Dirichlet Allocation
    • Bidirectional Encoder Representations from Transformers
    • An autoencoder application of LDA and BERT combined
  • Users are able to tell the model to remove certain words to fine tune results

  • Support is offered for a universal cleaning process in all major languages

  • Visualization techniques to display keywords and topics are included

  • Outputs can be cleanly organized in a directory or zip file

  • Runtimes for topic number comparisons are estimated using tqdm