AI-BASED RESUME SCREENING AND CANDIDATE RANKING SYSTEM

Dashboard
resume uploading page
job descrition can be given to choose the canditate by uploaded resume
ranked resume by our model
resume designer page students can design their resume
can enhance their resumes for roles
interview preparation can be done

Inspiration

Recruiters often spend a lot of time manually checking resumes and comparing them with job requirements. We wanted to develop a system that simplifies this process and helps identify suitable candidates more quickly.

What it does

Our system allows users to upload resumes and compare them with job descriptions. It analyzes the content, calculates similarity scores, and helps rank candidates based on how closely their resumes match the job requirements.

How we built it

We built the frontend using React.js and Tailwind CSS. The backend was developed using FastAPI, with MongoDB Atlas for storing data. PyPDF2 and python-docx are used to extract text from resumes, while Scikit-learn helps calculate similarity scores. JWT is used for authentication, and Recharts supports data visualization.

Challenges we ran into

We faced challenges in extracting text from different resume formats, calculating meaningful similarity scores, connecting the frontend with the backend, and handling data correctly. Testing and debugging the application also required time and effort.

Accomplishments that we're proud of

We developed a working application that brings resume uploading, resume analysis, similarity scoring, and candidate ranking into one system. We are proud of building a solution that can make the initial recruitment process simpler and more organized.

What we learned

We learned how to integrate frontend and backend technologies, work with databases, extract text from documents, and apply text similarity techniques. We also gained experience in debugging, testing, and developing a complete web application.

What's next for AI-Based Resume Screening and Candidate Ranking System

In the future, we plan to improve the accuracy of candidate matching, support additional resume formats, enhance the ranking process, and provide more detailed screening reports. We also aim to reduce potential bias and keep human review as an important part of recruitment decisions.