Enhancing employee performance appraisal through optimized association rule algorithms: a data mining approach

The planning and development department of the China Yangtze river three gorges engineering development corporation aims to improve its intelligent performance management system in accordance with the company's vision. This paper presents a study on enhancing intelligent performance management in the Planning and Development Department of the China Yangtze River Three Gorges Engineering Development Corporation. By combining data mining techniques with association rule algorithms, a performance prediction model was established. The goal is to explore a performance management system aligned with the company's vision and the specific characteristics of construction enterprises. Experimental results show the effectiveness of the GABPNN model, achieving a prediction error of 5% or less in seven out of seventeen sample points, with a maximum relative error of 20.86%. The suggested performance management system presents a useful strategy for construction companies to improve their performance evaluation procedures, boosting overall management efficiency and aligning with their distinctive traits.