Application research of support vector machine in E-Learning for personality

In order to accurately build the learner´s learning style in E-Learning, according to the needs and preferences to provide personalized learning materials and harmonious human-computer interaction environment. This paper combines Felder-Silverman learning style with support vector machine technology, and use machine learning technologies for learners to build dynamic learning style. Through the analysis of the Emotion and recognition interaction of the personalized E-Learning based on statistical learning theory and support vector machine technology, it demonstrates the correctness and feasibility using support vector machine to build learning styles. The combination of support vector machine, emotion and recognition interaction in the personalized E-Learning makes great contribution to build human-computer interaction environment.