195 results about "Response method" patented technology

The invention relates to the field of network security, and provides a security event tracing and response method and system based on an LLM intelligent agent, and the method comprises the steps: collecting log information from network equipment, and extracting a security event with a high threat degree in the log information; identifying an attack mode of the security event based on LLM, and generating a response strategy including atomization operation steps according to the identified attack mode; the natural language instruction in the response strategy is converted into a tool calling instruction through the intelligent agent, and related tools are called to execute specific operation. By constructing an LLM-driven intelligent decision-making body, full-process automation from event analysis to response execution is achieved, the LLM deep reasoning ability and a safety tool chain are innovatively and deeply fused, an unstructured log is converted into an executable disposal scheme through the semantic understanding ability of the LLM deep reasoning ability, and the processing efficiency is improved. And designing a multi-stage reasoning framework of attack mode analysis-target decomposition-tool matching, and supporting dynamic generation of a customized response scheme conforming to an enterprise strategy.

The invention relates to the technical field of distributed response, in particular to a distributed message dynamic response method based on websocket. The method comprises the following steps: constructing a distributed message service cluster to configure a websocket communication module, message middleware and a client for each service node, and providing a unified service access point to the outside through an Nginx load balancer, so as to automatically register and subscribe a global control theme to the message middleware and form a hierarchical theme subscription structure; when the client initiates a connection request, the connection is distributed and a secure channel is established; the client sends a service request message, packages the service request message into a standardized message format, and associates session information of the client at the same time; and receiving the session message, performing intelligent filtering, generating a response result, and pushing the response result to the client in real time. According to the invention, efficient processing and real-time response of messages in a distributed environment can be realized.

The embodiment of the invention relates to the field of large language models and multi-agents, and provides a multi-agent collaborative query response method based on a state dependency graph and a related device, and the method comprises the following steps: receiving a to-be-queried text input by a user; performing query semantic analysis on the to-be-queried text to obtain the analyzed to-be-queried text and query complexity; instructing the intention recognition agent to generate a domain index; calling a preference matching agent to generate preference information; calling a resource retrieval agent to query to obtain query use resource information corresponding to the to-be-queried text according to the query complexity; the query response information is generated at least according to the historical context of the to-be-queried text, the to-be-queried text, the analyzed to-be-queried text, the field structure information, the field index, the preference information and the query use resource information, and the personalized service corresponding to the to-be-queried text currently input by the user can be automatically adapted according to the actual interaction scene; and response type and high-efficiency intelligent assistance is realized.

The invention relates to the technical field of semantic recognition, can be applied to business scenes such as financial science and technology and medical health, and discloses a business response method, device and equipment based on communication theme recognition and a medium. And calculating the distribution density of the words in the plurality of text units, generating word weights in combination with word frequencies and the distribution density, identifying concerned topics, generating user feature tags or content classification identifiers, and associating with a service information system to trigger service operation. According to the method, the communication record is converted into the text data, the word frequency and the word distribution density are calculated, and the word weight with the discrimination degree is generated, so that a user concerned theme is automatically identified, and a label or a classification identifier is further constructed; automation of user behavior understanding, standardization of label generation and linkage of an operation process and a business system are realized, and personalized service response capability and operation efficiency are improved.

The invention provides a response method, device and equipment for a customer service robot, and relates to the technical field of customer service robots, and the method comprises the steps: obtaining multi-mode request data inputted into a current session with the customer service robot by a user, and a conversation state of the current session; according to the request data of different modals and the modal features of the request data of the corresponding modals, constructing a multi-modal heterogeneous graph; fusing the different modal features based on the request data of the different modalities, the corresponding modal features, the dialogue states and the multi-modal heterogeneous graph to obtain multi-modal fusion features; inputting the multi-modal fusion feature into a pre-constructed user intention response model based on a causal relationship to obtain a response strategy of the customer service robot to the multi-modal request data; wherein the user intention response model is used for representing the causal relationship between the multi-modal interaction data input by the user and the response strategy of the customer service robot. The response accuracy of the customer service robot can be improved, and the user interaction experience is improved.

The invention discloses a collaborative response method and device for large and small models, equipment, a medium and a program. The method comprises the steps of calling a low-rank adaptation small model to generate an initial response through an edge node when an input instruction of a user is received; calculating the whole sentence confidence coefficient in the initial response; if the whole sentence confidence coefficient is smaller than a sentence-level confidence coefficient threshold value, a collaborative response instruction is sent to the cloud server cluster; selecting a specified number of target large models from the plurality of large models, and correcting at least one lexical element based on a lexical element level confidence coefficient threshold to obtain a plurality of collaborative responses; and selecting the target collaborative response with the highest confidence as a real response, and returning the real response to the user. According to the embodiment of the invention, the large model and the small model are utilized to cooperatively work to quickly give a preliminary reply to a simple question, the large model intervenes in optimization when a complex question is encountered, a satisfactory answer is provided for a user, the user experience is improved, and the instruction processing capability is enhanced by performing fine tuning optimization on the low-rank adaptive small model.

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 discloses an intelligent response method and system based on a large model and a storage medium. The system comprises a user input module which is used for acquiring input information of a user; the keyword extraction module is used for extracting key information corresponding to the input information through a large model; the historical record conjoint analysis module is used for determining a plurality of dimension features of the user according to the key information and the historical record information; the permission judgment module is used for determining the knowledge base with the access permission of the user according to the permission level; the comprehensive portrait establishing module is used for generating a dynamic user portrait according to the multiple dimension features of the user; and the knowledge recommendation module is used for outputting a personalized reply of the user according to the dynamic user portrait and the knowledge base with the access authority of the user. According to the embodiment of the invention, through multi-dimensional analysis of user behaviors and historical data, an accurate user portrait is constructed, user demands are accurately matched, personalized knowledge recommendation is provided, and the knowledge service accuracy is remarkably improved.

The invention relates to the technical field of collaborative response management, and provides a business system collaborative response method and platform driven by a video AI analysis result, and the method comprises the steps: receiving a frame sequence generated by aligning a multi-source heterogeneous video stream, carrying out the parallelization AI reasoning to extract multi-dimensional features into an event feature set, carrying out the association mapping with a business strategy library to generate a collaborative instruction packet, and carrying out the collaborative response of the business system. The information is distributed to an unmanned aerial vehicle cluster through a distributed message bus and the like according to a route, and a terminal linkage response is triggered. The technical problem that communication among unmanned aerial vehicle clusters is unstable due to the fact that a communication network is prone to being interfered or interrupted in complex environments such as a disaster site is solved, events in a video are analyzed and processed, the cooperative instruction packet is generated and distributed to the target unmanned aerial vehicle cluster, the unmanned aerial vehicle clusters can efficiently execute tasks, and the efficiency of the unmanned aerial vehicle clusters is improved. And a self-organizing network protocol is deployed to carry out distributed collaborative decision making, so that the communication stability of the unmanned aerial vehicle cluster is improved.

The embodiment of the invention provides a message response method and device, computing equipment, a storage medium and a program product. Wherein the target server side provides account authorization prompt information for the target client side, responds to a first session authorization request of a first media account sent by the target client side for the account authorization prompt information, and sends a second session authorization request to the multimedia server side, and the multimedia server authorizes the first media account and feeds back the session access token. Based on the session access token, obtaining a first session message sent by a second client of the second media account to a first client of the first media account, generating a first response message by adopting a target artificial intelligence model corresponding to the first media account in combination with domain knowledge, and sending the first response message to the first client of the first media account through the multimedia server, and sending the first response message as a response message of the first client to the second client. According to the technical scheme provided by the embodiment of the invention, the session message in the multimedia application is automatically answered with low cost and high efficiency.

The invention discloses an inference type dialogue response method and system based on a large model, and a storage medium, relates to the technical field of service consultation dialogue response, and solves the problems that the existing service consultation dialogue response is generally relatively simple, lacks an active inquiry strategy, only can be passively responded and cannot simulate a questioning mechanism of service personnel, and the service consultation dialogue response cannot be simulated. The technical problems of insufficient suggestion judgment accuracy and high misjudgment rate caused by difficulty in comprehensively and accurately collecting the conditions of the demanders in the prior art are solved. The method comprises the steps of obtaining voice data of a demander for service consultation; the method comprises the steps of performing feature extraction on voice input data to obtain condition feature data; inquiring the demander through a pre-trained condition inquiry model based on the condition characteristic data to obtain judgment data; matching from a historical consultation database based on the condition feature data and the judgment data to obtain a reasoning target; and feeding back a judgment suggestion to the demander based on the reasoning target, thereby solving the technical problem.

The invention relates to the technical field of data processing, and discloses a response method and device based on a large model, electronic equipment and a storage medium, and the method comprises the steps: obtaining an original cue word which is determined based on a question text; obtaining intention information and / or target preference information, and modifying the original cue word based on the intention information and / or the target preference information to obtain a target cue word; and inputting the target cue word into a pre-trained first large model to obtain a response result, the target cue word being used for guiding the first large model to output the response result. On the basis, intentions or preferences of different users for the question can be displayed by obtaining the intention information and the target preference information. And modifying the original cue word to obtain a target cue word, and inputting the target cue word into the first large model to obtain a response result, so as to generate a response result more conforming to user differences.

The invention discloses a model training method, a response method and a related product, which are used for accurately and comprehensively analyzing session semantics so as to accurately identify a session intention. The model training method comprises the following steps: identifying a first intention and first entity information of a first session text; fusing the first intention and the first entity information to obtain a second intention of the first session text, and training a model based on the first session text and the second intention to obtain a first model; fusing the first intention, the first entity information and the second intention to obtain a third intention of the first session text, and training the model based on the first session text and the third intention to obtain a second model; and comparing the recognition accuracy of the first model and the recognition accuracy of the second model on the second session text, and determining a third model from the first model and the second model based on a comparison result.

The invention discloses a network public opinion event multi-department coordination response method and system, and relates to the technical field of multi-department response, and the method comprises the following steps: S1, an enterprise establishes a public opinion group in which a plurality of departments participate, and the public opinion group carries out the unified commanding and scheduling, and guarantees that each department can rapidly respond and cooperate with each other when a public opinion event occurs; and S2, the public gateway department assists in monitoring the dynamic state of the public opinion by defining the monitoring target and range, utilizing a whole-network public opinion monitoring tool, utilizing a social network public opinion monitoring tool, judging emotional tendency, searching engines, user feedback, public opinion analysis and information visualization. In the network public opinion management, through coordination response work of multiple departments, the departments closely cooperate and jointly face challenges according to clear responsibility division and efficient communication processes, so that the cooperation mode not only accelerates information transmission and processing, but also effectively avoids information delay and misunderstanding; and the timeliness and accuracy of the public opinion information are greatly improved.

The invention discloses a training method of a reply key point determination model, a verbal skill reply method and a related product, and the method comprises the steps: obtaining instruction information used for model training, and the instruction information is used for instructing a to-be-trained model to output historical reply key points corresponding to historical dialogue data based on the historical dialogue data, the historical reply key points are to-be-replied keyword information analyzed from historical dialogue data; constructing a training data set, wherein the training data set comprises historical dialogue data and historical reply key points; the to-be-trained model is trained based on the instruction information and the training data set, a reply key point determination model is obtained after training is finished, and the reply key point determination model is used for outputting reply key points corresponding to the to-be-processed dialogue data based on the to-be-processed dialogue data. Therefore, the customer service reply efficiency and response speed can be remarkably improved, and the customer satisfaction degree is further improved.

The invention relates to an A / B test problem response method and device based on a large model agent, and relates to the technical field of large models, agents and computers. The method comprises the steps of displaying an intelligent interaction page associated with an intelligent agent in response to a triggering operation on an intelligent agent identifier in an A / B test platform; in response to a work order creation operation in the intelligent interaction page, intercepting a target work order request corresponding to the work order creation operation sent to a work order server, and judging whether an intelligent agent can process a target problem in a target work order corresponding to the work order creation operation; acquiring a first similar question and a target answer corresponding to the first similar question in a question and answer knowledge base through a large model under the condition that the intelligent agent can process the target question; and displaying the target answer on the intelligent interaction page. Therefore, work orders submitted by the user can be reduced, waste of platform resources is reduced, the problem response speed and efficiency can be improved, and the use experience of the user is improved.

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 a service response method and device, electronic equipment and a storage medium, and relates to the technical field of data processing, and the specific scheme is as follows: loading an object of a first code unit into a heap memory in response to starting initialization of an application program of a server, establishing a global table containing the corresponding relationship among the business identifiers of the business modules, the memory addresses of the objects of the first code units and the event callback functions, traversing the global table before the main function of the application program is executed, and binding the business identifiers of the same business module, the memory addresses of the objects and the event callback functions; and in response to the received service request, if the identifier of the service requested by the service request is the same as the first service identifier, calling an object of the first code unit corresponding to the first service identifier by calling a callback function corresponding to the first service identifier. By applying the scheme provided by the embodiment of the invention, the applicability of the mode of externally providing services in different operating systems can be improved.

The invention relates to the technical field of computers, and discloses a response method and device based on deep learning, equipment and a medium, and the method comprises the steps: obtaining the current voice information and historical dialogue information of a user, analyzing the current voice information through a voice recognition model, and obtaining corresponding text information; the text information is analyzed through a natural language model, an analysis result corresponding to the text information is obtained, and the analysis result comprises potential intention information and context feature information; analyzing the context feature information and the historical dialogue information through an intention recognition model to obtain current intention information and a response prediction result; and if the current intention information is consistent with the potential intention information, outputting a response suggestion according to the response prediction result. The method can be applied to business management program systems such as financial science and technology, medical health, old-age care and the like, and response efficiency and response accuracy can be improved.

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 an e-commerce customer service response method and device, equipment and medium in the technical field of e-commerce, and the method comprises the steps: responding to a customer service consultation event triggered by a user, obtaining a target consultation text corresponding to the event, and determining the matching results between the target consultation text and preset dictionaries of a plurality of consultation categories; when the matching result represents that the dictionary is hit, determining a target consultation category to which the target consultation text belongs in a plurality of consultation categories according to the matching result; when all the matching results represent that the dictionary is missed, determining a target consultation category to which the target consultation text belongs in a plurality of consultation categories by adopting a preset intention recognition model; and from a preset question and answer knowledge base of the target consultation category, obtaining a customer service response text corresponding to the matched target consultation text, and pushing the customer service response text to the user. The user consultation can be efficiently and accurately responded, and the consultation customer service satisfaction degree 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.

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 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.

The embodiment of the invention provides an online customer service response method and device, equipment, a storage medium and a product. According to the embodiment of the invention, user input information is obtained, an information type corresponding to the user input information is identified through a classification model, and the user input information and the information type corresponding to the user input information are sent to a character extraction model; performing character extraction on the user input information and the information type corresponding to the user input information by using the character extraction model to obtain text total information, sending the user input information to the abstract extraction model, performing abstract extraction on the text total information by using the abstract extraction model to obtain abstract information, and sending the abstract information to the user input information. The summary information and the text total information are sent to the large model, so that the large model obtains the reply text and the response template according to the summary information and the text total information, the reply text is determined as the target reply according to the response template, and the reply accuracy of the online customer service can be 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 application provides a response method, apparatus, device, and medium for a DNS server. The method includes: receiving a user request and determining an identifier corresponding to the user request; determining a corresponding target device and its target identifier according to the identifier and multiple preset devices, and obtaining a request result of the user request according to the target device; determining whether the request result is obtained by the target device within a preset time limit; if the request result is obtained, determining the data type of the request result, and determining a device to be obtained in the preset devices based on the data type and the target identifier; if the request result is not obtained, determining a device to be requested and its device identifier in the preset devices, and determining the device to be obtained according to the target identifier and the device identifier; obtaining a target request result according to the device to be obtained, and sending the target request result to a terminal corresponding to the user request. In this way, the response speed of the DNS server is improved, and the user's network access experience is enhanced.