1827 results about "Service system" patented technology

The invention discloses an intelligent file service system generation method based on a low-code development mode. The method comprises the following steps: constructing a file service core data model, defining file metadata fields, a storage structure and an association relationship, and forming a standardized data architecture. According to the method, the core data model, the visual page component library and the drag-and-drop workflow template are constructed, linkage binding of data-component-process is achieved in combination with a low-code engine, and the efficiency bottleneck of a traditional development mode is broken through; through a three-way real-time synchronization mechanism, real-time hot repair and dynamic branch judgment, page layout and flow rule adjustment can take effect immediately through visual configuration, and the problem of dynamic demand response lag is solved; through the intelligent resource scheduling logic compiled through environment adaptation, a differentiation scheme is generated for different deployment environments, the configuration difference influence under a private cloud and server mixed deployment scene is remarkably reduced, the deployment failure rate is greatly reduced, and the system online stability is improved.

The invention discloses a product full-life-cycle traceability after-sales service system based on multi-source heterogeneous data, and relates to the technical field of product traceability after-sales management. Manufacturing resumes, work orders, spare part warehouse-in and warehouse-out and equipment logs are accessed, mapping of product instances, parts and software primary keys is established, and the product traceability after-sales service system is established. And normalizing the configuration change event into a configuration change event containing double time axes of effective time and warehousing time, and writing the configuration change event carrying differential operation, an evidence packet and an idempotent event identifier into an immutable event library. And constructing a conflict set for the same configuration target, executing uniqueness, causality and compatibility constraint verification, determining an effective event based on evidence packet arbitration, and outputting an arbitration record and confidence. And deriving a configuration version chain according to the effective event and generating a snapshot, performing incremental playback on the late or error correction event and generating an influence propagation list. And when any time point configuration is queried, playback restoration is performed, an evidence chain and confidence are output, an active verification backflow error correction event is triggered if the confidence is insufficient, and the accuracy of quality guarantee judgment and spare part matching is improved.

The invention relates to the field of intelligent operation and maintenance, and discloses a multi-source network data operation and maintenance system based on micro-service architecture and AI collaboration, comprising the steps of collecting multi-source data of a micro-service system, and performing cleaning, format unification and time alignment on the collected data; based on a data result of the data acquisition module, constructing a micro-service call chain and a dependency graph, embedding a real-time performance index and a log feature in each node, and dynamically updating a service relation graph; carrying out real-time anomaly detection on the multi-source data, and judging the alarm effectiveness in combination with a dynamic threshold and an AI alarm confidence self-learning mechanism; the AI conducts reasoning along the call chain anomaly map, causal relationship reasoning is added, and the anomaly propagation influence range is predicted; and feeding back a root cause positioning result and the optimized alarm information to an operation and maintenance system, optimizing an alarm threshold and decision parameters in combination with historical records, and outputting an updated operation and maintenance decision scheme. The method has the advantage of improving the operation stability of the system.

The invention provides a knowledge base and business system collaboration method under an AI platform, and belongs to the technical field of AI platform digital data processing.The method includes the steps that triple semantic analysis is conducted on query by constructing a multi-level semantic vector representation module, a parallel data retrieval engine is started, vector retrieval, graph reasoning and real-time data pulling are executed at the same time, and the query efficiency is improved; establishing a dynamic confidence evaluation mechanism to evaluate the quality of the data source, executing a weight distribution algorithm based on reinforcement learning, dynamically calculating the weight of the data source according to a query type by adopting a graph convolutional network intelligent routing decision model, and implementing multi-source data fusion and consistency verification to solve data conflicts through a weighted voting mechanism. An intelligent result sorting and filtering system is established, a multi-dimensional evaluation strategy is adopted to output high-quality answers, a continuous learning and feedback optimization loop is constructed, system performance is continuously optimized through active learning and a graph shortest path algorithm, and the technical problem that knowledge base data and a service system cannot effectively and uniformly make decisions is solved.

The invention relates to an intelligent customer service self-learning method and system, and the method comprises the steps: collecting the interaction data of a user and an intelligent customer service, and forming a multi-dimensional data set; based on a PID (Proportion Integration Differentiation) controller, processing the performance indexes in the multi-dimensional data set, calculating a current error signal, and generating a corresponding control instruction according to the current error signal so as to adjust the response behavior of the intelligent customer service system in real time; evaluating the system performance data adjusted by the control instruction to obtain evaluation feedback; and according to the evaluation feedback, dynamically adjusting the parameters of the PID controller through a self-adaptive control strategy, and feeding back the adjusted parameters to the PID controller in the step S2. According to the invention, by introducing a closed-loop feedback mechanism based on the PID controller and a parameter adaptive optimization strategy, real-time regulation and control of the response behavior of the intelligent customer service system are realized, and the stability, the response speed and the user satisfaction of the system are remarkably improved.

The invention provides an intelligent question and answer method based on a preset multi-dimensional knowledge base and a large language model, and the method comprises the steps: receiving a natural language query, converting the natural language query into a query semantic vector, and recognizing a corresponding intention type and a first confidence coefficient; if the first confidence coefficient is higher than an intention threshold value and the highest similarity between the query semantic vector and a standard question semantic vector in a preset multi-dimensional knowledge base is higher than a matching threshold value, returning a standard answer; otherwise, retrieving a generated context based on the query semantic vector, fusing the user query and the generated context, inputting the fused user query and generated context into a large language model to generate a preliminary answer, checking fact consistency of the preliminary answer and a standard answer in the generated context to generate a credibility score, and obtaining a target answer when the credibility score exceeds a credibility threshold; and dynamically optimizing the system based on feedback data of the user to the target answer. The intelligent customer service system with controllability, flexibility and self-optimization capability is realized, and the semantic understanding depth and response accuracy of the system are improved.

The invention discloses a tourism service agent system and method based on a multi-modal large model. The system comprises five parts: a user interaction interface, which is used for receiving a user request and returning a response; the agent center is used for performing intention understanding, task planning and response generation through a multi-modal large language model; and the tool calling module is used for executing specific API business operation. According to the intelligent tourism service system, the work of each module is coordinated through the intelligent agent center, a complete closed loop from user intention understanding to service execution is realized, accurate, reliable, whole-course and personalized intelligent tourism service can be provided, and the problems that a traditional tourism service system is single in function, inaccurate in information and lack of action ability are effectively solved.

The invention relates to the field of communication service support systems, and particularly provides a service provisioning process oriented anomaly identification and automatic compensation method and device, service provisioning process modeling is an ordered process chain composed of a plurality of processing nodes, and each node corresponds to a specific service system operation; a unique flow identifier Flow ID is generated for each service instance and used for whole flow state tracking, execution results, state codes and response time information of all flow nodes are recorded in a flow tracking database in real time, and after execution of each node is completed, events are published for other modules to subscribe to, so that an asynchronous observable link is formed. Compared with the prior art, the method can achieve the closed-loop processing of the abnormal process, remarkably reduces the manual intervention rate, improves the business activation success rate and customer service experience, and improves the stability and reliability of a service opening link.

The invention discloses a unified identity authentication and access control method for a power multi-service system based on a national secret algorithm. According to the invention, through systematic deployment of SM2, SM3 and SM4 cryptographic algorithms, a full-link security protection system from identity authentication to authority management is constructed. The unified identity authentication platform adopts a mode of combining a distributed micro-service architecture and a hardware encryption machine, so that the physical security of key storage and operation is guaranteed, and the stability and response speed of the system are improved through a master-slave synchronization mechanism and interface delay control. A multi-source identity information federation acquisition mechanism realizes real-time integration of static attributes and dynamic behavior data, abnormal characteristics of user operation can be accurately captured by combining a risk assessment matrix of an improved LSTM-attention mechanism, and an SM2 bidirectional dynamic authentication protocol is automatically triggered when a risk score exceeds a dynamic threshold. Closed-loop protection of collection-evaluation-authentication-auditing is formed, and security threats such as identity counterfeiting and authority crossing are effectively resisted.

The invention discloses an intelligent customer service dialogue management method and system fused with multi-layer memory, and belongs to the technical field of computers, and the method obtains a three-dimensional context through multi-mode context awareness, achieves the dynamic scheduling of a memory system through a memory coordinator, and combines a dynamic construction mechanism of a service situation portrait, thereby achieving the intelligent customer service dialogue management. The problem that the response of the intelligent customer service system is not matched with the complex and dynamic service demand of the user due to the single situation awareness dimension and the rigid memory scheduling mechanism is effectively solved, and the adaptive personalized service response can be generated according to the real-time change of the dialogue situation.

The invention relates to the technical field of industrial digital twinning, in particular to a digital twinning-oriented real-time data synchronization and consistency verification method, which comprises the following steps of: S1, acquiring multi-source heterogeneous data from a physical entity and a service system, and performing timestamp alignment based on a unified time reference to generate a standardized data stream; and S2, based on the standardized data stream, carrying out data cleaning, aggregation and preprocessing, verifying the integrity and time sequence of the data stream through a transmission verification mechanism, and outputting high-fidelity credible data. According to the method, a bidirectional consistency verification mechanism between a physical entity and a digital twinborn model is constructed, real-time deviation is quantified into a loss function, an online learning engine is driven to adaptively adjust physical parameters in the model, and a complete closed loop from data acquisition to parameter optimization is formed; the digital twinborn model can continuously adapt to dynamic conditions such as material aging and working condition change of a physical entity, and the tedious process that a traditional system depends on manual regular calibration is avoided.

The invention discloses an optical terminal intensity instrument and an earthquake monitoring service system and method, and the optical terminal intensity instrument comprises an optical fiber modem and an MEMS sensor module. The optical fiber modem comprises an MCU (Microprogrammed Control Unit) and an optical communication module electrically connected with the MCU; the optical communication module is used for realizing network access and data uploading; the MEMS sensor module is electrically connected with the MCU; the MEMS sensor module is used for collecting seismic intensity data in real time; and the optical fiber modem is used for providing a dual data transmission channel comprising broadband communication and the seismic intensity data. According to the technical scheme provided by the invention, the MEMS sensor is embedded in the optical fiber modem, and a more dense, more efficient and more economical solution is provided for earthquake early warning and intensity rapid reporting.

The invention relates to the technical field of forest fire management, in particular to an integrated forest fire intelligent analysis method and system. The system comprises a background service system, a central intelligent analysis system and a mobile intelligent analysis system. The background service system is deployed in a cloud computing server cluster and is used for uniformly storing personnel information, fire scene information and geographic information data and realizing multi-source data fusion and authority management through a standardized API (Application Program Interface); the central intelligent analysis system is deployed in a high-performance computer, integrates a forest fire danger auxiliary decision-making model, a forest fire spreading trend prediction model, a force distribution dynamic display module and a collaborative plotting module, and supports fire spreading prediction and real-time decision-making instruction issuing based on multi-dimensional data such as weather, terrain and vegetation; the mobile intelligent analysis system realizes fire spreading trend analysis, mobile plotting and instruction receiving in an offline environment, supports offline data caching and calling in an emergency scene, and effectively improves forest fire emergency response efficiency and resource scheduling accuracy.

The invention relates to the technical field of quantum cryptography, in particular to a dynamic key generation system and method based on multi-source QRNG and QKD, and the system comprises an interface registration method, a calling method, related equipment and a storage medium, is used for generating a high-security quantum key, and is a quantum key service system with a layered architecture. By abstracting, integrating and managing bottom-layer multi-source QRNG and QKD equipment and fully utilizing the flexible scheduling of quantum equipment, the security of key generation is ensured, so that the key service has higher performance, usability and security, and unified, dynamic and high-security quantum key generation and supply services are provided for various applications of the upper layer. The method is widely applied to the industries and fields of government, finance, energy, traffic, electric power and the like, meets the requirements of quantum key acquisition of various business applications in cloud computing and non-cloud environments, and ensures information security and business continuity.

The invention provides an intelligent customer service interaction content recommendation method and system based on artificial intelligence, and the method comprises the steps: obtaining power grid equipment state data and user behavior data, and carrying out the weighted fusion through an attention mechanism, and outputting a fusion feature vector; predicting a prediction vector set of a future time period based on the fused feature vector; screening a demand event set higher than a threshold in the prediction vector set, and generating a recommended content set; performing emotion recognition according to a current input text of the user, and calculating a recommended content score and a pushing priority score in combination with the recommended content set; a cross-modal consistency regular term is introduced to correct the push strategy vector, and an adjusted recommendation push score and a corresponding recommendation content set are obtained; and converting the adjusted recommendation push score and the corresponding recommendation content set into a scheduling task, and performing linkage execution with a scheduling system. According to the invention, efficient, active and intelligent upgrading of the intelligent customer service system in a power grid scene is realized.

A technique for resource allocation estimation for media content items is described. In accordance with the described techniques engagement by a set of user accounts with respective media content items of at least one media content service provider system is obtained. The media content service provider system and / or a payment service system generates historical streaming data for the respective media content items based on the engagement of the set of user accounts. An estimated streaming count of a media content item over a time period based on the historical streaming data for the respective media content items is determined. An estimated resource allocation for the artist is determined based on the estimated streaming count and an advance of funds is facilitated based on the estimated resource allocation to an account of the artist during the time period.

The invention relates to a pre-training language model fine tuning method, an inference service system, equipment and a medium, and the method comprises the steps: obtaining an original instruction of a target field and related fields, the original instruction comprising a language understanding task; evaluating and screening the original instruction according to a multi-dimensional index, and constructing a first high-value instruction set; extracting instructions in related fields from the first high-value instruction set, and performing filtering and mobility evaluation on the extracted instructions by using a pre-training language model to obtain a second high-value instruction set; adopting a pre-training language model to perform labeling, screening and enhancement processing on the second high-value instruction set in sequence, and generating a structured training sample; and training a pre-training language model according to the structured training sample to enable the pre-training language model to adapt to the target domain. Through the method and the device, the field annotation data quantity is reduced.

Techniques for creating and updating natural language summaries representing personalized user knowledge (e.g., user interests, user affinities, user preferences, family structure, routines, and other insights) based on conversational interactions with and other natural language content available to an AI system are described. In some embodiments, to provide a more personalized service, a system can use a generative model to summarize learnings about a user and determine helpful nuanced insights about the user such as “the user is learning how to play guitar.” This “user knowledge” can be updated based on further (later) conversations with the user, where updating can involve negating or deleting stored information, adding to or modifying stored information, etc.

The invention relates to a risk behavior early warning method and device based on adaptive time sequence slicing, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: collecting user operation behavior data aiming at each service in a service system, and obtaining user information and service characteristics of each service in the service system; generating a service activeness index; adjusting the length of a time interval between time sequence slices of the user operation behavior data; according to the adjusted time sequence slices, integrating the user operation behavior data, generating a user behavior sequence, and constructing a user behavior dependency graph; generating a normal behavior pattern of the user according to the time sequence slice intervals of different granularities, the user behavior sequence and the user behavior dependency graph; and according to the normal behavior mode, carrying out risk behavior early warning on the user actual operation behavior of each service in the service system. By adopting the method, the risk behavior prediction accuracy can be improved.

The invention provides a multi-modal neural causal inference micro-service fault positioning method and system, and the method comprises the steps: accessing observability data in a service operation process, and representing the tracking information of each request as a directed acyclic graph of a multi-modal feature; performing multi-modal feature coding and graph self-coding anomaly detection on the calling graph, and identifying an abnormal node through a reconstruction error; based on service topology prior, learning a sparse causal relationship graph between services by adopting a multi-scale neural causal inference method; calculating a node root cause score according to the causal relationship graph and the abnormal score, and executing causal path search to generate a fault propagation path; and marking the potential root cause according to the path weight of the propagation graph and the node popularity, and outputting a visual diagnosis result. According to the method, the system operation state is comprehensively described by fusing three kinds of micro-service system multi-modal data of logs, indexes and Trace in the micro-service system, and the structure-perceived causal diagram is constructed, so that accurate and explainable root cause positioning is realized.

The invention provides a business hall service system supporting multi-user security data circulation, which relates to the field of electric digital data processing and comprises a multi-user identity and access control module, a security data circulation and isolation module, a data life cycle security management module and a security monitoring and compliance auditing module, the multi-user identity and access control module is responsible for establishing a credible user identity system and realizing fine-grained authority control, and the security data circulation and isolation module ensures encryption protection, integrity verification and effective isolation among multiple users in the transmission process of data; the data life cycle safety management module covers whole-process safety protection of sensitive data from identification, processing to destruction, and the safety monitoring and compliance auditing module ensures that the system continuously meets compliance requirements and timely responds to safety threats through intelligent anomaly detection and whole-link auditing; the system can solve the problems of data security circulation and privacy protection in a business hall service system in a multi-user environment.

A method for constructing an intelligent bid-invitation purchasing customer service system based on a retrieval enhancement generation technology comprises the following steps: constructing a multi-source knowledge base, and integrating and processing customer service work orders, bid-invitation files and laws, regulations and policies; non-sensitive metadata information is extracted through entity recognition to construct a knowledge graph, and a block chain is used for evidence storage; classified navigation is provided during user consultation, and metadata is complemented through brief interactive questions and answers; performing fusion retrieval through a dual-channel RAG architecture to generate answers; and continuously supplementing data and optimizing training. According to the method, the data security is guaranteed, the semantic comprehension capability is improved, the agile response to information change is realized, and the compliance and controllability of the system are enhanced.

The invention discloses an AI customer service system dialogue strategy dynamic adjustment method and system, and relates to the field of artificial intelligence, and the method comprises the steps: obtaining user portrait data of a user; describing a user portrait based on the user portrait data; matching and configuring initial customer service personnel from a preset customer service personnel library according to the user portrait; in the multi-round dialogue process of the user and the AI customer service, the emotion value of the user is analyzed in real time, and the emotion value comprises a positive emotion value and a negative emotion value; when the emotion value is a forward emotion value, the dialogue style of the large language model is enhanced in real time through the prompt word engineering module, so that the reply satisfaction degree of the user is improved; when the emotion value is a negative emotion value, adjusting prompt words of the initial customer service personnel and the prompt word engineering module, and continuously monitoring the emotion value in the dialogue; and when the emotion value is converted from the negative direction to the positive direction, strengthening the current adjusted customer service personnel setting and prompt words. According to the method, the user experience can be effectively improved in the interaction process of the user and the AI customer service system.

The invention discloses a knowledge graph-based intelligent question and answer method for text travel. The method comprises the following steps of: obtaining and preprocessing related data in a text travel service system; constructing a structured knowledge graph in the text travel field; constructing a candidate entity pair and executing relation extraction and weight updating guided by a behavior sequence; dividing and generating a behavior preference sub-graph according to a behavior mode, and extracting a text travel knowledge slice set according to a theme; natural language questions of tourists are received, and path search and semantic aggregation with behavior weights and path structures as constraints are executed; and generating a text travel intelligent question-answer result through a question-answer generation engine, and recording a text travel question-answer interaction log for iterative updating. According to the method, knowledge graph modeling and behavior guiding relation extraction technologies are fused, dynamic reasoning and personalized question and answer generation of the travel knowledge are achieved, and the method has the advantages of being accurate in semantic understanding, high in answer association degree and continuous in self-adaptive evolution.

The invention relates to the technical field of airspace control, and discloses an AI-based low-altitude airspace information center collaborative control method, which comprises six core steps of multi-source sensing fusion, abnormal behavior discrimination, dynamic risk assessment, environmental constraint re-planning, communication collaborative optimization and collaborative execution decision-making to construct a closed-loop intelligent decision-making mechanism. Microsecond-level time synchronization is realized through a Beidou or GPS satellite time service system, and the target identification precision is improved in combination with a weighted evidence fusion theory; an R-tree and space-time bounding box dual rule engine is combined to accurately detect abnormal flight; the collision risk between the aircrafts is quantified by using a three-layer stacked multi-head map attention network, and trajectory re-planning under environmental constraints is realized through a multi-dimensional environment voxel model; a ground and satellite hybrid networking architecture is adopted for communication collaborative optimization, so that terrain shielding and electromagnetic interference are avoided in management and control communication, global coverage and accurate adjustment are realized, and the accuracy, real-time performance and safety of management and control are ensured.

The invention relates to a charging intelligent customer service industry knowledge base updating method and device based on online feedback, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring service object feedback information received by a charging intelligent customer service system; obtaining a knowledge base feature set corresponding to each industry knowledge base associated with the charging intelligent customer service system; the knowledge base feature set comprises at least one of a keyword set, a knowledge classification tag and a typical question library; according to the knowledge base feature set corresponding to each industry knowledge base, matching the service object feedback information with each industry knowledge base to obtain a matching result; and under the condition that the matching result indicates that the target industry knowledge base matched with the service object feedback information exists in the industry knowledge bases, updating the target industry knowledge base according to the service object feedback information. By adopting the method, the updating accuracy of the industry knowledge base in the charging intelligent customer service can be improved.

Systems, methods, and other embodiments associated with self-reliant characterization of activities of users are described. In one embodiment, a method includes generating a dataset of data points from a batch of electronic log messages that describe electronic actions taken by various accounts. A data point collectively describes actions of a single account. The method includes modeling distinct activities based on clustering of the data points into M behavioral groups and inferring M or more distinct activities from the dataset by probabilistic activity modeling of the actions. The value of M is derived automatically during the clustering. The method includes predicting activity of a user account to be non-conformant based on other accounts in a behavioral group satisfying a threshold for similarity. And, the method includes generating an electronic alert that indicates the user account to have non-conformant activity.

The invention relates to the technical field of e-commerce, and discloses an e-commerce customer service processing system with intelligent quality inspection and high-concurrency simulation capabilities. According to the invention, millisecond index calculation and real-time alarm of full customer service dialogues are realized through a bypass monitoring technology, a traditional lagging mode of post sampling inspection is changed, and management response is converted from passive remedy to active intervention; a high-concurrency pressure simulation module reproduces a business scene in an e-commerce peak period by simulating a script of a real user behavior and a distributed cluster, and a real basis is provided for system capacity planning and stability guarantee; the integrated intelligent verbal skill evaluation module deeply analyzes the dialogue quality from multiple dimensions such as semantics, compliance and emotional change based on a natural language processing technology, and generates an evaluation report with guidance, so that the professional level of customer service is improved; and the service quality, the operation robustness and the management intelligence level of the e-commerce customer service system are improved.

The invention relates to the technical field of passenger service, and discloses a construction method and device of a dynamic extension word bank, equipment and a medium. The method comprises the following steps: acquiring multi-source heterogeneous original knowledge data related to civil aviation passenger service, and converting the multi-source heterogeneous original knowledge data into a standard format text; processing the unstructured data in the standard format text based on the adaptive word segmentation model and the stop word list to obtain a plurality of candidate words; performing multi-dimensional corpus feature quantitative analysis on each candidate word to determine candidate keywords; and performing similarity calculation based on the entity word segmentation and the candidate keywords, determining effective candidate keywords, and adding the effective candidate keywords into the dynamic expansion word bank. By means of the method and device, the technical problems that in the prior art, a word bank used by a civil aviation service system is usually based on a static vocabulary or depends on manual compiling and updating, the static word bank cannot be updated in real time, the characteristics of the civil aviation field cannot be flexibly handled, and the maintenance cost is high due to manual updating and maintenance are solved.

The invention belongs to the technical field of geographic information technology and remote sensing image processing and service, and discloses a slice-free image service system and method based on dynamic projection and real-time mosaic, which abandons the traditional pre-slicing mode, directly provides online service based on original image data, and improves the service efficiency. The problem of redundant storage caused by pre-generation and storage of massive tiles is fundamentally eliminated, and storage space is saved by up to 90%. Meanwhile, when the original data is updated, the system does not need to carry out a time-consuming re-slicing process, real-time updating and publishing of services can be realized, and the core pain points of long data updating period and high delay in the traditional technology are thoroughly solved. Through the integrated dynamic projection engine and the real-time mosaic module, the on-demand service request of the client for any coordinate system, any spatial range and any resolution can be responded.