Emerging mobile short video services pose different yet stringent performance requirements compared to traditional long video services. Content providers (CPs) aspire to a better user-perceived Quality of Experience (QoE) at the application layer, which is imperceptible to the Content Delivery Network (CDN), which monitors Quality of Service (QoS) at the transport layer. The mismatch between QoS and QoE leads to a complex and diverse mapping correlation between the two metrics. In this paper, we illustrate the QoS-QoE mapping correlation in mobile short video services. Although data-driven QoE prediction models can achieve the desired accuracy, complex scenario features are proven to be necessary, and the prediction model still lacks interpretability. Deeper quantitative analysis shows that the correlation becomes complex and diverse when resources are insufficient. The clustering-based prediction framework can successfully summarize scenario features and perform QoE prediction based on QoS metrics alone. Furthermore, we propose predictive QoE-based CDN scheduling. Experiments show that compared to scheduling with QoS metrics, QoE-aware scheduling achieves an average QoE improvement of 9.9% under comparable QoS quality.