Titlebook: Rules and Reasoning; 4th International Jo Víctor Gutiérrez-Basulto,Tomá? Kliegr,Dumitru Roma Conference proceedings 2020 Springer Nature Sw

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Symbolic Similarity Relations for Tuning Fully Integrated Fuzzy Logic Programspossible to automatically tune such programs by appropriately substituting (with the concrete values that best satisfy the user’s preferences) the symbolic constants appearing in their program rules and similarity relations.

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Rule-Based Multi-label Classification: Challenges and Opportunities a whole, shared by other approaches. This includes the potential interpretability of rules, their ability to model (local) label dependencies in a flexible way, and the facile customization of a predictor to different loss functions. In this paper, we present a modular framework for rule-based MLC

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Tackling the DMN Challenges with cDMN: A Tight Integration of DMN and?Constraint Reasoningision logic. cDMN aims to enlarge the expressivity of DMN in order to solve more complex problems, while retaining DMN’s goal of being readable by domain experts. We test cDMN by solving the most complex challenges posted on the DM Community website. We compare our own cDMN solutions to the solution

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Query Answering in Fuzzy DL-Lite with Graded Axioms semantics or are limited to precise terminological knowledge, where only facts are graded. We study the problem of answering conjunctive queries over fuzzy DL-Lite. ontologies which allow also graded axioms, and whose semantics is based on mathematical fuzzy logic. We show that for the G?del t-norm

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New Rule Induction Method by Use of a Co-occurrence Set from the Decision Tablese methods by the conventional Rough Sets from a statistical view. The method recognizes condition attributes (CA) and the decision attribute (DA) in DT as random variables having the causality of an input-output relation, and uses the relation of transforming the inputs (outcomes of CA) into the ou