35 results about "Data exploration" patented technology

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 discloses a holographic flow monitoring method and system based on AI and BI, and relates to the technical field of network security monitoring. The method comprises the steps of flow collection and data processing, realization of multi-dimensional feature extraction, multi-model detection and dynamic decision by an AI engine, realization of trend, region and situation analysis by a BI engine, realization of anomaly detection based on a behavior baseline, and realization of AI detection result optimization and triggering of BI cross-dimension analysis by an adaptive weight algorithm. The holographic flow monitoring system is constructed through big data driving and fusion of an AI big model, millisecond-level real-time analysis of a security data flow is realized, immediate response of emergency events such as 0day attacks and the like is met, static rule limitation is broken through, the detection accuracy of unknown threats and APT attacks is improved, an AI analysis result and BI visualization capability are fused, and the system has a good application prospect. Multi-dimensional insight of the traffic situation is realized; low-latency interactive query is provided, and ad hoc data exploration of security analysts is supported.

Method, system, and computer-readable storage media for generating a data visualization. A plurality of algorithmic visualizations is received for a dataset. Based on the plurality of visualization matrices, a matrix is generated. Each visualization matrix of the plurality of visualization matrices corresponds with an algorithmic visualization of the plurality of algorithmic visualizations. A synthetic matrix is generated by randomly shuffling a plurality of values in each column of the matrix. A random forest classifier is trained to generate a random forest for distinguishing shuffled data of the synthetic matrix from unshuffled data of the matrix. Further, an ensemble visualization graph is generated using the random forest. From the ensemble visualization graph, an embedding vector corresponding to each sample of the dataset is extracted to generate an embedding matrix. Based upon the embedding matrix, the method includes generating the data visualization by harmonizing the plurality of algorithmic visualizations.

The invention discloses a multi-dimensional data exploration system and method based on large model enhanced embedding, the system comprises a front end and a rear end, the front end comprises a multi-dimensional data exploration interface, and the rear end comprises a large model, a pre-training model and an embedded network model; the large model converts multi-modal data into a text, an entity is extracted from the text and is subjected to semantic embedding through semantic matching, classification standards and label spaces are guided to be generated, and reasoning hierarchical labels are obtained; the pre-training model embeds text generation features; the embedded network model is used for performing embedded learning on the labeled data to generate a new embedded representation fusing embedded information and label information; and the multi-dimensional data exploration interface is used for organizing and classifying the multi-dimensional embedded data generated at the rear end, and displaying the multi-dimensional embedded data on a screen in a graph or image form to realize data analysis, query and interactive data exploration. According to the method, a multi-dimensional exploration mechanism is provided, and high-quality embedded expression and interpretable analysis capability are realized.

The invention provides a method and system for probing the data quality of original logs, and relates to the technical field of data probing, and the method comprises the steps: obtaining a plurality of original logs from a data source, and caching the original logs to a local server; the local server forms a probing process according to a plurality of probing rule nodes preset by probing personnel, and performs rule probing on each original log in sequence according to the probing process; and the local server performs processing according to rule probing results of all the original logs to obtain multiple data indexes, generates a probing analysis report and displays the probing analysis report. The method has the beneficial effects that an automatic probing process consisting of a plurality of probing rule nodes is constructed, so that low-efficiency and error-prone manual one-by-one verification is completely replaced, and the probing efficiency and accuracy are greatly improved; a plurality of data indexes and quality reports are generated based on a comprehensive rule exploration result, a set of objective and systematic data quality evaluation mechanism is established, logs with substandard quality are effectively prevented from entering a subsequent processing link, and high later repair cost is avoided.

A metadata synchronization system enables real-time interactive data exploration through a distributed metadata architecture. The system propagates metadata updates through an event-based synchronization path that maintains metadata consistency across system components. For discovered data sources, the system concurrently manages metadata in primary and secondary services instead of following traditional batch synchronization. A primary metadata service generates and manages metadata definitions while an event bus component propagates metadata update events to a secondary service maintaining a local metadata store. A query service provides immediate access to metadata for data exploration operations. In some implementations, the event bus components enables near-rime metadata availability. In some implementations, the secondary metadata service processes direct metadata updates and maintains metadata states prior to synchronization with the primary metadata service. The system reduces metadata access latency by eliminating batch synchronization overhead, enables immediate data exploration through coordinated metadata management, and maintains consistency through stateful task tracking.

The invention discloses a medical research data layered exploration method and device, electronic equipment and a medium. The method comprises the following steps: identifying a project demand document of a medical research project through a demand identification model, determining a data demand of the medical research project, and determining a standard library table matched with the data demand; generating a first-layer structured query statement and a second-layer structured query statement according to a data demand through a statement generation model; based on the standard library table, executing the first-layer structured query statement, and verifying the first query result through a result verification model; if the first query result passes the verification, executing a second-layer structured query statement on the first query result, and verifying a second query result through a result verification model; and taking the second query result passing the verification as a first probing result. The efficiency of medical research data exploration can be remarkably improved, and it is ensured that the first exploration result not only meets the overall requirements of a project, but also has high accuracy and integrity.

1.The name of the design product: electronic device with rail transit big data platform data management function graphical user interface. 2.The use of the design product: for an electronic device. 3.The design points of the design product: the graphical user interface in the screen. 4.The picture or photo that best shows the design points: front view. 5.The use of the graphical user interface: click the "filter" button in the upper right corner of the main view interface to enter the interface change state figure 1; after clicking the input box on the right side of the label in the interface change state figure 1, enter the interface change state figure 2; after inputting the relevant content and inputting the confirmation in the interface change state figure 2, enter the interface change state figure 3; click the label type in the interface change state figure 3 to enter the interface change state figure 4; click the data table name in the interface change state figure 4 to enter the interface change state figure 5; click the data exploration button in the interface change state figure 5 to enter the interface change state figure 6; click the blood relationship information button in the interface change state figure 6 to enter the interface change state figure 7; click the data space button in the interface change state figure 7 to enter the interface change state figure 8; click the data quality button in the interface change state figure 8 to enter the interface change state figure 9; click the access information button in the interface change state figure 9 to enter the interface change state figure 10; click the data service button in the interface change state figure 10 to enter the interface change state figure 11; click the index information button in the interface change state figure 11 to enter the interface change state figure 12; click the change record button in the interface change state figure 12 to enter the interface change state figure 13; click the data script button in the interface change state figure 13 to enter the interface change state figure 14.

A computerized method provides secure and controlled access provisions for data exploration in managed compute datasets. A workspace on a compute cluster is created for a user with permissions to the workspace. The compute cluster that includes a code analyzer is provisioned within a cloud computing infrastructure. The code analyzer is configured to: receive a data query from a task executing on the compute cluster; identify a query operation included in the data query; compare the query operation to a list of prohibited query operations for the workspace to which the user has the permissions; and terminate the data query without execution when the query operation is in the list of prohibited query operations for the workspace to which the user has the permissions.

The invention relates to the technical field of animal science data processing, and particularly discloses a feature derivation method and system for animal science original data. The method comprises the following steps: acquiring animal science original data, and constructing and storing a table structure in combination with data types, field meanings and user requirements; the method comprises the following steps: analyzing single-table column features and multi-table association relationships through data exploration, carrying out feature derivation based on an exploration conclusion, deeply mining data implicit association and internal laws, and converting the data implicit association and internal laws into quantifiable and explainable feature indexes. According to the scheme, the data quality is improved in a structured storage structured data form, the potential value of the data is released through a systematic feature derivation strategy, and the data information density and the analysis efficiency are enhanced. The technology breaks through the limitation of traditional data analysis, provides accurate and comprehensive data support for animal scientific research, assists in revealing essential rules and core mechanisms behind data, and lays a solid foundation for field theoretical innovation and practical application; the method is suitable for multiple directions in the animal science field and is wide in application range.

The present application relates to the technical field of geophysical electromagnetic data exploration, in particular to a three-dimensional time-frequency domain electromagnetic joint inversion method based on finite element algorithm. The method obtains time domain and frequency domain electromagnetic observation data of the region to be measured respectively; the region to be measured is profiled to obtain a non-structural tetrahedral mesh to construct a time-frequency domain inversion initial model; the time-frequency domain inversion initial model is forward calculated to obtain time domain and frequency domain electromagnetic response data; time domain electromagnetic data residuals and frequency domain electromagnetic data residuals are obtained, and their corresponding adaptive weights are obtained respectively to establish a joint inversion objective function; the joint inversion objective function is iteratively solved to calculate the update vector of the inversion initial model; the inversion initial model is iteratively updated until the set condition is reached, and the time-frequency domain electromagnetic joint inversion is completed. The present application effectively improves the accuracy of three-dimensional inversion through joint inversion, thereby enhancing the practical effect of three-dimensional inversion.

An adaptive hierarchical multidimensional data insight analysis method based on swarm intelligence, belonging to the field of artificial intelligence technology, utilizes recursive decomposition and synchronous data exploration mechanisms to construct a valid topic tree and automatically prune invalid branches. For leaf nodes, the swarm intelligence agent performs autonomous multi-round searches and multimodal heterogeneous data fusion, recording end-to-end evidence. The verification system verifies credibility through code replay and visual backtracking, quantifies the originality of node analysis using density clustering and truth constraint mechanisms, and scores based on relevance and depth. Finally, an interactive insight topology is constructed, supporting on-demand drill-down rendering from macro-level overview to micro-level evidence. This invention effectively solves the problems of ambiguous entry points and homogenized viewpoints in big data analysis. By lowering the threshold for data analysis through swarm intelligence, it leverages multi-angle analysis by the swarm to reveal non-explicit hidden correlations and high-value sparse insights, achieving full-process intelligentization from automatic planning to in-depth mining.

A computer-implemented method may comprise accessing data records comprising fields and identifying subsets of the data records based on the data records in each subset having an attribute in common with each other, with the subsets comprising a first subset and a second subset. The data records may be arranged in a page layout based on the identified subsets, with the data records being arranged into their subsets across a first dimension, and the fields being arranged across a second dimension. The page layout may be displayed, and a user interface element identifying the second subset may be displayed over the page layout. In response to receiving a user selection of the user interface element, the second subset may be moved from a first position to a second position, where the second position is within the viewport on the computing device.

The application discloses a data exploration method, device and storage medium. The data exploration method comprises the following steps: obtaining a data exploration entrance in a toolbar of an electronic form; the data exploration entrance is used for entering a data exploration mode; the data exploration mode comprises a brief mode and a detailed mode; if the data exploration mode is selected as the brief mode, generating exploration result overview information of each column of data according to a data type of the column of data and determining corresponding visualization tools, and displaying an exploration view corresponding to the exploration result overview information of each column of data in the electronic form through the visualization tools; and if the data exploration mode is selected as the detailed mode, generating exploration result detailed information of each column of data according to a data type of the column of data and determining corresponding visualization tools, and displaying an exploration view corresponding to the exploration result detailed information of each column of data in a new window through the visualization tools. The application can enrich data exploration means of the electronic form.

In various examples, an exploratory data analytics tool obtains a natural language query and generates a structured data query for execution on a sample of a dataset based on the natural language query. In an example, an intent is determined for the query and the intent is used, at least in part, to determine the most appropriate sample. In addition, the intent, in some examples, is used to generate recommended queries. A user interface of the exploratory data analytics tool, for example, can display the recommended queries and / or the results of the structured data query on the sample.

The application provides a graph layout optimization method and system based on force model parameter automatic search, acquires graph data, generates an initial graph layout result for the graph data, calculates the shortest path length between any pair of nodes in the graph, acquires the specified graph readability index of the user for the given graph data, generates a graph layout result satisfying the specified graph readability index according to the graph layout optimization method based on parameter automatic search, reuses the solved force model to new graph data to generate a layout result, and acquires the selection result of the user for the subgraph of interest in the layout result to perform local optimization on the subgraph corresponding to the selection result. The application can simultaneously satisfy the generation of corresponding visualization results according to the specified graph readability index and aesthetic criteria, so as to better show the structural characteristics of data, and simultaneously allows the user to perform interactive data exploration centered on analysis tasks according to requirements.

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 application discloses a modeling system for quickly developing a scoring card, a strategy tree and a fusion model, which comprises an item module for saving and opening an item, a data import module for importing data and processing data variables, a data exploration module for obtaining a plurality of variables required to be analyzed by a user to output frequency distribution of each variable, a scoring card module for analyzing variables, generating a scoring card and displaying a result, a strategy tree module for developing a strategy tree model and a strategy matrix, and a machine learning module for providing a machine learning model, wherein the machine learning model comprises developing a gradient boosting tree, a random forest and a neural network.

The invention discloses a high-performance data extraction method based on a wave field block chain, and relates to the related technical field of block chains, and the method comprises the following steps: after executing Schema initialization to establish a field mode and a column family database column table structure, executing the following operations in sequence: in an acquisition layer, executing access to a TRON archiving node gRPC and obtaining a block and a receipt; in the analysis layer, protocol-level strong type analysis and field normalization are executed; in a loading layer, executing column type write-in and high throughput library falling; in the increment layer, continuous synchronization and breakpoint resume are executed; in the verification layer, consistent health verification and missing block scanning are executed; in the exploration layer, data exploration oriented to research and risk control is executed; therefore, the operation of extracting high-performance data by using the wave field block chain is completed. According to the invention, an exploration interface for research and risk control is provided, and high-frequency problems such as resource renting, stable asset flow direction and contract abnormity can be quickly answered.

The invention discloses a data management method and device based on a large model and a medium, and relates to the technical field of electric digital data processing. The method comprises the steps of performing data exploration on sample data based on a preset large model to obtain sample metadata corresponding to the sample data, and storing the sample metadata in a preset data knowledge base; for a to-be-governed target table, performing correlation comparison on the target table and the data knowledge base so as to determine a target table field required for governing the target table and a governing operation function used for establishing a mapping relation between the target table field and a source table field corresponding to the target table field according to a comparison result; according to the influence effect of the governance operation function on the source table field, predicting the expected field credibility of the source table field, and based on the governance operation function and the expected field credibility, generating a governance task corresponding to the target table; and issuing the governance task to the processing node so as to realize data governance of the target table through the processing node.

This invention relates to the field of data processing and information transmission, and discloses a method, system, and medium for incremental mining and dynamic updating of media resources, comprising the following steps: The invention acquires incremental activity logs from a financial business system; it invokes a data exploration agent to perform rule matching, mines target business tags that meet thresholds, and determines popularity weights; based on these tags, it triggers a media generation agent to call a large model interface to generate candidate media resources; it performs compliance review and transfer of the resources through a collaborative routing module, and obtains confirmation logs; it writes the resources into a media library and dynamically updates the front-end panel according to the popularity weights. This invention drives large model generation through underlying data aggregation and quantification of weights, and combines pixel-level anti-counterfeiting watermarking and asynchronous network routing mechanisms to construct a system-level compliance closed loop, effectively solving the technical problems of traditional methods such as high reliance on manual labor, delayed updates, and low security in transfer.

A server repair part spare quantity prediction system and method based on a multi-time series model, by performing data exploration and matching historical experience data, a feature differentiation rule is established for the original features of the historical time series data, so as to segment the original features into multiple differentiated features, then verify the effectiveness of the differentiated features, and evaluate the change of the differentiated features in response to the target variable until the preset result is met, then segment the target variable to the same number as the differentiated features and correspond to each other, and input to the multi-time series model as training data for training, when predicting the spare quantity, the current time series data is received to input to the trained multi-time series model to obtain an accurate spare quantity prediction result, thereby achieving the technical effect of improving the evaluation accuracy of the spare quantity of the server.

The embodiment of the application discloses a kind of distributed sensitive data two-dimension exploration method, equipment and medium, belong to big data security technical field, solve the problem that existing distributed data exploration method is when facing mass data, scanning is extremely long in time, it is difficult to meet the timeliness of business. Including, receiving the exploration task configured by user;Analysis of the partition information of exploration target data set in distributed storage architecture, and based on partition information, scan task is distributed to the multiple computing nodes of distributed query processing system;Content scanning strategy is converted into query predicate, and is pushed to the storage layer of distributed storage architecture to execute data filtering;Parallelly execute data content matching based on content scanning strategy and field name matching based on field name scanning strategy;The matching results of multiple computing nodes are aggregated, to generate exploration result, match it with preset multistage security classification rule library, determine the security classification path corresponding to each exploration result, generate exploration report.

The application discloses a composite type data display method based on a Vue framework and a waterfall algorithm, and mainly solves the problem of single data type display and high difficulty in use of the prior art.The implementation scheme is as follows: 1) data is imported, and data elements and configuration objects are obtained;2) according to the data elements, five unit models of picture format data unit, audio format data unit, video format data unit, text format data unit and time sequence diagram format data are respectively constructed according to the requirements of the configuration file;3) based on the waterfall algorithm, the waterfall display model is established by using the various data unit models;4) the endless scroll algorithm is used to further optimize the waterfall display model, the burden of page loading and request is reduced, and the data elements are displayed.The application can visually display different types of data, has excellent display performance on the page space, and can be used for controlling and data exploration of potential internal relations of batch data by users.

A computer system receives, via a user interface, a first sketch input corresponding to a first measure data field of a dataset. The computer system converts the first sketch input into a first set of line segments and determines respective values for a first set of parameters corresponding to the first set of line segments. The computer system executes a first query against a database of linearized data using the first set of parameters to identify one or more sets of linearized data. Each set of linearized data corresponds to a respective dimensional dataset for the first measure data field. The computer system retrieves, from the database, one or more first dimensional datasets corresponding to the one or more sets of linearized data, generates one or more first data visualizations from the one or more retrieved first dimensional datasets, and displays the first data visualizations via the user interface.

The application discloses a data quality control compliance system fusing AI technology, relates to the technical field of data processing, and solves the technical problems that efficient cataloging and sharing of data are difficult to realize, comprehensive understanding and adaptability to data regulations are lacked, changing compliance requirements are difficult to meet, and potential value of data assets is limited; through a full-chain AI driving engine: a full-link AI engine of "data exploration-data directory identification-data intelligent cataloging-data quality detection-data quality inspection report generation-directory scene construction" is innovatively constructed, the limitation of traditional single rule or AI technology is broken through, automation of a closed loop from semantic analysis to cataloging generation and quality detection is realized, and adaptability of the system to a complex data environment is enhanced. The AI+cataloging module adopts a triple matching strategy, and cataloging accuracy and efficiency are greatly improved. Through automatic quality detection and report generation, quality problems in data can be quickly identified.

The application discloses a kind of real-time data question and answer training and chart generation system, including data access and preprocessing module, field self-adaptive training module, real-time question and answer interaction module, intelligent chart generation module and knowledge graph and feedback optimization module;The data access and preprocessing module is used for the access of multi-source heterogeneous real-time data, cleaning, standardization processing and dynamic caching, and outputs structured data and real-time data stream index;The field self-adaptive training module is based on prompt auxiliary self-learning mechanism, and a small amount of labeled field data and a large amount of unlabeled data are used for model fine-tuning, to generate field-specific question and answer model, while constructing field terminology dictionary and updating in real time.The application realizes the integration function of field self-adaptive model training, real-time accurate question and answer, intelligent chart generation and continuous iteration optimization, improves user data query efficiency and data exploration ability.

The invention discloses a data query recommendation method and device for a digital cockpit, equipment and a storage medium, and the method comprises the steps: obtaining historical query data, and constructing a query tree according to the historical query data; simulating user interaction through Monte Carlo tree search, generating reinforcement learning training data, and training a reinforcement learning algorithm by using the reinforcement learning training data; performing query recommendation optimization on the query tree by using the trained reinforcement learning algorithm to construct a query recommendation agent model; and receiving an input query condition by utilizing the query recommendation agent model, and generating a corresponding query recommendation result. The query recommendation agent model is trained by simulating user behaviors and representing the search space, so that the exploration process of a user in a complex data environment is enhanced, and by introducing the reinforcement learning technology, the query process and the analysis efficiency are optimized, the data query recommendation efficiency and precision of the digital cockpit are improved, and the user experience is improved. And the user experience and the data exploration capability are greatly improved.

To provide a treatment recommendation to a physician for treating a patient.SOLUTION: A method comprises determining, from a processor in communication with a patient data repository, a first treatment recommendation based on a combination of selected patient backgrounds from the patient data repository applicable to the patient, and operational parameters of a plurality of ventricular assist devices (VADs) suitable for treating the patient, the first treatment recommendation having a first survival rate and comprising the use of a first VAD. The method comprises then obtaining a first signal from the use of the first VAD on the patient. The method comprises then determining a second treatment recommendation based on the first signal and the first treatment recommendation, the second treatment recommendation having a second survival rate. The method comprises then providing the second treatment recommendation to the physician if the second survival rate is higher than the first survival rate.SELECTED DRAWING: Figure 1

The application belongs to the technical field of geological surveying and mapping equipment, and particularly relates to a main ridge line automatic extraction device and method suitable for mountain wind farm development, which comprises a unmanned aerial vehicle and a collector installed on the unmanned aerial vehicle; further comprises a multistage cleaning mechanism, which is used for cleaning the optical end of the collector to maintain the data collection effect of the collector; the impact assembly is arranged, when the unmanned aerial vehicle carries the collector to carry out field data exploration, the double protection is formed on the collector by using the jet flow mode of the spray head, so that the efficiency of the internal dust separating from the collector is improved, the probability of the external dust adhering to the collector is reduced, and the protection effect of the optical end of the collector is realized by cooperating with the roller brush assembly, so that the accuracy of data collection is improved.