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JOURNALS // Informatics and Automation // Archive

Tr. SPIIRAN, 2020 Issue 19, volume 5, Pages 915–941 (Mi trspy1121)

This article is cited 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.

UDC: 004.891;004.048;004.822

Received: 03.08.2020

DOI: 10.15622/ia.2020.19.5.1



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