Resume Parser And Ranker

Hiring Simplified.

Comment 3

Inspiration

During the process of hiring we used to see the employees of the HR department used to go through thousands of resumes by manually reading them and shortlisting like 10 candidates out of them. This process is very tedious and consumes a lot of human resource. Thus we came up with an idea to automate this job by making an AI powered Resume Parser.

What it does

The resume parser uses advance Artificial Intelligence and its exceptional ability to process Human Languages like English to go through 1000's of resume at immeasurably high speeds and give the output as the perfect candidate for the job or the top 5 best candidates along with match percentages of the candidates resume with the job description provided. It also has a very helpful feature where the user can explicitly select the skills that he is looking for and filter the candidates according to it.

How we built it

We used a state-of-the-art Natural Language Processing library known as spacy to build and train extremely powerful AI models that we used to read the resumes and extract the text from the resumes that can be provided in various file formats like .docx, .pdf, .png etc. Further we used libraries like Matplotlib and Ski-Kit learn for matching and analysis of resumes with respect to the job description. We also used HTML, CSS and Javascript in order to make the frontend of the website and flask to make the API.

Challenges we ran into

The current libraries that were being used in the current solutions of resume parsing and ranking were not perfectly optimized for being used in various file formats. Thus our challenge was to provide a fluid solution by giving the user an option to provide resumes in various file formats.

Accomplishments that we're proud of

In this solution we have provided an option to match the given resume and compare it with the provided job description given by HR or the employer. This way we can find the perfect candidate for the role.

What we learned

We learned advance techniques to work with natural language processing with this project. We also learned about extraction of content from various file formats. we also learned how to operate on spacy library and create new models.

What's next for Resume Parser And Ranker

In the near future we are thinking of integrating this project with an ATS and providing a complete end-to-end solution for the hiring process.

Share this project:

Updates