Abstract: Provided are a classification method and apparatus, an electronic device and a storage medium, which relate to the field of artificial intelligence and in particular, to the fields of natural language processing and deep learning. The classification method comprises: performing coding processing on to-be-classified data to obtain a to-be-classified coding feature; determining reference coding features of reference classification data similar to the to-be-classified data according to the to-be-classified coding feature; and determining a target category of the to-be-classified data according to the reference coding features and reference categories of the reference classification data.

Abstract: Provided is a data labeling method based on artificial intelligence, an apparatus, and a storage medium relating to the field of artificial intelligence, particularly data labeling, image recognition, and natural language processing. The method includes: determining a plurality of samples involved in clustering; performing a plurality of following operations circularly to realize iterative processing, until a convergence condition is satisfied or a quantity of iterations reaches a number threshold, comprising: pre-clustering the plurality of samples according to a vector representation of the respective samples to obtain a plurality of class clusters, each class cluster containing at least one sample; receiving labeling information for the respective class clusters and re-determining the plurality of samples according to the labeling information; and determining a clustering result according to the labeling information for the respective class clusters.

Abstract: A method of recognizing an address, an electronic device, and a storage medium, which relate to fields of artificial intelligence and computer technologies, fields of knowledge graph, deep learning and cloud computing. The method includes: performing a location entity recognition on a content to be recognized, so as to obtain a target location entity, the target location entity including at least one of a standardized location entity, an alias location entity, or a landmark location entity; determining a standardized address corresponding to each type of the location entity in the target location entity according to an address graph to obtain at least one standardized address, the address graph including a standardized location entity, an alias location entity, a landmark location entity, and a corresponding relationship between location entities; and determining, from the at least one standardized address, a first target standardized address corresponding to the content to be recognized.

Abstract: A task processing method, a task processing device and an electronic device are provided, which relate to the field of cloud computing technology and big data technology, in particular to the field of task processing technology. The task processing method includes: obtaining a task processing request for a to-be-processed task, the task processing request including processing time information of the to-be-processed task and a service type of the to-be-processed task; in the case that the processing time information of the to-be-processed task meets a triggering condition, writing the to-be-processed task into a corresponding message queue in accordance with the service type of the to-be-processed task, one message queue corresponding to a respective one service type; and processing the to-be-processed task in the message queue, to obtain a task processing result of the to-be-processed task.

Abstract: An SNP molecular marker for weight gain trait selection and genetic sex identification of Ictalurus punctatus as well as a screening method and application of the SNP molecular marker are provided. At least one of 17 SNP molecular markers for weight gain trait selection of Ictalurus punctatus and a molecular control means for genetic sex and weight gain trait selection and control of Ictalurus punctatus are further provided. Efficient and scientific identification of Ictalurus punctatus is achieved by means of simple PCR reactions and nucleic acid test strips, and the accuracy rate reaches 100%. A traditional agarose gel electrophoresis method is not used in the whole identification process, the cumbersome steps of gel preparation and running electrophoresis are omitted, nucleic acid dyes are not used, and the experimental process is safe and environmentally friendly.

Abstract: A method of processing event data, a device, and a medium are provided, which relate to fields of deep learning, natural language processing, cloud services, etc. The method of processing event data includes: determining target feature data corresponding to target event data, in response to receiving a query request containing the target event data; selecting correlated feature data from candidate feature data based on the target feature data, wherein a similarity between the correlated feature data and the target feature data meets a preset similarity condition; determining operation data associated with the correlated feature data, wherein the operation data represents a level of attention to correlated event data corresponding to the correlated feature data; and determining a level of attention to the target event data based on the operation data.

Abstract: A method of determining a location information, an electronic device, and a storage medium, which relate to a field of an artificial intelligence technology, and in particular, to fields of NLP and knowledge graph. The method includes: determining at least one location chain corresponding to a location information in a text to be recognized, wherein each of the at least one location chain includes a plurality of chain nodes cascaded according to a subordination relationship, and each level of chain node represents a current level name corresponding to the location information; and determining, from the at least one location chain, a target location chain having a greatest degree of relevance to the text to be recognized, according to a feature word indicating a location attribute in the text to be recognized.

Abstract: The present disclosure provides a method and apparatus for constructing an event library, which relate to the technical fields of deep learning, natural language processing, big data, and the like. An implementation includes: acquiring at least one event text data, the at least one event text data being to be assigned to a text library; obtaining an extraction event name based on the event text data; performing a match between the extraction event name and event information in the text library, to obtain a recalled event in the text library; detecting, based on the recalled event, whether the extraction event name meets a unifying condition; and in response to detecting that the extraction event name does not meet the unifying condition, obtaining a new event name in the event library based on the extraction event name, and adding the event text data as a new event into the text library.

Abstract: A method for incrementally training a model is provided. The method includes: obtaining a first soft tag of each raw sample in a raw sample set based on a basic target model trained using the raw sample set; selecting a plurality of raw samples from the raw sample set as first samples based on the first soft tag of each raw sample; obtaining second samples and a second soft tag of each second sample; determining the first samples, the respective first soft tags, the second samples and the respective second soft tags as training samples; and generating a final target model by inputting the training samples into the basic target model for model training.

Abstract: A method, an apparatus, a device and a storage medium for embedding user app interest are provided. The method includes: acquiring a user existing app installation list and a user app installation list within a predetermined time window, where the app includes app ID information and app category information; inputting the existing app installation list and the app installation list within the predetermined time window into a pre-trained user app interest embedding model to obtain a user app interest embedding vector. By combining the user existing app installation list information and the user recent app installation list information, the user app interest embedding vector may simultaneously reflect the user long-term interest and the user short-term interest.

Abstract: A system including a service terminal of a network account subsystem, an image acquisition subsystem and an oil machine subsystem. The service terminal of the network account subsystem provides an association relation between user payment account information and vehicle identifier information. The image acquisition subsystem acquires an image of a vehicle that enters the gas station for refueling, and identifies vehicle identifier information according to an image acquisition result. The oil machine subsystem, after obtaining resource information to be paid for refueling, provides the identified vehicle identifier information and the resource information to the service terminal of the network account subsystem. The service terminal of the network account subsystem further determines associated user payment account information according to the vehicle identifier information and generates a refueling transaction order based on the resource information to be paid.

Abstract: A downhole tool is disclosed for measuring wellbore geometry. The downhole tool may include a body with a bore extending at least partially therethrough. The body may include a radial recess. An arm may be movably coupled to the body at a first end portion of the arm. The arm may be within the radial recess in a retracted position and be pivotable in a radially-outward direction relative to the body to an expanded position. A measurement device coupled to the body may measure the pivoting motion of the arm. A piston coupled to the body may be movably coupled to a second end portion of the arm, and the piston may respond to changes in hydraulic pressure to pivot the arm between the retracted position and the expanded position.