 |
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
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
|
Issue: November 2025
Volume 10 | Issue 11
Review Result and Publication of Paper within : 2-3 days
Click Here For more DetailsFor Authors
Forms / Download
Published Issue Details
Editorial Board
Other IMP Links
Facts & Figure
Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 114
Article Submitted : 18456
Article Published : 7827
Total Authors : 20673
Total Reviewer : 756
Total Countries : 142
Indexing Partner
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
Published Paper Details
|
|
| Paper Title: | Recruitment platform: A Recommendation System Based Job Search Webapp |
| Authors Name: | Parth Amin , Prof. Khushboo Trivedi |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_201573
|
| Published Paper Id: | IJRTI2503150 |
| Published In: | Volume 10 Issue 3, March-2025 |
| DOI: | |
| Abstract: | The recruitment process is a crucial aspect of human resource management, requiring efficient methods to match job seekers with relevant opportunities. This research presents the development of an AI-driven recruitment platform designed to streamline candidate-employer interactions using a recommendation system powered by machine learning. The platform is built using HTML, CSS, and JavaScript for the frontend, with Flask as the backend framework, and SQLite for database management. The core functionality of the system lies in its recommendation engine, which analyses candidate profiles and job descriptions to provide personalized job suggestions. Machine learning techniques, including data preprocessing, feature engineering, and model training, are employed to enhance the accuracy of these recommendations. The platform integrates APIs for seamless data exchange, ensuring an efficient and user-friendly experience. Through this project, we demonstrate the potential of AI in automating and optimizing recruitment workflows. The results highlight improvements in candidate-job matching, reducing hiring time and enhancing employer decision-making. This research contributes to the growing field of AI-driven recruitment solutions and provides a scalable foundation for future enhancements |
| Keywords: | |
| Cite Article: | "Recruitment platform: A Recommendation System Based Job Search Webapp", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 3, page no.b356-b358, March-2025, Available :http://www.ijrti.org/papers/IJRTI2503150.pdf |
| Downloads: | 000403 |
| ISSN: |
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 |
| Publication Details: |
Published Paper ID: IJRTI2503150
Registration ID:201573
Published In: Volume 10 Issue 3, March-2025
DOI (Digital Object Identifier):
Page No: b356-b358 Country: Vadodara, Gujarat, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2503150 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2503150 |
| Share Article: | |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijrti.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
ISSN Details
 |
 |
|
ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
DOI (A digital object identifier)
| Providing A digital object identifier by DOI.ONE How to Get DOI? |
Conference
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Important Details
Join RMS/Earn 300
WhatsApp
Click Here
Click Here
Indexing Partner |
|||
| Copyright © 2025 - All Rights Reserved - IJRTI | |||