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Extracting Interval Temporal Logic Rules: A First Approach Bresolin, Davide Cominato, Enrico Gnani, Simone Muñoz-Velasco, Emilio Sciavicco, Guido Interval temporal logic Horn fragment Rule extraction Discovering association rules is a classical data mining task with a wide range of applications that include the medical, the financial, and the planning domains, among others. Modern rule extraction algorithms focus on static rules, typically expressed in the language of Horn propositional logic, as opposed to temporal ones, which have received less attention in the literature. Since in many application domains temporal information is stored in form of intervals, extracting interval-based temporal rules seems the natural choice. In this paper we extend the well-known algorithm APRIORI for rule extraction to discover interval temporal rules written in the Horn fragment of Halpern and Shoham's interval temporal logic. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Davide Bresolin and Enrico Cominato and Simone Gnani and Emilio Muñoz-Velasco and Guido Sciavicco 2018 Is Part Of LIPIcs, Volume 120, 25th International Symposium on Temporal Representation and Reasoning (TIME 2018) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.TIME.2018.7 urn:nbn:de:0030-drops-97728 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2018.7 eng https://creativecommons.org/licenses/by/3.0/legalcode