教学视频精准推荐算法研究
首发时间:2017-09-28
摘要:通过分析现有精准营销推荐算法,结合学员通过网络学习教学视频的特点,研究传统协同过滤算法的优缺点,提出一种基于教学视频的协同过滤算法。首先设计一种基于教学视频网站的聚类协同过滤算法,使用随机函数初始化多个聚类中心,再将样本分配给距离其最近的中心向量,由这些样本构造不相交的聚类,用各个聚类的中心向量作为新的中心。最后循环计算分组和确定中心的步骤,直到算法收敛或者到达确定的迭代步数为止。通过分析实验数据,该算法模型能提高学员搜索相关教学视频的速度、提高了学习效率。
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Research on accurate recommendation algorithm for teaching video
Abstract:By analyzing the existing accurate marketing recommendation algorithm, and combining the characteristics of students\' learning video through online learning, this paper studies the advantages and disadvantages of the traditional collaborative filtering algorithm, and proposes a collaborative filtering algorithm based on teaching video. First the design of a collaborative filtering algorithm based on clustering of teaching video website, the random function is used to initialize multiple cluster centers. The samples are assigned to the nearest cluster center vectors, these samples by constructing disjoint, with each clustering center vector as a new center. Finally, the loop calculates the steps of grouping and determining the center until the algorithm converges or arrives at the determined iteration step. By analyzing the experimental data, the proposed algorithm can improve the speed of the search related teaching video and improve the learning efficiency.
Keywords: Teaching Video Collaborative Filtering Accurate Recommendation
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