Personalized Resume Recommendation
This system employs machine learning methods and a big data platform to train on a massive volume of job seekers' resumes. Unlike ordinary conditional filtering, this system can efficiently and accurately provide suitable and reliable talent recommendations from a big data processing perspective for IT positions that recruiters are looking to fill, reducing recruitment costs and using big data technology to bridge the gap between recruiters and outstanding talent. Through research on massive resume data and company recruitment information, this project analyzes the characteristic features of personal resumes, companies, and company positions. From the recruiter's perspective, it conducts exploratory research centered on personalized recommendation technology to help recruiters obtain talent information in a more accurate and efficient manner. Based on this concept, a prototype system is implemented that can automatically recommend more appropriate resumes based on the characteristics of job postings.