Summarization - User Story

 

User Story:

Persona: Developer/Engineer

• As a developer managing large volumes of worknotes,

• I want to automate the summarization of these notes using Python libraries,

• So that I can quickly grasp key information and insights without reading through all the details, saving time and improving productivity.

High-Level Acceptance Criteria:

1. Completion Criteria:

   • Summarization should accurately capture key points and actions from worknotes.

   • The summary should be generated within 1 minute for each worknote.

2. Technical Requirements:

   • Utilize natural language processing (NLP) libraries such as NLTK, spaCy, or transformers.

   • The solution should handle various formats and lengths of worknotes.

   • Summaries must be concise, typically within 20% of the original content length.

3. Deliverables:

   • Python code for the summarization model.

   • Detailed documentation on how to set up and use the summarization tool.

   • Validation results demonstrating the effectiveness and accuracy of the summarization.