Application of the mivar expert system
News of the Kabardin-Balkar scientific center of RAS, no. 2 (2021), pp. 11-29
Voir la notice de l'article provenant de la source Math-Net.Ru
Reading and writing texts remains the basis for people's communication and training. A text is used
for attracting people and describing various services and products. The number of texts is constantly increasing, which creates the problem of automated assessment of the texts complexity, their quality and
the possibility of understanding by the target audience. Determining the complexity of texts is an important procedure that can be automated and used the following well-known methods for evaluating the
texts complexity: automatic readability index ARI, Coleman-Liau index, Flesch readability index, DaleChall formula, SMOG test.
The problem of the texts complexity determining is relevant, important and practically significant. To
assess the simplicity of the text for the reader's understanding, a mivar expert system for evaluating the
complexity of texts has been created. The scientific novelty of the project is as follows: the formalization
of decision-making and information processing tasks for assessing the texts complexity has been carried
out; a new mathematical model of the mivar bipartite network including five procedures for assessing the
texts complexity for the subject area "text complexity assessment" has been developed; a new problemoriented decision-making system for determining the texts complexity was developed.
The created mivar expert system for assessing the texts complexity can be used to work with texts in
various fields of activity: compiling automated textbooks, instructions, technical works descriptions, writing texts for SEO in the development of web sites. The evolution of mivar networks allows us to add new
ways and methods for evaluating the texts complexity to our project.
Keywords:
artificial intelligence, mivar networks, expert systems, recommendation systems,
knowledge graphs, knowledge networks, decision-making systems, big knowledge, robots,
understanding text meaning, texts complexity evaluating.
Mots-clés : mivar, MOGAN
Mots-clés : mivar, MOGAN
@article{IZKAB_2021_2_a1,
author = {L. E. Adamova and O. V. Surikova and I. G. Bulatova and O. O. Varlamov},
title = {Application of the mivar expert system},
journal = {News of the Kabardin-Balkar scientific center of RAS},
pages = {11--29},
publisher = {mathdoc},
number = {2},
year = {2021},
language = {ru},
url = {http://geodesic.mathdoc.fr/item/IZKAB_2021_2_a1/}
}
TY - JOUR AU - L. E. Adamova AU - O. V. Surikova AU - I. G. Bulatova AU - O. O. Varlamov TI - Application of the mivar expert system JO - News of the Kabardin-Balkar scientific center of RAS PY - 2021 SP - 11 EP - 29 IS - 2 PB - mathdoc UR - http://geodesic.mathdoc.fr/item/IZKAB_2021_2_a1/ LA - ru ID - IZKAB_2021_2_a1 ER -
L. E. Adamova; O. V. Surikova; I. G. Bulatova; O. O. Varlamov. Application of the mivar expert system. News of the Kabardin-Balkar scientific center of RAS, no. 2 (2021), pp. 11-29. http://geodesic.mathdoc.fr/item/IZKAB_2021_2_a1/