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Towards Cooperative Predictive Data Mining in Competitive Environments.

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F09%3A00157250" target="_blank" >RIV/68407700:21230/09:00157250 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Towards Cooperative Predictive Data Mining in Competitive Environments.

  • Original language description

    We study the problem of predictive data mining in a competitive multi-agent setting, in which each agent is assumed to have some partial knowledge required for correctly classifying a set of unlabelled examples. The agents are self-interested and therefore need to reason about the trade-offs between increasing their classification accuracy by collaborating with other agents and disclosing their private classification knowledge to other agents through such collaboration. We analyze the problem and propose a set of components which can enable cooperation in this otherwise competitive task. These components include measures for quantifying private knowledge disclosure, data-mining models suitable for multi-agent predictive data mining, and a set of strategies by which agents can improve their classification accuracy through collaboration. The overall framework and its individual components are validated on a synthetic experimental domain.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JC - Computer hardware and software

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2009

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Agents and Data Mining Interaction

  • ISBN

    978-3-642-03602-6

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    14

  • Pages from-to

    95-108

  • Publisher name

    Springer

  • Place of publication

    Heidelberg

  • Event location

    Budapest

  • Event date

    May 10, 2009

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000269949700008