DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Electronics and Computer Science-IJAECS |
 Journal Home Volume Issue |
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Issue |
Volume-10,Issue-7 ( Jul, 2023 ) | |||||||||
Paper Title |
A Machine Learning Approach to Job Recommendation and Resume Analyser Systems | |||||||||
Author Name |
Gauri Sachin Pethkar,Ishika Raipure,Sneha Savarkar, Sukanya Kulkarni | |||||||||
Affilition |
1,2,3 Department of Electronics and Telecommunication Sardar Patel Institute of Technology Mumbai, India 4Associate Professor, Department of Electronics and Telecommunication, Sardar Patel Institute of Technology Mumbai,India | |||||||||
Pages |
105-113 | |||||||||
Abstract |
Identifying one's field of interest and persevering inthatfieldintoday'scapitalistworldwithanabundanceofcuttingedgeindustriesisveryconvenient, butalackofinformation and awareness makes it difficult to identify one'sdream position. In this case, a job recommendation system isbeneficial.Thesystemrecommendsvariousjob applicationsbasedoneducation,skillset, and experience. The degree ofprofilesimilarityisusedtocreatepreferencelistsforcorporationsandstudents.Tocollectdatafromonlinerecruiting sites, the system uses web crawling. Loop matchingwould allow for better optimization of matching outcomes andmore effective suggestion recommendations. Machine learninganddataminingmethodswereappliedtoaWebServerapplication that connects the "Job Recommendation System"frontend and backend. The data transmitted via APIs is usedby the Recommendation System to synthesize the results aftertheyhavebeenentered into the database. In order to makeexisting systems more trustworthy, the concept of a system thatincorporates a wide range of parameters and is not simply aonewayrecommendationsystemhas been developed. Alongwith this, a detailed analysis of one's resume will be performed,andrecommendationswillbemadebasedonthatforacandidate to perform better in the face of ongoing competition. Keywords - Recommendation System, Web Crawling, DataMining,Resume Ranker. | |||||||||
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