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Agent-Based Customer Profile Learning in 3G Recommender Systems: Ontology-Driven Multi-source Cross-Domain Case

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Agents and Data Mining Interaction (ADMI 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9145))

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Abstract

Advanced recommender systems of the third generation (3G) emphasize employment of semantically clear models of customer cross-domain profile learned using all available data sources. The paper focuses on conceptual level of ontology-based formal model of the customer profile built in actionable form. Learning of cross-domain customer profile as well as its use in recommendation scenario requires solving a number of novel problems, e.g. information fusion and data source privacy preservation, among others. The paper proposes an ontology-driven personalized customer profile model and outlines an agent-based architecture supporting implementation of interaction-intensive agent collaboration in two variants of target decision making procedure that are content-based and collaborative filtering both exploiting semantic similarity measures.

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Acknowledgments

This work is supported by the Program “Intelligent Information Technologies, System Analysis and Automation” conducted by Department for Nano- and Information Technologies of the Russian Academy of Sciences, Project \(\#1.12\).

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Authors and Affiliations

  1. St. Petersburg Institute for Informatics and Automation, Russian Academy of Science, 39, 14-th Liniya, 199178, St. Petersburg, Russia

    Vladimir Gorodetsky, Vladimir Samoylov & Olga Tushkanova

Authors
  1. Vladimir Gorodetsky
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  2. Vladimir Samoylov
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  3. Olga Tushkanova
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Corresponding author

Correspondence to Vladimir Gorodetsky .

Editor information

Editors and Affiliations

  1. University of Technology Sydney, Sydney, New South Wales, Australia

    Longbing Cao

  2. Teesside University, Middlesborough, United Kingdom

    Yifeng Zeng

  3. Nanyang Technological University, Singapore, Singapore

    Bo An

  4. Aristotle University of Thessaloniki, Thessaloniki, Greece

    Andreas L. Symeonidis

  5. Russian Academy of Sciences, St. Petersburg, Russia

    Vladimir Gorodetsky

  6. University of Liverpool, Liverpool, United Kingdom

    Frans Coenen

  7. University of Illinois at Chicago, Chicago, Illinois, USA

    Philip S. Yu

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Gorodetsky, V., Samoylov, V., Tushkanova, O. (2015). Agent-Based Customer Profile Learning in 3G Recommender Systems: Ontology-Driven Multi-source Cross-Domain Case. In: Cao, L., et al. Agents and Data Mining Interaction. ADMI 2014. Lecture Notes in Computer Science(), vol 9145. Springer, Cham. https://doi.org/10.1007/978-3-319-20230-3_2

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  • DOI: https://doi.org/10.1007/978-3-319-20230-3_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20229-7

  • Online ISBN: 978-3-319-20230-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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