Semantics-aware Content-based Recommender Systems

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Knowledge-aware Autoencoders for Explainable Recommender Systems (2018, background): “Looking at the last mentioned method, it is worth noticing how Knowledge Graphs (KG) are recently being used in lots of applications; they freely offer a large amount of structured data which turned out to be very useful also in recommendation scenarios [4, 5, 12].”
Transparent, Scrutable and Explainable User Models for Personalized Recommendation (2019, background): “These approaches naturally lend themselves to intuitive explanations by listing content features/attributes that made an item appear in the recommendations [13].”
Computing Recommendations via a Knowledge Graph-aware Autoencoder (2018, background): “A detailed review of LOD-based recommender systems is presented in [7].”
Schema-summarization in linked-data-based feature selection for recommender systems (2017, background): “Several other approaches have been proposed afterwards, such as a knowledge-based framework leveraging DBpedia for cross-domain recommendation task [4], a content-based context-aware method able to adopt a semantic representation based on a combination of distributional semantics and entity linking ”