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Explanations in Recommender Systems using Linked Open Data - A Survey


Mohammed Alshammari


Vol. 22  No. 5  pp. 553-558


Explanations in recommender systems became a hot research topic due to the abundance of data on today’s internet. These explanations are proven to increase the transparency of the system and gain user trust. However, the data sparsity issue makes generating explanations a challenge and requires more meaningful data. Therefore, other information sources, such as linked open data (LOD), can play a key role in solving the problem. In this paper, we will examine the literature to find the impact of LOD on enhancing the process of generating explanations for recommender systems.


Artificial Intelligence, Machine Learning, Recommender Systems, Explanations, Linked Open Data, Semantic Web