E-commerce infringement monitoring system based on big data and machine learning algorithm engine

Based on big data and machine learning algorithm engine, a design scheme of intellectual property dynamic monitoring network system for e-commerce platform was put forward. Focusing on the design of big data remote acquisition system, real-time data monitoring and analyzing platform as well as the core algorithm engine model. The remote acquisition system of network big data includes the remote server platform and big data distributed acquisition program. The system uses Web information crawler to accurately collect all relevant datas of major businesses, network platforms and so on. The data monitoring and analyzing platform converts the relevant algorithms such as deep learning, word embedding and common representation of information into programs to analyze and process the intellectual property information involved by the collected data to digitize goods. Based on the traditional public opinion analysis and natural language processing technology, its core algorithm engine builds commodity features and the user opinion mining model, so as to realize the functions of search, analysis, preservation and prediction of intellectual property data of e-commerce products. The system can effectively reduce the cost of infringement and anti-counterfeiting, thus to establish a reliable channel for brand merchants to protect their rights and intellectual property rights.