Towards Intelligent Information Retrieval Engines: A Multi-agent Approach

  • Christos Makris
  • Athanassios Tsakalidis
  • Bill Vassiliadis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1884)


The amount of information available in on-line shops and catalogues is rapidly increasing. A single on-line catalogue may contain thousands of products thus posing the increasing need for fast and efficient methods for information filtering and retrieval. Intelligent agent communities may prove to be the needed item in transforming passive search and retrieval engines into active, evolving, personal assistants. In this paper we present a multi-agent architecture for an on-line shop and we propose new methods for performance balancing between filtering, retrieval, ranking, and server catalogue restructuring. This novel approach to multi-agent e-commerce systems provides intelligent, adaptive and personalised navigation within large hypertext environments useful for a wide range of Electronic Commerce applications.


User Agent Principal Eigenvector Partition Block Text Density Query Signature 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    Pyle, R.: Special Issue on Electronic Commerce on the Internet, Comm. of the ACM, vol 39, no6 (1996)Google Scholar
  2. [2]
    Adam, N., Yeshua, Y.: Electronic Commerce: Current Research Issues and Application, Springer Verlag, 155 pp. (1996)Google Scholar
  3. [3]
    Kleinberg, J.: Authoritative sources in a hyperlinked environment, Proc. ACM-SIAM Symposium on discrete Algorithms (1998)Google Scholar
  4. [4]
    Faloutsos, C.: A Survey of Information Retrieval and Filtering Methods, Technical Report CS-TR-3514, University of Maryland (1995)Google Scholar
  5. [5]
    Salton, G.: Automatic Text Processing, Reading, MA: Addison-Wesley (1989)Google Scholar
  6. [6]
    Zobel, J.R., Moffat, A., Ramamohanarao, K.: Inverted Files Versus Signature Files for Text Indexing, ACM Trans. On Database Systems, Vol. 23, No 4, pp. 863–896 (1998)CrossRefGoogle Scholar
  7. [7]
    Moukas, A.: Amalthaea: Information Discovery and Filtering using a Multiagent Evolving Ecosystem, Applied Artificial Intelligence: An International Journal, Vol. 11, No. 5, pp. 437–457 (1997)CrossRefGoogle Scholar
  8. [8]
    Han, S., Boley, D. et al.: WebACE: A Web Agent for Document Categorization and Exploration, Autonomous Agents 98 Conference (1998)Google Scholar
  9. [9]
    Fragoudis, D., Likothanassis, S.D.: Retriever: An Agent for Intelligent Information Discovery, Proceedings of the 20* Int. Conference on Information Systems (1999)Google Scholar
  10. [10]
    Bozanis P., Makris C., Tsakalidis A.: Parametric Weighted Filter: An Efficient Dynamic Manipulation of Signature Files, The Computer Journal, vol. 38, No. 6, pp. 479–488 (1995)Google Scholar
  11. [11]
    Zezula P., Rabitti F., Tiberio P.: Dynamic Partitioning of Signature Files, ACM Trans. on Inf. Systems, vol. 9, no. 4, pp. 336–367 (1991)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Christos Makris
    • 1
  • Athanassios Tsakalidis
    • 1
  • Bill Vassiliadis
    • 1
    • 2
  1. 1.Computer Technology Institute: Research Unit 5PatrasGreece
  2. 2.ZEUS Consulting S.A.PatrasGreece

Personalised recommendations