ItemCollab包括数据处理、物品推荐、质量评价三个模块。数据处理模块实现数据导入、稀疏度分析和训练集划分功能；物品推荐模块实现了目前主流的几种推荐算法；质量评价模块实现对推荐质量的图表展示功能。ItemCollab扩展性好，便于引用，可帮助用户构建自己的个性化推荐系统
ItemCollab是一个用于实现个性化推荐的Python软件包。
它包括数据处理、物品推荐、质量评价三个模块。数据处理模块实现数据导入、稀疏度分析和训练集划分功能；物品推荐模块实现了目前主流的几种推荐算法；质量评价模块实现对推荐质量的图表展示功能。ItemCollab扩展性好，便于引用，可帮助用户构建自己的个性化推荐系统
ml-100k.zip是本软件包内置的数据集，用户可将其下载解压后作为示例程序的数据输入
cosine_similarity.py是一个调整的余弦相似度模型的示例
recommendations.py是本软件包的主体程序，其运行示例如下：
r = recommender(users2) r.computeDeviations() g = users2["Ben"] print(r.slopeOneRecommendations(g))
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