CN116485308A - Method and device for generating auditing rule based on bill returning reason - Google Patents
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Abstract
The invention provides a method, a system, equipment and a storage medium for generating an audit rule based on a bill returning reason, wherein the method comprises the following steps: clustering and grouping the receipts of the receipt, and analyzing the reason of the receipt after clustering and grouping; and generating an auditing rule according to the return reason, and applying the auditing rule to the auditing of the bill. According to the invention, the intelligent auditing rules are summarized through the clustering analysis of the reason of the receipt withdrawal of a large number of documents, the detection range of intelligent auditing is perfected, the dependence on manual auditing during the approval is reduced, the accuracy of the result is ensured through the conclusion obtained through the classification and analysis of a large number of data, different auditing rules are added to different business scenes in a more targeted manner by classifying different documents, and the auditing detection range is enlarged.
Description
Technical Field
The present invention relates to the field of computer applications, and in particular, to a method, system, device, and storage medium for generating an audit rule based on a document return reason.
Background
In the current ERP (Enterprise Resource Planning ) system, a large number of bill flows occur, the number of bills to be examined and approved is also not counted, the traditional examination and approval links are all problems that people can identify the bill filling, the bill information is easy to miss and see, the pressure of an auditor is relieved due to the fact that the existing intelligent examination and approval rule cannot contain all problem scenes, the fact that a large number of returned bills still need to be processed even if the introduced intelligent examination and approval is conducted is caused, repeated submission and return of the bills in the examination and approval process seriously affect the efficiency of the whole examination and approval, and a large amount of time is lost to conduct repeated work.
Disclosure of Invention
In view of the above, an object of the embodiments of the present invention is to provide a method, a system, a computer device, and a computer readable storage medium for generating an audit rule based on a document return reason, which summarize the commonality of the return reason from mass data, perfect an intelligent audit check rule according to actual data, assist auditors to complete pre-audit of documents, reduce the content that the auditors need to audit, reduce workload of the auditors, thereby improving audit efficiency, reducing the degradation of audit quality caused by missed audit and false audit, inputting perfect intelligent audit rules into the constraint of subsequent document-making people, improving data accuracy, perfecting according to actual use conditions, and facilitating realization of intelligent checking, and reducing manual audit burden.
Based on the above object, an aspect of the embodiments of the present invention provides a method for generating an audit rule based on a reason for returning a document, including the following steps: clustering and grouping the receipts of the receipt, and analyzing the reason of the receipt after clustering and grouping; and generating an auditing rule according to the return reason, and applying the auditing rule to the auditing of the bill.
In some embodiments, the clustering the documents to be returned includes: and acquiring the bill major class and the bill type on the bill, and primarily classifying the bill according to the bill major class and the bill type.
In some embodiments, the clustering the documents to be returned includes: and acquiring the reason of returning the bill on the bill, and classifying the primarily classified bill according to the reason of returning the bill.
In some embodiments, the classifying the primarily classified documents according to the return reason includes: converting the reason of returning the list into corresponding data, and selecting three data as an initial center; dividing each rest of data into a group nearest to the corresponding initial center in turn; and responsive to the data grouping being completed, re-computing the current center point of each group and re-dividing each data according to the current center point until the current center point is no longer changed.
In some embodiments, the sequentially dividing each of the remaining data into a group nearest to the corresponding initial center comprises: the Manhattan cluster distances of the data to the three initial centers are calculated, and the data are divided into groups of initial centers corresponding to the minimum Manhattan cluster distances.
In some embodiments, the recalculating the current center point for each group comprises: the abscissas of the data of each group are summed separately and averaged separately to obtain the abscissas of the current center point in the corresponding group.
In some embodiments, the analyzing the reason for the drop back after clustering the packets includes: semantic analysis is carried out on the order return reasons in each group to extract the same points, and corresponding problems are summarized according to the same points; and determining the content to be checked according to the problem, and carrying out standardization processing on the content.
In another aspect of the embodiment of the present invention, a system for generating an audit rule based on a document return reason is provided, including: the grouping module is configured to group the bills of the return bill in a clustering way and analyze the reason of the return bill after the clustering grouping; and the execution module is configured to generate an auditing rule according to the return reason and apply the auditing rule to the auditing of the bill.
In yet another aspect of the embodiment of the present invention, there is also provided a computer apparatus, including: at least one processor; and a memory storing computer instructions executable on the processor, which when executed by the processor, perform the steps of the method as above.
In yet another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium storing a computer program which, when executed by a processor, implements the method steps as described above.
The invention has the following beneficial technical effects: summarizing and summarizing the commonalities of the reason of the return bill from mass data, perfecting an intelligent audit and check rule according to actual data, assisting an audit person to finish pre-check on the bill, reducing the content required to be checked by the audit person, and reducing the workload of the audit person, thereby improving the checking efficiency, reducing the drop of the checking quality caused by missed checking and wrong checking, inputting the perfect intelligent audit rule into the follow-up constraint on the bill making person, improving the data accuracy, perfecting according to the actual use condition, facilitating the realization of intelligent report and relieving the manual audit burden.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are necessary for the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention and that other embodiments may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of an embodiment of a method for generating audit rules based on document drop reasons provided by the present invention;
FIG. 2 is a schematic diagram of an embodiment of a system for generating audit rules based on document drop reasons provided by the present invention;
FIG. 3 is a schematic hardware architecture diagram of an embodiment of a computer device for generating audit rules based on document drop reasons provided by the present invention;
fig. 4 is a schematic diagram of an embodiment of a computer storage medium for generating an audit rule based on a document drop reason provided by the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the following embodiments of the present invention will be described in further detail with reference to the accompanying drawings.
It should be noted that, in the embodiments of the present invention, all the expressions "first" and "second" are used to distinguish two entities with the same name but different entities or different parameters, and it is noted that the "first" and "second" are only used for convenience of expression, and should not be construed as limiting the embodiments of the present invention, and the following embodiments are not described one by one.
In a first aspect of the embodiment of the invention, an embodiment of a method for generating an audit rule based on a document return reason is provided. Fig. 1 is a schematic diagram of an embodiment of a method for generating an audit rule based on a document return reason. As shown in fig. 1, the embodiment of the present invention includes the following steps:
s1, clustering and grouping the receipts of the receipt, and analyzing the reason of the receipt after clustering and grouping; and
s2, generating an auditing rule according to the return reason, and applying the auditing rule to the auditing of the bill.
The embodiment of the invention can be used in an ERP intelligent account reporting system, and the reasons for returning the bill are summarized through sorting and sorting the reasons for returning the bill of the historical bill, and then the reasons are further processed into intelligent auditing rules. The implementation of the embodiment of the invention can generate the checking rule according to the past data, thereby reducing the problems of overlong flow operation time and slow reimbursement process caused by repeated withdrawal of the bill in the approval process, and simultaneously reducing the times of repeated modification of the bill by a bill producer, so that the bill producer can check and modify filling problems before submitting the bill, reducing reimbursement time cost and improving reimbursement efficiency.
Clustering and grouping the receipts of the receipt, and analyzing the reason of the receipt after clustering and grouping.
In some embodiments, the clustering the documents to be returned includes: and acquiring the bill major class and the bill type on the bill, and primarily classifying the bill according to the bill major class and the bill type. Different bill major classes and different bill types relate to different services, the generated bill withdrawal reasons are different in emphasis, the bill major classes and the bill types of the bills are extracted, the service field is divided, and the accuracy of acquiring the bill withdrawal reasons is further improved. Main information on the receipt is acquired: the general form class of the bill, the bill type FormTYpeID and the reason for returning the bill, namely, the rebackRefraction; the bill major class and the bill type are primary classification factors, and the data complexity can be effectively reduced by dividing from the service field, so that the follow-up analysis is convenient.
In some embodiments, the clustering the documents to be returned includes: and acquiring the reason of returning the bill on the bill, and classifying the primarily classified bill according to the reason of returning the bill.
In some embodiments, the classifying the primarily classified documents according to the return reason includes: converting the reason of returning the list into corresponding data, and selecting three data as an initial center; dividing each rest of data into a group nearest to the corresponding initial center in turn; and responsive to the data grouping being completed, re-computing the current center point of each group and re-dividing each data according to the current center point until the current center point is no longer changed.
In some embodiments, the sequentially dividing each of the remaining data into a group nearest to the corresponding initial center comprises: the Manhattan cluster distances of the data to the three initial centers are calculated, and the data are divided into groups of initial centers corresponding to the minimum Manhattan cluster distances.
The embodiment of the invention adopts a K-means algorithm to cluster and group the data, and the implementation steps of the K-means algorithm are as follows: a. three data are selected as initial centers; b. calculating Manhattan clustering distances from the rest data to the three centers; c. classifying the data closest to the center point into one type, and storing the data into the same group; d. classifying all data into categories and storing the categories into corresponding groups; e. after the data are all grouped, calculating a center point again; f. the b, c, d, e steps are repeated with the recalculated center point until no more changes in the center point occur.
In some embodiments, the recalculating the current center point for each group comprises: the abscissas of the data of each group are summed separately and averaged separately to obtain the abscissas of the current center point in the corresponding group.
In some embodiments, the analyzing the reason for the drop back after clustering the packets includes: semantic analysis is carried out on the order return reasons in each group to extract the same points, and corresponding problems are summarized according to the same points; and determining the content to be checked according to the problem, and carrying out standardization processing on the content.
Analyzing the reason of the single withdrawal after clustering grouping: a. semantic analysis is carried out on the order-return reason data in each group, the same points are extracted, and the problem is summarized; b. the content requiring the increase of the inspection is extracted from the problem causes outlined in each group. Data information standardization: a. carrying out standardized processing on the summarized content needing to be added with the inspection, and describing the inspection content by using a technical term; b. the inspection rules are re-described from a business perspective to form an analysis report.
And generating an auditing rule according to the return reason, and applying the auditing rule to the auditing of the bill. And according to the obtained report, the intelligent auditing rule is summarized and put into use.
According to the embodiment of the invention, based on a data mining algorithm, the intelligent auditing rule is summarized by carrying out cluster analysis on the reason of returning a large number of bills, the detection range of intelligent auditing is perfected, and the dependence on manual auditing during approval is reduced; the embodiment of the invention ensures the accuracy of the result through the conclusion obtained from the classification and analysis of a large amount of data, separates different bill major categories, adds different auditing rules to different business scenes more pertinently, and expands auditing detection range. The invention can effectively reduce repeated submitting and returning times of the bill in the approval process, improves the bill circulation efficiency, ensures the accuracy of filling data when a bill making person makes the bill, can perfects the intelligent auditing and checking rule according to the actual use scene, reduces the effort spent in manual auditing, saves the time cost and has good application prospect.
It should be noted that, in the embodiments of the method for generating the auditing rule based on the document returning reason, the steps may be intersected, replaced, added and deleted, so that the method for generating the auditing rule based on the document returning reason by using these reasonable permutation and combination transformations should also belong to the protection scope of the present invention, and should not limit the protection scope of the present invention to the embodiments.
Based on the above object, in a second aspect of the embodiment of the present invention, a system for generating an audit rule based on a reason for returning a document is provided. As shown in fig. 2, the system 200 includes the following modules: the grouping module is configured to group the bills of the return bill in a clustering way and analyze the reason of the return bill after the clustering grouping; and the execution module is configured to generate an auditing rule according to the return reason and apply the auditing rule to the auditing of the bill.
In some embodiments, the grouping module is configured to: and acquiring the bill major class and the bill type on the bill, and primarily classifying the bill according to the bill major class and the bill type.
In some embodiments, the grouping module is configured to: and acquiring the reason of returning the bill on the bill, and classifying the primarily classified bill according to the reason of returning the bill.
In some embodiments, the grouping module is configured to: converting the reason of returning the list into corresponding data, and selecting three data as an initial center; dividing each rest of data into a group nearest to the corresponding initial center in turn; and responsive to the data grouping being completed, re-computing the current center point of each group and re-dividing each data according to the current center point until the current center point is no longer changed.
In some embodiments, the grouping module is configured to: the Manhattan cluster distances of the data to the three initial centers are calculated, and the data are divided into groups of initial centers corresponding to the minimum Manhattan cluster distances.
In some embodiments, the grouping module is configured to: the abscissas of the data of each group are summed separately and averaged separately to obtain the abscissas of the current center point in the corresponding group.
In some embodiments, the grouping module is configured to: semantic analysis is carried out on the order return reasons in each group to extract the same points, and corresponding problems are summarized according to the same points; and determining the content to be checked according to the problem, and carrying out standardization processing on the content.
In view of the above object, a third aspect of the embodiments of the present invention provides a computer device, including: at least one processor; and a memory storing computer instructions executable on the processor, the instructions being executable by the processor to perform the steps of: s1, clustering and grouping the receipts of the receipt, and analyzing the reason of the receipt after clustering and grouping; s2, generating an auditing rule according to the return reason, and applying the auditing rule to the auditing of the bill.
In some embodiments, the clustering the documents to be returned includes: and acquiring the bill major class and the bill type on the bill, and primarily classifying the bill according to the bill major class and the bill type.
In some embodiments, the clustering the documents to be returned includes: and acquiring the reason of returning the bill on the bill, and classifying the primarily classified bill according to the reason of returning the bill.
In some embodiments, the classifying the primarily classified documents according to the return reason includes: converting the reason of returning the list into corresponding data, and selecting three data as an initial center; dividing each rest of data into a group nearest to the corresponding initial center in turn; and responsive to the data grouping being completed, re-computing the current center point of each group and re-dividing each data according to the current center point until the current center point is no longer changed.
In some embodiments, the sequentially dividing each of the remaining data into a group nearest to the corresponding initial center comprises: the Manhattan cluster distances of the data to the three initial centers are calculated, and the data are divided into groups of initial centers corresponding to the minimum Manhattan cluster distances.
In some embodiments, the recalculating the current center point for each group comprises: the abscissas of the data of each group are summed separately and averaged separately to obtain the abscissas of the current center point in the corresponding group.
In some embodiments, the analyzing the reason for the drop back after clustering the packets includes: semantic analysis is carried out on the order return reasons in each group to extract the same points, and corresponding problems are summarized according to the same points; and determining the content to be checked according to the problem, and carrying out standardization processing on the content.
Fig. 3 is a schematic hardware structure of an embodiment of the computer device for generating an audit rule based on a document return reason according to the present invention.
Taking the example of the device shown in fig. 3, a processor 301 and a memory 302 are included in the device.
The processor 301 and the memory 302 may be connected by a bus or otherwise, for example in fig. 3.
The memory 302 is used as a non-volatile computer readable storage medium, and may be used to store a non-volatile software program, a non-volatile computer executable program, and a module, such as program instructions/modules corresponding to a method for generating an audit rule based on a document drop reason in the embodiments of the present application. The processor 301 executes various functional applications of the server and data processing, i.e., implements a method of generating an audit rule based on a document drop-out reason, by running non-volatile software programs, instructions, and modules stored in the memory 302.
Memory 302 may include a storage program area that may store an operating system, at least one application program required for functionality, and a storage data area; the storage data area may store data created according to the use of a method of generating an audit rule based on a document drop-out reason, and the like. In addition, memory 302 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, memory 302 may optionally include memory located remotely from processor 301, which may be connected to the local module 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.
One or more computer instructions 303 corresponding to a method of generating an audit rule based on a document drop reason are stored in the memory 302, and when executed by the processor 301, perform the method of generating an audit rule based on a document drop reason in any of the method embodiments described above.
Any embodiment of the computer device executing the method for generating the auditing rule based on the reason of the receipt return can achieve the same or similar effect as any corresponding embodiment of the method.
The invention also provides a computer readable storage medium storing a computer program which when executed by a processor performs a method of generating audit rules based on document drop-out reasons.
FIG. 4 is a schematic diagram of an embodiment of a computer storage medium for generating audit rules based on document drop-out reasons according to the present invention. Taking a computer storage medium as shown in fig. 4 as an example, the computer readable storage medium 401 stores a computer program 402 that when executed by a processor performs the above method.
Finally, it should be noted that, as will be appreciated by those skilled in the art, implementing all or part of the above-described embodiments of the method may be implemented by a computer program to instruct related hardware, and the program of the method for generating the audit rule based on the reason of document return may be stored in a computer readable storage medium, where the program may include the steps of the embodiments of the methods described above when executed. The storage medium of the program may be a magnetic disk, an optical disk, a read-only memory (ROM), a random-access memory (RAM), or the like. The computer program embodiments described above may achieve the same or similar effects as any of the method embodiments described above.
The foregoing is an exemplary embodiment of the present disclosure, but it should be noted that various changes and modifications could be made herein without departing from the scope of the disclosure as defined by the appended claims. The functions, steps and/or actions of the method claims in accordance with the disclosed embodiments described herein need not be performed in any particular order. Furthermore, although elements of the disclosed embodiments may be described or claimed in the singular, the plural is contemplated unless limitation to the singular is explicitly stated.
It should be understood that as used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly supports the exception. It should also be understood that "and/or" as used herein is meant to include any and all possible combinations of one or more of the associated listed items.
The foregoing embodiment of the present invention has been disclosed with reference to the number of embodiments for the purpose of description only, and does not represent the advantages or disadvantages of the embodiments.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program for instructing relevant hardware, and the program may be stored in a computer readable storage medium, where the storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
Those of ordinary skill in the art will appreciate that: the above discussion of any embodiment is merely exemplary and is not intended to imply that the scope of the disclosure of embodiments of the invention, including the claims, is limited to such examples; combinations of features of the above embodiments or in different embodiments are also possible within the idea of an embodiment of the invention, and many other variations of the different aspects of the embodiments of the invention as described above exist, which are not provided in detail for the sake of brevity. Therefore, any omission, modification, equivalent replacement, improvement, etc. of the embodiments should be included in the protection scope of the embodiments of the present invention.
Claims (10)
1. A method for generating an audit rule based on a bill returning reason is characterized by comprising the following steps:
clustering and grouping the receipts of the receipt, and analyzing the reason of the receipt after clustering and grouping; and
and generating an auditing rule according to the return reason, and applying the auditing rule to the auditing of the bill.
2. The method for generating an audit rule based on document drop-out reasons according to claim 1 wherein clustering the drop-out documents comprises:
and acquiring the bill major class and the bill type on the bill, and primarily classifying the bill according to the bill major class and the bill type.
3. The method for generating an audit rule based on document drop-out reasons according to claim 2 wherein clustering the drop-out documents comprises:
and acquiring the reason of returning the bill on the bill, and classifying the primarily classified bill according to the reason of returning the bill.
4. A method of generating audit rules based on document drop-out reasons according to claim 3 wherein classifying the initially classified documents according to drop-out reasons includes:
converting the reason of returning the list into corresponding data, and selecting three data as an initial center;
dividing each rest of data into a group nearest to the corresponding initial center in turn; and
and in response to the data grouping being completed, re-computing the current center point of each group, and dividing each data again according to the current center point until the current center point is unchanged.
5. The method of claim 4, wherein the sequentially dividing each remaining data into a group nearest to the corresponding initial center comprises:
the Manhattan cluster distances of the data to the three initial centers are calculated, and the data are divided into groups of initial centers corresponding to the minimum Manhattan cluster distances.
6. The method of generating audit rules based on document drop out reasons according to claim 4 wherein the recalculating the current center point for each group includes:
the abscissas of the data of each group are summed separately and averaged separately to obtain the abscissas of the current center point in the corresponding group.
7. The method for generating audit rules based on document drop-out reasons according to claim 1 wherein said analyzing the clustered grouping of drop-out reasons comprises:
semantic analysis is carried out on the order return reasons in each group to extract the same points, and corresponding problems are summarized according to the same points; and
and determining the content to be checked according to the problem, and carrying out standardization processing on the content.
8. A system for generating audit rules based on document drop-out reasons, comprising:
the grouping module is configured to group the bills of the return bill in a clustering way and analyze the reason of the return bill after the clustering grouping; and
and the execution module is configured to generate an auditing rule according to the return reason and apply the auditing rule to the auditing of the bill.
9. A computer device, comprising:
at least one processor; and
a memory storing computer instructions executable on the processor, which when executed by the processor, perform the steps of the method of any one of claims 1-7.
10. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method of any one of claims 1-7.
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