Grants and Contributions:

Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019).

TAS (Techno Aero Services inc.) is a Canadian recruitment agency specialized in aeronautics, engineering, andx000D
technology. At TAS, candidates currently submit resumes to a database through a web interface. These resumesx000D
are then manually processed by recruiters before a suitable candidate is matched to a position. Through thisx000D
laborious manual process, great prospective candidates often get lost in the piles. This project aims to leveragex000D
text mining and machine learning techniques to automatically collect information about prospective candidatesx000D
from their submitted resume and public profiles on websites like Linked In, Twitter, and Facebook to providex000D
recruiters with an overall picture of a candidate's strengths and weaknesses. Both the technical andx000D
communication skills of the candidates will be analyzed and summarized. The goal is to provide recruiters withx000D
the information they need to judge a candidate on both his mastery of key skills and his ability to fit into thex000D
company culture.x000D
To achieve this goal, we will leverage big data processing infrastructure, including machine learning throughx000D
frameworks like Google Tensorflow, to automatically extract useful information from textual data aboutx000D
prospective candidates. Deep learning approaches have proved to be powerful tools for patterns recognition andx000D
classification in diverse problems, such as speech, text, and image recognition. We expect it to also achieve ax000D
good performance in automatically detecting useful signal about prospective candidates from data collectedx000D
about them from their resume and the Web.