Abstract: Embodiments of the present application disclose a method and an apparatus for pushing information. One embodiment of the method comprises: in response to the receipt of an information push request sent by a user by means of a terminal, determining object information about at least one object associated with user information included in the information push request; determining target push information according to the user information, the object information, and a pre-established information determination model, the information determination model being used for characterizing a correlation between user information, object information, and target push information; and pushing the target push information to the terminal for the user to view by means of the terminal.

Abstract: A method and a system for garment try-on. The method includes: capturing a three dimensional (3D) image of a customer; obtaining first 3D pose of the customer in the 3D image; performing a machine learning model on the 3D pose to generate a first skinned multi-person linear model (SMPL) pose; calculating an angle of the whole body rotation of the customer based on the first SMPL pose; when the angle is in a predefined range relative to a front direction of the customer: constructing an SMPL model using the first SMPL pose; and when the angle is out of the predefined range: generating a second SMPL pose using two dimensional (2D) component of the 3D image, and constructing the SMPL model using the second SMPL pose.

Abstract: The present disclosure relates to an information processing method, device, system and computer-readable storage medium, which relates to the field of computer technology. The method of the present disclosure includes: obtaining an identification of an offline item in response to a case that a terminal of a user scans an identification code on the item to successfully obtain a possession or use right of the item; determining an identification of a Radio Frequency Identification (RFID) tag on the item according to the identification of the item; and modifying the RFID tag or a state corresponding to the RFID tag according to the identification of the RFID tag to cause the item to be determined as having passed a checkout verification when the RFID tag is read.

Abstract: A method and a system for recommending a target garment matching an inputted garment. The method includes: extracting attributes from text description and image of the inputted garment to obtain extracted attributes; querying a knowledge graph using the extracted attributes to obtain matched attributes; retrieving candidate products from a garment pool using the matched attributes; extracting features from the inputted garment and the candidate products; determining the target garment from the candidate products based on grading scores between the features of the inputted garment and the features of the candidate products; and recommending the target garment. The knowledge graph includes nodes corresponding to type of clothes, category of clothes, attribute keys, values of attribute keys, context keys, values of context keys, combination of the values of the attribute keys and the type of clothes, and combination of the value of the attribute keys and the category of clothes.

Abstract: A method and apparatus for determining a drug code. The method may include: obtaining a specification text of a drug (201); extracting drug key information in the specification text (202); obtaining, on the basis of a pre-created code inverted index, at least one code related to the drug key information and an ingredient corresponding to each code (203); and screening the at least one code on the basis of the drug key information and the ingredient corresponding to each code to obtain an anatomical therapeutic chemical classification system code of the drug (204).

Abstract: A human-computer interaction method and apparatus. Said method may include: receiving information of at least one modality of a user (201); identifying, on the basis of the information of the at least one modality, intention information of the user and user emotional features corresponding to the intention information (202); determining, on the basis of the intention information, reply information to the user (203); selecting, on the basis of the user emotional features, character emotional features to be fed back to the user (204); and generating, on the basis of the character emotional features and the reply information, a broadcast video of an animated character corresponding to the character emotional features (205).

Abstract: Provided are a speech recognition method, a speech recognition apparatus, a computer readable storage medium, and an electronic device. The method comprises: obtaining a sample speech signal, decoding the sample speech signal, obtaining a decoding result, and extracting a first feature from the decoding result; extracting a target speech segment from the sample speech signal, obtaining a log magnitude spectrum of the target speech segment, and determining a second feature according to the log magnitude spectrum; combining the first feature and the second feature to obtain a third feature; training an untrained classifier by using the third feature so as to obtain a trained classifier; and obtaining a third feature to be recognized of a speech signal to be recognized, so as to determine whether the third feature to be recognized comprises a prepositive word.

Abstract: A method for processing warehousing data includes: obtaining attribute data of a preset object from a warehousing data table; determining safety inventory data of the preset object and target inventory data of the preset object according to the attribute data of the preset object; obtaining current inventory data of the preset object from the warehousing data table; determining, in response to that the current inventory data of the preset object is less than or equal to the safety inventory data of the preset object, a replenishment quantity of the preset object according to the target inventory data of the preset object and the current inventory data of the preset object; and sending the replenishment quantity of the preset object to a warehouse management system, causing the warehouse management system to perform replenishment according to the replenishment quantity of the preset object.

Abstract: A system for knowledge graph construction. The system includes a computing device. The computing device has a processor and a storage device storing computer executable code. The computer executable code, when executed at the processor, is configured to: define entities and relations of the knowledge graph; provide documents having sentences; convert the sentences into fix length sentence embeddings and regard the sentence embeddings as primary capsule layers; use a set transformer to learn entity capsules and relation capsules from the primary capsule layers; for each triple, project head and tail entities from entity space to the specific relation space, and determine the relation exists when the sum of the projected head entity vector and the relation vector substantially equals to the projected tail entity vector; and construct the knowledge graph using the head entity, the tail entity, and the determined relation.

Abstract: A custom tone and vocal synthesis method and apparatus, an electronic device, and a storage medium. The synthesis method comprises: training a first neural network by means of a speaker record sample to obtain a speaker recognition model, the output training result of the first neural network being a speaker vector sample (S102); training a second neural network by means of an unaccompanied vocal singing sample and the speaker vector sample to obtain an unaccompanied singing synthesis model (S104); inputting a speaker record to be synthesized into the speaker recognition model to obtain speaker information output by the intermediate hidden layer of the speaker recognition model (S106); and inputting unaccompanied singing music information to be synthesized and the speaker information into the unaccompanied singing synthesis model to obtain a synthesized custom tone and vocal (S108).

Abstract: Disclosed in the present application are an information transmission method, system and apparatus. The specific implementation solution comprises: in response to reception of a data request sent by a client, parsing content of the data request to obtain identification information corresponding to the data request; in response to the identification information being null, obtaining a first data set corresponding to the data request; dividing all pieces of data in the first data set on the basis of data resources of the pieces of data and data time lengths of the pieces of data to obtain a second data set corresponding to the first data set, the division indicating performing division of data request order on all the pieces of data in the first data set on the basis of the data time lengths; and sending the second data set to the client.

Abstract: An image generation method and apparatus. The method includes: performing image composition on the basis of an acquired image generation condition, and determining a primitive type and layout information of an image, so as to obtain a composition image (201); according to scenario construction information corresponding to the image generation condition, performing scenario construction on the composition image, and determining a primitive corresponding to each primitive type from among a plurality of primitive types in the composition image, so as to obtain a scenario construction image (202); adjusting the color of each primitive in the scenario construction image according to color matching information corresponding to the image generation condition, so as to obtain a color-matched image (203); and rendering the color-matched image to obtain a target image (204).

Abstract: A video generation method and apparatus. The method may include: determining one template from multiple types of templates as a production template on the basis of an input instruction of a user (201); in response to determining that the type of commodity information inputted by the user is matched with the type of the production template, obtaining a commodity picture or commodity video material related to the commodity information (202); and processing the commodity picture or commodity video material on the basis of the production template to generate a commodity video (203).

Abstract: A method and apparatus for recommending information are provided. The method includes: acquiring, in response to determining that a user enters a preset interface based on a first preset operation of the user, operation information within a preset length of time before the user performs the first preset operation; determining behavior data of the user browsing the preset interface based on the operation information; and determining recommendation information for the user based on the behavior data, and displaying the recommendation information in the preset interface.

Abstract: The present application relates to the technical field of artificial intelligence. Disclosed are a data feature generation method and apparatus. A particular embodiment of the method comprises: issuing a feature configuration template, such that a user configures, on a configuration interface, the content of the feature configuration template; receiving configuration content configured by the user for the feature configuration template and at least one set of time sequence data to generate at least one set of data feature values.

Abstract: Provided are a data processing method and apparatus, and an electronic device and a storage medium, which relate to the technical field of computers. The data processing method comprises: acquiring data to be subjected to statistics collection, and performing fragmentation processing on said data to generate task fragment data; distributing the task fragment data to an event listener by means of a preset event broadcaster; and on the basis of the event listener, querying and assembling data according to the task fragment data, so as to generate multi-level category data corresponding to the data to be subjected to statistics collection.

Abstract: A method for rendering hair is provided and includes: obtaining a first rendered result by performing transparent channel test rendering on a specified pixel point in a hair model, wherein the specified pixel point is a pixel point with a pixel depth value less than a preset depth threshold and a transparency channel value greater than a preset transparency threshold; obtaining a second rendered result by performing transparent channel hybrid rendering on a backlight pixel point of the hair model based on the first rendered result; obtaining a third rendered result by performing transparent channel hybrid rendering on a light-oriented pixel point of the hair model based on the second rendered result; obtaining a final rendered result of the hair model by hybridizing the first rendered result, the second rendered result and the third rendered result.

Abstract: Systems and method for lifelong tag learning. The system includes a computing device having a processor and a storage device storing computer executable code. The computer executable code is configured to: provide product descriptions and seed tags characterizing products; train a named-entity recognition (NER) model using the product descriptions and the seed tags; predict pseudo tags from the product descriptions using the NER model; calculate confidence scores of the pseudo tags; compare the confidence scores with a threshold, and define the pseudo tags as true tags when the confidence scores are greater than the threshold; add the true tags to the seed tags to obtain updated tags; and repeat the steps of training, predicting, calculating, comparing and adding using the product descriptions and the updated tags, so as to keep updating the updated tags.

Abstract: A product management method and apparatus, a computer readable storage medium, and an electronic device, relating to the technical fields of computers and communications.

Abstract: A method and a system for predicting and using customer lifetime value (CLV). The method include: providing a classifier trained using customer feature data during a first period of time as input and whether there is spending during a second period of time as classifier label; providing a regressor trained using the customer feature data during the first period of time as input and amount of spending during a second period of time as regressor label; performing the classifier using customer feature data during a third period of time to obtain customers having positive predicted classifier labels; and performing the regressor using the customer feature data during the third period of time for the customers having positive predicted classifier labels, to obtain CLVs of the customers.