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Multi-Agent Web Recommendations

  • Conference paper
Distributed Computing and Artificial Intelligence, 11th International Conference

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 290))

Abstract

Due to the large amount of pages in Websites it is important to collect knowledge about users’ previous visits in order to provide patterns that allow the customization of the Website. In previous work we proposed a multi-agent approach using agents with two different algorithms (associative rules and collaborative filtering) and showed the results of the offline tests. Both algorithms are incremental and work with binary data. In this paper we present the results of experiments held online. Results show that this multi-agent approach combining different algorithms is capable of improving user’s satisfaction.

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Author information

Authors and Affiliations

  1. Faculty of Engineering, University of Porto, Porto, Portugal

    A. Jorge Morais

  2. Laboratory of Artificial Intelligence and Decision Support (LIAAD – INESC TEC L. A.), Porto, Portugal

    A. Jorge Morais

  3. National Laboratory of Civil Engineering (LNEC), Lisbon, Portugal

    Joaquim Neto

  4. Universidade Aberta (Portuguese Open University), Lisbon, Portugal

    Joaquim Neto & A. Jorge Morais

Authors
  1. Joaquim Neto
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  2. A. Jorge Morais
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Editor information

Editors and Affiliations

  1. Faculty of Engineering, Osaka Institute of Technology, Osaka, Osaka, Japan

    Sigeru Omatu

  2. Université Libre de Bruxelles, Bruxelles, Belgium

    Hugues Bersini

  3. Dept. of Computing Science and Control Faculty of Science, University of Salamanca, Salamanca, Spain

    Juan M. Corchado

  4. Department of Computing Science and Control, Faculty of Science, University of Salamanca, Salamanca, Spain

    Sara Rodríguez

  5. Faculty of Engineering Management, Poznan University of Technology, Poznan, Poland

    Paweł Pawlewski

  6. Dep. PPEQS, Section of Economics and Quantitative Methods, University of Chieti-Pescara, Pescara, Italy

    Edgardo Bucciarelli

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© 2014 Springer International Publishing Switzerland

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Neto, J., Morais, A.J. (2014). Multi-Agent Web Recommendations. In: Omatu, S., Bersini, H., Corchado, J., Rodríguez, S., Pawlewski, P., Bucciarelli, E. (eds) Distributed Computing and Artificial Intelligence, 11th International Conference. Advances in Intelligent Systems and Computing, vol 290. Springer, Cham. https://doi.org/10.1007/978-3-319-07593-8_28

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  • DOI: https://doi.org/10.1007/978-3-319-07593-8_28

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07592-1

  • Online ISBN: 978-3-319-07593-8

  • eBook Packages: EngineeringEngineering (R0)

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