kwx 1.0.0

• Release switches kwx over to semantic versioning and indicates that it is stable

kwx 0.1.8

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

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

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

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

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