Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-27T12:46:57.287Z Has data issue: false hasContentIssue false
  • English
  • Français

A context-sensitive framework for lexical ontologies

Published online by Cambridge University Press:  01 March 2008

TONY VEALE  and
YANFEN HAO
TONY VEALE
Affiliation:
School of Computer Science and Informatics, University College Dublin, Ireland e-mail: [email protected], [email protected]
YANFEN HAO
Affiliation:
School of Computer Science and Informatics, University College Dublin, Ireland e-mail: [email protected], [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Human categorization is neither a binary nor a context-free process. Rather, the criteria that govern the use and recognition of certain concepts may be satisfied to different degrees in different contexts. In light of this reality, the idealized, static structure of a lexical-ontology like WordNet appears both excessively rigid and unduly fragile when faced with real texts that draw upon different contexts to communicate different world-views. In this paper we describe a syntagmatic, corpus-based approach to redefining the concepts of a lexical-ontology like WordNet in a functional, gradable and context-sensitive fashion. We describe how the most diagnostic properties of concepts, on which these functional definitions are based, can be automatically acquired from the Web, and demonstrate how these properties are more predictive of how concepts are actually used and perceived than properties derived from other sources (such as WordNet itself).

Type
Articles
Information
The Knowledge Engineering Review , Volume 23 , Special Issue 1: Contexts and Ontologies , March 2008 , pp. 101 - 115
Copyright
Copyright © Cambridge University Press 2008

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Almuhareb, A. and Poesio, M. 2005 Concept learning and categorization from the web. In Proceedings of CogSci 2005, the 27th Annual Conference of the Cognitive Science Society. New Jersey: Lawrence Erlbaum.Google Scholar
Barsalou, L. W. 1983 Ad hoc categories. Memory and Cognition 11, 211–227.CrossRefGoogle ScholarPubMed
Bouquet, P., Giunchiglia, F., van Harmelen, F., Serafini, L. and Stuckenschmidt, H. 2003 C-OWL: contextualizing ontologies. In Proceedings of 2nd International Semantic Web Conference, LNCS vol. 2870:164–179.Springer Verlag.Google Scholar
Budanitsky, A. and Hirst, G. 2006 Evaluating WordNet-based measures of lexical semantic relatedness. Computational Linguistics 32(1), 13–47.CrossRefGoogle Scholar
Charniak, E. and Berland, M. 1999 Finding parts in very large corpora. In Proceedings of the 37th Annual Meeting of the Assoc. for Computational Linguistics. pp. 57–64.Google Scholar
Cimiano, P., Hotho, A. and Staab, S. 2005 Learning concept hierarchies from text Corpora using Formal Concept Analysis. Journal of AI Research 24, 305–339.Google Scholar
De Leenheer, P. and de Moor, A. 2005 Context-driven disambiguation in ontology elicitation. In Shvaiko, P. and Euzenat, J. (eds.), Context and Ontologies: Theory, Practice and Applications, AAAI Technical Report WS-05-01. AAAI Press, pp. 17–24.Google Scholar
Dong, Z. and Dong, Q. 2006 HowNet and the Computation of Meaning. Singapore: World Scientific.CrossRefGoogle Scholar
Fellbaum, C (ed.). 1998 WordNet: An Electronic Lexical Database. Cambridge, MA: The MIT Press.CrossRefGoogle Scholar
Gangemi, A., Guarino, N. and Oltramari, A. 2001 Conceptual analysis of lexical taxonomies: the case of WordNet's top-level. In Welty, C. and Barry, S. (eds.), Formal Ontology in Information Systems. In Proceedings of FOIS2001. ACM Press, pp. 285–296.Google Scholar
Ganter, B. and Wille, R. 1999 Formal Concept Analysis: Mathematical Foundations. Berlin: Springer Verlag.CrossRefGoogle Scholar
Giunchiglia, F. 1993 Contextual reasoning. Special issue on I Linguaggi e le Macchine XVI, 345–364.Google Scholar
Giunchiglia, F., Marchese, M. and Zaihrayeu, I. 2005 Towards a theory of formal classification. In Shvaiko, P. and Euzenat, J. (eds.), Context and Ontologies: Theory, Practice and Applications, AAAI Technical Report WS-05-01. AAAI Press pp. 25–32.Google Scholar
Guarino, N. (ed.). 1998 Formal ontology and information systems. Proceedings of FOIS1998, June 6–8, Trento, Italy. Amsterdam: IOS Press.Google Scholar
Guha, R. V. 1991 Contexts: a formalization and some applications. Technical Report STAN-CS-91-1399. Stanford, CA: Stanford Computer Science Dept.Google Scholar
Hanks, P. 2004 The syntagmatics of metaphor. International Journal of Lexicography 17(3), pp. 245–274.CrossRefGoogle Scholar
Hanks, P. 2006 Metaphoricity is gradable. In Stefanowitsch, A. and Gries, S. (eds.), Corpora in Cognitive Linguistics. Vol. 1: Metaphor and Metonymy. Berlin and New York: Mouton de Gruyter pp. 17–35.Google Scholar
Hearst, M. 1992 Automatic acquisition of hyponyms from large text corpora. In Proceedings of the 14th International Conference on Computational Linguistics. pp. 539–545.CrossRefGoogle Scholar
Lakoff, G. 1987 Women, Fire, and Dangerous Things: What Categories Reveal About the Mind. Chicago: University of Chicago Press.CrossRefGoogle Scholar
Lee, L. 1999 Measures of distributional similarity. In Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics. pp. 25–32.Google Scholar
Lenat, D. and Guha, R. V. 1990 Building Large Knowledge-Based Systems: Representation and Inference in the CYC project. Reading, MA: Addison-Wesley.Google Scholar
Morris, J. 2006 Readers’ Perceptions of Lexical Cohesion and Lexical Semantic Relations in Text. PhD thesis, University of Toronto.Google Scholar
Obrst, L. and Nichols, D. 2005 Context and ontologies: contextual indexing of ontological expressions. In Proceedings of the AAAI 2005 Workshop on Context and Ontologies, Pittsburgh, PA.Google Scholar
Patel-Schneider, P.F., Hayes, P. and Horrocks, I. 2003 Web Ontology Language (OWL) Abstract Syntax and Semantics. Technical report, W3C, www.w3.org/TR/owl-semantics.Google Scholar
Pustejovsky, J. 1995 Generative Lexicon. Cambridge, MA: The MIT Press.Google Scholar
Segev, A. and Gal, A. 2005 Putting things in context: a topological approach to mapping contexts and ontologies. In Shvaiko, P. and Euzenat, J. (eds.), Context and Ontologies: Theory, Practice and Applications, AAAI Technical Report WS-05-01. AAAI Press pp. 9–16.Google Scholar
Ushold, M. 2000 Creating, integrating and maintaining local and global ontologies. In Proceedings of the 1st Workshop on Ontology Learning (OL-2000), part of ECAI 2000.Google Scholar
Weeds, J. and Weir, D. 2005 Co-occurrence retrieval: a flexible framework for lexical distributional similarity. Computational Linguistics 31(4), 433–475.CrossRefGoogle Scholar
Welty, C. and Jenkins, J. 1999 An ontology for subject. Journal of Data and Knowledge Engineering 31(2), 155–181.CrossRefGoogle Scholar
Whissell, C. 1989 The dictionary of affect in language. In Plutchnik, R. and Kellerman, H. (eds.), Emotion: Theory and Research, New York: Harcourt Brace. pp. 113–131.Google Scholar