460 results about "User - individual" patented technology

Methods, systems, and techniques for processing natural language queries. A natural language query related to personal information of the user is obtained. Query vectors that include embeddings of the query are generated and matched with document vectors generated from chunks of reference documents related to the personal data. The document chunks are retrieved from a database and used as context for a prompt to a large language model that is used to respond to the natural language query. The query itself is also included in the prompt. The query may be in respect of a particular goal, and the large language model's response may include recommendations to help the user achieve that goal.

The invention relates to the technical field of data processing, and provides a social network privacy data protection method and system, and the method comprises the steps: obtaining to-be-encrypted privacy data, and obtaining a keyword popularity coefficient and a sensitivity weight coefficient according to the privacy data; acquiring behavior characteristics and basic information of a user group, and acquiring a group portrait index according to the behavior characteristics and the basic information; acquiring network behavior activeness, equipment characteristics and historical behavior information of the target user, and acquiring personal characteristics of the target user according to the network behavior activeness, the equipment characteristics and the historical behavior information; according to the keyword popularity coefficient, the sensitivity weight coefficient, the group portrait index and the personal characteristics of the target user, obtaining the encryption level of the privacy data; and calling different encryption algorithms to encrypt the privacy data according to the encryption level. According to the method, different encryption algorithms are called for encryption for the privacy data of different encryption levels, and the dynamic adaptability of encryption protection of the privacy data of the social network is improved.

The invention discloses a mild cognitive impairment brain rehabilitation training device and system in the technical field of cognitive nerve rehabilitation, and the device comprises a multi-modal data fusion module, a personalized training task generation module, a multi-sensory stimulation presentation module and a real-time adaptive regulation and control module. And the personalized training task generation module is used for dynamically generating a personalized narrative training task fusing the user interest theme and the cognitive training target by utilizing a reinforcement learning algorithm based on the user cognitive weak domain evaluation result and the user personal interest and life narrative content obtained through natural language processing. Clinical data of a patient and real-time electroencephalogram and behavior data are fused, a narrative training task deeply fused with life experience and interest of the patient is dynamically generated, the difficulty of the training task is automatically adjusted according to real-time physiological indexes, meanwhile, seamless connection with a medical system is achieved through digital biomarkers, and the training efficiency is improved. And the precision and compliance of rehabilitation training are obviously improved.

The invention relates to the technical field of intelligent control, in particular to an air conditioner control system and method based on a smart home. The air conditioning module is used for refrigerating or heating air; the image acquisition module is used for acquiring an image of a user smart home environment and defining the image as a first image; the analysis module is used for judging whether a user exists in the first image or not, identifying the identity, position and behavior of the user, retrieving a personal data packet of the user based on an analysis result, and outputting a control signal; the temperature adjusting module is used for adjusting the air supply temperature and speed of each air supply outlet; the wind direction adjusting module is used for adjusting wind directions of the air supply outlets. The operation parameters of each air supply outlet of the air conditioner are automatically adjusted based on the corresponding personal information database by recognizing the feature information such as the identity, the position and the behavior of the user, so that corresponding operation control is performed when different users are in different areas and different states, and the user experience is improved. And the air supply parameters of the air conditioner blown to the user are more suitable for the personalized requirements of the user in the current state.

The present invention relates to a personalized definition system and method for digital personal business cards, which is used for a server and a front-end application software that interacts with the server, wherein the server includes: a business card information configuration module, a multi-style management module, a back-end real-time update module, and a data interface module, and the front-end application software includes: a business card information display module and a multi-style selection and rendering module. This application can flexibly configure the user's personal details information and personal business card style templates through the server according to the different needs of the administrator, thereby avoiding the troublesome operation of code modification every time the display content is modified, thereby improving the flexibility of system development; based on the real-time information update and application synchronization mechanism, the latest personal business card template information and user personal details information can be obtained in real time by re-logining or manually refreshing the front-end application software, thereby reducing the situation of stopping and restarting the server and version updating, and improving the fluency of the personal digital business card update experience.

The invention relates to a data analysis technology, and discloses a personalized commodity recommendation method and system based on multi-modal data fusion, and the method comprises the steps: recognizing registration data in account data of a user and personal information of the user, and judging whether the user is a new user or not according to the registration data; if the user is a new user, generating a random commodity list based on the personal information of the user, obtaining browsing data of the user on the random commodity list, generating a first recommended commodity according to the browsing data, and displaying the first recommended commodity to the user; otherwise, generating a second recommended commodity according to the historical purchase data of the user, identifying multi-dimensional score data of a plurality of suppliers corresponding to the second recommended commodity, generating a multi-dimensional score weight of the multi-dimensional score data according to the historical evaluation data of the user, generating a comprehensive score of each supplier according to the multi-dimensional score weight and the multi-dimensional score data, and confirming the highest-score supplier according to the comprehensive score, and recommending a second recommended commodity of the highest-score supplier to the user. The commodity recommendation accuracy can be improved.

Systems and methods for improving cellular handover performance are provided. A user individual offset parameter (UIO) is provided which may modify a measured signal strength parameter for a particular user equipment, improving handover performance. The UIO may be calculated and optimized such that one or more key performance indicators including signal to interference and noise ratio, handover success rate, and signaling overhead are maximized. A base station may compute or retrieve the value of a UIO for a particular user equipment, and adjust a measured signal strength and quality metric using the UIO. The UIO may be calculated either by the user equipment, the base station, or the core network.

A computer-implemented method includes: receiving a signed challenge from a public key authenticator of a mobile device registered to a financial account of a user; receiving a transaction request and transaction data associated with the signed challenge; determining that the public key authenticator satisfies a basic integrity requirement; receiving stopgap authenticator data including device security data and one or more of the following: a user personal identifier, a user personal credential, transaction history data of the user, and behavioral biometrics data generated at the user mobile device; comparing the stopgap authenticator data to a hidden profile for the financial account to determine that a matching threshold is satisfied; based on the satisfaction of the matching threshold and of the basic integrity requirement, generating a stopgap authenticator token; and transmitting the stopgap authenticator token and the transaction data for real-time transaction approval.

A method for providing a personalized shopping experience using an AI-guided omnichannel shopping application is provided. The method includes presenting a user app interface on a user device associated with a user to receive user data comprising user styling preferences, shopping habits, and images of the user's personal wardrobe inventory. The method also includes providing a virtual closet for the user, wherein the virtual closet comprises processed images of the personal wardrobe inventory of the user. The method further includes providing a personalized product feed source by filtering product data. The method additionally includes providing a personal stylist interface that allows stylists to access the virtual closet of the user. The method includes analyzing using an AI model, the user preferences and shopping habits, sales history, browsing history, and the selected items, wherein the AI model continuously learns and generating personalized product recommendations to the user.

The invention belongs to the technical field of computer server management, and particularly discloses a laboratory collaborative environment-oriented user and data full-life-cycle server management system, which comprises a container virtualization layer, a server management layer and a server management layer, dynamic resource allocation is supported through a state saving-resource reallocation-environment recovery mechanism; the heterogeneous transaction coordination layer adopts a Saga transaction mode to coordinate a heterogeneous system so as to realize cross-system transaction consistency; the data collaboration ecological layer establishes typed management of a personal data volume, a shared software environment volume and a public data set volume, and supports software environment encapsulation sharing and versioning management; and the metadata management layer realizes real-time update and high-performance query of metadata based on a Redis hot update architecture. According to the method, the problems of inflexible resource allocation, incomplete environment isolation, dilemma in authority management and difficulty in data collaboration and recovery in the prior art are solved.

This invention discloses a method and apparatus for protecting personal information security, belonging to the field of personal information security protection technology. The method includes: verifying the identity information of the information collector and determining whether the information collector has the necessary authorization based on the identity information; verifying the compliance of the collection request through a compliance check algorithm, and requesting authorization from the user after successful verification; encrypting the data in the data card using a data card encryption algorithm, and decrypting and connecting the data by an encryption center after the user authorizes access; monitoring the information collector's collection behavior in real time, and immediately issuing a warning to the user and terminating the collection behavior if abnormal collection behavior is detected; and regularly updating the compliance check algorithm and the data card encryption algorithm. This automatically identifies and verifies the legitimacy of the data collector, while strengthening the protection barrier for the user's data card, thereby improving the security and privacy of the user's personal information.

The invention discloses a user state evaluation method and system based on heart rate characteristics, and relates to the technical field of data analysis, and the method comprises the steps: collecting heart rate time sequence data; performing phase-space reconstruction on the heart rate time series data, and extracting chaotic attractor features representing heart rate complex dynamic characteristics; constructing a heart rate dynamic graph according to the chaotic attractor features, and performing feature aggregation on the dynamic graph by using a graph convolutional network to obtain global topological dynamic features; inputting the global topology dynamic feature, the attention mechanism and the user individual baseline feature into a pre-trained neural network, and outputting an intermediate state value reflecting the current state of the user; and performing adaptive state adjustment on the intermediate state value to generate a final state evaluation result. The method not only improves the precision and robustness of state evaluation, but also provides scientific and reliable technical support for intelligent health management and risk early warning.

The invention discloses an application (App) and method capable of intelligently memorizing words, which can generate a personalized memory scene by acquiring personal interests and hobbies of a user, dynamically optimize an individual forgetting curve based on machine learning, and further refine optimal learning or review time according to a personal emotion curve. The system supports multi-language and multi-device adaptation, and comprises a personal interest scene generation module for constructing a personalized learning scene and generating example sentences and multimedia contents associated with interests by using natural language processing (NLP); a dynamic forgetting curve module; a two-stage modeling mechanism is adopted, and a fine-grained word-level review strategy is generated in combination with a group forgetting rule and user real-time test data; an emotion curve and a forgetting curve are combined, and review time is optimized through a double-layer algorithm; the multi-mode reward module is linked with the psychological health service platform through a point exchange mechanism; and the psychological consultation service is linked for the users with poor word reciting scores.

The invention relates to a diabetes exercise rehabilitation guidance system, relates to the technical field of diabetes rehabilitation, and aims to provide a personalized and scientific exercise management scheme for diabetics. The system comprises a user individual feature data acquisition module, an evaluation and classification module, an exercise scheme generation module, a real-time monitoring module and a feedback and adjustment module. By collecting the physiological parameters of the user in real time, the system automatically analyzes the health condition of the user and classifies the user into low-risk, medium-risk and high-risk exercise crowds. Based on a classification result, the system uses a machine learning algorithm to generate a personalized exercise scheme, and the safety of the exercise process is ensured through dynamic monitoring. The real-time monitoring module of the system can monitor the physiological data of the user in the exercise process and give an alarm in time when an abnormality is found. Through connection with an information system of a medical institution, the system also supports a remote medical function, so that doctors can check health data of patients in real time and provide professional guidance.

Techniques are provided for machine learning-based educational content adaptation based on user personal characteristics. One method comprises obtaining personal characteristics of at least one user; applying the personal characteristics of the at least one user to at least one machine learning model to automatically adapt at least one educational content item for the at least one user using one or more of the applied personal characteristics of the at least one user; and initiating a provision of the at least one automatically adapted educational content item to the at least one user. Technology-related characteristics of the at least one user may also be applied to the at least one machine learning model to further adapt the at least one educational content item for the at least one user using the applied technology-related characteristics.

To respond to a user with rich content.SOLUTION: An automatic response apparatus is configured to cooperate with a service providing apparatus that provides a service via a network and a terminal device of a user, to automatically respond to a message with a natural sentence from the user, the automatic response apparatus including: a request parameter acquisition unit which acquires a request parameter to be input to a response model by inputting at least the message to an AI chatbot trained so as to make a response on receipt of a natural sentence; a response content acquisition unit which acquires content of a response to the user by inputting the acquired request parameter and personal information of the user related to the service to the response model; and a reply unit which transmits the acquired content of the response to the user to the terminal device.SELECTED DRAWING: Figure 7

The invention provides a campus internal and external quality education resource collaborative configuration method based on big data analysis, and relates to the technical field of big data analysis, and the method comprises the steps: building a resource library based on an internal resource set and an external resource set; collecting user group feature information of the student user group; screening a plurality of resources with annotation information in cooperation with the user individual features and the education demand features; calling a resource evaluation mechanism to carry out fitness evaluation analysis on the target candidate resource set, and generating a target candidate resource list; and carrying out resource collaborative configuration of the student user group. Through the method and the device, the technical problem of resource mismatching or waste caused by lack of understanding and dynamic adaptability to user personalized demands in the prior art can be solved, intelligent screening and efficient configuration of quality-oriented educational resources are realized by cooperating user individual features and educational demand features and combining big data analysis, and the user experience is improved. And the accuracy of resource configuration is improved.

The invention discloses a natural interaction virtual scene generation system and method, and relates to the technical field of data processing, and the system comprises an initial preference setting module, a virtual scene configuration module, a sensing data acquisition module, an interaction instruction processing module and an interaction instruction feedback module. According to the method, the initial preference interaction data of the user and the personal body shape data of the user are collected in advance, the personalized behavior preset parameters of the interaction instructions of the user are generated through analysis and processing, and the personalized virtual scene is configured, so that personal habits and body characteristics of the user can be better matched, interaction in the virtual environment is more natural and comfortable, and the user experience is improved. And meanwhile, the identification accuracy of the interaction instruction of the user is improved.

The invention discloses a healthy diet knowledge accurate retrieval engine based on a large language model. The healthy diet knowledge accurate retrieval engine comprises a user interface module, a natural language understanding module, a healthy diet knowledge base module, an accurate retrieval module, a personalized suggestion module and a feedback learning module. The engine receives healthy diet related problems through a user interface, performs natural language understanding by using a large language model, and extracts user intentions and key information. And then, related data is accurately retrieved from the healthy diet knowledge base, and personalized diet suggestions are generated in combination with the personal health information of the user. The engine also has a feedback learning function, collects user feedback and optimizes the processing logic of each module. According to the method, intelligent retrieval and personalized recommendation of healthy diet knowledge are realized, the efficiency of acquiring accurate and practical healthy diet information by the user is improved, and the user is helped to formulate and execute a more scientific and reasonable diet plan, so that the formation of a healthy lifestyle is promoted, and long-term reliable healthy diet guidance service is provided for the user.

The invention discloses an automatic auditing method for a housing accumulation fund mobile terminal extraction application, and the method relates to the field of automatic auditing, and comprises the steps: obtaining the personal information of a user according to the housing accumulation fund extraction application submitted by the user, and verifying the identity of the user through employing a dynamic biological information verification technology; a cross-institution federated learning framework is introduced, a verification model is constructed in combination with multi-party data sources, and multi-dimensional cross verification is performed on user identity information; feature information in the verified user personal information is compared with preset standard feature information; deploying an auditing decision engine, performing risk behavior auditing on the user feature information, and returning auditing suggestions; auditing suggestions are pushed to the user in real time through a mobile terminal service page, a user personal information supplement list is automatically generated for applications needing material supplement or rejection, and the auditing progress is monitored in real time; a block chain technology is applied, and key data of each time of housing public accumulation fund mobile terminal extraction application and user data verification is subjected to uplink storage.

The invention provides a social network user viewpoint classification method and device, computing equipment and a storage medium. The method comprises the following steps: firstly, acquiring social network data including structured data and unstructured data; the unstructured data comprises a user personal description text, a user interaction text and a user interaction relationship; a social network edge text graph structure is constructed according to the obtained social network data, the structured data and the user personal description text serve as node attributes, and the user interaction text serves as edge connection attributes; reasoning a text topic of the whole network by utilizing a large language model according to text attributes on the connecting edges; combining the text topic, the text attribute of the node and the text attribute of the associated edge, and obtaining a node semantic vector by utilizing a large language model; extracting a node feature vector based on feature engineering, and splicing the node feature vector with the node semantic vector to obtain a node representation vector; and the node representation vectors are input into the graph attention network, user viewpoint classification is carried out, and the viewpoint classification accuracy is improved.

The invention discloses an information security protection system for a smart home, and relates to the technical field of smart home information security. A plurality of pieces of privacy data in obtained personal information of a user are segmented through a slicing unit and are divided into a plurality of privacy data segments; each privacy data segment corresponds to a real-time mapping numerical value which is analyzed in real time according to the personal characteristics of the user, and the real-time mapping numerical value is formed by combining a plurality of element numerical values which are sequenced according to a rule, so that a mapping relation formed by the privacy data segments of the user and the real-time mapping numerical values is obtained; according to the method, the mapping relation of the user is uploaded to the fragment mapping table of the manufacturer server by means of the uploading unit, so that only corresponding fragment type privacy data can be stored in the manufacturer server, each piece of data is stored in the server section by section, and the personal privacy cannot be acquired even if the data is leaked.

The invention belongs to the technical field of education assistance, and discloses an AI interaction method and system for instantly generating a composition writing thought. Comprising the steps of collecting writing task related input data of a user and performing data cleaning to obtain optimized writing task input data; executing structured semantic analysis on the optimized writing task input data to obtain a composition task intention data set; performing cognitive degree matching on the composition task intention data set based on the personal data of the user, and outputting an adaptive composition writing thought of the user; performing emotional rhythm promotion on the composition writing thought adapted to the user to generate an emotional visual composition writing thought; semantic embedding is carried out on the emotion visualization composition writing thought and newly-added writing requirements of the user, and a complete composition writing thought is obtained; performing feedback evaluation on the complete composition writing thought, and sending an evaluation result and the complete composition writing thought to a preset user terminal; and the writing thought generation efficiency and quality are obviously improved.

The invention relates to a data processing method for self-service borrowing service of a library. Constructing a personal behavior portrait of the user by using the historical borrowing record, borrowing duration, borrowing category and behavior characteristics including borrowing frequency and preference type of the user; historical data of user behaviors are analyzed through a time series data analysis technology, a user borrowing preference mode is mined, and periodic and seasonal changes are captured; fusing the historical borrowing data with spatio-temporal information including borrowing peak time periods and borrowing demand differences of different areas in a library, and constructing a multi-dimensional spatio-temporal data model; a multi-objective optimization algorithm is adopted, and dynamic resource allocation is carried out on the premise that the borrowing requirement is met; according to the real-time data of the borrowing system, the storage positions of the books are adjusted, the books are dynamically scheduled through the self-service borrowing terminal, and the load balance of each borrowing point of the library or the self-service borrowing machine is controlled; and modes in the borrowing history of the user are deeply analyzed.

The invention discloses a federated learning-based service deployment method and system, and relates to the field of edge computing service deployment, and the method comprises the steps: obtaining the personal information and service interaction data of a user, and carrying out the clustering of the user through a clustering algorithm, and obtaining a class cluster set; obtaining available edge servers in each class cluster, designing a plurality of objective functions through constraint conditions of the edge servers, solving an optimal solution of the plurality of objective functions by using a non-dominated sorting genetic algorithm, and searching for the edge cloud servers in each class cluster; obtaining a global federated prediction model through federated learning based on the deployed local prediction model; and on the basis of the available edge server in each class cluster, predicting the service request quantity of each class cluster at the future moment by using a global federation prediction model, and deploying the service with the popular increment into the available edge server. According to the invention, the service deployment efficiency is improved, the resource utilization is optimized, the communication overhead is reduced, the privacy security is guaranteed, and the user experience is enhanced.

The invention relates to the technical field of smart televisions, and particularly provides a smart television personalized content recommendation method, system and device and a storage medium, and the method comprises the steps: obtaining user basic data and behavior record data, the user basic data comprising user personal information and device information; extracting browsing content and browsing time from the behavior record data, and setting the browsing time as interestingness of the browsing content; analyzing the feature tag combination of the browsed content, and based on the feature tag combination of the browsed content and the corresponding interestingness, counting a core feature tag with the highest interestingness; video resources associated with the core feature tags serve as candidate resources, and priorities are divided for the candidate resources based on user basic data; and arranging the candidate resources from first to second according to the priority, and pushing the candidate resources according to the arrangement sequence. According to the invention, the recommendation accuracy and the user experience are improved.

The invention discloses an intelligent sleep environment adaptation method and system based on personal parameters of a user. The method comprises the steps that the personal parameters of the user and real-time monitoring data are acquired; substituting the acquired personal parameters of the user and the real-time monitoring data into a pressure calculation model to calculate an expected pressure value of each sampling contact point; substituting the acquired personal parameters of the user and the real-time monitoring data into a joint angle model to calculate an expected joint angle; substituting the calculated expected pressure value and the expected joint angle into an optimization function for optimization so as to obtain an optimal adaptive parameter; and adjusting the height of the mattress based on the optimal adaptive parameters. The method has the advantages of personalized optimization, customized design, real-time feedback and adjustment, energy consumption reduction, user friendliness and high adaptability.

The invention relates to a process for constitution of a history of personal data of a user and is carried out by a terminal of the user. The process includes a step for obtaining a symmetric encryption key associated with a profile of the user. The process includes a step for collecting personal data of the user. Throughout the collection of these personal data a step for encryption of these personal data with the symmetric encryption key of this user. Throughout the collection of these personal data a recording step, in a general database, of blocks including the encrypted data. The blocks being organised according to a blockchain constituting a sub-graph of a general graph whereof the topology is defined by a preset data model. A root block of the sub-graph being associated with a dynamic non-fungible token of this user.

The invention discloses a training task combination recommendation method based on a large language model. The method comprises the steps of firstly obtaining personal information and historical training data of a user, and sorting and selecting an initial training task combination according to a preset logic; and performing second-order knowledge expression on each task in the combination, and performing graph knowledge and structure alignment and fine tuning on the large language model by means of natural language description questions and answers to form a large language fine tuning model. Dividing the personal information of the user, the initial combination and the related knowledge expression into text and heterogeneous graph data, splicing to form fusion features, inputting the fusion features into a fine tuning model, outputting candidate task recommendation probability distribution, finally screening the candidate task with the highest recommendation probability, combining the candidate task with the initial training task to form a new combination, and pushing the new combination to the user. According to the method, multi-modal information is fused, combined retrieval is innovatively converted into task generation, auxiliary task learning, slow reasoning and progressive learning strategies are combined, the cold start problem is effectively solved, and the personalized requirements of users are met.

A system for securely storing personal information and memories of a user, such as through a software application, is disclosed. In particular, the system may utilize the application to transition the personal information and memories from cloud storage to cold storage and / or to an air-gapped data storage system. The personal information and memories of the user may be secured by the system using blockchain technology, multi-factor authentication, and / or other security technologies. The system may ensure that the information is highly secured until the user has passed and a next of kin of the user and / or other intended recipient of the user's information successfully authenticates with the system, such as by presenting a valid death certificate and / or acceptable credential. If the intended recipient of the data successfully provides a valid death certificate and / or credential, the intended recipient may be provided with access to the data associated with the user.