中文摘要：

[目的／意义]针对移动在线学习平台中用户评价具有布尔变量属性的学习资源，提出一种适用于该类资源的协同推荐方法。[方法／过程]首先采用基于用户自身属性和已有好友分布特征的FRUTAI算法，确定目标用户的最近邻集；然后在解决数据稀疏的基础上，提出适用于布尔型移动在线学习资源的协同推荐方法；最后选取实证对象，依据相关评估方法评估推荐结果。[结果／结论]在以豆瓣书评网数据作为数据集的实证中取得了较好的推荐效果。实证结果表明，本文提出的改进的协同推荐算法可以有效地应用于移动在线学习平台中的布尔型学习资源，具有较好的推荐效果。

英文摘要：

[ Purpose/significance ] The research aims to propose a collaborative recommendation method for boolean resource in mobile learning platform.[Method/process] Firstly, the nearest neighbor set of the target users is determined based on FRUTAI algorithm. Secondly, after filling the user data, a collaborative recommendation method for Boolean re- source is put forward. Thirdly, the result of the recommendation according to relevant methods is assessed.[Result/con- clusion ] Empirical results suggest that the recommendation method proposed has a good result by using of Douban as the data set. The improved collaborative recommendation algorithm can be effectively applied to boolean resources in mobile learning platform, and has a perfect effect on recommendation.