论文部分内容阅读
随着信息技术和互联网技术的发展,B2C远程教育网站作为高效、便捷的学习模式开始普及,但同时也带来了信息过载的问题。为此个性化推荐系统应运而生,它通过分析用户行为,预测其偏好并向其推荐他们真正感兴趣的课程。本文对不同的推荐技术进行了比较,并在此基础上分析了对教育类网站的适用性。
With the development of information technology and Internet technology, the B2C distance education website has started to popularize as an efficient and convenient learning mode, but it also brings the problem of information overload. To this end, a system of personalized referrals came into being, predicting its preferences by analyzing user behavior and recommending them to courses of genuine interest. This article compares the different recommended technologies, and on this basis, analyzes the applicability of educational websites.