35 results about "Personalized communication" patented technology

The invention discloses an oral diagnosis and treatment patient service platform based on reinforcement learning, and relates to the technical field of diagnosis and treatment services, and the platform comprises a health scoring module which integrates multi-source data, generates personalized oral health scores through a dynamic weight distribution model, and displays high-risk items in combination with 3D visualization; the patient management and marketing module tracks patient behaviors, clusters and classifies the patient behaviors, generates a dynamic follow-up visit path by using multi-target reinforcement learning, and matches a precise marketing verbal skill through a knowledge graph; the in-diagnosis auxiliary module synchronizes health data of the patient to the doctor terminal in real time, detects prescription conflicts and performs early warning, and generates personalized communication verbal skills in combination with historical preferences of the patient and real-time emotion analysis; through multi-dimensional data integration and intelligent processing, the whole oral diagnosis and treatment process is optimized, the diagnosis and treatment efficiency and the patient satisfaction degree are improved, the operation cost is reduced, and remarkable innovativeness and practicability are achieved.

Systems and methods for generating customized media content are provided. Data regarding engagement with customized media content may be tracked and used to train a neural network to generate a content generation module that optimize for increased engagement by adjusting parameters (weights). A new content generation module may be generated by the trained neural network based on a selected set of content attributes and generative artificial intelligence (AI) protocols. New customized media content may thereafter be generated by using the new video content generation module to incorporate multi-modal fusion of facial expression data into video content for the new customized media content based on the selected set of content attributes, use voice matching algorithms to generate an audio track for the video content, synchronize the audio track to the video content, and integrate one or more of the selected set of content attributes into the new customized media content.

An example digital therapy platform is disclosed that provides personalized, real-time feedback to patients during sessions. The platform collects real-time performance data during the sessions, including metrics such as range of motion, pelvic floor movements, exercise completion rates, and the accuracy of movements. The digital therapy platform may also retrieve historical data from past sessions to provide a comprehensive overview of the patient's context. The digital therapy platform dynamically generates structured prompts based on the analyzed data and provides these prompts to a large language model (LLM). The LLM generates personalized messages tailored to the patient's specific context. The digital therapy platform delivers the personalized messages to the patient through a user interface.

The invention discloses a personalized communication training content generation method based on big data. The method comprises the following steps: S1, constructing a multi-modal feature sequence; s2, constructing a user expression brain map; s3, performing cognitive causal alignment on the time axis of the user expression brain map; s4, identifying ambiguous expressions in user input, expanding a plurality of semantic interpretation paths, forming a semantic trajectory tree, and generating a primary semantic path and a secondary semantic path; s5, generating conventional communication content based on the primary semantic path, constructing an evolution expression path based on the secondary semantic path, generating challenging expression content, and integrating and outputting a double-track fusion training corpus; s6, identifying a negative expression fragment in the double-track fusion training corpus, and generating an evolution training sequence based on an annealing control function; and S7, performing content reconstruction on the double-track fusion training corpus based on the evolution training sequence, and generating personalized communication training content. According to the method, multi-modal modeling and a semantic evolution control method are fused, and personalized communication training content generation is realized.

The invention provides a system and method for improving business through multiple agents, and relates to the technical field of data analysis, and the system comprises a data layer and a multi-modal data layer for realizing data collection; data processing: preprocessing the data to form a customer portrait; constructing an ontology knowledge base; the vector database vectorizes customer portraits, insurance product information and communication content data; the personalized communication content generated by the application layer is stored, and the personalized communication content is pushed to a contact channel preferred by a customer through an API interface; the AI core layer is used for receiving requests transmitted by different application programs, users or systems; finely adjusting the model through the small model; various atomic energies are provided; and the application layer is used for constructing an intelligent software entity capable of perceiving an environment, making a decision and taking actions by applying a sequence, a dependency relationship and an execution logic of an arrangement definition task. Through multi-agent cooperation, automatic configuration and optimal scheduling of resources are realized, and personalized product and service recommendation is dynamically generated.

The invention discloses an intelligent psychological health education system based on an education robot. The system comprises (1) AI family-school cooperation: an improved YOLOv7 algorithm captures classroom behaviors, dynamic Gaussian blur protects privacy, directionally pushes student participation images containing desensitization IDs, supports AI to generate personalized communication verbal skills, and improves the degree of participation of parents; (2) an interdisciplinary fusion engine: constructing a knowledge graph to associate psychological courses with mathematics, sports and other subjects, predicting an optimal fusion opportunity in combination with educational administration data, and generating a double-teacher collaborative teaching plan; (3) interest and emotion driven daily penetration: analyzing student interest labels based on a latent semantic model (LFM), and triggering personalized family task pushing in combination with multi-modal emotion recognition to realize intelligent penetration of psychological health education in a family scene; and (4) full-link privacy protection: adopting differential privacy, block chain and federated learning technologies to realize'all anonymity 'and'availability and invisibility' of data, and ensuring information security through three-level desensitization and quantum encryption, so that the system meets the requirements of'personal information protection method '.

This invention discloses an assistive system for communication among people with disabilities, relating to the field of intelligent communication technology. The system includes: a signal capture and cloud upload unit, a signal filtering and verification unit, a data fusion and storage unit, a personal profile database construction unit, a personalized communication assistance database establishment unit, a mapping rule table formulation unit, and a mapping rule display unit. This invention captures communication signals from people with disabilities using sensor technology, and after cloud filtering and verification, ensures the accuracy and effectiveness of the communication signals. This greatly enhances the accessibility of communication between people with disabilities and others, enabling them to express themselves more smoothly, reducing communication barriers, and promoting barrier-free information exchange.

The invention discloses a personality self-adaption-based personalized communication scheme generation method and device, and the method comprises the steps: receiving a communication scene inputted by a user, and extracting the personality features of the user and the personality features of an interaction object; according to the personality characteristics of the user and the personality characteristics of the interaction object, a behavior disorder diagnosis report is generated in combination with a personality disorder rule base; generating a scene simulation interaction task according to the behavior disorder diagnosis report, and sending the scene simulation interaction task to the user for interaction; collecting interaction data of finishing the scene simulation interaction task by the user, and comparing the interaction data with risk points in the behavior disorder diagnosis report to obtain a comparison result; and an intervention instruction is generated according to a comparison result, and the non-adaptive behavior or psychological state glide of the user is intervened and corrected in real time according to the intervention instruction, so that a final communication scheme is generated, and the behavior change efficiency and continuous motivation of the user in multiple fields such as interpersonal communication, sales, fitness training, learning and growth and the like are improved.

We provide the system. [Solution] A means of collecting and organizing regional information from multiple data sources, A means of creating characteristic information for each user and managing interest information, means for generating personalized communication based on the aforementioned characteristic information, A means for transmitting the generated communication to an information terminal, A means of collecting and analyzing user evaluation information, A means of providing real-time communication to support participation in community activities, A system that includes this.

Systems and methods for a dynamic communication coordination system based on intelligent and personalized communications. For example, as opposed to a conventional routing system, where the router receives a communication and determines an intended recipient as defined by the communication, the system described herein receives a communication and processes the data in that communication using a standardizing relay. The standardizing relay may then determine where to send the communication.

A 6G-oriented intelligent, simple, efficient, and fully decoupled network architecture is based on base stations, users, and edge clouds, wherein the data base stations further include downlink base stations and uplink base stations; the edge cloud is connected to each base station with an optical fiber; the transmission delay of the control channel is lower than that of the data channel; the data channel is distributed and collaboratively sent, and transmission, processing, and storage are received in an integrated manner; the edge cloud is the entity for centralized processing of data in the entire collaborative area; the fully decoupled network is a network architecture in which multiple base stations collaborate in a local area to provide wireless access services to users; the control plane and data plane of the fully decoupled network are physically separated; the uplink and downlink of the data plane are also physically separated; and service transmission on the data plane is achieved through multi-point collaboration; the present invention can fully decouple the network, effectively promote the collaboration of multi-dimensional resources, improve the spectrum efficiency of the entire network, provide users with personalized communication services, and reduce networking costs.

The present disclosure relates to an antenna module and a terminal device. The antenna module comprises: a radio frequency component; at least two antennas distributed in different positions; a first switch component arranged on a connection line between the radio frequency component and each of the antennas; wherein the first switch component is used to turn on the connection line between the radio frequency component and a target antenna in the at least two antennas when an antenna selection instruction indicates the target antenna. The antenna module of the embodiment of the present disclosure is provided with multiple antennas with the same communication function and distributed in different positions, so that the communication coverage is larger, and the specified antenna in the multiple antennas can also be controlled to work in communication according to the antenna selection instruction, realizing personalized communication selection.

This invention relates to the field of multimodal analysis technology and discloses an AI-based method for stakeholder influence analysis and communication strategy optimization in IT projects. The method includes: constructing a unified terminology for an IT domain knowledge graph; achieving multi-source data fusion through anonymization and feature correlation calculation; outputting fused data; realizing comprehensive identification and dynamic role mapping of IT project-specific stakeholders; mining latent stakeholders through trajectory influence values; constructing a dynamic mapping model to track role changes; reusing trajectory influence values ​​and role suitability to complete priority ranking; extracting four types of IT-specific influence features; binding influence and technical risk through correlation strength; calculating a dynamic influence index based on a priority index; constructing and calibrating an IT project-specific communication profile; generating personalized communication strategies; performing quantitative verification of strategy suitability; and outputting communication strategies; collecting dual-channel feedback data according to the influence update cycle and simultaneously adjusting the dynamic influence index and communication strategies.

A contact hub that creates cross-website access to contact lists for more efficient and personalized communication. These lists detail a contact's name, social media profiles, URLs, notes, where users met or potentially plan on meeting, annotations, as well as all pertinent contact information. Contact information is both adopted from internal and external sources and there is an option for users to scan business cards, other documents, and media in association with contacts, creating a secure hub of information regarding an individual. Contact lists are accessible throughout a plurality of applications and employ an information retrieval system that manifests through an icon, and upon being clicked, discloses an array of information and data that has been input.

The present disclosure regards an electronic device configured to generate personalized communications regarding patient treatment plans. The electronic device includes a processor configured to perform various operations. These operations include receiving data regarding a patient, where the data includes treatment plan data regarding a treatment plan prescribed for the patient and other data regarding a healthcare provider, a clinician, a medical record, a social media account, a laboratory, or a pharmacy associated with the patient. The operations also include providing the data to a plurality of machine learning (ML) models configured to generate a personalized communication for the patient based on the data. Additionally, the operations include receiving the personalized from the plurality of ML models, where the personalized communication is addressed to the patient and regards the treatment plan prescribed for the patient. Further, the operations include delivering the personalized communication to the patient.

The system according to this embodiment aims to automatically provide personalized communication based on customer behavior data and lifecycle data. [Solution] The system according to the embodiment comprises a collection unit, an analysis unit, a generation unit, and a distribution unit. The collection unit collects customer behavior data and lifecycle data. The analysis unit analyzes the data collected by the collection unit. The generation unit generates messages and coupons based on the data analyzed by the analysis unit. The distribution unit automatically distributes the messages and coupons generated by the generation unit.

Systems and methods in the present disclosure relate to technology for automated and personalized message generation. A user interface on a user device presents instructions for performing a therapeutic activity. During a session, one or more sensors capture activity data for a user while the user performs the therapeutic activity. The activity data is processed to track performance of the therapeutic activity and generate session data. A prompt for a language model is automatically generated using a prompt data structure that is updated in real-time based on at least one of the session data or historical data associated with the user. A personalized message, as generated in real-time by the language model, is presented to the user via the user interface or via audio hardware associated with the user device.

Email clients typically store received email in a local device to allow faster retrieval of the email. There is a need to optimize the space for emails stored locally without sacrificing the ability to work in an offline mode. Emails for users are summarized and the summarized version of the email is stored on the local device without storing the original email. An electronic device receives an email that is summarized and provided to the user in a way that is easily digestible and saves storage space. A machine learning model is trained by the user to provide the user with a summarized version of the email. A baseline machine learning model is provided to a user and over time, based on user interactions that train the baseline machine learning model, a personalized machine learning model is generated to predict and provide summaries that are beneficial to the user.

Systems and methods for a dynamic communication coordination system based on intelligent and personalized communications. For example, as opposed to a conventional routing system, where the router receives a communication and determines an intended recipient as defined by the communication, the system described herein receives a communication and processes the data in that communication using a standardizing relay. The standardizing relay may then determine where to send the communication.

The present disclosure regards an electronic device configured to generate personalized communications regarding patient treatment plans. The electronic device includes a processor configured to perform various operations. These operations include receiving data regarding a patient, where the data includes treatment plan data regarding a treatment plan prescribed for the patient and other data regarding a healthcare provider, a clinician, a medical record, a social media account, a laboratory, or a pharmacy associated with the patient. The operations also include providing the data to a plurality of machine learning (ML) models configured to generate a personalized communication for the patient based on the data. Additionally, the operations include receiving the personalized from the plurality of ML models, where the personalized communication is addressed to the patient and regards the treatment plan prescribed for the patient. Further, the operations include delivering the personalized communication to the patient.

Systems and methods for a dynamic communication coordination system based on intelligent and personalized communications. For example, as opposed to a conventional routing system, where the router receives a communication and determines an intended recipient as defined by the communication, the system described herein receives a communication and processes the data in that communication using a standardizing relay. The standardizing relay may then determine where to send the communication.

This invention provides a method for constructing a consumer finance sales lead network based on a large language model, belonging to the field of data processing technology. Specifically, it includes: a data access module that reads related data to obtain unstructured text data; a feature enhancement module that uses a semantic network construction strategy and a large language model to perform in-depth analysis of the unstructured text data, performing intent recognition, sentiment analysis, and topic extraction to generate semantic feature tags; a network dynamic construction module responsible for forming a dynamic, multi-dimensional relationship network; an inference module that generates natural language-described, actionable sales leads; and a reach strategy generation module that automatically generates or recommends personalized communication scripts based on the generated sales leads. Furthermore, based on the semantic network construction strategy and the recommendation matching of different marketing activities, it determines the user profile groups that require optimization of the semantic network construction strategy, thereby improving the matching degree of the recommendation processing.

The present disclosure relates to an interactive account comment method and device. The method comprises: obtaining user post content; obtaining a first target generative language model corresponding to the user post content; wherein different target generative language models correspond to different accounts, different accounts correspond to different attributes, and the attributes include: roles, topics, text types, and / or comment methods; generating comment information corresponding to the user post content according to the first target generative language model; and outputting the comment information after the user post content through the account corresponding to the first target generative language model. In the present disclosure, based on the content of the generative language model, the user's needs and preferences can be better understood, personalized communication can be generated, the user experience can be improved, and based on the generative language model, more natural and coherent text content can be generated, so that the user feels communicating with a human.

The present invention relates to the field of communication technologies, and discloses a multi-channel communication management method and system for 5G messaging applications, including: analyzing the behavior patterns and communication requirements of user types in 5G messaging applications to construct a communication requirement analysis model for target users; identifying the multi-channel communication methods of 5G messaging applications and setting up personalized communication mechanisms for target users; identifying the communication change characteristics of target users and setting up a quality supervision system for multi-channel communication methods; identifying the communication faults of multi-channel communication methods, analyzing the causes of the communication faults, and constructing a fault recovery mechanism for multi-channel communication methods based on the causes of the faults and the quality supervision system; and combining the communication requirement analysis model, the quality supervision system, and the fault recovery mechanism to execute the multi-channel communication management of 5G messaging applications to obtain a management result. The present invention can improve the quality and efficiency of multi-channel communication management of 5G messaging applications.

The present disclosure regards an electronic device configured to generate personalized communications regarding patient treatment plans. The electronic device includes a processor configured to perform various operations. These operations include receiving data regarding a patient, where the data includes treatment plan data regarding a treatment plan prescribed for the patient and other data regarding a healthcare provider, a clinician, a medical record, a social media account, a laboratory, or a pharmacy associated with the patient. The operations also include providing the data to a plurality of machine learning (ML) models configured to generate a personalized communication for the patient based on the data. Additionally, the operations include receiving the personalized from the plurality of ML models, where the personalized communication is addressed to the patient and regards the treatment plan prescribed for the patient. Further, the operations include delivering the personalized communication to the patient.

The invention provides a consumer financial sales clue network construction method based on a large language model, which belongs to the technical field of data processing, and specifically comprises the following steps: a data access module reads associated data to obtain unstructured text data; the feature enhancement module performs deep analysis on unstructured text data by using a semantic network construction strategy and a large language model, performs intention recognition, sentiment analysis and topic extraction, and generates semantic feature tags, and the network dynamic construction module is responsible for forming a dynamic and multi-dimensional relationship network. The reasoning module generates operable sales clues described by natural languages, and the touch strategy generation module automatically generates or recommends personalized communication verbal skills on the basis of the generated sales clues and constructs strategies and recommendation matching conditions of different marketing activities on the basis of a semantic network. And the user portrait group needing to be optimized in the semantic network construction strategy is determined, so that the matching degree of recommendation processing is improved.

This invention discloses a personalized communication method based on dataset compression, specifically including the following steps: S1: Perform data distillation on the graph data stored by the k-th client to obtain the k-th synthetic dataset S. k S2: Based on the synthetic dataset S k The optimization objective is constructed and optimized. S3: Based on the optimization objective, the learning rate for training the global model on synthetic data is determined. S4: The central server constructs a pre-trained model based on the learning rate and distributes the pre-trained model to each client for personalized training. By introducing graph dataset extraction and replacing model parameters with synthetic datasets in a single transmission, global information collection is achieved. Next, server models are locally trained on synthetic data to compensate for model performance deficiencies caused by the lack of low-dimensional features in synthetic data. Finally, a balance is achieved between communication volume and accuracy in graph federated learning.

The invention discloses a short message optimal distribution method and device based on dynamic dictionaries and code codes. The method comprises the following steps: S1, deploying a short message distribution system based on a fixed dictionary set and a variable dictionary set; s2, using a server to initialize an update starting time, a historical message and a historical semantic unit set; s3, sending the compressed short message and ii to a server side by using any receiving and transmitting terminal; s4, performing first updating processing on the historical message and the historical semantic unit set by using the server; s5, performing second-level dictionary dynamic updating on the server and the Q transceiving terminals; s6, forwarding the compressed short message to the ii-th transceiving terminal by using the server; s7, performing decompression processing on the compressed short message by utilizing the ii receiving and transmitting terminal to obtain an original text; and S8, repeating the steps S3-S7 until an end signal input from the outside is received. According to the method, the dynamic scene adaptation capability and personalized communication requirements of short message distribution can be improved, and the communication security and universality are considered.

The invention discloses a computer communication quality evaluation and analysis system, which belongs to the technical field of computer communication quality evaluation, and comprises the following steps: acquiring various evaluation indexes for evaluating computer communication quality, and determining each potential index evaluation combination according to each evaluation index; analyzing various quality scoring modes of each evaluation index combination, and sending each evaluation index combination and the quality scoring mode to a reserve library for storage; receiving reference evaluation system information sent by each user side in real time, and matching each quality scoring mode from the reserve library according to the reference evaluation system information; monitoring display data of a reference evaluation system is acquired in real time, reference evaluation system information is acquired, the reference evaluation system information is sent to the platform end, and a target scoring mode of the user is determined according to each quality scoring mode; and analyzing the monitoring display data according to the target scoring mode to obtain a personalized communication evaluation result, and displaying the personalized communication evaluation result to the user.

An example digital therapy platform is disclosed that provides personalized, real-time feedback to patients during sessions. The platform collects real-time performance data during the sessions, including metrics such as range of motion, pelvic floor movements, exercise completion rates, and the accuracy of movements. The digital therapy platform may also retrieve historical data from past sessions to provide a comprehensive overview of the patient's context. The digital therapy platform dynamically generates structured prompts based on the analyzed data and provides these prompts to a large language model (LLM). The LLM generates personalized messages tailored to the patient's specific context. The digital therapy platform delivers the personalized messages to the patient through a user interface.