9646 results about "User information" patented technology

The invention provides a method and system for realizing electronic channel risk control processing based on a code insertion technology, and relates to the technical field of electronic channel risk control, and the method comprises the steps: encrypting user information and channel identification information through a dual Hash algorithm to generate a dynamic session identification code, and forming a target coding sequence through employing a self-adaptive segmentation algorithm and a business feature flag bit. And constructing a dynamic risk control rule model by using a graph neural network, extracting user multi-dimensional features, carrying out weighted fusion to generate a user risk score, comparing the user risk score with an adaptive risk threshold, analyzing abnormal behaviors based on a probability graph model, and generating an intelligent risk early warning report. And calling a reinforcement learning risk control strategy engine to determine an optimal disposal strategy, and issuing a multi-factor interaction verification instruction. And after verification, selectively activating a blocking mechanism according to a verification result, synchronizing interaction data and a result to a distributed risk control data center, and continuously optimizing the risk control model based on federal learning.

A system for development of an Artificial Intelligence (AI) model while protecting sensitive user information includes: a confidential computing environment in which original prompts to the AI model written by users are collected; a trained synthetic prompt generator to generate synthetic prompts based on the original prompts, wherein the synthetic prompt generator generates anonymized synthetic prompts without sensitive user information identifiable from the original prompts; and a developer computing environment in which the synthetic prompts are submitted to the AI model under development to generate a dataset that includes the synthetic prompts and corresponding AI model output for analysis to determine updates for the AI model while protecting the sensitive user information of actual users.

The embodiment of the invention provides an information generation method and device, electronic equipment and a storage medium. The information generation method comprises the following steps: in response to an obtained question and user information, calling a first agent to determine a target intention based on the question and the user information; a second agent is called to determine a to-be-executed task corresponding to the target intention, the second agent is called to execute the to-be-executed task to generate target information, the target information serves as reply information of the target intention to be sent to the client side, and the first agent and the second agent are responsible for intention confirmation and task planning respectively. According to the technical scheme, the intelligent agent has the learning ability and can make corresponding actions based on the change of the environment, so that the target intention can be determined according to the problem of the user and the experience of similar problems appearing before, the to-be-executed task is further determined, the efficiency of processing the user problem is finally improved, and the user experience is improved.

The invention discloses a mechanical arm control method, system and equipment for realizing a multi-modal universal operation task. The method comprises the following steps: acquiring multi-modal data of text, voice and vision; performing modal alignment on the multi-modal input data, encoding the multi-modal input data into a uniform input representation vector, and splicing the uniform input representation vector into a multi-modal instruction paragraph; retrieving a user information voice database based on voiceprint features of the voice instruction data to obtain task associated voice data; instruction information is input into the strategy large model to obtain an action plan; a post-processing task action planning input controller controls a mechanical arm, and a multi-mode input instruction is updated in real time to perceive the latest task state; and performing closed-loop control based on the initial target instruction information and the environment perception information until the task is completed. The task planning and error correction capacity of the mechanical arm is improved through closed-loop control and voice data retrieval based on the large strategy model, and the dynamic adaptive capacity, the autonomous error correction capacity and the multi-mode interaction capacity of the mechanical arm are improved.

A method for generating personalized responses in a conversation with a user includes generating real-time contexts capturing an environment of the user over time, including generating a particular real-time context based on a first data stream corresponding to a first modality in an environment of the user and a second data stream corresponding to a second modality in the environment of the user, generating historical contexts based on the real-time contexts, in response to receiving a conversational cue provided by the user, generating a current real-time context based on data corresponding to the first modality and the second modality in a current environment of the user, and generating, based on the current real-time context, a personalized response to the conversational cue, including identifying, based on the current real-time context, relevant user information, including identifying one or more relevant historical contexts, and generating the personalized response using the relevant user information.

The invention discloses an intelligent multimedia interactive teaching and examination system and method, and relates to the technical field of education informationization, and the method comprises the steps: obtaining user information and a learning state, and generating a learning portrait; based on the learning portrait, utilizing the generative AI to dynamically generate personalized teaching content, and marking the abnormal state of the user in real time; storing an abnormal state marking result of the user to a dynamic feature field of the learning portrait, and dynamically optimizing a learning path; based on the optimized learning path, a personalized assessment task is dynamically generated, and answer data and learning behavior data of the user are recorded; and performing multi-dimensional evaluation on the performance of the user through a semantic analysis method by utilizing the answer data and the learning behavior data. According to the method, through the comprehensive analysis model and the multi-modal feature vector, multi-dimensional evaluation of the performance of the learner is realized, multiple aspects of knowledge mastery, behavior performance, emotional state and the like are covered, and detailed feedback and improvement suggestions are provided for the learner.

The invention discloses a lower limb motion data real-time analysis method and system applied to rehabilitation guidance, and the method comprises the steps: calling a personalized model according to user information, converting real-time motion data into historical motion feature vectors, inputting the historical motion feature vectors into a real-time prediction module, and generating multiple frames of future motion feature vectors through coding and decoding; calculating a deviation value between each future motion feature vector and a preset threshold range to obtain a motion deviation value, calculating a motion risk proportion of each future motion feature vector, performing weighted fusion to obtain a motion risk probability, and generating an equipment parameter adjustment value and pose adjustment information through reverse mapping; and finally, according to risk probability assessment training stage promotion, synchronously displaying correction information and adjusting equipment operation parameters. According to the method, the dynamic model is constructed through pre-training, real-time prediction of future motion features is realized in combination with the lightweight LSTM, and the predictability and personalized adaptation ability of rehabilitation guidance are improved.

The invention discloses a liver disease diagnosis and treatment strategy recommendation method based on a knowledge graph, a medium and equipment, and the method comprises the steps: collecting the basic information of a user, constructing a space-time correlated individual liver disease knowledge graph according to the basic information of the user, and enabling the knowledge graph to comprise a disease cause feature node, a pathology grading node, a complication early warning node and a treatment response node which are correlated with each other; inputting the individual hepatopathy knowledge graph into a hierarchical reinforcement learning model for joint reasoning, and outputting multiple groups of strategy options including an antiviral treatment scheme, a liver protection drug combination and a metabolic intervention measure; analyzing a topological propagation path of a complication early warning node through a complication prediction sub-model, and dynamically adjusting an initial candidate diagnosis and treatment strategy set; and updating the individual hepatopathy knowledge graph when obtaining the basic information of the new user. According to the method, multi-dimensional data fusion and dynamic strategy optimization of liver disease diagnosis and treatment are realized, and the accuracy and timeliness of a diagnosis and treatment scheme are remarkably improved.

The invention discloses a dynamic power distribution network deduction method based on graph neural network perception and a privacy protection type Transform model. The method comprises the steps of collecting source load storage historical data in a power distribution network and performing standardization processing; performing time sequence segmentation; establishing a dynamic topological structure model of the power distribution network; extracting spatial features of the dynamic topological structure of the power distribution network by using a graph neural network; the spatial features are converted into time sequence data, the time sequence data are combined with time sequence data obtained after time sequence segmentation, and a source network load storage time sequence data set is established; differential privacy processing is carried out; training a Transform model, in the training process, using a differential privacy optimization technology, adding noise to the gradient when the gradient is updated each time, and finally obtaining a trained DP-Transform model; and inputting a specific scene, and deducing the state of the power distribution network by using a DP-Transform model. According to the method, the interpretability of deducing the state of the power distribution network by using the Transform is improved, so that the Transform model can fully receive the graph structure input of the network topology structure of the power distribution network, and privacy protection on user information in the deducing process is considered.

In accordance with the present disclosure, systems and methods are provided for providing personalized education to users. the systems and methods may collect, process, and analyze various user information including data from compatible IoT devices using a composite AI model. The systems and methods may generate a personalized education profile for the user using the composite AI model based on the analyzed user information. The systems and methods may generate and deliver personalized education content aided by the use of the composite AI model. the system may also monitor and receive user feedback in real-time for updating the composite AI model, the personalized education profile, and the personalized education content.

To reduce the burden on a business operator related to acquisition and management of a my number.SOLUTION: A method executed by a job offer management server 1 includes: an application information reception step of receiving application information indicating that a user has applied to a job offer posted by a job offer business operator from an employment support server 4; a first determination step of determining that provision of a my number from the user is required if the user information of the user does not include the my number; a my number provision request step of transmitting a my number provision request notification related to the user to the employment support server 4 or the user terminal device 3 of the user; and a my number registration step of registering the acquired my number in the user information of the user.SELECTED DRAWING: Figure 1

The invention relates to the technical field of system security, in particular to a computer storage file protection system which comprises a risk analysis module, a dynamic encryption module, an authentication management module and a behavior monitoring module. According to the method, the response speed and the personalized protection level of the file security are improved by automatically collecting location, time and user information parameters and executing context risk logic analysis, the system can provide customized protection schemes for different security requirements by dynamically adjusting an encryption mechanism and the key length, and the security of the file is improved. The system is allowed to strengthen protection measures under the high-risk condition, resource use is optimized under the low-risk condition, unnecessary performance burdens are avoided, through real-time monitoring and behavior analysis, the system can recognize and respond to abnormal behaviors in time, unauthorized access and data leakage are effectively prevented, potential threats to sensitive information are reduced, and the safety of the system is improved. The overall security management capability of the system is improved, and the continuity and effectiveness of data protection are ensured.

The invention discloses an AI-based cultural tourism content personalized recommendation system, which relates to the technical field of tourism planning and comprises a user information acquisition module, a cultural tourism content database information storage module, a recommendation engine module, an emotion analysis module, a real-time recommendation updating module and a multi-channel display module. According to the method, basic information, tourism preference, historical behaviors, geographic positions and social media data of users are collected, personalized portraits are generated and accurately recommended, sentiment analysis, real-time positions and dynamic behaviors are combined, the recommended content is continuously optimized by the system to adapt to the changing requirements of the users, and the user experience is improved. Through multi-channel display, personalized labels and clustering analysis, the system provides customized tourism suggestions, supports collaborative filtering and content recommendation strategies, real-time feedback and a self-optimization mechanism to improve the precision, adapts to intelligent equipment, recommends tourism contents according to environmental changes, and improves the user experience.

The invention discloses a multi-beam cooperative scheduling method and a multi-beam cooperative scheduling system for low-orbit satellite communication, which mainly solve the problems of poor beam scheduling flexibility and difficulty in adapting to time-varying requirements in a high-dynamic environment in the prior art, and the implementation scheme of the multi-beam cooperative scheduling method comprises the following steps of: collecting online user information by a low-orbit satellite through a wide beam; a hopping beam position is generated by using adaptive clustering under the constraint of channel resources; a hopping beam scheduling algorithm based on deep reinforcement learning outputs an optimal scheduling strategy according to the real-time environment variable; and optimizing a beam hopping time frame structure in each scheduling period, covering accessed users in a beam position through spot beams, and sending service data and control information to complete efficient service transmission. The method can adapt to changes of user distribution and service requirements in low-orbit satellite communication, the utilization rate of spectrum resources is improved, communication delay is reduced, the overall performance and service quality of the system in a high-dynamic environment can be enhanced, and the method can be used for dynamic beam position division, hopping beam scheduling and hopping beam resource allocation in a multi-beam low-orbit satellite communication scene.

The invention discloses a database management method and management system, and relates to the technical field of general database management, and the system comprises a user information management module, a work management module, a salary settlement module, an evaluation feedback module, an analysis prediction module, a multi-terminal integration module and a safety guarantee module. In the invention, a role-based access control permission model is constructed in a permission control layer and a module definition, and a field-level data control mechanism is implemented for three roles of a platform administrator, a customer enterprise and an employee, for example, the employee can only check a specific public field in a salary list, and sensitive fields such as a salary calculation formula are dynamically shielded; through a permission inheritance mechanism, the system automatically adds a filtering condition that employee ID = current user ID for a query request of an employee role, data isolation is ensured, a multi-dimensional data relation graph of employee-post-customer-contract is constructed, and a dynamic association path between entities is mapped in real time through a visual view.

The invention provides a digital certificate generation method and device, electronic equipment and a storage medium, and the method comprises the steps: receiving a certificate generation request sent by a user terminal, the certificate generation request comprises user information and an identifier of a certificate generation algorithm, and the certificate generation algorithm comprises a post quantum cryptographic algorithm and a preset national cryptographic algorithm; and generating a target mixed public key according to the post-quantum public key of the post-quantum cryptographic algorithm and a national cryptographic public key of a preset national cryptographic algorithm, generating a target digital certificate according to the user information and the target mixed public key, and sending the target digital certificate to the user terminal. The digital certificate is generated based on the post-quantum cryptographic algorithm and the national cryptographic algorithm, so that communication security can be ensured, quantum attacks are resisted, and certificate generation at an unconditional security level is realized.

The invention relates to the technical field of neuromuscular electrical stimulation, and provides a multi-modal feedback self-adaptive adjustment neuromuscular regulation and control treatment system, which comprises wearable working equipment for outputting pulse electric signals to adjust nerves and muscles to form movement or adjustment feeling, electromyographic signals, motion data and user feeling input are collected to conduct feedback adjustment on output parameters of the output pulse electric signals; the handheld control equipment is used for being connected with the wearable working equipment and controlling the output working mode and the working state of the wearable working equipment; and the server-side equipment is used for managing user information and preference of the handheld control equipment, setting function authority of the handheld control equipment, acquiring data acquired by the wearable working equipment, and realizing self-adaptive output of output parameters of the pulse electric signals of the wearable working equipment based on a self-adaptive reinforcement learning algorithm. Adaptive optimization of millisecond-level dynamic electrical stimulation parameters is realized through a multi-modal feedback data fusion technology in combination with a layered reinforcement learning architecture.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a product decision optimization method, device, equipment and medium based on a knowledge graph. And generating a user feature portrait in combination with the user related information, taking the user feature portrait and the information in the knowledge graph as an input state, taking the product information set as an action space, training and generating a decision model based on a preset incentive mechanism, outputting a target item by using the decision model, and updating the knowledge graph and the decision model based on user feedback information. The comprehensiveness of an input state is improved through a fusion modeling mode containing user information, product information and environment information, a dynamic updating mechanism is constructed in combination with a knowledge graph and user feedback, a decision model is driven to be continuously optimized, and then the pertinence of a recommendation result and the self-adaptive capacity of a system are improved.

The invention discloses a virtuality and reality combined display system of a universe museum, and relates to the field of universe technology and museum display technology, the system comprises a data acquisition module, a data analysis and user portrait module, a personalized guide planning module, a virtuality and reality combined display module and a feedback and optimization module; according to the system, user information and cultural relic data are comprehensively and meticulously collected through the data acquisition module, a basis is provided for subsequent personalized display and guide planning, and the data analysis and user portrait module digs potential demands and interests of users, so that displayed contents can accurately match preferences of the users, and the user experience is improved. The virtual-reality combined display module constructs a virtual cultural relic model by using a 3D modeling and rendering technology, realizes seamless joint with an entity exhibit through an AR technology, brings immersive visiting experience to the user, and in addition, due to the existence of the feedback and optimization module, the system can continuously collect user feedback, so that the user experience is improved. And display contents and functions are continuously optimized and perfected.

The invention relates to the technical field of semantic analysis, can be applied to business scenes of financial science and technology, medical health and the like, and discloses an intention analysis and strategy generation method, device, equipment and medium, and the method comprises the steps: obtaining interaction data, recognizing an interaction type according to metadata features, selecting a corresponding analysis model to analyze and process data, and generating a text corpus; current user information is extracted from the text corpus, user intention score analysis is executed based on an intention analysis strategy corresponding to the interaction type, and a current user intention score is generated; and generating a demand list according to the user information, the intention score and the interaction type, and generating and outputting an interaction strategy based on the user information and the demand list. Through interaction data processing and automatic intention scoring analysis, the demand list and the interaction strategy of the customer can be quickly and accurately generated, the customer information processing efficiency and accuracy are improved, the workload of manual input and analysis is reduced, and the customer service quality and the response speed are improved.

The invention relates to the technical field of task matching, and provides a task matching method based on user information and task characteristics, which comprises the following steps: step 1, collecting and analyzing user information which comprises but is not limited to employment information, skilled direction, experience and price; 2, analyzing task information, wherein the task information comprises but is not limited to basic information and additional information; the basic information collection includes but is not limited to task titles, task description, task categories, budget ranges, time requirements, task importance and geographic position requirements; 3, establishing a multi-dimensional matching model, and mapping the user information and the task features; step 4, optimizing and sequencing matching results by utilizing a machine learning algorithm; and 5, dynamically adjusting the matching weight, and continuously improving the matching precision according to historical data. According to the task matching method based on the user information and the task features, the task allocation efficiency and stability are improved, and personalized task recommendation is provided.

This disclosure describes a speech-to-video system that automatically generates enhanced short-form videos from speech. For example, the speech-to-video system utilizes different speech processing models to analyze speech in audio input and determine contextual features. Additionally, the speech-to-video system utilizes various video generation models to create enhanced short-form videos using text summaries, audio contexts, user information, video parameter inputs, and / or other user contexts. In some cases, the speech-to-video system leverages components of a mobile core network to efficiently generate and deliver these features to mobile devices.

The invention discloses a user information management method and system based on application information, and relates to the technical field of user information management, and the method comprises the steps: obtaining user information through an application program, generating a unique distributed identity label, and carrying out the multi-stage verification of the user identity through an edge calculation node and a distributed node network; user behaviors are analyzed in real time through a fuzzy logic algorithm, the priority of user data is adjusted according to an analysis result, and the data access permission is dynamically allocated. According to the method, the unique distributed identity label is generated, multi-level verification is carried out in combination with the edge computing node and the distributed node network, the identity verification efficiency and safety are remarkably improved, user behaviors are analyzed in real time through the fuzzy logic algorithm, the data priority is dynamically adjusted, the access authority is allocated, and the user experience is improved. The efficient management of resources is realized, and the flexibility of authority management and the user experience are improved.

A charging station information providing server receives a charging station recommendation request from an external device, generates, in response to the received charging station recommendation request, a charging station recommendation query based on user information and vehicle information corresponding to a user of the external device, obtains customized recommended charging station information based on charging station list information obtained by using a charging station evaluation model, and road condition information, by using a charging station recommendation model that takes the generated charging station recommendation query as input, and transmits the obtained customized recommended charging station information to the external device.

Disclosed are systems, apparatuses, processes, and computer-readable media for authentication. For instance, a process can include receiving first authentication information for a user; generating an authentication token based on the received first authentication information, wherein the authentication token does not include the first authentication information; receiving user information for the user; obtaining an anonymous identifier token, wherein the anonymous identifier token comprises a composite token, and wherein the anonymous identifier token includes an identity token generated based on the received user information; adding the authentication token to the anonymous identifier token; and storing the anonymous identifier token for authenticating a user.

An embodiment includes a method to increase the efficiency of security checkpoint operations. A security checkpoint kiosk serves as a Relying Party System (RPS). The RPS establishes a secure local connection between the RPS and a User Mobile-Identification-Credential Device (UMD). The RPS sends a user information request to the UMD, via the secure local connection, seeking release of user information associated with a Mobile Identification Credential (MIC). The RPS obtains authentication of the user information received in response to the user information request. The RPS retrieves user travel information based on the user information. The RPS determines that the user travel information matches the user information. When the user travel information matches the user information, the RPS approves the user to proceed past the security checkpoint kiosk.

The invention discloses a network information security verification management system and method based on artificial intelligence, and relates to the technical field of artificial intelligence data management, and the method comprises the following steps: collecting network flow data and user behavior data, constructing a user behavior mode model through employing a machine learning algorithm, and calculating the abnormal degree of a user network behavior; calculating a safety coefficient through the abnormal degree quantized value of the user network behavior, comparing the safety coefficient with a preset threshold range, and judging a risk level of the user network behavior; marking user information with security threats, and counting network traffic fluctuation amplitude and user abnormal operation frequency; by means of the network information security verification management method and system, network information security verification management is achieved.

To generate attractive commodity development information by merging image information that is visual and linguistic information that shows appeal in a well-balanced manner while simultaneously satisfying the need to broaden commodity ideas and arm them with data in a commodity development process.SOLUTION: In a commodity development support system in which a data terminal and a server device 1 communicate via a network 21, the server device 1 includes: a language information generation function that generates a commodity development concept using a language generation AI service based on commodity concept parameters, commodity development resources, and specific user information acquired via an AI platform 1A; and an image information generation function that generates a commodity image reflecting the commodity development concept using an image generation AI service based on the commodity concept parameters, the commodity development resources, and the specific user information.SELECTED DRAWING: Figure 1

The invention relates to the technical field of television image communication, in particular to a user information input method and system in an intelligent television all-in-one machine. The method comprises the following steps: collecting a user image, carrying out white balance correction and focusing processing, generating a moving object focusing image, carrying out identification and attention tendency analysis on a character in the focusing image, obtaining character tendency data, analyzing a historical interaction image, identifying an interaction mode and constructing a user intention prediction model, and obtaining a user intention prediction result. And when the tendency data shows that the user preferences the television content, intention drilling and auxiliary adjustment are performed on the current image based on the prediction model, predicted user input information is generated, logic conflicts in the predicted information are detected, feedback optimization is performed, and final user input information is output. According to the invention, a more accurate and more flexible user information input method is realized.

The invention discloses a cross-application unified identity authentication system, method and server based on the wide gap, the system comprises a plurality of applications running to the wide gap system, a unified identity authentication module is integrated in the applications, and the unified identity authentication module comprises an authentication processing module, a token management module and a user information database, the server is used for calling an authentication interface for verification, generating a unique user identity identifier and recording a plurality of applications associated with a user; the token management module is used for generating tokens and managing the tokens according to the user identity identifiers and the associated applications, performing token verification when token verification requests of a plurality of applications are received, and logging in after the verification is passed; and the user information database is used for storing the basic information of the user, the associated information of the user and the application and the security audit log. According to the system, the security, convenience and cross-platform property of identity authentication can be improved, and safer and more efficient identity authentication service is provided for users.