Method, device, electronic device and storage medium for generating chart information report

Abstract

The present invention relates to artificial intelligence technology and provides a method for generating a chart information report. First, a chart data model is formed; then, the chart data model is parsed to obtain key chart data, and the key chart data is processed into a chart data card through a model analysis system. Then, the chart data card is input into a preset chart parsing model with a unique identifier, and then the chart data card is parsed by the chart parsing model to generate a chart parsing text, and classification information corresponding to the unique identifier is annotated on the chart parsing text according to the category to which the unique identifier belongs to form a chart information report. Each data card has a unique identifier, so that in the process of processing the data card, the security and stability of the overall process are improved, and the layout is automatically performed to form a chart information report, so that a standardized chart information report can be formed without manual interpretation, thereby improving reporting efficiency, saving manpower, and reducing overall project time.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence, and in particular to a method, device, electronic device and computer-readable storage medium for generating a chart information report. Background Art

[0002] Data dashboards or visual data reports are mainly produced through mainstream business analysis tools currently available on the market, but they can only generate data cards, such as bar charts, line charts, pie charts and other charts, and then manually layout the data cards to generate rich data dashboards.

[0003] Usually, only the person who makes the data dashboard or report can clearly understand the actual meaning of each dashboard, but the data dashboard is often read by readers other than the producer. When viewing the data report filled with the data dashboard, the reader often cannot directly interpret the information in the chart. Therefore, the person who makes the dashboard needs to manually summarize the data dashboard for the reader, that is, write text around the data dashboard to form a data report with both text and pictures, which brings extra workload to the report producer. The report producer needs to read the chart information and think about the wording to form a data report with both text and pictures. Not only is the report inefficient, but it also wastes manpower and delays the overall time of the project.

[0004] Therefore, there is an urgent need for a method for generating chart information reports that can integrate chart production and chart analysis, reduce manpower waste, improve report production efficiency, and reduce the time spent on the overall project. Summary of the Invention

[0005] The present invention provides a method for generating a chart information report to solve the problem that readers are often unable to directly interpret the information in the chart when viewing a data report filled with a data dashboard. Therefore, the person who makes the dashboard needs to manually summarize the data dashboard for the readers, that is, write text around the data dashboard to form a data report with both text and pictures, which brings extra workload to the report maker. The report maker needs to read the chart information and think about the wording to form a data report with both text and pictures. Not only is the report efficiency low, but it also wastes manpower and delays the overall time consumption of the project.

[0006] To achieve the above-mentioned purpose, the present invention provides a method for generating a chart information report, comprising:

[0007] Establishing a dimension analysis table according to preset chart dimensions, and associating the dimension analysis table with a preset chart database to form a chart data model;

[0008] Parsing the chart data model to obtain chart key data, and processing the chart key data into chart data cards through a model analysis system;

[0009] Marking a unique identifier on the chart data card using a preset identifier control, so that the chart data card carries the unique identifier and is input into a preset chart parsing model; wherein the chart parsing model is trained using random chart data and statistical data formed by a statistical chart component;

[0010] The chart data card is parsed by the chart parsing model to generate a chart parsing text, and classification information corresponding to the unique identifier is annotated on the chart parsing text according to the category to which the unique identifier belongs to form a chart information report.

[0011] Optionally, establishing a dimension analysis table according to preset chart dimensions includes:

[0012] Use the name of each preset chart dimension as the first column;

[0013] Classifying the characteristics of each preset chart dimension into a second column, wherein the category information in the second column corresponds to the name of the preset chart dimension in the first column;

[0014] Information is sorted in the second-type vertical columns to form second-type sub-columns, and information is filled in the second-type sub-columns to form a dimensional analysis table.

[0015] Optionally, associating the dimension analysis table with a preset chart database to form a chart data model includes:

[0016] calling a chart database and associating the chart database with the dimensional analysis table;

[0017] extracting target data corresponding to the dimension analysis table from the chart database;

[0018] Modeling is performed according to the first type of vertical columns and the second type of sub-columns to form a model framework, and the target data is filled into the model framework to form a chart data model; wherein, after the target data is filled into the model framework to form the chart data model, the target data is updated at a preset time interval to update the chart data model.

[0019] Optionally, parsing the chart data model to obtain chart key data, and processing the chart key data into chart data cards through a model analysis system includes:

[0020] Parsing the chart data model to obtain chart key data, wherein the chart key data includes chart meaning and numerical data corresponding to the chart meaning;

[0021] The target chart is formed by using a model analysis system to use the chart meaning as a display item of the chart and the digital data as a size of the display item;

[0022] The display items are traversed through a preset reading program to obtain specific meanings of the display items, and the specific meanings are annotated in the target chart to form a chart data card.

[0023] Optionally, the process of training the graph parsing model includes:

[0024] Generate statistical charts through pre-acquired random data and Echart components;

[0025] Annotating the statistical graph using a preset automatic annotation plug-in to form test data, wherein the test data includes a test set and a training set;

[0026] Inputting the training set into a convolutional neural network to form a graph parsing script, and testing the graph parsing script using the test set to form a feedback function;

[0027] Parameters of the chart parsing script are adjusted according to the value of the feedback function. When the value of the feedback function is within a preset threshold range, the chart parsing script is used as a chart parsing model.

[0028] Optionally, performing in-depth parsing on the chart data card by using the chart parsing model to generate chart parsing text includes:

[0029] determining whether the obtained chart data card matches the unique identifier;

[0030] If the unique identifier matches the chart data card, the chart data card is verified using the chart parsing model, and the verified chart data card is deeply parsed to form parsed data;

[0031] The parsed data is expressed in words using the chart parsing model to generate chart parsing text.

[0032] Optionally, the step of annotating classification information corresponding to the unique identifier on the chart parsing text to form a chart information report includes:

[0033] Classify the preset unique identifiers into categories to form classification information, and configure numbering rules based on the classification information;

[0034] Acquire the classification information of the unique identifier corresponding to the chart data card, and number the chart parsing text based on the classification information and the numbering rule to form a classification number;

[0035] Marking the corresponding number on the chart analysis text to form a target report;

[0036] Inputting the chart data card and the target report into a BI tool, so that a dashboard editor of the BI tool typeset the target report, and printing the typeset chart information report into a PDF version to generate a chart information report;

[0037] Send the chart information report to a preset designated mailbox.

[0038] In order to solve the above problems, the present invention further provides a device for generating a chart information report, the device comprising:

[0039] a data model generating unit, configured to establish a dimension analysis table according to preset chart dimensions, and associate the dimension analysis table with a preset chart database to form a chart data model;

[0040] a key data processing unit, configured to parse the chart data model to obtain chart key data, and process the chart key data into chart data cards through a model analysis system;

[0041] a data card input unit, configured to mark a unique identifier on the chart data card using a preset identifier control, so that the chart data card carrying the unique identifier is input into a preset chart parsing model; wherein the chart parsing model is trained using statistical data formed by random chart data and statistical chart components;

[0042] An information report generating unit is used to parse the chart data card through the chart parsing model to generate a chart parsing text, and to annotate the classification information corresponding to the unique identifier on the chart parsing text according to the category to which the unique identifier belongs to form a chart information report.

[0043] In order to solve the above problem, the present invention further provides an electronic device, comprising:

[0044] a memory storing at least one instruction; and

[0045] The processor executes the instructions stored in the memory to implement the steps in the above-mentioned method for generating a chart information report.

[0046] In order to solve the above problem, the present invention also provides a computer-readable storage medium, in which at least one instruction is stored. The at least one instruction is executed by a processor in an electronic device to implement the above-mentioned method for generating a chart information report.

[0047] The embodiment of the present invention first establishes a dimension analysis table according to a preset chart dimension, and associates the dimension analysis table with a preset chart database to form a chart data model; then, the chart data model is parsed to obtain chart key data, and the chart key data is processed into a chart data card through a model analysis system, and then a unique identifier is marked on the chart data card through a preset identifier control, so that the chart data card carries the unique identifier and is input into the preset chart parsing model; wherein, the chart parsing model is trained by statistical data formed by random chart data and statistical chart components, and then the chart data card is parsed by the chart parsing model to generate a chart parsing text, and classification information corresponding to the unique identifier is annotated on the chart parsing text according to the category to which the unique identifier belongs to form a chart information report, each data card has a unique identifier, thereby improving the security and stability of the overall process in the process of processing the data card, and automatically performing layout to form a chart information report, so that a standardized chart information report can be formed without manual interpretation, thereby improving reporting efficiency, saving manpower, and reducing the overall project time. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A flowchart of a method for generating a chart information report according to an embodiment of the present invention is provided;

[0049] Figure 2 A schematic diagram of modules of a device for generating a chart information report according to an embodiment of the present invention;

[0050] Figure 3 A schematic diagram of the internal structure of an electronic device for a method for generating a chart information report according to an embodiment of the present invention;

[0051] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0052] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0053] Usually, only the person who makes the data dashboard or report can clearly understand the actual meaning of each dashboard, but the data dashboard is often read by readers other than the producer. When viewing the data report filled with the data dashboard, the reader often cannot directly interpret the information in the chart. Therefore, the person who makes the dashboard needs to manually summarize the data dashboard for the reader, that is, write text around the data dashboard to form a data report with both text and pictures, which brings extra workload to the report producer. The report producer needs to read the chart information and think about the wording to form a data report with both text and pictures. Not only is the report inefficient, but it also wastes manpower and delays the overall time of the project.

[0054] To solve the above problems, an embodiment of the present invention provides a method for generating a chart information report.

[0055] It should be noted that embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) refers to the theories, methods, technologies, and application systems that use digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to achieve optimal results.

[0056] like Figure 1 As shown, in this embodiment, the method for generating a chart information report includes:

[0057] S1: creating a dimension analysis table according to the preset chart dimension, and associating the dimension analysis table with the preset chart database to form a chart data model;

[0058] S2: Analyze the chart data model to obtain chart key data, and process the chart key data into chart data cards through the model analysis system;

[0059] S3: Marking a unique identifier on a chart data card using a preset identifier control, so that the chart data card carries the unique identifier and is input into a preset chart parsing model; wherein the chart parsing model is trained using statistical data formed by random chart data and statistical chart components;

[0060] S4: parsing the chart data card through the chart parsing model to generate a chart parsing text, and annotating the classification information corresponding to the unique identifier on the chart parsing text according to the category to which the unique identifier belongs to form a chart information report.

[0061] exist Figure 1 In the embodiment shown, step S1 is a process of establishing a dimension analysis table according to a preset chart dimension and associating the dimension analysis table with a preset chart database to form a chart data model; wherein,

[0062] The process of creating a dimensional analysis table based on preset chart dimensions includes:

[0063] S111: The name of each preset chart dimension is used as the first type of vertical column;

[0064] S112: Classifying the characteristics of each preset chart dimension into a second column, and the category information in the second column corresponds to the name of the preset chart dimension in the first column;

[0065] S113: sorting information in the second vertical column to form a second sub-column, and filling information in the second sub-column to form a dimensional analysis table;

[0066] The process of associating the dimensional analysis table with the preset chart database to form a chart data model includes:

[0067] S121: calling a chart database and associating the chart database with the dimension analysis table;

[0068] S122: extracting target data corresponding to the dimension analysis table from the chart database;

[0069] S123: Modeling is performed according to the first type of vertical columns and the second type of sub-columns to form a model framework, and the target data is filled into the model framework to form a chart data model; wherein, after the target data is filled into the model framework to form the chart data model, the target data is updated at a preset time interval to update the chart data model;

[0070] Specifically, step S11 is a process of establishing a dimension analysis table. The dimension analysis table is preset according to business needs. In this embodiment, taking job talent management as an example, in this embodiment, the names of the chart dimensions (first-category columns) include the number of employees, the number of recruits, the recruitment-to-application ratio, the employment rate, the number of resignations, the number of people to be resigned, the number of resignations, the number of new hires, etc. The second-category columns include various second-category sub-columns corresponding to the names of the chart dimensions, such as company, department, position, position level, length of service, gender and age, etc.

[0071] Step S12 is the process of connecting the dimensional analysis table to the chart database to form a chart data model. In this process, the association relationship between the chart database and the dimensional analysis table is first created, and then the data corresponding to the first type of vertical column and the second type of sub-column in the dimensional analysis table are called in the chart database according to the dimensional analysis table to construct a chart data model, and the frequency of data update is set, that is, the time interval is set, such as updating once a week.

[0072] exist Figure 1 In the embodiment shown, step S2 is a process of parsing the chart data model to obtain chart key data, and processing the chart key data into chart data cards through the model analysis system; which includes:

[0073] S21: parsing the chart data model to obtain chart key data, wherein the chart key data includes chart meaning and numerical data corresponding to the chart meaning; the process of parsing the chart data is to traverse the chart data and then extract keyword information from the chart to form the chart key data. For example, taking a line chart as an example, the line chart is first traversed and then information is extracted from the line chart to obtain information such as the data size of each category in the line chart to form the chart key data;

[0074] S22: using the model analysis system to use the meaning of the chart as a display item of the chart and the digital data as the size of the display item to form a target chart;

[0075] S23: traversing the display items through a preset reading program to obtain specific meanings of the display items, and annotating the specific meanings in the target chart to form a chart data card.

[0076] Specifically, step S21 is a process of parsing the chart data model to obtain chart key data, and step S22 is a process of using the chart meaning as the display item of the chart and using numerical data as the size of the display item to form a target chart, wherein the chart key data includes the chart meaning and the numerical data corresponding to the chart meaning. In this embodiment, still taking the above-mentioned personnel management as an example, the target chart can be any chart such as a bar chart, a line chart, a pie chart, etc. In this embodiment, taking the chart data card based on the line chart as an example, the chart meaning is the first type of vertical column. At the same time, the chart meaning is implemented in the line chart as the display item, that is, the item that needs to display a numerical value. For example, the display item can be the number of employees in the above example. In the line chart, the vertical axis represents the number of employees, and the horizontal axis represents the companies in the second type of sub-column. The meaning of the line chart represents the number of employees of each company, and the specific number of people is the numerical data.

[0077] The model analysis system may be any model that can automatically generate charts. In this embodiment, the model analysis system is a BI system.

[0078] Step S23 is the process of annotating the specific meaning of the display items in the target chart. Usually, the display items are expressed in numbers or English in the line chart itself, such as writing 1, 2, 3, etc. on the horizontal axis of the line chart, and then the specific meaning is noted next to the line chart to form a complete chart data card.

[0079] exist Figure 1In the illustrated embodiment, step S3 is a process of marking a unique identifier on a chart data card using a preset identifier control, so that the chart data card carries the unique identifier and is input into a preset chart parsing model; wherein the chart parsing model is trained using statistical data formed by random chart data and statistical chart components; wherein the identifier control is a pre-set program that can mark a unique identifier on the collected chart data card;

[0080] The process of marking unique identifiers on chart data cards includes:

[0081] S301: Compare the display item with a preset category set to obtain the category to which the display item belongs, obtain a unique identifier corresponding to the category, and overlay the unique identifier on the chart data card;

[0082] The process of training a graph parsing model includes:

[0083] S311: Generate a statistical chart using pre-acquired random data and the Echart component;

[0084] S312: Annotating the statistical graph using a preset automatic annotation plug-in to form test data, wherein the test data includes a test set and a training set; the annotation is a natural language capable of describing the statistical graph in detail;

[0085] S313: Inputting the training set into a convolutional neural network to form a chart parsing script, and testing the chart parsing script using the test set to form a feedback function;

[0086] S314: adjusting parameters of the chart parsing script according to the value of the feedback function, and using the chart parsing script as a chart parsing model when the value of the feedback function is within a preset threshold range;

[0087] Step S301 is a process of comparing a display item with a preset category set to obtain the category to which the display item belongs, obtaining a unique identifier corresponding to the category, and overlaying the unique identifier on the chart data card. The unique identifier can be a unique number or a unique character, without limitation. In this embodiment, the unique identifier is a sequence consisting of letters and numbers to improve security.

[0088] Specifically, in this embodiment, step S31 is a process of training a chart parsing model. In this process, random data is first obtained. The specific random data is not limited here, and the random data can be any random data combination. Then, a statistical graph is formed based on the random data and the Echart component. In this embodiment, the Echart component is an Echart line graph component, that is, in this embodiment, the chart parsing model is trained in the form of a line graph. The chart parsing model can also be trained in the form of a pie chart, a bar chart, etc., which is not limited here. Then, the statistical graph is annotated to form test data. In this embodiment, the test data includes at least 2,000 line graphs, and the line graphs are annotated to different types of graphic trends, such as an upward trend, a downward trend, a decelerating rise, an accelerating rise, a U-shaped trend, etc., through a labeling program to form test data. The test data includes a training set for training and a test set for testing. In this embodiment, 20% of the test data is a test set, that is, 400 test data are used as a test set, and 80% is used as a training set, that is, 1,600 test data are used as a training set.

[0089] The training set is then input into the convolutional neural network to form a chart parsing script, and the chart parsing script is tested through the test set to form a feedback function. The feedback function can reflect the accuracy of the chart parsing script, and then the parameters are repeatedly adjusted according to the feedback function to form a high-precision chart parsing model. In this embodiment, the chart parsing model can automatically generate chart parsing text based on the chart data card.

[0090] exist Figure 1 In the embodiment shown, step S4 is a process of deeply parsing the chart data card through the chart parsing model to generate a chart parsing text, and annotating the classification information corresponding to the unique identifier on the chart parsing text to form a chart information report, wherein:

[0091] The process of deeply parsing the chart data card using a chart parsing model to generate chart parsing text includes:

[0092] S411: Determine whether the obtained chart data card matches the unique identifier;

[0093] S412: If the unique identifier matches the chart data card, the chart data card is verified using the chart parsing model, and the verified chart data card is deeply parsed to generate parsed data;

[0094] S413: Textually represent the parsed data using a chart parsing model to generate chart parsing text;

[0095] The process of annotating the classification information corresponding to the unique identifier on the chart interpretation text to form a chart information report includes:

[0096] S421: Classify the preset unique identifier into categories to form classification information, and configure a numbering rule based on the classification information;

[0097] S422: Acquire the classification information of the unique identifier corresponding to the chart data card, and number the chart parsing text based on the classification information and the numbering rule to form a classification number;

[0098] S423: Mark the corresponding number on the chart analysis text to form a target report;

[0099] S424: Inputting the chart data card and the target report into the BI tool, so that the dashboard editor of the BI tool typeset the target report, and printing the typeset chart information report into a PDF version to generate the chart information report;

[0100] S425: Send the chart information report to a preset designated mailbox.

[0101] Specifically, step S421 is a process of presetting classification information and a numbering rule in advance, wherein the classification information corresponds to the aforementioned preset unique identifier, for example, the unique identifier corresponds to the category to which the display item belongs, each category corresponds to a classification information, and each classification information corresponds to a letter or symbol, so that the numbering rule is formulated based on the letter or symbol. For example, the first category of classification information corresponds to A, and the second category corresponds to B. In this embodiment, the numbering rule is to use the corresponding letter of the classification information as the first placeholder, and the order of the chart analysis text in the category as the second placeholder. No other restrictions are imposed.

[0102] Steps S422 and S423 are the process of obtaining the corresponding number of the chart parsing text according to the unique identifier corresponding to the chart parsing text, and then marking the corresponding number on the chart parsing text to form a target report;

[0103] It should be noted that the entire process is updated regularly according to the preset time so that a new standard target report (standard chart information report) is automatically sent within the specified time. That is, after the target data is filled in the model framework to form a chart data model, the target data is updated according to the preset time interval, thereby updating the entire process and forming a new standard target report.

[0104] In this embodiment, the server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0105] The chart information report generation method in this embodiment has the following advantages: 1. The target data in the data model is updated regularly to update the data model regularly, so that the corresponding chart information report is produced regularly; 2. Each data card has a unique identifier, thereby improving the security and stability of the overall process in the process of processing the data card; the parameters of the model can be adjusted in time according to the feedback function, thereby improving the accuracy of the chart analysis model; the layout is automatically performed to form a chart information report, thereby improving the formation of standardized chart information reports without manual interpretation, thereby improving reporting efficiency, saving manpower, and reducing the overall project time.

[0106] As described above, the method for generating a chart information report provided by the present invention first establishes a dimension analysis table according to the preset chart dimension, and associates the dimension analysis table with a preset chart database to form a chart data model; then the chart data model is parsed to obtain chart key data, and the chart key data is processed into a chart data card through a model analysis system, and then a unique identifier is marked on the chart data card, so that the chart data card carries the unique identifier and is input into the preset chart parsing model; wherein, the chart parsing model is trained by statistical data formed by random chart data and statistical chart components, and then the chart data card is deeply parsed by the chart parsing model to generate a chart parsing text, and classification information corresponding to the unique identifier is annotated on the chart parsing text according to the category to which the unique identifier belongs to form a chart information report, each data card has a unique identifier, thereby improving the security and stability of the overall process in the process of processing the data card, and automatically performing layout to form a chart information report, so that a standardized chart information report can be formed without manual interpretation, thereby improving reporting efficiency, saving manpower, and reducing the overall project time.

[0107] like Figure 2 As shown, the present invention provides a device 100 for generating chart information reports, which can be installed in an electronic device. Depending on the functionality implemented, the device 100 may include a data model generation unit 101, a key data processing unit 102, a data card input unit 103, and an information report generation unit 104. The modules described herein, also referred to as units, are a series of computer program segments that can be executed by an electronic device processor and perform a fixed function, and are stored in the electronic device's memory.

[0108] In this embodiment, the functions of each module / unit are as follows:

[0109] The data model generating unit 101 is configured to establish a dimension analysis table according to a preset chart dimension, and associate the dimension analysis table with a preset chart database to form a chart data model;

[0110] A key data processing unit 102 is configured to parse the chart data model to obtain chart key data, and process the chart key data into chart data cards through a model analysis system;

[0111] The data card input unit 103 is configured to mark a unique identifier on the chart data card using a preset identifier control, so that the chart data card carries the unique identifier and is input into a preset chart parsing model; wherein the chart parsing model is trained using statistical data formed by random chart data and statistical chart components;

[0112] The information report generating unit 104 is configured to parse the chart data card through the chart parsing model to generate a chart parsing text, and to annotate the classification information corresponding to the unique identifier on the chart parsing text according to the category to which the unique identifier belongs to form a chart information report.

[0113] In this embodiment, the data model generating unit 101 includes:

[0114] An analysis table creation module is configured to use the name of each preset chart dimension as a first column; use the characteristic classification of each preset chart dimension as a second column, with the category information in the second column corresponding to the name of the preset chart dimension in the first column; organize the information in the second column to form a second sub-column, and fill the second sub-column with information to form a dimensional analysis table;

[0115] a chart data model building module, configured to call a chart database and associate the chart database with the dimensional analysis table; extract target data corresponding to the dimensional analysis table from the chart database; perform modeling according to the first type of vertical columns and the second type of sub-columns to form a model framework, and fill the target data into the model framework to form a chart data model; wherein, after the target data is filled into the model framework to form the chart data model, the target data is updated at a preset time interval to update the chart data model;

[0116] The key data processing unit 102 includes:

[0117] a key data module, configured to parse the chart data model to obtain chart key data, wherein the chart key data includes chart meaning and numerical data corresponding to the chart meaning;

[0118] a target chart module, configured to use the chart meaning as a display item of the chart and the digital data as a size of the display item to form a target chart through a model analysis system;

[0119] A data card module, used for annotating the specific meaning of the display item in the target chart to form a chart data card;

[0120] The data card input unit 103 includes:

[0121] an identification module, configured to compare a display item with a preset category set to obtain the category to which the display item belongs, obtain a unique identifier corresponding to the category, and overlay the unique identifier on the chart data card;

[0122] Model training module, used to obtain random data;

[0123] Generate statistical charts through random data and Echart components;

[0124] Annotating the statistical graph to form test data, wherein the test data includes a test set and a training set; the annotation is a natural language capable of describing the statistical graph in detail;

[0125] Inputting the training set into a convolutional neural network to form a graph parsing script, and testing the graph parsing script using the test set to form a feedback function;

[0126] Adjusting parameters of the chart parsing script according to the value of the feedback function, and using the chart parsing script as a chart parsing model when the value of the feedback function is within a preset threshold range;

[0127] The information report generating unit 104 includes:

[0128] a chart parsing module, configured to determine whether the obtained chart data card matches the unique identifier; if the unique identifier matches the chart data card, verifying the chart data card using a chart parsing model, and performing in-depth parsing on the verified chart data card to form parsed data; and expressing the parsed data in text using the chart parsing model to generate chart parsing text;

[0129] An information reporting module is used to classify preset unique identifiers into categories to form classified information, and configure numbering rules based on the classified information;

[0130] Obtaining the classification information of the unique identifier corresponding to the chart data card, and numbering the chart parsing text based on the classification information and the numbering rule to form a classification number;

[0131] Mark the corresponding numbers on the chart interpretation text to form a target report;

[0132] Inputting the chart data card and the target report into the BI tool, so that the dashboard editor of the BI tool formats and lays out the target report, and printing the formatted chart information report into a PDF version to generate the chart information report;

[0133] Send chart information reports to the preset designated email address.

[0134] As described above, the chart information report generating device 100 provided by the present invention first establishes a dimension analysis table according to preset chart dimensions through the data model generating unit 101, and associates the dimension analysis table with a preset chart database to form a chart data model; then, the chart data model is parsed and processed by the key data processing unit 102 to obtain chart key data, and the chart key data is processed into a chart data card through the model analysis system, and then, the data card input unit 103 marks a unique identifier on the chart data card, so that the chart data card carries the unique identifier and is input into the preset chart parsing model; wherein the chart parsing model is trained by statistical data formed by random chart data and statistical chart components, and then the information report generating unit 104 performs in-depth parsing on the chart data card through the chart parsing model to generate chart parsing text, and annotates the chart parsing text with classification information corresponding to the unique identifier according to the category to which the unique identifier belongs to form a chart information report. Each data card has a unique identifier, thereby improving the security and stability of the overall process during the processing of the data card, automatically performing layout to form a chart information report, and thus forming a standardized chart information report without manual interpretation, thereby improving reporting efficiency, saving manpower, and reducing overall project time.

[0135] like Figure 3 As shown, the present invention provides an electronic device 1 for a method of generating a chart information report.

[0136] The electronic device 1 may include a processor 10 , a memory 11 and a bus, and may further include a computer program stored in the memory 11 and executable on the processor 10 , such as a chart information report generating program 12 .

[0137] The memory 11 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a mobile hard disk, a multimedia card, a card-type memory (for example, an SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as a mobile hard disk of the electronic device 1. In other embodiments, the memory 11 can also be an external storage device of the electronic device 1, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card, etc. equipped on the electronic device 1. Furthermore, the memory 11 can also include both an internal storage unit of the electronic device 1 and an external storage device. The memory 11 can not only be used to store application software and various types of data installed in the electronic device 1, such as codes for generating chart information reports, etc., but can also be used to temporarily store data that has been output or is to be output.

[0138] In some embodiments, the processor 10 may be comprised of an integrated circuit, such as a single packaged integrated circuit or a plurality of packaged integrated circuits with the same or different functions, including a combination of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control core (Control Unit) of the electronic device, connecting the various components of the entire electronic device using various interfaces and circuits. It executes or runs programs or modules stored in the memory 11 (e.g., a program for generating chart information reports), and calls data stored in the memory 11 to perform various functions of the electronic device 1 and process data.

[0139] The bus may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable connection and communication between the memory 11 and at least one processor 10, etc.

[0140] Figure 3 Only the electronic device with components is shown, and it can be understood by those skilled in the art that Figure 3The structure shown does not constitute a limitation on the electronic device 1 , and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0141] For example, although not shown, the electronic device 1 may further include a power source (such as a battery) for powering the various components. Preferably, the power source may be logically connected to the at least one processor 10 via a power management device, thereby implementing functions such as charging management, discharging management, and power consumption management through the power management device. The power source may further include any components such as one or more DC or AC power sources, a recharging device, a power failure detection circuit, a power converter or inverter, a power status indicator, etc. The electronic device 1 may further include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0142] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device 1 and other electronic devices.

[0143] Optionally, the electronic device 1 may further include a user interface, which may be a display or an input unit (such as a keyboard). Optionally, the user interface may also be a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touch device. The display may also be appropriately referred to as a display screen or a display unit, which is used to display information processed in the electronic device 1 and to display a visual user interface.

[0144] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0145] The chart information report generating program 12 stored in the memory 11 of the electronic device 1 is a combination of multiple instructions. When executed in the processor 10, it can achieve the following:

[0146] Establishing a dimension analysis table according to the preset chart dimensions, and associating the dimension analysis table with a preset chart database to form a chart data model;

[0147] Parse the chart data model to obtain chart key data, and process the chart key data into chart data cards through the model analysis system;

[0148] A unique identifier is marked on a chart data card through a preset identifier control, so that the chart data card carries the unique identifier and is input into a preset chart parsing model; wherein the chart parsing model is trained by statistical data formed by random chart data and statistical chart components;

[0149] The chart data card is parsed by a chart parsing model to generate a chart parsing text, and classification information corresponding to the unique identifier is annotated on the chart parsing text according to the category to which the unique identifier belongs to form a chart information report.

[0150] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to Figure 1 The description of the relevant steps in the corresponding embodiment is not repeated here. It should be emphasized that in order to further ensure the privacy and security of the above-mentioned chart information report, the data generated by the above-mentioned chart information report is stored in the node of the blockchain where this server cluster is located.

[0151] The server can be a stand-alone server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), as well as big data and artificial intelligence platforms.

[0152] Furthermore, if the modules / units integrated in the electronic device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable medium may include any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0153] An embodiment of the present invention further provides a computer-readable storage medium, which may be non-volatile or volatile, and stores a computer program. When the computer program is executed by a processor, the following is achieved:

[0154] Establishing a dimension analysis table according to the preset chart dimensions, and associating the dimension analysis table with a preset chart database to form a chart data model;

[0155] Parse the chart data model to obtain chart key data, and process the chart key data into chart data cards through the model analysis system;

[0156] A unique identifier is marked on a chart data card through a preset identifier control, so that the chart data card carries the unique identifier and is input into a preset chart parsing model; wherein the chart parsing model is trained by statistical data formed by random chart data and statistical chart components;

[0157] The chart data card is parsed by a chart parsing model to generate a chart parsing text, and classification information corresponding to the unique identifier is annotated on the chart parsing text according to the category to which the unique identifier belongs to form a chart information report.

[0158] Specifically, the specific implementation method when the computer program is executed by the processor can refer to the description of the relevant steps in the embodiment of the chart information report generation method, which will not be repeated here.

[0159] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the module division is merely a logical function division, and other division methods may be used in actual implementation.

[0160] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed across multiple network elements. Some or all of the modules may be selected to achieve the purpose of the solution of this embodiment according to actual needs.

[0161] In addition, the functional modules in various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional modules.

[0162] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0163] Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims rather than the foregoing description, and all changes that come within the meaning and range of equivalents of the claims are intended to be embraced therein. Any reference to a table in a claim should not be construed as limiting the claim.

[0164] Blockchain, as used in this article, refers to a novel application model for computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Blockchain is essentially a decentralized database, a series of data blocks generated using cryptographic methods. Each block contains information about a batch of online transactions, used to verify the validity of this information (to prevent counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, the platform product service layer, and the application service layer.

[0165] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices recited in a system claim may also be implemented by a single unit or device through software or hardware. Second-order terms are used to indicate names and do not imply any particular order.

[0166] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for generating a chart information report, characterized in that: include: Establishing a dimension analysis table according to preset chart dimensions, and associating the dimension analysis table with a preset chart database to form a chart data model; Parsing the chart data model to obtain chart key data, and processing the chart key data into chart data cards through a model analysis system; The method includes: parsing the chart data model to obtain chart key data, wherein the chart key data includes chart meaning and numerical data corresponding to the chart meaning; using the chart meaning as a display item of the chart and the numerical data as the size of the display item to form a target chart through a model analysis system; traversing the display items through a preset reading program to obtain the specific meaning of the display items, and annotating the specific meaning in the target chart to form a chart data card; A unique identifier is marked on the chart data card through a preset identifier control, so that the chart data card carries the unique identifier and is input into a preset chart parsing model; wherein the chart parsing model is trained by random chart data and statistical data formed by a statistical chart component; the process of training the chart parsing model includes: forming a statistical chart through pre-acquired random data and an Echart component; annotating the statistical chart through a preset automatic annotation plug-in to form test data, wherein the test data includes a test set and a training set; inputting the training set into a convolutional neural network to form a chart parsing script, and testing the chart parsing script through the test set to form a feedback function; adjusting the parameters of the chart parsing script according to the value of the feedback function, and when the value of the feedback function is within a preset threshold range, using the chart parsing script as a chart parsing model; The chart data card is parsed by the chart parsing model to generate a chart parsing text, and classification information corresponding to the unique identifier is annotated on the chart parsing text according to the category to which the unique identifier belongs to form a chart information report; wherein the chart data card is deeply parsed by the chart parsing model to generate a chart parsing text, including: determining whether the obtained chart data card matches the unique identifier; if the unique identifier matches the chart data card, the chart data card is verified by the chart parsing model, and the verified chart data card is deeply parsed to form parsed data; the parsed data is expressed in text by the chart parsing model to generate a chart parsing text.

2. The method for generating a chart information report according to claim 1, wherein: The step of establishing a dimension analysis table according to the preset chart dimensions includes: Use the name of each preset chart dimension as the first column; Classifying the characteristics of each preset chart dimension as a second type of column, wherein the category information in the second type of column corresponds to the name of the preset chart dimension in the first type of column; Information is sorted in the second-type vertical columns to form second-type sub-columns, and information is filled in the second-type sub-columns to form a dimensional analysis table.

3. The method for generating a chart information report according to claim 2, wherein: The step of associating the dimension analysis table with a preset chart database to form a chart data model includes: Calling a chart database and associating the chart database with the dimension analysis table; extracting target data corresponding to the dimension analysis table from the chart database; Modeling is performed according to the first type of vertical columns and the second type of sub-columns to form a model framework, and the target data is filled into the model framework to form a chart data model; wherein, after the target data is filled into the model framework to form the chart data model, the target data is updated at a preset time interval to update the chart data model.

4. The method for generating a chart information report according to claim 1, wherein: The step of annotating the classification information corresponding to the unique identifier on the chart parsing text to form a chart information report includes: Classify the preset unique identifiers into categories to form classification information, and configure numbering rules based on the classification information; Acquire the classification information of the unique identifier corresponding to the chart data card, and number the chart parsing text based on the classification information and the numbering rule to form a classification number; Marking the corresponding number on the chart analysis text to form a target report; Inputting the chart data card and the target report into a BI tool, so that a dashboard editor of the BI tool typeset the target report, and printing the typeset chart information report into a PDF version to generate a chart information report; Send the chart information report to a preset designated mailbox.

5. A device for generating a chart information report, characterized in that: The device comprises: a data model generating unit, configured to establish a dimension analysis table according to preset chart dimensions, and associate the dimension analysis table with a preset chart database to form a chart data model; a key data processing unit, configured to parse the chart data model to obtain chart key data, and process the chart key data into a chart data card through a model analysis system; wherein the process includes: parsing the chart data model to obtain chart key data, wherein the chart key data includes chart meaning and numerical data corresponding to the chart meaning; using the model analysis system to use the chart meaning as a display item of the chart and the numerical data as a size of the display item to form a target chart; traversing the display items through a preset reading program to obtain a specific meaning of the display item, and annotating the specific meaning in the target chart to form a chart data card; A data card input unit, configured to mark a unique identifier on the chart data card through a preset identifier control, so that the chart data card carries the unique identifier and is input into a preset chart parsing model; wherein the chart parsing model is trained by random chart data and statistical data formed by a statistical chart component; a process of training the chart parsing model comprises: forming a statistical chart through pre-acquired random data and an Echart component; annotating the statistical chart through a preset automatic annotation plug-in to form test data, wherein the test data includes a test set and a training set; inputting the training set into a convolutional neural network to form a chart parsing script, and testing the chart parsing script through the test set to form a feedback function; adjusting the parameters of the chart parsing script according to the value of the feedback function, and when the value of the feedback function is within a preset threshold range, using the chart parsing script as a chart parsing model; An information report generating unit is used to parse the chart data card through the chart parsing model to generate a chart parsing text, and to annotate the classification information corresponding to the unique identifier on the chart parsing text according to the category to which the unique identifier belongs to form a chart information report; wherein the deep parsing of the chart data card through the chart parsing model to generate the chart parsing text includes: determining whether the obtained chart data card matches the unique identifier; if the unique identifier matches the chart data card, verifying the chart data card through the chart parsing model, and deeply parsing the verified chart data card to form parsed data; and expressing the parsed data in text through the chart parsing model to generate the chart parsing text.

6. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the steps of the method for generating a chart information report according to any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for generating a chart information report according to any one of claims 1 to 4 is implemented.

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