Skip to main content

Towards an Emergent Taxonomy Approach for Adaptive Profiling

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5006))

Abstract

The omnipresence of data processing and mobile telephony in our life (computers, PDA, GSM, GPS...) along with the evolution of wireless technologies opens the door towards new habits. To avoid being submerged by too much information it is necessary to equip each electronic component present in user’s daily life with capacities to take into account his needs according to his actions, to assist him while learning and anticipating on his behavior in the most autonomous way. Personalization is clearly situated in this objective; it enables a user profile construction which has to dynamically evolve. It also has to take into account new preferences, needs and interests of this user and to forget old ones. This paper proposes a local, cooperative and real-time multi-agent approach to build adaptive and incremental profiles. First, documents are sequentially parsed, which leads to the construction of a Temporary Terminological Network (TTN). This Network is then merged with other document’s extracted networks, in order to create a Permanent Terminological Network (PTN), relevant to the studied collection and used to index this collection thanks to a clustering approach. Preliminary results of the built system are then presented as well as perspectives.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Luck, M., McBurney, P., Shehory, O., Willmott, S.: Agent Technology: Computing as Interaction (A Roadmap for Agent Based Computing). AgentLink (2005)

    Google Scholar 

  2. Wolpert, D.H., Macready, W.G.: No free lunch theorems for optimization. Evolutionary Computation, IEEE Transactions (1), 67–82

    Google Scholar 

  3. Gleizes, M.-P., Camps, V., Glize, P.: A Theory of Emergent Computation Based on Cooperative Self-Oganization for Adaptive Artificial Systems. In: 4th European Congress of Systems Science (1999)

    Google Scholar 

  4. Gleizes, M.-P., Camps, V., Georgé, J.-P., Capera, D.: Engineering Systems which Generate Emergent Functionalities. In: Engineering Environment-Mediated Multiagent Systems - Satellite Conference held at The European Conference on Complex Systems, Dresden, Germany, Katholieke Universiteit Leuven (2007)

    Google Scholar 

  5. Georgé, J.P., Gleizes, M.P., Glize, P., Régis, C.: Real-time Simulation for Flood Forecast: an Adaptive Multi-Agent System STAFF. In: AISB 2003 symposium on Adaptive Agents and Multi-Agent Systems, University of Wales, Aberystwyth, 07/04/03-11/04/03, Society for the Study of Artificial Intelligence and the Simulation of Behaviour, pp. 109–114 (2003)

    Google Scholar 

  6. Capera, D., Gleizes, M.-P., Glize, P.: Self-Organizing Agents for Mechanical Synthesis . In: Di Marzo Serugendo, G., Karageorgos, A., Rana, O.F., Zambonelli, F. (eds.) ESOA 2003. LNCS (LNAI), vol. 2977, pp. 169–185. Springer, Heidelberg (2003)

    Google Scholar 

  7. Picard, G.: Agent Model Instantiation to Collective Robotics in ADELFE . In: Gleizes, M.-P., Omicini, A., Zambonelli, F. (eds.) ESAW 2004. LNCS (LNAI), vol. 3451, pp. 209–221. Springer, Heidelberg (2005)

    Google Scholar 

  8. Bernon, C., Camps, V., Gleizes, M.P., Picard, G.: Engineering Adaptive Multi-Agent Systems: The ADELFE Methodology, pp. 172–202. dea Group Pub (2005)

    Google Scholar 

  9. Camps, V., Glize, P.: Towards a Self-Adaptive Multi-Agent Approach for Enhancing the Quality of Service provided by Open Information Systems. In: 3rd International Conference on WEB Information Systems and Technologies (WEBIST 2007), Web Interfaces and Applications, Barcelona, pp. 295–301. INSTICC Press (2007)

    Google Scholar 

  10. Montaner, M., López, B., De La Rosa, J.L.: A Taxonomy of Recommender Agents on the Internet. Artif. Intell. Rev. 19(4), 285–330 (2003)

    Article  Google Scholar 

  11. Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.): Adaptive Web 2007. LNCS, vol. 4321. Springer, Heidelberg (2007)

    Google Scholar 

  12. Daniels, P.J.: Cognitive models in information retrieval -an evaluative review. J. Doc. 42(4), 272–304 (1986)

    Article  Google Scholar 

  13. Lieberman, H.: Letizia: An Agent That Assists Web Browsing. In: Mellish, C.S. (ed.) Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI 1995), Montreal, Quebec, Canada, pp. 924–929. Morgan Kaufmann, San Francisco (1995)

    Google Scholar 

  14. Sieg, A., Mobasher, B., Burke, R.: Inferring users information context: Integrating user profiles and concept hierarchies. In: 2004 Meeting of the International Federation of Classification Societies, Chicago, IFCS (2004)

    Google Scholar 

  15. Baziz, M., Boughanem, M., Aussenac-Gilles, N.: Semantic Networks for a Conceptual Indexing of Documents in IR. In: ISPS 2005, Seventh International Symposium on Programming and Systems, Algiers, Algeria, pp. 213–224 (2005)

    Google Scholar 

  16. Menczer, F.: ARACHNID: Adaptive Retrieval Agents Choosing Heuristic Neighborhoods for Information Discovery. In: 14th International Conference on Machine Learning (1997)

    Google Scholar 

  17. Moukas, A.: User Modeling in a MultiAgent Evolving System. In: Workshop on Machine Learning for User Modeling, 6th International Conference on User Modeling, Chia Laguna, Sardinia. (1997)

    Google Scholar 

  18. Kilfoil, M., Ghorbani, A.: SWAMI: Searching the Web Using Agents with Mobility and Intelligence. In: Kégl, B., Lapalme, G. (eds.) Canadian conference on AI, Victoria, Canada, pp. 91–102. Springer, Heidelberg (2005)

    Google Scholar 

  19. Bottraud, J.C.: Un assistant adaptatif pour la recherche d’information: AIRA (Adaptative Information Retrieval Assistant). PhD thesis, Université Joseph Fourier (2004)

    Google Scholar 

  20. Videau, S.: Étude de la dynamique des profils adaptatifs dans un système d’informations. Master’s thesis, UPS Toulouse 3 (2007)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Ryszard Kowalczyk Michael Huhns Matthias Klusch Zakaria Maamar Quoc Bao Vo

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Videau, S., Lemouzy, S., Camps, V., Glize, P. (2008). Towards an Emergent Taxonomy Approach for Adaptive Profiling. In: Kowalczyk, R., Huhns, M., Klusch, M., Maamar, Z., Vo, Q.B. (eds) Service-Oriented Computing: Agents, Semantics, and Engineering. SOCASE 2008. Lecture Notes in Computer Science, vol 5006. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79968-9_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-79968-9_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-79967-2

  • Online ISBN: 978-3-540-79968-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics