Research paper recommender system evaluation using collaborative filtering
Khalid Haruna, Maizatul Akmar Ismail · AIP conference proceedings · 2018
Several approaches have been proposed to help researchers in retrieving relevant and useful information from the cyber-ocean of information. However, the approaches assumed the academic content to be easily accessible, which is not always the case considering the copyright restrictions. Different from the existing works, we proposed a collaborative approach that leverages public contextual metadata to personalize scholarly recommendations. Our proposed approach has the ability to recommend research papers to the individual researchers regardless of the researcher expertise and research field. As demonstrated using a freely accessible dataset, our proposed approach have shown significant improvements over another baseline method.