146 results about "Business intelligence" patented technology

The invention relates to the cross technical field of business intelligence and natural language processing, in particular to an interactive AI report generation method and system based on intelligent semantic driving, and the method comprises the steps: (1) a large language model analyzes user question semantics, calculates the matching degree with a report subject, and dynamically selects a question correction or report generation process; (2) the fuzzy query is converted into a deterministic request based on the domain knowledge base, and semantic ambiguity is eliminated; (3) analyzing field association in combination with database metadata, and generating an executable SQL (Structured Query Language); (4) dynamically rewriting SQL (Structured Query Language) according to user roles, adding permission filtering conditions, executing query and desensitizing sensitive data; (5) analyzing result features, automatically matching a visual form and generating natural language interpretation; and (6) collecting user feedback, and optimizing a semantic model and a query strategy. According to the scheme, the accuracy of natural language query and the adaptive capacity of the system can be remarkably improved, and the security of data access is guaranteed.

The invention relates to the technical field of medical data analysis and business intelligence, and discloses a hospital pharmacy competitiveness evaluation method and system based on multi-source data fusion, and the method comprises the following steps: collecting and processing multi-source data, and constructing a market entity feature vector; constructing an initial market causal atlas based on the feature vectors; initializing a digital twinning environment, and setting a dynamic behavior rule of a simulation entity; running simulation to obtain a reference competitiveness evolution trajectory; real data is periodically acquired to calculate simulation deviation; and if the deviation is greater than a preset threshold value, correcting the causal atlas and updating the simulation entity rule. The system comprises a data processing and feature construction module; a market causal relationship graph construction module; a market digital twin environment initialization module; a competitiveness evolution simulation module; a simulation reality deviation calculation module; and a causal atlas correction module. According to the method, the dynamic causal model is constructed by fusing multi-source data, so that accurate and prospective competitiveness evaluation is realized.

The invention discloses a dialogue type business intelligent analysis method based on a natural language, and relates to the technical field of business management systems, and the method mainly comprises the steps: recognizing the intention type of a user intention contained in a natural language request through a general large language model; according to the identified specific intention type, calling a corresponding special analysis module to perform semantic analysis and parameter extraction on the natural language request so as to generate an operable analysis instruction; calling a business intelligent system data interface to execute the analysis instruction, and obtaining corresponding structured data from a business intelligent system data warehouse; and generating a comprehensive analysis report which is matched with the identified intention type and the corresponding structured data and comprises visual elements and analysis explanations based on the identified intention type and the corresponding structured data. According to the method, the intention type of the natural language request of the user is understood through the large language model, so that the user with a non-professional background can easily perform complex data exploration, and the use threshold is reduced.

The invention provides a data processing method and system based on a business intelligence system. The method comprises the following steps: receiving request data, and standardizing the request data to obtain standardized data; analyzing the standardized data based on a pre-constructed dynamic semantic map to obtain an analysis result; the dynamic semantic graph is a directed attribute graph constructed based on business terms, data entities and business concepts; performing logic compiling on the analysis result to generate an executable operation chain; the executable operation chain comprises sequenced atomic operation steps, and the atomic operation steps comprise data processing logic and metadata binding information; and running the executable operation chain to obtain an analysis result corresponding to the request data. The method comprises the following steps: analyzing request data based on a dynamic semantic map; and the analysis result is logically compiled, an executable operation chain is generated, and the data processing process is decomposed into sequenced atomic operation steps, so that the data processing flow becomes clear, and the accuracy and efficiency of request data processing are improved.

Implementations described herein relate to systems and methods to generate a response to a business intelligence question received from a user. In some implementations, a computer-implemented method may include receiving the question as a natural language string, determining one or more fragments based on the natural language string, identifying one or more query operators based on the one or more fragments, constructing a structured query tree based on the one or more query operators, executing at least a portion of the structured query tree on a data source, receiving, from the data source, an output result based on the execution, generating the response based on the output result, and providing the response to the user.

Methods and system are disclosed to implement an interactive companion table alongside graphical data visualizations within a computing environment, aimed at enriching data analysis and interpretation. The underlying numerical data of the graphs are displayed through a specialized table and responses to user interactions between the graphs and the table are highly synchronized with the establishment of the bidirectional links between each graph and its corresponding cells in the table. The method encompasses several key procedures: initializing a table object, accessing graphs in the active data visualization, incorporating cell blocks to represent data elements of graphs, adding bidirectional links, refreshing the table display, and handling user interactions. The methods and system enhance the data analysis experience by closely integrating visual and numerical information and is especially useful in areas that demand an in-depth examination of data alongside a broad visualization, including financial analysis, scientific research, and business intelligence.

The invention relates to the technical field of data processing, can be applied to the fields of medical treatment and finance, and discloses a data query method, device and equipment based on a large language model and a medium, a natural language query request is rapidly analyzed through the large language model and converted into executable query key information, the query request understanding precision is improved, and the query efficiency is improved. And the query result accuracy is improved. High-correlation target data is screened out from a multi-modal fusion database fusing various types of data through a business intelligence BI tool, data of different sources and types are integrated, and the accuracy and integrity of a query result are ensured. The target data obtained through query is converted into a visual chart form through a chart data mapping model, so that the complex data relation and trend are clear, the decision support effect of the multi-modal data in the fields of financial risk assessment, medical diagnosis analysis and the like is fully played, a user can quickly understand a data analysis result, and the user experience is improved. Therefore, decisions based on the multi-modal data can be made more efficiently.

In accordance with an embodiment, described herein is a system and method for providing query acceleration with a computing environment such as, for example, a business intelligence environment, database, data warehouse, or other type of environment that supports data analytics. A middle layer is provided as a long-term table data storage format; and one more acceleration formats, or acceleration tables, can be periodically regenerated from the middle layer, wherein a determination can be made as to whether an accelerated table exists for a dataset table, and if so, then the accelerated table is used to process the query.

The invention relates to the technical field of data processing, in particular to a report generation method and device based on a business intelligence BI tool and electronic equipment, and is used for solving the problems that a traditional BI tool is high in use threshold, tedious in process and low in data processing efficiency. The method comprises the following steps: in response to a query request based on a natural language, performing semantic analysis on the query request by utilizing a pre-deployed language large model, and generating a structured query instruction corresponding to the query request; generating a target query statement based on the language large model and the structured query instruction; loading a target data source based on the target query statement, and executing the target query statement based on the loaded target data source to generate a data query result; analyzing the data query result by utilizing a language large model, and determining a first report generation strategy; and based on the first report generation strategy, generating the first report and performing visual display, so that the use threshold of the user can be reduced, the process can be optimized, and the data processing efficiency can be improved.

The invention aims to provide an intelligent data analysis multi-round reasoning method. The method comprises the following steps: receiving natural language query request data; performing entity recognition and intention recognition on the natural language query request data; performing complexity quantitative analysis on the natural language query request data by adopting complexity measurement evaluation to obtain a complexity evaluation result; constructing five types of Agents to carry out collaborative reasoning; a standardized cooperation interface and a data transmission protocol among the Agents are established; the accuracy and the reliability of a preliminary reasoning result are ensured through a cooperative conflict resolution mechanism; and sorting any preliminary retrieval result according to the evaluation data, and outputting a final retrieval result. According to the invention, intelligent processing of complex BI data analysis tasks is realized, and an efficient, reliable and intelligent technical solution is provided for enterprise data analysis and business intelligent application.

The invention provides an automatic process management method and system applied to foreign trade business intellectualization, and relates to the technical field of foreign trade business management.The method comprises the steps that firstly, initial order data, preset document template data, logistics resource configuration data and order change data of foreign trade business are obtained and integrated to form a foreign trade business total data set; then, carrying out change influence definition processing on the order change data, and determining influenced foreign trade business links and associated data; performing linkage adaptation processing on the associated data based on a defining result, and adjusting preset document template data and logistics resource configuration data; according to a linkage adaptation processing result and a foreign trade business process knowledge base, generating operation execution instructions of all links; finally, the instructions are distributed to the corresponding execution main bodies according to the execution sequence, operation execution results are received and integrated to form feedback information, automatic and intelligent management of the foreign trade business process is achieved, and the management efficiency and accuracy are improved.

The invention provides an intelligent engine collaboration method and system oriented to multi-modal query, and relates to the technical field of data collaboration process.The method comprises the steps that query dimension analysis is conducted according to a received multi-modal query request, a query analysis result is generated, tasks are dynamically distributed to matched engines based on the analysis result, and the tasks are distributed to the matched engines. All the engines execute processing operation in parallel or in a serialization mode, multi-source data association fusion is conducted on heterogeneous engine results, and fusion results are packaged into visual data to be fed back to a user; the system comprises a query dimension analysis module, an engine task distribution module, an engine execution module, a multi-source data association fusion module and a result visualization packaging module. According to the method, the multi-modal query fingerprint database and the graph structure collaborative network are constructed, and the pre-training graph convolutional network is combined to optimize the control parameters, so that the query performance is remarkably improved, the query delay is reduced, the accuracy is improved, and the method is suitable for complex scenes such as smart cities and business intelligence.

A system and method for generating an improved user interface for data analytics is provided. A first type of data analytics action is performed based on a user request. Data insights are fetched based on the first type of data analytics action for rendering one or more data assets as one or more result sets. Further, a sharing functionality is provided for sharing the one or more data assets for multiple access. Lastly, data assets are rendered in the form of one or more visualization types associated with different Business Intelligence (BI) tools based on a pre-defined set of rules. The rendered multiple data assets are combined based on a second type of data analytics action for configuring and rendering dashboard.

The invention belongs to the technical field of artificial intelligence, and provides a dialogue type business intelligent platform process optimization method, system and equipment in order to solve the problems of random errors, result adaptability defects and the like existing in a ChatBI process, and output results of all links in the dialogue type business intelligent platform process are obtained. Multi-dimensional verification is carried out on output results of all links in sequence according to the process execution sequence, the process links which possibly have problems can be found in time, and correction and optimization are carried out in time before errors are diffused to the next process link; and the output result is verified from three aspects of adapting to the original demand of the user input problem, conforming to the business logic of the process link and adapting to the use demand of the downstream process link, so that the suitability of the result is ensured, and the problems that each process link has no obvious error, but the output of the process link is disjointed from the downstream process link are avoided.

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.

The invention belongs to the technical field of self-media operation and business decision, and particularly relates to a self-media account business intelligent quotation method and system, and the method comprises the following specific steps: S1, collecting self-media account basic data, user portrait data, commercial value data and market dynamic data; s2, encrypting and storing the sensitive data through AES-256; s3, adopting a random forest algorithm to construct a basic quotation model, and combining account operation fluctuation and market nodes to realize dynamic adjustment; s4, displaying quotation composition details to the account party and supporting parameter adjustment preview; and S5, generating a multi-format personalized quotation list, and negotiating and recording full-link data based on the quotation and the cooperation effect. According to the method and the system, through integrating the self-media account basic data, the user portrait data, the commercial value data and the market dynamic data, the key information influencing the quotation is covered in multiple dimensions, the quotation association factors are comprehensively considered, the deviation caused by single data limitation is reduced, and the quotation accuracy is improved.

Comprehensive systems and methods manage software lifecycle processes in an enterprise environment, and ensures consistent, secure, and efficient handling of software applications, packages, and distribution methods. The system features a web application interface that validates user input, enforces multi-level authentication, and manages user roles and permissions. A directory system dynamically selects stored procedures based on input data and current database structure, executing operations entirely within the database. Stored procedures enforce business logic, manage complex data relationships, support data encryption, and anonymize sensitive information. Hierarchical data structures organize records with multi-level granularity, temporal tracking, and partitioning. The database management system optimizes operations, implements automatic failover, and supports real-time data synchronization. The system also includes advanced error handling, real-time monitoring with predictive alerts, a secure audit trail, and a reporting module integrating with external business intelligence tools. Automated maintenance and disaster recovery ensure scalable, secure software lifecycle management.

The invention relates to the technical field of natural language processing, and provides an ASR and NLP technology-based intelligent voice system for purchasing, which comprises an integrated application layer, a voice service layer and a data storage layer, the integrated application layer comprises an external APP, an internal purchasing subsystem and a voice assistant; the voice service layer comprises an intelligent voice model integrating an ASR voice recognition model and a UIE information extraction model; the data storage layer comprises a database component and a knowledge graph and is used for data storage and information query; the voice service layer is connected through the integrated application layer, voice data are input, an intelligent voice model of the voice service layer carries out semantic understanding on voice, and result information is output by querying the data storage layer. The intelligent voice technology and natural language processing (intelligent questions and answers) can be applied to internal purchase management and external client communication, internal company and client service voices are effectively utilized, and the improvement of operation intelligence and the improvement of service level are facilitated.

Embodiments described herein are generally related to computer data analytics, and computer-based methods of providing business intelligence data, and are particularly related to systems and methods for use with enterprise data for profile matching and generating gap scores and upskilling recommendations. In accordance with an embodiment, the system can operate to match a set of position requirements with candidate attributes or skillsets, ranking them on the basis of match scores. The system can be used, for example, to determine a skill gap between the position requirements and candidate attributes, and recommend which skills might be augmented to better address the position requirements.

The invention discloses an enterprise business intelligent aid decision-making method, device and equipment based on a multi-source large language model and a storage medium, relates to the field of artificial intelligence, is applied to terminal equipment carrying a target intelligent aid decision-making system, and comprises the following steps: obtaining a to-be-decided task related to a target enterprise business to determine target label data; obtaining corresponding target portrait data from a target business portrait database of the corresponding dimension based on the target label data by using the target business knowledge database to generate a corresponding structured parameter packet; based on a task type corresponding to the task to be decided and a pre-acquired target mapping table, determining a target large language model corresponding to the task type; and utilizing the target large language model to generate an intelligent auxiliary decision related to the target enterprise business based on the structured parameter packet and the target cue word template, so as to complete the target enterprise business based on the intelligent auxiliary decision. According to the invention, different large models can be called according to business requirements.

The present application belongs to the technical field of artificial intelligence, in order to solve the problems of random error and result adaptability defect existing in ChatBI process, the present application provides a dialogue business intelligence platform process optimization method, system and equipment, the output results of each link in the dialogue business intelligence platform process are obtained, the output results of each link are sequentially checked in multidimension according to the process execution sequence, the process link that may have problems can be found in time, and the error is corrected and optimized in time before it spreads to the next process link; moreover, the output results are checked from three aspects of adaptation to the original demand of user input problem, compliance with the business logic of the process link itself and adaptation to the use demand of the downstream process link, the adaptability of the result is guaranteed, and the problem that the output of each process link is disconnected with the downstream process link without obvious error is avoided.

The invention belongs to the technical field of service intelligent evaluation, and particularly provides a service provider SLA evaluation dynamic service model implementation method and system, and the method mainly comprises the steps: obtaining the SLA evaluation source data of a service provider, the SLA evaluation source data comprises operator SLA data, enterprise end-to-end APM data, third-party network quality data, and dependency link probe data between service providers; the method comprises the following steps: by taking service providers as nodes, setting a credibility weight for each node according to a preset rule, determining directed edges between the nodes according to a preset dependency relationship between the service providers, and determining a connection weight of the directed edges according to dependency link probe data; according to the method, dynamic accurate evaluation under multi-dimensional data fusion is realized, the objectivity and credibility of an SLA achievement rate evaluation result are improved, and reliable decision support is provided for enterprises to screen cloud service providers and optimize service deployment.

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.

The invention relates to the technical field of power grid project cost management and business intelligence, and discloses a project cost multi-stage intelligent analysis and examination method, system, equipment and medium, and the method comprises the steps: building a power grid project cost data warehouse, and achieving the integration and standardization of multi-source cost data; establishing an OLAP multi-dimensional analysis model, and supporting general cost comparison and key index analysis in a budget calculation stage, feasibility research estimation, preliminary design budget calculation, completion settlement three-calculation comparison, first supply material check and review list consistency check in a settlement stage; designing an intelligent decision engine based on data mining, and generating review opinions through association rules, a classification algorithm and an anomaly detection technology; and a BI visual instrument panel is developed, and multi-dimensional display, real-time monitoring and interactive analysis of the power grid cost data are realized. Through systematic application of the BI technology, deep mining, intelligent decision and visual display of engineering cost analysis are realized, and the efficiency and precision of cost review are remarkably improved.

The present application relates to the technical field of data processing and business intelligence, and more particularly to a dynamic multi-mode SQL generation method and system based on a four-quadrant strategy, the method comprising the following steps: obtaining and quantifying the complexity and flexibility of user queries; dynamically switching SQL generation modes based on a four-quadrant strategy and a decision gateway; under the selected SQL generation mode, performing data processing and analysis, and returning query results. Through an intelligent routing engine, the present application performs accurate qualitative and quantitative analysis on user queries before SQL generation, automatically shunts to the optimal solution according to the analysis results, and takes into account the reliability and flexibility of queries.

The invention relates to a natural language to SQL query method and system based on a large model, and relates to the technical field of artificial intelligence and business intelligence. The method comprises the following steps: constructing a vectorization knowledge base containing a business context; based on the vectorization knowledge base, receiving and analyzing a natural language problem of the user, generating and executing an SQL query, and returning a query result to the user; based on the query result, generating a parameterized index SQL template from the query result, and storing the parameterized index SQL template in an index template library; and providing a configuration interface for a user to create a report template, binding at least one index SQL template from the index template library in a paragraph of the report template, and configuring a copywriting generation rule for each paragraph. The method has the effect of solving the problem that a large model is understood insufficiently in a complex service scene as much as possible.

The invention discloses a private domain traffic competition relationship quantitative generation method, belongs to the technical field of business intelligent analysis, and aims to solve the problem that the competition relationship in a private domain scene is difficult to accurately quantify. Through an intelligent contract deployed in a block chain, user operation behaviors of each private domain scene are monitored in real time, and standardized tuple data and an operation data set are constructed. When new data is accessed, operation type codes are analyzed, key operations are identified, associated behaviors are retrieved by using a time window, and a causal association map of the key operations is constructed in combination with service priorities and time decay factors. And extracting map feature vectors, marking scene codes, dividing clustering categories, and triggering an updating mechanism to obtain a feature causal association map. And constructing a standardized behavior matrix based on the updated graph, quantifying the behavior mode similarity between scenes through a graph editing distance algorithm, generating a keyword vector in combination with semantic classification mapping, forming a private domain traffic competition relationship quantitative report, and providing data support for enterprise operation decision making.

A system is described that generates descriptive insights in a manner that does not require observations to be made by a visually-impaired user and that can present insights in a form perceptible by such a user. A structured dataset or a digital visual graph may include business intelligence or other types of data. In the case of a graph, the graph is converted to the structured dataset. Parameter names in the dataset are encoded using parameter metadata. Relationships among the data of the dataset are identified based on the encoded parameter names and content of the parameters. The relationships are evaluated based on domain knowledge to generate insights. The insights are applied to automatically-selected text templates to generate descriptive insights. The descriptive insights may be presented to a user in a user interface (e.g., in a BI dashboard) or converted to a form perceptible by a visually-impaired user (e.g., speech).

The invention discloses an intelligent advertisement putting optimization method based on multi-source data aggregation, which relates to the technical field of advertisement putting, and comprises the following steps: on the basis of a user interest state vector and an advertisement unified representation vector set, utilizing a multi-task prediction model to parallelly calculate a pre-estimated target value of a candidate advertisement, and according to the pre-estimated target value of the candidate advertisement, calculating the pre-estimated target value of the candidate advertisement; constructing a comprehensive value function, solving a Pareto front of the comprehensive value function by using a multi-objective optimization algorithm, screening an optimal dynamic weight combination from the Pareto front, and calculating the real-time comprehensive value of each candidate advertisement by using the optimal dynamic weight combination. And calculating a final sorting score of each candidate advertisement according to the real-time comprehensive value of each candidate advertisement, and executing advertisement putting according to the final sorting score. According to the invention, the timeliness and correlation of advertisement putting are enhanced, and the advertisement matching precision and the business intelligence level are improved.

This invention discloses a method and system for constructing a data model for a business intelligence agent based on deep learning, relating to the field of deep learning technology. Through continuous processing from steps S1 to S4, the business intelligence agent no longer trains its model solely based on the final adopted decision results. Instead, it incorporates candidate information explicitly rejected during historical decision-making processes into the modeling scope. It retains excluded candidate decisions by constructing a set of rejected information (Una), and transforms the original rejected information into computable multi-dimensional structured data by generating a set of rejected features (Ufc). Then, based on the density of rejected information (Ind), it characterizes the concentration of rejection behavior at different decision stages, forming a rejected boundary representation (Nbd) which is applied to the business intelligence agent. When generating new candidate decisions, it can proactively identify and avoid historically high rejection density regions. Compared to existing methods that rely solely on input and output results for training, this approach overcomes the problem of insufficient learning of decision boundaries.