CN117236303A - Data-based target form filling method and device - Google Patents
Data-based target form filling method and device Download PDFInfo
- Publication number
- CN117236303A CN117236303A CN202311193047.XA CN202311193047A CN117236303A CN 117236303 A CN117236303 A CN 117236303A CN 202311193047 A CN202311193047 A CN 202311193047A CN 117236303 A CN117236303 A CN 117236303A
- Authority
- CN
- China
- Prior art keywords
- target
- data
- metadata
- function
- function expression
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 43
- 230000006870 function Effects 0.000 claims description 148
- 230000014509 gene expression Effects 0.000 claims description 109
- 230000015654 memory Effects 0.000 claims description 24
- 238000012216 screening Methods 0.000 claims description 12
- 238000012549 training Methods 0.000 claims description 5
- 238000004458 analytical method Methods 0.000 claims description 2
- 238000012545 processing Methods 0.000 abstract description 2
- 230000008569 process Effects 0.000 description 12
- 238000004364 calculation method Methods 0.000 description 7
- 230000008520 organization Effects 0.000 description 4
- 238000004366 reverse phase liquid chromatography Methods 0.000 description 4
- 238000004891 communication Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 238000010195 expression analysis Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 239000007787 solid Substances 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 238000012821 model calculation Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Landscapes
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention relates to the technical field of digital data processing, and discloses a target form filling method and a device based on data.
Description
Technical Field
The invention relates to the technical field of digital data processing, in particular to a target form filling method and device based on data.
Background
With the increasing degree of informatization, various industries involve a large amount of data collection and analysis, so the filling and generation of reports have become an unavoidable task for many enterprises and institutions. The traditional report form filling mode generally needs to manually fill a large amount of structured data, such as provincial and urban area information, and the data has the grade attribute, so that manual filling workload is huge, error rate is high, and the grade corresponding error problem is easy to occur.
In order to solve the problem of high manual filling error rate, in the related technology, coordinate points are given to each content in the metadata table by establishing an X-axis and a Y-axis in the metadata table, so that the content in the metadata table is extracted by a preset program through positioning in the mode of the coordinate points, and further the content filling of the target table is realized. The filling of the contents of the target table is completed by establishing a coordinate system in the metadata table, and when the items and the contents in the metadata table are complex and various, the calculation amount required to be performed increases exponentially, so that the filling efficiency of the contents of the target table is affected, and the loading of the contents of the system operation target table is increased.
Disclosure of Invention
In view of the above, the embodiments of the present invention provide a method and an apparatus for filling a target table based on data, so as to solve the technical problem of low efficiency of filling the target table.
In a first aspect, the present invention provides a method for filling a target table based on data, including: acquiring metadata and a function expression; analyzing the function expression, and determining an analyzed data result; screening target metadata conforming to the data result based on the data result; and completing filling of the target table by the target metadata based on the preset corresponding relation between the metadata and the target table.
With reference to the first aspect, in one possible implementation manner of the first aspect, parsing the function expression, determining a parsed data result includes: traversing the function expression, and determining a data structure of the function expression; based on the data structure, the parsed data results are determined.
With reference to the first aspect, in one possible implementation manner of the first aspect, the data structure includes: function name and function content; traversing the functional expression, determining a data structure of the functional expression, comprising: traversing the function expression, executing stacking when the function expression traverses to the first starting mark, and determining the function name of the function expression; and when traversing the function expression to the first termination mark, performing stack stripping, and determining the function content of the function expression.
With reference to the first aspect, in one possible implementation manner of the first aspect, the data structure includes: function name, function content and sub-function expression; traversing the functional expression, determining a data structure of the functional expression, comprising: traversing the function expression, executing stacking when the function expression traverses to the first starting mark, and determining the function name of the function expression; when traversing the function expression to a second starting mark, if the stack is not empty, executing stacking, and determining the function name of the sub-function expression; determining the function content of the sub-function expression when the function expression traverses to the second termination mark; and when traversing the function expression to the first termination mark, performing stack stripping, and determining the function content of the function expression.
With reference to the first aspect, in one possible implementation manner of the first aspect, the target table includes: target data item number, and target content stored in the target data item number, target metadata, including: a first target field, and first target data stored in the first target field; based on the preset corresponding relation between the metadata and the target table, completing filling of the target table by the target metadata, including: determining the corresponding relation between the number of the target data item and the first target field based on the preset corresponding relation between the metadata and the target table; and filling the first target data into the target content based on the corresponding relation between the target data item number and the first target field.
With reference to the first aspect, in one possible implementation manner of the first aspect, the target table includes: target data item number, and target content stored in the target data item number, target metadata, including: a second target field, and second target data stored in the second target field; based on the preset corresponding relation between the metadata and the target table, completing filling of the target table by the target metadata, including: acquiring user rights; determining a second target field corresponding to the user rights based on the user rights; determining the corresponding relation between the number of the target data item and the second target field based on the preset corresponding relation between the metadata and the target table; and filling the second target data into the target content based on the corresponding relation between the target data item number and the second target field.
With reference to the first aspect, in one possible implementation manner of the first aspect, the method further includes: and inputting the target metadata into the trained training model to obtain target prediction data corresponding to the target metadata.
In a second aspect, the present invention provides a data-based object table filling apparatus, including: the acquisition module is used for acquiring the metadata and the function expression; the analysis module is used for analyzing the function expression and determining an analyzed data result; the screening module is used for screening target metadata conforming to the data result based on the data result; and the filling module is used for completing filling of the target table by the target metadata based on the preset corresponding relation between the metadata and the target table.
In a third aspect, the present invention provides a computer device comprising: the memory and the processor are in communication connection, computer instructions are stored in the memory, and the processor executes the computer instructions, so that the data-based target table filling method of the first aspect or any corresponding embodiment of the first aspect is executed.
In a fourth aspect, the present invention provides a computer readable storage medium having stored thereon computer instructions for causing a computer to perform the data-based target table population method of the first aspect or any of its corresponding embodiments.
The technical scheme of the invention has the following advantages:
according to the target form filling method based on the data, the metadata and the function expression are obtained, the analyzed data result is determined in a function expression analysis mode, namely the dimension related to the target form is determined, the data is screened through the determined dimension, the screened metadata is used as the basis of filling the target form, so that the data calculated amount is effectively reduced, the data which are irrelevant to the target form in the metadata are removed, and on the basis, filling of the target form is completed through the preset corresponding relation, the error rate of filling of the form is effectively reduced, and the filling efficiency of the target form can be effectively improved and the use load is lightened due to the fact that the data calculated amount is reduced.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow diagram of a method for data-based target table population in accordance with an embodiment of the present invention;
FIG. 2 is a block diagram of a data-based destination table populating apparatus in accordance with an embodiment of the present invention;
fig. 3 is a schematic hardware structure of a computer device according to an embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In general, a large number of work scenarios involving form filling occur in an ERP (Enterprise Resource Planning ) system, in which a large amount of structured data with order relationships needs to be filled in, errors are easily generated due to complicated operations, and since a large amount of calculation is required by a part of automated form filling program, the filling efficiency of forms is low, the required time for form filling is further increased, which is contrary to the original intention of introducing automated form filling, therefore, the present embodiment provides a data-based target form filling method, as shown in fig. 1, comprising the following steps:
s101, acquiring metadata and a function expression.
Specifically, the metadata refers to structured data, and is generally derived from a database table, an Excel file, a csv file, etc. maintained in the ERP system, where the Excel file and the csv file may also be converted into the database table. The content of the metadata and the target table can be divided into: a fillable data item and non-fillable format information, wherein the non-fillable format information is used for representing a project name of a certain item in the metadata or the target form, the fillable data item is used for representing specific content under a corresponding project name, for example, the project name of the certain item in the metadata or the target form is a year, and the specific content under the corresponding project name can be 2019, 2020 or other years.
In particular, a function expression refers to an expression consisting of function names and parameters, the function expression can be composed of a plurality of functions, each function can be used by AND logic or OR logic and nesting, the function expression is used for determining target metadata, namely, the metadata related to a target table is determined by analyzing the function expression,
specifically, the functions in the function expression include: context functions, string intercept functions, report fetch functions, call RPCs (Remote Procedure Call, remote procedure call protocol), etc. The context function is used for determining the item name of a certain item in the metadata or the target table, namely the dimension information of the report, such as organization, year, period, unique identification of the report and the like. The report form access function is used for determining specific contents under the corresponding item names, such as report form numbers, organization ids and the like, wherein if a certain item in the target table is connected with certain data in the metadata, the specific contents can be directly obtained through the report form access function. The string intercept function is used to determine the string from the intercept start flag to the intercept end flag. The call RPC is used to determine the return value of the RPC service.
S102, analyzing the function expression, and determining the analyzed data result.
Specifically, analyzing the function expression, determining the analyzed data result refers to determining the data structure of the function expression by traversing the function expression, so that the analyzed data result, namely determining the query condition statement of the screening metadata, is determined by the data structure. If the data structure of the parsed function expression is context (orgid) and orgname=bb (DWMC), where context represents a context function, bb represents a report access function, and the context function and the access function are logically connected through an and, the parsed data result may be represented as "xx" and orgname= "xxx", where orgid represents an organization identifier corresponding to "xx" represents dimension information of the report, orgName represents an organization name corresponding to "xxx" represents specific content in the dimension.
S103, screening target metadata conforming to the data result based on the data result.
Specifically, screening target metadata corresponding to the data result based on the data result means that the data result is combined, the matched metadata is screened through a query condition statement of the metadata, and the screened metadata is used as the target metadata. As the data result, "xx" indicates that the dimension information is year, and "xxx" indicates that the specific content in the dimension is 2021, the target metadata is only 2021 metadata.
S104, completing filling of the target table by the target metadata based on the preset corresponding relation between the metadata and the target table.
Specifically, completing the filling of the target table with the target metadata based on the preset correspondence between the metadata and the target table means that the filtered metadata, i.e., the target metadata, is respectively filled into the corresponding items of the target table through the preset correspondence between the metadata and the target table. If described by an expression, it can be described as: select (field 1, field2 from (field 1, field2, field3 from …) t where field 3= "xx" and a= "xxx" so that code1 corresponding to field1 in metadata, field1 in target form, and code2 corresponding to field2 are filled in target form, field1, field2 represent non-fillable format information in metadata and target form, i.e. the same item name, field3 represents the resolved data result, code1, code2 represent fillable data items in metadata and target form, i.e. the specific content under the corresponding item name.
According to the target form filling method based on the data, metadata and function expressions are obtained, the analyzed data result is determined in a function expression analysis mode, namely the dimension related to the target form is determined, the data is screened through the determined dimension, the screened metadata is used as the basis of filling the target form, so that the data calculation amount is effectively reduced, on the basis, the filling of the target form is completed through the preset corresponding relation, the error rate of filling the form is effectively reduced, and due to the fact that the data calculation amount is reduced, the filling efficiency of the target form can be effectively improved, and the use load is reduced.
In an alternative embodiment, to determine a query term statement for filtering metadata, a function expression is parsed to determine a parsed data result, including:
(1) Traversing the function expression, and determining a data structure of the function expression.
In an alternative embodiment, when each function is connected by AND, OR logic within an expression, the data structure includes: the function name and the function content traverse the function expression to determine the data structure of the function expression, comprising:
traversing the function expression, executing stacking when the function expression traverses to the first starting mark, and determining the function name of the function expression.
And when traversing the function expression to the first termination mark, performing stack stripping, and determining the function content of the function expression.
Specifically, the first start mark and the first end mark are used as a pair of symbols, which may be parentheses, square brackets, quotation marks, etc. The function name refers to a context function, a character string interception function, a report number taking function, a call RPC and the like, and the function content refers to parameters which can be calculated by a system.
Specifically, traversing the function expression refers to traversing characters in the character string, recording the traversed characters, executing a stacking operation until traversing to a first starting mark, namely storing function names of the function expression, continuing storing the traversed character string in a stack, and executing a stacking operation until traversing to a first ending mark. This process completes the identification of the function name and the function content, which in turn determines the data structure of the function expression by recursively executing this process. It should be appreciated that the stack is null when no push operation is performed, and after the pop operation is performed.
In an alternative embodiment, when the functions include a connection relationship for nested use in the expression, that is, the data structure includes: the function name, the function content and the sub-function expression, traversing the function expression, determining the data structure of the function expression, comprising:
traversing the function expression, executing stacking when the function expression traverses to the first starting mark, and determining the function name of the function expression.
And when the function expression traverses to the second starting mark, if the stack is not empty, executing the push stack, and determining the function name of the sub-function expression.
The functional content of the sub-functional expression is determined as the functional expression traverses to the second termination mark.
And when traversing the function expression to the first termination mark, performing stack stripping, and determining the function content of the function expression.
Specifically, the first start flag and the second start flag may be the same or different symbols, the first end flag and the second end flag may be the same or different symbols, and the second start flag and the second end flag are used in pairs.
Specifically, the operations of pushing and pulling the second start flag and the second end flag are the same as those of pushing and pulling the first end flag in the above embodiment, and will not be described in detail.
Specifically, when the function expression traverses to the second start mark, if the stack is not empty, it means that when traversing to the second start mark, part of the function name and the function content are already stored in the stack, and the stack is not empty at this time, so that whether the function expression contains the sub-function expression can be judged according to whether the stack is empty.
(2) Based on the data structure, the parsed data results are determined.
Specifically, when the function expression does not contain a subfunction expression, based on the data structure, determining that the parsed data result refers to the data result obtained by the system by calling the function specifically pointed by the function name and calculating by combining the parameters in the function content.
Specifically, when the function expression includes a sub-function expression, determining the parsed data result based on the data structure refers to calculating the result of the basic function in the sub-function expression first, and recursively executing the process until the data result of the function expression is calculated.
By implementing the embodiment, the function expression is analyzed, and the data structure of the function expression is determined in a manner of traversing the function expression, namely, the function name and the function content in the function expression are determined, so that the analyzed data structure is determined through calculation, namely, the query condition statement of the screening metadata is determined, a data basis is provided for the follow-up determination of the target metadata, the screened metadata can be used as the basis for filling the target form, the data calculation amount is effectively reduced, and the filling efficiency of the target form is improved.
In an alternative embodiment, to complete content filling of the target table and ensure correctness of content filling of the target table, completing filling of the target table with the target metadata based on a preset correspondence between the metadata and the target table, including:
and determining the corresponding relation between the target data item number and the first target field based on the preset corresponding relation between the metadata and the target table.
And filling the first target data into the target content based on the corresponding relation between the target data item number and the first target field.
Specifically, in the target form, the non-fillable format information refers to a target data item number, and the fillable data item refers to target content stored in the target data item number. In the target metadata, the non-fillable format information refers to a first target field, and the fillable data item refers to first target data stored in the first target field.
Specifically, the preset correspondence between metadata and the target table refers to a correspondence between the target data item number and the first target field, that is, the content to be filled in by the target data item number in the target table is the content stored in the first target field in the target metadata.
Through implementation of the embodiment, the corresponding relation between the target data item number and the first target field is determined through the preset corresponding relation between the metadata and the target form, so that the first target data is filled into the target content, the correctness of data filling is effectively ensured, the error rate of form filling is reduced, and the calculated amount required by filling the target form is reduced because the target metadata is data obtained by screening the data through the determined dimension, the filling efficiency of the target form is improved, and the use load is reduced.
In an alternative embodiment, if there is sensitive data in the metadata or there is data in the metadata that needs to be read and can be obtained, completing the filling of the target table with the target metadata based on the preset correspondence between the metadata and the target table, including:
and acquiring the user authority.
Based on the user rights, a second target field corresponding to the user rights is determined.
And determining the corresponding relation between the target data item number and the second target field based on the preset corresponding relation between the metadata and the target table.
And filling the second target data into the target content based on the corresponding relation between the target data item number and the second target field.
Specifically, in the target metadata, the non-fillable format information refers to the second target field, and the fillable data item refers to the first target data stored in the second target field.
Specifically, the user permission obtaining means that the user data obtaining permission or the user data reading permission is obtained by obtaining the user data permission table. Determining the second target field corresponding to the user authority refers to determining target metadata that the user can acquire under the corresponding authority. It should be understood that the process of recharging the target data bar with the target content is the same as the above embodiment, and will not be described again.
According to the embodiment, through the preset corresponding relation between the metadata and the target form, the corresponding relation between the target data item number and the second target field is determined, so that the second target data is filled into the target content, the correctness of data filling is effectively ensured, the error rate of form filling is reduced, and because the second target metadata is data which is further screened out through determining the user permission, the filling efficiency of the target form is improved, and meanwhile, only the metadata conforming to the user permission is used as the basis for filling the target form, the safety of the metadata is effectively ensured, and the method is suitable for application scenes with higher requirements on data safety.
In an alternative embodiment, when the target table is related to filling the prediction information, the target table filling method based on the data further comprises:
and inputting the target metadata into the trained training model to obtain target prediction data corresponding to the target metadata.
Specifically, the model training method belongs to a more conventional technology, and is not repeated, for example, the historical filling data of each unit of monthly financial statement is used as a training set to train out a financial prediction model, and when a target form to be filled in by a financial part relates to information such as expected income, expected expenditure and the like, the automatic filling of predicted contents can be realized by inputting target metadata into the trained financial prediction model. In the process, as the target metadata are the filtered data, the data irrelevant to the prediction result in the model calculation process is removed, and the data calculation amount is effectively reduced, so that the target metadata are taken as input, and the filling of the prediction information in the target form is completed.
The embodiment also provides a data-based target table filling device, which is used for realizing the above embodiment and the preferred implementation manner, and is not described in detail. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
The present embodiment provides a target table filling device based on data, as shown in fig. 2, including:
the obtaining module 21 is configured to obtain metadata and a function expression. The specific process may be referred to the related description of step S101 in the above embodiment, and will not be repeated here.
The parsing module 22 is configured to parse the function expression and determine a parsed data result. The specific process may be referred to the related description of step S102 in the above embodiment, and will not be repeated here.
And a screening module 23, configured to screen the target metadata corresponding to the data result based on the data result. The specific process may be referred to the related description of step S103 in the above embodiment, and will not be repeated here.
And the filling module 24 is configured to complete filling of the target table with the target metadata based on a preset correspondence between the metadata and the target table. The specific process may be referred to the related description of step S104 in the above embodiment, and will not be repeated here.
The embodiment of the invention also provides computer equipment, which is provided with the data-based target table filling device shown in the figure 2.
Referring to fig. 3, fig. 3 is a schematic structural diagram of a computer device according to an alternative embodiment of the present invention, and as shown in fig. 3, the computer device includes: one or more processors 10, memory 20, and interfaces for connecting the various components, including high-speed interfaces and low-speed interfaces. The various components are communicatively coupled to each other using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions executing within the computer device, including instructions stored in or on memory to display graphical information of the GUI on an external input/output device, such as a display device coupled to the interface. In some alternative embodiments, multiple processors and/or multiple buses may be used, if desired, along with multiple memories and multiple memories. Also, multiple computer devices may be connected, each providing a portion of the necessary operations (e.g., as a server array, a set of blade servers, or a multiprocessor system). One processor 10 is illustrated in fig. 3.
The processor 10 may be a central processor, a network processor, or a combination thereof. The processor 10 may further include a hardware chip, among others. The hardware chip may be an application specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general-purpose array logic, or any combination thereof.
Wherein the memory 20 stores instructions executable by the at least one processor 10 to cause the at least one processor 10 to perform the methods shown in implementing the above embodiments.
The memory 20 may include a storage program area that may store an operating system, at least one application program required for functions, and a storage data area; the storage data area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, memory 20 may optionally include memory located remotely from processor 10, which may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
Memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk, or solid state disk; the memory 20 may also comprise a combination of the above types of memories.
The computer device also includes a communication interface 30 for the computer device to communicate with other devices or communication networks.
The embodiments of the present invention also provide a computer readable storage medium, and the method according to the embodiments of the present invention described above may be implemented in hardware, firmware, or as a computer code which may be recorded on a storage medium, or as original stored in a remote storage medium or a non-transitory machine readable storage medium downloaded through a network and to be stored in a local storage medium, so that the method described herein may be stored on such software process on a storage medium using a general purpose computer, a special purpose processor, or programmable or special purpose hardware. The storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, a solid state disk or the like; further, the storage medium may also comprise a combination of memories of the kind described above. It will be appreciated that a computer, processor, microprocessor controller or programmable hardware includes a storage element that can store or receive software or computer code that, when accessed and executed by the computer, processor or hardware, implements the methods illustrated by the above embodiments.
Although embodiments of the present invention have been described in connection with the accompanying drawings, various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the invention, and such modifications and variations fall within the scope of the invention as defined by the appended claims.
Claims (10)
1. A method of populating a data-based target table, the method comprising:
acquiring metadata and a function expression;
analyzing the function expression, and determining an analyzed data result;
screening target metadata conforming to the data result based on the data result;
and completing filling of the target table by the target metadata based on the preset corresponding relation between the metadata and the target table.
2. The method of claim 1, wherein said parsing the functional expression to determine parsed data results comprises:
traversing the function expression, and determining a data structure of the function expression;
and determining a resolved data result based on the data structure.
3. The method of claim 2, wherein the data structure comprises: function name and function content;
the traversing the functional expression, determining a data structure of the functional expression, includes:
traversing the function expression, executing stacking when the function expression traverses to a first starting mark, and determining the function name of the function expression;
and when traversing the function expression to the first termination mark, executing pop and determining the function content of the function expression.
4. The method of claim 2, wherein the data structure comprises: function name, function content and sub-function expression;
the traversing the functional expression, determining a data structure of the functional expression, includes:
traversing the function expression, executing stacking when the function expression traverses to a first starting mark, and determining the function name of the function expression;
when traversing the function expression to a second starting mark, if the stack is not empty, executing stacking, and determining the function name of the sub-function expression;
determining the function content of the sub-function expression when the function expression traverses to the second termination mark;
and when traversing the function expression to the first termination mark, executing pop and determining the function content of the function expression.
5. The method of claim 1, wherein the target table comprises: a target data item number, and target content stored in the target data item number, the target metadata including: a first target field, and first target data stored in the first target field;
the filling of the target table with the target metadata based on the preset corresponding relation between the metadata and the target table comprises the following steps:
determining the corresponding relation between the number of the target data item and the first target field based on the preset corresponding relation between the metadata and the target table;
and filling the first target data into the target content based on the corresponding relation between the target data item number and the first target field.
6. The method of claim 1, wherein the target table comprises: a target data item number, and target content stored in the target data item number, the target metadata including: a second target field, and second target data stored in the second target field;
the filling of the target table with the target metadata based on the preset corresponding relation between the metadata and the target table comprises the following steps:
acquiring user rights;
determining the second target field corresponding to the user right based on the user right;
determining the corresponding relation between the target data item number and the second target field based on the preset corresponding relation between the metadata and the target table;
and filling the second target data into the target content based on the corresponding relation between the target data item number and the second target field.
7. The method according to any one of claims 1 to 6, further comprising, after the completion of the target table filling with the target metadata based on the preset correspondence of the metadata with the target table:
and inputting the target metadata into a trained training model to obtain target prediction data corresponding to the target metadata.
8. A data-based object table filling apparatus, the apparatus comprising:
the acquisition module is used for acquiring the metadata and the function expression;
the analysis module is used for analyzing the function expression and determining an analyzed data result;
the screening module is used for screening target metadata which is consistent with the data result based on the data result;
and the filling module is used for completing filling of the target table by the target metadata based on the preset corresponding relation between the metadata and the target table.
9. A computer device, comprising:
a memory and a processor communicatively coupled to each other, the memory having stored therein computer instructions that, upon execution, perform the data-based object table population method of any of claims 1 to 7.
10. A computer-readable storage medium having stored thereon computer instructions for causing a computer to perform the data-based object table population method of any one of claims 1 to 7.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202311193047.XA CN117236303A (en) | 2023-09-15 | 2023-09-15 | Data-based target form filling method and device |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202311193047.XA CN117236303A (en) | 2023-09-15 | 2023-09-15 | Data-based target form filling method and device |
Publications (1)
Publication Number | Publication Date |
---|---|
CN117236303A true CN117236303A (en) | 2023-12-15 |
Family
ID=89096108
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202311193047.XA Pending CN117236303A (en) | 2023-09-15 | 2023-09-15 | Data-based target form filling method and device |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN117236303A (en) |
-
2023
- 2023-09-15 CN CN202311193047.XA patent/CN117236303A/en active Pending
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US8626702B2 (en) | Method and system for validation of data extraction | |
CN110443552B (en) | Method and device for automatically transmitting product main data information | |
US20100280990A1 (en) | Etl for process data warehouse | |
US11693912B2 (en) | Adapting database queries for data virtualization over combined database stores | |
CN108628748B (en) | Automatic test management method and automatic test management system | |
CN111367976B (en) | Method and device for exporting EXCEL file data based on JAVA reflection mechanism | |
US11762920B2 (en) | Composite index on hierarchical nodes in the hierarchical data model within a case model | |
CN106293891B (en) | Multidimensional investment index monitoring method | |
CN111400288A (en) | Data quality inspection method and system | |
CN112287013A (en) | Data conversion method and adapter | |
CN110889272A (en) | Data processing method, device, equipment and storage medium | |
CN109636303B (en) | Storage method and system for semi-automatically extracting and structuring document information | |
CN112860581B (en) | Execution method, device, equipment and storage medium of test case | |
US20170132195A1 (en) | Method and Apparatus Providing Contextual Suggestion in Planning Spreadsheet | |
CN112395339B (en) | Intersystem data admission verification method, device, computer equipment and storage medium | |
CN113608955A (en) | Log recording method, device, equipment and storage medium | |
CN111198678A (en) | Method and device for generating GraphQL front-end operation interface | |
CN115329011A (en) | Data model construction method, data query method, data model construction device and data query device, and storage medium | |
CN113868219A (en) | Method and device for migrating account set data, electronic equipment and computer storage medium | |
CN116227454A (en) | Universal automatic report generation method and system | |
CN117236303A (en) | Data-based target form filling method and device | |
CN114880387A (en) | Data integration script generation method and device, storage medium and electronic equipment | |
US20230195792A1 (en) | Database management methods and associated apparatus | |
CN114298749A (en) | Access method, device and medium for cost data source | |
CN109783105B (en) | Coding statistical method, equipment, storage medium and device of enterprise service platform |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination |