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Enhancing Human Resource Management Practices in Marketing Companies Using Dual Graph Attention Networks
Conference proceeding

Enhancing Human Resource Management Practices in Marketing Companies Using Dual Graph Attention Networks

N. Roopalatha, Dhanalakshmi K, G N P V Babu, P. Vamsi Krishna, Anvesh Perada and Harun Kumar Mulagapati
2025 3rd International Conference on Integrated Circuits and Communication Systems (ICICACS), pp 1-6
21 Feb 2025
DOI: https://doi.org/10.1109/ICICACS65178.2025.10968426

Abstract

Accuracy Decision making Generative adversarial networks human resource management (HRM) Integrated circuit modeling Management training marketing strategy multi-granularity gated graph attention network (MGGAN) Predictive models Principal component analysis Recruitment Shape Regulation
Marketing organization features and strategy implementation have been studied for over 30 years. These include organizational structure, culture, leadership, and processes. HR regulations can motivate marketing professionals to support group and individual goals when correctly implemented, but this part of HR has gotten little attention. Model preparation, feature extraction, and training comprise the suggestive technique. It reviewed data quality, evaluated dataset structure, and described data types during pre-processing. Principal component analysis (PCA) ranked and evaluated decision-making units to reduce dimension. Model training used MGGAN. In comparison to GAN and CNN, the proposed model performed well. With an average accuracy rate of 94.36%, it surpassed earlier approaches and captured all dataset peculiarities. MGGAN modeling can increase predictive performance, and marketing organizations should integrate HR regulations, according to this study. This study opens up new organizational analysis and strategy execution methods.

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