Name
Title | ||
|---|---|---|
Feature evaluation for mobile phone changing based on large-scale user behavioral data |
Abstract | ||
|---|---|---|
When and why people change their cell phones are important issues in mobile communications industry because it will impact greatly on the marketing strategy and revenue estimation for both telecommunication operators and manufactures. In this paper, we evaluate the key features that affect the mobile phone changing based on statistical data of mobile users provided by one mobile communication operator. First, we investigate the impact of static features like user age, phone brands, and then the dynamic traffic features. We also discuss the effect that long term influence related factors by statistical analysis. According to statistical analysis, we recognize 8 important features for mobile phone changing events. Our work present an first step knowledge about the feature importance for the issue concerned, which are significant for further phone changing prediction tasks using various prediction models. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/WCSP.2016.7752503 | 2016 8th International Conference on Wireless Communications & Signal Processing (WCSP) |
Keywords | Field | DocType |
Mobile Big Data,Phone Changing Prediction,Phone Brand Segregation,Feature Evaluation | Mobile identification number,Mobile computing,Mobile technology,Mobile search,Computer science,GSM services,Mobile Web,Mobile phone,Multimedia,Mobile telephony | Conference |
ISSN | ISBN | Citations |
2325-3746 | 978-1-5090-2861-0 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qingli Ma | 1 | 0 | 1.69 |
| Jiewen Zheng | 2 | 0 | 0.34 |
| Sihai Zhang | 3 | 63 | 19.50 |
| Wuyang Zhou | 4 | 226 | 47.51 |