100 results about "Response method" patented technology

The invention discloses an intelligent reply method for an electric power marketing inspection work order. The method comprises the following steps: S1, obtaining work order data of a current inspection work order and a multi-dimensional capability index of a current business person to construct a state vector; s2, inputting the state vector into a pre-trained hierarchical reinforcement learning model, and outputting a decision instruction containing a high-level strategy instruction and a bottom-layer reply action; s3, determining a target interaction mode from a plurality of preset interaction modes based on the high-level strategy instruction; s4, displaying a corresponding reply auxiliary information set on a user interface based on different target interaction modes, and receiving actual operation of a user; the auxiliary information set is generated based on bottom-layer reply actions; and S5, calculating a reward value based on an actual operation result, and updating the hierarchical reinforcement learning model by using the reward value. According to the invention, capability states and work order characteristics of business personnel can be dynamically sensed, and real personalized intelligent assistance is provided.

The embodiment of the invention provides an intelligent reply method and device, computer equipment and a storage medium, and belongs to the technical field of artificial intelligence. The method comprises the steps of obtaining a target question initiated by a target object, and obtaining user behavior data, user portrait data and current dialogue data of the target object; performing emergency degree evaluation on the target question according to the current dialogue data to obtain a reply emergency degree; performing priority evaluation on the target problem according to the user portrait data and the user behavior data to obtain a problem priority; determining reply demand prediction information according to the question category, the reply emergency degree, the question priority and the current dialogue data; screening out a target customer service system from preset candidate customer service systems according to the question complexity of the target question and the reply demand prediction information; and replying the target question through the target customer service system. The method can be applied to business systems needing a large amount of data, such as financial science and technology and health medical treatment, and can improve reply intelligence, accuracy and user experience.

The embodiment of the invention provides an intelligent customer service response method and device, electronic equipment and a medium, belongs to the technical field of artificial intelligence, and is suitable for financial scenes and medical scenes. The method comprises the following steps: performing service period prediction by combining user portrait features and behavior features extracted from service interaction data to obtain a user service period state; performing product demand prediction according to dialogue features, behavior features, user portrait features and user service period states extracted from the service interaction data to obtain a product service demand degree; and sending a target service response scheme generated based on the product service demand degree and the user service cycle state to the user. According to the embodiment of the invention, the target service response scheme is generated by combining the product service demand degree and the user service period state generated by the dialogue features, the behavior features and the portrait features of the user, differentiated service strategies can be adopted for clients with different demand degrees in a proper service stage, and the intelligent customer service response effect is improved.

The invention relates to a request response method and system based on a model context protocol and related components, and relates to the technical field of data analysis, the method comprises the following steps: responding to a client to enter an information query interface, and initializing a software development kit which is at least provided with an MCP client module; establishing a connection relationship between the MCP client module and the MCP server so as to register tool information acquired from the MCP server into a tool registry of the MCP client module; receiving and analyzing a user information query request to obtain an analysis result, and calling a tool corresponding to the user information query request according to the analysis result and the tool registry to obtain structured service data; and processing the structured service data, generating response information of the user information query request, and displaying the response information on the client. The development efficiency and the user query efficiency are improved, and the maintenance cost is reduced.

The application relates to a government affair cross-domain collaborative response method and system based on a large model and RPA dynamic arrangement. The method converts user appeal into structured instructions by adopting a domain fine-tuning large language model through an intention decoupling module; then, a reinforcement learning agent hub in a dynamic assembly module is generated according to the instruction and the real-time state of an RPA cluster, and a dynamic scheduling strategy is output; further, a cross-domain execution module drives an RPA robot to interact with a heterogeneous government affair system in a non-intrusive manner to execute a task according to the strategy; finally, a work order derivation module generates a standard work order by using a conditional generative adversarial network (cGAN) to aggregate returned data. The application has the beneficial effect that the constructed cognitive-to-execution automation closed loop can effectively improve the efficiency, accuracy and flexibility of government affair services while ensuring the safety of existing systems.

Method for selecting source data for generating a response. The invention relates to a method for selecting at least one source data item made available by a data provider (Fourn), said source data being suitable for generating a response to a request from a client agent (Agt) associated with a large language model (LLM). The method comprises: - receiving (E30) from the client agent (Agt) a request and a certificate associated with a statement from the client agent regarding the request, - calculating (E40) a vector representing the received request and statement, - selecting (E40) the at least one source data item by comparing a vector representing the source data, used for generating a response to the request and also representing a constraint on the use of the source data, with the calculated vector. Abstract figure: Figure 1

To improve the accuracy of responses to users who make inquiries about a predetermined service. [Solution] An inquiry answering system (1) includes an inquiry information acquisition unit. The inquiry information acquisition unit (103) acquires inquiry information related to an inquiry from a user for a predetermined service. The classification information acquisition unit (102) acquires classification information related to a classification related to the inquiry, which is a classification predetermined for the service. The model answer acquisition unit (103) inputs the inquiry information and the classification information into a large-scale language model, and acquires a model answer related to the classification generated by the large-scale language model and a confidence level of the classification. An output control unit (104) controls output of the model answer based on the confidence level.

The invention provides a heat supply customer service response method and device, equipment and a medium, and relates to the technical field of management. Determining priority levels of the consultation questions based on the consultation questions; based on the candidate customer service data corresponding to the consultation question and the priority level of the consultation question, determining customer service personnel for processing the consultation question; and the processing result fed back by the customer service staff is received, and the processing experience of the customer service staff is updated based on the processing result, so that accurate matching of the problem and the customer service staff is realized, and the overall service efficiency is improved.

To accurately perform corresponding processing for identifying a pair of mutually corresponding information in two pieces of sequence information.SOLUTION: A corresponding device includes: a question generation unit configured to receive a first language text and a second language text as input and generate a span prediction problem between the first language text and the second language text; and a span prediction unit configured to predict a span to be an answer to the span prediction problem generated by the question generation unit, using a span prediction model created using data consisting of span prediction problems between first and second languages and their answers.SELECTED DRAWING: Figure 1

The present disclosure provides a request response method and device, computer equipment and storage medium, the method comprises: in response to receiving the network service request initiated by the target application in the service logic layer of the terminal equipment, based on the request model object indicated by the network service request, determine whether there is a target interface simulation entity corresponding to the network service request; the target interface simulation entity is used to simulate the response result corresponding to the network service request returned by the data access layer of the terminal equipment through the interface; in the case where the target interface simulation entity exists, based on the request model object, the target interface simulation entity is used to determine the simulation response result corresponding to the request model object; based on the simulation response result, the simulation response model object corresponding to the request model object is generated, and the simulation response model object is called back to the service logic layer, so that the target application executes the operation corresponding to the network service request according to the received simulation response model object.

The application provides a gas intelligent customer service response method, and relates to the technical field of gas intelligent customer service, and comprises the following steps: receiving a query request input by a user, retrieving structured data and / or unstructured data corresponding to the query request from a gas industry knowledge base, and generating retrieval enhanced data; the gas industry knowledge base comprises gas user information, gas equipment information, gas safety specifications and operation processes; based on the query request and the retrieval enhanced data, a corresponding natural language reply is generated, and the natural language reply is output to a user terminal. The application retrieves the gas industry knowledge base, including safety specifications, equipment information and operation processes, converts structured and unstructured knowledge into retrieval enhanced data, realizes deep integration of the knowledge base, solves the problem of inconsistent decision-making caused by the dependence on manual experience reply after the existing system reads the query request, and realizes machine intelligent response.

To provide a consultation response system for achieving more appropriate consultation.SOLUTION: The consultation response system 1 realizes an input device 12 that receives the content of the consultation from the user, a user feeling estimation unit 111 that estimates the feeling of the user by inputting the content of the consultation to a predetermined machine-learning model, a response generation unit 11,14 that generates a response to the user based on the analyzed feeling of the user and predetermined machine-learning model AI, and an output device 13 that outputs the generated response. The response generation unit inputs the content of the consultation received by the input unit to the predetermined machine learning model to estimate the feeling of the user from the content of the consultation, and generates the response on the basis of the estimated feeling of the user, the learned response method, and the content of the consultation.SELECTED DRAWING: Figure 1

The invention discloses a customer service response method and device, and the method comprises the steps: taking the last sentence of user response of a current dialogue as an end point, carrying out the slicing processing of the current dialogue according to M sliding windows with variable sizes, obtaining M slices, and enabling the last sentence of each slice in the M slices to be the last sentence of user response; calculating the similarity between the M slices and a plurality of historical slices in a database, and determining N historical slices similar to the M slices and N historical response expressions of the N historical slices; the historical slices are obtained by taking any sentence of user response in the historical dialogue as a terminal point and performing slicing processing according to a sliding window with a variable size; and according to the N historical response expressions, determining a customer service response expression enabling the current dialogue to realize the dialogue target. By adopting the method, the accuracy of customer service response can be improved.

This application relates to the field of natural language processing technology, and discloses an assistant dialogue response method, apparatus, device, and storage medium. The method includes: generating metadata for the Nth round of dialogue at the end of the Nth round; the metadata for any round of dialogue includes a summary of the current round's dialogue and an assessment of the impact of the current round's dialogue on the dynamic context; updating the dynamic context of the (N-1)th round of dialogue based on the metadata of the Nth round's dialogue to obtain the dynamic context of the Nth round's dialogue; and generating an assistant response for the N+1th round of dialogue in response to user input in the N+1th round's dialogue, based on the dynamic context of the Nth round's dialogue, the historical dialogues within the dialogue window, and the corresponding metadata. Thus, by updating the dynamic context of the dialogue, persistent memory of key information is achieved in long dialogues, improving the accuracy of the generated assistant responses.

The embodiment of the invention relates to a response method, a medium and a program product, and the method comprises the steps: responding to a received first text to be responded, and generating a second text used for responding to the first text through a preset network model; when it is detected that the second text contains a target identifier, determining a to-be-triggered target event corresponding to the target identifier based on a mapping relationship between a preset event triggering identifier and a to-be-triggered event, and triggering and executing the target event; wherein the target identifier is an event trigger identifier in a preset event trigger identifier set; determining a response text corresponding to the first text based on the type of the target event and reference information; wherein the reference information comprises contents, except the target identifier, in the second text and / or an execution result of the target event. According to the embodiment of the invention, the reliability of the response result and the dialogue service quality are greatly improved.

Provided are an answer providing server device that provides an answer to a consultation, an answer program, an answer method, a learned model, a model learning device, a model learning method, and a model learning program.SOLUTION: The answer providing server 8, which is a robot attorney, includes a reception processing unit 81A that receives the consultation data-item, a determination unit 81C that determines whether to answer the consultation data-item by using the learned model or the logic chart, and an answer processing unit 81D that answers the consultation data-item by using the learned model when it is determined to answer the consultation data-item by using the learned model, and answers the consultation data-item by using the logic chart when it is determined to answer the consultation data-item by using the logic chart. The answer includes contents indicating to which article of which law the consultation contents determined by the consultation data correspond.SELECTED DRAWING: Figure 2A

The invention discloses a data request response method and device, electronic equipment and a storage medium, and the method comprises the steps: receiving a data request sent by a client, wherein the data request carries a resource identifier, a client cluster mapping version number, a lock version and a monotonic clock value; querying a corresponding effective version interval, a maximum lock version and a monotonic clock value corresponding to the maximum lock version in a locally maintained version record according to the resource identifier; determining whether the data request is an expired request according to one of the first comparison result, the second comparison result and the third comparison result; the first comparison result is a comparison result between a client cluster mapping version number and an effective version interval, and the second comparison result comprises a comparison result between a lock version in the data request and a maximum lock version and the first comparison result; the third comparison result comprises a comparison result of the monotonic clock value in the data request and the monotonic clock value corresponding to the maximum lock version and the second comparison result; an expired data request is intercepted.

The invention discloses an e-commerce customer service response method and device based on an agent, equipment and a storage medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: carrying out the intention classification processing of a commodity dialogue text sent by a user side, so as to obtain a processed text, a historical inquiry text, a user preference record and a historical response answer corresponding to the processed text of the user side are obtained through a preset memory network model, intention correction processing is carried out on the processed text, a corrected text is obtained, and an intention association relation matrix corresponding to the corrected text is constructed; determining a target routing policy from preset routing policies based on the intention association relationship matrix, and calling a target agent to generate an initial response policy based on the target routing policy; and auditing the initial response strategy by using a preset conflict cutting mechanism, and determining the initial response strategy passing the auditing as a target response strategy so as to respond to the commodity dialogue text based on the target response strategy. In this way, the intellectualization of e-commerce customer service can be realized.

The application relates to the technical field of intelligent response to comment crisis, and discloses an intelligent response method and device for comment crisis, electronic equipment and a storage medium, wherein the method comprises the following steps: through deep semantic analysis and clustering of multi-source comment data, independent crisis event entities can be accurately and efficiently identified and aggregated from noise information; through construction of a time sequence social communication network model and quantification of user node influence, scientific prediction and evaluation of crisis diffusion trend and intensity are realized, so that a crisis index can more accurately reflect the severity of an event; and in combination with cultural characteristics related to the event and the crisis index, a first-level response language suitable for the event is dynamically generated.The application has the beneficial effect that the response strategy is improved in pertinence, timeliness and cultural suitability, so that a subject can more actively and effectively manage and resolve online comment crisis, and automation and intelligentization of a main process from identification to response are realized.

The invention relates to a response method and device based on charging intelligent customer service dialogue state tracking, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring a predefined intention slot structure definition set and a historical dialogue data set, and inputting the intention slot structure definition set and the historical dialogue data set into a graph neural network model to generate a state graph structure; obtaining semantic input content of a user in a current round, generating a node context sensing embedding set and a node semantic response intensity set in combination with the initial node embedding set, and determining candidate state scores in combination with a platform service state set and a node frequency scalar set; generating candidate state sub-graphs and candidate state score vectors according to the candidate state scores; and executing graph neural network propagation on the candidate state sub-graph, and determining a current dialogue state, a corresponding slot set and a state propagation path to generate a response strategy for responding to the semantic input content. By adopting the method, the accuracy of the response to the user request can be improved.

The invention relates to the technical field of artificial intelligence and information, and particularly discloses an intelligent interaction and accurate response method and system for legal questions and answers. The method comprises the following steps: receiving and analyzing user consultation, and determining a cause of action and facts; calling a legal element map corresponding to the cause of action, wherein the map defines a logic prerequisite relationship among elements in a directed graph structure; matching facts with map nodes, and initializing node states; dynamically deciding a questioning target based on the graph topology and the node state; asking information is generated and presented, a reply is received, and the state is iteratively updated until all core elements are met; and generating a legal conclusion with an inference chain based on the final state and the graph logic. The corresponding system comprises a text analysis module, a knowledge storage module, a state management module, a reasoning control module, a conclusion generation module and the like. Through state management and intelligent inquiry driven by the atlas, progressive guide interaction from incomplete information consultation to accurate and legal conclusion explaining is realized.

The invention discloses a response method and device for government affair business consultation, electronic equipment and a storage medium. According to the method, a knowledge base including an item situation database, an item handling information database and an item consultation information database is pre-constructed, and the knowledge base is retrieved according to a consultation request to actively query a user, or a recommended handling item is provided for the user, or the user is prompted to check a demand material for service handling. According to the technical scheme, the response accuracy and comprehensiveness of the consultation request of the user are improved, so that the government affair business handling efficiency of the user is improved, and the business handling complexity is reduced.

The invention relates to the technical field of intelligent response of crisis comment, and discloses an intelligent response method and device of crisis comment, electronic equipment and a storage medium, and the method comprises the steps: carrying out the deep semantic analysis and clustering of multi-source comment data, can precisely and efficiently recognize and aggregate an independent crisis event entity from noise information, and improves the accuracy of the crisis event entity. By constructing a time sequence social communication network model and quantifying user node influence, scientific prediction and evaluation of crisis diffusion trend and intensity are realized, so that a crisis index can more accurately reflect the severity of an event, and an adaptive first-level response skill is dynamically generated in combination with cultural features associated with the event and the crisis index. The method has the beneficial effects that the pertinence, the timeliness and the cultural suitability of the response strategy are improved, so that the subject is helped to more actively and effectively manage and resolve the online comment crisis, and the automation and the intelligentization of the main process from identification to response are realized.

The invention discloses a response method and device based on a large language model, a storage medium and computer equipment, and the method comprises the steps: in response to a dialogue instruction for the large language model, determining current input information indicated by the dialogue instruction, and obtaining context question and answer information corresponding to the current input information; recalling at least one piece of first current-round recall information based on the current-round input information, and recalling at least one piece of second current-round recall information based on the context question and answer information; reference knowledge information of the round is determined according to the first recall information of the round and the second recall information of the round, and response information of the round is output based on the reference knowledge information of the round through a large language model. According to the method, double knowledge recall is carried out by combining the input information of the round and the context question and answer information of the round, and the recalled knowledge is utilized to guide the large language model to generate the response information of the round which not only accurately responds to the current demand of the user, but also keeps the continuity of the dialogue history, so that the understanding and response quality of a dialogue system is improved.

The invention discloses an event response method and device, a storage medium and electronic equipment, and the method is applied to an emergency system, and comprises the steps: determining a response department responding to an alarm event based on a scheduling agent according to the alarm level of the triggered alarm event, and determining an execution instruction of a department agent corresponding to the response department based on the scheduling agent according to the event data of the alarm event, transmitting the execution instruction to the department agent, and responding to the execution instruction based on the department agent. And obtaining execution data corresponding to an execution field in the execution instruction from a data source, generating an execution report according to the execution data, and outputting the execution report to each response department. By the adoption of the method and device, all departments are efficiently and accurately called for information sharing and cooperative work, and the efficiency and accuracy of responding to the alarm event are improved.

The embodiment of the invention relates to the technical field of power system dispatching and control, in particular to a multi-load aggregator collaborative response method based on power grid limited adjustment budget, and the method comprises the steps: combing the interaction relationship among a power grid company, load aggregators and terminal users; constructing an interaction model comprising a power grid company, a load aggregator and a terminal user, wherein the interaction model comprises a power grid company constraint, a load aggregator constraint and a terminal user constraint; constructing a multi-load aggregator collaborative response strategy model considering the power grid limited adjustment budget, and taking the minimum adjustment deviation and the load side adjustment cost as optimization targets; a business solver BARON is called for solving the interaction model and the multi-load aggregator collaborative response strategy model in a GAMS environment, a solving result is output, response results of all scenes are analyzed, the load aggregators are guided to reasonably respond to power grid adjustment requirements, and coordination and balance of interests among multiple subjects are achieved.

This application discloses a RAID request and response method, a data storage system, and an apparatus, relating to the field of computer technology. By dividing the RAID logical space into a foreground area and a background area according to the progress of background tasks, and determining the target response strategy for the RAID request based on the intersection of the target area of ​​the RAID request to be responded to with the foreground and background areas, the foreground area's target response strategy is used to respond to the RAID request when there is no conflict between the RAID request to be responded to and the background task. This eliminates the need for striping locks and improves request response efficiency. When there is a conflict between the RAID request to be responded to and the background task, it is further determined whether the background task meets the preset request splitting conditions. If it does, it is split to prioritize responding to the part of the request that does not conflict with the background task, further improving request response efficiency.

This invention provides a method for cross-business system event rule determination and multi-dimensional response triggering, relating to the field of multi-business system collaboration technology. It includes steps such as event rule definition, cross-system data integration, multi-dimensional event rule determination, multi-dimensional response triggering, event querying and tracing, and dynamic rule adjustment. By establishing a unified event rule template and determination framework, standardized access and centralized management of cross-system events are achieved. Based on multi-dimensional determination conditions such as time, event attributes, and priority, combined with response methods such as event storage, data forwarding, message notification, and alarm generation, diverse business needs are met. A real-time rule loading mechanism enables dynamic adaptation to changes in business requirements. This invention solves the problems of fragmented event processing, poor collaboration, and low response efficiency in existing multi-business systems. It is applicable to scenarios such as the Internet of Things, Industrial Internet, and smart parks, and has good practicality and scalability.

A customer service demand intelligent anticipation active response method and system relates to the technical field of intelligent customer service and artificial intelligence, constructs a data acquisition-model anticipation-response execution-closed loop optimization-operation and maintenance guarantee full-link technology collaborative system, and innovatively proposes a five-in-one framework of center-perception-execution-evolution-escort. The data layer adopts a multi-mode implicit signal acquisition and edge and cloud collaborative architecture to realize full-contact data comprehensive acquisition, real-time processing and secure transmission; the model layer improves cross-scene adaptability and pre-judgment accuracy through a dynamic adaptive federated learning and large model deep reasoning fusion system; the response layer drives a hierarchical response engine based on the priority of emotion fusion, and realizes humanized and precise active response; the optimization layer constructs a full-link closed-loop system and pushes the system to continuously iterate; the operation and maintenance guarantee layer provides intelligent monitoring and exception handling capacity and guarantees stable operation of the system.