Artifi cial Intelligence-driven Personalized Advertising Teaching Strategy

Abstract

This paper discusses the application of artifi cial intelligence in personalized advertising teaching strategy. Traditional advertising teaching often cannot meet the individual needs of students, but through the use of artifi cial intelligence technology, students’ personalized characteristics and learning data can be collected and analyzed, and customized advertising teaching content and recommendations can be provided for each student. This personalized teaching strategy can improve students’ learning interest and participation, and achieve more eff ective education results. This paper mainly studies the framework design of personalized advertising teaching, student characteristics analysis and model building, advertising content generation and recommendation algorithms, and system implementation and evaluation. These studies provide new ideas and methods for personalized advertising teaching and have positive signifi cance for improving the quality of advertising teaching.