The Semantic Processing of Continuous Quantities for Discrete Terms in Ontologies

We consider continuous quantities that are used to describe the physical world, such as colour, shape, sound, texture and spatial and temporal arrangements. Natural languages are not adept at describing these quantities, nor are they easily incorporated into ontologies in the form of discrete terms. In this article, we analyse the way that natural languages handle continuous quantities, propose a general semantics based on metric spaces, and describe how to treat semantic values computationally, so that we may automate the processing of texts which describe continuous quantities allowing, for example, query evaluation and the integration of multiple texts. This provides a basis for incorporating these quantities into ontologies and combining their semantics with automated reasoning tools. We run a series of experiments to evaluate the semantics, the general framework, and the computational system we have developed.

[1]  Thomas Ertl,et al.  Computer Graphics - Principles and Practice, 3rd Edition , 2014 .

[2]  Martha Palmer,et al.  Verb Semantics and Lexical Selection , 1994, ACL.

[3]  John Lyons,et al.  Linguistic Semantics: An Introduction , 1995 .

[4]  M. Carter Computer graphics: Principles and practice , 1997 .

[5]  A. Tversky Features of Similarity , 1977 .

[6]  Remco C. Veltkamp,et al.  State of the Art in Shape Matching , 2001, Principles of Visual Information Retrieval.

[7]  Jeff Z. Pan,et al.  Integrating and Querying Parallel Leaf Shape Descriptions , 2006, SEMWEB.

[8]  Jeff Z. Pan,et al.  Ontology-Based Representation and Query Colour Descriptions from Botanical Documents , 2005, OTM Conferences.

[9]  Jeff Z. Pan Description Logics: Reasoning Support for the Semantic Web , 2004 .

[10]  Aleksandra Mojsilovic A method for color naming and description of color composition in images , 2002, Proceedings. International Conference on Image Processing.

[11]  G. Lakoff,et al.  Women, Fire, and Dangerous Things: What Categories Reveal about the Mind , 1988 .

[12]  G. Lakoff Women, fire, and dangerous things : what categories reveal about the mind , 1989 .

[13]  Ian Horrocks,et al.  OWL-Eu: Adding Customised Datatypes into OWL , 2005, ESWC.

[14]  Frank van Harmelen,et al.  Information Sharing on the Semantic Web , 2004, Advanced Information and Knowledge Processing.

[15]  Patrick F. Reidy An Introduction to Latent Semantic Analysis , 2009 .

[16]  J. M. Kittross The measurement of meaning , 1959 .

[17]  Simone Santini,et al.  Similarity Measures , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  L. Stein,et al.  OWL Web Ontology Language - Reference , 2004 .

[19]  Peter W. Foltz,et al.  An introduction to latent semantic analysis , 1998 .

[20]  Roy Rada,et al.  Development and application of a metric on semantic nets , 1989, IEEE Trans. Syst. Man Cybern..

[21]  Kaufman,et al.  A New Color-Namiing System for Graphics Languages , 1982, IEEE Computer Graphics and Applications.

[22]  Michael S. Lew,et al.  Principles of Visual Information Retrieval , 2001, Advances in Pattern Recognition.

[23]  Philip Resnik,et al.  Using Information Content to Evaluate Semantic Similarity in a Taxonomy , 1995, IJCAI.

[24]  N. Foo Conceptual Spaces—The Geometry of Thought , 2022 .

[25]  C. Stace,et al.  New Flora Of The British Isles , 1998 .