Construction of Common Automation Management System for Intelligent Enterprises

Employee recruitment is one of the important commonalities of all enterprises. Traditional employee recruitment relies on manual communication, which has problems such as complex processes, long processing times, and low matching degree. This article aims to explore the common automation management system of intelligent enterprises, with employee recruitment as the research focus. Firstly, Microsoft Power BI is used to process and analyze employee data to identify the required positions in the company. The Survey Monkey tool is used to obtain the direction of enterprise planning through a questionnaire survey; Next, natural language processing is used to analyze the candidate information of submitted resumes, and collaborative filtering algorithms are used to find candidates who meet the company's job requirements and recommend positions to them; This article uses the Calendar tool to coordinate interview time, and finally uses support vector machines to analyze the interview results to determine whether the candidate meets the requirements. After experimental comparison, the precision rate of the system for job recommendation reached 91%, the F1 value of the system model reached 0.9, and the processing time for one piece of information was only 0.106 seconds. The quality of candidates using this system has significantly improved. This indicates that the system has the advantages of short processing time and high matching degree in employee recruitment, which is also helpful for improving employee quality. It provides ideas for the research of building an intelligent enterprise common automation management system.