459 results about "Service process" patented technology

Disclosed in the present invention is a fully automated log analysis and fault handling system and method based on an NLP large model. The method comprises: collecting a service state, an operating environment, and log files; extracting and generating log summaries from the log files, extracting key information from the log summaries to obtain state information of a service process; if an error is fed back, the NLP large model performing fault analysis on the error by using the service state and the operating environment as prior knowledge, and recording upstream and downstream key information involved in the error; on the basis of the upstream and downstream key information involved in the error, finding a fault cause and providing a fault handling action; and then executing a plan on the basis of the fault handling action. Log collection of the present invention is not limited to a prescribed format, and an NLP large model using a service state and an operating environment as prior knowledge is introduced for fault analysis.

The invention provides an operating system updating method based on cloud service, which comprises the following steps: acquiring operating system versions and patch installation conditions of different hosts by scanning system information of cloud hosts, and dividing the hosts into corresponding management groups according to operating system types and version numbers, formulating a unified patch strategy and an update plan for each group; a monitoring agent is deployed on a cloud host, operation indexes and log information of service processes are collected in real time, collected data are summarized to a centralized log analysis platform, logs are analyzed and mined through a batch computing framework, and a service operation behavior model is constructed; for data in a log analysis platform, a machine learning algorithm is used, an anomaly detection model is trained in a supervised learning mode, and the model can automatically discover various abnormal behaviors in the service operation process from massive log data and generate alarm information.

The invention relates to the field of data processing, and particularly provides a big data mining method and system based on digital enterprise management, and the method comprises the steps: obtaining multi-modal session data generated in the process of carrying out digital service interaction between a target enterprise and a user, extracting a user demand feature set from the multi-modal session data, and based on a preset multi-task learning framework, carrying out joint training on the user demand feature set, generating a demand analysis model, calling the demand analysis model to analyze the user demand feature set, generating an optimization strategy set associated with the target enterprise service process, and sending the optimization strategy set to the server. And updating the digital service execution logic of the target enterprise according to the optimization strategy set, and performing incremental training on the demand analysis model based on user feedback data. According to the invention, the response efficiency and the function adaptability of the digital service process can be improved.

The present invention discloses a method and apparatus for simulating thermal stress of a casting mold during a service process, and a storage medium. The method comprises: importing a pre-built three-dimensional geometric model of the casting mold, processing the geometric model, and then performing grid division to obtain a casting simulation finite element physical model; assigning material parameters, interface parameters, process parameters, and boundary conditions to the finite element physical model to obtain a casting simulation finite element calculation model; performing casting process simulation calculations to obtain casting simulation results such as mold temperature field and stress field, and exporting result data; interpolating a temperature-stress correction factor; multiplying all correction factor data under the same node numbers with mold stress data to obtain final thermal stress distribution data of the mold during the service process.

The invention relates to the technical field of artificial intelligence and natural language processing, in particular to an intelligent customer service method and system based on a large model, and the method comprises the steps: generating a unique session ID based on a user identity, and associating a historical context; multi-modal input of texts, voices, images and the like is carried out, and data standardization is carried out through a unified interface; realizing mixed intention recognition by combining a rule engine and a large model; constructing a dynamic customer portrait through multiple rounds of dialogue records, historical work orders and business data; according to the question emergency degree and customer value grading response, analyzing customer emotion in real time, adjusting a reply style, and outputting an answer; the manual operation process of the traditional customer service is converted into an AI automatic closed loop; the method has the beneficial effects that customer intention deep understanding, multi-mode interaction, emotion perception and service process automation are realized through a large language model (LLM) technology, and the service efficiency and the user satisfaction are remarkably improved.

The invention relates to the technical field of voice recognition, in particular to a voice interaction system and method for customer service based on artificial intelligence, and the system comprises a voice input processing module, an intention classification and routing module, a context dynamic adjustment module, a user behavior learning module, a multi-level intention fusion module and a final result module. According to the method, a multi-dimensional feature system is constructed by extracting tone intensity, speech speed frequency and emotional fluctuation amplitude, intention categories, priority weights and confidence scores are generated to realize accurate acquisition of appeals, and dialogue history, context and emotional change dynamic reconstruction path nodes, switching rules and response time sequences are tracked during interaction. Historical behavior mining preference features, habit fusion intention relevance, emergency calculation of an optimal strategy, construction of service steps, resource allocation schemes and execution timelines, adjustment of an interactive interface, a service process and a feedback mechanism according to multi-dimensional analysis, guarantee of differentiated service experience, and improvement of response accuracy and user satisfaction.

The invention discloses a service processing method based on emotion recognition and related equipment thereof, belongs to the technical field of artificial intelligence, and is applied to processing of insurance elimination service. Firstly, unified format conversion and feature extraction are carried out on three data sources of voice, video and text; then, a multi-modal fusion algorithm is combined with an attention mechanism to carry out weighted splicing on the features, and a comprehensive emotion feature vector is constructed; and emotional expression deviation caused by cultural difference is effectively corrected by combining a regional cultural emotion mapping table and customer regional information. And when the corrected emotional feature vector triggers an emotional threshold, the specific emotional state of the customer is accurately judged by a classification algorithm. And finally, determining a corresponding service response strategy according to the emotional state of the customer. According to the invention, the accuracy and response speed of emotion recognition are improved, the dynamic optimization of the service process is realized, the customer experience and satisfaction are enhanced, and the insurance industry is assisted to realize intelligent and precise customer service management.

The invention relates to the field of emerging software and information technology service, in particular to an artificial intelligence-based application system integrated management method, which comprises the following steps of: analyzing an API (Application Program Interface) log, structured data, an unstructured document, business work order data and business image data by pre-training a large model, and generating a unified semantic representation in combination with multi-modal contrast learning; a knowledge distillation technology is adopted to migrate the large model capability to a lightweight neural network, and a domain knowledge base is generated based on fine tuning of business work order data; a user multi-mode instruction is analyzed, a DAG service agent template library is matched, and an execution chain is dynamically combined based on a reinforcement learning strategy, so that text processing, multi-system collaborative reasoning and RPA service process automation are realized; and collecting an execution log, and updating lightweight network parameters and an intelligent agent strategy library through an online distillation algorithm to form a closed-loop optimization mechanism. According to the method, the service response efficiency can be improved, and the problems of enterprise multi-service system data splitting and process stiffness are solved.

The invention provides an AI-based customer service intelligent interaction method and system, and a medium. The method comprises the following steps: collecting attribute information and behavior track information of a target customer, processing to obtain a customer information portrait, extracting personalized demand information of the target customer according to the customer information portrait, executing intelligent interaction service based on the personalized demand information, monitoring an interaction service process in real time, collecting service state parameters, and sending the service state parameters to the target customer. Whether manual customer service switching needs to be executed or not is judged according to the service state parameters, intelligent interaction service in a preset time period is monitored, service index data is extracted, quantitative evaluation processing is conducted according to the service index data, a service reliability coefficient is obtained, the reliability of the intelligent interaction service is judged, and corresponding optimization measures are taken. Therefore, the AI-based customer service intelligent interaction technology is realized.

The invention provides an SCRM customer management method and system, and relates to the technical field of customer management, and the method comprises the steps: collecting customer data; preprocessing the customer data, and obtaining integrated data based on a preset integration rule; performing multi-dimensional analysis on the integrated data, and mining rules and trends of the integrated data to obtain an integrated data analysis result; based on an integrated data analysis result, through an association rule mining technology and a clustering algorithm, constructing a customer portrait of the customer; according to the customer portrait, personalized marketing content is pushed to the customer through a preset marketing rule; and collecting a feedback problem of the customer, providing a solution of the feedback problem according to the customer portrait of the current customer, and updating the customer portrait according to customer data generated in the service process. According to the method, the client feedback is continuously collected and the client portrait is updated in real time, so that the latest behavior change of the client is reflected, and the accuracy of marketing decision making is further improved.

The invention discloses an AI infrastructure performance detection method and device and a storage medium, and belongs to the technical field of data processing. The method comprises the steps that according to chip information of container nodes, dynamic instrumentation is conducted on a kernel layer and a calculation layer by expanding a Burkley packet filter, first performance indexes of the kernel layer and the calculation layer are collected, a hardware management library function is called, second performance indexes of a chip hardware layer are collected, and on the basis of a control group mechanism, the kernel layer and the calculation layer are subjected to dynamic instrumentation; and obtaining meta-information of the business process group in the container node, constructing an association relationship between the first performance index and the business process group and between the second performance index and the business process group through association marking according to the meta-information, and performing association analysis on the first performance index and the second performance index based on the association relationship to obtain a performance detection result of the business process group. According to the method, the performance parameters are collected through a non-intrusive scheme, the performance indexes of different service processes are determined through a service association mode, and the accuracy of AI performance problem positioning is improved.

The invention provides a resource leakage point positioning method, electronic equipment and a storage medium, and relates to the technical field of terminals. In the method, in a service process, when a service thread calls a resource application interface to apply for resources, corresponding resource calling information is obtained, and the resource calling information comprises function stack memory information and register information corresponding to the resource application interface; the business process comprises one or more business threads; according to the technical scheme, the target thread is newly added in the business process, the stack return is carried out on the nat ive layer based on the function stack memory information and the register information, and the backtracking from the nat ive layer to the java layer is not needed during the stack return, so that the performance overhead and the resource consumption caused by the stack return are reduced, and the technical effect of improving the positioning efficiency of the resource leakage point is realized.

The invention discloses an agent building workbench based on a multi-agent framework, and relates to the technical field of artificial intelligence. The system comprises an agent building module, a workflow configuration module, a release and integration module and an enterprise WeChat access module. The agent building module is used for quickly creating an agent according to business requirements and configuring parameters, a function module and a knowledge base of the agent at the same time; the workflow configuration module constructs a task allocation mechanism based on an open source multi-agent architecture, and the workflow configuration module is used for supporting configuration of a multi-agent workflow through a graphical interface and a programming interface, and embedding an open source tool and a self-research tool in the workflow to realize modular processing of tasks; by constructing the Roles intelligent agent construction workbench, the problem that an existing intelligent agent development tool is insufficient in flexibility and expansibility is solved, an efficient intelligent agent construction and management platform is provided for enterprise users, intelligence and automation of the service process are achieved, and the method has wide market application prospects.

The invention discloses a hotel guest room service task intelligent scheduling system based on a cloud platform, and relates to the technical field of hotel service management, the intelligent scheduling system comprises a mobile client, a cloud server and a database system; and the mobile client is used for configuring a special mobile application program running on mobile equipment such as a smart phone or a tablet personal computer for hotel guest room service personnel. According to the intelligent hotel guest room service task scheduling system based on the cloud platform, service personnel can quickly respond to service requirements through real-time task pushing and mobile operation, the task waiting time is shortened, the moving speed of the service personnel is increased through positioning and navigation functions, the service response time is shortened, and the service efficiency is improved. Through detailed recording and picture and video uploading in the service process, service quality tracing and supervision are facilitated, weak links of the service process can be found and improved through data analysis, in addition, special requirements of guests are met through personalized service recommendation, and the satisfaction degree of the guests is improved.

The invention provides an RPA operation report automatic generation method based on full-business process data fusion and a financial robot thereof, and the method comprises the steps: collecting task logs, business action events and context data generated in the execution process of the financial robot, and standardizing the task logs, the business action events and the context data into a unified event unit; constructing a flow path diagram based on the event time sequence; performing structure comparison on the trajectory diagrams of different service periods, identifying node addition and deletion or path rearrangement, and generating a structure attribution result; combining the attribution result and the event data to construct a structure perception type semantic index; and finally, automatically filling the indexes and attribution contents into the financial operation report template to generate a complete report. The method does not need to depend on a process definition file, can automatically restore a real execution path, achieves the interpretability analysis of process change and the full-automatic generation of a report, and remarkably improves the accuracy, integrity and decision support capability of financial RPA operation analysis.

The invention discloses an SOP flow rapid generation method based on activity features, and particularly relates to the technical field of computer application, and the method comprises the steps of S1, activity feature dynamic extraction, S2, knowledge graph enhanced semantic understanding, S3, reinforcement learning flow optimization, and S4, real-time feedback and dynamic adjustment. Through multi-aspect technical innovation, the method has remarkable effects on flow generation, execution and knowledge updating, in the flow generation stage, multi-source heterogeneous data collection is combined with an advanced algorithm, the generation time is greatly shortened, in the execution process, knowledge maps, reinforcement learning and a real-time feedback mechanism are coordinated, the error rate is reduced, the resource utilization rate and compliance are improved, and the method is suitable for large-scale popularization and application. Meanwhile, the knowledge graph can be continuously updated according to the optimization process, the adaptability of the SOP process to service changes is enhanced, the intelligence and automation level of the service process is comprehensively improved, and an efficient, high-quality and flexible process solution is brought.

The invention relates to the technical field of maintenance service management and intelligent scheduling, in particular to a one-stop maintenance service management platform based on a cloud platform, which comprises a user demand analysis module, a service resource scheduling module, a maintenance process collaboration module, a data tracing analysis module and a service report generation module. Wherein the user demand analysis module is used for analyzing and extracting equipment type parameters and generating maintenance aging parameters; the service resource scheduling module is used for generating a resource scheduling instruction containing a service provider ID and committed arrival time; the maintenance process collaboration module is used for generating an aging verification parameter containing an actual time difference of arrival; and the data tracing analysis module is used for generating fitting compliance parameters. According to the invention, through constructing the maintenance service management platform which integrates demand analysis, resource scheduling, process collaboration and result evaluation, structured processing and quality traceable supervision of the whole service process are realized.

The invention discloses a method for managing service nodes capable of being dynamically expanded based on a Camuda process engine, which belongs to the technical field of electric digital data processing and comprises the following steps of: uniformly configuring service process nodes into a pointing proxy delegation class; querying an external mapping table based on the execution context to obtain a business logic unit identifier; obtaining metadata from a logic registration center according to the identifier, and dynamically loading and instantiating a business logic implementation class through a sandbox class loader; driving service logic execution through a security context object of a white list only exposure method; and recording a full-link audit log. According to the method, structural decoupling of process definition and service logic is realized, so that the process definition does not need to be modified during service change, and dynamic replacement and gray release are supported; through sandbox isolation and security agent, isolated operation of dynamic codes and security and stability of an engine are ensured; and in combination with an audit tracking and fusing mechanism, the observability, the reliability and the operation and maintenance efficiency of the system are improved.

The present application provides a sleep method for an electronic control unit (ECU), an ECU, a system, and a vehicle. The method is applied to a vehicle comprising a controller area network (CAN) and a gateway, wherein the CAN comprises a CAN bus and an ECU, and the ECU is connected to the gateway via the CAN bus. The method comprises: the ECU receiving a power-off signal from the gateway; the ECU determining the presence of a service process in the ECU; the ECU identifying the type of service being executed by the service process; the ECU determining, based on the service type, that the service is abnormal; and the ECU terminating the service process and executing a sleep mode. In an embodiment of the present application, when a service in the ECU is abnormal, the ECU can terminate the service process and execute a sleep mode, thereby reducing vehicle power consumption and conserving vehicle battery power.

The invention provides a user power consumption business question and answer method and system based on a knowledge graph, and belongs to the technical field of power business handling. According to the method, entity extraction and association are carried out on the historical customer work orders, the historical customer work orders are converted into triples, the triples are stored in the neo4j database to construct the knowledge graph, and business data are effectively integrated to form a structured knowledge system. By means of the constructed common question template and the VSM algorithm, the user question can be quickly and accurately recognized, a Cypher query statement is utilized to efficiently search for question reasons and solving measures in the knowledge graph, finally, an answer text is generated based on an answer text template to be fed back to the user, a work order is sent, efficient circulation from question consultation to service processing is achieved, and the user experience is improved. The quality and efficiency of the power consumption business question and answer service are comprehensively improved, the service process is optimized, and more professional and convenient service experience is provided for the user.

The invention discloses a cross-platform intelligent project dynamic information real-time synchronization method and device, and relates to the technical field of information synchronization. Comprising the following steps: S1, obtaining a latest update request through communication connection with each platform, performing sensitive analysis on the update request, and performing different security verification strategies on the update request according to a sensitive analysis result; s2, comprehensively analyzing each service node to select an optimal service node to serve the update request, and executing a fusing strategy when an exception exists in the service process; and S3, encrypting and storing the update request to the block chain by the control service node, and executing different encryption modes for the update requests of different sensitive types at the same time. According to the method, the problem of performance bottleneck and expansion of a traditional synchronization architecture when the number of users and the data volume are increased exponentially is effectively solved, and meanwhile, through multi-level security protection, the security risk in the data transmission process is remarkably reduced.

The invention provides an information technology consultation process management system based on the Internet, and relates to the technical field of information technology management. A client interaction port of the system collects consultation texts and operation events in real time to generate a behavior track data set; the semantic path tracking module analyzes the data set to construct a demand evolution diagram; the path response arrangement module generates a service sequence according to the demand evolution diagram and binds consultant resources; the service recording module monitors data such as satisfaction and time delay to trigger path optimization, analyzes the weight of an efficiency attenuation point reconstruction demand evolution diagram and inputs the weight into the information pushing module during path optimization; and the information pushing module actively pushes a solution entry according to the information. The problems that dynamic changes of client intentions are difficult to accurately capture and the service process cannot be optimized in real time are solved, the intelligent level and the execution efficiency of the consultation process are improved, the experience feeling and the satisfaction degree of clients are improved, and meanwhile the utilization efficiency of consultation resources is improved.

The invention discloses a vehicle queue control method, device and system integrating ETC and a self-service robot. The method comprises the following steps: constructing a transaction cooperation mechanism based on double control queues; when the front-end ETC antenna recognizes the vehicle, if the control queue does not have the vehicle success record, adding a non-passing queue and triggering the initial ETC transaction; when the vehicle drives into the grating, recognizing a license plate through a front-end license plate recognition instrument, if the non-passing queue is empty, creating a vehicle record containing the license plate and a non-transaction state, adding the vehicle record into the passing queue, otherwise, adding the head of the non-passing queue into the tail of the passing queue; when the self-service robot is not occupied, the rear-end ETC antenna triggers the secondary transaction of the vehicle with the first ETC failure in the passing queue; when the self-service robot is used and the trigger coil induces the vehicle, starting a self-service process, and inserting into the head of the passing queue if the transaction succeeds; correcting or deleting abnormal vehicle records in the control queue; and determining whether to lift the rod to release according to the transaction result of the vehicle at the head of the passing queue, and deleting the vehicle record at the head of the queue.

The invention discloses an insurance service full-process processing method and device based on multi-agent cooperation, and belongs to the technical field of artificial intelligence. A user request is received through the user interaction layer, a natural language processing technology is utilized to identify a user intention and extract key entity information, and structured user input data is generated; dynamically routing the request to a corresponding AI agent through a task distribution module according to the intention type, wherein the AI agent comprises a customer consultation agent, a risk assessment agent and a claim settlement processing agent; each agent cooperatively processes a business process based on shared session context information, exchanges structured data through a unified communication protocol and executes a cross-link task; and finally, integrating processing results of all agents, generating a service response conforming to insurance business logic, and feeding back the service response to a user through a user interaction layer. According to the invention, efficient automation and intelligent cooperation of the whole insurance service process are realized, and the accuracy and response speed of service processing are remarkably improved.

The invention provides an intelligent gas station optimization scheduling method and system, is applied to the technical field of vehicle scheduling, and aims to guide a vehicle to enter a proper initial parking position by obtaining the identity and service demand of the vehicle when the vehicle enters the station and generating a service voucher and combining real-time resource information in an energy station. And when the service resources in the station are available, selecting the most suitable target vehicle for resource allocation according to the type of the available service resources and the demand information recorded in the waiting vehicle service voucher. In the service process, if service demand update information exists, the service voucher of the vehicle is dynamically adjusted according to the update information, and according to the adjusted service voucher, the system can provide an accurate second guide signal for the vehicle completing the current service to guide the vehicle to go to the next stop, so that the service quality of the vehicle is improved. The whole process of the vehicle in the station is ensured to be smooth and efficient, and path conflict or congestion caused by demand change is avoided, so that optimal scheduling of the vehicle in the whole life cycle in the energy station is realized.

The invention relates to the technical field of data security, can be applied to business system platforms of medical health, financial science and technology and the like, and discloses an intelligent processing method for business process abnormity, which comprises the following steps: acquiring a business task, analyzing the business task, and generating a business component; sequentially executing the business components according to a preset execution sequence; capturing an abnormal execution state of the business task through an exception capturing mechanism, and classifying the abnormal execution state to obtain an exception type and a business identifier; selecting an exception handling mode according to the exception type and the service identifier; and processing the exception according to the exception processing mode and the service identifier. According to the method, the service assemblies are generated by obtaining and analyzing the service tasks, the assemblies are executed according to the preset sequence, and the execution state is monitored in real time. And if the exception occurs, the exception state is classified and processed, the exception type and the service identifier are determined, and then the exception processing mode is selected, so that the exception in the service process is effectively processed, and stable operation of the service is ensured.

The invention provides a government affair element universe digital person-based system for realizing intelligent guide of affair handling personnel, and belongs to the technical field of government affair service intellectualization. The system deeply integrates element universe, intelligent interaction, big data and artificial intelligence technologies, realizes natural interaction with the affair handling personnel by means of an intelligent virtual digital person, and realizes intelligent guide of the affair handling personnel. And the government affair service process can be smoothly completed. A local intelligent knowledge base system and a knowledge base exclusive to multiple government affair departments are built, and a DeepSeek large model is applied. Voice or text query of business knowledge, handling processes, policies and regulations is supported, and contents cover latest policies of tax payment services, meta universe, offline business handling places and modes and the like. The digital human has abundant functions, provides business consultation, hall navigation guidance and intelligent explanation, can also perform daily question and answer interaction, and creates a relaxed communication atmosphere. And after logging in the meta universe cloud hall, the accompanying real-time efficient interactive guide service can be obtained by clicking the guide digital person, so that the government affair service efficiency and the user satisfaction are remarkably improved.

The invention provides an SIM card identification method based on LCS and low-rank CP reconstruction attention, and the method comprises the steps: obtaining label data for a first target image, the label data comprising the coordinates of a minimum enclosing rectangle of a unique identifier and the unique identifier; detecting an area of the unique identifier in the first target image through an alternative detection model to obtain a third target image; identifying the unique identifier of the third target image through an alternative identification model to obtain an identification mark; comprehensive performance parameters are determined according to the label data and the recognition result, and under the condition that requirements are met, the alternative model is determined as a target model; and extracting a unique identifier from a first target image obtained in the business process according to the target model, and inputting the unique identifier into the target system in batches to activate the target object. According to the method, the problems that business handling depends on manual input and the efficiency is relatively low in the prior art are solved.

The invention relates to the technical field of intelligent management, and discloses an after-sales service management method based on intelligent scheduling and automatic order dispatching, and the method comprises the steps: obtaining the maintenance and after-sales work order of a customer, and extracting the work order information; classifying the work order information according to a preset classification rule, generating different types of work orders, and distributing the work orders to a to-be-processed queue; matching a plurality of engineers for the work order to be processed by adopting an intelligent matching algorithm, and calculating an engineer score based on factors such as skill matching, load, response time efficiency and historical evaluation; assigning engineer processing work orders according to the scores, marking the work orders as to-be-processed work orders if the work orders cannot be matched, and transferring to manual auditing; if the distribution is successful, tracking the position of the engineer and the service progress in real time, and pushing information to the client; after the work order is completed, client evaluation is collected, and engineer scores are updated in real time. According to the method, the problem that a multi-dimensional scoring judgment, real-time position information tracking and service process visualization feedback mechanism is lacked can be solved.

The invention discloses an intelligent system for customer service quality inspection based on multi-source data, and particularly relates to the technical field of customer service quality inspection. The method comprises the following steps: acquiring session texts generated in a customer service process and associated product purchase and consumption data in a customer account in real time, and performing cleaning and standardization processing; a large-model automatic marking algorithm is constructed to carry out category marking on customer problems, and recognition of problem backgrounds and customer appeals is realized through context correlation analysis; performing double evaluation on customer attitude and customer service quality by using an emotion analysis model and a customer service verbal skill analysis model; and generating a comprehensive evaluation result of the overall quality of the customer service through fusion analysis, finally predicting a customer conversion rate and a contract extension rate based on the overall quality evaluation result, and generating a targeted customer service optimization strategy, thereby realizing accurate evaluation of the customer service quality and intelligent management of the customer relationship.