Lander - A text-mining tool evaluating resumes and job position.
Project Author
Issue Date
2023-05-05
Authors
Nguyen, Mai
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First Reader
Luman, Douglas J.
Additional Readers
Bonham-Carter, Oliver N.
Keywords
Text mining , Natural language processing , Applicant tracking system , Recruitment , Human Resources , Resume , Job
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Abstract
Recent statistics show that 75% of applicants are filtered out from applicant pools for a position by the Applicant Tracking System due to the inflexi- bility of machines in understanding different resume formats and wordings. The gloomy scenery of the job market in general, adding to the inclining competitiveness in the tech job market makes it much harder for candidates to successfully land their dream job. Thus, it is important to examine and form a tool that can assist new graduates, the most vulnerable individu- als in the job market, to elevate their employment prospects. Lander is a text-mining-based tool that helps the student increase their chance of pass- ing the initial resume screening round by optimizing their resume using a keyword-suggesting system. Moreover, Lander will also match a candidate to a compatible job by matching the experience in their resume to a job description, and in return, increase the chance of getting accepted into the job.
Description
Chair
Major
Computer Science
Department
Computer Science
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Honors
Computer Science, 2023