Multi-scale map representation of geographic information has been a persistent research challenge, especially in the era of big data and ubiquitous map services. Methods for automatic generalization of multi-scale maps are still missing. We aim to explore a deep learning-based framework to address this issue, which consists of recognition of map data patterns, scale transformation, and automatic map generalization.