TY - GEN

T1 - Semantic methods of intelligent assistant developing

AU - Palchunov, Dmitry

AU - Tregubov, A. S.

N1 - Funding Information: The research was funded by RFBR and Novosibirsk region, project number 20-47-540005. The study was carried out within the framework of the state contract of the Sobolev Institute of Mathematics (project no. 0314-2019-0002). Publisher Copyright: © 2021 IEEE.

PY - 2021

Y1 - 2021

N2 - Human-computer interaction with people whose visual perception is limited is possible only with tactile and voice interfaces, the latter are being used more and more recently. The aim of the work is to create an intelligent assistant for an indoor navigation system designed for blind and visually impaired people. The development of an intelligent assistant is based on a semantic user model and a four-level ontological model of the subject domain. To build a dialogue between an intelligent assistant and a user, we use the theory of speech acts, argumentation theory and case-based reasoning. The developed software system is aimed at identifying the desires and user needs and proposing possible user actions aimed at achieving them. The system allows for the decomposition of user tasks and the formation of a sequence of their execution based on semantic models of the user and the subject domain.

AB - Human-computer interaction with people whose visual perception is limited is possible only with tactile and voice interfaces, the latter are being used more and more recently. The aim of the work is to create an intelligent assistant for an indoor navigation system designed for blind and visually impaired people. The development of an intelligent assistant is based on a semantic user model and a four-level ontological model of the subject domain. To build a dialogue between an intelligent assistant and a user, we use the theory of speech acts, argumentation theory and case-based reasoning. The developed software system is aimed at identifying the desires and user needs and proposing possible user actions aimed at achieving them. The system allows for the decomposition of user tasks and the formation of a sequence of their execution based on semantic models of the user and the subject domain.

KW - argumentation theory

KW - case-based reasoning

KW - Intelligent assistant

KW - intent recognition

KW - machine learning

KW - natural language processing

KW - ontology

UR - http://www.scopus.com/inward/record.url?scp=85126804899&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/18788cf9-ab17-3785-9e77-f81d9e442c90/

U2 - 10.1109/KNOTH54462.2021.9686335

DO - 10.1109/KNOTH54462.2021.9686335

M3 - Conference contribution

AN - SCOPUS:85126804899

SN - 9781665467193

T3 - 2021 International Symposium on Knowledge, Ontology, and Theory, KNOTH 2021

SP - 30

EP - 35

BT - 2021 International Symposium on Knowledge, Ontology, and Theory, KNOTH 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2021 International Symposium on Knowledge, Ontology, and Theory, KNOTH 2021

Y2 - 4 December 2021

ER -