Map slicing service-oriented crawler behavior detection method based on machine learning

The invention provides a crawler behavior detection method for a map slicing service based on machine learning. According to the method, from the mechanism angle of a crawler oriented to map slicing service, content information of user request flow data is deeply mined through a feature engineering method, so that crawler behaviors are fully described; and meanwhile, a machine learning model is established by using a LightGBM framework, efficient fitting analysis is performed on features obtained by traffic data mining, and finally accurate recognition of crawler behaviors oriented to map slicing service is realized. 本发明提出一种基于机器学习的面向地图切片服务的爬虫行为检测方法。所述方法从面向地图切片服务的爬虫的机理角度出发，通过特征工程的方法对用户请求流量数据的内容信息进行深度挖掘，以对爬虫行为进行充分的描述；同时利用LightGBM框架建立机器学习模型，对流量数据挖掘得到的特征进行高效的拟合分析，最终实现对面向地图切片服务的爬虫行为的精准识别。