360 results about "User - individual" patented technology

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 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.

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.

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 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 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 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 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 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 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.

The invention discloses a physiotherapy couch physiotherapy strategy management method based on user physiological data, and relates to the technical field of physiotherapy management, and the method comprises the steps: based on the collection operation of user personal information before physiotherapy, collecting the user physiological data in real time through a sensor, and then analyzing the collected data to generate an optimized adjustment strategy. According to the physiotherapy couch physiotherapy strategy management method based on the user physiological data, preliminary strategy adjustment operation meeting user requirements is completed by achieving screening and extraction operation on the collected data, and an optimized adjustment strategy is determined by combining the collected real-time data with a threshold value evaluation algorithm; re-evaluation of the user condition is completed within a time threshold after strategy adjustment response, reciprocating operation is carried out, a final physiotherapy strategy is obtained, a personalized physiotherapy strategy is generated for the user, physiotherapy strategy optimization is carried out according to physiological data of the user in the physiotherapy process, safety and effectiveness of the physiotherapy process are ensured, and the user experience is improved. And the comfort level for physical therapy is effectively improved.

Methods for product recommendation are provided. This includes collecting personal user data including profession, gender, size, preferences, user's apparel size, user's address, who the user's friend are, user's friends' information, users' medical records including eyeglass and contact lens prescription information; collecting vendor data including product size, product description, product location, price; and recommending vendor products that best match the users' personal data.

The invention discloses an intelligent medical service system based on large language model oneself. The system comprises a user information acquisition module; an intelligent recommendation engine; a data analysis and evaluation module; an intelligent algorithm and a big data analysis technology are applied, matched medical resources, treatment schemes or doctors are intelligently recommended according to information provided by a user, through an optimization and feedback mechanism, in the fields of common disease diagnosis and chronic disease management, the diagnosis accuracy can reach 85% or above, and the diagnosis accuracy can reach 85% or above. Personalized health management plans and medical consultation suggestions are customized according to personal information of users, recommendation results are updated and optimized in real time through machine learning and data mining, individuation and precision of services are ensured, a system technical architecture supports self-learning and self-adaption, and by accumulating user feedback and historical data, the health management plan and the medical consultation suggestions are made to be more intelligent. A medical recommendation engine and user experience are continuously optimized, the intelligent level of the platform is gradually improved along with the increase of the number of users, and more accurate and efficient medical recommendation is realized.

QR codes or the like are used in hardlink applications, by which different users may receive different information in response to a user's interaction with a touchpoint. The content delivered to a particular user in response to a hardlink code or a presented hyperlink may be dependent on the time of the scan, the geographic location of the user, a weather condition at the geographical location, personal information associated with the user, a number of previous scans of the code by prior individuals, and any combination of the these or other variables, which may be determined by an originator of the QR code or other party. User devices may be re-directed to alternate content or network addresses based on one or more programmed conditions.

To provide an information processing system, an information processing device, a program and an information processing method, which enable efficient generation of any document.SOLUTION: An information processing system executes: personal information reception processing for receiving input of personal information of a user associated with a commodity or service to be provided to the user; and proposal document generation processing for autonomously generating a proposal document to propose the commodity or service to the user based on the personal information received in the personal information reception processing.SELECTED DRAWING: Figure 1

The invention provides an attention mechanism and LSTM-based automobile brand recommendation method and system, and relates to the technical field of data processing. Comprising the following steps: inputting user comment data into an emotion analysis model, and processing the user comment data through an LSTM layer and an attention layer in the emotion analysis model to obtain predicted emotion scores of a user on multiple aspects; according to the predicted emotion score, respectively obtaining an importance score of each aspect, an emotion demand score of each aspect and an overall feature vector of the automobile, and further obtaining a preference degree of the user in each aspect; and obtaining a recommended automobile brand according to the preference degree of the user, the overall feature vector of the automobile and the random forest classifier. The LSTM layer and the attention layer in the sentiment analysis model process the user comment data, deeper text understanding is provided, and the number of the needed user comment data is reduced. The relevance between the personal preference of the user and the multiple feature dimensions of the automobile brand is established, and the recommendation accuracy is improved.

A computer system for determining personalized loss event valuations is provided. The computer system includes one processor in communication with at least one memory device, and the at least one processor is programmed to: (i) receive user data from the user computer device, wherein the user data include data related to a user's personal information and personal property, (ii) utilize a trained machine learning model to determine a first loss valuation associated with a first loss event based at least in part upon the user data, (iii) utilize the trained machine learning model to determine a second loss valuation associated with a second loss event based at least in part upon the user data, wherein the first loss event and the second loss event are different loss events, and / or (iv) generate a loss event policy that includes the first loss valuation and the second loss valuation.

The invention discloses a user power consumption behavior prediction method based on big data aggregation analysis, and particularly relates to the technical field of power data processing. The method comprises the following steps: constructing a user power consumption behavior matrix by collecting multi-dimensional historical power consumption data of a user; fusing environmental factors such as air temperature, humidity and weather types to generate an enhanced feature map; extracting key behavior nodes of a user through a multi-scale graph convolutional network, and introducing a time attention mechanism to generate a time sensitive weight vector; generating a user individual prediction feature vector in combination with the behavior node and the time weight, and outputting a future power consumption behavior prediction sequence; when the predicted volatility exceeds a set threshold value, model reconstruction and weight updating are triggered; if the volatility is within a threshold value, behavior category identification and prediction result output are completed; the method improves the accuracy and stability of user behavior prediction, has the advantages of being high in period recognition capability, sensitive in fluctuation response and high in adaptive adjustment capability, and is suitable for intelligent power grid load management.

The invention discloses an e-commerce platform cross-channel data fusion and analysis optimization method. User behavior data, transaction data, commodity data and market information are collected in real time from multiple channels (such as official websites, mobile applications, social media and offline stores); performing standardization processing, abnormal value detection and missing value completion on the acquired data, and expanding small sample data by using a data enhancement technology to improve data quality; and encrypting the sensitive data. Through a self-attention mechanism and a deep learning method, correlation and features among different channel data can be accurately captured, so that a more comprehensive and efficient user portrait is generated. The analysis result after data fusion is more accurate, a reliable basis can be provided for platform decision making, the differential privacy technology and the encryption protocol are adopted, and the safety of user personal information and sensitive data is effectively guaranteed. The user trust of the platform can be improved, and the legal compliance of the platform in multiple regions can be ensured.

The invention provides an emotion recognition method and device, and relates to the technical field of emotion recognition. Performing multi-modal feature extraction according to the emotion perception data of the user, determining character features of the user, covering multi-dimensional state information of the user and tracking character changes of the user in real time; the attention weight of each feature item in each single-mode feature and the weight of each single-mode feature are calculated in sequence by taking the character features of the user as guidance, multi-mode fusion features of character perception strongly related to the character of the user are generated, and an emotion recognition result is obtained through an emotion recognition model. The technical problem that the emotion recognition accuracy is limited due to the fact that an emotion recognition method in the prior art only depends on single-modal features or simple multi-modal fusion and ignores individual character differences of users is solved, deep fusion of comprehensive representation of user states and character features of the users is achieved, and the emotion recognition accuracy is improved. And the emotion recognition accuracy and the individual suitability are improved.

Described are systems and methods for providing virtual and remote access to virtual content in a virtual safebox. A computer system includes a virtual vault database for storing a plurality of virtual safeboxes storing digital / virtual content provided by a user. The stored content includes image content representing personal identification documents of the user. The computing device includes at least one processor configured to receive an access request message from a first safebox access computing device and, in response retrieve, from the virtual vault database, the first virtual safebox. The processor is further configured to generate an inventory list identifying each content item and transmit an inventory message to the first safebox access computing device. The processor is further configured to receive a content retrieval message from the first safebox access computing device and transmit a content message to the first safebox access computing device.

The application discloses an end-to-end communication record synchronization method and system, relates to the technical field of communication, and saves user personal communication record data in a private device, satisfies the convenient and safe use of the user in multiple terminals, and thus guarantees that the personal communication record data can be recovered, synchronized, conveniently saved and found, and accessed and used by the user at any time and in any place. The data of the user communication record does not need to be saved in a platform, is completely stored in the private device, and finally realizes the functions of the synchronization, recovery and storage of the user communication record data in multiple terminals, avoids data leakage to a larger extent compared with previous methods, guarantees the safety of the data, and realizes the convenient personal data management.