Data processing method and device, electronic equipment and storage medium

Abstract

The invention provides a data processing method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining an item classification mark of each first classification item which corresponds to an item parameter; a merging rule corresponding to each second classification item is obtained, the classification granularity of the first classification item is finer than that of the second classification item, and the merging rule is used for indicating a merging mapping relation between the second classification item and the item classification mark; and merging the item parameters of the first classification items to the corresponding second classification items based on the merging mapping relation indicated by the merging rule. Through the item classification mark and the merging rule, the second classification item to which the first classification item belongs can be determined, so that the item parameters of the first classification item can be automatically merged to the corresponding second classification item, and the merging efficiency is relatively high.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a data processing method, device, electronic device and storage medium. Background Art

[0002] In many fields, actual application scenarios have different requirements for the level of classification detail (i.e., classification granularity). In order to flexibly respond to these diverse requirements, classification items usually need to be flexibly converted and merged between different classification granularities to ensure fast data retrieval, efficient statistics, and in-depth analysis. However, the current mainstream merging method is to manually construct mapping relationships between classification items of different granularities. This process is not only time-consuming and labor-intensive, but also greatly reduces overall efficiency. Summary of the invention

[0003] The present application aims to solve one of the technical problems in the related art at least to some extent.

[0004] To this end, a first aspect of the present application is to propose a data processing method.

[0005] A second aspect of the present application is to provide a data processing device.

[0006] A third aspect of the present application is to provide an electronic device.

[0007] A fourth aspect of the present application is to provide a non-transitory computer-readable storage medium.

[0008] A fifth aspect of the present application is to provide a computer program product.

[0009] To achieve the above-mentioned purpose, the first embodiment of the present application proposes a data processing method, including:

[0010] Obtaining an item classification mark of each first classification item, wherein the first classification item corresponds to an item parameter;

[0011] Acquire a merging rule corresponding to each second classification item, wherein the classification granularity of the first classification item is finer than that of the second classification item, and the merging rule is used to indicate a merging mapping relationship between the second classification item and the item classification mark;

[0012] Based on the merging mapping relationship indicated by the merging rule, the item parameters of each of the first classification items are merged into the corresponding second classification items.

[0013] To achieve the above-mentioned purpose, a second aspect of the present application provides a data processing device, including:

[0014] A first acquisition module, used to acquire a project classification mark of each first classification project, wherein the first classification project corresponds to a project parameter;

[0015] A second acquisition module is used to acquire a merging rule corresponding to each second classification item, wherein the classification granularity of the first classification item is finer than that of the second classification item, and the merging rule is used to indicate a merging mapping relationship between the second classification item and the item classification mark;

[0016] A merging module is used to merge the item parameters of each first classification item into the corresponding second classification item based on the merging mapping relationship indicated by the merging rule.

[0017] To achieve the above-mentioned purpose, the third aspect of the present application provides an electronic device, including:

[0018] A processor, and a memory communicatively connected to the processor;

[0019] The memory stores computer-executable instructions;

[0020] The processor executes the computer-executable instructions stored in the memory to implement the data processing method described in the first aspect.

[0021] In order to achieve the above-mentioned objectives, the fourth aspect of the present application proposes a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable a computer to execute the data processing method described in the first aspect.

[0022] In order to achieve the above-mentioned purpose, the fifth aspect of the present application proposes a computer program product, including a computer program, which implements the data processing method described in the first aspect when executed by a processor.

[0023] The present application obtains the project classification mark of each first classification project, wherein the first classification project corresponds to a project parameter; obtains the merging rule corresponding to each second classification project, wherein the classification granularity of the first classification project is finer than that of the second classification project, and the merging rule is used to indicate the merging mapping relationship between the second classification project and the project classification mark; based on the merging mapping relationship indicated by the merging rule, the project parameters of each first classification project are merged into the corresponding second classification project. Through the project classification mark and the merging rule, the second classification project to which the first classification project belongs can be determined, and then the project parameters of the first classification project can be automatically merged into the corresponding second classification project, and the merging efficiency is high.

[0024] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0026] Figure 1 A flowchart of a data processing method provided in an embodiment of the present application;

[0027] Figure 2 A flowchart of another data processing method provided in an embodiment of the present application;

[0028] Figure 3 A flowchart of another data processing method provided in an embodiment of the present application;

[0029] Figure 4 A flowchart of another data processing method provided in an embodiment of the present application;

[0030] Figure 5 A schematic diagram of the structure of a data processing device provided in an embodiment of the present application;

[0031] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0033] It should be noted that the acquisition, transmission, storage, use, and processing of data (including but not limited to user device information, user personal information, etc.) in the technical solution of this application comply with the relevant provisions of relevant laws and regulations.

[0034] A data processing method, device, electronic device, and storage medium according to an embodiment of the present application are described below with reference to the accompanying drawings.

[0035] Embodiment 1:

[0036] Figure 1 A flow chart of a data processing method provided in an embodiment of the present application. Figure 1 As shown, the method comprises the following steps:

[0037] Step 101, obtaining the project classification mark of each first classification project, wherein the first classification project corresponds to a project parameter.

[0038] In an embodiment of the present application, the first classification project may refer to a classification project obtained by dividing the project based on the first classification granularity. The project classification mark of the first classification project is used to indicate the project category of the first classification project. The first classification projects with the same project category have the same project classification marks.

[0039] As an example, the project classification mark may be manually configured, wherein the project classification mark may refer to characters such as numbers and letters.

[0040] As an example, the first classification item may refer to an accounting subject, and the item parameter corresponding to the accounting subject refers to the account balance. Each accounting subject corresponds to a debit balance and a credit balance, and the netting operation is performed based on the debit balance and the credit balance, that is, the debit balance minus the credit balance to obtain the account balance. See Table 1, which shows some accounting subjects and the item classification marks corresponding to the accounting subjects:

[0041] Project Code Project Name Project classification mark 000001 Original value of houses and buildings A 000002 Original value of computer equipment A 000003 Original value of transportation equipment A 000004 Original value of office equipment A 100001 Original value of patent B 100002 Original value of copyright B 100003 Original value of trademark rights B

[0042] Table 1

[0043] Step 102, obtaining merging rules corresponding to each second classification item, wherein the classification granularity of the first classification item is finer than that of the second classification item, and the merging rules are used to indicate the merging mapping relationship between the second classification item and the item classification mark.

[0044] In an embodiment of the present application, the second classification item may refer to a classification item obtained by dividing the item based on a second classification granularity, where the second classification granularity is coarser than the first classification granularity; the merging rule corresponding to the second classification item may refer to a rule pre-configured manually.

[0045] As an example, the second classification item may refer to a report item, such as fixed assets, intangible assets, other assets, other liabilities, etc. See Table 2, which shows the merging rules corresponding to some report items:

[0046] Report Items Merge rules Fixed assets The balance of the account marked as A in the project classification is recorded in Intangible assets The balance of the account marked as B in the project classification is recorded in

[0047] Table 2

[0048] Based on Table 2, it can be seen that there is a merge mapping relationship between fixed assets and project classification mark A, and there is a merge mapping relationship between intangible assets and project classification mark B.

[0049] Step 103: Based on the merging mapping relationship indicated by the merging rule, the item parameters of each first classification item are merged into the corresponding second classification item.

[0050] In the embodiment of the present application, based on the item classification mark of the first classification item and the merging rule of the second classification item, the second classification item to which each first classification item belongs is determined, and the item parameters of each first classification item are included in the corresponding second classification item.

[0051] The project classification mark of the first classification project may be matched with the project classification mark in the merging rule of the second classification project, and the second classification project corresponding to the matched merging rule is the second classification project to which the first classification project belongs.

[0052] The present application obtains the project classification mark of each first classification project, wherein the first classification project corresponds to a project parameter; obtains the merging rule corresponding to each second classification project, wherein the classification granularity of the first classification project is finer than that of the second classification project, and the merging rule is used to indicate the merging mapping relationship between the second classification project and the project classification mark; based on the merging mapping relationship indicated by the merging rule, the project parameters of each first classification project are merged into the corresponding second classification project. Through the project classification mark and the merging rule, the second classification project to which the first classification project belongs can be determined, and then the project parameters of the first classification project can be automatically merged into the corresponding second classification project, and the merging efficiency is high.

[0053] Embodiment 2:

[0054] Figure 2 A flowchart of a data processing method provided by another embodiment of the present application is shown as follows: Figure 2 As shown, the method comprises the following steps:

[0055] Step 201, obtaining description information of each first classification item, the description information including item attribute information, item code and item name.

[0056] In the embodiment of the present application, the project attribute information may refer to business attribute information, and the project code may refer to the project number of the first classification project. Wherein, when the first classification project is an accounting subject, the business attribute information, project code and project name of the accounting subject may be obtained from the chart of accounting subjects.

[0057] Step 202: Determine a project classification mark of each first classification project based on at least one of the project attribute information, the project code and the project name.

[0058] As an example, the project classification mark is determined based on any one of the project attribute information, the project code and the project name.

[0059] As another example, a project classification mark is determined based on project attribute information, project code and project name. Specifically, for any first classification project, the first classification project is classified based on the project attribute information to obtain a first classification mark; the target code value at the set position in the project code is extracted, and based on the first set mapping relationship between the code value and the classification mark, the second classification mark corresponding to the target code value is determined; the keywords in the project name are extracted, and the target keyword set to which the keywords belong is determined; based on the second set mapping relationship between the keyword set and the classification mark, the third classification mark corresponding to the target keyword set is determined; based on the first classification mark, the second classification mark and the third classification mark, the project classification mark of the first classification project is determined.

[0060] As a possible implementation manner, the project attribute information may be input into a project classification model to obtain a first classification label output by the project classification model.

[0061] As another possible implementation, when the first classification item is an accounting account, the asset type corresponding to the accounting account is determined based on the business attribute information of the accounting account, and the first classification mark is determined according to the asset type. For example, from the perspective of business attributes, the original value of houses and buildings, the original value of computer equipment, the original value of transportation equipment, and the original value of office machinery and equipment belong to fixed asset accounts, the original value of patents, copyrights, and trademarks belong to intangible asset accounts, and some accounting accounts belong to asset transfer accounts.

[0062] Among them, the set position in the project code can refer to the first N positions in the project code. Taking the project code in Table 1 as an example, the set position can refer to the first 4 positions in the project code. Specifically, the target code value corresponding to the original value of houses and buildings, the original value of computer equipment, the original value of transportation equipment, and the original value of office machinery and equipment in Table 1 is 0000. Based on the first set mapping relationship, the project classification mark corresponding to 0000 is A; the target code value corresponding to the original value of patent rights, the original value of copyrights, and the original value of trademark rights is 1000. Based on the first set mapping relationship, the project classification mark corresponding to 1000 is B.

[0063] Among them, the keywords in the project name refer to words that can reflect the project category of the first classification project. The keywords in the original value of houses and buildings in Table 1 can refer to houses and buildings, and the keywords in the original value of computer equipment can refer to computer equipment. The keyword set includes at least one keyword, and each keyword set corresponds to a project classification mark. Based on the second set mapping relationship, the project classification mark corresponding to each keyword set can be determined. For example, a keyword set includes houses, buildings, computer equipment, transportation equipment, office machinery and equipment, etc., and the corresponding project classification is marked as A. Another keyword set includes patents, copyrights and trademarks, etc., and the corresponding project classification is marked as B. It should be noted that the first set mapping relationship, the second set mapping relationship and the keyword set can be pre-configured.

[0064] In order to ensure the accuracy of the project classification mark, the mark that appears most frequently among the first classification mark, the second classification mark and the third classification mark can be used as the final project classification mark.

[0065] Combining the project attribute information, project code and project name can more comprehensively reflect the essential characteristics of the first category projects. Therefore, classifying and marking the first category projects through the project attribute information, project code and project name can further improve the accuracy of the project classification marking.

[0066] Step 203: Obtain the merging rules corresponding to each second classification item.

[0067] Step 204 , based on the merging mapping relationship indicated by the merging rule, merge the item parameters of each first classification item into the corresponding second classification item.

[0068] It should be noted that the execution process of step 203 and step 204 can be implemented in any way in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be repeated.

[0069] The present application obtains description information of each first classification project, the description information includes project attribute information, project code and project name; based on at least one of the project attribute information, project code and project name, determines the project classification mark of each first classification project; obtains the merging rules corresponding to each second classification project; based on the merging mapping relationship indicated by the merging rules, merges the project parameters of each first classification project into the corresponding second classification project. The project attribute information, project code and project name can reflect the essential characteristics of the first classification project to a certain extent. Therefore, based on at least one of the project attribute information, project code and project name, determining the project classification mark of the first classification project can not only realize the automatic marking of the first classification project and reduce the subjectivity of human judgment, but also ensure the accuracy of the project classification mark.

[0070] Embodiment three:

[0071] Figure 3 A flowchart of a data processing method provided by another embodiment of the present application is shown as follows: Figure 3 As shown, the method comprises the following steps:

[0072] Step 301, obtaining the item classification mark of each first classification item.

[0073] Step 302: Obtain the merging rules corresponding to each second classification item.

[0074] Step 303: for any project classification mark, according to the set parameter merging logic, merge the project parameters of each first classification project under the project classification mark to obtain the target project parameters.

[0075] The set parameter merging logic is used to indicate how to merge the project parameters of the first classification project. For example, the parameter merging logic may refer to project parameter addition logic, project parameter subtraction logic, etc.

[0076] Step 304: Search the merging rules corresponding to the second classification items for a target merging rule that matches the item classification tag.

[0077] Among them, each project classification tag corresponds to a matching target merging rule.

[0078] As an example, for any project classification mark, the project classification mark is matched with the project classification marks included in each merging rule to obtain the target merging rule matched by the project classification mark.

[0079] As another example, when the first classification item is an accounting subject, the second classification item is a report item, the item parameter is an account balance, and the target item parameter is a summary amount, rule matching is performed based on the item classification mark; in response to matching a merge rule, the matched merge rule is used as the target merge rule; in response to matching multiple merge rules, the summary amount is compared with a set amount threshold to obtain an actual amount comparison result; in combination with the actual amount comparison result and the amount comparison result included in the found merge rule, the target merge rule is determined among the multiple merge rules.

[0080] When the first classification items are accounting items and the second classification items are report items, there are some special accounting items that need to determine the report items they belong to based on the positive or negative situation of the account balance. For example, the second classification items also include other assets and other liabilities. At this time, the accounting items of asset transfer are included in the "other assets" report item when their account balance is positive, and are included in the "other liabilities" report item when their account balance is negative.

[0081] In the above case, assuming that the item classification corresponding to the accounting subject of asset transfer is marked as C, then refer to Table 3, the consolidation rules corresponding to other assets and other liabilities are:

[0082]

[0083] Table 3

[0084] Among them, CS C Indicates the target project parameter corresponding to the project classification mark C.

[0085] According to Table 3, there are two merging rules matched based on the project classification tag C. At this time, it is necessary to combine CS C The amount is compared with the set amount threshold (e.g. 0), and the target merge rule matching the project category marked as C is determined from the two-day merge rules. C If CS is greater than 0, the target consolidation rule is the consolidation rule corresponding to the "Other Assets" report item; C If it is less than 0, the target consolidation rule is the consolidation rule corresponding to the "Other Liabilities" statement item.

[0086] It should be noted that for accounting items that need to determine the report items to which they belong based on the positive or negative situation of the account balance, the relevant technology determines the report items to which they belong after making positive or negative judgments on such accounting items one by one, and the number of judgments is relatively large. In this application, the project parameters of such accounting items are first merged, and then the positive or negative situation of the target project parameters corresponding to such accounting items is judged, and then the target merging rules are matched according to the positive or negative judgment of the target project parameters. This can not only accurately match the target merging rules corresponding to the project classification mark, but also greatly reduce the number of positive and negative judgments in the merging process, thereby improving the merging efficiency.

[0087] Step 305: Based on the merging mapping relationship, the target item parameter is included in the second classification item corresponding to the target merging rule.

[0088] Based on the merging mapping relationship, the second classification item corresponding to the target merging rule can be determined, and then the target item parameters are counted into the corresponding second classification item to obtain the item parameters of the second classification item.

[0089] It should be noted that the execution process of step 301 and step 302 can be implemented in any way in the embodiments of the present application, and the embodiments of the present application do not limit this and will not be repeated.

[0090] For any project classification mark, the present application merges the project parameters of each first classification project under the project classification mark according to the set parameter merging logic to obtain the target project parameters; in the merging rules corresponding to each second classification project, the target merging rule matching the project classification mark is searched; based on the merging mapping relationship, the target project parameters are included in the second classification project corresponding to the target merging rule. The present application first merges the project parameters based on the project classification mark, and then includes the target project parameters in the corresponding second classification project. There is no need to perform multiple merging operations on the project parameters of each first classification project, which simplifies the merging process and improves the merging efficiency.

[0091] Embodiment 4:

[0092] Figure 4 A flowchart of a data processing method provided by another embodiment of the present application is shown as follows: Figure 4 As shown, the method comprises the following steps:

[0093] Step 401 : in response to an abnormality in an item parameter of any second classification item, obtaining an item classification tag matching the second classification item.

[0094] Among them, whether the project parameters of the second classification project are abnormal can be determined through manual monitoring or automatic monitoring.

[0095] The project classification mark that matches the second classification item refers to the classification mark corresponding to the first classification item of the project parameter merged into the second classification item during the merging process. For example, the project parameters corresponding to the original value of houses and buildings, the original value of computer equipment, the original value of transportation equipment, and the original value of office machinery and equipment are merged into fixed assets, and the project classification mark that matches the fixed assets is A.

[0096] Step 402, when a plurality of project classification tags are obtained, based on the project classification tags, determine the abnormal classification items whose project parameters are to be checked in the first classification items corresponding to the plurality of project classification tags.

[0097] As an example, the first classification item corresponding to multiple project classification marks can be determined as an abnormal classification item; or, the number of abnormal occurrences corresponding to each project classification mark in the multiple project classification marks is obtained, and the first classification item corresponding to the project classification mark whose number of abnormal occurrences is greater than a set number threshold is determined as an abnormal classification item.

[0098] As another example, obtain reference project parameters of each project classification mark among multiple project classification marks; compare the reference project parameters with corresponding target project parameters; based on the project parameter comparison results, select a target project classification mark whose reference project parameters and target project parameters are different from each other from multiple project classification marks; and determine a first classification item corresponding to the target project classification mark as an abnormal classification item.

[0099] The reference project parameters may refer to project parameters obtained from a relevant parameter statistical table (eg, a paper statistical table).

[0100] By comparing the target project parameters with the corresponding reference project parameters, the target project classification mark can be quickly selected from the multiple project classification marks corresponding to the abnormal classification project, and then the abnormal classification project can be accurately locked based on the target project classification mark, thereby narrowing the scope of project verification and improving the efficiency of problem troubleshooting.

[0101] It should be noted that when it is found that the project parameters of a first-category project are incorrect, the project classification mark on the first-category project can also be used to quickly confirm the second-category project affected by it.

[0102] It should be noted that step 401 and step 402 can be performed after step 103 .

[0103] In response to an abnormality in the project parameters of any second classification project, the present application obtains a project classification tag that matches the second classification project; in the case where multiple project classification tags are obtained, based on the project classification tags, the abnormal classification project whose project parameters are to be checked is determined in the first classification projects corresponding to the multiple project classification tags. The tag comparison process is simple and fast. Therefore, through the project classification tag, the present application can quickly locate the first classification project that may have a problem with the project parameters when an abnormality occurs in the project parameters of the second classification project.

[0104] Embodiment five:

[0105] Figure 5 A schematic diagram of the structure of a data processing device provided in an embodiment of the present application is shown in FIG. Figure 5 As shown, it includes a first acquisition module 501, a second acquisition module 502 and a merging module 503.

[0106] Among them, the first acquisition module 501 is used to obtain the project classification mark of each first classification project, wherein the first classification project corresponds to a project parameter; the second acquisition module 502 is used to obtain the merging rule corresponding to each second classification project, wherein the classification granularity of the first classification project is finer than that of the second classification project, and the merging rule is used to indicate the merging mapping relationship between the second classification project and the project classification mark; the merging module 503 is used to merge the project parameters of each first classification project into the corresponding second classification project based on the merging mapping relationship indicated by the merging rule.

[0107] As a possible implementation method, the first acquisition module 501 is used to: obtain description information of each first classification project, the description information including project attribute information, project code and project name; determine the project classification mark of each first classification project based on at least one of the project attribute information, project code and project name.

[0108] As a possible implementation method, the first acquisition module 501 is used to: for any first classification project, classify the first classification project based on the project attribute information to obtain a first classification mark; extract the target code value at the set position in the project code, and determine the second classification mark corresponding to the target code value based on the first set mapping relationship between the code value and the classification mark; extract the keywords in the project name and determine the target keyword set to which the keywords belong; determine the third classification mark corresponding to the target keyword set based on the second set mapping relationship between the keyword set and the classification mark; determine the project classification mark of the first classification project based on the first classification mark, the second classification mark and the third classification mark.

[0109] As a possible implementation method, the merging module 503 is used to: for any project classification mark, merge the project parameters of each first classification project under the project classification mark according to the set parameter merging logic to obtain the target project parameters; in the merging rules corresponding to each second classification project, search for the target merging rule that matches the project classification mark; based on the merging mapping relationship, include the target project parameters in the second classification project corresponding to the target merging rule.

[0110] As a possible implementation method, when the first classification item is an accounting subject, the second classification item is a report item, the item parameter is an item balance, and the target item parameter is a summary amount, the merging module 503 is used to: perform rule matching based on the item classification mark; in response to matching a merging rule, use the matched merging rule as the target merging rule; in response to matching multiple merging rules, compare the summary amount with the set amount threshold to obtain an actual amount comparison result; and determine the target merging rule from multiple merging rules by combining the actual amount comparison result and the amount comparison result included in the found merging rule.

[0111] As a possible implementation method, the second classification item corresponds to a project parameter, and the device also includes: a third acquisition module, used to obtain a project classification tag matching the second classification item in response to an abnormal project parameter of any second classification item; a determination module, used to determine the abnormal classification item whose project parameters are to be verified in the first classification items corresponding to the multiple project classification tags based on the project classification tags when multiple project classification tags are acquired.

[0112] As a possible implementation method, the determination module is used to: obtain reference project parameters of each project classification mark among multiple project classification marks; compare the reference project parameters with the corresponding target project parameters; based on the project parameter comparison results, select a target project classification mark whose reference project parameters and target project parameters are different from each other from multiple project classification marks; and determine the first classification project corresponding to the target project classification mark as an abnormal classification project.

[0113] It should be noted that the above explanation of the method embodiment is also applicable to the device of this embodiment, and will not be repeated here.

[0114] Embodiment six:

[0115] Figure 6 A schematic diagram of the structure of an electronic device provided for an embodiment of the present application. Among them, the electronic device 600 in this embodiment is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0116] like Figure 6 As shown, the electronic device 600 includes: a memory 610, a processor 620, and computer instructions stored in the memory 610 and executable on the processor 620.

[0117] When the processor 620 executes the instructions, the data processing method provided in the above embodiment is implemented.

[0118] Furthermore, the electronic device 600 further includes:

[0119] The communication interface 630 is used for communication between the memory 610 and the processor 620 .

[0120] The memory 610 is used to store computer instructions that can be executed on the processor 620 .

[0121] The memory 610 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0122] The processor 620 is used to implement the data processing method of the above embodiment when executing a program.

[0123] If the memory 610, the processor 620 and the communication interface 630 are implemented independently, the communication interface 630, the memory 610 and the processor 620 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 6 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0124] Optionally, in a specific implementation, if the memory 610, the processor 620 and the communication interface 630 are integrated on a chip, the memory 610, the processor 620 and the communication interface 630 can communicate with each other through an internal interface.

[0125] The processor 620 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0126] In order to implement the above embodiments, the present application also proposes a non-transitory computer-readable storage medium storing computer instructions, where the computer instructions are used to enable a computer to execute the above method.

[0127] In order to implement the above embodiments, the present application also proposes a computer program product, including a computer program, which implements the above method when executed by a processor.

[0128] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0129] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0130] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0131] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0132] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0133] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0134] In addition, each functional unit in each embodiment of the present application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into one module. The above-mentioned integrated module can be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. The above-mentioned storage medium can be a read-only memory, a disk or an optical disk, etc.

[0135] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0136] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A data processing method, characterized in that: The following steps are involved: Obtaining an item classification mark of each first classification item, wherein the first classification item corresponds to an item parameter; Acquire a merging rule corresponding to each second classification item, wherein the classification granularity of the first classification item is finer than that of the second classification item, and the merging rule is used to indicate a merging mapping relationship between the second classification item and the item classification mark; Based on the merging mapping relationship indicated by the merging rule, the item parameters of each of the first classification items are merged into the corresponding second classification items.

2. The method according to claim 1, characterized in that The step of obtaining the item classification mark of each first classification item includes: Acquire description information of each of the first classification items, the description information including item attribute information, item code and item name; Based on at least one of the item attribute information, the item code and the item name, an item classification mark of each of the first classification items is determined.

3. The method according to claim 2, characterized in that The determining of the project classification mark of each of the first classification projects based on at least one of the project attribute information, the project code and the project name includes: For any of the first classification items, classify the first classification item based on the item attribute information to obtain a first classification label; Extracting a target code value at a set position in the project code, and determining a second classification mark corresponding to the target code value based on a first set mapping relationship between code values ​​and classification marks; Extracting keywords from the project name and determining a target keyword set to which the keywords belong; determining a third classification mark corresponding to the target keyword set based on a second set mapping relationship between the keyword set and the classification mark; Based on the first classification mark, the second classification mark, and the third classification mark, an item classification mark of the first classification item is determined.

4. The method according to claim 1, characterized in that: The merging the item parameters of each of the first classification items into the corresponding second classification items based on the merging mapping relationship indicated by the merging rule includes: For any of the project classification marks, according to the set parameter merging logic, the project parameters of each of the first classification projects under the project classification mark are merged to obtain the target project parameters; Searching for a target merging rule that matches the item classification mark in the merging rules corresponding to each of the second classification items; Based on the merging mapping relationship, the target item parameter is included in the second classification item corresponding to the target merging rule.

5. The method according to claim 4, characterized in that When the first classification item is an accounting subject, the second classification item is a report item, the item parameter is an account balance, and the target item parameter is a summary amount, searching for a target merging rule that matches the item classification mark in the merging rules corresponding to each of the second classification items includes: Perform rule matching based on the project classification tag; In response to matching a merge rule, taking the matched merge rule as the target merge rule; In response to matching multiple merging rules, the summary amount is compared with a set amount threshold to obtain an actual amount comparison result; The target merging rule is determined from among the multiple merging rules by combining the actual amount comparison result with the amount comparison result included in the found merging rule.

6. The method according to claim 4, characterized in that The second classification item corresponds to an item parameter, and the method further includes: In response to an abnormality in an item parameter of any of the second classification items, obtaining an item classification tag matching the second classification item; In the case where a plurality of project classification marks are obtained, based on the project classification marks, an abnormal classification item whose project parameters are to be checked is determined from among the first classification items corresponding to the plurality of project classification marks.

7. The method according to claim 6, characterized in that The determining, based on the project classification mark, among the first classification items corresponding to the multiple project classification marks, of abnormal classification items whose project parameters are to be checked comprises: Obtaining reference project parameters of each of the project classification marks in the plurality of project classification marks; Comparing the reference project parameters with the corresponding target project parameters; Based on the project parameter comparison result, selecting a target project classification mark having different reference project parameters and target project parameters from the plurality of project classification marks; The first classification item corresponding to the target item classification mark is determined as the abnormal classification item.

8. A data processing device, characterized in that: include: A first acquisition module, used to acquire a project classification mark of each first classification project, wherein the first classification project corresponds to a project parameter; A second acquisition module is used to acquire a merging rule corresponding to each second classification item, wherein the classification granularity of the first classification item is finer than that of the second classification item, and the merging rule is used to indicate a merging mapping relationship between the second classification item and the item classification mark; A merging module is used to merge the item parameters of each first classification item into the corresponding second classification item based on the merging mapping relationship indicated by the merging rule.

9. The device according to claim 8, characterized in that The first acquisition module is used for: Acquire description information of each of the first classification items, the description information including item attribute information, item code and item name; Based on at least one of the item attribute information, the item code and the item name, an item classification mark of each of the first classification items is determined.

10. The device according to claim 9, characterized in that The first acquisition module is used for: For any of the first classification items, classify the first classification item based on the item attribute information to obtain a first classification label; Extracting a target code value at a set position in the project code, and determining a second classification mark corresponding to the target code value based on a first set mapping relationship between code values ​​and classification marks; Extracting keywords from the project name and determining a target keyword set to which the keywords belong; determining a third classification mark corresponding to the target keyword set based on a second set mapping relationship between the keyword set and the classification mark; Based on the first classification mark, the second classification mark, and the third classification mark, an item classification mark of the first classification item is determined.

11. The device according to claim 8, characterized in that The merging module is used for: For any of the project classification marks, according to the set parameter merging logic, the project parameters of each of the first classification projects under the project classification mark are merged to obtain the target project parameters; Searching for a target merging rule that matches the item classification mark in the merging rules corresponding to each of the second classification items; Based on the merging mapping relationship, the target item parameter is included in the second classification item corresponding to the target merging rule.

12. The device according to claim 11, characterized in that When the first classification item is an accounting subject, the second classification item is a report item, the item parameter is an account balance, and the target item parameter is a summary amount, the merging module is used to: Perform rule matching based on the project classification tag; In response to matching a merge rule, taking the matched merge rule as the target merge rule; In response to matching multiple merging rules, the summary amount is compared with a set amount threshold to obtain an actual amount comparison result; The target merging rule is determined from among the multiple merging rules by combining the actual amount comparison result with the amount comparison result included in the found merging rule.

13. The device according to claim 11, characterized in that The second classification item corresponds to an item parameter, and the device further includes: A third acquisition module, configured to acquire an item classification mark matching the second classification item in response to an abnormal item parameter of any of the second classification items; A determination module is used to determine, when a plurality of project classification marks are obtained, the abnormal classification items whose project parameters are to be checked in the first classification items corresponding to the plurality of project classification marks based on the project classification marks.

14. The device according to claim 13, characterized in that The determination module is used for: Obtaining reference project parameters of each of the project classification marks in the plurality of project classification marks; Comparing the reference project parameters with the corresponding target project parameters; Based on the project parameter comparison result, selecting a target project classification mark having different reference project parameters and target project parameters from the plurality of project classification marks; The first classification item corresponding to the target item classification mark is determined as the abnormal classification item.

15. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 7.

16. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

17. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 7.

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