AI-Based Enterprise Notification Systems and Optimization Strategies for User Interaction

Qianru Xu

doi:10.71222/hr73t268

Authors

Qianru Xu Independent Researcher, Mountain View, CA, 94040, USA Author

DOI:

https://doi.org/10.71222/hr73t268

Keywords:

enterprise level notification system, artificial intelligence, user interaction, data privacy, content optimization

Abstract

In modern enterprises, notification systems play an important role as key tools for information exchange and user interaction. However, the current notification system faces various challenges such as data confidentiality, security protection, message quality, development costs, and technical difficulties. The introduction of artificial intelligence (AI) technology has brought new solutions to these problems. For example, AI can enhance data confidentiality, use deep reinforcement learning to improve content distribution, utilize cloud computing to reduce development costs, and incorporate fairness principles into model training, thereby improving the performance and user satisfaction of notification systems. This study explores the problems existing in current notification systems and proposes targeted improvement solutions based on AI technology, providing theoretical support and practical guidance for enterprises to create efficient, secure, and highly intelligent notification systems.

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