1288 results about "User profile" patented technology

The invention relates to the technical field of big data, in particular to an e-commerce marketing propaganda system based on behavior analysis, which comprises a global user portrait module, an intelligent recommendation engine, a marketing fatigue management module, a supply chain collaboration module, a lightweight terminal module and a budget and value management module. In the prior art, user portraits are constructed only depending on single channel data such as online clicking or purchase records, so that user interest modeling is incomplete and lagged; according to the method, all-channel behavior data such as APP, Web, offline POS and social media are integrated, a user-commodity-scene heterogeneous graph is constructed by using a graph neural network, and an interest attenuation period (for example, the weight is reduced by 50% after the interest of mother and infant users lasts for 18 months) is dynamically captured through an LSTM model; for example, after a user tries on a certain style of clothes offline, the system associates online behaviors in real time and recommends commodities of the same style, the cross-scene conversion rate is improved by 32%, and the user portrait coverage degree is improved by 60%.

Systems and methods are described for dynamic execution of artificial intelligence (“AI”) agents. A server can receive, from a client device, an input associated with an AI agent. Based on a manifest file or user profile, the server can identify a management policy that applies to the AI agent. The server then dynamically configures access to the agent objects based on applying the management policy. The management policy is applied to a device status of the client device, a user profile of a user of the client device, and / or a network configuration of the client device. The server then executes a modified workflow based on the dynamically configured access, wherein the modified workflow bypasses or changes operation of at least one of the agent objects. Based on the modified workflow, the server transmits an output to the client device.

A system and method for real-time or near real-time multilingual language transformation in telecommunications environments using distributed artificial intelligence (Al). The system includes at least one processor configured to instantiate a plurality of Al agents, each corresponding to a user in a communication session, and to manage their operation via an Al-agent runtime adapter comprising a microkernel agent manager and a virtual machine layer. A language model abstraction layer enables access to language models and Al algorithm libraries through publish-subscribe interfaces. The system supports contextual transformation of speech based on user profile data such as sentiment, emotional tone, and cultural background. Execution can occur on telecommunication-class switches, edge devices, or general-purpose computing hardware. Al agents operate asynchronously, access shared or private memory, and produce personalized, bidirectional linguistic output. The architecture supports secure, scalable deployment across heterogeneous devices and networks.

The invention discloses a high-low voltage linkage line loss comprehensive intelligent diagnosis system and method. The system comprises a distributed storage and high-performance calculation module, a data fusion and processing module, a multi-dimensional feature construction module, a high-low voltage linkage analysis module and a line loss intelligent diagnosis module. The method is used for carrying out line loss comprehensive intelligent diagnosis based on the system, and comprises the following steps: processing multi-source data in real time through the distributed storage and high-performance calculation module; bus-line-user archive data are fused, and a line loss index is calculated; extracting time, space and electrical three-dimensional characteristic indexes; performing high-low voltage linkage analysis based on the Pearson's correlation coefficient and the DTW distance; and fusing the system state model and the isolated forest anomaly detection model to output an anomaly diagnosis result. The method is suitable for accurate analysis and treatment of line loss in an intelligent power grid environment, and the efficiency and quality of line loss management can be improved.

Aspects of the present application help to alter searches in non-linear media. In some embodiments, a server may receive a part of a user search query related to non-linear content. The server may access progress data that is associated with the user profile and perform a search on a database using the progress data and the search query to produce a number of candidate content items (e.g., search results). The server may access a data structure that defines possible paths through the non-linear media, and may filter the candidate content items based on the progress data and the data structure that defines the possible paths through the non-linear media to generate output of a filtered candidate content item.

A system for the real-time delivery of personalized motivational content based on biometric information; the system includes: a biometric acquisition module configured to capture a variety of physiological signals from a user, wherein the physiological signals include at least heart rate variability, electrodermal activity, facial expressions and electroencephalographic (EEG) signals; a preprocessing module that is operationally coupled with the biometric acquisition module, wherein the preprocessing module is configured to remove noise, normalize and extract signal features from the physiological signals in real time; a multimodal biometric fusion engine configured to temporally align and synchronize the extracted features across signal modalities using dynamic time distortion and confidence-weighted interpolation; a motivational state inference model with a hybrid neural architecture comprising a Convolutional Neural Network (CNN) for spatial pattern recognition and a Recurrent Neural Network (RNN) for temporal sequence modeling, wherein the inference model is configured to output a motivational input score and an affective state classification; an engine for recommending motivational content, configured to select and prioritize content from a content repository based on motivational uptake score, user profile metadata, contextual signals including time of day and geolocation, and historical content effectiveness profiles; and a content delivery subsystem comprising one or more output modalities selected from an acoustic actuator, a visual display, a haptic actuator or an environmental controller, wherein the content delivery subsystem is capable of presenting the selected motivational content in a modality that is dynamically adapted to the user's current psychophysiological state.

Systems and methods are described for dynamic execution of artificial intelligence (“AI”) agents. A server can receive, from a client device, an input associated with an AI agent. Based on a manifest file or user profile, the server can identify a management policy that applies to the AI agent. The server then dynamically configures access to the agent objects based on applying the management policy. The management policy is applied to a device status of the client device, a user profile of a user of the client device, and / or a network configuration of the client device. The server then executes a modified workflow based on the dynamically configured access, wherein the modified workflow bypasses or changes operation of at least one of the agent objects. Based on the modified workflow, the server transmits an output to the client device.

A recommendation system is described, which identifies engaged fans for an artist and requests input from the engaged fans regarding a collaboration by the artist with at least one different artist. In implementations, engaged fans are identified as having user profiles on a media content platform that satisfy at least one threshold engagement criteria based on consumption of at least one media content item associated with the artist. The recommendation system presents a user interface that includes at least one prompt for feedback that enables engaged fans to recommend how the artist collaborate with others. In some implementations, the user interface includes controls that are selectable to define artist characteristics to feature in a collaboration and the recommendation system is configured to generate a synthesized collaboration by automatically combining different artists' characteristics using a trained machine learning model. Recommendations based on engaged fan feedback are then provided to artists.

The embodiment of the invention provides a financial credit intelligent marketing system and method. Comprising a multi-source data acquisition and integration module, a data preprocessing and fusion module, a multi-modal data fusion and feature engineering module, a user portrait construction and subdivision module, an intelligent marketing strategy making module, a marketing execution and real-time monitoring module and an effect evaluation and strategy iteration module. The financial credit intelligent marketing system comprises a plurality of functional modules such as data acquisition, data processing, model training, strategy making, real-time marketing, batch marketing, execution monitoring and the like. A comprehensive and multi-dimensional user portrait is formed by integrating enterprise internal data and an external third-party authorization data source. And machine learning algorithms such as XGBoost, LightGBM and the like are utilized to carry out deep mining and analysis on user behaviors, and purchase intention and demand change of the user are predicted. Meanwhile, based on the Flink real-time data processing technology, quick response and dynamic adjustment of marketing activities are achieved.

Systems and methods for automating workflows, improving operating efficiency, and / or improving security in a multi-party document management platform are disclosed. The systems and methods utilize artificial intelligence (AI) models to analyze user profiles, generate risk scores for multi-party agreements, and determine risk mitigation actions. User interactions with modified agreements are monitored, and the AI models are updated based on these interactions. The system automatically adjusts operating parameters to improve operating efficiency and / or security. The methods and systems also provide for generating recommendations, utilizing user feedback, analyzing user action patterns, performing portfolio-level risk assessments, and identifying workflow inefficiencies. These features enable a dynamic, adaptive platform that continuously improves its performance in managing multi-party agreements while also enhancing security and operational efficiency.

The invention relates to the field of artificial intelligence, and discloses an E-commerce platform commodity recommendation method based on AI intelligence, and the method comprises the steps: obtaining user environment and behavior data through multi-modal perception, generating a three-dimensional intention vector through space-time convolution network coding, and driving a dynamic strategy selector to configure a recommendation weight; generating an initial recommendation list in combination with the commodity feature library and the user portrait; collecting user interaction feedback in real time, analyzing and outputting a correction vector through a lightweight loop network, dynamically adjusting a strategy, and reordering recommendation results; after a user places an order, a scene complementation generator is started, a complementation commodity sub-list adaptive to a current transaction scene is generated based on knowledge graph multi-hop reasoning, and visual fusion presentation is carried out. According to the technical scheme, accurate intention recognition, millisecond-level strategy correction and dynamic complementary recommendation are achieved, and recommendation real-time performance, adaptability and diversity are improved.

The invention relates to the field of artificial intelligence and personalized recommendation, and discloses a sensing data intelligent recommendation system. The system comprises a perception data acquisition module, a multi-dimensional feature analysis module, a user portrait construction module, an intelligent recommendation decision module and an enhanced feedback optimization module. The method comprises the following steps: acquiring original data through a multi-source sensing device, and extracting multi-dimensional statistical characteristics after standardization processing; a user portrait model is constructed in combination with user historical behaviors, candidate recommendation vectors are generated, a recommendation strategy is dynamically optimized based on user feedback, efficient, accurate and personalized recommendation results are achieved, and the method is suitable for complex application environments such as intelligent interaction, mobile terminals and intelligent scenes.

The invention discloses a digital cultural tourism management system based on multi-source data analysis, and the system comprises a multi-source heterogeneous data collection module which is used for collecting tourist behavior data, environment data, cultural resource data and third-party platform data in real time; the user demand intelligent analysis module is used for constructing a dynamic user portrait through the multi-modal interaction data and identifying dominant and implicit demands; the culture knowledge graph construction module is used for generating a reasonable multi-dimensional knowledge network based on culture resource attributes and historical data; the travel route dynamic generation module is used for generating a personalized touring route in combination with the user portrait, the real-time environment and the resource state; according to the digital cultural tourism management system based on multi-source data analysis disclosed by the invention, the utilization rate of cultural resources is greatly improved, and the decision response speed is increased; the cultural cognition depth of tourists is improved, and the residence time of the tourists is prolonged; the damage rate of high-sensitivity cultural relics is reduced; and the special group culture acquisition efficiency is improved in a breakthrough manner.

A display improvement support method and device for improving a display in accordance with the user's conscious reaction is provided. [Solution] In the display object improvement support device, the generation AI control unit executes the following steps: a reaction prediction prompt generation step of generating a reaction prediction prompt that instructs the generation AI to predict the reaction that will occur in the mind of a virtual user having user profile information of at least one of age, sex, occupation, height, and weight when the virtual user uses the display object; a reaction acquisition step of inputting the reaction prediction prompt into the generation AI and acquiring reaction information, which is information related to the reaction, from the generation AI; a screen operation prediction prompt generation step of generating a screen operation prediction prompt that instructs the generation AI to predict the screen operations that the user will perform on the screen of an information device based on the reaction information; and a screen operation acquisition step of inputting the screen operation prediction prompt into the generation AI and acquiring screen operation information, which is information related to screen operations, from the generation AI.

The invention relates to the technical field of block chains, in particular to a block chain multi-platform data credible management method and system based on a user portrait, and the method comprises the steps: carrying out the multi-platform data collection, obtaining a plurality of original user data sets, carrying out the encryption processing of the original user data sets, obtaining an encrypted user data set, carrying out the block packaging processing of the encrypted user data set, and carrying out the block packaging processing of the encrypted user data set. Performing consensus verification on the block to be subjected to consensus encryption to obtain an on-chain encryption block; performing feature extraction on the on-chain encryption block to obtain a user feature data set; performing feature division on the user feature data set to obtain a user feature type set; performing portrait construction based on the user feature type set to obtain a user portrait; and obtaining a portrait access standard, and according to the portrait access standard, performing authorization judgment by using the data access authorization unit. According to the method and the device, the problem of low data credibility in the current management process of the multi-platform data of the block chain can be solved.

An apparatus comprises a memory communicatively coupled to a processor. The memory is configured to store network interchange parameters and user profiles. The processor is configured to receive a data exchange request triggered by a user device. Further, the processor is configured to request, to a decentralized network, a token indicating that a user profile associated with the user device is entitled to access an entitlement, determine whether a data exchange network is available to exchange data in accordance with the network interchange parameters, identify a second data exchange network that is available in accordance with second network interchange parameters in response to determine that the data exchange network is unavailable, and request a data exchange output from the second data exchange network via the token. The processor is configured to receive the data exchange output from the second data exchange network.

Provided is a system for robotic collaboration. A first robotic device executes a first action and a second robotic device executes a second action upon the first robotic device completing the first action. An application of a communication device is paired with the first robotic device and the second robotic device. The application is configured to receive at least one input designating, for example, a hitting speed of a tennis ball, a hitting direction of a tennis ball, a unique tag of a subarea in a map of an environment, a task schedule of the first robotic or second robotic device, a driving speed, a selection of a particular user profile, an instruction to drive to a user-identified location, an instruction to turn in a left or right direction, an instruction to drive forwards or backwards, an instruction to stop moving, etc.

Automatic detection and handling of security-related anomalies by utilizing machine learning and a large language model (LLM). A computerized method for detecting and handling security threats in an organizational network of an organization includes: (a) collecting event data that pertain to organizational users, organizational devices, and organizational resources of the organizational network; (b) constructing user profiles, device profiles, and resource profiles; (c) constructing Organizational Context information that pertains to organizational users, organizational devices, and organizational resources; (d) constructing a time-series of events, enriched with the Organizational Context information; (e) analyzing the time-series of events using a Machine Learning process that detects an anomalous event, and automatically generating an alert message pertaining to and describing the anomalous event.

An apparatus and method for personalization of educational machine learning models. The apparatus includes at least a processor and a memory communicatively connected to the at least a processor. The memory instructs the processor to receive input data comprising one or more of a user profile and a request datum, generate, using a return generator, return output based on the request datum, identify, using a machine learning model, attribute data of the input data, generate, using a classifier, one or more classifications for the input data as a function of the attribute data associated with the input data, modify, using a natural language processor, the return output as a function of the user profile and one or more classifications assigned to the input data to generate user specific output, and display, using a downstream device, the user specific output.

According to an embodiment, disclosed is a system comprising one or more sensors; and a processor storing instructions in a memory that, when executed, cause the processor to identify, a user from one or more users of a vehicle, based on a user profile comprising a user identification detail; detect, a presence of one or more objects within the vehicle; monitor, the objects and the user using data from the sensors; generate, a first message based on a continued presence of the objects after an exit location of the user based on an image analysis of a first image and a second image of a portion of an interior region of the vehicle; and transmit, the first message to a user device; and wherein the system is configured for dynamic tracking of the objects and reminding via an alert notification.

The invention provides a multi-factor marketing data correlation analysis method and system, and the method comprises the steps: carrying out the collection and integration processing of multi-dimensional marketing data of an advertisement putting platform, a user behavior tracking system, and a sales transaction system, so as to generate an original data set containing a timestamp, a channel label, a user portrait, and a numerical index; performing time fluctuation factor calculation, market scale normalization and channel weight distribution processing on the original data set to generate a normalized and weighted data set; performing correlation matrix construction, correlation coefficient calculation and core factor screening processing on the normalized data set to generate a core factor set; and the recommendation module is used for carrying out model training, prediction, strategy simulation and recommendation generation processing on the core factor ranking result and the normalized and weighted data set so as to generate a marketing decision optimization recommendation. According to the method, multi-source data is integrated to solve the compatibility problem, dynamic processing and accurate analysis are achieved, and the marketing decision-making efficiency is improved through closed-loop generation of optimization suggestions.

A system and method are provided for dynamically generating interactive multimedia storytelling experiences using integrated artificial intelligence models. The system comprises a generative language model for producing narrative content in response to user input, a generative video synthesis module for visualizing story segments, and a generative audio synthesis module for producing synchronized speech, effects, and music. In alternative embodiments, a single multimodal generative model may perform both video and audio synthesis. A user interaction module accepts free-form input to evolve the story in real time, and a content generation coordinator manages orchestration, timing, and latency optimization between components. The system supports modular architecture, lip synchronization with character visuals, predictive pre-generation to reduce delay, personalization based on user profiles, and deployment across various platforms including desktop, mobile, and extended reality environments. The invention enables open-ended, user-driven narrative generation with seamless and adaptive audiovisual synthesis.

Embodiments described herein relate to systems and methods for providing a recommendation panel for a graphical user interface of an issue tracking platform. The system and methods can include causing display of the recommendation panel in the issue-view graphical user interface. The recommendation panel can include a first section including a set of one or more selectable link objects, where each selectable link object associated with a respective content item identified for the request type; a second section including a link to a user profile of a subject matter expert user, where the subject matter expert user selected based on a subject matter determined using the issue data; and a third section including suggested action narrative. The suggested action narrative can be determined using a generative response received from the generative output engine in response to the prompt.

The invention relates to the technical field of artificial intelligence, in particular to a large model dialogue management method and device.The method comprises the steps that dialogue information of a user input dialogue initiated by a user to a large model is intercepted; obtaining user information corresponding to a user; filling the first cue word template based on dialogue information of a dialogue input by a user and user information to obtain a first cue word; sending the first cue word as first-round user input dialogue information to the large model, so that the large model generates large model output dialogue information for the first-round user input dialogue based on the first cue word; and in response to establishment of the update trigger condition, updating the user contour information based on the historical round dialogue of the current session and / or the dialogue content of the current round dialogue. According to the method, the structured user background information is provided for the large model at the beginning of the dialogue, so that the reply accuracy and pertinence of the large model are remarkably improved, and cross-session personalized interaction experience is realized.

Systems and methods receive input(s) for identifying a user profile, transmit identifier data identifying the user profile, and display an initial GUI depicting information associated with the user profile. Prompt data is received to initiate generation of GUI(s) that include customized prompt(s) that identify opportunity-based development actions. Based on receiving the prompt data, the GUI that includes at least one prompt of the customized prompt(s) is dynamically generated and displayed via a user interface of a user device, where the at least one prompt of the customized prompt(s) provides transfer information for redirecting a third-party to one or more locations for effectuating an opportunity-based development action.

An apparatus and method for generating resource output as a function of a query and multimodal data. The apparatus includes at least a processor and a memory communicatively connected to the at least a processor. The memory instructs the processor to receive multimodal data associated with a user profile, receive a first query of a plurality of queries, generate at least a first output of a plurality of outputs as a function of the first query and the multimodal data, wherein the plurality of outputs comprises a question data structure, wherein the question data structure comprises each output associated with a weight, generate a score associated with the at least a first output using system feedback, adjust at least the weight associated with the at least a first output, select a plurality of questions, and display the first question followed temporally by the second question.

Techniques for content generation using machine learning. A device may access textual content from a user device associated with a user profile, access content preferences associated with the user profile, and provide the textual content to a classification model to identify one or more topics of the textual content. The classification model may be trained to identify topics within text. The device may access, from a content repository, supplementary textual content associated with the one or more topics; form, based on the content preferences, an instruction prompt for a generative model; and provide the topics, the textual content, and the supplementary textual content to the generative model to obtain additional content. The device may identify, from the user profile, one or more additional user profiles having a relationship with the user profile; and provide the additional content to an external server.

The invention relates to the technical field of museum intelligent service, and discloses an intelligent-based interactive museum display guide explanation system, which comprises an interactive perception module, a user portrait construction module, a content matching module, a path planning module and a feedback optimization module. The interactive perception module processes user behaviors and display environment data and constructs a multi-modal interactive perception model; the user portrait construction module integrates the user basic information and the behavior preference data to form a user feature portrait set; the content matching module combines the multi-modal interactive perception model and the user feature portrait to generate a personalized explanation content candidate sequence; the path planning module optimizes and determines an optimal guiding path; and the feedback optimization module evaluates the explanation effect and dynamically adjusts the content. According to the system, personalized explanation and intelligent guidance are realized, the interactivity and accuracy of museum service are improved, and the visiting experience of the user is optimized.

The invention discloses an interactive personalized information pushing method, and the method comprises the steps: obtaining user data, building a dynamic user portrait for a user based on the user data, and enabling the dynamic user portrait to comprise a demand tag, a preference weight coefficient and an economic capability evaluation index; user requirements are analyzed in real time through natural language interaction, and dynamic features and intention keywords are extracted; in combination with multi-dimensional information of a commodity database, the system adopts a priority matching algorithm to generate a recommended commodity list, and generates personalized push content through a natural language generation engine, including commodity core selling points, matching degree analysis and interactive question and answer guidance; and finally, the system sends the content to a user terminal through multi-channel pushing, monitors user behaviors in real time to update a user portrait, and continuously optimizes a recommendation strategy.

A locking control system and method include providing a base plate with an attachment interface and attaching at least one accessory to the base plate via the attachment interface. A user profile is provided that comprises one or more classes of authorization. Locking and unlocking of the at least one accessory to the base plate is controlled based on the user profile and / or locking and unlocking of the at least one accessory itself is controlled based on the user profile.