Tumblr Blog Recommendation with Boosted Inductive Matrix Completion

  title={Tumblr Blog Recommendation with Boosted Inductive Matrix Completion},
  author={Donghyuk Shin and Suleyman Cetintas and Kuang-chih Lee and Inderjit S. Dhillon},
Popular microblogging sites such as Tumblr have attracted hundreds of millions of users as a content sharing platform, where users can create rich content in the form of posts that are shared with other users who follow them. Due to the sheer amount of posts created on such services, an important task is to make quality recommendations of blogs for users to follow. Apart from traditional recommender system settings where the follower graph is the main data source, additional side-information of… CONTINUE READING


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