The present invention provides an item recommendation method,
system, electronic device and storage medium. Starting from the reference factors when users make decisions on
item selection, a recommendation method is constructed that can dynamically weight and embed rich decision-making information and feature information: it integrates the content features and fine-grained sentiment features of comments, integrates the social relationship network of users and the similarity space of items, introduces social relationship and item similarity space information in addition to the interaction relationship between users and items, integrates the influence of
temporal information on comments, social relationships, and user-item interactions, takes into account the influence of comments, social relationships, and user-item interaction information in different periods on user decisions, is close to the real recommendation
scenario, and provides a dynamic recommendation strategy. A multi-gating mechanism
feature fusion method is proposed to weight and fuse features, considering the contribution of different spatial features to recommendation and fusing them in a weighted form, thus improving the item recommendation effect.