In recent years, the competition in the IPTV industry is becoming more and more fierce. It is important for IPTV service providers to study and improve users' QoE. In this paper, we discuss the relationship between user's QoE and the status of IPTV set-top box. We firstly clean the imbalanced data and then create a mapping between user's complaints and user's QoE. We improve the AdaBoost algorithm with the idea of cost-sensitive. So the improved AdaBoost algorithm can be used in imbalanced dataset we get from Jiangsu Telecom. In addition, we make a comparison between original AdaBoost algorithm and the improved AdaBoost algorithm in predicting user' QoE. The experiments show that the improved AdaBoost algorithm performs better than the original AdaBoost algorithm when predicting user's QoE in imbalanced dataset.
['Qifeng Liu', 'Xin Wei', 'Ruochen Huang', 'Hao Meng', 'Yi Qian']
Improved AdaBoost model for user's QoE in imbalanced dataset