Real-time Extraction of B2C E-commerce Logistics Network Information Based on Multi-scale Deep Learning
Traditional information extraction methods are difficult to deal with large-scale logis-tics data,resulting in more information noise.Therefore,the real-time extraction of B2C e-com-merce logistics network information based on multi-scale deep learning is proposed.Mining B2C e-commerce logistics network information and preprocessing the collected original e-commerce logistics network information.Multi-scale deep learning is used to reconstruct the features of pre-processed e-commerce logistics information.Multi-scale deep learning captures the features of different scales and generates new feature vectors to extract the reconstructed e-commerce lo-gistics network information.The experimental results show that the research method has less noise content and better extraction effect when extracting c-commerce logistics network infor-mation.
multi-scale deep learningB2C e-commerce logisticsnetwork informationreal-time extraction
万方数据
维普
