Name
Title | ||
|---|---|---|
Dynamic customer churn prediction strategy for business intelligence using text analytics with evolutionary optimization algorithms |
Abstract | ||
|---|---|---|
•Propose a new Dynamic Customer Churn Prediction model for Business Intelligence.•Apply Text Analytics with Metaheuristic Optimization algorithm for Churn Prediction.•Design a new Chaotic Pigeon Inspired Optimization based Feature Selection technique.•Employ Parameter Tuned LSTM-SAE model to classify the feature reduced data.•Validate the classification performance on benchmark churn prediction dataset. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.ipm.2021.102706 | Information Processing & Management |
Keywords | DocType | Volume |
Business intelligence,Churn prediction,Deep learning,Telecommunication industry,Text analytics,Predictive models | Journal | 58 |
Issue | ISSN | Citations |
6 | 0306-4573 | 1 |
PageRank | References | Authors |
0.40 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Irina Valeryevna Pustokhina | 1 | 1 | 0.40 |
| Denis Alexandrovich Pustokhin | 2 | 1 | 0.40 |
| Aswathy RH | 3 | 1 | 0.40 |
| T. Jayasankar | 4 | 1 | 0.40 |
| C. Jeyalakshmi | 5 | 1 | 0.40 |
| Vicente García-Díaz | 6 | 1 | 0.40 |
| K. Shankar | 7 | 95 | 13.88 |