Результаты исследований: Материалы конференций › материалы › Рецензирование
Application of a Posteriori Estimates for Multifactor Ranking of Transport Companies. / Есин, Максим Сергеевич; Корепанова, Анастасия Андреевна; Сабреков, Артём Азатович.
2024. 49-52 Работа представлена на 2024 XXVII International Conference on Soft Computing and Measurements (SCM), Санкт-Петербург, Российская Федерация.Результаты исследований: Материалы конференций › материалы › Рецензирование
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TY - CONF
T1 - Application of a Posteriori Estimates for Multifactor Ranking of Transport Companies
AU - Есин, Максим Сергеевич
AU - Корепанова, Анастасия Андреевна
AU - Сабреков, Артём Азатович
PY - 2024/5/22
Y1 - 2024/5/22
N2 - The paper discusses the concept of an automated service that aggregates offers on the cost and delivery time of goods from different transport companies. An important part of the service work is the ranking of search results in order to give out offers from the most reliable companies in the first place. At the same time, the ranking of results cannot be based solely on user ratings due to the limited sample of customers and the possible subjectivity of the reviews taken into account. The study presents an algorithm for ranking transport companies based on the analysis of statistical metrics of the company and user reviews. The algorithm allows you to obtain a consistent rating of companies using a posteriori estimate of the probability of truth of hypotheses about positions in the rating.
AB - The paper discusses the concept of an automated service that aggregates offers on the cost and delivery time of goods from different transport companies. An important part of the service work is the ranking of search results in order to give out offers from the most reliable companies in the first place. At the same time, the ranking of results cannot be based solely on user ratings due to the limited sample of customers and the possible subjectivity of the reviews taken into account. The study presents an algorithm for ranking transport companies based on the analysis of statistical metrics of the company and user reviews. The algorithm allows you to obtain a consistent rating of companies using a posteriori estimate of the probability of truth of hypotheses about positions in the rating.
KW - Bayes formula
KW - a posteriori estimates
KW - adaptive multifactorial assessment
KW - development of web services
KW - expert assessments in ranking
KW - service for estimating the cost of delivery
KW - task of ranking
UR - https://www.mendeley.com/catalogue/e7aaba05-3bfa-3351-b313-7463daea4529/
U2 - 10.1109/scm62608.2024.10554246
DO - 10.1109/scm62608.2024.10554246
M3 - Paper
SP - 49
EP - 52
Y2 - 22 May 2024 through 24 May 2024
ER -
ID: 124122034