Methods of organizing question-answering systems
News of the Kabardin-Balkar scientific center of RAS, Tome 26 (2024) no. 6, pp. 175-187.

Voir la notice de l'article provenant de la source Math-Net.Ru

Today the issue of human-machine interaction via natural language text, including the use of question answering systems, is relevant. The purpose of the work is to analyze the methods of developing question answering systems. It was achieved by considering the types of questions and types of question answering systems, describing the methods of building question answering systems. Embedding question answering systems into digital platforms will allow improving customer interaction without significantly expanding staff, contributing to more effective solutions to their problems, and improving service. This will simultaneously contribute to the growth of income of supplier organizations and improve the life quality of goods and services consumers.
Keywords: robotics, positioning, computer vision, hydroacoustic, group control of robots
Mots-clés : navigation, SLAM
@article{IZKAB_2024_26_6_a14,
     author = {G. V. Dorokhina and A. G. Polous},
     title = {Methods of organizing question-answering systems},
     journal = {News of the Kabardin-Balkar scientific center of RAS},
     pages = {175--187},
     publisher = {mathdoc},
     volume = {26},
     number = {6},
     year = {2024},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/IZKAB_2024_26_6_a14/}
}
TY  - JOUR
AU  - G. V. Dorokhina
AU  - A. G. Polous
TI  - Methods of organizing question-answering systems
JO  - News of the Kabardin-Balkar scientific center of RAS
PY  - 2024
SP  - 175
EP  - 187
VL  - 26
IS  - 6
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/IZKAB_2024_26_6_a14/
LA  - ru
ID  - IZKAB_2024_26_6_a14
ER  - 
%0 Journal Article
%A G. V. Dorokhina
%A A. G. Polous
%T Methods of organizing question-answering systems
%J News of the Kabardin-Balkar scientific center of RAS
%D 2024
%P 175-187
%V 26
%N 6
%I mathdoc
%U http://geodesic.mathdoc.fr/item/IZKAB_2024_26_6_a14/
%G ru
%F IZKAB_2024_26_6_a14
G. V. Dorokhina; A. G. Polous. Methods of organizing question-answering systems. News of the Kabardin-Balkar scientific center of RAS, Tome 26 (2024) no. 6, pp. 175-187. http://geodesic.mathdoc.fr/item/IZKAB_2024_26_6_a14/

[1] V. A. Lapshin, “Question-answering systems: development and prospects”, Automatic Documentation and Mathematical Linguistics, 2012, no. 6, 1–9 (In Russian)

[2] V. V. Ponomarev, V. E. Tumanov, “Model of a digital interactive document in the systems analysis of subject ontology”, Collection of scientific papers of the XXV International scientific and educational-practical conference, Systems Analysis in design and management: in 3 parts, Part 3 \date October 13-14, 2021 (In Russian) | DOI

[3] D. I. Muromtsev, “Models and methods of individualization of e-learning in the context of the ontological approach”, Ontology of Designing, 10:1 (35) (2020), 34–49 (In Russian) | DOI | MR

[4] I. I. Verevichev, Logic: a short theoretical course: a tutorial for students of humanities faculties, UlGTU, Ulyanovsk, 2009, 101 pp. (In Russian)

[5] V. Is. Lopez, V. Uren, M. Sabou, E. Motta, “Question answering fit for the Semantic Web?”, Article in Semantic Web | DOI | MR

[6] D. A. Tyurina, S. V. Palmov, “Application of neural networks in natural language processing”, Journal of Applied Research, 2023, no. 7, 158–162 (In Russian) | DOI

[7] T. S. Chernomorova, S. P. Vorobyov, “Classification and principles of constructing question answer search systems”, Bulletin of Science and Practice, 6:8 (2020), 145–156 (In Russian) | DOI

[8] N. O. Dorodnykh, A. Yu. Yurin, “An approach to automated filling of knowledge graphs with entities based on table analysis”, Ontology of Designing, 12:3 (45) (2022), 336–352 (In Russian) | DOI

[9] A. V. Vidiya, N. O. Dorodnykh, A. Yu. Yurin, “An approach to creating ontologies based on spreadsheets with an arbitrary structure”, Ontology of Designing, 11:2 (40) (2021), 212–226 (In Russian) | DOI

[10] P. A. Lomov, M. L. Nikonorova, M. G. Shishaev, “Extracting relations from NER-labeled sentences for ontology training”, Proceedings of the Kola Science Center of the Russian Academy of Sciences: Technical sciences, 13:2 (2022), 23–30 (In Russian) | DOI

[11] O. Yu. Tikhobaeva, E. P. Bruches, T. V. Batura, “Extracting semantic relations from the texts of scientific articles”, Bulletin of NSU: Information technologies, 20:3, 65–76 (In Russian) | DOI | MR

[12] A. A. Mezentseva, E. P. Bruches, T. V. Batura, “Methods and approaches to automatic linking of entities in Russian”, Proceedings of The Institute for System Programming of the RAS, 34:4 (2022), 187–200 (In Russian) | DOI

[13] A. A. Golikov, D. A. Akimov, M. S. Romanovsky, S. V. Trashchenkov, “Aspects of creating a corporate question-answering system using generative pre-trained language models”, Litera, 2023, no. 12, 190–205 (In Russian) | DOI

[14] D. V. Derevyanko, D. E. Palchunov, “Formal methods for developing a question-answering system in natural language”, Bulletin of the Novosibirsk State University. Series: Information Technology, 12:3 (2014), 34–47 (In Russian)

[15] M. A. Milkova, I. V. Nevolin, D. P. Pigorev, “Modern methods for extracting key information from regulatory documents”, Economics of Contemporary Russia, 2021, no. 2 (93) (In Russian) | DOI

[16] P. A. Gulyaev, E. A. Elistratova, V. P. Konovalov et al., “Tracking the state of a goal-oriented dialogue based on BERT”, Proceedings of Moscow Institute of Physics and Technology, 13:3 (51) (2021), 48–61 (In Russian) | DOI

[17] M. N. Favorskaya, V. V. Andreev, “Adaptive block tensor decomposition in visual question answering systems”, Software Systems, 34:1 (2021), 164–171 (In Russian) | DOI | DOI

[18] V. Bali, A. Verma, “A study on components, benchmark criteria and techniques used in ontology-based question answering systems”, IJISAE, 10(1s) (2022), 9–17, Chandigarh, India