AI-Based Automation of the Candidate Recruitment and Management System for TAS

TAS (Techno Aero Services Inc.) is a Canadian recruitment agency specialized in aeronautics, engineering, and technology. At TAS, candidates currently submit resumes to a database through a web interface. These resumes are then manually processed by recruiters before a suitable candidate is matched to a position. Through this laborious manual process, great prospective candidates often get lost in the piles. This project aims to leverage text mining and machine learning techniques to automatically collect information about prospective candidates from their submitted resume and profiles on social and professional networks like LinkedIn, Twitter, and Facebook to provide recruiters with an overall picture of a candidates strengths and weaknesses. Both the technical and communication skills of the candidates will be analyzed and summarized. The goal is to provide recruiters with the information they need to judge a candidate on both his mastery of key skills and his ability to fit into the company culture. In addition, we aim to leverage the existing data of the candidates and their employment records to build Business Intelligence (BI) component for the proposed system to predict business trends, support business decisions and to reach and recommend prospective candidates for available jobs in TASs job pool.

Faculty Supervisor:

Foutse Khomh

Student:

Biruk Muse

Partner:

TAS Inc.

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Program: