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Targeted Trust-Based Merging of Customers’ Opinions

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F25%3A00640202" target="_blank" >RIV/67985556:_____/25:00640202 - isvavai.cz</a>

  • Alternative codes found

    RIV/60460709:41110/25:101915

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-032-04555-3_29" target="_blank" >http://dx.doi.org/10.1007/978-3-032-04555-3_29</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-032-04555-3_29" target="_blank" >10.1007/978-3-032-04555-3_29</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Targeted Trust-Based Merging of Customers’ Opinions

  • Original language description

    In this article, we investigate how a rational agent forms their opinion based on prior knowledge, available information, and the opinions of other agents. We propose methodology of how to purposefully merge agent’s opinion and expert opinions. We describe the agent’s opinion and the opinions of experts in the form of distributions. Formulating opinion formation as a decision-making task and solve it using Fully Probabilistic Design (FPD). T o demonstrate our approach, we apply the solution on simulated data describing features of mobile phone brands. Methodology is verified on a test bed example of choosing a mobile phone brand based on expert opinions while taking into account agent’s trust in experts.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10102 - Applied mathematics

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2025

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Artificial Neural Networks and Machine Learning – ICANN 2025

  • ISBN

    978-3-032-04554-6

  • ISSN

    0302-9743

  • e-ISSN

    0302-9743

  • Number of pages

    15

  • Pages from-to

    351-365

  • Publisher name

    Springer

  • Place of publication

    Cham

  • Event location

    Kaunas

  • Event date

    Sep 9, 2025

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article