Most companies burden so much to their HR department with the hiring procedure. Most of the companies do shortlist candidates manually. This manual procedure consumes so much time and resources. Pakistan produces around 4,45,000 university graduates and 10,000 computer science graduates every year.
HR Automated Assistant
Most companies burden so much to their HR department with the hiring procedure. Most of the companies do shortlist candidates manually. This manual procedure consumes so much time and resources. Pakistan produces around 4,45,000 university graduates and 10,000 computer science graduates every year.
Moreover, the average number of candidates who apply for a job is 118, and almost 20 percent of those candidates get an interview call. In our FYP, we will develop an automated system that will facilitate the HR department by categorizing candidates using machine learning techniques. This system aims to save the time and resources of the organization.
In this document, we will briefly explain the features of HR automated assistant. It focuses on the capabilities needed by the stakeholders and the target users and why these needs exist.
Objective of this system is to help company in analysing the resumes without any human effort. Company employees must work for reading hundreds of resumes that is very time taking task. Our system will reduce human effort as well as company resources. Objective of this system is to help company in analysing the resumes without any human effort. Company employees must work for reading hundreds of resumes that is very time taking task. Our system will reduce human effort as well as company resources.
This project targets the companies that post the job online and get thousands of resumes. HRAA is an automated resumes categorization web-based application. HRAA will reduce the human effort of filtering the resumes out of thousands of resumes.
The user can register himself as a recruiter or as a candidate. In the registration process, the recruiters will insert their company information, and the candidates will insert their personal information.
The recruiter can post multiple jobs based upon the skills they needed.
As the candidate will upload his/her resume, the system will perform text processing using NLP algorithms. After processing, the system will check to which category the candidate belongs.
After categorization, the system will shortlist candidates based on the recruiter’s requirements.
As the system will shortlist candidates, the system will let the recruiter auto-generate email to respective candidates.
Technologies:
For frontend: React js.
For Backend: Node js
Database: MongoDB
Skills are categorized using NLP.

| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Softwares, Courses | Miscellaneous | 2 | 5 | 10 |
| Total in (Rs) | 10 |
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