Hire support: resume verification and applicant ranking system using natural language processing/ John Paulo C. Alcantara, Alexis Glenn A. Aspiras, Princess Nichole B. Espinosa, Abbegail Miles Leonen, and Laica D. Ygot.--

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Alcantara, John Paulo C [author]

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TextPublication details: Manila: Technological University of the Philippines, 2025.Description: x, 143pages: 29cmContent type:

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BTH T 58.5 A43 2025

Dissertation note: College of Science.-- Bachelor of science in computer science: Technological University of the Philippines, 2025. Summary: Year by year, the job market has become more competitive, with numerous applicants submitting their resumes across multiple platforms, causing companies to invest significant time in screening resumes and assessing applicant qualifications. This situation is further worsened by resume deception and embellishment issues, creating unfairness among applicants and potential losses for companies. To address these challenges, this study developed 'Hire Support: Resume Verification and Applicant Ranking System using Natural Language Processing,' a web-based application that used NLP to help Human Resource personnel and companies by verifying resumes through supporting documents and ranking applicants based on company-defined criteria. In the web application, applicants can apply for positions from various registered companies, while companies can view applicants' score summaries across various criteria accompanied by resume verification results. The system was developed using Python, Django, and PostgreSQL for the web application, alongside Python, Tesseract OCR, SpaCy, and BERT Base Case Model for the resume verification and scoring model. Evaluation results demonstrate that the system is fully functional with compliance with ISO/IEC 25010 standards, achieving a weighted mean of 3.52, described as "Highly Acceptable" by thirty (30) respondents. The developed system efficiently automates the resume screening process, significantly reducing manual effort while enhancing credibility through verification processes, thereby supporting companies in making informed decisions in identifying the most qualified applicant.

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Item type	Current library	Shelving location	Call number	Copy number	Status	Date due	Barcode
Bachelor's Thesis COS	TUP Manila Library	Thesis Section-2nd floor	BTH T 58.5 A43 2025 (Browse shelf(Opens below))	c.1	Not for loan		BTH0006609

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Bachelor's thesis

College of Science.--
Bachelor of science in computer science: Technological University of the Philippines,
2025.

Includes bibliographic references and index.

Year by year, the job market has become more competitive, with numerous applicants
submitting their resumes across multiple platforms, causing companies to invest significant
time in screening resumes and assessing applicant qualifications. This situation is further
worsened by resume deception and embellishment issues, creating unfairness among
applicants and potential losses for companies. To address these challenges, this study
developed 'Hire Support: Resume Verification and Applicant Ranking System using
Natural Language Processing,' a web-based application that used NLP to help Human
Resource personnel and companies by verifying resumes through supporting documents
and ranking applicants based on company-defined criteria. In the web application,
applicants can apply for positions from various registered companies, while companies can
view applicants' score summaries across various criteria accompanied by resume
verification results. The system was developed using Python, Django, and PostgreSQL for
the web application, alongside Python, Tesseract OCR, SpaCy, and BERT Base Case
Model for the resume verification and scoring model. Evaluation results demonstrate that
the system is fully functional with compliance with ISO/IEC 25010 standards, achieving a
weighted mean of 3.52, described as "Highly Acceptable" by thirty (30) respondents. The
developed system efficiently automates the resume screening process, significantly
reducing manual effort while enhancing credibility through verification processes, thereby
supporting companies in making informed decisions in identifying the most qualified
applicant.

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