Abstract: Highlights•We propose a recommendation system using graph-based features and Autoencoders.•We investigate and analyze each step of the method to find the best setup.•We examine the method with the most popular evaluation metrics and datasets.•Results show an improvement in comparison with basic and state of the art methods.
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