A Semantic Map as Basis for the Decision Process in the www Navigation

  • Hartwig Hochmair
  • Andrew U. Frank
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2205)


In the physical world, decision making in common navigation strategies is based on a mental map which includes a mental representation of geometric features such as distances and directions between places. We propose that decision making in the web is also based on a mental map. Contrary to the physical world navigation, the mental map used for web navigation describes a part of the agent’s epistemology of the world, hence consists of semantic relations between concepts and includes hardly any geometrical features. We focus on the navigation situation where the detailed web structure is unknown to the agent before the navigation, therefore the agent’s decisions are completely based on his semantic mental map. We give a potential structure of the agent’s mental map, simulated using WordNet, and simulate the agent’s decision making process during the web navigation. The simulation of the strategies allows to assess existing web environments with regard to ease of navigability.


semantic map web navigation strategy decision process epistemology web searching 


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  1. Barsalou, L. W. (1987). The instability of graded structure: implications for the nature of concepts. Neisser: 101–140.Google Scholar
  2. Dieberger, A. (1998). Social Connotations of Spatial Metaphors and Their Influence on (Direct) Social Navigation. Workshop on Personalized and Social Navigation in Information Space. A. M. K. Hook, D. Benyon. Kista, Sweden, Swedish Institute of Computer Science.Google Scholar
  3. Dijkstra, E. W. (1959). “A note on two problems in connection with graphs.” Numerische Mathematik 1: 269–271.zbMATHCrossRefMathSciNetGoogle Scholar
  4. Ellis, D. and M. Haugan (1997). “Modelling the Information Seeking Patterns of Engineers and Research Scientists in an Industrial Environment.” Journal of Documentation 53(4): 384–403.CrossRefGoogle Scholar
  5. Fellbaum, C. and G. A. Miller (1990). “Folk psychology or semantic entailment? A reply to Rips and Conrad.” The Psychological Review 97: 565–570.CrossRefGoogle Scholar
  6. Gibson, J. J. (1977). The Theory of Affordances. J. Bransford. R. E. Shaw. Hillsdale, NJ, Lawrence Erlbaum Associates.Google Scholar
  7. Hochmair, H. (to app.). Adapting One’s Mental Model: An Essential Process for Successful Navigation in an Environment. Spatial Information in the Environment, Innovations in GIS 8, Taylor & Francis.Google Scholar
  8. Jones, K. S. (1986). Synonymy and semantic classification. Edinburgh, Edinburgh University Press.Google Scholar
  9. Jordan, T., M. Raubal, et al. (1998). An Affordance-Based Model of Place in GIS. 8th Int. Symposium on Spatial Data Handling, SDH’98, Vancouver, Canada (July 11–15, 1998), International Geographic Union.Google Scholar
  10. Kirschenhofer, P. (1995). The Mathematical Foundation of Graphs and Topology for GIS. Geographic Information Systems–Materials for a Post Graduate Course. A. U. Frank. Vienna, Department of Geoinformation, TU Vienna. 1: 155–176.Google Scholar
  11. Kuhn, W. (1996). Handling Data Spatially: Spatializing User Interfaces. 7th Int. Symposium on Spatial Data Handling, SDH’96, Delft, The Netherlands, Faculty of Geodetic Engineering, Delft University of Technology.Google Scholar
  12. Kuipers, B. (1978). “Modeling Spatial Knowledge.” Cognitive Science 2.Google Scholar
  13. Lakoff, G. (1987). Women, Fire, and Dangerous Things. Chicago and London, The University of Chicago Press.Google Scholar
  14. Marchionini, G. M. (1995). Information Seeking in Electronic Environments. Cambridge, England, Cambridge University Press.Google Scholar
  15. Miller, G. A. (1995). “WordNet: A Lexical Database for English.” Communications of the ACM 38(11): 39–41.CrossRefGoogle Scholar
  16. Miller, G. A. (1998). Nouns in WordNet. WordNet–an electronic lexical database. C. Fellbaum. Cambridge, Massachusetts, MIT Press.Google Scholar
  17. Norman, D. A. (1999). “Affordances, Conventions, and Design.” interactions.Google Scholar
  18. Peuquet, D. (1998). Cognitive Models of Dynamic Phenomena and their Representations,
  19. Raubal, M. (to app.). “Ontology and Epistemology for Agent-based Wayfinding Simulation.” 15(7) IJGIS.Google Scholar
  20. Raubal, M. and M. Worboys (1999). A Formal Model of the Process of Wayfinding in Built Environments. Conference on Spatial Information Theory–Cognitive and Computational Foundations of Geographic Information Science. C. Freksa and D. Mark. Berlin-Heidelberg, Springer-Verlag. 1661: 381–399.CrossRefGoogle Scholar
  21. Rips, L. J., E. J. Shoben, et al. (1973). “Semantic distance and the verification of semantic relations.” Journal of Verbal Learning and Verbal Behavior (12): 1–20.Google Scholar
  22. Rosch, E. and C. B. Mervis (1975). “Family resemblance: Studies in the internal structure of categories.” Cognitive Psychology(7): 573–605.Google Scholar
  23. Sholl, M. J. (1987). “Cognitive maps as orienting schemata.” Journal of Experimental Psychology: Learning Memory, and Cognition 13(4): 615–628.CrossRefGoogle Scholar
  24. Smith, B. (2001). Objects and Their Environments: From Aristotle to Ecological Ontology. The Life and Motion of Socioeconomic Units. A. U. Frank, J. Raper and J.-P. Cheylan. London, Taylor and Francis.Google Scholar
  25. Smith, E. E., E. J. Shoben, et al. (1974). “Structure and process in semantic memory: A featural model for semantic decisions.” Psychol. Rev.(81): 214–241.Google Scholar
  26. Svensson, M. (1998). Social Navigation. Exploring Navigation; Towards a Framework for Design and Evaluation of Navigation in Electronic Spaces. N. Dahlbaeck. Kista, Sweden, Swedish Institute of Computer Science.Google Scholar
  27. Thompson, S. (1996). Haskell–The Craft of Functional Programming. Harlow, England, Addison-Wesley.Google Scholar
  28. Wilson, T. D. (1997). “Information Behavior: An Interdisciplinary P Processing & Management 33(4): 551–572.Google Scholar
  29. Wittgenstein, L. (1953). Philosophical Investigations. New York, Macmillan.Google Scholar
  30. Wooldridge, M. (1999). Intelligent Agents. Multiagent Systems–A modern Approach to Distributed Artificial Intelligence. G. Weiss. Cambridge, Massachusetts, The MIT Press.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Hartwig Hochmair
    • 1
  • Andrew U. Frank
    • 1
  1. 1.Institute for GeoinformationTechnical University ViennaViennaAustria

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