Abstract
Paraconsistency and its dual paracompleteness are now counted as key concepts in intelligent decision systems because so much inconsistent and incomplete information can be found around us. In this paper, a framework of conditional models for conditional logic and their measure-based extensions are introduced in order to represent association rules in a logical way. Then paracomplete and paraconsistent aspects of conditionals are examined in the framework. Finally we apply conditionals into the definition of association rules in data mining with confidence and consider their extension to the case of Dempster-Shaer theory of evidence serving double-indexed confidence.
Dedicated to Jair Minoro Abe for his 60th birthday
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Murai, T., Kudo, Y., Akama, S. (2016). Paraconsistency, Chellas’s Conditional Logics, and Association Rules. In: Akama, S. (eds) Towards Paraconsistent Engineering. Intelligent Systems Reference Library, vol 110. Springer, Cham. https://doi.org/10.1007/978-3-319-40418-9_9
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DOI: https://doi.org/10.1007/978-3-319-40418-9_9
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