CareerBoost:通过改进简历和量身定制的建议彻底改变求职方式

Asoke Nath, Sunayana Saha, Shrestha Dey Sarkar, Anchita Bose
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引用次数: 0

摘要

简历增强器和工作推荐系统旨在应对求职者在当今动态就业市场中面临的独特挑战。本系统利用最先进的自然语言处理(NLP)技术,为简化求职流程提供量身定制的解决方案。本系统的简历增强器组件利用先进的 NLP 算法分析简历和职位描述,生成全面的资格评分和有针对性的技能建议。这可确保对求职者的简历进行优化,向潜在雇主有效展示其资历和专长。目前的 "工作推荐 "功能可根据每个用户选定的角色或职业抱负提供个性化的工作列表。作者采用了随机森林分类器和 K-means 聚类等机器学习算法,将候选人的偏好和资历与相关工作机会相匹配,提高了找到最合适工作的可能性。总之,简历增强器和工作推荐系统是求职者的宝贵工具,使他们能够自信地应对现代就业市场的复杂局面。凭借以用户为中心的方法和先进的技术,本系统提高了求职者的就业能力,促进了求职者在职业生涯各个阶段的职业发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CareerBoost: Revolutionizing the Job Search with Resume Enhancement and Tailored Recommendations
The Resume Enhancer and Job Recommendation System is designed to meet the unique challenges faced by job seekers in today's dynamic job market. Leveraging cutting-edge natural language processing (NLP) techniques, the present system provides a tailored solution to streamline the job search process. The present Resume Enhancer component utilizes advanced NLP algorithms to analyse resumes and job descriptions, generating comprehensive eligibility scores and targeted skill recommendations. This ensures that candidates' resumes are optimized to effectively showcase their qualifications and expertise to potential employers. The present Job Recommendation feature delivers personalized job listings tailored to each user's selected roles or career aspirations. The authors implemented machine learning algorithms such as the Random Forest Classifier and K-means Clustering, the system matches candidate preferences and qualifications with relevant job opportunities, increasing the likelihood of finding the perfect fit. Overall, the Resume Enhancer and Job Recommendation System serves as a valuable tool for job seekers, empowering them to navigate the complexities of the modern job market with confidence. With its user-centric approach and advanced technology, the present system enhances employability and facilitates career growth for individuals at every stage of their professional journey.
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