I often feel that it is difficult to recruit and find employment. Why is this happening?

Since China's rapid economic development, with the development of science and technology and the improvement of life quality, people's general education level has been improved, and the quality of talents has become higher and higher. The recruitment market is no longer inclined to one-way selection (companies choose talents) as before, but to two-way selection.

From the perspective of job seekers and HR, the recruitment market can be regarded as a supply and demand map. In the standard model, the difficulty of job hunting represents redundant labor and the difficulty of recruitment represents scarcity, and the two should only make up for each other. However, the seemingly identical concept only creates a gap in the actual market. This is because the surplus labor force does not match the jobs. Due to the epidemic, many executives left their jobs, and most of the job seekers were graduates. Therefore, this gap is getting wider and wider, which leads to the situation that it is hard to find a job at first sight.

However, this does not mean that there is no way to solve this problem. Because we are committed to the research of artificial intelligence, we put forward a perfect solution to this problem, matching people and positions for HR and filling this gap for job seekers and recruiters. Win-win, the specific matching ideas are as follows:

Person-post matching is defined as the portrait of the enterprise determining the job recruitment demand and target talents. According to the job recruitment model, the potential candidates are intelligently matched to find highly matched talents that meet the job recruitment model. In essence, it is an abstraction and expression of the recruitment needs of enterprises, standardizing the talent screening standards of enterprises and realizing rapid and efficient talent recruitment.

20 18 Up to now, Maisui intelligent job matching system has successfully served 9.7 million job projects, and calculated the matching degree of talent resumes for 654.38+billion times. Here we share how to scientifically determine the matching degree of people and posts and realize the intelligent matching system that understands HR best. The output of matching must be to calculate the scientific and reasonable matching degree of each candidate and position, so it is very important to determine the scoring standard and the factors to be considered. There are many factors that affect the matching degree of people and posts, which can be simply divided into two attributes:

1) The filtering type affects the matching between people and posts: for example, there are some specific hard standards for posts, which can be used as certain filtering valves, that is, they cannot be included in the calculation of the matching degree between people and posts. Usually, some positions have specific age requirements or license requirements.

2) The ranking type affects the matching of people and posts: the specific hard criteria are easy to be applied across the board, so enterprises will try to reduce some filtering rules and strengthen some ranking rules, that is, if a certain standard is reached, other information is the same, and the bonus items with higher ranking will be obtained. A typical scenario is "more than 5 years of experience as a product manager", so don't take 5 years as a filter calculation, because a 4-year product manager may also be qualified for this position, but 5 years of experience is better.

Enterprises need to sort out job requirements, distinguish core matching decision-making factors according to the above two categories, and then build a scientific and reasonable scoring strategy to calculate job matching degree. With the development of the Internet and the advent of the era of big data, resumes are becoming more and more online. Enterprises are increasingly using intelligent technology to analyze job requirements, extract the core decision-making factors that affect talent matching, integrate the previous experience of internal recruitment and resume selection, and realize an intelligent personalized matching system for enterprises. When matching, it will intelligently read job requirements, extract core features, and then comprehensively consider more than 100 features to simulate experienced HR to realize intelligent job matching.