/Automatic-Text-Summarizer

Automatic Text Summarizer with various approaches in NLP and Django

Primary LanguagePythonMIT LicenseMIT

Automatic-Text-Summarizer

Automatic Text Summarizer with various approaches in NLP and Django

Approahces used

  • LexRank
  • LSA (Latent semantic analysis)
  • KL-Sum
  • Summarization with T5 Transformers
  • Summarization with BART Transformers
  • Summarization with GPT-2 Transformers
  • Summarization with XLM Transformers
  • Luhn

Technologies

  • Django Framework
  • NLTK library for NLP
  • Postgresql ( currently using Sqlite )
  • Django REST Framework

Improvements for the future

  • Inputs not taken for the document text
  • Integrating with Postgresql
  • API creation with DRF
  • Analysing the performance of the results of all the algos
  • Manually Hypertuning the algos to increase performance
  • Adding animations and proper styling
  • A Dashboard to compare the results of all the algos
  • ( optional ) Analysis of the text data using elasticsearch ?

Issues

  • Output file is not automatically created ( might use callback, asynchronous ? )
  • The form field of the input algo and text area is not styled properly
  • About Page is blank
  • Slow loading of the algo's ( add Redis for caching ? )

New Ideas