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Using spaCy (an NLP library) I created a custom project for semantic analysis and custom rule-matcher for Job Descriptions/ Resumes.

Job-Description-Parser

Using spaCy (an NLP library) I created a custom project for semantic analysis and custom rule matcher for Job Descriptions/ Resumes. You can parse multiple resumes/job descriptions at once and check the perfect profile-match for your future.

Packages required:

  • Python 3.7+
  • Pandas
  • Matplotlib
  • spaCy library (for anaconda)
    • command for installing: conda install -c conda-forge spacy
  • spaCy english core language package
    • command for downloading: python -m spacy download en_core_web_sm
  • For any confusion you can visit https://spacy.io/ and check out their documentation.

Files Required:

  • An excel file with 2 sheets:
    • Keywords: for custom rule matching
    • JDs/Resume: list of company/candidate names and their Job Descriptions/resumes.

Output Files:

  • An Excel sheet with company/candidate names, Main-Skill domain, Specific-skill, Specific-skill count(no. of time a particular skill is mentioned).
  • An Excel sheet with proportions of skill domains for each profile.
  • A bar graph chart(.png file) visualizing the skill-set and their ratios for each and every profile.