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Titlebook: Conceptual Modeling - ER 2009; 28th International C Alberto H. F. Laender,Silvana Castano,José Palazzo Conference proceedings 2009 Springer

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Modeling Domain Variability in Requirements Engineering with Contextsr, most requirements specifications do not consider contextual properties and few modeling notations explicitly specify how domain variability affects the requirements. In this paper, we propose an approach for using contexts to model domain variability in goal models. We discuss the modeling of con
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Towards an Ontological Modeling with Dependent Types: Application to Part-Whole Relationsproperties, leading to reason outside the logic. Alternatively, classical languages for conceptual modeling such as UML lack of formal foundations resulting in ambiguous interpretations of mereological relations. Moreover, they cannot prove that a given specification is correct from a logical perspe
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Tractable Query Answering over Conceptual Schemata and relationships, and cardinality constraints. This is a common setting in conceptual data modelling, where reasoning over incomplete data with respect to a knowledge base is required. We adopt a semantics for EER schemata based on their relational representation. We identify a wide class of EER s
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Cluster-Based Exploration for Effective Keyword Search over Semantic Datasetsh to access such data. Data is available in forms that may not be of easy access for not expert users. Keyword Search approaches are an effort to abstract from specific data representations, allowing users to retrieve information by providing a few terms of interest. Many solutions build on dedicate
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Geometrically Enhanced Conceptual ModellingGERM), which preserves the key principles of ER modelling and at the same time introduces bulk constructions and types that support geometric objects. The model distinguishes between a syntactic level of types and an explicit internal level, in which types give rise to polyhedra that are defined by
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