Tax data processing method and device, computer equipment and storage medium

Abstract

The invention provides a tax data processing method and device, computer equipment and a storage medium, and relates to a data processing technology, a server obtains an identity tag of a user, generates a corresponding management plug-in and sends the management plug-in to a user management end; the user management end interacts with the management plug-in after judging that the target fixed assets exist, and the management plug-in generates a corresponding data acquisition template based on the attributes of the fixed assets and performs data acquisition; the server identifies and verifies the data in the data acquisition template, performs tax verification on the target fixed assets based on a database, generates a corresponding verification link and feeds back the verification link to the user management end; and the user management end fills the corresponding active tax declaration information according to the verification link, and if the active tax declaration information does not meet the verification link requirement, the associated data acquisition slot position in the data acquisition template is highlighted, so that the corresponding tax data can be automatically processed according to different user tax identities, and the tax data processing efficiency is improved.

Description

Technical Field

[0001] The present invention relates to data processing technology, and in particular to a tax data processing method, device, computer equipment and storage medium. Background Art

[0002] With the continuous advancement of the digitalization of tax management, the tax management of fixed assets has gradually become one of the core links in tax management. Fixed assets have the characteristics of high value, complex depreciation, and long use cycle. Their tax treatment directly affects the company's accounting compliance and the accuracy of tax declaration. However, due to the diverse types and complex attributes of fixed assets, in actual tax management, how to efficiently collect fixed asset data, accurately verify tax information, and timely generate tax information has become an important challenge in corporate tax management.

[0003] At present, the fixed asset tax processing of enterprises mainly relies on the traditional manual management mode and some single tool assistance. Manual management requires a lot of form filling, manual comparison and verification, which greatly increases the workload, affects the efficiency and accuracy of tax declaration, and easily leads to data errors or omissions.

[0004] Therefore, how to automatically process corresponding tax data according to the tax identities of different users and improve the efficiency of tax data processing has become an urgent problem that needs to be solved. Summary of the invention

[0005] The present invention provides a tax data processing method, device, computer equipment and storage medium, which can automatically process corresponding tax data according to different user tax identities and improve tax data processing efficiency.

[0006] A first aspect of the present invention provides a tax data processing method, comprising: After obtaining the user's identity tag, the server generates a corresponding management plug-in and sends it to the user management terminal; After determining that there is a target fixed asset, the user management terminal interacts with the management plug-in, and the management plug-in generates a corresponding data collection template based on the attributes of the fixed asset and performs data collection; The server identifies and verifies the data in the data collection template, performs tax verification on the target fixed assets based on the database, generates corresponding verification links and feeds them back to the user management end; The user management end fills in the corresponding active tax reporting information with reference to the verification link. If the active tax reporting information does not meet the verification link requirements, the associated data collection slot in the data collection template is highlighted.

[0007] Optionally, in a possible implementation of the first aspect, the server acquires the user's identity tag, generates a corresponding management plug-in, and sends the plug-in to the user management terminal, including: The user management terminal sends a fixed asset tax management request to the server, and the server obtains the user's identity tag, which includes at least a small-scale tag and a general taxpayer tag; Based on the small-scale label or the general taxpayer label, a corresponding management plug-in is determined and sent to the user management terminal.

[0008] Optionally, in a possible implementation of the first aspect, the data collection template includes a plurality of data collection slots; The user management terminal interacts with the management plug-in after determining that there is a target fixed asset. The management plug-in generates a corresponding data collection template based on the attributes of the fixed asset and performs data collection, including: After determining that there is a target fixed asset, the user management terminal interacts with the management plug-in, selects the interactive column corresponding to the target fixed asset, and obtains the properties of the corresponding fixed asset; Generate a data collection template corresponding to the attributes of the fixed assets, each attribute of the fixed assets having a preset data collection template; Determine the image acquisition slots and text acquisition slots in the data acquisition template, generate corresponding processing links according to the attributes of each image acquisition slot and text acquisition slot, and the processing links are used to call processing functions to perform associated processing on the associated image acquisition slots and text acquisition slots.

[0009] Optionally, in a possible implementation of the first aspect, the determining the image acquisition slot and the text acquisition slot in the data acquisition template, generating a corresponding processing link according to the attributes of each image acquisition slot and the text acquisition slot, and the processing link is used to call a processing function to perform associated processing on the associated image acquisition slot and the text acquisition slot, including: Obtain the attributes of each image acquisition slot and text acquisition slot, and input them into the attribute mapping network corresponding to the attributes of the fixed assets; The attribute mapping network includes two-dimensional multi-level mapping nodes with levels from low to high, and the attribute mapping network is divided into a horizontal node comparison sub-strategy and a vertical node comparison sub-strategy based on a pre-trained comparison strategy; Based on the horizontal node comparison sub-strategy and the vertical node comparison sub-strategy, the multi-level mapping nodes in the attribute mapping network are optimized and traversed, and if it is determined that they correspond to the attributes of the image acquisition slot and the text acquisition slot, they are selected; After determining that all image acquisition slots and text acquisition slots have been traversed, the selected multi-level mapping nodes are retained. If it is determined that the retained multi-level mapping nodes have a mapping relationship, the corresponding processing links are called. Each mapping connection in the attribute mapping network has a preset processing link.

[0010] Optionally, in a possible implementation manner of the first aspect, the optimizing traversal processing of the multi-level mapping nodes in the attribute mapping network based on the horizontal node comparison sub-strategy and the vertical node comparison sub-strategy, if it is determined that the attributes of the image acquisition slot and the text acquisition slot correspond to each other, includes: The two-dimensional multi-level mapping nodes are in the first quadrant of the coordinate axis, and the levels of the multi-level mapping nodes in the positive direction of the X positive coordinate axis and the Y positive coordinate axis increase in sequence; First, traverse multiple multi-level mapping nodes that lock the smallest X-axis coordinate, and traverse each multi-level mapping node in turn along the positive direction of the Y axis until the first segmentation line is determined; After determining the first segmentation line, traverse the next multiple multi-level mapping nodes of the X-axis coordinate backward, and traverse each multi-level mapping node in turn along the positive direction of the Y-axis again until another first segmentation line is determined; Repeat the above steps until all the multi-level mapping nodes corresponding to the image acquisition slots and text acquisition slots are determined, and the segmentation lines in the vertical node comparison sub-strategy are optimized.

[0011] Optionally, in a possible implementation of the first aspect, the method further includes: If it is determined that after traversing the multi-level mapping node corresponding to the last X-axis coordinate in the positive direction of the X-axis, and after determining another first segmentation line in the positive direction of the Y-axis; Lock the smallest X-axis coordinate again and traverse the corresponding multi-level mapping nodes again with the first segmentation line as the starting point until another second segmentation line is determined and the traversal stops or all multi-level mapping nodes are traversed and the traversal stops; After determining that the second segmentation line traverses the next multiple multi-level mapping nodes of the X-axis coordinate, each multi-level mapping node is traversed in turn along the positive direction of the Y-axis until another second segmentation line is determined or all multi-level mapping nodes are traversed and the traversal stops.

[0012] Optionally, in a possible implementation manner of the first aspect, generating an attribute mapping network through the following steps includes: Receiving the attributes of the fixed assets configured by the server, and the multi-level mapping nodes with preset associations corresponding to the attributes of the corresponding fixed assets; Obtain all associated multi-level mapping nodes to form an associated chain, and add corresponding sequence labels according to the order of each node in the associated chain, wherein there is at least one multi-level mapping node in the associated chain; Count the maximum values ​​of the order in the order label to generate a corresponding number of X-axis coordinates, and count the number of associated chains to generate a corresponding number of multiple Y-axis coordinates; The corresponding attribute mapping network is generated by receiving the position configured by the user for each association chain.

[0013] Optionally, in a possible implementation of the first aspect, the above steps are repeated until all multi-level mapping nodes corresponding to the image acquisition slots and the text acquisition slots are determined, and the segmentation line in the vertical node comparison sub-strategy is optimized, including: After determining the preset time interval, obtaining the traversal hit count of each multi-level mapping node within the first dividing line of each X-axis coordinate to obtain the first hit count, obtaining the traversal hit count of each multi-level mapping node between the first dividing line and the second dividing line to obtain the second hit count, and obtaining the traversal hit count of each multi-level mapping node above the second dividing line to obtain the third hit count; Extract the minimum second hit count, compare the third hit counts of all multi-level mapping nodes with the minimum second hit count, extract the multi-level mapping nodes with a second hit count greater than the minimum to between the first dividing line and the second dividing line, and place the multi-level mapping node with the minimum second hit count on the upper part of the second dividing line; The minimum first hit count is extracted, the second hit counts of all multi-level mapping nodes are compared with the minimum first hit count, and the multi-level mapping nodes with a number greater than the minimum first hit count are extracted to the lower part of the first dividing line to obtain the attribute mapping network after the dividing line position is optimized.

[0014] Optionally, in a possible implementation of the first aspect, the method further includes: Counting the number of first nodes of all multi-level mapping nodes extracted between the first dividing line and the second dividing line, if the number of the first nodes is greater than or equal to a first preset number; Then, the multi-level mapping nodes with the second hit count are arranged in reverse order, and the multi-level mapping nodes with the second hit count with the first fixed number at the front are selected and moved to the upper part of the second dividing line; Counting the number of second nodes of all multi-level mapping nodes extracted to the lower part of the first segmentation line, if the number of the second nodes is greater than or equal to a second preset number; Then, the multi-level mapping nodes with the first hit count are arranged in reverse order, and the front second fixed number of multi-level mapping nodes with the first hit count are selected and moved between the first dividing line and the second dividing line.

[0015] Optionally, in a possible implementation of the first aspect, the server identifies and verifies the data in the data collection template, performs tax verification on the target fixed assets based on the database, generates a corresponding verification link and feeds it back to the user management terminal, including: After receiving the data collection template filled with slots by the user management terminal, the server calls at least one of the text recognition module, the barcode recognition module, the QR code recognition module and the image recognition module to perform data recognition verification, and obtains the identity tag information, verification value information and verification period information of the corresponding target fixed asset; Based on the identity tag information, verification value information, and verification period information, a tax verification is performed by comparing the database to generate tax value information for the tax verification, wherein the tax value information is an interval value, and each identity tag information, verification value information, and verification period information has a preset tax value information; A verification link is generated by counting all the compared data, identity tag information, verification value information, verification years information and tax value information in the database.

[0016] Optionally, in a possible implementation of the first aspect, the user management terminal fills in corresponding active tax reporting information with reference to the verification link, and if the active tax reporting information does not meet the verification link requirement, highlights the associated data collection slot in the data collection template, including: If it is determined that the value of the active tax reporting information is not within the range of the tax value information, the corresponding data collection slot is retrieved and the data collection slot is highlighted.

[0017] A second aspect of the present invention provides a tax data processing device, comprising: The request module is used to enable the server to obtain the user's identity tag and generate a corresponding management plug-in to send to the user management terminal; A judgment module is used to enable the user management terminal to interact with the management plug-in after judging that there is a target fixed asset, and the management plug-in generates a corresponding data collection template based on the attributes of the fixed asset and performs data collection; Feedback module, used to enable the server to identify and verify the data in the data collection template, conduct tax verification on the target fixed assets based on the database, generate corresponding verification links and feedback to the user management end; The verification module is used to enable the user management end to fill in the corresponding active tax reporting information with reference to the verification link. If the active tax reporting information does not meet the verification link requirements, the associated data collection slot in the data collection template is highlighted.

[0018] According to a third aspect of the present invention, a storage medium is provided, wherein a computer program is stored in the storage medium, and when the computer program is executed by a processor, it is used to implement the aforementioned method.

[0019] The beneficial effects of the present invention are as follows: 1. The present invention can automatically process corresponding tax data according to different user tax identities, thereby improving the efficiency of tax data processing. This method can automatically identify user identities and generate adaptive management plug-ins, and generate highly correlated data collection templates according to the attributes of fixed assets, and accurately collect and process data through a multi-dimensional attribute mapping network; at the same time, this method can also efficiently connect to the tax verification database, complete rapid verification and generate verification links, supplemented by intelligent feedback and data highlighting functions, to guide users to accurately fill in tax information, and ultimately achieve high efficiency, accuracy and intelligence in fixed asset tax management.

[0020] 2. The present invention can dynamically generate management plug-ins to improve the adaptability and convenience of tax management. Among them, the present invention sends a fixed asset tax management request to the server through the user management end. The server dynamically generates a corresponding management plug-in based on the user's identity tag, such as a small-scale taxpayer or a general taxpayer, and returns it to the user management end, realizing accurate identification and classification management of user identities, so that the system can provide customized tax management functions for different user needs. Through the generation of dynamic management plug-ins, the adaptability of tax management can be effectively improved, the management end interface can be clearer and more concise, and the user's operation complexity is reduced, which significantly improves the efficiency of fixed asset tax management. Secondly, the present invention interacts with the user management end through the management plug-in, and dynamically generates a data collection template for the attributes of the target fixed assets. The template contains image collection slots and text collection slots, and an attribute mapping network is designed for optimizing the traversal of the multi-level mapping nodes of the slots. Through the horizontal and vertical comparison sub-strategies, the attributes of each node are accurately matched to ensure the integrity and accuracy of the collected data. At the same time, by optimizing the position of the dividing line of the attribute mapping network, the number of invalid traversals is reduced, and the data processing efficiency is improved.

[0021] 3. The present invention can intelligently verify data and improve the accuracy and guidance of tax declaration. Specifically, after receiving the data collection template filled in by the user management terminal through the server, the present invention uses a variety of recognition modules to identify and verify the data in the template, extracts the identity tag information, verification value information and verification period information of the target fixed assets, and compares them with the database to generate tax verification results; at the same time, the system feeds back the verification results in the form of a verification link to provide users with clear tax reference information. When the user fills in the active tax declaration information, if the data does not meet the verification requirements, the system automatically highlights the associated slots in the template and guides the user to correct it, thereby improving the guidance and convenience of the tax declaration operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A flow chart of a tax data processing method provided by the present invention; Figure 2This is a schematic diagram of the structure of a tax data processing device provided by the present invention. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] The terms "first", "second", "third", "fourth", etc. (if any) in the description and claims of the present invention and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in sequences other than those illustrated or described herein.

[0025] It should be understood that in various embodiments of the present invention, the size of the sequence number of each process does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0026] It should be understood that in the present invention, "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products or apparatuses.

[0027] It should be understood that in the present invention, "plurality" refers to two or more than two. "And / or" is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "Contains A, B and C", "Contains A, B, C" means that A, B, and C are all included, "Contains A, B or C" means that one of A, B, and C is included, and "Contains A, B and / or C" means that any one, any two, or any three of A, B, and C are included.

[0028] It should be understood that in the present invention, "B corresponding to A", "B corresponding to A", "A corresponds to B" or "B corresponds to A" means that B is associated with A and B can be determined based on A. Determining B based on A does not mean determining B based only on A, but B can also be determined based on A and / or other information. A and B match when the similarity between A and B is greater than or equal to a preset threshold.

[0029] Depending on the context, "if" as used herein may be interpreted as "when" or "when" or "in response to determining" or "in response to detecting."

[0030] The technical solution of the present invention is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0031] like Figure 1 As shown, the present invention provides a tax data processing method, comprising: S1, the server obtains the user's identity tag and generates a corresponding management plug-in and sends it to the user management terminal.

[0032] It is understandable that when a user needs to process fixed asset tax returns, the server can obtain the identity tag and generate a corresponding management plug-in to send to the user management end, so as to collect relevant data for subsequent analysis and processing.

[0033] Among them, the user management end is the user information terminal for tax declaration, for example, it can be the computer of the tax declaration user, the identity label is the label of the user identity type, such as the general taxpayer or small-scale enterprise label, etc., and the management plug-in is a plug-in for data management and processing.

[0034] Through the above implementation, the present invention can generate a management plug-in according to the user identity tag and send it to the user management terminal, so as to improve the data processing efficiency of the fixed asset tax data through the management plug-in later.

[0035] In some embodiments, the specific implementation of step S1 (the server obtains the user's identity tag, generates a corresponding management plug-in and sends it to the user management terminal) includes: S11, the user management terminal sends a fixed asset tax management request to the server, and the server obtains the user's identity tag, which includes at least a small-scale tag and a general taxpayer tag.

[0036] It can be understood that the fixed asset tax management request is the declaration request information for fixed asset tax management, and the identity tag includes at least a small-scale tag and a general taxpayer tag.

[0037] It is not difficult to understand that the information content and required materials of the tax data corresponding to different identity tags are somewhat different. For example, general taxpayers can generate deduction information, while users corresponding to small-scale tags do not have deduction information, that is, no corresponding deduction information is generated. Therefore, the user's identity tag can be obtained so that a management plug-in can be generated based on the identity tag to improve the accuracy and efficiency of personnel's tax processing.

[0038] S12: Determine a corresponding management plug-in based on the small-scale tag or the general taxpayer tag and send it to the user management terminal.

[0039] It is understandable that the corresponding management plug-in generated according to the corresponding identity tag is sent to the user management end so that the user's relevant tax data can be processed through the management plug-in later to improve the accuracy and timeliness of the user's tax data processing.

[0040] S2, after determining that there is a target fixed asset, the user management terminal interacts with the management plug-in, and the management plug-in generates a corresponding data collection template based on the attributes of the fixed asset and performs data collection.

[0041] It can be understood that when the user management end determines that it has the target fixed assets, it interacts with the management plug-in so that the management plug-in generates a data collection template corresponding to the attributes of the fixed assets to collect the data in the user management end, and then analyzes and processes the collected data to complete the user's tax information processing.

[0042] The data collection template is a template for collecting data, and may be a data table with multiple data collection slots, where the data collection slots are slots for collecting data.

[0043] Through the above implementation, the present invention can generate a data collection template corresponding to the fixed asset attributes and perform data collection, so as to subsequently process the data information collected and filled into the data collection slot to complete the handling of tax data.

[0044] In some embodiments, the specific implementation of step S2 (the user management terminal interacts with the management plug-in after determining that there is a target fixed asset, and the management plug-in generates a corresponding data collection template based on the attributes of the fixed asset and performs data collection) includes: S21, after determining that there is a target fixed asset, the user management terminal interacts with the management plug-in, selects the interactive column corresponding to the target fixed asset, and obtains the attributes of the corresponding fixed asset.

[0045] It should be noted that the user management end is verified in real time by the management personnel. When it is found that the personnel purchases a device but does not report the tax, the corresponding equipment information can be sent to the accounting personnel for tax reporting. Therefore, when it is determined that there are target fixed assets, information interaction is carried out with the management plug-in to select the interactive column corresponding to the target fixed asset and determine the corresponding attributes according to the target fixed asset, so that the corresponding data collection template can be generated through the attributes of the fixed asset to facilitate data collection.

[0046] It can be understood that the target fixed assets are the fixed assets that need to be evaluated, such as engineering equipment, electronic equipment, etc. The interactive column is the item for terminal information interaction, and the attributes of the fixed assets are the attribute information corresponding to the target fixed assets. For example, when the target fixed asset is a computer, the corresponding attributes are computer attributes, and when the target fixed asset is experimental equipment, the corresponding attributes are the attributes of the experimental equipment.

[0047] It is not difficult to understand that if there are corresponding equipment and instruments in the management plug-in, the corresponding equipment and instruments in the management plug-in can be selected according to the determined target fixed assets, so as to subsequently generate the corresponding data collection template to facilitate data collection.

[0048] S22, generating a data collection template corresponding to the attributes of the fixed assets, each attribute of the fixed assets has a preset data collection template, and the data collection template includes a plurality of data collection slots.

[0049] It can be understood that the corresponding data collection template is generated according to the attributes of the fixed assets, wherein the attributes of each fixed asset have a pre-set data collection template, such as a barcode, a QR code, a photo, etc., and different attributes have corresponding data collection templates.

[0050] S23, determining the image acquisition slots and text acquisition slots in the data acquisition template, generating corresponding processing links according to the attributes of each image acquisition slot and text acquisition slot, and the processing links are used to call the processing function to perform associated processing on the associated image acquisition slots and text acquisition slots.

[0051] It can be understood that the data acquisition template includes image acquisition slots and text acquisition slots, wherein the image acquisition slot is a slot for acquiring images, and the text acquisition slot is a slot for acquiring the text name of the device, and there is a correlation between the image acquisition slot and the text acquisition slot. Therefore, corresponding processing links can be generated according to the attributes between different slots to obtain the collected data corresponding to the target fixed assets, thereby improving data processing efficiency.

[0052] The processing link is a slot link for data processing, and the processing function is function information for data processing.

[0053] It is not difficult to understand that the image acquisition slot can scan the barcode to automatically generate the corresponding attributes, which are then filled in the text acquisition slot to facilitate subsequent personnel to verify the device information in the background.

[0054] In some embodiments, the specific implementation of step S23 (determining the image acquisition slot and the text acquisition slot in the data acquisition template, generating corresponding processing links according to the attributes of each image acquisition slot and the text acquisition slot, and the processing links are used to call the processing function to perform associated processing on the associated image acquisition slot and the text acquisition slot) includes: S231, obtaining the attributes of each image acquisition slot and text acquisition slot, and inputting them into the attribute mapping network corresponding to the attributes of the fixed assets.

[0055] It can be understood that each image acquisition slot and text acquisition slot has corresponding attributes. For example, the attribute of the image acquisition slot can be the barcode of the experimental equipment, and the corresponding text acquisition slot contains the text name attribute information of each experimental equipment. Therefore, the attributes of the image acquisition slot and the attributes of the text acquisition slot can be mapped in the attribute mapping network to subsequently generate corresponding processing links.

[0056] The attribute mapping network is an information node network mapped with various attribute information.

[0057] S232, the attribute mapping network includes two-dimensional multi-level mapping nodes with levels from low to high, and the attribute mapping network is divided into a horizontal node comparison sub-strategy and a vertical node comparison sub-strategy based on a pre-trained comparison strategy.

[0058] It can be understood that since the attribute mapping network includes multi-level two-dimensional multi-level mapping nodes, in order to improve the accuracy of data processing, the multi-level mapping nodes in the attribute mapping network can be divided, and the nodes in the same row can be used as horizontal nodes, and the nodes in the same column can be used as vertical nodes. Subsequently, the horizontal node comparison sub-strategy can be used to compare the horizontal nodes in the attribute mapping network, and the vertical node comparison sub-strategy can be used to compare the vertical nodes in the attribute mapping network and analyze the data.

[0059] The multi-level mapping nodes are nodes of mapping information of multiple levels.

[0060] It is not difficult to understand that the multi-level mapping nodes in the attribute mapping network are generated by information mapping of the attribute information in the image acquisition slots and the text acquisition slots. One multi-level mapping node corresponds to one slot and is pre-set. When a device corresponds to 6 slots, 6 nodes can be selected and the remaining nodes can be deleted.

[0061] S233, based on the horizontal node comparison sub-strategy and the vertical node comparison sub-strategy, the multi-level mapping nodes in the attribute mapping network are optimized and traversed, and if it is determined that they correspond to the attributes of the image acquisition slot and the text acquisition slot, they are selected.

[0062] It can be understood that the multi-level mapping nodes in the attribute mapping network can be optimized and traversed through the horizontal node comparison sub-strategy and the vertical node comparison sub-strategy, so that when the attributes corresponding to the collected image acquisition slots and text acquisition slots are determined, the node can be selected to facilitate the subsequent selection of all related nodes, and the remaining nodes can be deleted, thereby facilitating the subsequent generation of corresponding processing links and improving the processing efficiency of tax data.

[0063] In some embodiments, the specific implementation of step S233 (the optimization traversal processing of the multi-level mapping nodes in the attribute mapping network based on the horizontal node comparison sub-strategy and the vertical node comparison sub-strategy, if it is determined that it corresponds to the attributes of the image acquisition slot and the text acquisition slot) includes: S2331, the two-dimensional multi-level mapping nodes are in the first quadrant of the coordinate axis, and the levels of the multi-level mapping nodes increase in sequence along the positive direction of the X positive coordinate axis and the Y positive coordinate axis.

[0064] It can be understood that all two-dimensional multi-level mapping nodes are located in the first quadrant of the coordinate axis, and the level of the corresponding multi-level mapping node gradually increases with the positive direction of the positive X coordinate axis and the positive Y coordinate axis, that is, the farther the multi-level mapping node is from the origin in the horizontal direction, the higher the level, and the farther the multi-level mapping node is from the origin in the vertical direction, the higher the level.

[0065] It is not difficult to understand that, since the multi-level mapping nodes have corresponding asset attribute information, the level will not be negative, and thus, all the multi-level mapping nodes are located in the first quadrant of the coordinate axis.

[0066] S2332, first traverse the multiple multi-level mapping nodes that lock the smallest X-axis coordinate, and traverse each multi-level mapping node in turn along the positive direction of the Y-axis until the first segmentation line is determined.

[0067] It is understandable that a column of multi-level mapping nodes with the smallest X-axis coordinate can be preferentially determined, and the multi-level mapping nodes are traversed in sequence along the positive direction of the Y-axis until the first dividing line is reached, and the traversal of the column of multi-level mapping nodes is stopped.

[0068] Among them, the first dividing line is a line segment that divides the multi-level mapping nodes, which can be pre-set. Due to the large number of nodes in the attribute mapping network, the nodes in the same column cannot be completely traversed in sequence. When the corresponding nodes are located in other columns, the same column will be infinitely traversed, which will greatly increase the traversal time and affect the data processing efficiency. Therefore, the node traversal can be intermittently divided by the first dividing line so that the horizontal nodes can be traversed and compared smoothly later.

[0069] S2333: after determining that the first segmentation line is determined, traverse the next plurality of multi-level mapping nodes of the X-axis coordinate backwards, and traverse each multi-level mapping node in turn again along the positive direction of the Y-axis until another first segmentation line is determined.

[0070] It can be understood that after the first dividing line is identified, the position can be moved horizontally to the multi-level mapping node of the next column corresponding to the X-axis, and the multi-level mapping nodes can be traversed in sequence along the positive direction of the Y-axis until the first dividing line in the column is determined and the traversal of the column nodes is stopped, so that the multi-level mapping nodes with attributes corresponding to the image acquisition slots and the text acquisition slots can be determined among the many nodes subsequently.

[0071] S2334, repeat the above steps until all the multi-level mapping nodes corresponding to the image acquisition slots and the text acquisition slots are determined, and the segmentation lines in the vertical node comparison sub-strategy are optimized.

[0072] It can be understood that the above-mentioned implementation steps of traversing and comparing the multi-level mapping nodes are repeated until all the multi-level mapping nodes corresponding to the image acquisition slots and the text acquisition slots are selected in the attribute mapping network, and the dividing line between the multi-level mapping nodes in the vertical node comparison sub-strategy is optimized to make the position of the first dividing line more reasonable, facilitate the subsequent comparison and traversal of the multi-level mapping nodes, and improve the efficiency of node selection.

[0073] In some embodiments, the specific implementation of step S2334 (repeating the above steps until all multi-level mapping nodes corresponding to all image acquisition slots and text acquisition slots are determined, and the segmentation line in the vertical node comparison sub-strategy is optimized) includes: S23341, after judging the preset time period, obtain the traversal hit count of each multi-level mapping node within the first dividing line of each X-axis coordinate to obtain the first hit count, the traversal hit count of each multi-level mapping node between the first dividing line and the second dividing line to obtain the second hit count, and the traversal hit count of each multi-level mapping node above the second dividing line to obtain the third hit count.

[0074] It can be understood that the preset time period is the time period of the pre-set traversal interval, the traversal hit count is the number of times the node is selected when traversing, the first hit count is the traversal hit count of each multi-level mapping node within the first dividing line of each X-axis coordinate, the second dividing line is the dividing line above and adjacent to the first dividing line in the multi-level mapping nodes corresponding to the same X-axis, the second hit count is the number of times each multi-level mapping node between the first dividing line and the second dividing line is selected during the traversal process, and the third hit count is the traversal hit count of each multi-level mapping node above the second dividing line.

[0075] It is not difficult to understand that the number of hits corresponding to the multi-level mapping nodes between different segmentation lines is obtained so that the position of the segmentation line segment can be adjusted according to the number of hits later to reduce the time of data traversal.

[0076] S23342, extract the minimum second hit count, compare the third hit counts of all multi-level mapping nodes with the minimum second hit count, extract the multi-level mapping nodes with a number greater than the minimum second hit count between the first dividing line and the second dividing line, and place the multi-level mapping nodes with the minimum second hit count on the upper part of the second dividing line.

[0077] It can be understood that the minimum number corresponding to the second hit number is determined so that the multi-level mapping node corresponding to the third hit number greater than the second hit number and located above the second dividing line can be moved downward to between the first dividing line and the second dividing line, and the multi-level mapping node with the minimum second hit number can be placed on the upper part of the second dividing line. The multi-level mapping node can be dynamically positioned according to the hit number, and the multi-level mapping node with the selected number can be adjusted downward to reduce the traversal time and improve data processing efficiency.

[0078] S23343, extract the minimum first hit count, compare the second hit counts of all multi-level mapping nodes with the minimum first hit count, extract the multi-level mapping nodes with a number greater than the minimum first hit count to the lower part of the first dividing line, and obtain the attribute mapping network after the dividing line position is optimized.

[0079] It can be understood that the minimum number corresponding to the first hit number is determined so that the multi-level mapping node above the first dividing line whose second hit number is greater than the first hit number can be moved downward to below the first dividing line, and the multi-level mapping node with the minimum first hit number can be placed on the upper part of the first dividing line. The position of the multi-level mapping node is dynamically adjusted according to the hit number, and the multi-level mapping node with the selected number can be adjusted downward to reduce the time for subsequent traversal and selection of the attributes of the multi-level mapping nodes, thereby improving data processing efficiency.

[0080] S234, after determining that all image acquisition slots and text acquisition slots have been traversed, retain the selected multi-level mapping nodes. If it is determined that the retained multi-level mapping nodes have a mapping relationship, call the corresponding processing link. Each mapping connection in the attribute mapping network has a preset processing link.

[0081] It can be understood that after traversing all image acquisition slots and text acquisition slots, the selected multi-level mapping nodes can be retained. When it is determined that there is a mapping relationship between the retained multi-level mapping nodes, the corresponding data processing links can be called out, wherein the nodes with the mapping relationship can be connected, so that the processing links pre-set for the corresponding mapping connections can be called out and displayed.

[0082] It is not difficult to understand that the mapping lines are connecting lines between multi-level mapping nodes.

[0083] In some embodiments, it also includes: A1: if it is determined that after traversing the multi-level mapping node corresponding to the last X-axis coordinate in the positive direction of the X-axis, and after determining another first segmentation line in the positive direction of the Y-axis.

[0084] It can be understood that, after traversing the multi-level mapping nodes corresponding to the last X-axis coordinate in the positive direction of the X-axis during the traversal process, and determining a first dividing line in the multi-level mapping nodes in the column corresponding to the last X-axis coordinate in the positive direction of the Y-axis, if the nodes mapped corresponding to the image acquisition slot and the text acquisition slot have not yet been determined, then the remaining multi-level mapping nodes that have not been traversed and compared in the column corresponding to the first X-axis coordinate can be subsequently identified again, so as to determine the multi-level mapping nodes corresponding to the attribute information corresponding to the image acquisition slot and the text acquisition slot.

[0085] A2, locking the smallest X-axis coordinate again and traversing the corresponding multi-level mapping nodes again with the first segmentation line as the starting point, until another second segmentation line is determined and the traversal stops or all multi-level mapping nodes are traversed and the traversal stops.

[0086] It can be understood that when the multi-level mapping nodes corresponding to all image acquisition slots and text acquisition slots are not determined during the first round of traversal, the multi-level mapping nodes above the first dividing line in the smallest X-axis coordinate can be traversed again, that is, the corresponding multi-level mapping nodes are traversed again with the first dividing line as the starting point until the second dividing line is identified or the multi-level mapping nodes of the corresponding column have been traversed, and then the traversal of the multi-level mapping nodes of the column is stopped.

[0087] It should be noted that the positions of the dividing lines in the multi-level mapping nodes of each column corresponding to the X-axis coordinate are preset, and the number of the multi-level mapping nodes spaced between the first dividing line and the second dividing line is also predetermined.

[0088] A3, after determining the second segmentation line, traverse the next multiple multi-level mapping nodes of the X-axis coordinate backward, and traverse each multi-level mapping node in turn along the positive direction of the Y-axis again until another second segmentation line is determined or all multi-level mapping nodes are traversed and the traversal stops.

[0089] It can be understood that after the second dividing line is identified, the position can be moved horizontally to the multi-level mapping node of the next column corresponding to the X-axis, and the multi-level mapping nodes can be traversed in sequence along the positive direction of the Y-axis until the second dividing line in the column is determined or the traversal of the column nodes is stopped after all the multi-level mapping nodes have been traversed, so as to subsequently determine the multi-level mapping nodes with attributes corresponding to the image acquisition slots and the text acquisition slots among many nodes.

[0090] In some embodiments, the attribute mapping network is generated by the following steps, including: B1, receiving the attributes of the fixed assets configured by the server, and the multi-level mapping nodes with preset associations corresponding to the attributes of the corresponding fixed assets.

[0091] It is understandable that the attribute information configured by the server for the fixed assets, such as images, dates, etc., is received, and associated multi-level mapping nodes are pre-set for the attributes corresponding to the fixed assets, so as to subsequently generate an attribute mapping network.

[0092] Among them, the multi-level mapping nodes are nodes associated with the attributes corresponding to the fixed assets and are preset.

[0093] B2, obtaining all associated multi-level mapping nodes to form an associated chain, and adding corresponding sequence labels according to the order of each node in the associated chain, wherein there is at least one multi-level mapping node in the associated chain.

[0094] It can be understood that connecting all associated multi-level mapping nodes forms an association chain, so that corresponding sequence labels can be added to each node in order of the node level, such as from left to right, and there is at least one multi-level mapping node in the association chain.

[0095] The association chain is a chain formed by connecting the associated multi-level mapping nodes, and the sequence label is an information label added to each multi-level mapping node in sequence, such as information labels 1, 2, 3, etc.

[0096] B3 counts the maximum values ​​of the order in the order labels to generate a corresponding number of X-axis coordinates, and counts the number of associated chains to generate a corresponding number of multiple Y-axis coordinates.

[0097] It can be understood that in order to determine the maximum setting value of the X-axis coordinate, the maximum value of the sequence in the sequence label can be counted, wherein the maximum value of the sequence represents the number of multi-level mapping nodes in the longest associated chain. At the same time, in order to obtain the maximum setting value of the Y-axis coordinate set in the vertical direction, the number of associated chains can be counted. Since the corresponding multi-level mapping nodes in each associated chain will only be arranged horizontally but not vertically, when the number of associated chains is determined, the maximum setting value of the Y-axis coordinate can be obtained.

[0098] The maximum value of the sequence is the maximum value of the number arrangement in the sequence label.

[0099] B4, receiving the position configured by the user for each association chain and generating a corresponding attribute mapping network.

[0100] It can be understood that the placement position of each association chain sent by the receiving server is used to place and arrange the multi-level mapping nodes of the corresponding association chain to obtain a corresponding attribute mapping network.

[0101] In some embodiments, it also includes: C1, counting the number of first nodes of all multi-level mapping nodes extracted between the first dividing line and the second dividing line, if the number of the first nodes is greater than or equal to a first preset number.

[0102] It can be understood that the first node quantity is the quantity of all multi-level mapping nodes between the first dividing line and the second dividing line, and the first preset quantity is a preset first quantity.

[0103] C2, the multi-level mapping nodes with the second hit times are arranged in reverse order, and the multi-level mapping nodes with the second hit times with the first fixed number at the front are selected and moved to the upper part of the second dividing line.

[0104] It can be understood that when the number of first nodes is greater than the first preset number, the multi-level mapping nodes corresponding to the second hit number can be arranged in reverse order. When it is determined that the number of multi-level mapping nodes to be adjusted is large, a first fixed number of multi-level mapping nodes located in the front will be selected and moved to the upper part of the second dividing line, so that the number of multi-level mapping nodes below the second dividing line will not be too large, which is convenient for subsequent traversal of the multi-level mapping nodes.

[0105] The first fixed number is a preset number value, which may be 20.

[0106] C3, counting the number of second nodes of all multi-level mapping nodes extracted to the lower part of the first segmentation line, if the number of the second nodes is greater than or equal to a second preset number.

[0107] It can be understood that the second node number is the number of all multi-level mapping nodes below the first dividing line, and the second preset number is the preset number of multi-level mapping nodes located below the first dividing line, which can be preset manually.

[0108] It is not difficult to understand that when it is determined that the number of second nodes is greater than or equal to the second preset number, the corresponding multi-level mapping nodes can be adjusted subsequently.

[0109] C4, the multi-level mapping nodes with the first hit count are arranged in reverse order, and the front second fixed number of multi-level mapping nodes with the first hit count are selected and moved to between the first dividing line and the second dividing line.

[0110] It can be understood that when the number of the second nodes is greater than the second preset number, the multi-level mapping nodes corresponding to the first hit number can be arranged in reverse order. When it is determined that the number of multi-level mapping nodes to be adjusted is large, a second fixed number of multi-level mapping nodes located in the front will be selected and moved between the first dividing line and the second dividing line, so that the number of multi-level mapping nodes below the first dividing line will not be too large, which is convenient for subsequent traversal of the multi-level mapping nodes.

[0111] The second fixed number is a preset number value, which may be 10.

[0112] It is not difficult to understand that, since the multi-level mapping nodes located under the first dividing line are also located under the second dividing line, when the multi-level mapping nodes under the first dividing line are moved, the first preset number will not be exceeded.

[0113] S3, the server identifies and verifies the data in the data collection template, performs tax verification on the target fixed assets based on the database, generates corresponding verification links and feeds them back to the user management end.

[0114] It can be understood that when the user management end fills the corresponding attribute information in the corresponding data collection template, it can be sent to the server, so that the server can identify and verify the data in the data collection template, such as scanning the barcode, QR code or identifying text in the data collection template, so that the tax information of the target fixed assets can be verified according to the information in the database, and a verification link can be generated and sent to the user management end, so that the user can intuitively view the information related to the target fixed assets.

[0115] Among them, the database is a tax information library that interacts with the server, including various types of fixed assets and related information, including but not limited to equipment type, name, date, etc. The verification link is a node link corresponding to the target fixed asset and generated after tax verification.

[0116] In some embodiments, the specific implementation of step S3 (the server identifies and verifies the data in the data collection template, performs tax verification on the target fixed assets based on the database, generates a corresponding verification link and feeds it back to the user management terminal) includes: S31, after receiving the data collection template after the user management terminal fills in the slot, the server calls at least one of the text recognition module, barcode recognition module, QR code recognition module and image recognition module to perform data recognition verification, and obtains the identity tag information, verification value information and verification period information of the corresponding target fixed asset.

[0117] It is understandable that after receiving the data collection template, multiple modules can be called to identify and verify the data in order to determine the various relevant information corresponding to the target fixed assets, facilitate subsequent tax verification and registration, and improve the efficiency of tax information processing.

[0118] Among them, the text recognition module is a module for recognizing text information, the barcode recognition module is a module for recognizing barcode information, the QR code recognition module is a module for recognizing QR code information, the image recognition module is a module for recognizing image information, such as the image information of the target fixed assets, the identity label information is the information of the type label corresponding to the target fixed assets, such as the experimental equipment label, electronic engineering equipment label information, etc., the verification value information is the value information of the fixed assets determined after verification, and the verification period information is the period information corresponding to the target fixed assets.

[0119] S32, performing tax verification by database comparison based on the identity tag information, verification value information, and verification period information, and generating tax value information of the tax verification, wherein the tax value information is an interval value, and each identity tag information, verification value information, and verification period information has preset tax value information.

[0120] It can be understood that by comparing the database based on the identity tag information, verification value information, and verification period information, the tax value information of the tax verification can be obtained. For example, when the identity of the target fixed asset is a computer, the market value of its new equipment is 9,000. Due to different computer brands, configurations, etc., the prices are also inconsistent. The verification period is the current moment and the number of years of use. Different years will cause different depreciation of fixed assets. Therefore, multiple types of information can be summed up to determine the corresponding tax value information, that is, an interval value.

[0121] Among them, the identity tag information, verification value information, and verification period information have preset tax value information. For example, the value of brand A is 8,000-10,000, the value of brand B is 7,000-7,500, the tax value information with a verification period of 1 year is a deduction of 1%, and the tax value information with a verification period of 5 years is a deduction of 50%, etc., so as to determine the tax value information of tax verification based on the identity tag information, verification value information, and verification period information.

[0122] S33, generates a verification link by counting all the compared data, identity tag information, verification value information, verification years information and tax value information in the database.

[0123] It can be understood that the multi-level mapping nodes corresponding to the data compared with the database, identity tag information, verification value information, verification year information and tax value information are connected to generate a verification link.

[0124] S4, the user management terminal fills in the corresponding active tax reporting information with reference to the verification link. If the active tax reporting information does not meet the verification link requirements, the associated data collection slot in the data collection template is highlighted.

[0125] It is understandable that the user management end can fill in the corresponding active tax reporting information based on the generated verification link. When it is determined that the active tax reporting information does not match the information in the verification link, the associated data collection slot in the data collection module can be highlighted so that personnel can intuitively see that the information corresponding to the slot does not match and an abnormality occurs, which facilitates data verification again and improves the efficiency of tax data processing.

[0126] Among them, the active tax reporting information is the tax data information actively input by the user, for example, it can be an asset data table, or it can be data information actively filled in by personnel, including asset name, age, name, etc.

[0127] For example, when the actively entered years are different from the verified years information collected in the database, the slot of the associated years information in the data collection template can be highlighted so that subsequent personnel can quickly view the abnormal data.

[0128] In some embodiments, the specific implementation of step S4 (the user management terminal fills in the corresponding active tax reporting information with reference to the verification link, and if the active tax reporting information does not meet the verification link requirements, the associated data collection slot in the data collection template is highlighted) includes: S41, if it is determined that the value of the active tax reporting information is not within the range of the tax value information, the corresponding data collection slot is retrieved and the data collection slot is highlighted.

[0129] It is understandable that when it is determined that the value of the active tax reporting information is not within the range of the tax value information, the corresponding associated data collection slot can be retrieved for highlighting, for example, the color of the corresponding slot box can be replaced for easier viewing by personnel.

[0130] like Figure 2 As shown, the present invention provides a schematic diagram of the structure of a tax data processing device, the tax data processing device comprising: The request module is used to enable the server to obtain the user's identity tag and generate a corresponding management plug-in and send it to the user management terminal.

[0131] The judgment module is used to enable the user management end to interact with the management plug-in after judging that there is a target fixed asset. The management plug-in generates a corresponding data collection template based on the attributes of the fixed asset and performs data collection.

[0132] The feedback module is used to enable the server to identify and verify the data in the data collection template, perform tax verification on the target fixed assets based on the database, and generate corresponding verification links to feedback to the user management end.

[0133] The verification module is used to enable the user management end to fill in the corresponding active tax reporting information with reference to the verification link. If the active tax reporting information does not meet the verification link requirements, the associated data collection slot in the data collection template is highlighted.

[0134] The present invention also provides a storage medium, in which a computer program is stored. When the computer program is executed by a processor, it is used to implement the methods provided by the various embodiments described above.

[0135] Among them, the storage medium can be a computer storage medium or a communication medium. The communication medium includes any medium that facilitates the transmission of a computer program from one place to another. The computer storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer. For example, the storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an application-specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). In addition, the ASIC can be located in a user device. Of course, the processor and the storage medium can also exist in a communication device as discrete components. The storage medium can be a read-only memory (ROM), a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0136] The present invention also provides a program product, which includes an execution instruction, which is stored in a storage medium. At least one processor of a device can read the execution instruction from the storage medium, and at least one processor executes the execution instruction so that the device implements the methods provided in the above various embodiments.

[0137] In the above-mentioned terminal or server embodiments, it should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly implemented as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0138] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A tax data processing method, characterized in that: include: After obtaining the user's identity tag, the server generates a corresponding management plug-in and sends it to the user management terminal; After determining that there is a target fixed asset, the user management terminal interacts with the management plug-in, and the management plug-in generates a corresponding data collection template based on the attributes of the fixed asset and performs data collection; The server identifies and verifies the data in the data collection template, performs tax verification on the target fixed assets based on the database, generates corresponding verification links and feeds them back to the user management end; The user management end fills in the corresponding active tax reporting information with reference to the verification link. If the active tax reporting information does not meet the verification link requirements, the associated data collection slot in the data collection template is highlighted.

2. The tax data processing method according to claim 1, characterized in that: After obtaining the user's identity tag, the server generates a corresponding management plug-in and sends it to the user management terminal, including: The user management terminal sends a fixed asset tax management request to the server, and the server obtains the user's identity tag, which includes at least a small-scale tag and a general taxpayer tag; Based on the small-scale label or the general taxpayer label, a corresponding management plug-in is determined and sent to the user management terminal.

3. The tax data processing method according to claim 1, characterized in that: The data collection template includes a plurality of data collection slots; The user management terminal interacts with the management plug-in after determining that there is a target fixed asset. The management plug-in generates a corresponding data collection template based on the attributes of the fixed asset and performs data collection, including: After determining that there is a target fixed asset, the user management terminal interacts with the management plug-in, selects the interactive column corresponding to the target fixed asset, and obtains the properties of the corresponding fixed asset; Generate a data collection template corresponding to the attributes of the fixed assets, each attribute of the fixed assets having a preset data collection template; Determine the image acquisition slots and text acquisition slots in the data acquisition template, generate corresponding processing links according to the attributes of each image acquisition slot and text acquisition slot, and the processing links are used to call processing functions to perform associated processing on the associated image acquisition slots and text acquisition slots.

4. The tax data processing method according to claim 3, characterized in that: The step of determining the image acquisition slot and the text acquisition slot in the data acquisition template, and generating corresponding processing links according to the attributes of each image acquisition slot and the text acquisition slot, wherein the processing links are used to call processing functions to perform associated processing on the associated image acquisition slot and the text acquisition slot, includes: Obtain the attributes of each image acquisition slot and text acquisition slot, and input them into the attribute mapping network corresponding to the attributes of the fixed assets; The attribute mapping network includes two-dimensional multi-level mapping nodes with levels from low to high, and the attribute mapping network is divided into a horizontal node comparison sub-strategy and a vertical node comparison sub-strategy based on a pre-trained comparison strategy; Based on the horizontal node comparison sub-strategy and the vertical node comparison sub-strategy, the multi-level mapping nodes in the attribute mapping network are optimized and traversed, and if it is determined that they correspond to the attributes of the image acquisition slot and the text acquisition slot, they are selected; After determining that all image acquisition slots and text acquisition slots have been traversed, the selected multi-level mapping nodes are retained. If it is determined that the retained multi-level mapping nodes have a mapping relationship, the corresponding processing links are called. Each mapping connection in the attribute mapping network has a preset processing link.

5. The tax data processing method according to claim 4, characterized in that: The optimizing traversal processing of the multi-level mapping nodes in the attribute mapping network based on the horizontal node comparison sub-strategy and the vertical node comparison sub-strategy, if it is determined to correspond to the attributes of the image acquisition slot and the text acquisition slot, includes: The two-dimensional multi-level mapping nodes are in the first quadrant of the coordinate axis, and the levels of the multi-level mapping nodes in the positive direction of the X positive coordinate axis and the Y positive coordinate axis increase in sequence; First, traverse multiple multi-level mapping nodes that lock the smallest X-axis coordinate, and traverse each multi-level mapping node in turn along the positive direction of the Y axis until the first segmentation line is determined; After determining the first segmentation line, traverse the next multiple multi-level mapping nodes of the X-axis coordinate backward, and traverse each multi-level mapping node in turn along the positive direction of the Y-axis again until another first segmentation line is determined; Repeat the above steps until all the multi-level mapping nodes corresponding to the image acquisition slots and text acquisition slots are determined, and the segmentation lines in the vertical node comparison sub-strategy are optimized.

6. The tax data processing method according to claim 5, characterized in that: Also includes: If it is determined that after traversing the multi-level mapping node corresponding to the last X-axis coordinate in the positive direction of the X-axis, and after determining another first segmentation line in the positive direction of the Y-axis; Lock the smallest X-axis coordinate again and traverse the corresponding multi-level mapping nodes again with the first segmentation line as the starting point until another second segmentation line is determined and the traversal stops or all multi-level mapping nodes are traversed and the traversal stops; After determining the second segmentation line, traverse the next multiple multi-level mapping nodes of the X-axis coordinate backward, and traverse each multi-level mapping node in turn along the positive direction of the Y-axis until another second segmentation line is determined or all multi-level mapping nodes are traversed and the traversal stops.

7. The tax data processing method according to claim 5, characterized in that: The attribute mapping network is generated through the following steps, including: Receiving the attributes of the fixed assets configured by the server, and the multi-level mapping nodes with preset associations corresponding to the attributes of the corresponding fixed assets; Obtain all associated multi-level mapping nodes to form an associated chain, and add corresponding sequence labels according to the order of each node in the associated chain, wherein there is at least one multi-level mapping node in the associated chain; Count the maximum values ​​of the order in the order label to generate a corresponding number of X-axis coordinates, and count the number of associated chains to generate a corresponding number of multiple Y-axis coordinates; The corresponding attribute mapping network is generated by receiving the position configured by the user for each association chain.

8. The tax data processing method according to claim 7, characterized in that: The above steps are repeated until all the multi-level mapping nodes corresponding to the image acquisition slots and the text acquisition slots are determined, and the segmentation lines in the vertical node comparison sub-strategy are optimized, including: After determining the preset time interval, obtaining the traversal hit count of each multi-level mapping node within the first dividing line of each X-axis coordinate to obtain the first hit count, obtaining the traversal hit count of each multi-level mapping node between the first dividing line and the second dividing line to obtain the second hit count, and obtaining the traversal hit count of each multi-level mapping node above the second dividing line to obtain the third hit count; Extract the minimum second hit count, compare the third hit counts of all multi-level mapping nodes with the minimum second hit count, extract the multi-level mapping nodes with a second hit count greater than the minimum to between the first dividing line and the second dividing line, and place the multi-level mapping node with the minimum second hit count on the upper part of the second dividing line; The minimum first hit count is extracted, the second hit counts of all multi-level mapping nodes are compared with the minimum first hit count, and the multi-level mapping nodes with a number greater than the minimum first hit count are extracted to the lower part of the first dividing line to obtain the attribute mapping network after the dividing line position is optimized.

9. The tax data processing method according to claim 8, characterized in that: Also includes: Counting the number of first nodes of all multi-level mapping nodes extracted between the first dividing line and the second dividing line, if the number of the first nodes is greater than or equal to a first preset number; Then, the multi-level mapping nodes with the second hit count are arranged in reverse order, and the multi-level mapping nodes with the second hit count with the first fixed number at the front are selected and moved to the upper part of the second dividing line; Counting the number of second nodes of all multi-level mapping nodes extracted to the lower part of the first segmentation line, if the number of the second nodes is greater than or equal to a second preset number; Then, the multi-level mapping nodes with the first hit count are arranged in reverse order, and the front second fixed number of multi-level mapping nodes with the first hit count are selected and moved between the first dividing line and the second dividing line.

10. The tax data processing method according to claim 1, characterized in that: The server identifies and verifies the data in the data collection template, performs tax verification on the target fixed assets based on the database, generates a corresponding verification link and feeds it back to the user management end, including: After receiving the data collection template filled with slots by the user management terminal, the server calls at least one of the text recognition module, the barcode recognition module, the QR code recognition module and the image recognition module to perform data recognition verification, and obtains the identity tag information, verification value information and verification period information of the corresponding target fixed asset; Based on the identity tag information, verification value information, and verification period information, a tax verification is performed by comparing the database to generate tax value information for the tax verification, wherein the tax value information is an interval value, and each identity tag information, verification value information, and verification period information has a preset tax value information; A verification link is generated by counting all the compared data, identity tag information, verification value information, verification years information and tax value information in the database.

11. The tax data processing method according to claim 10, characterized in that: The user management terminal fills in the corresponding active tax declaration information with reference to the verification link. If the active tax declaration information does not meet the verification link requirements, the associated data collection slot in the data collection template is highlighted, including: If it is determined that the value of the active tax reporting information is not within the range of the tax value information, the corresponding data collection slot is retrieved and the data collection slot is highlighted.

12. A tax data processing device, characterized in that: include: The request module is used to enable the server to obtain the user's identity tag and generate a corresponding management plug-in to send to the user management terminal; A judgment module is used to enable the user management end to interact with the management plug-in after judging that there is a target fixed asset, and the management plug-in generates a corresponding data collection template based on the attributes of the fixed asset and performs data collection; Feedback module, used to enable the server to identify and verify the data in the data collection template, conduct tax verification on the target fixed assets based on the database, generate corresponding verification links and feedback to the user management end; The verification module is used to enable the user management end to fill in the corresponding active tax reporting information with reference to the verification link. If the active tax reporting information does not meet the verification link requirements, the associated data collection slot in the data collection template is highlighted.

13. An electronic device, characterized in that: include: A memory, a processor, and a computer program, wherein the computer program is stored in the memory, and the processor runs the computer program to execute the method according to any one of claims 1 to 11.

14. A storage medium, characterized in that The storage medium stores a computer program, which is used to implement the method according to any one of claims 1 to 11 when executed by a processor.

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