The Design And Implementation Of An Express Delivery Guidance Management System Based On Big Data

It is difficult for the courier dispatcher to know how to deliver the parcel according to the consumer behavior habits and the current special scene requirements.A courier delivery guidance management system based on big data analysis is proposed.It can predict and deliver the express parcel delivery method from the mass consumer characteristics,preferences,behavior data and the order data of the e-commerce platform,so as to guide the courier dispatcher to deliver according to the wishes of the consumers,and solve the problem of the receiving experience at the end of the express delivery domain.The goal is to improve the delivery efficiency of the dispatcher and to allow each express parcel to be delivered according to the consumer's true intentions.The system adopts the idea of SOA(Service Oriented Architecture).Its main structure includes data channel layer,basic service layer,and data memory layer.Consumer feature data collection function,receiving tendency analysis function,and order data analysis function,consumer receipt data mining function,express package delivery mode prediction function and delivery performance monitoring function are the main functions.The consumer feature data collection function is responsible for extracting user characteristics,behaviors,preference data,and distribution calculation and data storage from the e-commerce platform and logistics details.The receiving tendency analysis function is responsible for obtaining the tendency of the goods to be self-expressed by consumers in remarks or complaints.The order data parsing function is responsible for cleaning and normalizing the data extracted from the logistics order and the electronic receipt.The consumer receipt data mining function is responsible for combining consumer expressed,predicted data and receipt trend analysis data and extracting consumer characteristics to find similar features.The user mines the person and address based consumer receipt preferences.The forecast courier package delivery method accurately predicts the delivery method of the package based on the behavioral characteristics of the consumer and the details of the order.The delivery performance monitoring function is responsible for determining whether the delivery agent is dispatched according to the wishes of the consumer.The express delivery guidance management system database was designed.The system reduces the complaint rate by guiding the courier dispatcher service to identify the special harvesting needs such as pregnant women and the elderly through consumer characteristics and behavioral data.The GBDT and LR integration scheme finds similar characteristics of consumer output based on person and address receipt preferences to cover more risk groups.The dispatching guide predictive calculation engine calculates the delivery method of the express parcel through the online data to improve the delivery efficiency of the express delivery staff and the harvesting experience of the consumer.