Optimization Design of Human Resource Management Mode Based on Big Data Algorithm

Abstract

The traditional HRM (human resource management) model has been difficult to meet the actual development needs of knowledge-innovative society and enterprises. This topic launches the optimization design of HRM mode based on BD(big data) algorithm. Under the scenario of BD algorithm, we re-examine HRM system from the perspective of association rule mining, and try to apply association rule mining algorithm in HRM system, so that the data can be transformed into ants with different attributes, and the clustering center finally obtained by its algorithm is equal to the "food source" that ants seek through cooperation. Through such communication means, this model has the characteristics of positive feedback. The results show that the statistical correlation coefficients of the mining results in this system are all above 0. 90, and the average test accuracy rate after "cyclic cross-validation" is between 65% and 79%. By adjusting the threshold similarity in the moving process of ants, it can effectively avoid falling into local optimum, and make the final clustering result roughly accord with the actual situation of enterprise department personnel system.