Abstract
In this tutorial, we provide a rich blend of theory and practice regarding graph algorithms, to deal with challenging issues such as scalability, data noise, and sparsity in recommender systems. We also demonstrate real-life systems that use the graph algorithms for Social Media (http://delab.csd.auth.gr/moviexplain/), News (http://metarec.inf.unibz.it) and Health (https://drugrec.inf.unibz.it) industry along with user studies which were used to evaluate the acceptance of the users for these systems.
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Symeonidis, P. (2021). Similarity Search, Recommendation and Explainability over Graphs in Different Domains: Social Media, News, and Health Industry. In: Brambilla, M., Chbeir, R., Frasincar, F., Manolescu, I. (eds) Web Engineering. ICWE 2021. Lecture Notes in Computer Science(), vol 12706. Springer, Cham. https://doi.org/10.1007/978-3-030-74296-6_46
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DOI: https://doi.org/10.1007/978-3-030-74296-6_46
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