Resume intelligent recommendation algorithm based on natural semantic analysis technology

Abstract

The invention discloses a resume intelligent recommendation algorithm based on a natural semantic analysis technology. Based on massive user behavior data of delivery, screening, interview, job entryand the like of the cloud recruitment platform, a resume and position matching recommendation algorithm is designed, and proper resumes or positions can be automatically recommended to the recruitersand job seekers according to the algorithm, so that the efficiency of network recruitment and job hunting is improved; the traditional recommendation algorithm includes content-based recommendation orpreference-based recommendation, the algorithm of the invention is based on the combination of the synergisms of the content-based recommendation or preference-based recommendation and adds some potential influence factors such as industries and companies at the same time so as to achieve accurate and rapid recommendation; the method has the advantages that on the basis of a cloud recruitment platform, hundreds of billions of recruitment behavior data are deposited on the platform, a recommendation algorithm is based on the matching degree of posts and the preference of user behaviors, afterrecommendation, the recommendation algorithm feeds back to a recommendation system according to a processing result of a user, and the recommendation system learns a data model again, so that the accuracy is higher and higher.

Description

technical field [0001] The invention relates to the relevant field of resume information retrieval, in particular to a resume intelligent recommendation algorithm based on natural semantic analysis technology. Background technique [0002] As the competition for talents among enterprises continues to intensify, how to find talents faster and more accurately within a reasonable budget has become an issue of increasing concern to enterprises, and it is also a major challenge faced by the human resources department (HR) of enterprises. Among these challenges , the more obvious pain points include: a. Understanding of recruitment needs: For corporate HR, to improve recruitment performance, the first task is to be able to deeply understand the recruitment needs of the employing department. There are differences in the understanding of recruitment requirements, and if the requirements are not well understood, it will not only waste HR's resume screening time, but also waste the in...

AI Technical Summary

Problems solved by technology

[0002] As the competition for talents among enterprises continues to intensify, how to find talents faster and more accurately within a reasonable budget has become an issue of increasing concern to enterprises, and it is also a major challenge faced by the human resources department (HR) of enterprises. Among these challenges , the more obvious pain points include: a. Understanding of recruitment needs: For corporate HR, to improve recruitment performance, the first task is to be able to deeply understand the recruitment needs of the employing department. There are differences in the understanding of recruitment requirements, and if the requirements are not well understood, it will not only waste HR's resume screening time, but also waste the interview time of the employing department, thereby reducing the employing department's recruitment satisfaction with HR

b. Resume screening consumes a lot of time for HR: In the recruitment process, HR spends a lot of time on resume screening. Manually screening resumes, the average pass rate of resumes is about 20%, which means that browsing 100 resumes may only 20 suitable resumes, and these 20 suitable resumes, after telephone communication, there may be only 5 candidates who are willing to accept interviews, and only 2-3 people may actually be interviewed. Such a recruitment funnel makes HR have to be exhausted every day Continuously screen a large number of resumes, but cannot invest enough energy in relatively accurate talent identification

c. The company's own talent pool cannot be well utilized: the company has accumulated a large number of resumes that have been screened and left for interview evaluation during the recruitment process. Many of them have a high degree of job matching, but they did not accept the offer for various reasons. Yes, with the development of enterprises and the continuous improvement of candidate experience, resumes in the talent pool are actually an important source of recruitment channels. Channel newly acquired resumes instead of effectively utilizing the more valuable corporate talent pool

[0003] After the above analysis, the current recruitment efficiency is not high. The main reason is that candidates and companies cannot be well matched. Job seekers need to post jobs on different recruitment websites, and the same job has dozens or even hundreds of pages. Similarly, in order to save trouble, the candidate’s resume is “sea investment”, and the company’s HR is “sea selection”. Both parties are time-consuming and laborious, and the efficiency is low.

Images