Abstract: Provided are a real-time prediction method, an electronic device and a non-transitory computer-readable storage medium, which relate to the field of data processing, and in particular to the field of artificial intelligence. The specific implementation solution is acquiring a user request based on a business scenario; acquiring, from a plurality of pre-stored original features, at least one target original feature corresponding to the user identifier; determining, from a plurality of pre-trained models, a target model corresponding to the scenario identifier, and determining, from a plurality of feature engineering services, a target feature engineering service corresponding to the target model; performing real-time feature processing on the at least one target original feature by means of the target feature engineering service, so as to obtain a target model entry feature; and inputting the target model entry feature into the target model.

Abstract: A data processing method is provided. The method includes: obtaining a sample data set for modeling; selecting a first sample data from the sample data set; generating, in response to determining that a similarity between a first semantic vector corresponding to a first feature dimension and a second semantic vector corresponding, to a second feature dimension meets a preset condition, a second sample data based on the first sample data; and adding the second sample data to the sample data set.

Abstract: Disclosed are a method for acquiring information. The method includes: acquiring a file to be processed and an information type; recognizing at least one piece of candidate information related to the information type from the file to be processed; determining a target recognition feature and a semantic feature of each piece of candidate information, the target recognition feature is configured to describe a matching condition between the each piece of candidate information and the information type; and determining target information from the at least one piece of candidate information based on the target recognition feature and the semantic feature.

Abstract: An entity recognition method and apparatus, an electronic device, a storage medium, and a computer program product are provided. The method includes: recognizing a to-be-recognized image to determine a preliminary recognition result for entities in the to-be-recognized image; determining, in response to determining that the preliminary recognition result includes a plurality of entities of a same category, image features of the to-be-recognized image and textual features of the plurality of entities; determining whether the plurality of entities is a consecutive complete entity based on the image features and the textual features, to obtain a complete-entity determining result; and obtaining a final recognition result based on the preliminary recognition result and the complete-entity determining result.