免费
发表于 2025-3-28 14:40:37
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Chronic
发表于 2025-3-28 21:06:47
Consequence-Based Axiom Pinpointings for the pinpointing problem. Recently, consequence-based decision procedures have been proposed as a promising alternative for tableaux-based reasoners for standard ontology languages. In this work, we present a general framework to extend consequence-based algorithms with axiom pinpointing.
archenemy
发表于 2025-3-29 01:09:26
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揭穿真相
发表于 2025-3-29 04:06:43
Conference proceedings 2018sions. The conference is dedicated to the management of large amounts of complex, uncertain, incomplete, or inconsistent information. New approaches have been developed on imprecise probabilities, fuzzy set theory, rough set theory, ordinal uncertainty representations, or even purely qualitative models..
抱负
发表于 2025-3-29 07:31:53
Modeling the Dynamics of Multiple Disease Occurrence by Latent Statesn states is not known beforehand. We evaluate the proposed approach based on a large dataset from Dutch practices of patients that had events on comorbidities related to atherosclerosis. The discovered clusters are further correlated to medical-oriented outcomes in order to show the usefulness of the proposed method.
从属
发表于 2025-3-29 13:59:11
Discovering Ordinal Attributes Through Gradual Patterns, Morphological Filters and Rank Discriminatihematical morphology tools, more precisely alternated filters, to induce an associated order on the categorical attributes. The third step evaluates the quality of the candidate rankings through an original measure derived from the rank entropy discrimination.
Alopecia-Areata
发表于 2025-3-29 17:19:25
Probabilistic Semantics for Categorical Syllogisms of Figure IIa probabilistic meaning to the other syllogisms of Figure II. Moreover, our semantics also allows for generalizing the traditional syllogisms to new ones involving generalized quantifiers (like .) and syllogisms in terms of defaults and negated defaults.
星球的光亮度
发表于 2025-3-29 19:50:13
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群岛
发表于 2025-3-30 02:35:44
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ventilate
发表于 2025-3-30 04:55:52
https://doi.org/10.1007/978-3-030-00461-3argumentation; artificial intelligence; bayesian; bayesian networks; data integration; formal logic; fuzzy