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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: July 2026
Volume 11 | Issue 7
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 122
Article Submitted : 25161
Article Published : 9448
Total Authors : 25094
Total Reviewer : 870
Total Countries : 172
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| Paper Title: | Smart Job-Matching Web Platform Using Vector Embeddings and Resume Parsing |
| Authors Name: | M.VIJAYA KUMAR , PATNANA GEETHIKA , AFREEN SHAIK , BAJJURI VENKATESH , MUZAVUR MABHU SUBHANI |
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IJRTI_212441
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| Published Paper Id: | IJRTI2605080 |
| Published In: | Volume 11 Issue 5, May-2026 |
| DOI: | |
| Abstract: | Recruitment is a time-consuming process in which human resource professionals manually review and analyze large volumes of resumes for every job opening. This manual screening process is inefficient, inconsistent, and often affected by human bias. Traditional recruitment systems rely primarily on keyword-based matching techniques, which fail to capture the semantic relationship between job requirements and candidate skills. To address these limitations, this paper proposes a Smart Hiring System that automates resume screening using Natural Language Processing (NLP) techniques. The system extracts important information such as skills, education, experience, and location from resume documents and compares them with job descriptions. Semantic similarity techniques employing transformer-based text embeddings and cosine similarity are used to perform accurate job-candidate matching. The system ranks candidates based on multiple weighted criteria and provides explainable results highlighting key factors influencing candidate selection. A user-friendly web interface developed using Streamlit allows recruiters to efficiently analyze resumes and view candidate rankings, thereby improving the efficiency, transparency, and consistency of the recruitment process. |
| Keywords: | Resume parsing, job matching, vector embeddings, cosine similarity, natural language processing, named entity recognition, explainable AI, recruitment automation. |
| Cite Article: | "Smart Job-Matching Web Platform Using Vector Embeddings and Resume Parsing", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 5, page no.a661-a666, May-2026, Available :http://www.ijrti.org/papers/IJRTI2605080.pdf |
| Downloads: | 000157 |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2605080
Registration ID:212441
Published In: Volume 11 Issue 5, May-2026
DOI (Digital Object Identifier):
Page No: a661-a666 Country: HYDERABAD, Telangana, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2605080 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2605080 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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