Automated Resume Scoring and Course Recommendation

The AI-powered Automated Resume Scoring and Course Recommendation system analyzes resumes and makes suggestions for improvement. The system, which uses machine learning algorithms to detect areas that require improvement, assists job seekers in crafting resumes that can successfully navigate the screening procedures of job interviews. In addition to analyzing the layout, language, and spelling to make sure industry standards are fulfilled, the system uses methods like natural language processing, text mining, and sentiment analysis to collect insights from the candidate's achievements, education, experience, and abilities. To close skill gaps, the algorithm might suggest appropriate courses or certifications in addition to resume analysis. This technique helps both recruiters and job seekers: recruiters can identify the best applicants, which promotes the hiring process, while job seekers may improve their resumes to better match job requirements, enhancing their chances of obtaining interviews.

Authors

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2024-11-27
DOI
https://doi.org/10.36948/ijfmr.2024.v06i06.29890
Citations
1
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
Field-Weighted Citation Impact
0.35
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article

Automated Resume Scoring and Course Recommendation

Pritesh Patil, Ashok Kale, Yash Deshpande -, Abhishek Hole - et al.
1 citations
International Journal For Multidisciplinary Research
Intelligent Tutoring Systems and Adaptive Learning
0.35
article

Automated Resume Scoring and Course Recommendation

Pritesh Patil, Ashok Kale, Yash Deshpande -, Abhishek Hole -, Manisha Mali -
article en
1 citations

Abstract

The AI-powered Automated Resume Scoring and Course Recommendation system analyzes resumes and makes suggestions for improvement. The system, which uses machine learning algorithms to detect areas that require improvement, assists job seekers in crafting resumes that can successfully navigate the screening procedures of job interviews. In addition to analyzing the layout, language, and spelling to make sure industry standards are fulfilled, the system uses methods like natural language processing, text mining, and sentiment analysis to collect insights from the candidate's achievements, education, experience, and abilities. To close skill gaps, the algorithm might suggest appropriate courses or certifications in addition to resume analysis. This technique helps both recruiters and job seekers: recruiters can identify the best applicants, which promotes the hiring process, while job seekers may improve their resumes to better match job requirements, enhancing their chances of obtaining interviews.

International Journal For Multidisciplinary ResearchVol. 6(6)
Quality Education
Openalex Percentile: Top 31%
Intelligent Tutoring Systems and Adaptive Learning
0.35
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Automated Resume Scoring and Course Recommendation — Pritesh Patil, Ashok Kale, et al. · International Journal For Multidisciplinary Research (2024) | TGRS Research Map | TGRS