17 results about "User confidence" patented technology

Backup and recovery of multi-party computation (MPC) security data utilized to secure digital assets and transactions thereof can enhance user confidence and user experience in digital asset transactions. Example MPC security data can include cryptographic keys and key shares utilized with a N×M MPC signature and validation framework. A computing device participating in generation of MPC secure data can retain a segment of the MPC secure data and can encrypt and store an encrypted segment at a second device. A recovery service or recovery application at the second device can facilitate recovery of the MPC secure data segment at the computing device, or at an additional device not involved in generation of the MPC secure data. The recovery service or application can facilitate recovery of the MPC secure data segment even in the event the computing device is lost.

A method for an interactive communication session includes receiving a request regarding a commitment associated with a user; initiating an interactive communication session with a user device; generating a prompt for inclusion in the interactive communication session, the prompt including a first question regarding an expected duration of a hardship; providing the prompt in the interactive communication session such that the prompt is provided via the user device; receiving a reply to the prompt from the interactive communication session; analyzing the reply to determine a confidence of the user in satisfying a modified commitment included with the prompt; comparing the confidence to a predefined confidence threshold; iteratively repeating the receiving, analyzing, and comparing processes until a determined confidence of the user meets or exceeds the predefined confidence threshold; and transmitting an updated term for the user based on the iterative process to the user device.

Examples provide a system and method for dynamically improving and validating automation plans using generative artificial intelligence (AI). An automation manager analyzes automation plans during the design phase and the testing phase. The automation plan makes suggestions for improving the automation plan in real time using natural language prompts. The automation plan validates the automation plan against guardrails defining restrictions on the actions performed by the system during automation plan execution. The system generates explainability data describing the next planned actions and reasons why each planned action is selected for execution during the automation to increase user confidence in the automation. The system requests user approval prior to performing each action for more accurate and efficient workflow automation while reducing system resource usage consumed during execution of inefficient or ineffective automation plans.

The present disclosure relates generally to computer-implemented systems and techniques for leveraging a virtual decentralized database to enable user identity authentication and verification of user activity and associated behaviors on open internet and public web-based and native applications. Techniques are disclosed for user identification profile onboarding using biometrics, frictionless CAPTCHA (Completely Automatic Public Turing Tests To Tell Humans And Computers Apart) processes, passive data capture of physiological and behaviors using device sensors, and cryptographic methods of storing user engagement activity as immutable data files for secure distribution on a decentralized virtual private network. Such technologies operate to establish a high confidence level for user authenticity, communication origin, engagement outcome transparency and clarity of intent for users active on social, commercial, e-commerce and information sharing platforms. More specifically, an unobtrusive passive data capture method of authentication and verification on a secure VPN supports the organic, spontaneous and original experience audiences desire while simultaneously eliminating opportunities for unscrupulous actors to exploit open internet exchanges by inserting fraudulent user accounts, automated bots and other measures that mimic or impersonate live humans, which ultimately undermines user confidence in data safety and erodes mutual trust between people, companies and institutions.

Backup and recovery of multi-party computation (MPC) security data utilized to secure digital assets and transactions thereof can enhance user confidence and user experience in digital asset transactions. Example MPC security data can include cryptographic keys and key shares utilized with a N x M MPC signature and validation framework. A computing device participating in generation of MPC secure data can retain a segment of the MPC secure data and can encrypt and store an encrypted segment at a second device. A recovery service or recovery application at the second device can facilitate recovery of the MPC secure data segment at the computing device, or at an additional device not involved in generation of the MPC secure data. The recovery service or application can facilitate recovery of the MPC secure data segment even in the event the computing device is lost.

The invention relates to a virtual power plant baseline calculation method introducing user confidence, and the method comprises the following steps: carrying out the analysis based on a user load prediction curve, and obtaining a historical prediction load value before an event release day and a user load prediction value of the event release day; calculating a user confidence coefficient by using the historical predicted load value and the corresponding actual load value; screening out a plurality of typical days before the demand response day; calculating a historical baseline load value according to the actual load value of the typical day; and calculating a virtual power plant load baseline based on the user confidence, the historical baseline load value and the user load prediction value. According to the method, the load baseline of the virtual power plant can be optimized, the influence of the load prediction deviation on the baseline is reduced, and users are better encouraged to adjust energy consumption behaviors.

The invention discloses a data analysis system and method for a performance management platform, and relates to the technical field of data analysis, and the method comprises the following steps: 1, a user inputs evaluation content through a text or an option, and constructs a mapping relation between option input and text input; step 2, comparing options input by the user with options input by the to-be-assessed person, and weighting and calculating a deviation degree through weight distribution; step 3, based on historical input records of the user and the to-be-assessed person, respectively calculating an average deviation degree to obtain a user confidence coefficient and a to-be-assessed person confidence coefficient; and step 4, in combination with a manually set option normativity coefficient, respectively calculating normativity scores of the user and the to-be-assessed person, and carrying out weighted summation to obtain a total normativity score. The method can effectively improve the condition that the performance management is further affected due to the fact that the assessment is affected due to the fact that the personal viewpoint is too subjective in the prior art.

The present application relates to a kind of virtual power plant baseline calculation method of introducing user confidence, comprising the following steps: based on user load prediction curve, the historical predicted load value before event release day and the user load prediction value of event release day are obtained by analysis;User confidence is calculated using the historical predicted load value and its corresponding actual load value;Filter out several typical days before demand response day;According to the actual load value of the typical day, the historical baseline load value is calculated;Based on the user confidence, the historical baseline load value and the user load prediction value, the virtual power plant load baseline is calculated.The present application can optimize the load baseline of virtual power plant, reduce the influence of load prediction deviation on baseline, better encourage user to adjust energy behavior.

This application relates to the technical field of electronic signature and evidence preservation, and specifically relates to a method for preserving all-process data of electronic signatures based on blockchain. The method includes: collecting all historical transaction behavior data of each user before each transaction in the blockchain, including transaction users, transaction times, and text data of signed documents; determining the theme difference degree of signed documents for any two transactions; determining the transaction behavior anomaly coefficient for each user at each transaction; obtaining the malicious user confidence level for each user at each transaction; for each transaction, based on the number of transactions between each user and each user to be signed, combined with the malicious user confidence level of each user to be signed, obtaining the selectable coefficient of each user to be signed for each user at each transaction, screening the users to be signed, and using an encrypted signature algorithm for electronic signature. This application ensures the anonymity of the signer's identity and improves the privacy and security of both trading parties.

A reminding method, system, and apparatus, a vehicle, a computer-readable storage medium, and a computer program product, which relate to the field of intelligent vehicles. According to the reminding method, a masking result of a sound masking system on a target sound at a sound masking location is determined, and the masking result is displayed to a user, so that user confidence in using the sound masking system can be improved. The reminding method further provides a plurality of modes for receiving user instructions and a plurality of modes for presenting reminder information to the user, so that various possible situations can be promptly and effectively fed back to the user, thereby improving user confidence in using the sound masking system, and further improving the usability of the sound masking system.

Presented is a network security system (NSS) that reliably detects malleable C2 traffic. The NSS intercepts outgoing transactions from user devices associated with user accounts. The NSS filters out transactions to known benign servers and analyzes remaining transactions for indicators of malleable command and control (C2) including heuristic, anomalous, and pattern-based detections. The NSS lowers the user confidence score associated with the user account or the user device based on the severity and number of detected indicators for each impacted outgoing transaction. When the user confidence score decreases below a threshold, the NSS implements a restricted security protocol for future outgoing transactions. Based on the detected indications, the NSS can identify malleable C2 attacker servers and add them to a blacklist of destination servers to further identify infected user accounts and devices.

Examples provide a system and method for dynamically improving and validating automation plans using generative artificial intelligence (AI). An automation manager analyzes automation plans during the design phase and the testing phase. The automation plan makes suggestions for improving the automation plan in real time using natural language prompts. The automation plan validates the automation plan against guardrails defining restrictions on the actions performed by the system during automation plan execution. The system generates explainability data describing the next planned actions and reasons why each planned action is selected for execution during the automation to increase user confidence in the automation. The system requests user approval prior to performing each action for more accurate and efficient workflow automation while reducing system resource usage consumed during execution of inefficient or ineffective automation plans.

A method includes receiving a plurality of textual data from one or more users within an online chat group. The method also includes rendering the plurality of textual data for each user of the online chat group. The method includes further enabling one user from the online chat group to edit a textual data originated by another user from the online chat group. A notification is rendered on a graphical user interface (GUI) that the textual data originated by the another user has been edited. In response to a user selection thereof, the edit is accepted, rejected, or further edited.

The invention relates to the technical field of humectant process optimization, in particular to a process optimization method and system for achieving a skin humectant, and the method comprises the steps: determining a to-be-optimized direction group, designing a multi-dimensional option questionnaire based on the to-be-optimized direction group, carrying out the user experience return visit through a customer experience end and the multi-dimensional option questionnaire, and obtaining a multi-dimensional experience report, constructing a user skin feature matrix by using a multi-dimensional experience report, calculating user confidence, correcting the user skin feature matrix to obtain a corrected skin feature matrix, inputting the corrected skin feature matrix into a humectant proportion adjustment model to obtain a humectant proportion, and performing weighted averaging on a humectant proportion set by using a user confidence set to obtain a humectant proportion; the target humectant proportion is obtained. According to the method, the user universality of humectant process optimization can be improved, and the dynamic change required by a user can be met.

The present invention discloses a method for recognizing railway alarm processing information text based on a large language model. This method addresses existing problems in the railway alarm processing information text recognition process by providing a scientific, rational, highly applicable, and effective solution for deeply mining and analyzing the effective information contained in this text data. The method's framework is easy to establish and implement, leveraging the powerful generation capabilities of the large language model to expand and enhance different categories of railway alarm processing information text, addressing the problem of sample imbalance. Furthermore, combined with retrieval enhancement generation technology, it integrates input prompts with knowledge base search results, providing a stronger basis for reasoning, improving user confidence in the data classification model, and enhancing the accuracy of railway alarm processing information text classification. Overall, the method possesses the advantages of being scientific, rational, highly applicable, and effective.

The present application relates to the technical field of moisturizer process optimization, and a process optimization method and system for realizing skin moisturizers, comprising: determining a to-be-optimized direction group, designing a multi-dimension option questionnaire based on the to-be-optimized direction, conducting user experience follow-up visits by using a customer experience terminal and the multi-dimension option questionnaire, obtaining a multi-dimension experience report, constructing a user skin quality characteristic matrix by using the multi-dimension experience report and calculating user confidence, correcting the user skin quality characteristic matrix to obtain a corrected skin quality characteristic matrix, inputting the corrected skin quality characteristic matrix into a moisturizer proportioning adjustment model to obtain a moisturizer proportion, and obtaining a target moisturizer proportion by using weighted average on a user confidence set and a moisturizer proportion set. The present application can improve the user universality of moisturizer process optimization and meet the dynamic changes of user demand.