Paper Title
A Machine Learning Approach to Job Recommendation and Resume Analyser Systems

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.

Author - Gauri Sachin Pethkar,Ishika Raipure,Sneha Savarkar, Sukanya Kulkarni

Published : Volume-10,Issue-7  ( Jul, 2023 )

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