Research on Resume Recommendation of Employment Platform based on Decision Tree Algorithm

The current resume recommendation solution of the employment platform has the shortcomings of complex process and large recommendation errors, and so it is difficult to meet the actual application requirements of the enterprise recruitment management. In order to solve these problems and with the goal of improving the recommendation accuracy, this paper proposes a resume recommendation method for employment platform based on the decision tree algorithm. First, the principle of resume recommendation on relevant platforms is analyzed, and a large number of data related to resume recommendation are collected. Then, the cluster analysis algorithm is used to pre-process the resume recommendation data. After that, the decision tree algorithm is used to establish the resume recommendation model, and resume recommendation is carried out according to the model. Finally, a specific example is used to carry out the validation analysis of resume recommendation. The results show that the accuracy of the proposed resume recommendation method is more than 90%, which can achieve very ideal results, and the recommendation effect is significantly better than other current resume recommendation methods.