Research on Semantic Analysis-Based Recognition of Telecommunication Fraud Discourse Patterns

Abstract

This study explores the recognition of telecommunication fraud discourse patterns based on semantic analysis. The paper first analyzes the fundamental characteristics and evolving trends of telecommunication fraud discourse. It then elucidates the principles of the recognition method and its application in telecommunication fraud detection and early warning systems. Additionally, the challenges faced by this method are introduced, such as the difficulty of identifying complex and ambiguous fraudulent language, model updates, as well as data privacy and ethical issues. Finally, potential directions for future research are proposed, including the development of new semantic analysis techniques, the design of more effective model training strategies, and in-depth investigations into data privacy and ethical concerns.