1098 results about "Business enterprise" patented technology

The invention discloses a method for analyzing a matching degree between a demand and an output result based on text semantics. The method comprises the following steps: step 1, labeling a data set; step 2, technical document preprocessing; 3, training and predicting a single-parameter model; 4, integrating prediction results of the multi-parameter model; the method has the beneficial effects thatthe method is simple; deep learning and the NLP technology are applied to the field of project association degree calculation of enterprise project management for the first time. Calculating an association matching degree between the two projects according to project requirements and result description; the associated project positioning difficulty is effectively reduced; meanwhile, the demand side can be helped to quickly and efficiently locate high-quality projects adapting to the demand of the demand side; time and resource investment for achievement screening and matching are greatly reduced, the association matching degree between projects is calculated by means of text data of existing project achievement technical documents and project declaration guidelines, and then large enterprises are assisted in screening high-quality projects with the high matching degree in the project bidding and tendering link.

A system may include a data classification module configured to classify data into classified data based on predefined sensitivity levels and regulatory compliance requirements. A system may include an access control module configured to manage permissions for different user roles within an enterprise, granting access to the classified data in accordance with the sensitivity levels and regulatory compliance requirements. A system may include a data formatting module configured to format classified data into formatted data with customized presentations for various enterprise departments. A system may include an integration module configured to interface with at least one of an Enterprise Resource Planning (ERP) system or a Customer Relationship Management (CRM) system to retrieve and classify the data. A system may include a user interface module configured to present the formatted data within the host application, providing a seamless user experience for accessing the embedded marketplace.

The application belongs to the technical field of business intelligence evaluation, and specifically provides a service provider SLA evaluation dynamic business model implementation method and system. The method mainly comprises: obtaining SLA evaluation source data of a service provider, wherein the SLA evaluation source data comprises operator SLA data, enterprise end-to-end APM data, third-party network quality data and dependent link probe data between service providers; taking the service provider as a node, setting a credibility weight for each node according to a preset rule, determining a directed edge between nodes according to a preset dependent relationship between service providers, and determining a connection weight of the directed edge according to the dependent link probe data. The application realizes dynamic and accurate evaluation under multi-dimensional data fusion, improves the objectivity and credibility of SLA achievement rate evaluation results, and provides reliable decision support for enterprise screening of cloud service providers and optimization of service deployment.

1. The name of the design product: electronic device with cartoon image dynamic online customer service consultation user interface. 2. The use of the design product: an electronic device. 3. The design points of the design product: the content of the graphical user interface in the screen. 4. The picture or photo that best indicates the design points: design 1 front view. 5. The entity product is a common design, and other views are omitted. 6. Design 1 is designated as the basic design. 7. The use of the graphical user interface: the design product is used for enterprise website platform consultation. When users visit the website, they can conduct online consultation by clicking different buttons of online customer service on the page. 8. The human-computer interaction mode of the graphical user interface: design 1 front view, design 2 front view, design 3 front view, and design 4 front view are all initial interface diagrams; design 1 interface change state diagram is the interface change state diagram based on design 1 front view, automatically scrolling complete subtitles and automatically playing IP image animation, wherein the enterprise IP image circulates to welcome users by opening hands, and the left side circulates to display "xxxx company welcomes you!" subtitles from bottom to top; design 2 interface change state diagram is the interface change state diagram based on design 2 front view, moving the mouse to the blue telephone icon, wherein the consultation hotline is displayed, and the telephone information can be copied through the mouse; design 3 interface change state diagram is the interface change state diagram based on design 3 front view, moving the mouse to the blue email icon, wherein the email information is displayed; design 4 interface change state diagram is the interface change state diagram based on design 4 front view, moving the mouse to the blue communication icon, wherein the scan code information and text are displayed.

This invention discloses a data mining-based method for predicting enterprise operational risks, comprising the following steps: Step 1: retrieving and extracting operational records from the enterprise's operational ledger to obtain operational risk-related data; Step 2: performing periodic slicing and slot arrangement on the operational risk-related data; Step 3: generating an operational risk state tensor through state vector organization and slot-based foldback input mapping; Step 4: generating a target operational risk prediction sequence from the operational risk state tensor using an improved DLinear network; Step 5: performing risk inertia determination based on the target operational risk prediction sequence using rescaled range analysis and identifying abnormal transition cycles using the Z-score method; Step 6: determining the operational risk level of the target enterprise; and Step 7: generating operational adjustment suggestions. This invention improves the accuracy of enterprise operational risk prediction through the improved DLinear network and rescaled range analysis.

The application relates to the technical field of resource scheduling, in particular to an enterprise resource scheduling management method and system based on big data. The method comprises the following steps: acquiring and determining process parameters and a delivery deadline of a demand product based on order information, and performing reverse analysis on the process parameters to obtain a production mode of the demand product; the production mode comprises a demand process and corresponding demand load; calling production planning of an enterprise section corresponding to the demand process based on the delivery deadline, and analyzing a load trend of the enterprise section based on the production planning through a preset big data model to generate a dynamic constraint baseline; in response to the case that the demand load meets the dynamic constraint baseline in the production planning, first allowed calling prompt information is generated; the first allowed calling prompt information is used for indicating that production resources of the enterprise section are allowed to be called; and the method can effectively solve the problem of poor scheduling accuracy.

The application provides a kind of blow molding product full life cycle quality tracing and process sharing system based on blockchain, belongs to intelligent manufacturing and industrial data security technical field.The system includes data acquisition and storage module, for obtaining production information and storing key characteristic value or hash value in blockchain;Multi-party collaborative management module, for configuring dynamic data access rights for participants through smart contract;And process knowledge asset management module, for extracting process parameter set from blockchain data that is strongly associated with high-quality output results, encapsulating as verifiable process knowledge package, and realizing its pricing, transaction and feedback loop through smart contract.The method realizes cross-enterprise trusted data tracing, safe sharing and value realization of process knowledge through the collaborative work of the above modules, improves product quality consistency and industry knowledge reuse efficiency.

The application discloses a kind of based on working condition division concentrator electric load modeling and production plan optimization method.The method first defines normal production, low production operation, three production states and corresponding load coefficients of shutdown maintenance, in combination with typical daily load curve, daily random fluctuation factor and seasonal variation factor, construct multi-layer composite annual load refinement model;Again, initial production plan is generated by state coding, and the scattered maintenance day and low production operation day are integrated into continuous period by using centralized scheduling optimization algorithm, to reduce the frequency of production state switching;Finally, the optimized production plan and load model are integrated to generate a 8760-hour refined load sequence throughout the year.The application realizes the deep coupling of production plan and electric load, significantly improves the stability and accuracy of load prediction, provides reliable data support and decision basis for power grid planning, demand side response and enterprise energy efficiency optimization, and is highly adaptable and easy to implement.

The objective is to provide a method for businesses to efficiently manage and calculate their greenhouse gas emissions. [Solution] A method for recommending carbon credits for a business operator according to one embodiment of the present invention, wherein the control unit of a management terminal receives search conditions for carbon credits from the business operator terminal, refers to carbon credit information stored in the storage unit of the management terminal, extracts one or more carbon credits that match the search conditions, and transmits the extracted carbon credits to the business operator terminal.

This invention relates to the technical fields of data quality, data management, and data governance. Specifically, it relates to a method for simultaneously conducting data governance within a newly built business information system. This method establishes a general data management standard covering data specifications, database specifications, and process specifications; builds a supervisory standard that runs through the entire process of project requirements analysis, design, development, deployment, and operation and maintenance; and integrates these two types of standards into the technical requirements of the newly built business system project. Data governance is implemented step-by-step at each stage of the project, thus avoiding data quality problems from the source of business system construction. This avoids the additional costs and schedule risks of traditional post-event governance, ensures that the system data format is uniform, secure, and compliant, and can seamlessly integrate with the enterprise's existing data governance system, solving the problems of data silos, redundancy, and inconsistency in multi-system parallel scenarios.

The application provides a construction scheme intelligent generation method and system based on multi-agent cooperation, and relates to the field of building engineering digitization technology. The method comprises the following steps: constructing a project knowledge base containing vector index and knowledge graph index; retrieving similar historical schemes based on project characteristics and learning chapter structure characteristics; generating a construction scheme outline; performing knowledge-enhanced retrieval on the chapter to be generated to obtain structured technical data; using a double-channel generation mechanism to process general chapters and construction method chapters respectively; receiving natural language fine-tuning instructions to complete content correction; converting the generated content into a standard Word document and applying an enterprise template. The system comprises a knowledge base construction module, a template retrieval module, an outline generation module, a knowledge retrieval module, a multi-agent cooperation module, a full-text integration module, and a document output module. The application significantly improves the efficiency and technical accuracy of construction scheme preparation through multi-agent division of labor, knowledge-enhanced retrieval, and double-channel generation, and solves the problems of low efficiency, case residue, and insufficient targeting in traditional scheme preparation.

This invention discloses a patent collaborative recommendation method based on a topic-enhanced neural network model, belonging to the field of patent recommendation technology based on deep learning models, and mainly involving a patent collaborative recommendation method based on a topic-enhanced neural network model. The specific method includes: S1 constructing a university-enterprise patent fusion dataset; S2 preprocessing the summary text in the fusion dataset to obtain preprocessed samples; S3 identifying R&D topics on the pre-trained samples based on the BERTopic model; S4 constructing feature datasets for universities and enterprises respectively based on the sample topics; S5 constructing a topic-enhanced neural network recommendation model; and S6 outputting a list of recommendation results. This invention effectively alleviates the problem of model overfitting caused by data sparsity and the low accuracy of traditional recommendation models.

A system associated with an enterprise computing environment infrastructure may include a chaos testing tool data store that contains a plurality of electronic records, each record including a chaos engineering fault parameter. A computer processor of a chaos testing tool may receive, from a chaos testing user, injection information associated with an element of the enterprise computing environment infrastructure. The chaos testing tool may then access the chaos engineering fault parameter from the chaos testing tool data store and automatically arrange to inject a chaos engineering fault into operation of the element of the enterprise computing environment infrastructure in accordance with the injection information and the chaos fault parameter. A response of the element of the enterprise computing environment infrastructure may then be measured subsequent to said injection, and the system may output an indication of the measured response to the chaos testing user.

This invention relates to the field of intelligent auditing, and more particularly to a graph neural network method and system for mining hidden relationships among multiple sets of enterprise accounts. The method includes: acquiring multiple sets of accounts of a target enterprise, extracting entity and transaction information, and constructing a heterogeneous graph network containing multiple types of nodes such as enterprises, individuals, bank accounts, and transaction vouchers, as well as multiple types of edges such as fund transfers, control, and voucher associations; inputting the heterogeneous graph into a pre-trained GNN, aggregating neighbor features through graph convolutional layers, and updating node embedding vectors; based on the embedding vectors, using an attention mechanism to calculate the confidence of hidden relationships between node pairs, and filtering suspicious related node pairs; performing path reasoning and backtracking on suspicious node pairs, mining multiple paths, and generating a chain of evidence for related paths. This application, by constructing a heterogeneous graph containing multiple types of nodes and edges, comprehensively captures entities such as enterprises, individuals, accounts, and vouchers and their multidimensional relationships, solving the problem that existing methods are unable to comprehensively characterize complex relationship scenarios and capture hidden relationships.

The embodiment of the specification provides a method, system and storage medium for detecting health status of an organization, comprising obtaining at least one health detection index item and enterprise data of a target organization, analyzing the enterprise data based on the at least one health detection index item, and determining at least one health detection index value of the target organization; obtaining a standard health detection index corresponding to the at least one health detection index value, and determining health assessment data of the target organization based on the at least one health detection index value and the corresponding standard health detection index; determining recommended learning content based on the health assessment data and the enterprise data; and determining a regular evaluation plan based on a preset method.

Embodiments of the present application provide a report processing method, device, equipment and medium. The method comprises: identifying the to-be-merged account data generated by the internal transaction of an enterprise from a plurality of single reports, then performing a merging and offsetting processing on each group of to-be-merged account data, generating a corresponding merging and offsetting voucher, storing the offsetted account data in a preset offsetting information storage area, and generating an offsetting account single report. Finally, a final merging report is generated according to the single report data and the offsetting account single report data. Through the above method, the account data merging efficiency is effectively improved, and the reporting period of the merging report is shortened.

The application discloses an offline evaluation system for enterprise ecological strategy based on a Web front end, comprising a front-end application layer, a resource management layer, a core function layer and a data storage layer; user registration is completed through the resource management layer, and a core shard storage module is pre-cached, and a WebAssembly inference engine module is initialized; user input is received through a user interface, and data input by the user is stored in the core shard storage module in real time, network state detection is performed through the resource management layer, when in an offline state, the WebAssembly inference engine module obtains data from the core shard storage module and performs relevant calculation tasks to determine the risk of the ecological system; the WebAssembly inference engine module transmits the calculation result to the front-end application end and visually presents it to the user. In the application, enterprise ecological strategy evaluation can be performed whether the user is in a network environment or not, the continuity of enterprise decision-making work is ensured, and internal data does not need to be uploaded to a third-party platform, so that the risk of leakage of core business secrets is reduced.

This application provides a credit risk analysis method applicable to the fields of big data and artificial intelligence. The method includes: responding to a credit risk analysis request for a target enterprise, acquiring multi-dimensional credit data of the target enterprise, and extracting a set of credit risk features for each dimension based on the credit data. These multiple dimensions include financial, cash flow, and financing dimensions. The method also involves inputting the set of credit risk features for each dimension into a corresponding sub-model to obtain analysis results for that dimension. These results include the initial credit risk level of the target enterprise under different performance periods and risk types in each dimension. Finally, the analysis results are input into a fusion model to obtain the final credit risk level of the target enterprise under different performance periods and risk types across multiple dimensions. This application also provides a credit risk analysis device, equipment, storage medium, and program product.

The application discloses a kind of multi-dimension resume intelligent screening and post matching method based on large model, it is related to artificial intelligence and recruitment technical field.The method includes: resume and post information are preprocessed and standardized;Using recruitment field fine-tuning large model, combined with knowledge graph, hierarchical attention mechanism and BiLSTM-CRF structure, extract the multi-dimension feature of resume and post;By cosine similarity, analytic hierarchy process and hungarian algorithm, construct matching model, realize global optimal matching;Adaptive threshold is used to complete final screening and output matching result.The application can significantly improve resume screening efficiency and matching precision, solve the problems of traditional mode such as insufficient semantic understanding, one-sided feature extraction and simple matching logic, suitable for various enterprise recruitment and human resource management scenarios, with high practicality and popularization value.

The application provides a process consultation and responsibility association question-answering method and system based on an enterprise knowledge base, comprising: obtaining dialogue information of inquiring process consultation and responsibility association; querying in an enterprise knowledge base according to the dialogue information to obtain corresponding query results, wherein the enterprise knowledge base comprises a vector database for vector representation information, a document database for storing document content, and a knowledge graph for storing responsibility association; and analyzing the query results by a large model to generate and display the results of the final relevant process information and responsibility association information, so as to solve the problems of low efficiency of traditional query methods and unclear responsibility in enterprise knowledge management.

The application discloses a marine product inspection digital application system and method based on a lightweight database and a configurable interface, an electronic device and a medium. The method can include: an enterprise user runs a client, initiates enterprise authentication to a CA authentication; after the client is authenticated, the enterprise's product basic data, inspection item list and corresponding data dictionary configuration are automatically obtained from the server end; the enterprise user applies for product inspection on the client; the client automatically assembles the locally stored structured data into a message conforming to the interface specification according to the data dictionary configuration, and submits it to the server through the CA authentication channel; after the inspection is completed on the server, the product certificate is sent to the client of the enterprise and stored locally. The application integrates a lightweight database, a configurable interface and a secure authentication mechanism, realizes seamless connection of enterprise and classification society data, guarantees data quality and safety, and implements marine product inspection digital specification.

The invention provides a rules engine that manages user requests within an interface integrating multiple AI platforms and AI Models. Upon receiving a query, the engine assigns scores based on factors like management rules, user preferences, and contextual information. Determinative scores, such as those enforcing strict enterprise policies, can override others, leading the engine to block or reroute the query. If no score is determinative, the engine forwards the query and associated prompts to a specialized routing AI Model for contextual analysis. Based on this analysis, the rules engine directs the query to the most appropriate AI Model or defaults to the user-designated AI Model. This system balances user intent with rule enforcement, optimizing query processing across various AI platforms while ensuring compliance with enterprise guidelines.

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.

To provide a method for evaluating feasibility of commercialization of corporate commercialization plans or academic papers using generative AI, and a cloud-based commercialization determination support system for implementing the method.SOLUTION: A method for evaluating feasibility of corporate commercialization plans using generative AI and commercialization evaluation scores, includes the steps of: preparing a commercialization evaluation score in which evaluation points are assigned for every piece of evaluation criteria information prepared in advance with respect to a commercialization plan of a target company; inputting the evaluation points assigned to the evaluation criteria information of the commercialization evaluation score and necessary questions or instructions / commands to a generative AI to learn; and causing the generative AI to create a commercialization evaluation relating to the commercialization plan and output it in text or voice. In addition, a cloud-type commercialization determination support system capable of determining commercialization evaluation from a communication terminal has been proposed at the same time.SELECTED DRAWING: Figure 1

This invention discloses a multi-dimensional analysis system and method for regional economic development potential, aiming to solve the problems of scattered data, single dimensions, and subjective and lagging assessments in traditional regional economic analysis. It adopts a three-layer architecture: a data layer, a model layer, and an application layer. The data layer integrates multi-source data from statistical yearbooks, government information disclosure, the internet economy, and geospatial data, forming a unified analytical foundation through standardization and outlier processing. The model layer constructs a six-core dimension indicator system, including economic scale and industrial structure, and uses entropy weighting, TOPSIS, and regression analysis to achieve quantitative assessment, supporting dynamic updates and adjustments. The application layer outputs analysis results through visualization and customizable functions. This invention achieves deep integration of multi-source data, comprehensive characterization of multi-dimensional potential, and objective, accurate, and timely assessment results, adapting to various scenarios such as government decision-making and corporate investment, providing scientific and efficient decision support for high-quality regional economic development.

The application discloses an enterprise financial data analysis method and system based on big data processing, which comprises the following steps: collecting multi-source heterogeneous financial data of an enterprise, generating a global financial relationship structure and a partition structure set; performing hierarchical structure etching processing, generating an etching skeleton structure, and constraining the etching process; performing continuous structure etching evolution, generating an etching stable structure; injecting constraint driving and performing structure domestication processing, generating a domestication evolution structure; performing structure convergence behavior analysis, dividing structure domesticable states, and generating a structure domesticable state set; constructing a structure domestication adjustment mapping relationship, and generating a financial data analysis result. The application realizes financial data analysis through a structure etching and constraint propagation method, and has the advantages of clear structure expression and high analysis accuracy.

Provided is a commodity transaction system with which convenience for a business operator or user can be achieved. A management server of the commodity transaction system 1 sets an assortment of commodities that can be provided to a user, selects, by means of a lottery, one or more of the commodities from the assortment in accordance with a lottery operation of a user-side information terminal used by the user, and transmits, to the user-side information terminal, winning information pertaining to the selected commodity. The user-side information terminal displays the winning information transmitted from the management server and selects, on the basis of a selection operation by the user, whether to acquire the commodity indicated by the winning information. The management server carries out a process for providing the user with the commodity for which acquisition was selected by the user-side information terminal from among the commodities selected by means of the lottery, transfers, from a winning list to a picking list, data of the commodity selected for acquisition, prevents said data from remaining in an assortment setting, and prevents data of commodities not selected for acquisition by the user-side information terminal from among the commodities selected by the lottery from remaining in the assortment setting.

This invention discloses a closed-loop management and method for the entire lifecycle of enterprise strategic planning, relating to the fields of enterprise information management and network security technology. It involves acquiring the enterprise strategic plan and creating a separate version after each change; encrypting the version and obtaining a hash fingerprint; storing the hash fingerprint and unique version number in a decentralized manner; storing the encrypted version and key on a cloud server; when a user accesses the platform, network traffic characteristics are collected and input into a network security analysis model trained by a spatially limited multi-stage exploration algorithm to determine the security monitoring results; if secure, the target version data is scheduled and its integrity is verified using the decentralized hash fingerprint; after successful verification, the data and the key encrypted with the user's public key are securely transmitted to the user. This achieves absolute tamper-proof and closed-loop traceability of the strategic planning version, and improves the accuracy of network environment perception through a multi-stage exploration algorithm, constructing a highly secure data access and transmission defense line.

The application discloses a kind of AIGC content generation and GEO optimization distribution method and system based on knowledge graph constraint.The core of the method is to change the AIGC content generation process from "unconstrained free generation" to "knowledge graph hard constraint generation", and change the content distribution from "passive waiting for inclusion" to "active reverse optimization distribution".The method first establishes the brand exclusive text business travel structured knowledge graph, and uses the hard facts such as merchant coordinates, joint IP and product SKU as mandatory boundary prompt words to constrain the text generation of large language model;At the same time, through the reverse analysis of the recommendation preference of mainstream generative AI engine by automatic probe, the preference vector matrix is formed to guide corpus generation;Then, through the full-automatic distribution platform, the corpus is fed to the whole network in batches through multiple channels;Finally, through the inclusion tracking probe and feedback closed-loop mechanism, the dynamic rectification of strategy is realized.The application realizes the generative engine optimization (GEO) for large model for the first time at the system level, effectively eliminates AI content illusion, realizes more than 80% automation of core operation process, and significantly reduces the cost of enterprise customer acquisition.