613 results about "User group" patented technology

The invention discloses an anomaly detection method and system for transaction flow data, and relates to the technical field of big data analysis. The method comprises the following steps: based on transaction flow data, acquiring operation behavior data of a target user in a transaction process and interaction behavior data after the transaction is completed, and sorting according to timestamps to form a user operation behavior sequence and a user interaction behavior sequence; inputting the sequence into a pre-trained abnormal risk prediction model, and outputting an initial risk coefficient, wherein the model integrates an individual behavior baseline and an adaptive weight module; acquiring a group behavior baseline of the similar user group, and correcting the initial risk coefficient in combination with a matching result of the sequence and the group baseline to obtain a final risk coefficient; and performing classification abnormity early warning operation on the final risk coefficient based on a preset risk threshold. According to the method, through whole-process behavior sequence analysis, individual and group baseline dual calibration and dynamic weight adjustment, the accuracy and timeliness of transaction flow data anomaly detection are effectively improved.

The invention provides a multi-modal emotion recognition fusion method based on a multi-head attention mechanism, and the method comprises the steps: carrying out the feature extraction and fusion of various data, capturing the internal relation of a modal through the multi-head attention mechanism, achieving the information complementation between modals through cross-modal interaction, and dynamically adjusting the weight according to the quality of the modals. And a self-built database containing a large amount of Chinese data is constructed, and a culture adaptation optimization strategy is combined, so that the generalization performance and culture adaptability of the model in Chinese user groups are improved. The system is deployed on a cloud server, optimized hardware and software configuration is adopted, efficient model reasoning and multi-user concurrent processing are achieved, and the large-scale real-time application requirement is met. The emotion of the user can be monitored in real time and early warning can be provided in scenes such as psychological counseling and group emotion monitoring, professionals are assisted in better understanding the emotion state of the user, and the service effect is improved.

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.

The invention relates to the technical field of artificial intelligence, in particular to a verbal skill confrontation training generation method and device based on a large model, equipment and a storage medium, and the method comprises the steps: generating a simulation inquiry based on a preset user portrait, then obtaining a response of a service large model, and comprehensively evaluating the response quality; and the specific defect type of the service model in logic understanding or verbal skill expression is diagnosed through the cognitive deviation between the response and the user expectation by another evaluation model, so that a targeted optimization strategy is generated, the service model is finally driven to carry out directional reinforcement learning, and the verbal skill ability of the large service model is iteratively improved. According to the method, an adversarial sample is dynamically generated, and deep diagnosis is carried out in combination with cognitive deviation, so that a service model can understand deep intentions and emotion demands of different user groups fundamentally. Therefore, the strain capacity and the communication accuracy of the service model in a real interaction scene are remarkably improved, and the user satisfaction is effectively improved.

The invention belongs to the technical field of intelligent household appliances, and particularly relates to a control method and equipment of water purification equipment and a storage medium. The method comprises the steps that human physiological data of a target user is obtained through cloud equipment, the cloud equipment classifies the target user based on the human physiological data, and the cloud equipment determines a water purification scheme for the target user based on the classification of the target user and the human physiological data of the target user, the cloud equipment sends the water purification scheme to water purification equipment, and the water purification equipment adjusts the water purification equipment based on the water purification scheme and a raw water detection result; according to the method, the water quality of the water purification equipment is adjusted according to the intake requirements of different types of user groups on trace elements, the intelligence of the water purification equipment is improved, and the user experience is improved.

The invention provides a power grid online channel operation method based on multi-dimensional fusion identity and flywheel fission, and the method comprises the steps: obtaining the multi-dimensional identity information of a user, carrying out the fusion processing of the multi-dimensional identity information, and forming a unified user identity identifier; establishing a user tag system containing industry exclusive tags, and carrying out real-time circling selection on users based on the user tag system and a preset circling selection rule to generate a target user group; and initiating a marketing activity to the target user group. Executing the marketing activity on the basis of a multi-level cache mechanism, performing real-time acquisition, analysis and visual display on full-life-cycle data of the marketing activity, and performing iterative optimization on a strategy of the marketing activity according to an analysis result; therefore, the user identification accuracy can be improved, the marketing strategy can be dynamically optimized, the fission conversion efficiency can be improved, and the system response capability can be enhanced.

An information processing apparatus includes, a setting unit that sets a condition for a user classified into a user group from input data; a selecting unit that selects a to-be-analyzed group based on a user attribute corresponding to each condition with respect to each the condition; a scoring unit that scores each user meeting the condition based on a behavior history of each user corresponding to each condition with respect to each the condition; an extractor that extracts a warm-prospect user having a higher score than other users in the to-be-analyzed group based on a result of scoring by the scoring unit; and a provision unit that selects a to-be-compared user, specifies information on a characteristic behavior of the warm-prospect user, transmits information on the specified characteristic behavior and attribute information indicating the attribute corresponding to the warm-prospect user to a terminal device, and provides the specified and attribute information.

The invention discloses a code-configuration-free digital twin warehouse system and a construction method thereof. The construction method comprises the following steps: initializing a warehouse digital twin platform, importing entity object data, and establishing a basic two-dimensional data visualization framework and a three-dimensional rendering engine; collecting multi-source heterogeneous data in real time and preprocessing the multi-source heterogeneous data to obtain a real-time data source; 2D / 3D coordinate precision mapping and dynamic data coupling are carried out; calling a code-free configuration tool, receiving a real-time data source for a user to drag and use, and assembling a logic flow chart by the user through dragging; analyzing the logic flow chart assembled by the user through middleware to generate a low-level instruction sequence; the low-level instruction sequence is input into an external actuator and a physical simulation engine; virtual verification and situational simulation are executed through a physical simulation engine, and optimization suggestions are output and adjusted. The invention provides a code-free configuration integration mechanism, supports non-technical personnel to autonomously construct data-driven twinning application, and realizes transformation of warehouse digital twinning from static monitoring to dynamic iteration.

The invention provides a user intention recognition method based on a multi-modal model, and the method comprises the steps: determining a keyword set of a user group according to a historical description text of a user in the user group to be recognized for a required service; inputting the keywords in the keyword set into a text encoder in a preset image-text multi-modal model to obtain semantic feature vectors of the keywords output by the text encoder; performing clustering processing on the keyword set according to the semantic feature vector of each keyword in the keyword set, and processing various clusters obtained by clustering to obtain one or more high-quality class clusters; the semantic similarity of the semantic feature vector of each keyword in the high-quality class cluster meets a preset similarity condition, and the distance distribution between the semantic feature vector of each keyword and the center of the class cluster meets a preset concentration condition; and determining the user intention of the user group for the required service according to each keyword in the high-quality class cluster.

Methods for assisting one or more users in organizing content-items, such as location information (e.g., URLs) for online information resources (e.g., webpages) and clips taken from information resources, accessed via content-access software, such as one or more web browsers, using a content item-bundle primitive that allows users to create, build, manipulate, and / or populate their own content-item bundles according to their information investigation and collection desires / needs. In some embodiments, the methods include automatically bundling content items into suggested content-item bundles based on learned relationships among various content items. In some embodiments, the methods can be implemented to provide bundle-based task managers that allow users to not only organize their content items but also define tasks and / or projects rooted in the content-item-bundle primitive. Further embodiments are disclosed, as is software for executing disclosed methods.

The invention relates to the technical field of graphic processing, and discloses an e-commerce commodity image-text intelligent generation and distribution system, which comprises a multi-source data acquisition module, a personalized template synthesis module, a commodity image precise embedding module, a rule-driven text generation module, a self-adaptive image-text fusion module and an intelligent grouping and directional distribution module, obtaining commodity basic information data and user historical behavior data; extracting user visual preference features, applying the user visual preference features to the basic template, and generating a personalized commodity image template; seamlessly embedding the commodity main image into a personalized commodity image template to obtain a personalized commodity image; extracting the structured visual information and the commodity feature abstract, and integrating into a description text; fusing the personalized commodity image and the description text into image-text content; grouping the user historical behavior data to obtain a target user group set, and pushing the description text and the image-text content to the target user group set; according to the invention, the accuracy of image-text intelligent generation and distribution can be improved.

The invention provides a user side shared energy storage multilayer optimization method considering joint pricing and demand response, and relates to the technical field of integrated energy systems.The method comprises the steps that firstly, basic operation parameter data in a regional integrated energy system are collected, and the relation between the power of a shared energy storage power station and the power of the shared energy storage power station used by each user is determined; and calculating the price excitation demand response income and peak regulation cost of the user group, and further constructing a user-side shared energy storage multilayer optimization model and solving the user-side shared energy storage multilayer optimization model. Through optimizing a joint pricing and energy scheduling strategy, the model significantly reduces the overall operation cost of a user group, and effectively reduces the power purchase demand of a power grid in a peak period. Meanwhile, the system fully consumes the renewable energy generating capacity, and the problem of low utilization rate caused by resource waste is avoided. Therefore, the power supply pressure of the power grid is relieved, the operation stability is improved, the synergistic interaction of the source network load storage is realized, and the win-win situation among multiple main bodies is achieved.

The invention provides a user portrait recommendation method based on a high-order structure and semantic enhancement, and the method specifically comprises the following steps: S1, introducing a multi-hop adjacent matrix to capture a high-order behavior pattern in an interaction graph for the interaction graph of a user and a project through a high-order structure maintenance module of user grouping, and employing a low-rank approximation and clustering method to obtain a high-order behavior pattern in the interaction graph; grouping the users based on the behavior similarity; s2, extracting a representative keyword set from items interacted by the same group of users, and obtaining group-level keywords of the users; s3, through a portrait perception recommendation module based on cross-view comparative learning, user semantic embedding and project semantic embedding based on keywords are constructed; obtaining user structure embedding and project structure embedding according to a collaborative structure between a user and a project in the interaction graph; then, alignment of project semantic embedding and project structure embedding is achieved through cross-view comparative learning; and S4, calculating a user-project combination score and generating a recommendation result. According to the invention, the recommendation performance is enhanced.

The invention relates to the technical field of power system auxiliary services, in particular to a multi-agent participated user group dynamic combination and economic optimization method in power auxiliary services, which comprises the following steps of: constructing a multi-agent collaborative model of'upper-layer scheduling-middle-layer aggregation-lower-layer execution ', formulating an incentive price through a Stackelberg game between upper-layer ISO (International Standard Organization) and LAs (Local Assisted Services), and establishing a multi-agent collaborative model of'upper-layer scheduling-middle-layer aggregation-lower-layer execution'; the evolutionary game between the lower-layer LAs and the user realizes user strategy interaction; introducing maximum profit power reduction and power transfer potential indexes, and performing user group preliminary screening in combination with a multi-energy profit map; and outputting an optimal user group combination scheme through iterative solution and joint uncertainty analysis. The invention further provides an alternative scheme, and dynamic combination optimization is realized by utilizing the user potential portrait and a reinforcement learning mechanism. The method can effectively improve the economy, flexibility and robustness of the power auxiliary service, and gives consideration to the comfort of the user and the adjustment demands of the system.

The application discloses a health-care robot knowledge graph dynamic updating method based on reinforcement learning, and relates to the technical field of artificial intelligence and rehabilitation medical treatment. The application realizes zero-risk virtual exploration through a counterfactual reasoning mechanism, avoids the security risks caused by the trial-and-error process to users from the root, and uses the current knowledge graph as a world model. When a high-fuzziness knowledge node is identified, instead of directly executing unknown actions in a real environment, a virtual result generated by executing a virtual action is deduced based on similar user group records and association rules in the knowledge graph, a virtual reward value is calculated, virtual experience samples are stored in an experience replay pool to participate in subsequent network training, the reinforcement learning intelligent agent can learn the potential value of the action without ever executing the action in reality, and thus a virtual learning environment is constructed in the whole knowledge exploration process, and the security threat of the trial-and-error process to users is solved.

This disclosure discloses a terminal device control method, apparatus, electronic device, and computer-readable medium. One specific implementation of the method includes: generating a set of associated user groups based on an acquired set of user attribute information; performing time-series information fusion processing on the associated user group set based on acquired user virtual item circulation information to obtain a heterogeneous graph of virtual item circulation among associated nodes; extracting node features from the heterogeneous graph of virtual item circulation among associated nodes using an associated node feature extraction model to obtain a set of associated node feature vectors; reconstructing nodes in the associated node feature vector set to obtain a reconstructed feature vector set of associated nodes; generating an abnormal associated user group set based on the reconstructed feature vector set and the associated node feature vector set; and performing circulation interception control on the user terminal device set corresponding to the abnormal associated user group set. This implementation can reduce server load and minimize system resource waste.

The present invention relates to a personal awareness system that provides users physical health / wellness / welfare safety as well as online digital safety by blocking inappropriate digital content. The personal awareness system comprises a network protection appliance for use on a local area network (LAN), a software application that is used on a mobile computing device, a cloud-based remote data processing resource to administer the system, artificial intelligence (AI) information systems, and a monitor computing device that an observer can use to monitor, track, and receive alerts related to the user. The system can support many users individually as well as groups of users. In operation, sensors associated with the mobile computing device monitor the health, wellness, and location of users and digital filter rules suppress inappropriate digital content from user access providing digital safety. The mobile computing device seamlessly transitions between LAN environments and wireless mobile environments.

This application discloses a user behavior attribution method and related products. The method constructs a behavior sequence for each user based on multimodal behavior data of multiple users within a preset time window. Based on each user's behavior sequence, corresponding natural language semantic tags are determined, and these tags are converted into corresponding semantic vectors. The semantic vectors of multiple users in the current time window and in historical time windows are clustered to obtain clustering results for the current and historical time windows. The clustering results of the two time windows are compared to determine the semantic drift trajectory of each user group. Based on the semantic drift trajectories of multiple user groups, the contribution of each user group to the fluctuation of preset business indicators is quantified, and the quantification results are generated, along with an attribution report. Compared to the low accuracy of existing user behavior attribution technologies, this application has significant advantages.

The invention relates to the technical field of mobile communication, in particular to an urban resident lifestyle identification method based on Wi-Fi handshake data. Wi-Fi handshake data of the mobile terminal are collected; based on the Wi-Fi handshake data, identifying visit events of an individual at different points of interest (POI), and forming a continuous visit sequence according to a time sequence; compressing the visited sequence, and extracting a long-term repeated high-frequency sequence mode; calculating the similarity between the users based on a high-frequency sequence mode, and obtaining a user group cluster with similar lifestyles through clustering; and performing feature analysis on each user group cluster, extracting a core visit sequence, and generating a lifestyle group portrait. Through the technical combination of Wi-Fi handshake data acquisition, sequence compression clustering and sample representativeness correction, comprehensive optimization of urban resident lifestyle identification on coverage integrity, result accuracy, implementation efficiency and cost control is realized, and high-quality data support is provided for urban related decisions.

A system is provided for artificial intelligence based predictive analytics of electronic user data. In particular, the system may comprise an artificial intelligence (“AI”) engine that continuously aggregates user data associated with a user and / or a group of users based on internal and external data sources across various different communication channels. The AI engine may then parse and tokenize the user data to generate a complete user snapshot associated with the user and / or the group of users. Based on analyzing the user data, the AI engine may generate a probability score associated with a predicted user action within the network environment. Based on the predicted user action and the probability score associated with the predicted user action, the system may drive decisioning processes within the network environment and / or generate one or more outputs to be presented on one or more user computing devices in and out of the network environment.

According to an aspect, there is provided a construction time monitoring system for a construction site, the construction time monitoring system comprising: at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the construction time monitoring system to at least perform: associating a remotely readable identifier for each tool of a set of tools; associating a remotely readable identifier for each member of a user group; linking each tool of the set of tools to at least one member of the user group by associating the remotely readable identifier of the tool with the remotely readable identifier of the at least one member of the user group; receiving tracking data comprising remotely readable identifiers read with at least one remotely readable identifier reader arranged at the construction site; and monitoring a flow of remotely readable identifiers at the construction site based on the tracking data.

A method, computer system, and computer program product are provided for generating personalized knowledge session content using a generative machine learning model. User profile data of a plurality of users and service description data that is descriptive of a service are processed to assign the plurality of users to a plurality of user groups. A personalized message is generated for each user group based on the user profile data and the service description data, wherein the personalized message is generated using one or more machine learning models. Each personalized message is provided to each user group and feedback data is collected based on the providing of each personalized message. Based on analyzing of the feedback data, one or more of: the user profile data, the one or more machine learning models, and the service description data are updated.

The application discloses a kind of dynamic self-adapting recommendation strategy optimization methods for business handling failure scene, it is related to business handling recommendation and intelligent decision-making technical field, first, it is collected to handle the whole process of business multi-class data, with 100 millisecond / second frequency guarantee complete real-time;With decision tree and bayesian network fusion algorithm attribution, direct and indirect reasons are clear;Integrate data to build user portrait, mine potential and subsequent demand;Based on attribution and portrait generation recommendation scheme set, priority and form are adjusted in combination with scene characteristics;Feedback data is introduced, and the strategy weight is optimized using gradient descent algorithm, and the scheme is updated regularly;Set multi-dimensional index weighted evaluation effect, not up to standard then emergency optimization;Establish distributed strategy library, and reuse similar scene optimal strategy using K nearest neighbor algorithm.The application realizes accurate positioning and personalized recommendation of failure causes, and the recommendation effect is continuously optimized with data accumulation, and is suitable for multiple business types and user groups.

The application discloses a generalized shared energy storage optimization configuration method and system based on fuzzy chance constrained programming, relates to the technical field of electric power, considers the operation characteristics of various generalized energy storage resources, and respectively models the energy storage, wherein the base station energy storage model needs to consider communication load communication quality and base station power supply reliability, the air conditioner model needs to consider user comfort, and the electric vehicle charging station model needs to consider user driving characteristics, so that the existing large number of idle multi-energy generalized energy storage resources are fully tapped, and the generalized shared energy storage optimization configuration model considering multiple uncertainties is designed. The shared energy storage operator and the user group form a cooperative alliance by transferring the energy storage use right, the generalized shared energy storage optimization configuration model is decomposed into two sub-problems of alliance energy consumption cost minimization and internal payment negotiation based on Nash bargaining theory, and the risk brought by the parameter uncertainty of the user group source and load output and virtual energy storage is quantified based on the fuzzy chance constrained programming theory.

The invention relates to the technical field of industrial internet, artificial intelligence and human-computer interaction, in particular to an industrial internet software intelligent customer service interaction method based on multi-modal deep fusion. According to the method, an intelligent customer service system integrating natural language processing, a voice technology, computer vision and augmented reality (AR) is constructed aiming at the characteristics of complex operation, multiple user groups, high problem speciality and the like in an industrial scene. The core of the method is that operation questions, interface states and potential faults of engineers in software use are accurately understood through multi-modal input; an accurate solution is generated in combination with the knowledge graph of the industrial software and the real-time data of the equipment; a 3D virtual expert image is driven, and immersive and scene-based guidance is provided by fusing voice explanation, interface marking guidance, AR superposition demonstration and operation demonstration videos. The method has the working condition self-adaptive capability, can identify the professional level (such as a green hand / expert mode) of a user, and adjusts the explanation depth; and cross-region collaboration is supported, a plurality of users are allowed to synchronously share a guidance picture of a virtual expert, and efficient remote collaboration troubleshooting is realized. The method solves the technical problems that traditional industrial software is slow in customer service response, abstract in guidance, difficult to process complex problems on site and the like, and operation and maintenance efficiency and user experience are remarkably improved.

The invention provides a multi-agent collaborative MCP registration, authorization and execution method based on a block chain, and relates to the technical field of artificial intelligence, the method comprises three parties of an MCP provider, an LLM provider and a terminal user, and MCP registration, joint authorization and trusted execution are realized through an intelligent contract. Comprising the steps of registering MCP metadata uplink, applying for authorization for a user-LLM combination, initiating double-signature calling by the LLM, verifying a contract and triggering execution, and returning a result and updating a state by Oracle. According to the method, decentralization, multi-agent collaboration, verifiability of MCP calling full links and accurate definition of rights and responsibilities are realized, fine-grained authority control and automatic expense settlement are supported, compliance supervision requirements of GDPR, HIPAA and the like are met, bottom support is provided for large-scale and secure calling of external services by a large model, and multi-scene application of SaaS, API markets and the like is adapted.

A method implemented by one or more processors and comprising: Receiving a request, wherein the request is entered by a user via a user interface input device of the user's computing device; identifying response documents in response to the request, wherein the response documents include access-restricted documents of the user, the access-restricted documents being accessible only to the user and any limited group of other users specified by the user; identifying one or more request attributes for the request; for each of several of the access-restricted documents: identifying one or more document attributes for the access-restricted document;and generating a query-dependent measure for the access-restricted document based on measures of past interactions between the query features and the document features, wherein each of the measures is based on a set of past interactions by corresponding users with other documents exhibiting one or more of the document features, when the other documents were presented in response to corresponding queries exhibiting one or more of the query features, and wherein the other documents include several inaccessible documents that the user cannot access; using the query-dependent measures for the access-restricted documents to determine a presentation order for the response documents;and providing one or more of the response documents in response to the presentation request based on the presentation order, the presentation being made via a user interface output device of the computing device.

The application relates to the field of real-time translation, and provides a real-time duplex translation method based on multi-channel parallel processing and a corresponding product.The method comprises the following steps: collecting multi-channel voice signals of at least two user groups in real time through a group of audio acquisition modules respectively; dynamically adjusting beam forming parameters of each audio acquisition module in the group of audio acquisition modules based on a sound source positioning result and feeding back to the corresponding audio acquisition module; monitoring voice activity of each audio channel corresponding to each audio acquisition module; when the voice activity of any audio channel reaches a predetermined condition, automatically activating a translation processing procedure of the audio channel and keeping the remaining audio channels in a monitoring state; using a parallel processing mechanism for the voice signals of the activated audio channel, simultaneously performing real-time translation of the currently activated audio channel and voice activity monitoring of the remaining audio channels; and transmitting the translation result of the current speaker to other users participating in the conversation in the user group, so that multi-channel data is synchronously coordinated.

The embodiment of the invention provides a page color system adjusting method and device, electronic equipment and a storage medium. The page color system adjusting method comprises the steps that page behavior data of a current user is collected; calculating the behavior similarity between the current user and each preset user group based on the page behavior data of the current user and the page behavior data of each preset user group; based on the behavior similarity between the current user and each preset user group and the preference degree of each preset user group for each preset page color system, determining a target page color system from each preset page color system; and adjusting the current page color system used by the current user to the target page color system. According to the page color system adjusting method, the problems of poor visual effect, inconvenience in use and the like caused by the fact that a user needs to manually select a page color system of an existing webpage are solved.

The invention discloses a service traffic prediction method and device, a network element, a computer storage medium and a program product. The method comprises the steps of obtaining traffic data of a plurality of applications, dividing application categories to which the applications belong based on the traffic data of each application, and generating a classification list according to a division result; obtaining user information and application use data of the user, dividing user groups to which the user belongs based on the user information and the application use data, and determining a portrait label corresponding to each user group; determining first traffic consumption of the first user in the historical specified time, determining second traffic consumption of a first user group to which the first user belongs in the historical specified time, and determining a first coefficient based on the first traffic consumption and the second traffic consumption; and predicting the service traffic of the first user according to the first coefficient, the classification list and a first portrait label corresponding to a first user group to which the first user belongs, and generating service traffic prediction information.