524results about How to "Examples cannot be limited" patented technology

A neural network model training method and device, and a computer device are disclosed. The neural network model training method includes: performing training by using a source domain sample set to obtain a neural network model; performing iterative processing by using the following steps until an iterative stop condition is satisfied: inputting an uncertain label sample in a target domain sampleset into the current neural network model, and using the output prediction result as a current learning label of the uncertain label sample; inputting a source domain sample set and the current targetdomain sample set in to the current neural network model, constructing a neural network loss function on the basis of the output prediction result, wherein independent variables of the neural networkloss function include at least: a difference between a mapping feature of the source domain sample set and a mapping feature of the current target domain sample set; using the current neural networkloss function to perform back propagation so as to update model parameters of the current neural network model; and determining the current neural network model as the final trained neural network model after iteration is ended.

The invention discloses a model training method based on federated learning. In one training iteration, the nodes can achieve noise adding and confusion of the gradient through differential privacy protection operation, and the server can obtain the sum of the gradients after noise adding and confusion to update model parameters.

The invention discloses a transaction method and system based on centralized settlement and block chain deposit certification. A block chain network comprises a plurality of member nodes, a user registers a virtual resource account on a designated member node, and the designated member node comprises a business logic execution module, a database management module and a block chain function module.The business logic execution module verifies the feasibility of the transaction according to a transaction request, after passing the verification, the database management module is instructed to perform an account balance modification operation, that is, a designated resource amount is deducted from a virtual resource account corresponding to an expenditure user identity, and the designated resource amount is added to a virtual resource account corresponding to an income user identity. Besides, the business logic execution module also generates a log file for recording the account balance modification operation, the log file is sent to the block chain function module, and the block chain function module broadcasts the log file to the block chain network.

A method, device and equipment for constructing a merchant classification model and merchant classification are disclosed. A method for constructing a merchant classification model includes obtaininga plurality of merchant samples, wherein each merchant sample includes historical transaction information and business model type of that merchant; extracting eigenvectors of each merchant sample; themerchant classification model being trained by a machine learning algorithm according to the business model types of several merchant samples and the extracted eigenvectors. A merchant classificationmethod based on the merchant classification model comprises the following steps: acquiring historical transaction information of the merchant to be classified; extracting a feature vector of the merchant to be classified; the extracted feature vector of the merchant to be classified being input to the merchant classification model to predict the business mode type of the merchant to be classified.

The invention discloses a method and device for the credit evaluation of a work publisher based on blockchain. The method and device can perform the originality analysis of target work published by atarget business node (any one business node) to the blockchain to obtain an originality representation value of the target work. If the originality representation value is lower (indicating that the target work is suspected of plagiarism), the copyright credit score corresponding to the target business node will be reduced, and after the reduced copyright credit score (copyright credit score reduction quantity) of the target business node needs to pass through the common verification of a plurality of business nodes, the reduced copyright credit score (copyright credit score reduction quantity) of the target business node can be publically displayed on the blockchain. The blockchain can publically display the copyright credit score reduction record of the target business node so as to determine the copyright credit score of the target business node according to the copyright credit score reduction record. The lower the copyright credit score of the target business node is, the poorer the credit level of the target business node is.

The invention discloses a claim settlement service processing method and device. The claim settlement service processing method comprises the steps of obtaining claim settlement data in a claim settlement application; obtaining a claim settlement rule corresponding to the insurance policy information of the insurance policy needing to be claimed according to the insurance policy identifier; obtaining credit data of a claim settlement user according to the user identifier; determining a plurality of rule features needing to be extracted according to a preset corresponding relation between the claim settlement rule and the rule features, and extracting the rule features from the claim settlement proof; extracting a plurality of preset credit characteristics from the credit data; and inputting the extracted features into a pre-trained claim audit model, and determining whether the claim application is passed or not according to an output result of the model.

The invention discloses a business risk prevention and control method, device and equipment. A first training sample set and a second training sample set are summarized to form a mixed training sampleset, and each training sample is endowed with a corresponding sampling weight. And then corresponding model training is carried on the training sample set to obtain a classification model, and an error recognition rate of the classification to the first training sample is calculated. And then the sampling weights of the first training sample and the second training sample in the training sample set are continuously adjusted based on the error recognition rate, so that a target classification model with certain accuracy on the first training sample can be finally obtained, and accurate risk control defense can be carried out on the first service according to the target classification model.

The invention discloses a method and a system for storing copyright event based on a block chain. The devices of some works service providers that operate works-related services can be used as membernodes to form a federation chain network, and each works service provider broadcasts copyright events generated based on its own works-related services to the federation chain network, and each worksservice provider performs distributed certification based on the block chain.

The invention discloses a method and a system for collecting evidence based on block chain storage. The user (party) may operate the user equipment, records his behavior and/or voice as a multimedia file, Then, the user equipment sends the multimedia file to the service equipment, and the service equipment builds the target transaction based on the multimedia file, broadcasts the target transaction to the block chain network, and each node in the block chain network publishes the target transaction to the block chain based on the consensus mechanism. Thus, the multi-party storage of the multimedia file is realized.

The invention discloses a replacing operation method and device after model update and a business server. The method comprise that comprehensive properties of different updated models are compared; the updated model with the optimal comprehensive property is determined to be a candidate model; performance of the candidate model is compared with that of a present online operation model in a specific risk threshold, the performance of the candidate model or the present online operation model in the specific risk threshold is determined according to a standard score corresponding the a score output by a specific online event set as well as an auditing result for the specific online event set obtained according to the standard score and the specific risk threshold, and the specific risk threshold is determined according to a preset model strategy; if the comparison result shows that the performance of the candidate model is higher than that of the present online operation model, the candidate model is disposed as the online operation model.

The invention discloses a data inquiry method, a device and a service server integrated with multiple data sources. The method comprises the following steps: receiving a data inquiry request, whereinthe data inquiry request carries data attributes of data to be inquired; determining a target data source attribute according to a mapping relationship between a pre-configured data attribute and a data source attribute, wherein the data source attribute comprises a data source name and a field name; determining a target atomic interface of the target data source attribute mapping according to a pre-configured mapping relationship between the data source attribute and the atomic interface; according to the mapping relationship between the pre-configured atomic interface and the underlying data, the data being extracted from the underlying data mapped by the target atomic interface to obtain the data to be queried.

The invention discloses a third party authorized login method. The method comprises the following steps: when an authorized website detects that a login operation of a third party account of a user istriggered, the authorized website generates a two-dimensional code corresponding to the third party account; the authorized website displays the two-dimensional code to the user; when a third party client monitors that a two-dimensional code scanning operation of the user is triggered, the third party client identifies the two-dimensional code and prompts the user for authorization or not; when the third party client monitors that an authorization confirmation operation of the user is triggered, a third party server performs third party authorization authentication with the authorized website; and after the third party authorization authentication between the third party server and the authorized website is passed, the third party authorized login of the authorized website is successful.

The invention discloses a model operation method, a device and a service server. The method comprises the following steps: in any preset model operation cycle, the following steps are executed: obtaining a prediction result output by the current running model for the preset test event set, and carrying out statistics on the prediction result to obtain at least one performance index value; obtaining at least one quantitative index value of a model independent variable of the current operating model; determining whether the current operating model is abnormal according to the at least one performance index value and the at least one quantitative index value; when it is determined that the current running model is abnormal, updating the current running model according to a preset set of optimization training events; comparing the performance of the updated model with that of the current running model, and if the performance of the updated model is superior to that of the current running model, deploying the updated model as an on-line running model.

Disclosed are a block chain-based copyright event broker authentication method and system. The equipments of some works service providers that operate works-related services can be used as member nodes to form a federation chain network, and each works service provider broadcasts copyright events generated based on its own works-related services to the federation chain network, and each works service provider performs distributed certification based on the block chain. In addition, at least one proxy member node exists in each member node, and for each proxy member node, the proxy member nodehas the right to proxy non-member nodes corresponding to the proxy member node for copyright event certification.

The invention discloses a risk control model training method and device, and equipment. When the black samples in the training samples are impure and the risk control model is trained, cross validation is carried out on the training samples through other related trained risk identification models, so that the black samples with low scores and the white samples with high scores are filtered out, and the model is retrained by utilizing the screened samples.