A Thorough Formalization of Conceptual Spaces

Autor(en): Bechberger, L.
Kühnberger, K.-U. 
Herausgeber: Furnkranz, J.
Thimm, M.
Kern-Isberner, G.
Stichwörter: Artificial intelligence; Conceptual spaces; Different domains; Fuzzy sets; High dimensional spaces; Reasoning process; Star-shaped sets; Star-shaped sets, Potassium compounds; Stars, Computationally efficient
Erscheinungsdatum: 2017
Herausgeber: Springer Verlag
Enthalten in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band: 10505 LNAI
Startseite: 58
Seitenende: 71
The highly influential framework of conceptual spaces provides a geometric way of representing knowledge. Instances are represented by points in a high-dimensional space and concepts are represented by convex regions in this space. After pointing out a problem with the convexity requirement, we propose a formalization of conceptual spaces based on fuzzy star-shaped sets. Our formalization uses a parametric definition of concepts and extends the original framework by adding means to represent correlations between different domains in a geometric way. Moreover, we define computationally efficient operations on concepts (intersection, union, and projection onto a subspace) and show that these operations can support both learning and reasoning processes. © 2017, Springer International Publishing AG.
Conference of 40th Annual German Conference on Artificial Intelligence, KI 2017 ; Conference Date: 25 September 2017 Through 29 September 2017; Conference Code:199309
ISBN: 9783319671895
ISSN: 03029743
DOI: 10.1007/978-3-319-67190-1_5
Externe URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030864878&doi=10.1007%2f978-3-319-67190-1_5&partnerID=40&md5=e96e6a36a79451efda16f1860d3f2d4e

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