292 results about "User oriented" patented technology

A method for facilitating conversational interaction with users to help the users includes transmitting a conversational interaction interface for conversationally interacting with a user to a user device, receiving a request of the user through the conversational interaction interface from the user device, identifying an information based on the request, generating an input comprising the request and the information for a machine learning model based on the request and the information, processing the input using the machine learning model, generating a response for the request based on the processing of the input, transmitting the response through the conversational interaction interface for conversationally interacting with the user to the user device, and storing the machine learning model, the request, and the response.

The invention provides a Prompt prompt template automatic construction method for an intelligent reimbursement system, and belongs to the technical field of intelligent financial management. Comprising the steps of obtaining form structure information of a current reimbursement receipt, extracting field attributes, control configurations and business rules in a main table and a sub-table, and constructing a field semantic model; collecting context information in a user filling process, and generating a context semantic model; identifying a user intention in a current form filling stage, and determining a corresponding prompt task type; matching the target template structure from a preset template library, and generating a structured natural language Prompt prompt template; and transmitting the generated Prompt prompt template as input to a large language model agent, and driving the large language model agent to generate user-oriented intelligent prompt content. By constructing the field and context bilingual model, automatic and personalized generation of the Prompt prompt template is realized, and the accuracy, adaptability and user experience of large model prompt in an intelligent reimbursement system are remarkably improved.

The invention provides a method, system and device for achieving industry knowledge questions and answers based on a large model and a medium, and belongs to the technical field of artificial intelligence. The method comprises the steps that standard answers of industry experts are collected for questions with the occurrence frequency higher than a threshold value in a target industry, and a standard answer library is constructed; collecting professional knowledge related to the target industry, and constructing an industry knowledge base; responding to a target question, input by a user, of a target industry on a front-end interface, matching a standard answer library and a retrieval industry knowledge library according to the target question, when a return result exists, constructing a cue word according to the return result, and when the return result does not exist, constructing the cue word according to the retrieval industry knowledge library; according to historical multi-round dialogue information of the user on the front-end interface, cue words are constructed and provided for the general large model; and returning a knowledge question and answer result output by the general large model to the user through a front-end interface. By constructing the standard answer library and the industry knowledge library and combining the general large model, intelligent answering of the industry questions is achieved, and the accuracy and specialty of question answering are improved.

The invention provides a method for debugging an intelligent agent through computing power of an intelligent computing center, which comprises the following steps: S1, a debugging intelligent agent receives task information provided by a user through an interactive interface, and the task information is used for indicating to debug a debugged object; the debugged object is a debugged intelligent agent or a function module or a tool function of the debugged intelligent agent; s2, the debugging agent determines a debugging requirement according to the task information; s3, the debugging agent determines a debugging method according to the debugging requirement, deploys a debugging environment according to the debugging method, generates a running instruction and debugs the debugged object; s4, the debugging agent obtains the operation information of the debugged object and analyzes the operation information, and whether the debugging requirement is met or not is evaluated according to the analysis result; s5, if not, the debugging agent checks the code of the debugged object, modifies the code according to the check result, and returns to the step S3 until the condition is met; and S6, the debugging agent feeds back a debugging result to the user through the interactive interface.

The invention relates to the technical field of artificial intelligence and software development, in particular to a DevOps assembly line intelligent generation system based on natural language description. According to the intelligent generation system for the DevOps assembly line based on the natural language description, an interaction layer is responsible for visually editing an interaction interface and outputting a generated executable script and a flow chart to a user; the intelligent processing layer takes Python and Go as development languages, fuses a knowledge graph technology, supports a dynamic code generation capability and realizes intelligent business process management and automatic execution; the infrastructure layer comprises three core modules, namely a metadatabase, a sandbox environment and an execution engine, and is responsible for providing basic support and resource guarantee for system operation. According to the intelligent generation system for the DevOps assembly line based on the natural language description, the configuration threshold of the DevOps assembly line is remarkably reduced, the cross-platform compatibility is ensured, the safety and reliability of the assembly line are greatly improved, and production accidents caused by manual configuration errors can be effectively avoided.

An extended Reality (XR) system is provided that enhances user interaction within XR environments. The XR system captures tracking data using one or more sensors, including hand tracking data of a user's hand and pose data of the XR system itself. By continuously capturing this data, the XR system dynamically generates a hand-located user interface that includes interactive virtual objects associated with specific locations on the surface of the user's hand. Additionally, the XR system generates labels for the interactive virtual objects that are dynamically oriented toward the user as the user moves their hands and head when interacting with an XR environment.

The invention relates to the technical field of large language models, and provides a user preference oriented instruction tuning data selection method, which comprises the following steps of: performing supervision and fine tuning on a pre-trained large language model to obtain a supervision and fine tuning large language model; constructing a preheating preference data set optimization supervision fine tuning large language model; generating a basic candidate response of the verification instruction through a basic candidate model, and generating a preference candidate response of the verification instruction through a preference candidate model; performing evaluation according to the evaluation model, and constructing a preference pair set according to an evaluation result; calculating a preference gradient by using a preference loss function to obtain a bidirectional user preference gradient; and scoring the training data, selecting a training data set according to the score, and performing fine tuning on the direct preference large language model to obtain an optimized large language model. According to the method, the matching degree of the selected data and the target task can be remarkably improved, and the generalization ability of the instruction fine tuning model on the target task is improved.

The invention relates to the technical field of information processing, in particular to a user-oriented multi-tenant security enhancement service isolation system, comprising: at least one tenant, each tenant having an independent namespace, at least one corresponding service, at least one corresponding node, and a network storage space; the public node pool comprises a plurality of public nodes, and firewalls are arranged between the public nodes and the nodes corresponding to the tenants; and the resource controller is used for dynamically adjusting the resources of different tenants. A safe isolation environment of computing resources, storage resources and network resources is constructed in a mode of combining soft isolation and hard isolation, safe and efficient resource intensive management of a multi-tenant environment is realized, a resource adjustment mode of each tenant is determined according to index data of each tenant, tenant resources are automatically and dynamically allocated, and the resource utilization rate is improved. And the business isolation requirements of the tenants are met on the premise of ensuring the system stability and security.

Methods, systems, and apparatuses include receiving input, from a user of an online system, via a chat interface. A set of facets is determined for the input using data for the user. An embedding is generated for the input. Content item embeddings are retrieved. The content item embeddings are filtered using the determined set of facets. A set of relevant content items is determined using the input embedding and the filtered content item embeddings. A response prompt is generated using the input embedding and the set of relevant content items. A response is generated by applying a generative machine learning model to the response prompt. The generated response is sent to the user via the chat interface.

The invention is applicable to the field of power demand analysis, and provides a user demand-oriented power transaction matching recommendation method and system. The method comprises the following steps of: acquiring power consumption data of a user, and generating a resonance group and a feature packet with similar power consumption modes and risk tolerance; generating a power utilization comprehensive bidding plan in combination with the resonance group characteristics and the real-time market data; performing transaction matching based on the bidding plan, preferentially selecting the power generation resource with the closest electrical distance, introducing a green energy premium coefficient, and outputting a transaction result; and performing investment portfolio optimization analysis according to a transaction result, and generating a customized power package containing traditional energy, new energy and stored energy in combination with user risk preference. Through multi-dimensional data integration and intelligent algorithm application, accurate matching of power generation resources and user demands is realized, power transaction efficiency and user satisfaction are improved, and new energy consumption and sustainable development of the power market are promoted.

A data platform monitors a compute environment by performing multi-stage heuristic analysis of event data representing a plurality of events occurring within the environment. The platform utilizes multiple event analyzers, each configured according to a distinct analysis heuristic, to evaluate different subsets of the event data and generate corresponding output signals. A higher-level event analyzer applies a further heuristic to the multiple output signals to generate a composite alert signal, indicating whether the combination of analyzed events collectively represents a security intrusion or other anomalous condition of sufficient severity to warrant alerting. Based on the composite alert signal, the platform performs an alert-based operation, such as generating a user-facing alert, initiating an automated mitigation, or updating a contextual model of system behavior. By combining the analytical outputs of heterogeneous heuristics, the disclosed architecture enhances the accuracy and contextual relevance of automated intrusion detection within complex computing environments.

Systems and methods are disclosed for driver assistance. In one example a method for an advanced driver alert system for a vehicle comprises monitoring, via a user-facing camera, facial movement of a user over time. The method includes determining a plurality of facial movement metrics based on the facial movement over an adjustable time window, transforming the plurality of facial movement metrics into a machine readable representation of the adjustable time window, and determining, via a code reading model, one or more user requests based on the machine readable representation of the facial movement metrics. The method includes executing one or more user assistance operations based on the determined user requests.

The business travel service management method based on the LLM is applied to a service system constructed based on the LLM. Services provided by the service system for users comprise a plurality of service fields; the service system manages a plurality of service models in one-to-one correspondence with a plurality of service fields; comprising the following steps: receiving a user question related to business travel service input by a user; retrieving target structured knowledge from a target sub-knowledge base related to the user questions in a plurality of sub-knowledge bases in one-to-one correspondence with the plurality of service fields, and acquiring historical context information from historical user questions input by the user; generating a cue word based on the user question, the target structured knowledge and the historical context information, and inputting the cue word to an LLM, so that the LLM generates structured intention description information based on the cue word; and analyzing the intention description information, determining a target service field corresponding to the user intention, and distributing the user question to a target service model corresponding to the target service field.

The embodiment of the invention provides a ship industry standard document intelligent processing method, which comprises the following steps: S1, document analysis: carrying out structured analysis and restoration on a ship industry standard document to generate a structured text supporting vectorization storage and semantic retrieval; s2, database construction: constructing a document vector index database based on the structured text to form a semantic retrieval task-oriented efficient data structure; and S3, content retrieval: performing user-oriented query, constructing a semantic retrieval mechanism, and completing high-precision matching from a natural language problem to a structured document content and result return. According to the embodiment of the invention, the document structure can be accurately restored, the content segmentation is more reasonable, the retrieval matching is more accurate, the retrieval result has more content depth, the technical path is clear, and the project landing is easy.

Various implementations disclosed herein include systems, methods, and apparatuses for automatically generating a customizable virtual interface embedded in a platform. For example, a specialized interface configured to provide communications between a user and the electronic device may be presented in response to a single executed action and in response to a prompt from the user executed via the specialized interface, sensor and apparatus design data associated with generating a virtual interface is obtained from external systems. The virtual interface is configured to enable actions associated with enabling the user to create a specialized structure. The process may further generate the virtual interface embedded in a platform based on the sensor and apparatus design data and may include potential configurations of the specialized structure. 3D renderings of the plurality of potential configurations of the specialized structure may be presented to the user via the virtual interface.

The invention provides a method for realizing agent memory system development through computing power of an intelligent computing center. The method comprises the following steps: S1, a memory system development agent receives task information provided by a user and used for constructing a target agent memory system; s2, determining a development demand of the memory system according to the task information in combination with a large language model method and a user; s3, determining a design scheme of the memory system according to the development requirements in combination with a large language model method; s4, generating codes of the memory system according to the development requirements and the design scheme in combination with a large language model method; s5, deploying a debugging environment and codes of a debugging memory system in combination with a large language model method; when the debugging result indicates that the memory system does not meet the debugging requirement, the design scheme and codes of the memory system are checked in combination with the large language model, the step S3 is executed if the design scheme needs to be modified, and the step S4 is executed if the codes need to be modified until the debugging requirement is met; and S6, feeding back result information to the user through the interactive interface.

The invention provides a trusted data space platform and a fusion base thereof, in one embodiment of the trusted data space platform, a system architecture comprises a fusion base layer, a capability supporting layer, an application service layer and a global monitoring layer from bottom to top; the fusion base layer is a base support of a trusted data space, internalizes a space-time code and a digital network into a bottom layer protocol rule, and externally embodies a function service related to a right root; the capability supporting layer is used for forming basic capability of the trusted data space platform with the fusion base layer and directly carrying out interactive activities facing a user, the interactive activities are triggered by a data connector on a user side, and the data connector serves as an engine of the trusted data space platform; the application service layer provides data service for each application field; and the global monitoring layer is used for realizing global credible and controllable monitoring and analysis. Clear data ownership and credible data circulation are guaranteed from a global level, and large-scale circulation of data elements is supported.

The invention provides a user portrait-oriented label list automatic generation method and system, and relates to the technical field of label management, and the method comprises the steps: firstly obtaining basic right attribute data and right use behavior data of a target user; secondly, determining a static right label of a target user through the basic right attribute data; then, according to the right and interest use behavior data, extracting implicit preference chains and explicit behavior characteristics of a target user in different right and interest use scenes, and further constructing dynamic right and interest tags of the target user in different right and interest use scenes through the implicit preference chains and the explicit behavior characteristics; and further, when it is detected that the right tag of the target user triggers an updating condition, automatically generating a tag list of the portrait of the target user based on the static right tag and the dynamic right tag. By adopting the scheme, the user portrait-oriented label list can be generated based on the static characteristics and the dynamic characteristics of the user rights and interests.

The invention discloses a user-oriented personalized game plot recommendation method and a user-oriented personalized game plot recommendation system, and relates to the technical field of personalized games. Game hobby features of a user are determined based on recognition of previous game events of the user; according to the method, the corresponding game content frame is determined based on the game hobby characteristics of the user, the identity information of the user and the current scene where the user is located, and the corresponding personalized game plot is constructed according to the synthesis of the game content frame and the game style selected by the user, so that the high matching of the personalized game plot is realized. Therefore, when the user is in the game time period, the personalized game drama is recommended to the current APP of the user; according to the embodiment of the invention, the switching of the current APP of the user is triggered according to the click of the user on the personalized game plot, and the user enters the virtual scene of the personalized game plot, so that the one-key switching of the user in the game time period is realized, and the user can better experience the personalized game plot in an immersive manner.

The invention discloses a transfer travel planning method, which is applied to a service program constructed based on LLM. Comprising the following steps: in response to a direct travel planned for a user, generating at least one guide tag in real time based on target data related to a transit travel demand of the user; the at least one guide label is used for guiding a user to carry out transfer route planning; the guide tag is a composite tag which is composed of a plurality of basic tags and can represent the transit travel demand of the user; outputting and displaying the at least one guide label to the user in an itinerary planning interface; and in response to a selection operation of a user for any target guide tag in the at least one guide tag, further inputting the target guide tag to the LLM, performing reasoning calculation by the LLM based on the target guide tag, planning a transfer travel having the same travel information as the direct travel for the user, and sending the transfer travel to the user. And outputting and displaying the planned transfer travel to a user through a travel planning interface.

The invention provides a technical supervision document retrieval method and a related device, and belongs to the field of technical supervision document retrieval. The method comprises: acquiring a user query intention; retrieving from a database according to the query intention of the user to obtain a natural language answer facing the user question; the database construction method comprises the steps of obtaining an existing technical supervision document; performing analysis and knowledge extraction on the technical supervision document to obtain a knowledge multi-tuple; after the knowledge multi-tuple is verified, time dimension attributes are added to the knowledge multi-tuple; and respectively storing the knowledge multi-tuples added with the time dimension attributes according to data types to obtain a database. According to the technical supervision document retrieval method and device, the problem of low accuracy of technical supervision document retrieval is solved.

The invention relates to the technical field of intelligent peripherals, in particular to a user-oriented interaction information expansion method, which comprises the following steps that: each keycap acquires displacement and pressure, generates an event packet, uploads the event packet through an optical wireless link, and obtains a clock and supplies power; constructing a keycap graph by a master controller, obtaining an intention vector through graph convolution and pooling, inputting the intention vector into a cyclic network to generate a pixel matrix and a phase matrix, and downlink after Bernoulli sparse coding; performing key cap side orthogonal matching pursuit decoding and four-round gradient optimization, and outputting a differential pixel set, a differential phase set and a synchronization mark; the master control refreshes the digital micromirror array and the ultrasonic phased array in a differential manner, locks a frame-level time sequence through a synchronization pulse, compensates link delay and hardware drift in real time based on Kalman filtering, and keeps an optical-acoustic alignment error to be less than 100 microseconds; degradation monitoring enables a link to be automatically switched to a pre-carved character layer and to be quickly recovered when the link is abnormal, and a keyboard interaction information expansion scheme with low delay and high consistency is provided.

The invention discloses a simulated inquiry interaction analysis method, device and equipment based on man-machine conversation, and relates to the technical field of artificial intelligence and medical treatment, and the method comprises the steps: obtaining inquiry conversation data generated by interaction between a user object and a virtual user; performing multi-dimensional interaction analysis on the inquiry dialogue data based on a preset medical knowledge graph and preset diagnosis information to generate a corresponding evaluation index and a corresponding index score; and generating and outputting an evaluation report containing the index score and the user object-oriented inquiry dialogue improvement suggestion. According to the method, the objectivity and the accuracy of an evaluation result are ensured, prejudice and inconsistency caused by subjective experience difference in manual evaluation are overcome, the evaluation result is accurate, and a user can clearly know the expression level of the user in each dimension and can also obtain a targeted inquiry optimization direction.

The invention provides an intention-based task cooperation method and device, relates to the technical field of computers, and mainly aims to solve the problem that the interaction effect is affected due to the fact that complex or fuzzy instructions of a user cannot be fed back during intention-based task cooperation in the prior art. According to the main technical scheme, a user intention is determined based on input information of a user; the user intention is analyzed, a plurality of response tasks with an execution sequence are obtained, and different response tasks have different operation categories; an intelligent agent corresponding to the operation category is used for executing each response task to obtain response information, and the intelligent agent is used for querying the response information matched with the response task in a preset database; and processing the response information according to the execution sequence to obtain a response result corresponding to the user intention, and feeding back the response result to the user through the browser page.

The invention belongs to the technical field of task scheduling of a storage system, and discloses a user-mode-oriented storage task self-adaptive scheduling method and system, and a more efficient task processing framework is realized by replacing an original kernel thread-based storage task scheduling scheme with a user-mode coroutine scheduling mechanism. The multi-level priority queues are directly managed in task scheduling, and CPU core binding configuration is carried out, so that the switching delay of a user mode / kernel mode is reduced, and the task execution controllability is improved. A dual-threshold self-adaptive scheduling strategy switching technology is introduced, and a greedy scheduler and a reinforcement learning scheduler are combined, so that the problem of adaptability of a static scheduling strategy in a dynamic load environment is relieved, performance loss caused by scheduling strategy solidification is avoided, and the self-adaptive capability and service quality guarantee of a system under a complex load are improved. Compared with an existing task scheduling method based on a kernel thread, the task scheduling method has the advantages that the overall performance and the resource utilization rate of a storage system can be remarkably improved while the task execution efficiency and the SLA requirement are guaranteed.

The invention discloses a method, a device, equipment, a medium and a product for enhancing the estrus sharing ability of a virtual digital human, and relates to the technical field of human-computer interaction and virtual digital humans. The method comprises the following steps: firstly, based on dialogue data of a user, extracting to obtain multi-modal feature information for reflecting a dialogue understanding result of the user, voice emotion of the user and facial emotion of the user, and then importing the multi-modal feature information into a user real intention recognition model obtained by pre-training based on a machine learning algorithm; and finally, according to the big language model prompt word bank, combining the recognition result and the dialogue content, generating a response prompt word, and according to the prompt word, controlling the virtual digital person to carry out big language model-based common situation response to the user, so that the response content of the digital person is accurate and appropriate, and the user experience is improved. And the mood, expression and the like of the digital human can be kept consistent with those of the user, so that more real common-situation interaction experience is realized.

A robot control method includes: the first control instruction of the robot is obtained; the behavior blueprint corresponding to the first control instruction is determined, the behavior blueprint including the plurality of blueprint nodes connected according to the target sequence; and the preset functions corresponding to the blueprint nodes are executed according to the target sequence. The preset functions corresponding to the blueprint nodes may include the atomic API ability, the meta skill and the task skill. The atomic API ability is used for characterizing a specific function executed by the robot through a component, the meta skill is used for characterizing a function of an execution unit of the robot, the task skill is used for characterizing a function of user-oriented execution of a target task by the robot, the robot includes one or a plurality of execution units, and each execution unit includes one or more components.

The invention provides a label system intelligent generation system and method for user portrait construction, and relates to the technical field of portrait label generation, and the method comprises the steps: setting a label layering rule corresponding to a dynamic behavior of a target user according to inherent attribute data; determining common behavior identifiers corresponding to a plurality of common behavior states of the target user for the state transition node of the target user behavior through a label layering rule; identifying a behavior association probability in the common behavior identifier, actively adapting to a business conflict trend in all common behavior states according to the behavior association probability, obtaining a behavior tolerance value of the common behavior states, and further determining a behavior confidence coefficient of the target user; and updating a user tag directory of the target user during actual service adjustment according to the behavior confidence, and outputting a newly-added portrait tag oriented to the user portrait. According to the invention, layered verification can be carried out on the updating process of the user portrait label, so that the accuracy of the newly added portrait label is improved.

The invention discloses a lightweight security protection method for file permission access in a localization scene, and belongs to the technical field of information security and localization system security. According to the method, the attack process is effectively delayed and automatic attacks are blocked through three aspects of technologies, including file access interception and underlying authority control, virtual Shell hiding and induction, and external command hiding and path migration. Meanwhile, a set of user-oriented file permission access and Shell obtaining and approving system is formulated, a set of file permission access management and control mechanism is formed, and safety energizing and force applying are carried out on a localized system. According to the lightweight security protection method, the limitation of a traditional method is broken through, a security policy is embedded into a file system and a command path, the lightweight security protection method is suitable for a domestic system in a specific scene, and on the premise that normal users and operation and maintenance process availability are guaranteed, attack chain execution can be effectively delayed, automatic attacks are prevented, and system security is enhanced.

The application discloses a cloud desktop throughput prediction method for cold start and mode forgetting, comprising the following steps: step 1, similarity attention federated learning assisted training; step 2, throughput prediction for safe cold start in the initial stage of a new user; step 3, fluctuation-residual feature extraction based on a TDLinear network model; step 4, model updating based on an adaptive memory module and EWC; and step 5, throughput prediction for training forgetting in the long-term use stage of a user. Through a federated learning algorithm, the existing throughput historical use knowledge of other users is utilized to assist training under the premise of guaranteeing user data privacy. Old modes are continuously reviewed based on continuous incremental prediction, and a memory module is designed to incrementally update new modes, so that the occurrence of forgetting in training is avoided, and the advantages of two stages are combined to realize the throughput prediction of a cloud desktop user in the whole life cycle.