https://libeldoc.bsuir.by/handle/123456789/32556
Название: | Unsupervised ranking of clients: machine learning approach to define a "good customer" |
Авторы: | Parkhimenka, U. Tatur, M. Khandogina, O. |
Ключевые слова: | публикации ученых;loyalty ladder;ranking;ecommerce;automatic marketing decision-making;machine learning;data mining & knowledge discovery;latent variable analysis |
Дата публикации: | 2017 |
Издательство: | Faculty of Management Science and Informatics |
Описание: | Parkhimenka, U. Unsupervised ranking of clients: machine learning approach to define a "good customer" / U. Parkhimenka, M. Tatur, O. Khandogina // Central European Researchers Journal. – 2017. - Volume 3, Issue 2. - Pp. 10 - 15. |
Аннотация: | Ranking of clientsis a natural problem for every business. Though usually it can be solved by common sense and intuition of managers, in the case of a big business entity (e.g. global online stores), the problem becomes more complicated with obvious obstacles in derivation of fast and accurate solution. This article deals with the clients ranking problem using machine learning methodology. |
URI: | https://libeldoc.bsuir.by/handle/123456789/32556 |
Располагается в коллекциях: | Публикации в зарубежных изданиях |
Файл | Описание | Размер | Формат | |
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Parkhimenka_Unsupervised.pdf | 488.88 kB | Adobe PDF | Открыть |
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