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Trudy SPIIRAN, 2020, Issue 19, volume 5, Pages 915–941
DOI: https://doi.org/10.15622/ia.2020.19.5.1
(Mi trspy1121)
 

This article is cited in 2 scientific papers (total in 2 papers)

Artificial Intelligence, Knowledge and Data Engineering

Context-aware approach to intelligent decision support based on user digital traces

A. Smirnov, T. Levashova

St. Petersburg Federal Research Center of the Russian Academy of Sciences
Abstract: A context-aware approach to intelligent decision support based on user digital traces is proposed. The concept of human digital life with regard to intelligent decision support is discussed. The aims of addressing this concept in diverse domains are clarified and approaches to modelling human digital life are identified. In the proposed approach, digital traces serve as a source of information to reveal user preferences and decision-making behaviour. Perspectives on decision support based on user digital traces are developed. The research outcomes are the specification of requirements to intelligent decision support based on user digital traces, the principles, conceptual framework and information model of such support. The principles form the basis for the conceptual framework of intelligent decision support based on user digital traces. Components of the conceptual model are user profiles; a user digital life model that structures information containing in the digital traces; group patterns that describe preferences and decision-making behavior shared by a user group; and a decision maker ontology. The information model defines information flows between the framework’s components, identifies tasks that require solutions to implement the framework and offers techniques for this. The novelties of the research are applying the concept of human digital life to intelligent decision support and context-dependent ontological inference of the type of user as a decision-maker, which determines a group of users sharing their preferences and behaviours with the active user, to predict a recommended decision. The paper contributes to the areas of modelling human digital life and intelligent decision support.
Keywords: intelligent decision support, recommending systems, model of user digital life, user classification.
Funding agency Grant number
Russian Foundation for Basic Research 20-07-00490
20-07-00455
Ministry of Science and Higher Education of the Russian Federation 0073-2019-0005
The research overview is due to project number 20-07-00490 from RFBR (sec. 2), the requirements to and principles of intelligent decision support based on user digital life (sec. 3 and 4) are due to project number 20 07 00455 from RFBR, the conceptual framework (sec. 5) in parts of user digital life modelling and group patterns revealing is due to project number 20-07-00455 from RFBR, in part of ontology-based user classification is due to project number 20 07 00490 from RFBR, and in part of context-dependent user categorization is due to State Research, project number 0073-2019-0005. The information model of intelligent decision support based on user digital life (sec. 6) in part of the group patterns implementation is due to project number 20-07-00455 from RFBR and in part of the implementation of the decision maker ontology is due to project number 20-07-00490 from RFBR.
Received: 03.08.2020
Document Type: Article
UDC: 004.891;004.048;004.822
Language: Russian
Citation: A. Smirnov, T. Levashova, “Context-aware approach to intelligent decision support based on user digital traces”, Tr. SPIIRAN, 19:5 (2020), 915–941
Citation in format AMSBIB
\Bibitem{SmiLev20}
\by A.~Smirnov, T.~Levashova
\paper Context-aware approach to intelligent decision support based on user digital traces
\jour Tr. SPIIRAN
\yr 2020
\vol 19
\issue 5
\pages 915--941
\mathnet{http://mi.mathnet.ru/trspy1121}
\crossref{https://doi.org/10.15622/ia.2020.19.5.1}
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  • https://www.mathnet.ru/eng/trspy/v19/i5/p915
  • This publication is cited in the following 2 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Informatics and Automation
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