6 results about "Multiple attribute" patented technology

This invention discloses a method, device, storage medium, and processor for predicting user churn, comprising: acquiring attribute information of multiple user attributes, wherein the multiple attributes are attributes included in an attribute set; and predicting user churn based on the attribute information using a classification model trained by machine learning, wherein the classification model includes a first classifier model and a second classifier model. The attribute set includes a first subset and a second subset, and the attributes included in the first subset and the second subset are mutually exclusive. The first classifier model is trained based on the attributes in the attribute set and performs classification operations based on the attributes in the first subset. The second classifier model is trained based on the attribute set after adding new attributes. The new attributes are formed by combining at least a portion of the attributes in the second subset. This invention solves the technical problem of inaccurate prediction in existing technologies.

This application provides a data processing method, electronic device, storage medium, and product. The method includes acquiring multiple attribute data corresponding to data to be processed; calculating the comprehensive fuzzy proximity degree corresponding to each attribute data based on the multiple attribute data of the data to be processed; and calculating the attribute fusion result corresponding to the data to be processed based on the comprehensive fuzzy proximity degree. The method obtains the comprehensive fuzzy proximity degree of multiple attribute data corresponding to any position of the data to be processed in the data matrix through a membership function, then calculates the weight value of each attribute data based on the comprehensive fuzzy proximity degree, and finally performs data fusion to obtain a comprehensive attribute fusion result. Although the attribute fusion result loses the physical meaning inherent in the original attribute data, it retains the commonalities and advantages of each attribute data, enabling a more accurate, comprehensive, and reliable description of the same target. Therefore, it improves the accuracy of describing and characterizing underground geological structures.

The application discloses a kind of multi-authority attribute-based encryption protocol implementation method and system, method as follows: one, each attribute management authority center executes main key generation according to the attribute set managed by itself;Two, client obtains the key corresponding to attribute set from multiple attribute management authority centers;Three, server selects random number, encrypts model parameter according to access structure, generates ciphertext component containing policy information;Four, client reconstructs coefficient using the private key component held locally, calculates shared secret locally and decrypts model parameter if attribute satisfies access structure;If attribute does not satisfy access structure, ciphertext does not need re-encryption through policy token to realize policy update.The protocol system proposed in the application significantly improves the flexibility, verifiability and system stability of permission management in large-scale collaboration, long-term task and high supervision requirement application scenarios.

The application provides a robot simulation data generation method, device, equipment, medium and product, relates to the field of data processing, and the method comprises the following steps: acquiring an attribute template of a robot and an article, wherein the attribute template comprises static attribute data and perturbable attribute data; copying multiple attribute templates, modifying the perturbable attribute data in the attribute template, and obtaining multiple robot instances and multiple article instances; assigning position information to the robot instances and the article instances in a task scene, and generating a robot simulation task; and inputting the robot simulation task into a simulation engine for simulation, and generating robot simulation data. The application can improve the generation efficiency of robot simulation data.

The application discloses a kind of data augmentation methods for multi-attribute word extraction, it is related to data processing field, including: first, for the original training sample sentence containing multiple attribute words, attribute word labeling is carried out based on text fragment;Then, according to the labeling result, construct multi-attribute word label data set;Finally, each subset in the multi-attribute word label data set is combined with the original sample sentence to generate new training samples;The application reduces the cost of artificial data labeling, alleviates the problem of insufficient labeled data, designs a data augmentation method based on text fragment label in the multi-attribute extraction application scenario, synthesizes new training samples, and expands the training data;The augmented training data set enables the model to learn more features from the data, enhances the robustness of the model, prevents overfitting, and improves the generalization ability.