Human resource bidirectional recommendation system based on data mining and privacy protection technology

Abstract

The invention discloses a human resource bidirectional recommendation system based on data mining and privacy protection technology, and belongs to the technical field of data mining and recommendation systems. The system comprises a data acquisition module, a database establishment module, a data anonymization module, a data arrangement module, a data mining module and a recommendation algorithmmodule. According to the invention, accurate recommendation can be provided for colleges and universities in the field of recruitment and employment of graduates so as to improve the employment rate.Social recruitment resources can be managed by recruitment enterprises or human resource departments; Meanwhile, a big data visual display module in the system can be used for school employment or government related departments to monitor market conditions, make scientific decisions and take measures as soon as possible, and the application range is wide. Meanwhile, the problems of insufficient information amount of the recommendation system, lack of accurate recommendation, unequal recommendation of two parties of the recommendation system, lack of bidirectional recommendation, risk of recommendation system data and lack of privacy protection are solved.

Description

technical field [0001] The invention belongs to the technical field of data mining and recommendation systems, and in particular relates to a two-way recommendation system for human resources based on data mining and privacy protection technology. Background technique [0002] In recent years, the global economic situation has been in an unstable development trend. Under the influence of intensified international economic frictions, my country's economic growth has continued to decline. At the same time, the number of college graduates has also increased year by year, and employment competition has become increasingly fierce. The employment pressure faced by college graduates is increasing, and many problems such as rising unemployment rate are becoming more and more prominent. The overall quality structure is not high and other objective factors, the employment mechanism of the industry is not sound and perfect; the employment channels are not smooth and transparent; The cogn...

AI Technical Summary

Problems solved by technology

[0002] In recent years, the global economic situation has been in an unstable development trend. Under the influence of intensified international economic frictions, my country's economic growth has continued to decline. At the same time, the number of college graduates has also increased year by year, and employment competition has become increasingly fierce. The employment pressure faced by college graduates is increasing, and many problems such as rising unemployment rate are becoming more and more prominent. The overall quality structure is not high and other objective factors, the employment mechanism of the industry is not sound and perfect; the employment channels are not smooth and transparent; The cognition is not clear, and the efficiency is low when it hits the wall everywhere; the recruiter frequently interviews the employees, but they can't find the right candidates they need, which wastes precious human resources. Therefore, we urgently need a set of accurate and scientific human resources Two-way recommendation system to solve the above outstanding problems

[0003] The existing technology has the following problems: 1. The existing recommendation system has insufficient information and lacks accurate recommendation: it only matches and recommends based on the tags provided or selected by the job seeker, without taking into account the internal conditions of the job seeker, such as: resume or Detailed information such as school history, lack of analysis and comparison of the abilities and demands of similar job seekers as well as the final results in the big data environment, ultimately leading to inaccurate recommendation results; 2. The two sides of the existing recommendation system are not equal, lacking two-way recommendation : The focus is only on the unilateral wishes of the job seekers or recruiters, and the personal wishes of the job seekers and the objective needs of the recruiters cannot be considered at the same time. The lack of comprehensive consideration of the interests of both parties leads to the failure of the recommendation due to the asymmetry of information between the two parties. It also lacks relevant functions for recruiters to search and recommend suitable talents; 3. The existing recommendation system data is risky and lacks privacy protection: accurate recommendation depends on accurate personal data and past recruitment and employment data. Without protection, employees and recruiters may refuse to provide or provide incomplete and untrue data due to concerns about privacy risks caused by their own data leakage, which directly leads to failure of recommendation. In response to this problem, the system The privacy protection of raw data often plays an important role, but in the current research, it often lacks the consideration of this aspect

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