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Twitter users get the latest tweets of their followees on their timeline. In this work we present a tweet recommendation approach, which takes advantage of the semantic relatedness of concepts that interest users. Our approach could be leveraged to build an efficient, online tweet recommender. We construct a Concept Graph (CG), containing a variety of concepts, use graph theory algorithms not yet...
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