基于标签的混合推荐算法:实现与分析

Ruiguo Yu, Hongyue Mao, Zan Wang, Minjie Zhang, Zhenxia Yuan, MuWen He, Peng Chang
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引用次数: 1

摘要

推荐系统作为一种信息过滤方法得到了广泛的应用,其中混合推荐算法是目前最常用的技术。但在在线学习系统领域,推荐系统还不够成熟。本文以天津大学在线评委为研究对象,建立了推荐算法应用模型,提出了一种适用于该系统的基于标签的混合推荐算法。并在天津大学在线评判系统的真实用户数据上进行了实验,对算法进行了评估,取得了良好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lable-based Hybrid Recommendation Algorithm: Implementation and Analysis
Recommendation system, as an information filtering method, has been widely applied and the hybrid recommendation algorithm is by far the most commonly used technique. But in the field of online learning system, recommendation system is not mature enough. In this paper, we analyzed the Tianjin University Online Judge, established a model to apply the recommendation algorithm to it, and then proposed a label-based hybrid recommendation algorithm which is applicable to the system. Also, by conducting experiments on real users’ data of Tianjin University Online Judge System, we evaluated our algorithm and obtained good results.
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