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Pricing Information Goods in Distributed Agent-Based Information Filtering

  • Conference paper
On the Move to Meaningful Internet Systems: OTM 2011 (OTM 2011)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7044))

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Abstract

Most approaches to information filtering taken so far have the underlying hypothesis of potentially delivering notifications from every information producer to subscribers; this exact information filtering model creates efficiency and scalability bottlenecks and incurs a cognitive overload to the user. In this work we put forward a distributed agent-based information filtering approach that avoids information overload and scalability bottlenecks by relying on approximate information filtering. In approximate information filtering, the user subscribes to and monitors only carefully selected data sources, to receive interesting events from these sources only. In this way, system scalability is enhanced by trading recall for lower message traffic, information overload is avoided, and information producers are free to specialise, build their subscriber base and charge for the delivered content. We define the specifics of such an agent-based architecture for approximate information filtering, and introduce a novel agent selection mechanism based on the combination of resource selection, predicted publishing behaviour, and information cost to improve publisher selection. To the best of our knowledge, this is the first approach to model the cost of information in a filtering setting, and study its effect on retrieval efficiency and effectiveness.

Part of the work was done while the authors were with Max-Planck Institute for Informatics. The authors would like to thank David Midgley for his comments and suggestions on the economic aspects of this work.

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Author information

Authors and Affiliations

  1. University of Peloponnese, Tripoli, Greece

    Christos Tryfonopoulos

  2. APYDOS, Luxembourg

    Laura Maria Andreescu

Authors
  1. Christos Tryfonopoulos
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  2. Laura Maria Andreescu
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Editor information

Editors and Affiliations

  1. STAR Lab, Vrije Universiteit Brussel (VUB), Bldg G/10, Pleinlaan 2, 1050, Brussel, Belgium

    Robert Meersman

  2. DEBII, Curtin University of Technology, Technology Park, De Laeter Way, 6102, Bentley, WA, Australia

    Tharam Dillon

  3. Facultad de Informática, Universidad Politécnica de Madrid, Campus de Montegancedo S/N, 28660, Boadilla del Monte, Madrid, Spain

    Pilar Herrero

  4. Smeal College of Business, Pennsylvania State University, University Park, PA 16802, U.S.A.

    Akhil Kumar

  5. Institute of Databases and Information Systems, Ulm University, Germany

    Manfred Reichert

  6. City University of Hong Kong, Hong Kong

    Li Qing

  7. National University of Singapore (NUS), Singapore

    Beng-Chin Ooi

  8. Dipartemento Tecnologie dell’Informazione, Universitá degli Studi di Milano, Via Bramante 65, 26013, Crema, Italy

    Ernesto Damiani

  9. VU Station B #1829, Vanderbilt University, 2015 Terrace Place, TN 37203, Nashville, USA

    Douglas C. Schmidt

  10. Virginia Tech, 24060, Blacksburg, VA, USA

    Jules White

  11. Digital Enterprise Research Institute (DERI), National University of Ireland, IDA Business Park, Lower Dangan, Galway, Ireland

    Manfred Hauswirth

  12. Kno.e.sis Center, Wright State University, Dayton, Ohio, USA

    Pascal Hitzler

  13. IBM India Research Lab, 4, Block C, Institutional Area, Vasant Kunj, 110 070, New Delhi, India

    Mukesh Mohania

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Tryfonopoulos, C., Andreescu, L.M. (2011). Pricing Information Goods in Distributed Agent-Based Information Filtering. In: Meersman, R., et al. On the Move to Meaningful Internet Systems: OTM 2011. OTM 2011. Lecture Notes in Computer Science, vol 7044. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25109-2_12

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  • DOI: https://doi.org/10.1007/978-3-642-25109-2_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25108-5

  • Online ISBN: 978-3-642-25109-2

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