Fully probabilistic knowledge expression and incorporation

التفاصيل البيبلوغرافية
العنوان: Fully probabilistic knowledge expression and incorporation
المؤلفون: Miroslav Kárný, Tatiana V. Guy, Fabrizio Ruggeri, Antonella Bodini, Petr Nedoma, Jan Kracík
المصدر: Statistics and its interface 7 (2014): 503–515. doi:10.4310/SII.2014.v7.n4.a7
info:cnr-pdr/source/autori:M. Karny, T.V. Guy, J. Kracik, P. Nedoma, A. Bodini, and F. Ruggeri/titolo:Fully probabilistic knowledge expression and incorporation/doi:10.4310%2FSII.2014.v7.n4.a7/rivista:Statistics and its interface/anno:2014/pagina_da:503/pagina_a:515/intervallo_pagine:503–515/volume:7
بيانات النشر: International Press of Boston, 2014.
سنة النشر: 2014
مصطلحات موضوعية: Automatised knowledge elicitation, Statistics and Probability, Controlled autoregressive model, Descriptive knowledge, Bayes estimator, Estimation theory, Computer science, business.industry, Just-in-time modelling, Applied Mathematics, Probabilistic logic, Bayesian estimation, Machine learning, computer.software_genre, Expression (mathematics), Autoregressive model, Facilitator, Data mining, Artificial intelligence, business, computer
الوصف: An exploitation of prior knowledge in parameter estimation becomes vital whenever measured data is not informative enough. Elicitation of quantified prior knowledge is a well-elaborated art in societal and medical applications but not in the engineering ones. Frequently required involvement of a facilitator is mostly unrealistic due to either facilitator’s high costs or complexity of modelled relationships that cannot be grasped by humans. This paper provides a facilitator-free approach based on an advanced knowledgesharing methodology. It presents the approach on commonly available types of knowledge and applies the methodology to a normal controlled autoregressive model.
تدمد: 1938-7997
1938-7989
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b3042335bb2105c3f11bbdbcb35a8969
https://doi.org/10.4310/sii.2014.v7.n4.a7
حقوق: OPEN
رقم الأكسشن: edsair.doi.dedup.....b3042335bb2105c3f11bbdbcb35a8969
قاعدة البيانات: OpenAIRE