相关文章推荐，应该算是一个比较大的功能点了。好像也很多的书专门写这个的实现，搞的很复杂。以前我试用，用tag的方式做推荐。用分词工具提取出文章关键词，或是作者手工设置tag。然后在用脚本匹配各个文章的tag，实现相关文章的推荐。我知道的好像就这些，不知道大家是怎么做的？希望能一起讨论一下相关文章的比较好的实现方案
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相关文章推荐，应该算是一个比较大的功能点了。好像也很多的书专门写这个的实现，搞的很复杂。以前我试用，用tag的方式做推荐。用分词工具提取出文章关键词，或是作者手工设置tag。然后在用脚本匹配各个文章的tag，实现相关文章的推荐。我知道的好像就这些，不知道大家是怎么做的？希望能一起讨论一下相关文章的比较好的实现方案
给你推荐一个：推荐系统实践
Kindle 版的才 10 块钱。
文章正文、Tag。分词。找相同的点然后排序？
找一个好用的推荐系统算法就可以了，比如Slope One算法。
试试这个：https://github.com/piersroberts/SlopeOne
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