dc.contributor
Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics
dc.contributor
Universitat Politècnica de Catalunya. SOCO - Soft Computing
dc.contributor.author
García, David L.
dc.contributor.author
Vellido Alcacena, Alfredo
dc.contributor.author
Nebot Castells, M. Àngela
dc.identifier
García, D., Vellido, A., Nebot, M. "Predictive models in churn data mining: a review". 2007.
dc.identifier
https://hdl.handle.net/2117/86182
dc.description.abstract
The development of predictive models of customer abandonment plays a central role in any churn management strategy. These models can be developed using either qualitative approaches or can take a data-centred point of view. In the latter case, the use of Data Mining procedures and techniques can provide useful and actionable insights into the processes leading to abandonment. In this report, we provide a brief and structured review of some of the Data Mining approaches that have been put forward in recent academic literature for customer abandonment prediction.
dc.description.abstract
Postprint (published version)
dc.format
application/pdf
dc.subject
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
dc.subject
Predictive models
dc.title
Predictive models in churn data mining: a review
dc.type
External research report
