This application discloses a method, apparatus, device, and medium for item recommendation across multiple user groups, scenarios, and tasks, relating to the field of
artificial intelligence technology. The method involves acquiring user-
side information, item-
side information, and corresponding scene environment information in different scenarios; calculating weight dimensions, shared feature vectors, and environment dimensions to obtain a first dimension, a dense vector, and a second dimension; performing attention mechanism feature cross-calculation to obtain a third dimension; calculating item recommendation scores using the first dimension, dense vector, second dimension, and third dimension to obtain an item recommendation value; determining the target item recommendation value; identifying the target item information corresponding to the item recommendation value; and recommending the target item information to the user. This application can construct a three-dimensional perspective model encompassing multiple scenarios, user groups, and tasks, thereby improving the ability to represent differentiated user groups, meeting diverse
user needs, and achieving comprehensive item recommendation across multiple user groups, scenarios, and tasks.