Acquisition method of financial software information

Abstract

The invention relates to the technical field of financial software information collection, in particular to a financial software information collection method. A financial software information acquisition method comprises the following steps: SS01, permission acquisition: acquiring a data acquisition permission given by a management end under a user ID according to the user ID logged in by financial software, and establishing a financial software information acquisition system according to the data acquisition permission, SS02, acquisition port docking: when the financial software information acquisition system is established, establishing an API data interface, and when the financial software information acquisition system is established, establishing an API data interface; and after the API data interface is established, obtaining various specified data. The financial software information acquisition device has the beneficial effects that when the financial software information acquisition device acquires financial software information, on one hand, various data during financial software operation can be comprehensively acquired, and on the other hand, real-time optimization, addition and updating of acquisition scripts can be carried out during financial software information acquisition; and therefore, the data acquisition correspondence, the data acquisition rate and the data acquisition accuracy can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of financial software information collection, in particular to a method for collecting financial software information. Background Art

[0002] Financial software is a common enterprise management software, which is mainly used for the management of the company's financial accounts, capital accounts, income and expenditure status, etc. When managing multiple financial software in an enterprise or the financial software of multiple enterprises, it is necessary to collect the corresponding financial software to obtain the corresponding information and data.

[0003] In the prior art, a patent document with publication number CN115757595B discloses a method for collecting financial software information, which includes the following steps: Step 1: Each financial software sets a database, and the database is set with a mark I; Step 2: The financial software marks and classifies the input information and data, and divides the input information into categories with mark I and non-mark I; when the information and data marked as I are backed up to the local host of the financial software, a group of data is also copied and transmitted to the database; Step 3: The collection host end is connected to each financial software through a protocol and sets permissions; Step 4: The collection host end sends a request instruction to obtain data of the corresponding financial software; the instruction includes classification information and data with mark I and classification information and data without mark I.

[0004] However, the above-mentioned collection method is not convenient for comprehensive collection of various data during the operation of financial software on the one hand, and is not convenient for real-time optimization and updating of collection scripts when collecting financial software information on the other hand, and is subsequently not convenient for effectively improving the responsiveness, data collection rate and accuracy of data collection. Based on this, the present invention provides a method for collecting financial software information to solve the problems raised in the above-mentioned background technology. Summary of the invention

[0005] The present invention aims at the technical problems existing in the prior art and provides a method for collecting financial software information to solve the problem that the existing collection device is not convenient for comprehensive collection of various data when the financial software is running, and is not convenient for real-time optimization and updating of the collection script when collecting financial software information, and is subsequently not convenient for effectively improving the responsiveness, data collection rate and accuracy of data collection.

[0006] The technical solution of the present invention to solve the above technical problem is as follows: A method for collecting financial software information comprises the following steps:

[0007] SS01. Establish a data collection database, establish a data collection script execution library, execute valid data scripts in the data collection script execution library one by one, and obtain the financial data collected by each data script. Each data script and its collected financial data are named PN, and multiple PNs are finally integrated into the database;

[0008] SS02, log collection. When the user queries, browses, edits and modifies the database, the log collection script records each execution data of the user. Finally, the log collection script obtains the number of clicks U of each PN, the time ST of each PN being consulted in the non-editing state, the percentage value K of the secondary editing ratio of each PN, the secondary editing time WT of each PN, and the click order value B of each PN;

[0009] SS03, execution level sorting, based on the log data of each PN obtained in the log collection script in step SS02, to calculate the execution priority ∑1 of each PN;

[0010]

[0011] SS04, AI script establishment, establish artificial intelligence script generation algorithm, and finally generate and input N AI collection scripts in the data collection script execution library;

[0012] SS05, acquisition option establishment, respectively establish fast data acquisition command option and comprehensive data acquisition option;

[0013] SS06, update of sorting table: the collection algorithm updates the sorting table of collection scripts in real time according to the real-time log data of the database. Finally, each item or each type of data requirement corresponds to a real-time optimal data collection script.

[0014] SS07, data verification, when the fast data collection command is executed, a fast data set KSJ is obtained. When the comprehensive data collection command is executed, each data script executed by the comprehensive data collection instruction finally obtains a comprehensive data set QSJ. The comparison algorithm is used to calculate the similarity of the two QSJs. After the similarity of the two QSJs is calculated, a public data with high accuracy QSJ is finally obtained. After the QSJ with high data accuracy is obtained, it is compared with the KSJ data and a similarity value QR is obtained;

[0015] When QR ≥ 90%, execute the data push command and push KSJ. When KSJ pushes, the number of pushes is recorded as KN;

[0016] When QR is less than 90%, execute the data push command, and push KSJ and a QSJ with a higher public data accuracy synchronously. When KSJ and a QSJ with a higher public data accuracy are pushed synchronously, the number of pushes of QSJ is recorded as NN;

[0017] SS08, weight value addition, add weight values ​​to multiple data collection scripts under each item or each type of data requirement, and calculate the weight addition value ∑2 of each script:

[0018]

[0019] KN is the number of times the data collected by the first-ranked data collection script under each item or category of data requirements is pushed;

[0020] NN is the number of times the data collected by the data collection script is pushed;

[0021] Finally, each data collection script obtains a push weight ∑3;

[0022]

[0023] SS09, data push, collect push algorithm to execute push command, and automatically calculate the click rate of the push command∑4;

[0024]

[0025] SS10, data correction, after the financial software information collection system runs for a specified time, it automatically corrects the data in the data collection script execution library. When the data in the data collection script execution library is corrected, the accurate matching priority ∑ of each data collection script is automatically calculated;

[0026]

[0027] After the data is corrected, the data collection script execution library automatically creates the optimal data collection script for each item or each type of number requirement. During the next specified time of the financial software information collection system, the data collection script execution library executes the optimal data collection script for each item or each type of number requirement and obtains data.

[0028] The beneficial effects of the present invention are:

[0029] When collecting financial software information, this collection device can, on the one hand, comprehensively collect various data when the financial software is running, and on the other hand, can perform real-time optimization, addition and update of the collection script when collecting financial software information, thereby effectively improving the responsiveness, data collection rate and accuracy of data collection.

[0030] Based on the above technical solution, the present invention can also be improved as follows.

[0031] Furthermore, the data acquisition script execution library also includes the following steps before being established:

[0032] SS011, authority acquisition, based on the user ID logged in to the financial software, obtain the data collection authority given by the management end to the user ID, and establish a financial software information collection system based on the data collection authority;

[0033] SS012, collection port docking, when the financial software information collection system is built, establish an API data interface, and after the API data interface is established, obtain various specified data;

[0034] SS013, Collection script establishment, obtain the user's data collection requirements, establish multiple data collection scripts for each item or each type of data requirement, after multiple data collection scripts are generated, integrate the generated data collection scripts into the data collection script execution library, and the data collection script execution library has a built-in data collection script sorting table when executing;

[0035] SS014, collection script verification, execute the data scripts in the data collection script execution library one by one to determine whether the script can be run and obtain matching data. If the script cannot be executed and cannot obtain valid data, the invalid script will be removed from the data collection script execution library.

[0036] Furthermore, in the SS012 step, when the API data interface is connected, the API data interface is connected with the bank data terminal, the tax data terminal, the data entry terminal and the log output terminal of the financial software. When the financial software is running, a web crawler is injected into the background management terminal of the financial software. The web crawler collects the interface image and operation database of each operation of the financial software. After the above data is obtained, the real-time key feature words, data generation time, data format, data type and data storage path of the financial software are collected using OCR recognition technology and data recognition algorithm.

[0037] Furthermore, in the SS013 step, each of the data collection scripts includes the following parameters: data collection key feature words P1, key data format P2, data type P3, data generation time P4, data storage path P5, collection frequency P6 and collection process P7, and the script parameters of each data collection script are different.

[0038] Furthermore, in the SS01 step, the database can be queried, browsed, edited and modified by users, the database has a built-in log collection script, and the data in the database is backed up to the cloud in real time.

[0039] Furthermore, in the SS04 step, when the AI ​​script generation algorithm establishes the AI ​​acquisition script, the AI ​​script generation algorithm acquires the top 10 PN feature sets in priority order. After the PN feature sets are integrated, P1, P2, P3, P4, P5, P6, and P7 contained in the PN are rearranged in a random order, and exhaustive addition and exhaustive editing of the P1, P2, P3, P4, P5, P6, and P7 data are performed at the same time.

[0040] Furthermore, in the SS05 step, when the fast data collection command option is executed by the user, the data collection script execution library executes the data collection script ranked first in the data collection script sorting table; when the comprehensive data collection option is executed, the data collection script execution library executes the first M data collection scripts in the data collection script sorting table; when the fast data collection command option and the comprehensive data collection option are executed, the collected data are backed up to the database in real time.

[0041] Furthermore, when the collection push algorithm executes the push command in the SS09 step, the pushed data is automatically encrypted. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A schematic diagram of the principle of a method for collecting financial software information according to the present invention;

[0043] Figure 2 The present invention is a flowchart of a method for collecting financial software information. DETAILED DESCRIPTION

[0044] The principles and features of the present invention are described below in conjunction with the accompanying drawings. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0045] The present invention provides the following preferred embodiments

[0046] like Figure 1 and Figure 2 As shown, a method for collecting financial software information includes the following steps:

[0047] SS01. Establish a data collection database, establish a data collection script execution library, execute valid data scripts in the data collection script execution library one by one, and obtain the financial data collected by each data script. Each data script and its collected financial data are named PN, and multiple PNs are finally integrated into the database;

[0048] In step SS01, the database can be queried, browsed, edited and modified by users. The database has a built-in log collection script, and the data in the database is backed up to the cloud in real time;

[0049] The data acquisition script execution library also includes the following steps before being established:

[0050] SS011, authority acquisition, based on the user ID logged in to the financial software, obtain the data collection authority given by the management end to the user ID, and establish a financial software information collection system based on the data collection authority;

[0051] SS012, collection port docking, when the financial software information collection system is built, establish an API data interface, and after the API data interface is established, obtain various specified data;

[0052] In step SS012, when the API data interface is connected, the API data interface is connected with the bank data terminal, tax data terminal, financial software data entry terminal, and log output terminal data;

[0053] After the API data interface is connected, the data from the bank data terminal, tax data terminal, financial software data entry terminal, and log output terminal are imported into the financial software information collection system;

[0054] When the financial software is running, a web crawler is injected into the background management terminal of the financial software. The web crawler collects the interface images and operation database of each operation of the financial software. After the above data is obtained, the real-time key feature words, data generation time, data format, data type and data storage path of the financial software when it is running are collected using OCR recognition technology and data recognition algorithm;

[0055] SS013, Collection script establishment, obtain the user's data collection requirements, establish multiple data collection scripts for each item or each type of data requirement, after multiple data collection scripts are generated, integrate the generated data collection scripts into the data collection script execution library, and the data collection script execution library has a built-in data collection script sorting table when executing;

[0056] In step SS03, each data collection script includes the following parameters: data collection key feature words P1, key data format P2, data type P3, data generation time P4, data storage path P5, collection frequency P6 and collection process P7. The script parameters of each data collection script are different.

[0057] SS014, collection script verification, execute the data scripts in the data collection script execution library one by one to determine whether the script can be run and obtain matching data. If the script cannot be executed and cannot obtain valid data, the invalid script will be removed from the data collection script execution library;

[0058] SS02, log collection. When the user queries, browses, edits and modifies the database, the log collection script records each execution data of the user. Finally, the log collection script obtains the number of clicks U of each PN, the time ST of each PN being consulted in the non-editing state, the percentage value K of the secondary editing ratio of each PN, the secondary editing time WT of each PN, and the click order value B of each PN;

[0059] SS03, execution level sorting, based on the log data of each PN obtained in the log collection script in step SS02, to calculate the execution priority ∑1 of each PN;

[0060]

[0061] When the number of clicks on PN is 90, then U = 90;

[0062] When the PN is not edited and the access time is 30 minutes, ST = 30;

[0063] When the secondary editing time of PN is 120min, TS=120;

[0064] When the percentage of secondary editing of PN is 10%, K = 10;

[0065] When the click order value of PN is 1, B=1;

[0066] SS04, AI script establishment, establish artificial intelligence script generation algorithm, and finally generate and input N AI collection scripts in the data collection script execution library;

[0067] In step SS04, when the AI ​​script generation algorithm establishes the AI ​​acquisition script, the AI ​​script generation algorithm collects the top 10 PN feature sets in priority order. After the PN feature sets are integrated, P1, P2, P3, P4, P5, P6, and P7 contained in the PN are re-arranged in a disordered manner, and at the same time, exhaustive addition and exhaustive editing of P1, P2, P3, P4, P5, P6, and P7 data are performed;

[0068] SS05, acquisition option establishment, respectively establish fast data acquisition command option and comprehensive data acquisition option;

[0069] In step SS05, when the fast data collection command option is executed by the user, the data collection script execution library executes the data collection script ranked first in the data collection script sorting table. When the comprehensive data collection option is executed, the data collection script execution library executes the first M data collection scripts in the data collection script sorting table. When the fast data collection command option and the comprehensive data collection option are executed, the collected data are backed up to the database in real time.

[0070] SS06, update of sorting table: the collection algorithm updates the sorting table of collection scripts in real time according to the real-time log data of the database. Finally, each item or each type of data requirement corresponds to a real-time optimal data collection script.

[0071] SS07, data verification, when the fast data collection command is executed, a fast data set KSJ is obtained. When the comprehensive data collection command is executed, each data script executed by the comprehensive data collection instruction finally obtains a comprehensive data set QSJ. The comparison algorithm is used to calculate the similarity of the two QSJs. After the similarity of the two QSJs is calculated, a public data with high accuracy QSJ is finally obtained. After the QSJ with high data accuracy is obtained, it is compared with the KSJ data and a similarity value QR is obtained;

[0072] When QR ≥ 90%, execute the data push command and push KSJ. When KSJ pushes, the number of pushes is recorded as KN;

[0073] When QR is less than 90%, execute the data push command, and push KSJ and a QSJ with a higher public data accuracy synchronously. When KSJ and a QSJ with a higher public data accuracy are pushed synchronously, the number of pushes of QSJ is recorded as NN;

[0074] SS08, weight value addition, add weight values ​​to multiple data collection scripts under each item or each type of data requirement, and calculate the weight addition value ∑2 of each script:

[0075]

[0076] KN is the number of times the data collected by the first-ranked data collection script under each item or category of data requirements is pushed;

[0077] NN is the number of times the data collected by the data collection script is pushed;

[0078] When KN=100, NN=50, ∑2=2;

[0079] Finally, each data collection script obtains a push weight ∑3;

[0080]

[0081] SS09, data push, collect push algorithm to execute push command, and automatically calculate the click rate of the push command∑4;

[0082]

[0083] When the collection and push algorithm executes the push command in step SS09, the pushed data is automatically encrypted;

[0084] SS10, data correction, after the financial software information collection system runs for a specified time, it automatically corrects the data in the data collection script execution library. When the data in the data collection script execution library is corrected, the accurate matching priority ∑ of each data collection script is automatically calculated;

[0085]

[0086] After the data is corrected, the data collection script execution library automatically creates the optimal data collection script for each item or each type of number requirement. During the next specified time of the financial software information collection system, the data collection script execution library executes the corrected optimal data collection script for each item or each type of number requirement and obtains data.

[0087] Through data correction, the collection speed and accuracy of financial software information can be effectively guaranteed;

[0088] At the same time, through data correction, the bandwidth load during financial software information collection can be effectively reduced.

[0089] The working process of the present invention is as follows:

[0090] Collection database establishment and permission acquisition:

[0091] First, establish a data collection script execution library and execute the valid data scripts one by one to collect financial data.

[0092] According to the user ID logged in to the financial software, the corresponding data collection permissions are obtained, and the financial software information collection system is established accordingly.

[0093] Collection port connection and data acquisition:

[0094] Establish an API data interface and connect it with the bank data terminal, tax data terminal, financial software data entry terminal, and log output terminal.

[0095] Through web crawler technology, real-time key feature words, data generation time, data format, data type, data storage path and other information are collected when the financial software is running.

[0096] Collection script creation and verification:

[0097] According to the user's data collection needs, multiple data collection scripts are established and integrated into the data collection script execution library.

[0098] Verify each data collection script to ensure that it can run normally and obtain valid data.

[0099] Log collection and execution level sorting:

[0100] Record the user's query, browsing, editing and modification operations on the database, and obtain relevant log data.

[0101] The execution priority of each PN (data script and the financial data it collects) is calculated based on the log data.

[0102] AI script creation:

[0103] Using the artificial intelligence script generation algorithm, N AI acquisition scripts are generated and input according to the top 10 PN feature sets ranked by priority.

[0104] Collection options set up:

[0105] Provides fast data acquisition command options and comprehensive data acquisition options to meet the needs of different users.

[0106] Sorting table update and data verification:

[0107] The collection script sorting table is updated in real time according to the real-time log data of the database.

[0108] The similarity calculation is performed on the fast dataset and the comprehensive dataset, and the dataset to be pushed is determined based on the result.

[0109] Weight value addition:

[0110] A weight value is added to each data collection script to reflect the priority of its data being pushed.

[0111] Data push:

[0112] Execute the data push command, automatically encrypt the pushed data, and record the click rate.

[0113] Data correction:

[0114] After the financial software information collection system runs for a specified time, the data collection script execution library will be automatically corrected.

[0115] An optimal data collection script is established based on the correction results and executed within the next specified time.

[0116] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for collecting financial software information, characterized in that: The following steps are involved: SS01. Establish a data collection database, establish a data collection script execution library, execute valid data scripts in the data collection script execution library one by one, and obtain the financial data collected by each data script. Each data script and its collected financial data are named PN, and multiple PNs are finally integrated into the database; SS02, log collection. When the user queries, browses, edits and modifies the database, the log collection script records each execution data of the user. Finally, the log collection script obtains the number of clicks U of each PN, the time ST of each PN being consulted in the non-editing state, the percentage value K of the secondary editing ratio of each PN, the secondary editing time WT of each PN, and the click order value B of each PN; SS03, execution level sorting, based on the log data of each PN obtained in the log collection script in step SS02, to calculate the execution priority ∑1 of each PN; SS04, AI script establishment, establish artificial intelligence script generation algorithm, and finally generate and input N AI collection scripts in the data collection script execution library; SS05, acquisition option establishment, respectively establish fast data acquisition command option and comprehensive data acquisition option; SS06, update of sorting table: the collection algorithm updates the sorting table of collection scripts in real time according to the real-time log data of the database. Finally, each item or each type of data requirement corresponds to a real-time optimal data collection script. SS07, data verification, when the fast data collection command is executed, a fast data set KSJ is obtained. When the comprehensive data collection command is executed, each data script executed by the comprehensive data collection instruction finally obtains a comprehensive data set QSJ. The comparison algorithm is used to calculate the similarity of the two QSJs. After the similarity of the two QSJs is calculated, a public data with high accuracy QSJ is finally obtained. After the QSJ with high data accuracy is obtained, it is compared with the KSJ data and a similarity value QR is obtained; When QR ≥ 90%, execute the data push command and push KSJ. When KSJ pushes, the number of pushes is recorded as KN; When QR is less than 90%, execute the data push command, and push KSJ and a QSJ with a higher public data accuracy synchronously. When KSJ and a QSJ with a higher public data accuracy are pushed synchronously, the number of pushes of QSJ is recorded as NN; SS08, weight value addition, add weight values ​​to multiple data collection scripts under each item or each type of data requirement, and calculate the weight addition value ∑2 of each script: KN is the number of times the data collected by the first-ranked data collection script under each item or category of data requirements is pushed; NN is the number of times the data collected by the data collection script is pushed; Finally, each data collection script obtains a push weight ∑3; SS09, data push, collect push algorithm to execute push command, and automatically calculate the click rate of the push command∑4; SS10, data correction, after the financial software information collection system runs for a specified time, it automatically corrects the data in the data collection script execution library. When the data in the data collection script execution library is corrected, the accurate matching priority ∑ of each data collection script is automatically calculated; After the data is corrected, the data collection script execution library automatically creates the optimal data collection script for each item or each type of number requirement. During the next specified time of the financial software information collection system, the data collection script execution library executes the optimal data collection script for each item or each type of number requirement and obtains data.

2. A method for collecting financial software information according to claim 1, characterized in that: The data acquisition script execution library also includes the following steps before being established: SS011, authority acquisition, based on the user ID logged in to the financial software, obtain the data collection authority given by the management end to the user ID, and establish a financial software information collection system based on the data collection authority; SS012, collection port docking, when the financial software information collection system is built, establish an API data interface, and after the API data interface is established, obtain various specified data; SS013, Collection script establishment, obtain the user's data collection requirements, establish multiple data collection scripts for each item or each type of data requirement, after multiple data collection scripts are generated, integrate the generated data collection scripts into the data collection script execution library, and the data collection script execution library has a built-in data collection script sorting table when executing; SS014, collection script verification, execute the data scripts in the data collection script execution library one by one to determine whether the script can be run and obtain matching data. If the script cannot be executed and cannot obtain valid data, the invalid script will be removed from the data collection script execution library.

3. A method for collecting financial software information according to claim 2, characterized in that: In the SS012 step, when the API data interface is connected, the API data interface is connected with the bank data terminal, the tax data terminal, the data entry terminal of the financial software, and the log output terminal. When the financial software is running, a web crawler is injected into the background management terminal of the financial software. The web crawler collects the interface image and operation database of each operation of the financial software. After the above data is obtained, the real-time key feature words, data generation time, data format, data type and data storage path of the financial software are collected using OCR recognition technology and data recognition algorithm.

4. A method for collecting financial software information according to claim 3, characterized in that: In the SS013 step, each of the data collection scripts includes the following parameters: data collection key feature words P1, key data format P2, data type P3, data generation time P4, data storage path P5, collection frequency P6 and collection process P7, and the script parameters of each data collection script are different.

5. The method for collecting financial software information according to claim 1, characterized in that: In the SS01 step, the database can be queried, browsed, edited and modified by users. The database has a built-in log collection script, and the data in the database is backed up to the cloud in real time.

6. A method for collecting financial software information according to claim 1, characterized in that: In the SS04 step, when the AI ​​script generation algorithm establishes the AI ​​acquisition script, the AI ​​script generation algorithm acquires the top 10 PN feature sets in priority order. After the PN feature sets are integrated, P1, P2, P3, P4, P5, P6, and P7 contained in the PN are re-arranged in a random order, and at the same time, exhaustive addition and exhaustive editing of P1, P2, P3, P4, P5, P6, and P7 data are performed.

7. A method for collecting financial software information according to claim 1, characterized in that: In the SS05 step, when the fast data acquisition command option is executed by the user, the data acquisition script execution library executes the data acquisition script ranked first in the data acquisition script sorting table. When the comprehensive data acquisition option is executed, the data acquisition script execution library executes the first M data acquisition scripts in the data acquisition script sorting table. When the fast data acquisition command option and the comprehensive data acquisition option are executed, the collected data are backed up to the database in real time.

8. A method for collecting financial software information according to claim 1, characterized in that: When the collection and push algorithm executes the push command in the SS09 step, the pushed data is automatically encrypted.

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