Abstract: A method and apparatus for recommending a content, a device, and a medium are provided. The method may include: determining, based on historical behavior data of a user using a product and a feature of a structure of a to-be-recommended content, a target structural preference of the user, the structure being determined by classifying the to-be-recommended content based on any classifying method of a content tag system; and determining each recommendation result of the user based on the target structural preference, the recommendation result including at least two structures and a recommendation content corresponding to each structure.

Abstract: The present invention provides a geotechnical centrifuge platform-based earthquake fault simulation system, involving the field of earthquake disaster simulation technology. A bottom support system of the geotechnical centrifuge platform-based earthquake fault simulation system is used to support a horizontal actuation system and simulate earthquake faults and site covering layers. The horizontal actuation system is used to apply horizontal thrusts to simulated earthquake faults and site covering layers. The simulated earthquake faults are used to fill fault test blocks to simulate bedrock layers of earthquake faults and the site covering layers are used to fill sand layer materials onto surfaces of the simulated earthquake faults to simulate soil layers of the earthquake faults.

Abstract: A method of determining a fusion parameter, a method of recommending an information, a method of training a parameter determination model, an electronic device and a storage medium are provided. The method of determining the fusion parameter includes: inputting a recommendation reference information of a target object into a feature extraction network in a parameter determination model to extract a first object feature for the target object; and inputting the first object feature into a multi-task network in the parameter determination model to obtain a first fusion parameter of a plurality of evaluation indexes for the target object. The plurality of evaluation indexes are used to evaluate a preference of the target object for a recommendation information.

Abstract: Provided are a resource recommendation method and apparatus, a parameter determination method and apparatus, a device, and a medium. The specific implementation is as follows: determining a recommendation reference characteristic of a target user; and determining a resource recommendation result for the target user according to the recommendation reference characteristic of the target user and based on at least two resource recommendation models; where at least two recommendation strategy parameters in the at least two resource recommendation models are jointly determined according to recommendation behavior data of a historical user, and a resource processing stage associated with each of the at least two resource recommendation models is different.

Abstract: A method and apparatus for recommending a content, a device, and a medium are provided. The method may include: determining, based on historical behavior data of a user using a product and a feature of a structure of a to-be-recommended content, a target structural preference of the user, the structure being determined by classifying the to-be-recommended content based on any classifying method of a content tag system; and determining each recommendation result of the user based on the target structural preference, the recommendation result including at least two structures and a recommendation content corresponding to each structure.