Semantic integrity constraints specify relations between entity classes. These relations must hold to ensure that the data conforms to the semantics intended by the data model. For spatial data many semantic integrity constraints are based on spatial properties like topological or metric relations. Reasoning on such spatial relations and the corresponding derivation of implicit knowledge allow ...

The identification of semantic relations between terms within texts is a fundamental task in Natural Language Processing which can support applications requiring a lightweight semantic interpretation model. Currently, semantic relation classification concentrates on relations which are evaluated over open-domain data. This work provides a critique on the set of abstract relations used for seman...

Words representing concrete concepts are processed more quickly and efficiently than words representing abstract concepts. Concreteness effects have also been observed in studies using event-related brain potentials (ERPs). The aim of this study was to examine concrete and abstract words using both reaction time (RT) and ERP measurements to determine (1) at what point in the stream of cognitive...

During monitoring of the discourse, the detection of the relevance of incoming lexical information could be critical for its incorporation to update mental representations in memory. Because, in these situations, the relevance for lexical information is defined by abstract rules that are maintained in memory, a central aspect to elucidate is how an abstract level of knowledge maintained in mind...

Abstract. The paper employs and extends methods from Formal Concept Analysis for constructing semantic hierarchies from lexical classifications by binary semantic features. In particular, we show how the dichotomic character of binary features can be captured within an appropriate logical framework that makes recourse to intuitionistic logic. The investigation is motivated by the use of semanti...

In static analysis, approximation is typically encoded by abstract domains, providing systematic guidelines for specifying approximate semantic functions and precision assessments. However, it may well happen that an abstract domain contains redundant information for the specific purpose of approximating a given semantic function modeling some behavior of a system. This paper introduces Example...

Research into the representation and processing of conceptual knowledge has typically associated perceptual facts with sensory brain regions and executive retrieval mechanisms with the left prefrontal cortex. However, this dichotomy between knowledge content and retrieval processes leaves unanswered how the brain supports concepts less reliant on direct sensory experiences. We used neuroimaging...

Different accounts have been proposed to explain the nature of concept representations. Embodied accounts claim a key involvement of sensory-motor systems during semantic processing while more traditional accounts posit that concepts are abstract mental entities independent of perceptual and motor brain systems. While the involvement of sensory-motor areas in concrete language processing is sup...

Completeness is a desirable, although uncommon, property of abstract interpretations, formalizing the intuition that, relatively to the underlying abstract domains, the abstract semantics is as precise as possible. We consider here the most general form of completeness, where concrete semantic functions can have different domains and ranges, a case particularly relevant in functional programmin...

Two experiments are reported that investigated the effect of concreteness on the ability to generate words to fit sentence contexts. When participants attempted to retrieve words from dictionary definitions in experiment 1, abstract words were associated with more omissions and more alternates than were concrete words. These findings are consistent with the view that the semantic-lexical weight...