Application of a Posteriori Estimates for Multifactor Ranking of Transport Companies

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Application of a Posteriori Estimates for Multifactor Ranking of Transport Companies. / Есин, Максим Сергеевич ; Корепанова, Анастасия Андреевна ; Сабреков, Артём Азатович.

2024. 49-52 Paper presented at 2024 XXVII International Conference on Soft Computing and Measurements (SCM), Санкт-Петербург, Russian Federation.

Research output: Contribution to conference › Paper › peer-review

BibTeX

@conference{7b2bbd09579048bdb7355929ed9d8653,

title = "Application of a Posteriori Estimates for Multifactor Ranking of Transport Companies",

abstract = "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.",

keywords = "Bayes formula, a posteriori estimates, adaptive multifactorial assessment, development of web services, expert assessments in ranking, service for estimating the cost of delivery, task of ranking",

author = "Есин, {Максим Сергеевич} and Корепанова, {Анастасия Андреевна} and Сабреков, {Артём Азатович}",

year = "2024",

month = may,

day = "22",

doi = "10.1109/scm62608.2024.10554246",

language = "English",

pages = "49--52",

note = "null ; Conference date: 22-05-2024 Through 24-05-2024",

url = "https://ieeexplore.ieee.org/xpl/conhome/10554068/proceeding",

}

RIS

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