Similarity Search, Recommendation and Explainability over Graphs in Different Domains: Social Media, News, and Health Industry

Published: 01 Jan 2021, Last Modified: 06 Aug 2024ICWE 2021EveryoneRevisionsBibTeXCC BY-SA 4.0
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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