Fecha de publicación: 08/03/2022 Fuente: Wipo "BigData" The invention discloses an e-commerce content recommendation method adopting AI and big data analysis and a big data system, and the method comprises the steps: extracting push connection data in e-commerce behavior event big data of an e-commerce content service system associated with a hotspot e-commerce module, and a push connection attribute corresponding to the push connection data; and taking the push connection data of which the push connection attributes meet a preset requirement as target push mining data, and performing e-commerce intention decision-making on the target push mining data based on a pre-trained e-commerce intention decision-making model to obtain an e-commerce intention thermodynamic diagram corresponding to the target push mining data, and on the basis of the e-commerce intention thermodynamic diagram corresponding to the target push mining data, e-commerce content recommendation corresponding to the hotspot e-commerce section is carried out on an e-commerce content service system, so that the target push mining data is determined by taking the push connection dimension in the e-commerce content push process as a key dimension to carry out e-commerce intention decision making. Therefore, the accuracy of e-commerce content recommendation can be improved.