https://github.com/richackashyap/using-bart-model-and-named-entity-recognition-to-summarize-text-and-create-a-mind-map-

Generation of mind maps based on any given paragraph
https://github.com/richackashyap/using-bart-model-and-named-entity-recognition-to-summarize-text-and-create-a-mind-map-

mind-mapping nlp spacy

Last synced: about 2 months ago
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Generation of mind maps based on any given paragraph

• Host: GitHub
• URL: https://github.com/richackashyap/using-bart-model-and-named-entity-recognition-to-summarize-text-and-create-a-mind-map-
• Owner: richackashyap
• Created: 2024-07-20T17:05:36.000Z (7 months ago)
• Default Branch: main
• Last Pushed: 2024-07-20T17:18:01.000Z (7 months ago)
• Last Synced: 2024-12-18T18:12:53.745Z (about 2 months ago)
• Topics: mind-mapping, nlp, spacy
• Language: Python
• Homepage:
• Size: 316 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
This study explores the application of Natural Language Processing algorithms which is used to summarize text paragraphs and create a mind map off it. 

The main objective involves extracting only the sentences and words that are directly linked to the main topic and using those words to create a summarization of the paragraphs. 

The methodology involves using libraries such as spaCy and Graphviz. 

The output is obtained by involving three steps: summarizing, extracting key points and making the mind map