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recsys's Introduction

RecSys

项亮的《推荐系统实践》的代码实现以及结果展示分析，所有结果见:

Recommend System

测试用例见:

Tests

第一章

第一章主要介绍一些推荐系统的评价指标

第二章

第二章介绍推荐系统一些基本的模型。这里实验的数据同书上用MovieLen数据集。整个第二章实验包括前半部分的流行度分析以及后半部分基于MovieLen的推荐算法(协同过滤第一次运算会生成协同矩阵，会比较慢):

第三章

第三章主要讲冷启动问题：

  • 用户冷启动
    • 根据用户信息特征分组推荐
    • 外站信息导入
    • 根据用户首次进入反馈的兴趣点
  • 物品冷启动
    • 基于物品内容信息提取
    • 人工标注信息

第四章

介绍基于UGC的推荐。数据集用Delicious数据集(对于冷启动问题推荐热门商品)。

第五章

主要讲时间上下文的推荐算法

recsys's People

Contributors

qcymkxyc avatar

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