LINK RECOMMENDER: Collaborative-Filtering for Recommending URLs to Twitter Users

Abstract

Twitter, the popular micro-blogging service, has gained a rapid growth in recent years. Newest information is accessible in this social web service through a large volume of real-time tweets. Tweets are short and they are more informative when they are coupled with URLs. Due to tweet overload in Twitter, we believe that an accurate URL recommender system is… (More)
DOI: 10.1016/j.procs.2013.06.056

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