Abstract: A recommendation device obtains to-be-predicted data and a plurality of target reference samples based on a similarity between the to-be-predicted data and the plurality of reference samples. Each reference sample and the to-be-predicted data each include user feature field data indicating a feature of a target user, and item feature field data indicating a feature of a target item. Each target reference sample and the to-be-predicted data have partially identical user feature field data and/or item feature field data. The recommendation device obtains target feature information of the to-be-predicted data based on the plurality of target reference samples and the to-be-predicted data. The recommendation device then uses the target feature information as input to a deep neural network to obtain a target item that is to be recommended.

Abstract: A pressure relief valve includes a valve body with a hollow internal cavity. The internal cavity has two opposite ends, which are in communication with a high-pressure side and a low-pressure side of the pressure relief valve respectively. The pressure relief valve further includes a separating plate disposed in the valve body and located in the hollow internal cavity, and a penetrating member configured to slide linearly in the valve body. The penetrating member has a force applied thereto from the low-pressure side towards the high-pressure side by an elastic component located in the internal cavity. The pressure relief valve further includes a locking structure disposed in the valve body in a fixed manner and spaced apart from the separating plate. The penetrating member is locked in a cut-off state of the pressure relief valve by the locking structure.