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• W4377699356 abstract "A job seeker always spends hours searching through the massive amount of recruiting information on the Internet to identify ones that are helpful. The field of job recommender systems for recruiting has just evolved and experienced rapid growth. The job recommender systems view user profiles and design recommendation technologies that have drawn interest, been studied in academia, and been put into practice for some use cases in industries. This study creates and puts into practice a recommendation system for online job searching to lessen this tedious task. In this study, an architecture has been proposed to extract the most suitable professions based on the resume of the individual. Natural Language Processing and Machine learning are used to train the model that predicts the profession. Then using this profession as a key, jobs are web scraped from Naukri.com. The required skills of the jobs are matched with the individual's skills using a cosine similarity algorithm and are ranked and displayed to the user." @default.
• W4377699356 created "2023-05-24" @default.
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• W4377699356 date "2023-04-07" @default.
• W4377699356 modified "2023-10-17" @default.
• W4377699356 title "Resume Analysis and Job Recommendation" @default.
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• W4377699356 doi "https://doi.org/10.1109/i2ct57861.2023.10126171" @default.
• W4377699356 hasPublicationYear "2023" @default.
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