Building recommender systems for scholarly information
Maya Hristakeva, Daniel Kershaw, Marco Rossetti, Petr Knoth, Benjamin Pettit, Saúl Vargas, Kris Jack · 2017
The depth and breadth of research now being published is overwhelming for an individual researcher to keep track of let alone consume. Recommender systems have been developed to make it easier for researchers to discover relevant content. However, these have predominately taken the form of item-to-item recommendations using citation network features or text similarity features.