Recommendation Algorithm for Potential Candidates in Human Resources Based on the Integration of Dynamic Decision Diagram

A recommendation algorithm is put forward for the potential candidate recommendation technology in human resources. The dynamic decision diagram is combined in this method based on collaborative filtering technology and partition clustering technology. Firstly, the computational matrix that integrates the dynamic decision diagram recommendation algorithm is established so that the algorithm can recommend information in reference to the matrix. Secondly, the assignment range of the matrix is improved, so that the recommendation algorithm can integrate the evaluations of all users. Finally, the evaluation value and the update coefficient are added, which makes the dynamic update of the algorithm possible, thus recommending the most satisfactory information to the users. On this basis, an advanced recommendation algorithm based on partition clustering is proposed, which has further improved the precision and real-time performance of the algorithm. In addition, experiments are carried out to verify that the ultimate commendation algorithm based on partition clustering is the optimal recommendation algorithm for potential candidates in human resources, which can provide the most satisfactory information to users.