Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
Bayesian BeliefNetwork as a Behavior Intensity Rate Model on the Example of Posting in a Social Network. / Toropova, Aleksandra V.; Tulupyeva, Tatiana V.
Proceedings of 2020 23rd International Conference on Soft Computing and Measurements, SCM 2020. ред. / S. Shaposhnikov. Institute of Electrical and Electronics Engineers Inc., 2020. стр. 22-24 9198795.Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
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TY - GEN
T1 - Bayesian BeliefNetwork as a Behavior Intensity Rate Model on the Example of Posting in a Social Network
AU - Toropova, Aleksandra V.
AU - Tulupyeva, Tatiana V.
N1 - A. V. Toropova and T. V. Tulupyeva, "Bayesian BeliefNetwork as a Behavior Intensity Rate Model on the Example of Posting in a Social Network," 2020 XXIII International Conference on Soft Computing and Measurements (SCM), 2020, pp. 22-24, doi: 10.1109/SCM50615.2020.9198795.
PY - 2020/5
Y1 - 2020/5
N2 - Intensity is a very important characteristic of human behavior. Knowing behavior intensity you can make predictions about behavior, which can be used in a number of areas: sociology, economics etc. We present a Bayesian belief network estimating the behavior intensity based on data about last episodes of behavior. We consider the work of this model on the data about posting activity in the social network Vkontakte. The intensity rate predicted by the model and the actual intensity of users posting are compared.
AB - Intensity is a very important characteristic of human behavior. Knowing behavior intensity you can make predictions about behavior, which can be used in a number of areas: sociology, economics etc. We present a Bayesian belief network estimating the behavior intensity based on data about last episodes of behavior. We consider the work of this model on the data about posting activity in the social network Vkontakte. The intensity rate predicted by the model and the actual intensity of users posting are compared.
KW - bayesian belief network
KW - behavior intensity
KW - episodes of behavior
KW - posting
UR - http://www.scopus.com/inward/record.url?scp=85093870379&partnerID=8YFLogxK
U2 - 10.1109/SCM50615.2020.9198795
DO - 10.1109/SCM50615.2020.9198795
M3 - Conference contribution
AN - SCOPUS:85093870379
SP - 22
EP - 24
BT - Proceedings of 2020 23rd International Conference on Soft Computing and Measurements, SCM 2020
A2 - Shaposhnikov, S.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd International Conference on Soft Computing and Measurements, SCM 2020
Y2 - 27 May 2020 through 29 May 2020
ER -
ID: 78033509