Meronomy

Abstract: Within cognitive linguistics, the notion of domain is central. In the literature, the notion of domain has been interpreted in an all-encompassing way, which has led to conceptual confusion. The article proposes to distinguish between a more psychologically oriented description of domains based on dimensional structures, on the one hand; and meronomic relations, on the other. It is shown how Langacker's notion of a configurational domain can be analyzed as higher-level dimensional structures. An added benefit of the distinction between dimensional domains and meronomic relations is that it generates a natural account of the difference between metaphors and metonymies.

Abstract: This article assesses the role of the model of the integrated whole in the linguistics of collective nouns and, more particularly, collective discrete nouns The cognitive dimension of the integrated whole whose prototype is given by the discrete noun body is twofold and concerns both metalinguistic and linguistic referential constructions A number of features are isolated in the prototypical integrated whole, such as meronomical features, tri-dimensional object-reference, token-reference as well as position in the hierarchy of integrated wholes Collective discrete nouns are analysed along the same lines as less prototypical integrated wholes Isomorphism between a discrete whole and similarly discrete homeomerous parts accounts for the fascination collective discrete nouns hold for scholars, be it in English or French linguistics The features pertaining to prototypical or collective integrated wholes help explain how collective mass-nouns are very frequently excluded from the class of collective nouns and how a number of collective discrete nouns are hardly ever mentioned in linguistic or grammatical works Lastly, the noun body is analysed as a semantically derived collective noun: the prototypical integrated whole is used as a collective, less prototypical, integrated whole to unite and interlock the most independent discrete entities, human animates

Abstract: Semantic relatedness measures provide a means to determine how closely related two concepts may or may not be. In the area of ontology alignment, many lexical-based relatedness measures have been successfully applied within the realm of domain ontologies. The alignment initiative, however, has not included all measures of relatedness. More generic measures of relatedness, such as meronomy-based, have yet to be established beyond lexical ontologies. This paper introduces an algorithm for measuring meronomic relatedness between concepts within a domain ontology. Specifically, a new method is proposed for measuring how much one concept is “part of” another in a domain ontology. This is accomplished by utilizing inherent attributes of these ontologies in concert with protocols currently applied in established relatedness measures. Key features of this method include a unique approach to the weighted edge measure, one in which each edge is weighted based on applying a concept probability algorithm to a multiset composed of ontology property ranges. The application of this method is then illustrated with the aid of two case-studies, namely a camera ontology and a wine ontology, and the results are discussed.

Abstract: In the literature there are no standard meanings for words like aspect, attribute, characteristic, feature, property, and quality. Because the denoted concepts have not been well understood or differentiated, the terminology is highly unsettled, resulting in significant mis communication, imprecision, and confusion in scientific discourse. Ascriptive ontology is the name given here to the science of basic types of aspects, those ubiquitous facts by which we know, describe, and represent things of interest. Aspects underlie virtually every scientific construct, from theories, models, meronomies, taxonomies, concepts, and laws to simple empirical facts. Specifically in terminology, aspects underlie all types of definitions, concepts and concept systems. A new comprehensive taxonomy of aspects is proposed, and concise, uniform names are suggested for the respective concepts. Based on this taxonomy, a new semantic network notation called ETA is briefly introduced.