Artificial Intelligence Review

, Volume 11, Issue 6, pp 453–482 | Cite as

Application of Spreading Activation Techniques in Information Retrieval

  • F. Crestani


This paper surveys the use of Spreading Activation techniques onSemantic Networks in Associative Information Retrieval. The majorSpreading Activation models are presented and their applications toIR is surveyed. A number of works in this area are criticallyanalyzed in order to study the relevance of Spreading Activation forassociative IR.

spreading activation information storage and retrieval semantic networks associative information retrieval information processing knowledge representation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Agosti, M. and Crestani, F. (1993). A methodology for the automatic construction of a Hypertext for Information Retrieval. In Proceedings of the ACM Symposium on Applied Computing, pages 745–753, Indianapolis, USA.Google Scholar
  2. Agosti, M., Crestani, F., Gradenigo, G., and Mattiello, P. (1990). An approach to conceptual modelling of IR auxiliary data. In Proceedings of IEEE International Conference on Computer and Communications, Scottsdale, Arizona, USA.Google Scholar
  3. Agosti, M., Melucci, M., and Crestani, F. (1995). Automatic authoring and construction of hypertext for Information Retrieval. ACM Multimedia Systems, 3(1):15–24.Google Scholar
  4. Chung, M. and Moldovan, D. (1994). Applying parallel processing to natural-language processing. IEEE Expert, pages 36–44.Google Scholar
  5. Cohen, P. and Kjeldsen, R. (1987). Information Retrieval by constrained spreading activation on Sematic Networks. Information Processing & Management, 23(4):255–268.Google Scholar
  6. Crestani, F. (1991). A survey on the application of Neural Networks's supervised learning procedures in Information Retrieval. Rapporto Tecnico CNR 5/85, Progetto Finalizzato Sistemi Informatici e Calcolo Parallelo — P5: Linea di Ricerca Coordinata Multidata.Google Scholar
  7. Crestani, F. and van Rijsbergen, C. (1993). Modelling Adaptive Information Retrieval. Departmental Research Report IR-93-2, Department of Computing Science, University of Glassgow, Glasgow, Scotland.Google Scholar
  8. Croft, W. (1987). Approaches to Intelligent Information Retrieval. Information Processing & Management, 23(4):249–254.Google Scholar
  9. Croft, W., Lucia, T., and Cohen, P. (1988). Retrieving documents by plausible inference: a preliminary study. In Proceedings of ACM SIGIR, Grenoble, France.Google Scholar
  10. Croft, W., Lucia, T., Crigean, J., and Willet, P. (1989). Retrieving documents by plausible inference: an experimental study. Information Processing & Management, 25(6):599–614.Google Scholar
  11. Croft, W. and Thompson, R.H. (1987). I 3 R: a new approach to the design of Document Retrieval Systems. Journal of the American Society for Information Science, 38(6):389–404.Google Scholar
  12. Fahlman, S., Touretzky, D., and van Roggen, W. (1981). Cancellation in a parallel semantic network. In Proceedings of the International Joint Conference on Artificial Intelligence, pages 257–263.Google Scholar
  13. Frakes, W. and Baeza-Yates, R., editors (1992). Information Retrieval: data structures and algorithms. Prentice Hall, Englewood Cliffs, New Jersey, USA.Google Scholar
  14. Fujii, H. and Croft, W. (1993). A comparison of indexing techniques for japanese text retrieval. In Proceedings of ACM SIGIR, pages 237–246, Pittsburgh, PA, USA.Google Scholar
  15. Harman, D. (1993). Overview of the first TREC conference. In Proceedings of ACM SIGIR, pages 36–47, Pittsburgh, PA, USA.Google Scholar
  16. Jacobs, P., editor (1992). Text-Based Intelligent Systems. Lawrence Erlbaum Associates, Hillsdale, new Jersey, USA.Google Scholar
  17. Jacobs, P. and Rau, L. (1993). Innovations in text interpretation. Artificial Intelligence, 63:143–191.Google Scholar
  18. Kim, J. and Moldovan, D. (1993). Classification and retrieval of knowledge on a parallel marker-passing architecture. IEEE Transactions on Knowledge and Data Engineering, 5(5):753–761.Google Scholar
  19. Kimoto, H. and Iwadera, T. (1990). Construction of a dynamic thesaurus and its use for Associative Information Retrieval. In Proceedings of ACM SIGIR, Brussels, Belgium.Google Scholar
  20. Kjeldsen, R. and Cohen, P. (1987). The evolution and performance of the GRANT system. IEEE Expert, Summer:73–79.Google Scholar
  21. Pearl, J. (1988). Probabilistic reasoning in intelligent systems: networks of plausible inference. Morgan Kaufmann, San Mateo, California.Google Scholar
  22. Preece, S. (1981). A spreading activation model for Information Retrieval. PhD thesis, University of Illinois, Urbana-Champaign, USA.Google Scholar
  23. Quillian, R. (1968). Semantic memory. In Minsky, M., editor, Semantic Information Processing, pages 216–270. The MIT Press, Cambridge, MA, USA.Google Scholar
  24. Rau, L. (1987). Knowledge organization and access in a conceptual information system. Information Processing & Management, 23(4):269–283.Google Scholar
  25. Robertson, S. and Sparck Jones, K. (1976). Relevance weighting of search terms. Journal of the American Society for Information Science, 27:129–146.Google Scholar
  26. Rumelhart, D., McClelland, J., and PDP Research Group (1986). Parallel Distributed Processing: exploration in the microstructure of cognition. MIT Press, Cambridge.Google Scholar
  27. Rumelhart, D. and Norman, D. (1983). Representation in memory. Technical report, Department of Psychology and Institute of Cognitive Science, UCSD La Jolla, USA.Google Scholar
  28. Salton, G. (1968). Automatic information organization and retrieval. Mc Graw Hill, New York.Google Scholar
  29. Salton, G. (1989). Automatic Text Processing. Addison-Wesley.Google Scholar
  30. Salton, G. and Buckley, C. (1988). On the use of spreading activation methods in automatic Information Retrieval. In Proceedings of ACM SIGIR, Grenoble, France.Google Scholar
  31. Savoy, J. (1992). Bayesian inference networks and spreading activation in hypertext systems. Information Processing & Management, 28(3):389–406.Google Scholar
  32. Schiel, U. (1989). Abstraction in Semantic Networks: axiom schemata for generalization, aggregation and grouping. SIGART Newsletters, 107:25–26.Google Scholar
  33. Shoval, P. (1981). Expert/consultation system for a retrieval data-base with semantic network of concepts. In Proceedings of ACM SIGIR, pages 145–149.Google Scholar
  34. van Rijsbergen, C. (1979). Information Retrieval. Butterworths, London, second edition.Google Scholar
  35. Voorhees, E. (1994). Query expansion using lexical-semantic relations. In Proceedings of ACM SIGIR, pages 61–69, Dublin, Ireland.Google Scholar

Copyright information

© Kluwer Academic Publishers 1997

Authors and Affiliations

  • F. Crestani
    • 1
  1. 1.Dipartimento di Elettronica e InformaticaUniversitá di PadovaPadovaItaly, email

Personalised recommendations