25 results about "Fact table" patented technology

The invention relates to the technical field of intelligent law education and law reasoning, and discloses a law immersive education system based on artificial intelligence, and the system comprises an input processing module which is configured to carry out the multistage semantic analysis of a law text inputted by a user, and generates a structured law fact representation; the legal knowledge graph construction module is connected with the input processing module and is used for receiving the structured legal facts and constructing and updating a legal knowledge graph; and the automatic theorem proving module is connected with the legal knowledge graph construction module and is used for executing multi-hop reasoning on the legal knowledge graph based on probabilistic reasoning. According to the technical scheme, the self-adaptive optimization module and the dynamic reasoning mechanism are combined, the technical effects of adjusting the priority of the legal rule in real time and automatically optimizing the reasoning path are achieved, the defects that the reasoning process is stiff, the adaptability is poor, and reasoning errors are likely to be caused are overcome, and the intelligent decision-making capacity of the system is remarkably improved.

In some embodiments, there is provided generating a logical query plan for a query that includes a single fact table and multiple reducer tables; optimizing the logical query plan for query execution; and executing the optimized logical query plan.

The invention discloses a multi-dimensional data association analysis system and method based on unified modeling, and relates to the technical field of big data intelligent analysis. Comprising the following steps: 1, constructing a semantic model; step 2, carrying out query compiling and optimization; 3, performing query execution and scheduling; 4, interactive analysis and visualization are carried out, wherein a multi-dimensional report designer MRD is used for providing end-to-end full-process visualization display, and interactive drilling and narrative analysis are supported; step 5, performing closed-loop optimization; according to the method, the complexity of an underlying data structure is shielded through the semantic model, and automatic correlation analysis of a cross-fact table is supported, so that business personnel can independently complete deep data exploration and decision support without mastering professional technologies such as SQL (Structured Query Language) and the like.

The present invention proposes a large-screen data statistics method based on multi-dimensional configuration, which includes: configuring database query statements and determining the configurations corresponding to the input database and the output database; aligning the source data business fact table using a high-frequency value inheritance conflict resolution algorithm; configuring different field accumulation strategies for local organizational statistical data with policy tags, and configuring an accumulation extraction strategy; sorting the data bound to the extraction strategy and the local organizational statistical data with policy tags; generating a path animation sequence based on a secondary pop-up data set and a statistical optimization path scheme, and integrating it into the display large screen to obtain the final large-screen display result. The present invention automatically standardizes heterogeneous fields of different databases through a database-driven semantic alignment algorithm, solves the problem of multi-source data integration, and uses high-frequency value inheritance conflict resolution technology to significantly improve the accuracy of filling empty fields and eliminate statistical deviations.

Arrangements for partition handling for multi table scan semi join operations are provided. Partition information of a first logical relation may be determined. Partition information of a first physical operator may be determined based on the partition information of the first logical relation. The partition information of the first physical operator may be stored in a data structure which includes partition information of a fact table and of each reducer in a predefined sequence. Partition information of a second logical relation may be determined. The partition information of a second physical operator may be determined based on the partition information of the second logical relation and the partition information of the first physical operator. The partition information of the second physical operator may be stored in the data structure. Execution of the second physical operator may be performed using the stored partition information, skipping mappings between pairs of partitions.

This invention relates to the field of rural economic data analysis technology, specifically an artificial intelligence-based method for rural economic data analysis. The method includes: delineating an economic data perception domain in a geographic information system based on the administrative division vector data of the target administrative village; collecting multi-source heterogeneous economic data through a protocol parser of an agricultural IoT terminal and converting it into standardized economic behavior data; extracting entities using natural language processing technology to generate a structured rural economic behavior fact table; inputting the fact table into a pre-trained economic activity association model and constructing a rural industry relationship graph using a graph embedding algorithm; and calculating the centrality index of economic entities based on the graph topology to identify core operating entities. This method enables accurate processing and association analysis of rural economic data, clearly presenting industry relationships and providing effective technical support for rural economic analysis.

The invention discloses a data fusion system and method based on a logistics system and a financial system, and relates to the technical field of data fusion, and the system comprises a multi-source data collection layer which is used for capturing the logistics state in real time through an Internet of Things device, connecting the financial system to obtain main data of commodities and clients, and filtering abnormal data through a data cleaning rule engine; the business and financial mapping layer is used for dynamically matching logistics events and accounting subjects through a weighted Bayesian model based on a preset rule base to realize intelligent mapping; the automatic processing layer is used for generating an accounting document in real time according to a mapping result and detecting an abnormal pipeline by adopting a convolutional neural network; and the unified data layer is used for constructing a fusion warehouse containing a logistics fact table and a financial dimension table based on data output by the acquisition layer and a mapping result of the mapping layer, forming a unified data view through data fusion, and providing a cross-system BI board to support correlation analysis. According to the invention, data fusion of a logistics system and a financial system can be realized.

The present application relates to a distributed data warehouse construction method for hydropower production equipment health monitoring, comprising: analyzing hydropower equipment data application requirements to determine the analysis theme of the hydropower equipment; constructing a data warehouse layered architecture comprising an original data layer ODS, a detailed data layer DWD, a service data layer DWS, a theme data layer DWT, and a data application layer ADS; establishing a hydropower production equipment data model; and constructing a hydropower production data warehouse physical model comprising dimension tables and fact tables. The present application realizes unified extraction, conversion and loading of various system data sources of the hydropower plant, guarantees data quality, and breaks data silos; realizes centralized and unified management of data, utilizes data backup, data security control and access permission management functions of the data warehouse to ensure data security and reliability; reduces manual workload for data collection, arrangement and management, and improves data processing and analysis efficiency.

In some embodiments, there is provided generating a logical query plan for a query that includes a single fact table and multiple reducer tables; optimizing the logical query plan for query execution; and executing the optimized logical query plan.

The present disclosure relates to a data processing method, platform, computer readable storage medium and electronic device, and relates to the technical field of big data processing. The method comprises the following steps: based on a preset standardized data interface, extracting original data to a message engine; wherein the original data comprises terminal data generated by a terminal device and / or system data generated by an application system (S110); reading the original data from the message engine and storing the original data in a distributed file system to form a fact table (S120); storing the fact table in a columnar database and obtaining target column data required for generating a target chart from the columnar database (S130); and generating the target chart according to the target column data (S140). The present disclosure improves the accuracy of data processing results.

The application discloses a kind of legal advice automatic generation method based on search enhancement, including legal advice dataset construction step, legal clause search step, case fact splitting step, case fact coding step and legal advice automatic generation step.Legal advice dataset construction is to collect legal advice data and legal clause data and carry out cleaning, legal clause search step is to search out the legal clause relevant to case fact, case fact splitting step is to split case fact into fragments for model processing, case fact coding step is to code the split case fact one by one and obtain case fact representation, legal advice automatic generation step is to generate legal advice according to case fact representation.The present application can handle complex case facts under limited hardware resources, and through the combination with the searcher, the fluency and logic of the generated legal advice can be effectively improved, and the update of legal clauses can be flexibly responded.

The application relates to a management and query method for the same index of multi-fact tables based on an index center, which performs index definition on the same indexes of various source tables, and arranges the various source tables according to the data volume scale from small to large; according to the index query condition input by a user, the query dimension is acquired, and the source table matched with the query dimension is found and taken as a target source table; then, index query is carried out based on the target source table, and the corresponding index calculation result is returned. According to the screening dimension range of the index query condition, the available analysis dimensions on the various source tables are dynamically matched once, the current source table is selected to carry out data query when the matching succeeds, the best source table meeting the business requirement is found, and the index query efficiency is improved. The index platform does not need to create multiple indexes to respectively map different fact tables, one index is used for mapping, the query table is positioned according to the query condition and a preset table acceleration sequence, and the index management is simpler, and the index analysis is more intelligent.

The application discloses a kind of intelligent diagnosis and decision support method of coronary heart disease angina TCM syndrome factor based on HIS, it is related to medical information and TCM diagnosis and treatment technical field, the method will coronary heart disease angina TCM syndrome factor diagnostic criteria be deconstructed into standardization diagnostic item, build machine-readable weight rule base containing score, threshold and severity grading rule, response syndrome differentiation operation generates electronic collection form, receives structured data storage to the TCM syndrome factor fact table associated with patient main index and medical record, after structured data is submitted, trigger intelligent computing engine verification essential item, total score is accumulated, determine the establishment of syndrome factor and severity, through TCM diagnosis and treatment knowledge graph push personalized treatment or nursing suggestion in clinical business node, and continuously update rule base and knowledge graph through clinical data feedback.The application integrates corresponding function module to realize and deeply fuse with hospital information system, improves the standardization and efficiency of diagnosis and treatment, and has strong practicality.

The invention discloses a data warehouse layering and domain dividing design method, and belongs to the technical field of data warehouses, and the method comprises the steps: constructing a data warehouse, and carrying out the layering of the data warehouse; extracting traffic flow related data from a source end service system in a data operation layer, and establishing a data model in a zoning manner; in the data detail layer, standardizing and cleaning the data of the data operation layer, and establishing a data model based on the processed data; preprocessing the data of the detail layer in the data intermediate layer, establishing a fact table and performing light summarization; exchanging the data to a Dores database for processing; in the data summarization layer, summarization processing is provided for the theme library based on the data of the middle layer, and business indexes are developed according to different business dimensions; in the data mart layer, the fact table and the index data are subjected to domain processing according to business requirements and are docked to an application thematic library. According to the method, the problems of high data processing delay, long period and analysis singleness are effectively solved, and data redundancy and delay are remarkably reduced.

The invention discloses a data writing method and device, and the method comprises the steps: obtaining a query result of a multi-dimensional query request, the query result comprising first data of a first measurement field corresponding to the field values of N first dimension fields recorded in a fact table in a database; displaying a query result through N dimensions by using the field values of the N second dimension fields through the multi-dimensional virtual table; obtaining a writing operation of writing second data based on the multi-dimensional virtual table by a user, and converting the representation of the second data in the multi-dimensional virtual table into representation by using a two-dimensional virtual table; according to the relationship between the N second dimension fields and the N first dimension fields, a write-in request for the fact table is generated according to the write-in operation and the two-dimensional virtual table; and sending a write request to the database to write the second data at a position determined according to the N first dimension fields. Therefore, the multi-dimensional analysis system depending on the relational database can support the data to be written into the fact table of the database, and the query efficiency of the data can be improved.

A system for analyzing graph databases using intelligent reasoning systems including scalable collection of, and transformation of, graph data into facts suitable for use with programming logic languages doing deductive reasoning. A graph analyzer ingests disparate graph data from across the Internet and transforms the graph data into a fact table. In order to reduce latency and processing congestion, a stream processing engine and sharding strategy are employed to ensure scalability through parallelized processing of programming logic queries. Transformed graph data, now relational data, is utilized with programming logic languages that allow for hypothetical queries whereby an inference engine can deduce new information to satisfy such a query. Furthermore, the self-contained nature of inputs, outputs, and transformations of the system means strict data provenance can be observed and adhered to.

The application discloses a system and method for multi-dimensional data correlation analysis based on unified modeling, and relates to the technical field of intelligent analysis of big data; the system comprises the following steps: step 1, semantic model construction is performed; step 2, query compilation and optimization are performed; step 3, query execution and scheduling are performed; step 4, interactive analysis and visualization are performed; end-to-end full-process visual display is provided by using a multi-dimensional report designer MRD, and interactive drilling and narrative analysis are supported; and step 5, closed-loop optimization is performed; the complexity of a bottom-layer data structure is shielded by the semantic model, automatic correlation analysis across fact tables is supported, and thus a business personnel can independently complete deep data exploration and decision support without mastering professional techniques such as SQL.

The invention discloses a modeling method and device based on financial data, electronic equipment and a storage medium. The method comprises the steps of obtaining at least one document fact table in a data table; according to the at least one document fact table, constructing a document model corresponding to each document fact table; constructing a corresponding basic model according to the document model; and according to a model splicing rule, splicing the plurality of receipt models or the basic models to obtain a corresponding advanced model, and according to the basic model and / or the advanced model, querying the financial data in the data medium to obtain a target query result. By implementing the embodiment of the invention, the advanced model can be more conveniently obtained, and according to the constructed basic model and / or advanced model, the financial data of the data medium station can be directly queried without docking with a manager of the management data medium station, so that the efficiency of querying the financial data is improved. The method can be widely applied to the technical field of information.

The invention discloses an official car operation data analysis method based on a multi-source heterogeneous data fusion and treatment technology, and relates to the technical field of official car operation data analysis, and the method comprises the following steps: accessing business data and GPS track flow data, and obtaining decision guidance data; correcting the real-time GPS track flow data based on an official car track anomaly detection algorithm of RVM; associating the decision guidance data with the corrected real-time GPS track flow data to generate a travel fact table; and storing the travel fact table in an HDFS (Hadoop Distributed File System) in a Parquet format for offline analysis, and carrying out real-time query by virtue of Phoenix and HBase. Through multi-source heterogeneous data fusion and association, the problem of historical business data islands is solved.

Arrangements for partition handling for multi table scan semi join operations are provided. Partition information of a first logical relation may be determined. Partition information of a first physical operator may be determined based on the partition information of the first logical relation. The partition information of the first physical operator may be stored in a data structure which includes partition information of a fact table and of each reducer in a predefined sequence. Partition information of a second logical relation may be determined. The partition information of a second physical operator may be determined based on the partition information of the second logical relation and the partition information of the first physical operator. The partition information of the second physical operator may be stored in the data structure. Execution of the second physical operator may be performed using the stored partition information, skipping mappings between pairs of partitions.

The application discloses a kind of knowledge conflict-oriented evidence constraint decoding type retrieval enhancement generation method, belong to artificial intelligence, natural language processing and information retrieval technical field.The method includes: generating structured fact representation set based on the question to be answered and constructing self-consistent fact chain;Based on the question to be answered, self-consistent fact chain and candidate answer hypothesis, perform multi-signal retrieval, and rearrange, conflict detection, counterfactual alignment and evidence coverage analysis, obtain evidence support information and conflict perception control signal;Based on evidence support condition distribution and control condition distribution, perform control type constraint decoding;According to evidence conflict degree, candidate divergence, evidence coverage and reference closure degree, construct risk control quantity, and dynamically adjust decoding parameter, output structured answer and evidence-based uncertainty report.The method can improve the fact consistency, robustness and explainability of the generated results in knowledge conflict and high noise retrieval scenarios.

The embodiments of the present application belong to the fields of artificial intelligence and big data, and are applied to the field of data warehouse construction. It relates to a method for predicting HQL execution statements based on user characteristics and related devices, including storing source data into each data fact table and each data dimension table; obtaining foreign key fields and primary key fields of each data fact table, and obtaining the inter-table distance between each data fact table through preset algorithm rules, foreign key fields and primary key fields; constructing an inter-table association topology graph; assembling the optimal HQL execution statement; obtaining the optimal HQL execution statements of several first users for pre-training of the prediction model; receiving an optimal HQL execution statement assembly request sent by a second user, and obtaining the optimal HQL execution statement of the second user based on the pre-trained prediction model. This solution realizes lightweight coding and automated data processing, binds this automation with user characteristics, generates based on user-driven data processing models, and reduces the time consumption of repeated construction.

This invention discloses an auxiliary decision-making and precision diagnosis system based on interpretable multimodal reasoning, belonging to the field of medical informatics and clinical decision support technology. It includes: a data acquisition module for acquiring DKD clinical medical knowledge and multi-source patient data; a feature extraction module for processing the multi-source patient data to obtain a time-series data view of the patient; wherein the time-series data view includes: a fact table and a wide index table; multiple patient time-series data views constitute a structured feature warehouse; a knowledge graph construction module for constructing a medical knowledge graph based on DKD clinical medical knowledge; and a local reasoning module for constructing a local reasoning model and performing retrieval reasoning based on the structured feature warehouse and the medical knowledge graph to obtain the decision result.

Disclosed in the present application are a data warehouse creation method and apparatus based on a knowledge graph, and a computer device and a storage medium. Specifically, the data warehouse creation method based on a knowledge graph disclosed in the present application comprises: creating a data warehouse fact table layer, wherein the data warehouse fact table layer comprises a first node, and the first node corresponds to data in an external database; creating a data warehouse service layer, wherein the data warehouse service layer comprises a second node, and the second node corresponds to data obtained after nodes of the data warehouse fact table layer are aggregated; and creating a data application layer, wherein the data application layer comprises a third node, and the third node corresponds to data obtained after nodes of the data warehouse service layer are aggregated. By means of the method, the present application provides a new solution for creating a data warehouse on the basis of a knowledge graph, and allows the creation of subject-based aggregated wide tables without extracting original data into a local database, thereby enhancing both data sensitivity and the convenience of data warehouse creation operations.

The invention provides a multi-dimensional configuration-based large-screen data statistical method, which comprises the following steps of: configuring a database query statement, and determining configurations corresponding to an input database and an output database; performing data alignment on the source data service fact table by using a high-frequency value inheritance conflict resolution algorithm; different field accumulation strategies are configured for local organization statistical data with strategy marks, and an accumulation extraction strategy is configured; performing data sorting on the data bound by the extraction strategy and the local organization statistical data with the strategy mark; and generating a path animation sequence according to the secondary popup data set and the statistical optimization path scheme, and integrating the path animation sequence to a large display screen to obtain a final large screen display result. According to the method, heterogeneous fields of different databases are automatically standardized through a database-driven semantic alignment algorithm, the problem of multi-source data integration is solved, the accuracy of empty field filling is greatly improved by utilizing a high-frequency value inheritance conflict resolution technology, and statistical deviation is eliminated.