Titlebook: Advances in Databases and Information Systems; 28th European Confer Joe Tekli,Johann Gamper,Yannis Manolopoulos Conference proceedings 2024

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0302-9743 mata,?Discovery and Data Analysis,?Algorithms and Optimization,?Access Methods and Query Processing,?Advanced Architectures,?Machine Learning,?Large Language Models..978-3-031-70628-8978-3-031-70626-4Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Cheyenne L. Laue,Alden H. Wrighton these evidences, we present JSON Model, an alternative to previous proposals which is both lightweight and featureful, discuss key design choices, its efficient implementation, and its integration into OpenAPI.

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Advances in Databases and Information Systems978-3-031-70626-4Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Cheyenne L. Laue,Alden H. Wrightd verify values. Three JSON-based schema description languages have been proposed for JSON so far: JSON Schema, JSound and JSound-C. These languages are verbose and use a lax validation semantics: 60% of public schemas have been found defective because JSON Schema is particularly error-prone. Based

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Cheyenne L. Laue,Alden H. Wright faced yet. In several tasks and applications (e.g., planning, scheduling, workflows, guidelines), the exact time of occurrence of facts is not known (i.e., time is .), and preferences can be assigned to the different temporal possibilities. In a recent paper, we have laid the theoretical basis of t

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Formalising Evolutionary Theory to the role SQL plays in relational data querying. Although this goal is still a work in progress, the graph database community has been advancing by not only defining the GQL specification but also introducing additional specifications such as Property Graph Key, PG-Key, and later Property Graph S

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Formalising Evolutionary Theory the data for a specific need is time-consuming. This paper presents an approach that identifies and extracts the relevant portion of RDF data sources for some application requirements described by a target schema. The identification process is based on a semi-supervised learning algorithm that iter