Algorithmic Research on Personalized Resume Recommendation System Based on Network Recruitment

According to the rapid growth of Internet technologies in recent years, now the main bridge linking corporations with job hunters happens to be by way of online recruitment platforms. However, the sheer number of resumes and job postings makes it difficult for traditional resume screening to satisfy individual needs, rendering these methods ineffective. Gradually, personalized resume recommendation systems have come up as solutions to this effect, using intelligent algorithms to match resumes with jobs, thereby improving the overall efficiency of recruitment as well as job seeker satisfaction. The systems not only present exact recommendations based on users' past activity and interest profiles, but also increase the accuracy and relevancy of the recommendations by optimizing keyword weights. The purpose of this article is to present the design of a personalized resume recommendation system based on genetic algorithms, making it better equipped for precise resume recommendation through optimized keyword weights, thus achieving efficiency and precision.