A Collaborative Filtering Recommendation Algorithm for Human Resource Management MOC Resources Based on Spark Architecture

The MAE value of the conventional resource collaborative filtering recommendation algorithm is high, so a collaborative filtering recommendation algorithm for Human Resource Management MOC resources based on the Spark architecture is proposed. The algorithm adopts a hierarchical response form, establishes a user-resource rating relationship model, subtracts the average of user ratings from the resource, completes the optimization of the resource collaborative filtering similarity calculation, introduces a highly integrated Spark architecture, predicts the user's rating of the resource and generates a recommendation list to achieve accurate recommendation of Human Resource Management resources MOC. After comparing the results with the two traditional algorithms, it can be aware of the MAE values of the studied algorithm are inferior to those of the two conventional methods for the training in different proportions and testing collection, indicating that the collaborative filtering recommendation algorithm based on the Spark schema for Human Resource Management resources MOC has upper accuracy of recommendation and exceed capability.