A framework for identification of high-value customers by including social network baded variables for churn prediction using neuro-fuzzy techniques
Year of publication: |
2013
|
---|---|
Authors: | Abbasimehr, Hossein ; Setak, Mostafa ; Soroor, Javad |
Published in: |
International journal of production research. - London : Taylor & Francis, ISSN 0020-7543, ZDB-ID 160477-6. - Vol. 51.2013, 4 (15.2.), p. 1279-1294
|
Subject: | churn prediction | data mining | high-value customer | neuro-fuzzy | word-of-mouth | Beziehungsmarketing | Relationship marketing | Data Mining | Data mining | Prognoseverfahren | Forecasting model | Soziales Netzwerk | Social network | Konsumentenverhalten | Consumer behaviour | Virales Marketing | Viral marketing | Social Web | Social web |
-
Büttner, Ricardo, (2017)
-
User response to e-WOM in social networks : how to predict a content influence in Twitter
Dahka, Zohreh Yousefi, (2020)
-
Online newspaper subscriptions : using machine learning to reduce and understand customer churn
Belchior, Lúcia Madeira, (2024)
- More ...
-
Abbasimehr, Hossein, (2013)
-
Improving churn prediction using imperialist competitive algorithm for feature selection in telecom
Abbasimehr, Hossein, (2024)
-
Supply chain single vendor: Single buyer inventory model with price-dependent demand
Ahmadi Rad, Mona, (2014)
- More ...