Abstract
This paper describes a technique for creating generalizable depictions of cognitive spaces from natural language documents, and presents a Web-based system that uses this procedure to visualize structure in geographic discourse. We implement a concept abstraction routine that leverages a lexical ontology to infer the semantics of discussion terms at increasing levels of generalization. A Web discussion medium that uses the Delphi method to guide geographic discourse serves as the framework from which concept structures are elicited. Delphi discussants explore these structures using two Web-enabled visualization schemes: Self-Organizing Maps and concept graphs. These visualization tools rely on a set of concept similarity measures tailored to conceptual information at multiple levels of abstraction. The cognitive spaces produced using this system can reveal key themes in a domain, and can help guide the creation of domain ontologies. We apply these tools to explore concept structures in the field of human-environment interaction.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Guarino, N.: Understanding, building, and using ontologies. International Journal of Human- Computer Studies 46, 293–310 (1997)
Chen, H., et al.: Information visualization for collaborative computing. IEEE Computer, 75–82 (1998)
Turoff, M., Hiltz, S.: Computer based Delphi processes. In: Adler, M., Ziglio, E. (eds.) Gazing into the Oracle: The Delphi Method and its Application to Social Policy and Public Health, Kingsley, London (1996)
Fabrikant, S., Buttenfield, B.: Formalizing semantic spaces for information access. Annals of the Association of American Geographers 91(2), 263–280 (2001)
Miller, N., et al.: Topic Islands - A wavelet-based text visualization system. In: Proceedings of IEEE Visualization 1998, pp. 189–196 (1998)
Havre, S., Hetzler, B., Nowell, L.: ThemeRiver: Visualizing theme changes over time. In: Proceedings of IEEE Symposium on Information Visualization, InfoVis 2000, pp. 115–123 (2000)
Feldman, R., et al.: Trend graphs: Visualizing the evolution of concept relationships in large document collections. In: Żytkow, J.M. (ed.) PKDD 1998. LNCS, vol. 1510, pp. 38–46. Springer, Heidelberg (1998)
Redeker, G.: Coherence and structure in text and discourse. In: Bunt, H.C., Black, W.J. (eds.) Abduction, Belief and Context in Dialogue, pp. 233–264. John Benjamins, Philadelphia (2000)
Smith, B., Mark, D.M.: Geographical categories: an ontological investigation. International Journal of Geographical Information Science 15(7), 591–612 (2001)
Fonseca, F., et al.: Semantic granularity in ontology-driven geographic information systems. Annals of Mathematics and Artificial Intelligence 36(1-2), 121–151 (2002)
Frank, A.U.: Tiers of ontology and consistency constraints in geographical information systems. International Journal of Geographical Information Science, 2001 15(7), 667–678 (2001)
Rodriguez, M.A., Egenhofer, M.J.: Determing semantic similarity among entity classes from different ontologies. IEEE Transactions on Knowledge and Data Engineering 15(2), 442–456 (2003)
Fellbaum, C. (ed.): WordNet: An electronic lexical database, p. 433. MIT Press, Cambridge (1998)
Mani, I.: Automatic summarization. Natural Language Processing, p. 285. John Benjamins, Philadelphia (2001)
Lin, C.-Y.: Topic identification by concept generalization. In: Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics (ACL 1995), pp. 308–310. Association for Computational Linguistics, New Brunswick (1995)
Kohonen, T.: Self-organizing maps, p. 426. Berlin, New York (1997)
Garson, G.: Neural networks: an introductory guide for social scientists, p. 194. Sage, London (1998)
Sammon, J.: A nonlinear mapping for data structure analysis. IEEE Transactions on Computers, C-18(5), 401–08 (1969)
Kaski, S., et al.: WEBSOM - Self-organizing maps of document collections. Neurocomputing 21, 101–117 (1998)
Sowa, J.: Knowledge Representation: Logical, Philosophical, and Computational Foundations, p. 594. Brooks/Cole, Pacific Grove (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pike, W., Gahegan, M. (2003). Constructing Semantically Scalable Cognitive Spaces. In: Kuhn, W., Worboys, M.F., Timpf, S. (eds) Spatial Information Theory. Foundations of Geographic Information Science. COSIT 2003. Lecture Notes in Computer Science, vol 2825. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39923-0_22
Download citation
DOI: https://doi.org/10.1007/978-3-540-39923-0_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20148-9
Online ISBN: 978-3-540-39923-0
eBook Packages: Springer Book Archive