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dc.contributor.authorSalam, Abdus-
dc.contributor.authorSchwitter, Rolf-
dc.contributor.authorOrgun, Mehmet A.-
dc.date.accessioned2023-10-09T06:40:58Z-
dc.date.available2023-10-09T06:40:58Z-
dc.date.issued2019-12-
dc.identifier.urihttp://dspace.aiub.edu:8080/jspui/handle/123456789/1421-
dc.description.abstractWhy-questions try to get to the bottom of the matter and ask for explanations. In this paper, we show how we can learn the complete structure of probabilistic rules for a question-answering system from example interpretations. These rules are then used by a meta-interpreter to find answers in the form of explanations for why-questions for a particular application domain.en_US
dc.language.isoenen_US
dc.subjectwhy-questionsen_US
dc.subjectexplainabilityen_US
dc.subjectprobabilistic logic programmingen_US
dc.subjectprobabilistic rule learningen_US
dc.titleLearning Probabilistic Rules for Answering Why-Questionsen_US
dc.typeArticleen_US
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