Developing Churn Models Using Data Mining Techniques and Social Network Analysis

Erscheinungsjahr 2014
ISBN: 978-1-4666-6288-9
Verlag: Information Science Reference

Buch, Englisch, 361 Seiten, Hardback, Format (B × H): 183 mm x 260 mm, Gewicht: 814 g

Reihe: Research Essentials Collection

Churn prediction, recognition, and mitigation have become essential topics in various industries. As a means for forecasting and manageing risk, further research in this field can greatly assist companies in making informed decisions based on future possible scenarios.

Developing Churn Models Using Data Mining Techniques and Social Network Analysis provides an in-depth analysis of attrition modeling relevant to business planning and management. Through its insightful and detailed explanation of best practices, tools, and theory surrounding churn prediction and the integration of analytics tools, this publication is especially relevant to managers, data specialists, business analysts, academicians, and upper-level students.

Autoren/Hrsg.

Klepac, Goran

Kopal, Robert

Mr¿i¿, Leo

Über Autor(innen)

Goran Klepac, Raiffeisenbank Austria Zagreb, Croatia.

Robert Kopal University College for Law and Finance Effectus Zagreb, Croatia and University College for Applied Computer Engineering Algebra Zagreb, Croatia.

Leo Mršic University College for Law and Finance Effectus Zagreb, Croatia and University College for Applied Computer Engineering Algebra Zagreb, Croatia.