206 results about "Enterprise management" patented technology

The invention relates to the technical field of enterprise management, in particular to an intelligent decision support system and method based on cognitive logic and scenarized semanteme, and the method comprises the steps: obtaining enterprise decision data through multi-source data monitoring, carrying out the preprocessing, and generating cross-modal enterprise scene cognitive information; analyzing cross-modal association among the data, fusing a cognitive logical reasoning rule and a semantic understanding model, and constructing scenarized semantic decision fusion features; training an enterprise decision-making quality evaluation model based on historical cases, performing quality perception on a current decision-making scene, and outputting decision-making quality information; and an execution effect is judged in combination with an expected target, an optimization mechanism is started if the target is deviated, candidate schemes are generated by using a historical knowledge base and a multi-target optimization algorithm, an optimal solution is screened, and intelligent adjustment of a decision scheme is realized. According to the method, multi-source heterogeneous data and cognitive logic are fused, semantic understanding, dynamic evaluation and adaptive optimization capabilities of a decision system are enhanced, and scientificity and real-time performance of enterprise decision are improved.

The invention discloses an intelligent interaction system based on a large language model and a knowledge graph, and relates to the technical field of artificial intelligence and intelligent interaction. According to the system, data processed by a data acquisition and preprocessing module is stored in a local knowledge warehouse in a three-layer nested structure; the multi-modal semantic understanding module constructs a knowledge system in which a triple knowledge graph and a vector database are complementary by optimizing a BERT model and performing dual-channel analysis; the intelligent interaction module realizes natural language interaction and business task automatic triggering based on an RAG technology and a dialogue memory mechanism; the information change identification and analysis module generates a personnel change risk report and performs early warning; and the summary report automatic generation module outputs a structured report. According to the method, the problems of data splitting, complex interaction and slow response in traditional enterprise management are solved, the functions of system intelligent question answering, personnel change risk analysis, structured report automatic generation and the like are realized, and the management efficiency and the information consistency are improved.

The invention relates to the technical field of enterprise management and information processing, in particular to an intelligent contract-driven enterprise tax risk management system, which adopts a rule management layer and contract execution layer separation architecture: the rule management layer is responsible for configuring and testing a tax rule and generating a rule version identifier; and the contract execution layer is composed of intelligent contracts deployed in the block chain, and comprises a rule state contract for anchoring a rule version and a business risk contract for executing business logic. And coupling the off-chain rule with the on-chain contract through the rule version identifier. And the business risk contract monitors an on-chain evidence storage event, obtains a current effective rule version, delegates under-chain service calculation, verifies a returned result by signature, version, time and the like, and executes corresponding treatment after the verification is passed. For high-risk disposal, the system provides an on-chain arbitration mechanism by governing a contract. According to the method, dynamic and safe updating of the tax risk management rule is realized on the premise of ensuring that the process is automatic, credible and non-tampering.

An information technology system generally includes a cloud-based management platform with a micro-services architecture deploying a set of adaptive intelligence facilities that can be configured to automate a set of capabilities of the platform related to at least one of the value chain network entities and the features of the platform and a set of data storage facilities that can be configured to store data collected and handled by the platform. The data can be related to at least one of the value chain network entities and the features of the platform. A set of monitoring facilities can be configured to monitor the value chain network entities. The platform can be configured to host a set of applications for directing an enterprise to manage the value chain network entities from a point of origin of a product of the enterprise to a point of customer use.

The invention discloses a sports market demand prediction method and device based on deep learning and a medium, and relates to the technical field of market demand prediction, and the method comprises the steps: collecting sports demand data, and carrying out the preprocessing; performing relation mining and graph structure learning on the preprocessed sports demand data through a graph attention space-time network to generate a macroscopic demand potential energy graph; performing potential area identification on the macroscopic demand potential energy diagram by adopting a pre-trained sports market simulation model, and outputting local demand prediction data; performing weighted fusion and error correction on the macroscopic demand potential energy map and the local demand prediction data, and outputting a sports demand prediction score; and making a sports market demand strategy according to the sports demand prediction score and the multi-granularity demand prediction report, and transmitting the sports market demand strategy to an enterprise manager through an enterprise decision support interface. According to the method, multi-level accurate prediction and decision support of sports market demands are realized through dual-mechanism cooperation of the graph attention space-time network and the space-time convolution.

The invention relates to the technical field of enterprise management, in particular to a dynamic performance management system based on artificial intelligence and an implementation method. The system comprises a data acquisition and processing module used for acquiring structured and unstructured data from a plurality of data sources; the knowledge graph construction module is used for constructing a knowledge graph representing an organization semantic model by utilizing the structured and unstructured data; the performance indicator construction and adjustment module is used for constructing and adjusting performance indicators of the organization by utilizing a reinforcement learning agent based on the knowledge graph; and the visualization module is used for providing a user interface to display the performance indicators and the analysis results. According to the method, KPI strategic correlation is ensured by constructing the organization knowledge graph, closed-loop adaptive optimization of performance indicators is realized by introducing reinforcement learning, and the organization work gravity center can be guided to automatically align with the strategic direction of dynamic change, so that the strategic executive force and agility of the organization are remarkably improved.

The invention discloses a templated business process management method, and relates to the technical field of enterprise management.The method comprises the steps that repeatable task units in a business process are represented and packaged into function components capable of being configured in a draggable mode, combined arrangement is conducted in a visual working area template, and process construction is conducted from the development coding level to the development coding level; according to the technical scheme, the method sinks to a configuration level which can be understood by business personnel, in the step of creating the visual workflow template, when the working area templates bearing specific tasks are bound with process nodes, separation and standardized packaging of business logic and execution logic are achieved, and various working area templates are predefined through a graphical interface; the node function assembly can be quickly completed only by quoting the templates in the flow chart, the defect that each node needs to be independently developed or written in a traditional mode is overcome, and the core defects that in the prior art, flow construction is complex, the reuse rate is low, and the method excessively depends on technicians are overcome.

The invention discloses an enterprise digital management system based on multi-source data fusion, and the system comprises a data collection module which is used for constructing a multi-source data view from internal and external data sources of an enterprise; the embedding mapping module is used for generating a feature domain embedding vector set; the improved extremely deep factorization machine model module is used for feature extraction and explicit high-order interactive modeling and outputting a basic matching score; the triple generation module is used for constructing a positive and negative sample triple and calculating a business importance coefficient and an exposure probability; the Bayesian personalized sorting module is used for constructing weighted sorting loss and updating model parameters; and the online recommendation module is used for calculating matching scores of the candidate schemes and sorting and outputting a recommendation management list. According to the method, accurate and intelligent recommendation and sorting decision of candidate schemes in an enterprise management scene are realized by improving an extremely deep factorization machine model and Bayesian personalized sorting.

The invention discloses an enterprise management process service system based on big data, and relates to the technical field of enterprise incubation and intelligent management, and the system comprises a settlement management module, a resource demand module, a resource scheduling module and a project tracking module. The entering management module analyzes enterprise basic information and market environment data through information acquisition and value evaluation, and realizes regional grading and risk grade judgment; the resource demand module calculates a resource comprehensive value and matches an optimal allocation strategy through thermodynamic diagram analysis, shop classification and commuting evaluation; the resource scheduling module outputs, dynamically adjusts and automatically issues funds based on resource demand; and the project tracking module carries out full-cycle data monitoring and risk assessment on the project after investment. Through big data driving and an automatic process, the problems of information isolated island and much manual intervention of a traditional incubator are solved, the full-life-cycle intelligent service of an enterprise from entering to post-investment management is realized, and the resource allocation efficiency and the risk management level are improved.

The invention discloses a data processing method of a full-stack AI enterprise management system. The method comprises the following steps: constructing a time difference sequence of financial links; a delay fluctuation value is calculated through multi-scale wavelet transform and time sequence analysis, and an abnormal service link is identified by using an isolated forest algorithm; generating a consistency deviation index fusing a financial field matching rate and a domain rule weight based on a sequence-to-sequence model of an attention mechanism; inputting the deviation index and the time difference sequence into a space-time diagram convolutional network, and tracing a root business link; a timestamp synchronization strategy is adjusted according to the tracing path, and a financial rule engine is triggered to generate a correction entry; an LSTM model and a reinforcement learning agent are introduced, so that optimization verification and parameter adaptive adjustment are realized; and finally generating an abnormal positioning report and a risk assessment result. By means of the technical scheme, automatic detection, source tracing, correction and continuous optimization are carried out on abnormities in the enterprise management process, and the reliability, compliance and system autonomy ability of financial data circulation are improved.

The invention relates to the technical field of enterprise operation management evaluation, and discloses a national-owned enterprise operation evaluation method and system based on total event traceability and a computer readable medium, and the method comprises the steps: collecting original multi-source heterogeneous data in an enterprise operation process, converting the original multi-source heterogeneous data into a standard structure, and constructing a standardized three-dimensional event data set; performing weight attribute configuration and dynamic weight calibration on each standardized event number to obtain a dynamic event value weight table; performing political, economic and social event subset classification on the standardized event data, generating an initial score of each dimension, and generating a national enterprise three-dimensional evaluation result by using an event impact factor diffusion algorithm and nonlinear weighted fusion; and finally, determining an abnormal standard based on evaluation data of the same-industry and same-scale national-owned enterprises, carrying out abnormal identification and reverse traceability analysis, and constructing a complete event chain of a reason event, an intermediate event and a result event.

The invention provides an employee performance prediction method based on multi-source heterogeneous data, and relates to the technical field of enterprise management. Structured data and time sequence data of employees are collected, the two types of data are preprocessed and then associated and fused with unique identifiers of the employees as cores, and a panoramic data wide table is constructed; then static and dynamic time sequence features are extracted from the wide table, the features are input into an artificial intelligence evaluation model, the model calculates basic performance indicators through a rule engine, and performance prediction scores are obtained through comprehensive evaluation in combination with a random forest regression model; the method is further provided with a potential prediction model based on an LSTM architecture integrated attention mechanism, and performance improvement potential scores and confidence intervals in the next three months can be output. According to the method, the problems of multi-source heterogeneous data fusion, model self-adaption, single evaluation dimension and the like are solved, and the employee performance can be predicted and evaluated comprehensively, objectively and prospectively.

The invention relates to the technical field of enterprise management and artificial intelligence, discloses a management method for cooperatively solving problems based on multiple roles, and aims to improve enterprise problem processing efficiency and cooperative capability. The management method for solving the problem based on multi-role cooperation comprises the following steps: collecting and cleaning front-line work details through an employee client of a scenarized template; the AI processing module calls a fusion model of NLP semantic analysis, computer vision identification and time series data comparison, identifies problems from work details and generates a report; the role matching engine screens matched experts and pushes related information to an expert client to input a solution; after receiving the scheme, the decision-making client synchronizes a decision-making instruction to the execution main body; and the server storage module associatively stores the full-process information through the unique identifier to form a reusable corpus packet. According to the method, multi-role efficient collaboration and knowledge precipitation are realized, and a management closed loop is optimized.

The invention discloses a group-type enterprise data governance method and system, and relates to the field of data governance, and the method comprises the steps: constructing an organization structure of a group-type enterprise, and distributing an enterprise management authority corresponding to an organization condition corresponding to an organization to which the enterprise belongs based on the organization structure; obtaining a business request, analyzing a corresponding business structure based on the business request to obtain a business analysis result, and determining a data management business field corresponding to the organization according to the enterprise management authority corresponding to the organization and the business analysis result; and making a data governance work plan based on the data governance business field, and implementing data governance based on the data governance work plan. According to the method, the problems of unclear working steps and unclear responsibility division of data treatment work contents of all parties of a group type enterprise data treatment method are solved.

The invention belongs to the field of enterprise management, and particularly relates to an employee intelligent working system and a working efficiency evaluation method, and the system comprises a scheduling management module which is used for generating or adjusting a scheduling scheme according to an employee state change event and a business load change event; the performance tracking module is used for updating the performance score in real time according to the working process event and the result event of the employee; the performance early warning module is also used for generating periodic performance data according to the historical performance data and performing early warning on periodic performance abnormity according to a preset rule; the process processing module is used for automatically adjusting approval nodes according to a process initiation event based on a process type and a business rule, pushing a prompt to related personnel after the process is initiated, performing timeout monitoring on the approval nodes, and automatically urging the timeout approval nodes to do; the server is also used for counting the flow average processing duration, the node time consumption distribution and the rejection rate, generating a flow efficiency report and pushing optimization suggestions; and the terminal is used for receiving user input and displaying information. The problems of low decision-making efficiency and performance evaluation lagging are solved.

The invention relates to the technical field of enterprise management, in particular to an enterprise management-oriented enterprise operation supervision method based on a micro-service architecture, and the method comprises the steps: collecting observability data from a plurality of micro-services deployed in the micro-service architecture, carrying out the standardization processing of the observability data, and injecting a unified label set; calculating a real-time supervision index value through a supervision algorithm model by using the observability data after standardization processing, and generating corresponding interpretability information; and obtaining a real-time supervision index value, calculating to obtain a supervision index risk score at the current moment, comparing the supervision index risk score with a dynamic threshold value, generating alarm events when a preset alarm triggering condition is met, and aggregating the alarm events.

The invention belongs to the technical field of enterprise management, and particularly relates to a green transformation cost optimization method and system based on green premium, and the method comprises the steps: collecting the specified parameters of a target enterprise, so as to determine the green premium cost, the green premium cost comprises self-generation and self-use cost, special line direct supply cost, green electricity direct purchase cost, green electricity transaction participation cost, green certificate cost and green electricity investment cost; and formulating or optimizing an existing green transformation method according to the green premium cost so as to minimize the green transformation cost. Collecting specified parameters of the target enterprise to determine green premium cost; and according to the green premium cost, an existing green transformation method is formulated or optimized, so that the green transformation cost is minimized, reasonable suggestions can be provided for transformation of enterprises, and the transformation efficiency is improved.

An attendance punch-card machine based on face dynamic recognition for enterprise management comprises a punch-card machine body, a storage groove is formed in the left side of the front wall of the punch-card machine body, a clamping groove is fixedly connected to the interior of the storage groove, a handle is connected to the interior of the clamping groove, a first camera is fixedly connected to the upper portion of the outer wall of the handle, and a second camera is fixedly connected to the upper portion of the outer wall of the first camera. A first light supplementing lamp is fixedly connected to the lower portion of the first camera, a switching key is fixedly connected to the lower portion of the first light supplementing lamp, one end of a connecting line is fixedly connected to the bottom of the handle, and the other end of the connecting line is fixedly connected with the bottom of the containing groove. And when the height does not conform to the current set height and human face recognition is relatively laborious, the staff can take out the handle in the storage groove and switch the recognition camera to the first camera for face recognition by pressing a switching key on the handle, so that the convenience of the equipment is improved, and the experience feeling of the staff is improved.

The invention provides an enterprise management method and system and computer equipment, and the method comprises the steps: determining initial enterprise data of a plurality of enterprises and a corresponding enterprise management strategy, carrying out the preprocessing of the initial enterprise data, obtaining target enterprise data, generating an enterprise global database, and carrying out the calculation of the enterprise global database according to the enterprise management strategy. Determining at least one target evaluation algorithm and a corresponding service providing strategy, and based on each target evaluation algorithm, according to the target enterprise data of the plurality of enterprises in the enterprise global database, performing evaluation processing on the development conditions of the plurality of enterprises to obtain an enterprise development condition evaluation result corresponding to each target evaluation algorithm, and providing a service matched with the development condition of the target enterprise for the target enterprise based on the enterprise development condition evaluation result and the service providing strategy corresponding to each target evaluation algorithm. Therefore, operation complexity of enterprise management is reduced, timeliness and accuracy of service providing and enterprise management are improved, enterprise satisfaction is improved, and corresponding management of multiple enterprises is facilitated.

The invention provides an enterprise management process intelligent optimization system and method based on a knowledge graph, and the method comprises the steps: mapping an entity dependency relationship between graph structure nodes in an enterprise management process into the knowledge graph, and generating a process knowledge graph of enterprise management; determining time sequence influence characteristics of content update in the process knowledge graph through the dynamic attenuation factor of each management process sub-graph; calculating the data variation amplitude and the information entropy weight of each graph structure node, and further performing amplitude weighting on each data variation amplitude according to each information entropy weight to obtain the structure saliency of each management process sub-graph; and determining an aging evaluation index of each graph structure node according to the time sequence influence characteristics and each structure saliency, and carrying out batch updating on the enterprise management process based on each aging evaluation index. Based on the scheme, fusion updating of data value and data timeliness in enterprise process management can be realized, so that the execution efficiency of an enterprise business process can be improved.

A business management system with integrated business intelligence and IT-supported optimization, consisting of: a computer device comprising at least one processor and a memory arrangement for storing executable instructions; a data acquisition and integration unit that is operationally connected to the at least one processor and is configured to receive heterogeneous enterprise data from a variety of source systems, including financial transaction systems, operational control systems, human resource information systems, supply chain systems, customer interaction systems, and IT infrastructure monitoring systems, wherein the data acquisition and integration unit is further configured to normalize syntactic formats, resolve temporal inconsistencies, and map source-specific attributes into a unified enterprise data representation stored in the storage system; a business intelligence processing unit that is operationally coupled with the data acquisition and integration unit and is configured to calculate business performance indicators through multidimensional aggregation, correlation analysis, and trend extraction over the unified business data representation, with the calculated business performance indicators being time-stamped and permanently stored; an optimization unit that is operationally coupled with the business intelligence processing unit and is configured to compare the calculated business performance indicators with stored business objectives and constraints and to determine optimized business control parameters that correspond to resource allocation, operational planning, cost efficiency or performance improvement; a control and orchestration unit that is operationally linked to the data acquisition and integration unit, the business intelligence processing unit, and the optimization unit, wherein the control and orchestration unit is configured to coordinate the execution sequence, forward the results of the business intelligence analysis to the optimization unit, and manage feedback by incorporating the effects of applied optimized business control parameters into subsequent data acquisition cycles; and a communication interface that is connected to at least one processor and configured to exchange data and control signals with external enterprise systems and user terminals.

Various embodiments are directed to apparatuses, methods, computer program products, and systems related to multi-factor digital transmission screening. In some embodiments, an outbound digital transmission originating from a monitored enterprise management system may be detected. One or more data elements associated with the outbound digital transmission may be applied to one or more anomalous transmission prediction models to generate a prediction associated with the outbound digital transmission. The one or more anomalous transmission prediction models may comprise at least a contextual analytical model configured to generate the prediction associated with the outbound digital transmission based at least in part on historical digital transmission activity data based on a plurality of past digital transmissions originating from the monitored enterprise management system. Responsive to the prediction corresponding to an anomalous transmission prediction, performance of one or more data exfiltration mitigation actions to mitigate risk of data theft may be initiated.

The application provides a procurement document generation and evaluation method based on process mining analysis, relates to the technical field of enterprise management, and comprises the following steps: collecting event log data in an enterprise procurement system, constructing a procurement process hypergraph model through a process hypergraph discovery algorithm, and generating a variation correlation topological structure; constructing a self-adaptive rule mapping network according to the procurement process hypergraph model and the variation correlation topological structure, inputting specific procurement demand data into the evolved template by utilizing the network to dynamically evolve the procurement document template, filling the file content by applying a semantic intervention filling mechanism, and generating a complete procurement document; the process hypergraph discovery algorithm is introduced to construct the procurement process hypergraph model, so that complex correlations such as multi-party interaction, group decision and high-order dependence in the procurement activity can be effectively captured, and the expression capacity of the process model is significantly improved compared with the traditional Petri net or simple directed graph model.

The invention discloses a multi-agent-based enterprise operation automatic control system and method, and relates to the technical field of enterprise operation management and artificial intelligence. The system comprises a data modeling and storage layer, a data acquisition and perception layer, a multi-agent operation brain layer and an execution and feedback layer. The data modeling and storage layer constructs a unified operation data model containing three core entities of Item, Actor and Event; the data acquisition and sensing layer acquires heterogeneous data and converts the heterogeneous data into standard Event; the multi-agent operation brain layer generates a global optimal decision set through parallel decision making of a plurality of service agents and overall planning and optimal selection of coordination agents; and the execution and feedback layer converts the decision into a standardized instruction adaptive to manpower, a system and a robot to realize execution and adaptive optimization. According to the invention, multi-industry adaptation, automatic decision making and full-link closed loop are realized, the future robot operation form is supported, and the enterprise operation cost is reduced.

The invention discloses a multi-module collaborative enterprise management intelligent decision-making method and system, and relates to the technical field of enterprise management. The method comprises the following steps: integrating business modules, extracting entity nodes, and connecting the entity nodes into a flow chart according to a business flow direction; measuring points are arranged at nodes through an industrial interface, real-time and historical data and equipment start-stop and over-limit events are collected, and a data set is obtained through time alignment; identifying abnormal data; carrying out anti-fact expansion on the abnormal data based on the flow chart; performing multi-path parallel reasoning by combining original and anti-factual data; and carrying out collaborative consistency analysis on the multiple groups of results to obtain a collaborative intelligent decision result. The technical problems of data isolation among multiple service modules in enterprise management and difficulty in real-time monitoring and quick response to production abnormity are solved, and the purposes of performing multi-agent collaborative decision making by constructing a process-driven enterprise knowledge graph and combining real-time data and anti-fact deduction and improving enterprise management efficiency are achieved. The enterprise decision-making efficiency is improved; the resource configuration is optimized; and the production collaboration is enhanced.

The invention discloses an enterprise online interaction data management system, and relates to the field of enterprise data management, the enterprise online interaction data management system comprises an enterprise management center, the enterprise management center is in communication connection with an employee management module, a business process management module, a database module, a business analysis module, an employee operation module and a data monitoring module; the enterprise management center is used for setting a corresponding management area for an enterprise; the employee management module is used for managing corresponding employees and managing comprehensive points of the employees; the business process management module is used for acquiring business data and distributing the business data to corresponding management areas; the business analysis module is used for analyzing and obtaining comprehensive business data corresponding to the business data; the employee operation module distributes the business data to the corresponding employees according to the comprehensive points and the comprehensive business data of the employees; the data monitoring module is used for monitoring the business completion progress of the employees; according to the invention, business data distribution in an enterprise is more reasonable to a certain extent, and the working efficiency of employees is improved.

This application relates to a method and related system for processing cross-domain heterogeneous data of a digital twin of an enterprise management building, including: acquiring a standard semantic library of the digital twin of the enterprise management building; receiving cross-domain heterogeneous process data from different management systems; acquiring system prompt words of a large language model; inputting the system prompt words and cross-domain heterogeneous process data into the large language model to obtain a business process model file output by the large language model; parsing the business process model file and extracting the node attributes of each process node from the business process model file; mapping the node attributes of each process node to the standard definitions and standard expressions corresponding to each management atom in the standard semantic library, so as to complete the semantic fusion of cross-domain heterogeneous process data from different management systems. The above method can automatically parse and transform cross-domain heterogeneous process data from different management systems into a unified standard format, thereby realizing the semantic fusion of cross-domain heterogeneous process data from different management systems.

The invention discloses a multi-level system hierarchical management and control environment problem investigation and rectification system and method in the technical field of enterprise management. The method comprises the steps of obtaining an initial task allocation parameter set calculated by a superior unit through a task allocation algorithm; the initial task allocation parameter set is issued to a lower-level unit for troubleshooting execution; receiving problems entered by a subordinate unit after checking execution based on the initial task allocation parameter set, and performing severity judgment; on the basis of the severity obtained through judgment, early warning time of auditing of a superior unit is calculated in combination with an early warning time threshold algorithm; and calculating the rectification completion quality index of the subordinate unit based on the early warning time. According to the invention, by integrating the core module, the specialty, the collaboration and the efficiency are balanced, troubleshooting and rectification of hierarchical management and control environment problems of a multi-level system are facilitated, and the management requirements of'controllable whole process and traceable risk 'are met.

This invention relates to the field of enterprise management technology, and in particular to an intelligent decision support system and method based on cognitive logic and contextualized semantics. The method acquires enterprise decision-making data through multi-source data monitoring and preprocesses it to generate cross-modal enterprise scenario cognitive information; analyzes cross-modal correlations between data, integrates cognitive logic reasoning rules and semantic understanding models, and constructs contextualized semantic decision fusion features; trains an enterprise decision quality assessment model based on historical cases to perceive the quality of the current decision-making scenario and outputs decision quality information; judges the execution effect in conjunction with expected goals, and if deviations from the goals are detected, an optimization mechanism is initiated, using a historical knowledge base and multi-objective optimization algorithms to generate candidate solutions and select the optimal solution, thereby achieving intelligent adjustment of the decision-making plan. This method integrates multi-source heterogeneous data and cognitive logic, enhancing the semantic understanding, dynamic evaluation, and adaptive optimization capabilities of the decision-making system, and improving the scientific rigor and real-time performance of enterprise decisions.

This invention relates to the field of enterprise information management and intelligent document processing technology, specifically to an AI-based enterprise management document automatic archiving system based on semantic analysis. The system includes a cloud-based multi-source heterogeneous data acquisition module and a base semantic anchoring module, a spatiotemporal business graph construction module, a semantic context gravity coupling calculation module, and a fluid archiving execution module. By acquiring the location characteristics and flow range of business interface nodes and data source nodes, the system divides data into sub-regions, periodically collects document flow data and business pulse flow data, generates basic semantic vectors and business state weights, constructs a dynamic graph, calculates real-time correlation gravity, and executes virtual view archiving and permission mapping switching. This invention achieves the synchronous evolution of document archiving location, document permissions, and business visibility, avoiding the formation of knowledge silos due to fixed folder structures.