Making use of similarity in referential semantics

Autor(en): Gust, H.
Umbach, C.
Herausgeber: Papadopoulos, G.A.
Stojanovic, I.
Christiansen, H.
Stichwörter: Artificial intelligence; Cognitive systems, Cognitive science; Conceptual structures; Indistinguishability; Many dimensional; Measure function; Multi dimensional; Natural languages; Referential semantics, Semantics
Erscheinungsdatum: 2015
Herausgeber: Springer Verlag
Enthalten in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band: 9405
Startseite: 425
Seitenende: 439
Similarity is well-known to be a core concept of human cognition, e.g., in categorization and learning. Therefore, expressions of similarity in natural language are of special interest: How to account for their meaning including the results on similarity in Cognitive Science and Artificial Intelligence without abandoning referential semantics? In this paper we will lay out a framework connecting referential semantics to conceptual structures by generalizing the notion of measure functions known in degree semantics from the one-dimensional to the many-dimensional case mapping individuals to points in multi-dimensional attribute spaces. Similarity is then spelled out as indistinguishability with respect to a given set of attributes. © Springer International Publishing Switzerland 2015.
Conference of 9th International and Interdisciplinary Conference on Modeling and Using Context, CONTEXT 2015 ; Conference Date: 2 November 2015 Through 6 November 2015; Conference Code:159379
ISBN: 9783319255903
ISSN: 03029743
DOI: 10.1007/978-3-319-25591-0_31
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