流媒体点播学习系统自适应性研究

针对为流媒体学习系统提供个性化点播服务的问题,通过研究学习系统自适应性实施的相关文献,给出一个基于朴素贝叶斯分类的自适应流媒体点播系统的实现模型。为了提高分类诊断性能,适合流媒体学习特性,重点讨论为不同知识点类型赋予不同权重的基于概率加权的贝叶斯分类算法和加入时序的贝叶斯分类算法。实验结果表明,算法设计合理、科学。

The adaptability of research in streaming media VOD learning system

Aiming at for streaming media learning system providing personalized VOD service problems, this paper presents an adaptive streaming media on demand system implementation model based on Naive Bayesian Classifier by researching on the related literature of the adaptability implementation in learning system. In order to improve the classification performance, suitable for streaming media studying characteristics, this paper focuses on two methods setting different weights of different knowledge based on probability inference for using with Naive Bayesian Classification and Naive Bayesian Classification by adding timing. Experimental results indicate that the methods are reasonable, scientific.