Improve Skill Extraction Logic

[sriraamav]

Description:

To enhance the accuracy of skill extraction from resumes, we need to improve the logic used for matching skills. The current system uses basic regular expressions, but this issue focuses on implementing a more flexible approach using NLP or Named Entity Recognition (NER) techniques.

Tips for the issue:

• Explore using spaCy or nltk to identify skills dynamically.
• Test the extraction process with a wide variety of resumes and skill lists.
• Ensure the system can handle variations in skill names (e.g., “JavaScript” vs. “JS”).

To do:

• Ask us to assign the issue.
• Once the issue is assigned, you can start working on it.
• Create a PR.

Resource:

• spaCy documentation
• nltk documentation
• Example datasets for Named Entity Recognition (NER)

Notes:
The task is assigned on a first-come, first-serve basis, and the contributor must report progress every 3 days to ensure active development.