Tax Data Processing Method, Device, Computer Equipment and Storage Medium

Abstract

The present invention provides a tax data processing method, device, computer equipment and storage medium, relating to data processing technology. After obtaining the identity tag of a user, 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 conducts data collection; the server identifies and verifies the data in the data collection template, conducts tax verification on the target fixed asset based on the database, and generates a corresponding verification link and feeds it back to the user management terminal; the user management terminal fills in the corresponding active tax filing information with reference to the verification link. If the active tax filing information does not meet the requirements of the verification link, the associated data collection slots in the data collection template are highlighted. It can automatically process corresponding tax data according to different user tax identities, improving the efficiency of tax data processing.

Description

Technical Field

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

[0002] With the continuous advancement of the digitalization process of tax management, the tax management of fixed assets has gradually become one of the core links in tax management. Fixed assets have characteristics such as high value, complex depreciation, and long usage cycles, and their tax processing directly affects the accounting compliance of enterprises and the accuracy of tax declarations. 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 return information has become an important challenge in enterprise tax management.

[0003] Currently, the tax processing of enterprises' fixed assets mainly relies on traditional manual management models and some single tool assistance. Manual management requires a large amount of form filling, manual comparison, and verification, which greatly increases the workload, affects the efficiency and accuracy of tax declarations, and is prone to data errors or omissions.

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

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

[0006] In a first aspect of the present invention, a method for processing tax data is provided, including:

[0007] After obtaining the identity tag of the user, the server generates a corresponding management plugin and sends it to the user management terminal;

[0008] After the user management terminal determines that there is a target fixed asset, it interacts with the management plugin, and the management plugin generates a corresponding data collection template based on the attributes of the fixed asset and performs data collection;

[0009] The server identifies and validates the data in the data collection template, and performs tax verification on the target fixed asset based on the database to generate a corresponding verification link and feedback it to the user management terminal;

[0010] The user management terminal fills in the corresponding proactive tax return information with reference to the verification link. If the proactive tax return information does not meet the requirements of the verification link, the associated data collection slots in the data collection template are highlighted.

[0011] Optionally, in a possible implementation of the first aspect, after the server obtains the identity tag of the user, it generates a corresponding management plugin and sends it to the user management terminal, including:

[0012] The user management terminal sends a fixed asset tax management request to the server, and the server obtains the identity tag of the user. The identity tag includes at least a small-scale tag and a general taxpayer tag;

[0013] Based on the small-scale tag or the general taxpayer tag, a corresponding management plugin is determined and sent to the user management terminal.

[0014] Optionally, in a possible implementation of the first aspect, the data collection template includes multiple data collection slots;

[0015] After the user management terminal determines that there is a target fixed asset, it interacts with the management plugin. The management plugin generates a corresponding data collection template based on the attributes of the fixed asset and performs data collection, including:

[0016] After the user management terminal determines that there is a target fixed asset, it interacts with the management plugin, selects the interaction column corresponding to the target fixed asset, and obtains the attributes of the corresponding fixed asset;

[0017] Generate a data collection template corresponding to the attributes of the fixed asset. Each fixed asset has a preset data collection template;

[0018] Determine the image collection slots and text collection slots in the data collection template, and generate corresponding processing links according to the attributes of each image collection slot and text collection slot. The processing links are used to call processing functions to perform associated processing on the associated image collection slots and text collection slots.

[0019] Optionally, in a possible implementation of the first aspect, the determining the image collection slots and text collection slots in the data collection template, and generating corresponding processing links according to the attributes of each image collection slot and text collection slot. The processing links are used to call processing functions to perform associated processing on the associated image collection slots and text collection slots, includes:

[0020] Obtain the attributes of each image collection slot and text collection slot, and input them into the attribute mapping network corresponding to the attributes of the fixed asset;

[0021] The attribute mapping network includes multi-level mapping nodes in two dimensions with levels from low to high. Based on a pre-trained comparison strategy, the attribute mapping network is divided into a horizontal node comparison sub-strategy and a vertical node comparison sub-strategy;

[0022] Based on the horizontal node comparison sub-strategy and the vertical node comparison sub-strategy, perform an optimized traversal process on the multi-level mapping nodes in the attribute mapping network. If it is determined that they correspond to the attributes of the image acquisition slot and the text acquisition slot, then select them;

[0023] 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, then retrieve the corresponding processing link. Each mapping connection in the attribute mapping network has a preset processing link.

[0024] Optionally, in a possible implementation manner of the first aspect, the performing an optimized traversal process on 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, and if it is determined that they correspond to the attributes of the image acquisition slot and the text acquisition slot, includes:

[0025] 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 sequentially in the positive directions of the X-axis and the Y-axis;

[0026] First, traverse and lock multiple multi-level mapping nodes with the smallest X-axis coordinate, and sequentially traverse each multi-level mapping node in the positive direction of the Y-axis until the first dividing line is determined;

[0027] After determining the first dividing line, traverse the multiple multi-level mapping nodes with the next X-axis coordinate backward, and again sequentially traverse each multi-level mapping node in the positive direction of the Y-axis until another first dividing line is determined;

[0028] Repeat the above steps until all multi-level mapping nodes corresponding to the image acquisition slots and the text acquisition slots are determined, and optimize the dividing line in the vertical node comparison sub-strategy.

[0029] Optionally, in a possible implementation manner of the first aspect, it further includes:

[0030] If it is determined that after traversing the multi-level mapping nodes corresponding to the last X-axis coordinate in the positive direction of the X-axis, and after determining another first dividing line in the positive direction of the Y-axis;

[0031] Lock the smallest X-axis coordinate again and start traversing the corresponding multi-level mapping nodes from the first dividing line until another second dividing line is determined and then stop traversing or stop traversing after traversing all multi-level mapping nodes;

[0032] After determining the second dividing line, traverse the multiple multi-level mapping nodes with the next X-axis coordinate backward, and again sequentially traverse each multi-level mapping node in the positive direction of the Y-axis until another second dividing line is determined or stop traversing after traversing all multi-level mapping nodes.

[0033] Optionally, in a possible implementation of the first aspect, generating an attribute mapping network through the following steps, including:

[0034] 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;

[0035] Obtaining all associated multi-level mapping nodes to form an association chain, adding corresponding sequence tags in the order of each node in the association chain, and there is at least one multi-level mapping node in the association chain;

[0036] Counting the maximum value in the sequence tags to generate the corresponding number of X-axis coordinates, and counting the number of association chains to generate the corresponding number of multiple Y-axis coordinates;

[0037] Receiving the positions configured by the user for each association chain to generate the corresponding attribute mapping network.

[0038] Optionally, in a possible implementation of the first aspect, repeating the above steps until all multi-level mapping nodes corresponding to the image acquisition slots and text acquisition slots are determined, and optimizing the dividing line in the vertical node comparison sub-strategy, including:

[0039] After judging and waiting for a preset time period, obtaining the traversal hit times of each multi-level mapping node within the first dividing line of each X-axis coordinate to obtain the first hit times, the traversal hit times of each multi-level mapping node between the first dividing line and the second dividing line to obtain the second hit times, and the traversal hit times of each multi-level mapping node above the second dividing line to obtain the third hit times;

[0040] Extracting the smallest second hit times, comparing the third hit times of all multi-level mapping nodes with the smallest second hit times, extracting the multi-level mapping nodes greater than the smallest second hit times between the first dividing line and the second dividing line, and placing the multi-level mapping nodes with the smallest second hit times above the second dividing line;

[0041] Extracting the smallest first hit times, comparing the second hit times of all multi-level mapping nodes with the smallest first hit times, and extracting the multi-level mapping nodes greater than the smallest first hit times below the first dividing line to obtain the attribute mapping network after optimizing the dividing line position.

[0042] Optionally, in a possible implementation of the first aspect, it further includes:

[0043] Counting the number of the 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 the first preset number;

[0044] Then, reverse the order of the multi-level mapping nodes of the second hit count, and select the first fixed number of multi-level mapping nodes of the second hit count in the front part to move them above the second dividing line;

[0045] Count the second node quantity of all the multi-level mapping nodes extracted below the first dividing line. If the second node quantity is greater than or equal to the second preset quantity;

[0046] Then, reverse the order of the multi-level mapping nodes of the first hit count, and select the second fixed number of multi-level mapping nodes of the first hit count in the front part to move them between the first dividing line and the second dividing line.

[0047] Optionally, in a possible implementation manner of the first aspect, the server identifies and verifies the data in the data collection template, and performs tax verification on the target fixed assets based on the database to generate a corresponding verification link and feedback it to the user management end, including:

[0048] After receiving the data collection template filled with slots by the user management end, the server calls at least one of the character recognition module, barcode recognition module, two-dimensional code recognition module, and image recognition module to perform data identification and verification, and obtains the identity label information, verification value information, and verification year information of the corresponding target fixed assets;

[0049] Perform tax verification by comparing with the database based on the identity label information, verification value information, and verification year information, and generate tax value information for tax verification. The tax value information is an interval value, and each identity label information, verification value information, and verification year information has a preset tax value information;

[0050] Count all the compared data, identity label information, verification value information, verification year information, and tax value information in the database to generate a verification link.

[0051] Optionally, in a possible implementation manner of the first aspect, the user management end fills in the corresponding active tax declaration information with reference to the verification link. If the active tax declaration information does not meet the requirements of the verification link, the associated data collection slots in the data collection template are highlighted, including:

[0052] If it is determined that the value of the active tax declaration information is not within the interval of the tax value information, the corresponding associated data collection slot is retrieved and the data collection slot is highlighted.

[0053] In the second aspect of the present invention, a tax data processing device is provided, including:

[0054] A request module, configured to enable the server to generate a corresponding management plugin after obtaining the identity label of the user and send it to the user management end;

[0055] A judgment module, which is used to enable the user management terminal to interact 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 conducts data collection;

[0056] A feedback module, which is used to enable the server to identify and verify the data in the data collection template, and generate a corresponding verification link for tax verification of the target fixed asset based on the database and feedback it to the user management terminal;

[0057] A verification module, which is used to enable the user management terminal to fill in the corresponding active tax declaration information with reference to the verification link. If the active tax declaration information does not meet the requirements of the verification link, the associated data collection slots in the data collection template are highlighted.

[0058] In the third aspect of the present invention, a storage medium is provided. 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 foregoing method.

[0059] The beneficial effects of the present invention are as follows:

[0060] 1. The present invention can automatically process corresponding tax data according to different user tax identities, improving the efficiency of tax data processing. This method can automatically identify the user identity and generate an adapted management plug-in, and generate a highly relevant data collection template based on the attributes of the fixed asset, 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 a verification link, supplemented by intelligent feedback and data highlighting functions, guiding users to accurately fill in tax declaration information, and finally realizing the high efficiency, accuracy and intelligence of fixed asset tax management.

[0061] 2. The present invention can dynamically generate management plugins to enhance the adaptability and convenience of tax management. Among them, the present invention sends a fixed asset tax management request from the user management terminal to the server. The server dynamically generates corresponding management plugins according to the user's identity tags, such as small-scale taxpayers or general taxpayers, and returns them to the user management terminal, realizing accurate identification and classification management of user identities. The system can provide customized tax management functions according to different user needs. Through the generation of dynamic management plugins, the adaptability of tax management can be effectively improved, the management terminal interface can be made clearer and more concise, and at the same time, the operation complexity of users can be reduced, significantly improving the efficiency of fixed asset tax management. Secondly, the present invention interacts with the user management terminal through the management plugin, dynamically generates a data collection template for the attributes of the target fixed asset. The template contains an image collection slot and a text collection slot, and designs an attribute mapping network to optimize the traversal of multi-level mapping nodes of the slots. Through 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, through the optimization of 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.

[0062] 3. The present invention can intelligently verify data to improve the accuracy and guidance of tax declaration. Among them, after the server receives the data collection template filled by the user management terminal, 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 year information of the target fixed asset, and compares them with the database to generate a tax verification result; at the same time, the system feedbacks the verification result in the form of a verification link to provide clear tax filing reference information for users. When users fill in and actively file tax information, if the data does not meet the verification requirements, the system automatically highlights the associated slots in the template and guides users to correct them, thereby improving the guidance and convenience of tax filing operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 is a flowchart of a tax data processing method provided by the present invention;

[0064] Figure 2 is a schematic structural diagram of a tax data processing device provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0065] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0066] The terms "first", "second", "third", "fourth", etc. (if any) in the description, claims and the above-mentioned drawings of the present invention are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein.

[0067] It should be understood that in various embodiments of the present invention, the magnitude of the serial numbers of the various processes does not mean the order of execution, and the order of execution of the various processes should be determined by their functions and internal logics, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0068] It should be understood that in the present invention, "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0069] It should be understood that in the present invention, "a plurality of" means two or more. "And / or" is merely a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally represents an "or" relationship between the associated objects before and after. "Including A, B and C" and "including A, B, C" mean that all of A, B and C are included. "Including A, B or C" means including any one of A, B and C. "Including A, B and / or C" means including any one or any two or all three of A, B and C.

[0070] It should be understood that in the present invention, "B corresponding to A", "B corresponding to A relatively", "A corresponding to B relatively" or "B corresponding to A relatively" means that B is associated with A, and B can be determined according to A. Determining B according to A does not mean determining B only according to A, and B can also be determined according to A and / or other information. The matching of A and B means that the similarity between A and B is greater than or equal to a preset threshold.

[0071] Depending on the context, as used herein, "if" can be interpreted as "when", "while", "in response to determining", or "in response to detecting".

[0072] The technical solutions of the present invention will be described in detail below with specific embodiments. These several specific embodiments below can be combined with each other, and the same or similar concepts or processes may not be described in some embodiments.

[0073] As Figure 1 shown, the present invention provides a method for processing tax data, including:

[0074] S1. After the server obtains the identity tag of the user, it generates a corresponding management plugin and sends it to the user management terminal.

[0075] It can be understood that when the user needs to conduct tax declaration processing for fixed assets, the server may obtain the identity tag and generate the corresponding management plugin and send it to the user management terminal for subsequent collection of relevant data for analysis and processing.

[0076] Among them, the user management terminal is the user information terminal for tax declaration. For example, it can be the computer of the tax declaration user. The identity tag is the tag of the user identity type. For example, it can be a general taxpayer or a small-scale enterprise tag, etc. The management plugin is a plugin for data management and processing.

[0077] Through the above implementation manner, the present invention can generate a management plugin according to the user identity tag and send it to the user management terminal, so as to improve the data processing efficiency of fixed asset tax data through the management plugin subsequently.

[0078] In some embodiments, the specific implementation manner of (the server obtains the identity tag of the user and generates a corresponding management plugin and sends it to the user management terminal) in step S1 includes:

[0079] S11. The user management terminal sends a fixed asset tax management request to the server, and the server obtains the identity tag of the user. The identity tag at least includes a small-scale tag and a general taxpayer tag.

[0080] 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 at least includes a small-scale tag and a general taxpayer tag.

[0081] It is not difficult to understand that the information content and required materials of tax data corresponding to different identity tags are somewhat different. For example, a general taxpayer can generate deduction information, while a user with a small-scale tag does not have deduction information, that is, does not generate corresponding deduction information. Thus, the identity tag of the user can be obtained to subsequently generate a management plugin for corresponding information according to the identity tag, so as to improve the accuracy and efficiency of personnel's tax handling.

[0082] S12. Based on the small-scale tag or general taxpayer tag, determine the corresponding management plugin and send it to the user management terminal.

[0083] It can be understood that the corresponding management plug-in generated according to the corresponding identity tag is sent to the user management end, so that the relevant tax data of the user can be processed through the management plug-in subsequently, improving the accuracy and timeliness of the user's tax data processing.

[0084] S2. After the user management end determines that it has the target fixed assets, it interacts with the management plug-in. The management plug-in generates a corresponding data collection template based on the attributes of the fixed assets and conducts data collection.

[0085] It can be understood that when the user management end determines that it has the target fixed assets, it conducts information interaction 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.

[0086] Among them, the data collection template is a template for collecting data, which can be a data table with multiple data collection slots, and the data collection slot is a slot for collecting data.

[0087] Through the above implementation manner, the present invention can generate a data collection template corresponding to the attributes of the fixed assets and conduct data collection, so as to process the data information collected and filled into the data collection slots subsequently and complete the handling of tax data.

[0088] In some embodiments, the specific implementation manner of (the user management end interacts with the management plug-in after determining that it has the target fixed assets, and the management plug-in generates a corresponding data collection template based on the attributes of the fixed assets and conducts data collection) in step S2 includes:

[0089] S21. After the user management end determines that it has the target fixed assets, it interacts with the management plug-in, selects the interaction column corresponding to the target fixed assets, and obtains the attributes of the corresponding fixed assets.

[0090] It should be noted that the user management end is used by the management personnel for real-time verification. When it is found that a person purchases a device and the purchaser does not file a tax return, the corresponding device information can be sent to the accounting personnel for tax filing. Therefore, when it is determined that there are target fixed assets, information interaction is conducted with the management plug-in to select the interaction column corresponding to the target fixed assets and determine the corresponding attributes according to the target fixed assets, so as to generate a corresponding data collection template through the attributes of the fixed assets subsequently for facilitating data collection.

[0091] It can be understood that the target fixed assets are the fixed assets that need to be appraised, such as engineering equipment, electronic equipment, etc. The interactive columns are the items for terminal information interaction, and the attributes of the fixed assets are the corresponding attribute information of the target fixed assets. For example, when the target fixed asset is a computer, the corresponding attribute is the computer attribute; when the target fixed asset is experimental equipment, the corresponding attribute is the experimental equipment attribute.

[0092] It is not difficult to understand that if there are corresponding equipment and instruments in the management plugin, the corresponding equipment and instruments in the management plugin can be selected according to the determined target fixed assets, so as to generate the corresponding data collection template for subsequent data collection.

[0093] S22, generate 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 multiple data collection slots.

[0094] It can be understood that a corresponding data collection template is generated according to the attributes of the fixed assets. Among them, each attribute of the fixed assets has a pre-set data collection template, such as barcodes, QR codes, photos, etc. Different attributes have corresponding data collection templates.

[0095] S23, determine the image collection slots and text collection slots in the data collection template, and generate corresponding processing links according to the attributes of each image collection slot and text collection slot. The processing links are used to call the processing function to perform the associated processing of collecting the associated image collection slots and text collection slots.

[0096] It can be understood that the data collection template contains image collection slots and text collection slots. Among them, the image collection slots are the slots for collecting images, and the text collection slots are the slots for collecting the text names of the equipment. Moreover, there is a correlation between the image collection slots and the text collection slots. Therefore, corresponding processing links can be generated according to the attributes between different slots, so as to obtain the collection data corresponding to the target fixed assets and improve the data processing efficiency.

[0097] Among them, the processing link is the slot link for data processing, and the processing function is the function information for data processing.

[0098] It is not difficult to understand that the image collection slots can scan barcodes to automatically generate corresponding attributes, which are then filled in the text collection slots to facilitate subsequent personnel to check the equipment information in the background.

[0099] In some embodiments, the specific implementation of (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 being used to call processing functions to perform associated processing on the associated image acquisition slots and text acquisition slots) in step S23 includes:

[0100] S231, obtain the attributes of each image acquisition slot and text acquisition slot, and input them into an attribute mapping network corresponding to the attributes of the fixed assets.

[0101] It can be understood that each image acquisition slot and text acquisition slot has a corresponding attribute. For example, the attribute of an image acquisition slot can be the barcode of an experimental device, and the text acquisition slot corresponding to it contains the text name attribute information of each experimental device. Therefore, the attributes of the image acquisition slot and the text acquisition slot can be mapped in the attribute mapping network to generate corresponding processing links later.

[0102] Among them, the attribute mapping network is an information node network mapped with various attribute information.

[0103] S232, the attribute mapping network includes multi-level mapping nodes with two dimensions from low to high. Based on a pre-trained comparison strategy, the attribute mapping network is divided into a horizontal node comparison sub-strategy and a vertical node comparison sub-strategy.

[0104] It can be understood that since the attribute mapping network includes multi-level two-dimensional mapping nodes, in order to improve the accuracy of data processing, the multi-level mapping nodes in the attribute mapping network can be divided. The nodes in the same row are used as horizontal nodes, and the nodes in the same column are 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 and analyze the data of the vertical nodes in the attribute mapping network.

[0105] Among them, the multi-level mapping nodes are nodes with multiple levels of mapping information.

[0106] 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 text acquisition slots. One multi-level mapping node corresponds to one type of slot and is preset. When a device corresponds to 6 slots, 6 nodes can be selected and the remaining nodes can be deleted.

[0107] S233. Optimize and traverse 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 they correspond to the attributes of the image acquisition slot and the text acquisition slot, select them.

[0108] 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. In order to determine that when they correspond to the attributes in the collected image acquisition slot and text acquisition slot, the node can be selected, which is convenient for subsequently selecting all relevant nodes and deleting the remaining nodes. Thus, it is convenient to generate corresponding processing links subsequently and improve the processing efficiency of tax data.

[0109] In some embodiments, the specific implementation of step S233 (optimize and traverse 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 they correspond to the attributes of the image acquisition slot and the text acquisition slot) includes:

[0110] S2331. The two-dimensional multi-level mapping nodes are in the first quadrant of the coordinate axis. The levels of the multi-level mapping nodes increase sequentially in the positive directions of the X-axis and the Y-axis.

[0111] It can be understood that all two-dimensional multi-level mapping nodes are located in the first quadrant of the coordinate axis. At the same time, the levels of the corresponding multi-level mapping nodes gradually increase in the positive directions of the X-axis and the Y-axis. That is, the higher the level of the multi-level mapping node is, the farther it is from the origin position in the horizontal direction, and the higher the level of the multi-level mapping node is, the farther it is from the origin position in the vertical direction.

[0112] It is not difficult to understand that since the multi-level mapping nodes have corresponding asset attribute information, the level will not be negative. Thus, all multi-level mapping nodes are located in the first quadrant of the coordinate axis.

[0113] S2332. First, traverse and lock multiple multi-level mapping nodes with the smallest X-axis coordinates, and traverse each multi-level mapping node in turn in the positive direction of the Y-axis until the first dividing line is determined.

[0114] It can be understood that a column of multi-level mapping nodes with the smallest X-axis coordinates can be determined first, and the multi-level mapping nodes can be traversed in turn in the positive direction of the Y-axis until the first dividing line is traversed, and then the traversal of this column of multi-level mapping nodes is stopped.

[0115] Among them, the first dividing line is a line segment that divides multi-level mapping nodes, which can be preset. Since there are a large number of nodes in the attribute mapping network, it is impossible to traverse all the nodes in the same column in sequence. When the corresponding node is in another column, infinite traversal of the same column will greatly increase the traversal time and affect the data processing efficiency. Therefore, the traversal of nodes can be intermittently divided by the first dividing line so that the horizontal nodes can be traversed and compared smoothly subsequently.

[0116] S2333. Determine multiple multi-level mapping nodes with the next X-axis coordinate for backward traversal of the first dividing line, and then traverse each multi-level mapping node in sequence in the positive direction of the Y-axis until another first dividing line is determined.

[0117] It can be understood that after the first dividing line is recognized, the position can be horizontally moved to the multi-level mapping nodes corresponding to the next X-axis column, and the traversal of the multi-level mapping nodes is carried out in sequence in the positive direction of the Y-axis again until the traversal of the nodes in this column stops after the first dividing line in this column is determined, so as to subsequently determine the multi-level mapping nodes corresponding to the image acquisition slot and the text acquisition slot among many nodes.

[0118] 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 optimize the dividing line in the vertical node comparison sub-strategy.

[0119] It can be understood that repeat the above implementation steps of traversing and comparing the multi-level mapping nodes 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 optimize the dividing line between the multi-level mapping nodes in the vertical node comparison sub-strategy, so that the position of the first dividing line is more reasonable, which is convenient for subsequent comparison and traversal of the multi-level mapping nodes and improves the selection efficiency of the nodes.

[0120] In some embodiments, the specific implementation manner of (repeating the above steps until all the multi-level mapping nodes corresponding to the image acquisition slots and the text acquisition slots are determined, and optimizing the dividing line in the vertical node comparison sub-strategy) in step S2334 includes:

[0121] S23341. After a preset time period is judged to pass, obtain the first hit count of the traversal hit count of each multi-level mapping node within the first dividing line of each X-axis coordinate, the second hit count of the traversal hit count of each multi-level mapping node between the first dividing line and the second dividing line, and the third hit count of the traversal hit count of each multi-level mapping node above the second dividing line.

[0122] It can be understood that the interval preset time period is the time period of the traversal interval preset in advance, the traversal hit count is the number of times selected when traversing the nodes, 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 adjacent above the first dividing line among 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, and the third hit count is the traversal hit count of each multi-level mapping node above the second dividing line.

[0123] It is not difficult to understand that the hit counts corresponding to the multi-level mapping nodes between different dividing lines are obtained, so as to subsequently adjust the positions of the dividing line segments according to the hit counts, in order to reduce the time of data traversal.

[0124] S23342, extract the smallest second hit count, compare the third hit counts of all multi-level mapping nodes with the smallest second hit count, extract the multi-level mapping nodes greater than the smallest second hit count between the first dividing line and the second dividing line, and place the multi-level mapping nodes with the smallest second hit count above the second dividing line.

[0125] It can be understood that the smallest count corresponding to the second hit count is determined, so as to subsequently move the multi-level mapping nodes above the second dividing line whose third hit count is greater than the second hit count downward to between the first dividing line and the second dividing line, and place the multi-level mapping nodes with the smallest second hit count above the second dividing line. By dynamically adjusting the positions of the multi-level mapping nodes according to the hit counts, the multi-level mapping nodes with a large number of selected times can be adjusted downward, so as to reduce the traversal time and improve the data processing efficiency.

[0126] S23343, extract the smallest first hit count, compare the second hit counts of all multi-level mapping nodes with the smallest first hit count, extract the multi-level mapping nodes greater than the smallest first hit count below the first dividing line, and obtain the attribute mapping network after the position optimization processing of the dividing line.

[0127] It can be understood that the smallest count corresponding to the first hit count is determined, so as to subsequently move the multi-level mapping nodes above the first dividing line whose second hit count is greater than the first hit count downward to below the first dividing line, and place the multi-level mapping nodes with the smallest first hit count above the first dividing line. By dynamically adjusting the positions of the multi-level mapping nodes according to the hit counts, the multi-level mapping nodes with a large number of selected times can be adjusted downward, so as to reduce the time for subsequently traversing and selecting the attributes of the multi-level mapping nodes and improve the data processing efficiency.

[0128] 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, then retrieve the corresponding processing link. Each mapping connection line in the attribute mapping network has a preset processing link.

[0129] It can be understood that after traversing all the 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 link can be retrieved. Among them, the nodes with a mapping relationship can be connected, so that the processing link preset for the corresponding mapping connection line can be retrieved and displayed.

[0130] It is not difficult to understand that the mapping connection line is the connection line between multi-level mapping nodes.

[0131] In some embodiments, it further includes:

[0132] A1. If it is determined that after traversing the multi-level mapping nodes corresponding to the last X-axis coordinate in the positive X-axis direction, and after determining another first dividing line in the positive Y-axis direction.

[0133] It can be understood that when, during the traversal process, after traversing the multi-level mapping nodes corresponding to the last X-axis coordinate in the positive X-axis direction, and after determining a first dividing line in the positive Y-axis direction among the multi-level mapping nodes in the column corresponding to the last X-axis coordinate, and when the nodes corresponding to the image acquisition slots and text acquisition slots have not been determined yet, then subsequently, the remaining un-traversed and uncompared multi-level mapping nodes in the column corresponding to the first X-axis coordinate can be identified again, so as to determine the multi-level mapping nodes corresponding to the attribute information corresponding to the image acquisition slots and text acquisition slots.

[0134] A2. Lock the smallest X-axis coordinate again and traverse the corresponding multi-level mapping nodes starting from the first dividing line until another second dividing line is determined or all multi-level mapping nodes have been traversed and then stop traversing.

[0135] It can be understood that when all the multi-level mapping nodes corresponding to the image acquisition slots and text acquisition slots have not been 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, traverse the corresponding multi-level mapping nodes starting from the first dividing line until the second dividing line is identified or all the multi-level mapping nodes in the corresponding column have been traversed, and then stop traversing the multi-level mapping nodes in this column.

[0136] It should be noted that the positions of the dividing lines in the multi-level mapping nodes corresponding to each column of X-axis coordinates are all preset, and the number of multi-level mapping nodes separated by the first dividing line and the second dividing line is also predetermined.

[0137] A3. After determining the second dividing line, traverse the multiple multi-level mapping nodes of the next X-axis coordinate backward, and then traverse each multi-level mapping node in the positive direction of the Y-axis in turn until another second dividing line is determined or all multi-level mapping nodes are traversed and then stop traversing.

[0138] It can be understood that after the second dividing line is recognized, the position can be horizontally moved to the multi-level mapping nodes corresponding to the next column of the X-axis, and then the traversal of the multi-level mapping nodes is carried out in the positive direction of the Y-axis in turn until the second dividing line in this column is determined or all multi-level mapping nodes are traversed and then stop traversing the nodes in this column, so as to subsequently determine the multi-level mapping nodes corresponding to the attributes of the image acquisition slot and the text acquisition slot among many nodes.

[0139] In some embodiments, the attribute mapping network is generated through the following steps, including:

[0140] B1. Receive the attributes of the fixed assets configured by the server, and the multi-level mapping nodes corresponding to the attributes of the corresponding fixed assets with preset associations.

[0141] It can be understood that the attribute information configured by the server for the fixed assets is received, for example, including images, dates, etc., and the multi-level mapping nodes associated with the corresponding attributes of the fixed assets are preset in advance, so as to generate the attribute mapping network subsequently.

[0142] Among them, the multi-level mapping nodes are nodes associated with the attributes corresponding to the fixed assets and are preset in advance.

[0143] B2. Obtain all associated multi-level mapping nodes to form an association chain, and add corresponding sequence tags according to the order of each node in the association chain. There is at least one multi-level mapping node in the association chain.

[0144] It can be understood that connecting all the associated multi-level mapping nodes forms an association chain. Thus, corresponding sequence tags can be added to each node in turn according to the node level order, for example, in the order from left to right, and there is at least one multi-level mapping node in the association chain.

[0145] Among them, the association chain is a chain formed by connecting the associated multi-level mapping nodes, and the sequence tag is an information tag added to each multi-level mapping node according to the order, such as information tags like 1, 2, 3, etc.

[0146] B3. Statistically generate the corresponding number of X-axis coordinates based on the maximum order value in the order tags, and statistically generate the corresponding number of multiple Y-axis coordinates based on the number of associated chains.

[0147] It can be understood that, in order to determine the maximum setting value of the X-axis coordinates, the maximum order value in the order tags can be statistically obtained. Among them, the maximum order value 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 coordinates set vertically, the number of associated chains can be statistically obtained. Since the corresponding multi-level mapping nodes in each associated chain will only be arranged horizontally and not vertically, therefore, when the number of associated chains is determined, the maximum setting value of the Y-axis coordinates can be obtained.

[0148] Among them, the maximum order value is the maximum value in the order tags arranged by numbering.

[0149] B4. Receive the positions configured by the user for each associated chain to generate the corresponding attribute mapping network.

[0150] It can be understood that receive the placement positions of each associated chain sent by the server, so as to place and arrange the multi-level mapping nodes of the corresponding associated chain to obtain the corresponding attribute mapping network.

[0151] In some embodiments, it further includes:

[0152] C1. Statistically extract the number of first nodes of all multi-level mapping nodes between the first dividing line and the second dividing line. If the number of the first nodes is greater than or equal to the first preset number.

[0153] It can be understood that the number of first nodes is the number of all multi-level mapping nodes between the first dividing line and the second dividing line, and the first preset number is the first number set in advance.

[0154] C2. Then reverse the order of the multi-level mapping nodes with the second hit count, and select the first fixed number of multi-level mapping nodes with the second hit count in the front part and move them above the second dividing line.

[0155] It can be understood that when the number of the first nodes is greater than the first preset number, the multi-level mapping nodes corresponding to the second hit count can be reversed in order. When it is determined that the number of multi-level mapping nodes to be adjusted in position is relatively large, the first fixed number of multi-level mapping nodes in the front part will be selected and moved above 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.

[0156] Among them, the first fixed number is the numerical value set in advance, which can be 20.

[0157] C3, count the number of second nodes of all multi-level mapping nodes extracted to the lower part of the first dividing line. If the number of the second nodes is greater than or equal to the second preset number.

[0158] It can be understood that the number of second nodes is the number of all multi-level mapping nodes in the lower part of the first dividing line, and the second preset number is the number of multi-level mapping nodes located below the first dividing line, which can be set artificially in advance.

[0159] 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.

[0160] C4, then reverse the order of the multi-level mapping nodes with the first hit count, and select the first second fixed number of multi-level mapping nodes with the first hit count and move them between the first dividing line and the second dividing line.

[0161] It can be understood that when the number of second nodes is greater than the second preset number, the multi-level mapping nodes corresponding to the first hit count can be reversed. When it is determined that the number of multi-level mapping nodes to be adjusted is relatively large, the first second fixed number of multi-level mapping nodes located in the front part 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 multi-level mapping nodes.

[0162] Among them, the second fixed number is a preset value, which can be 10.

[0163] It is not difficult to understand that since the multi-level mapping nodes located below the first dividing line are also below the second dividing line, when moving the positions of the multi-level mapping nodes below the first dividing line, it will not exceed the first preset number.

[0164] S3, the server identifies and verifies the data in the data collection template, and generates a corresponding verification link for tax verification of the target fixed assets based on the database and feedbacks it to the user management terminal.

[0165] It can be understood that when the user management terminal fills in the corresponding attribute information in the corresponding data collection template and sends it to the server, the server can identify and verify the data in the data collection template, such as scanning barcodes, QR codes in the data collection template or recognizing text, etc., so as to verify the tax information of the target fixed assets according to the information in the database, generate a verification link and send it to the user management terminal, which is convenient for users to intuitively view the information related to the target fixed assets.

[0166] Among them, the database is a tax information database that interacts with the server, including various types of fixed assets and related information, including but not limited to equipment types, names, dates, etc. The verification link is a node link corresponding to the target fixed asset and generated after tax verification.

[0167] In some embodiments, the specific implementation of step S3 (the server identifies and verifies the data in the data collection template, conducts tax verification on the target fixed asset based on the database, and generates a corresponding verification link and feedbacks it to the user management terminal) includes:

[0168] S31. After the server receives the data collection template filled with slots by the user management terminal, it calls at least one of the character recognition module, barcode recognition module, QR code recognition module, and image recognition module to perform data identification and verification, and obtains the identity label information, verification value information, and verification year information of the corresponding target fixed asset.

[0169] It can be understood that when the data collection template is received, multiple modules can be called to identify and verify the data, so as to determine various relevant information corresponding to the target fixed asset, facilitate subsequent tax verification registration, and improve the processing efficiency of tax information.

[0170] Among them, the character recognition module is a module for recognizing character 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, and the image recognition module is a module for recognizing image information. For example, it can recognize the image information of the target fixed asset. The identity label information is the information of the type label corresponding to the target fixed asset, such as an experimental equipment label, an electronic engineering equipment label information, etc. The verification value information is the value information of the fixed asset determined after verification, and the verification year information is the year information corresponding to the target fixed asset.

[0171] S32. Based on the identity label information, verification value information, and verification year information, conduct tax verification by comparing with the database, and generate tax value information for tax verification. The tax value information is an interval value, and each identity label information, verification value information, and verification year information has a preset tax value information.

[0172] It can be understood that by comparing the database according to the identity label information, verification value information, and verification year information, the tax value information for tax verification is obtained. For example, when the identity of the target fixed asset is a computer, the market value of its brand-new equipment is 9000. Due to differences in computer brands, configurations, etc., the prices are also inconsistent. The verification year is the current time and how many years it has been used. Different years also result in different depreciation of fixed assets. Therefore, multiple types of information can be combined to determine the corresponding tax value information, that is, an interval value.

[0173] Among them, the identity tag information, verification value information, and verification age 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 for a verification age of 1 year is a 1% depreciation, and the tax value information for a verification age of 5 years is a 50% depreciation, etc., so as to determine the tax value information for tax verification based on the identity tag information, verification value information, and verification age information.

[0174] S33. Statistically generate a verification link for all the compared data, identity tag information, verification value information, verification age information, and tax value information in the database.

[0175] It can be understood that the multi - level mapping nodes corresponding to the data, identity tag information, verification value information, verification age information, and tax value information compared with the database are connected to generate a verification link.

[0176] S4. 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 requirements of the verification link, the associated data collection slots in the data collection template are highlighted.

[0177] It can be understood that the user management terminal can fill in the corresponding active tax declaration information according to the generated verification link. When it is determined that the active tax declaration information does not match the information in the verification link, the associated data collection slots 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 there is an abnormality, which is convenient for re - verifying the data and improving the processing efficiency of tax data.

[0178] Among them, the active tax declaration information is the tax data information actively input by the user. For example, it can be an asset data table, or the data information actively filled in by the personnel, including asset name, age, name, etc.

[0179] For example, when the actively input age is different from the verification age information collected in the database, the slot of the age information associated in the data collection template can be highlighted, so that subsequent personnel can quickly view the abnormal data.

[0180] In some embodiments, the specific implementation manner of (the user management terminal fills in the corresponding active tax declaration information with reference to the verification link, and if the active tax declaration information does not meet the requirements of the verification link, the associated data collection slots in the data collection template are highlighted) in step S4 includes:

[0181] S41. If it is determined that the value of the active tax return information is not within the range of the tax value information, the corresponding associated data collection slot is retrieved and the data collection slot is highlighted.

[0182] It can be understood that when it is determined that the value of the active tax return information is not within the range of the tax value information, the corresponding associated data collection slot can be retrieved and highlighted. For example, the color of the corresponding slot frame can be replaced for easy viewing by personnel.

[0183] As Figure 2 shown, the present invention provides a schematic structural diagram of a tax data processing device. The tax data processing device includes:

[0184] A request module for causing the server to generate a corresponding management plugin after obtaining the user's identity tag and send it to the user management terminal.

[0185] A judgment module for causing the user management terminal to interact with the management plugin after determining that there is a target fixed asset, and the management plugin generates a corresponding data collection template based on the attributes of the fixed asset and performs data collection.

[0186] A feedback module for causing the server to identify and verify the data in the data collection template, and generate a corresponding verification link based on the database for tax verification of the target fixed asset and feedback it to the user management terminal.

[0187] A verification module for causing the user management terminal to fill in the corresponding active tax return information with reference to the verification link. If the active tax return information does not meet the requirements of the verification link, the associated data collection slots in the data collection template are highlighted.

[0188] 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 above various embodiments.

[0189] 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 (ASIC). In addition, the ASIC can be located in the user equipment. Of course, the processor and the storage medium can also exist as discrete components in the communication device. The storage medium can be a read-only memory (ROM), a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0190] The present invention also provides a program product, which includes execution instructions stored in a storage medium. At least one processor of the device can read the execution instructions from the storage medium, and the execution of the execution instructions by at least one processor enables the device to implement the methods provided by the above various embodiments.

[0191] In the above embodiments of the terminal or the server, it should be understood that the processor can be a central processing unit (CPU for short), and can also be other general-purpose processors, digital signal processors (DSP for short), application specific integrated circuits (ASIC for short), etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in combination with the present invention can be directly embodied as being executed and completed by a hardware processor, or can be executed and completed by a combination of hardware and software modules in the processor.

[0192] 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 them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for processing tax data, characterized in that, Including: After the server obtains the user's identity tag, it generates a corresponding management plugin and sends it to the user management terminal; After the user management terminal determines that there is a target fixed asset, it interacts with the management plugin. The management plugin generates a corresponding data collection template based on the attributes of the fixed asset and performs data collection, including: Determine the image collection slots and text collection slots in the data collection template, and generate corresponding processing links according to the attributes of each image collection slot and text collection slot. The processing links are used to call processing functions to perform associated processing on the associated image collection slots and text collection slots, including: Obtain the attributes of each image collection slot and text collection slot and input them into the attribute mapping network corresponding to the attributes of the fixed asset; The attribute mapping network includes multi-level mapping nodes in two dimensions with levels from low to high. Based on a pre-trained comparison strategy, the attribute mapping network is divided into a horizontal node comparison sub-strategy and a vertical node comparison sub-strategy; Perform an optimized traversal process on 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 they correspond to the attributes of the image collection slot and the text collection slot, select them; After determining that all image collection slots and text collection 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; The server identifies and validates the data in the data collection template, performs tax verification on the target fixed asset based on the database, and generates a corresponding verification link and feedbacks it to the user management terminal; The user management terminal fills in the corresponding active tax return information with reference to the verification link. If the active tax return information does not meet the requirements of the verification link, highlight the associated data collection slots in the data collection template.

2. The tax data processing method according to claim 1, characterized in that The server generates a corresponding management plugin and sends it to the user management terminal after obtaining the user's identity tag, including: The user management terminal sends a fixed asset tax management request to the server, and the server obtains the user's identity tag, and the identity tag at least includes a small-scale tag and a general taxpayer tag; Determine the corresponding management plugin based on the small-scale tag or the general taxpayer tag and send it to the user management terminal.

3. The tax data processing method according to claim 1, characterized in that, The data collection template includes multiple data collection slots; After the user management terminal determines that there is a target fixed asset, it interacts with the management plugin. The management plugin generates a corresponding data collection template based on the attributes of the fixed asset and performs data collection, including: After the user management terminal determines that there is a target fixed asset, it interacts with the management plugin, selects the interaction column corresponding to the target fixed asset, and obtains the attributes of the corresponding fixed asset; Generate a data collection template corresponding to the attributes of the fixed asset. Each fixed asset attribute has a preset data collection template.

4. The tax data processing method according to claim 1, characterized in that Performing an optimized traversal process on 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 they correspond to the attributes of the image acquisition slot and the text acquisition slot, it includes: The two-dimensional multi-level mapping nodes are in the first quadrant of the coordinate axis. The levels of the multi-level mapping nodes increase in sequence along the positive directions of the X-axis and the Y-axis; First, traverse and lock multiple multi-level mapping nodes with the smallest X-axis coordinate, and sequentially traverse each multi-level mapping node in the positive direction of the Y-axis until the first dividing line is determined; After determining the first dividing line, traverse multiple multi-level mapping nodes with the next X-axis coordinate backward, and again sequentially traverse each multi-level mapping node in the positive direction of the Y-axis until another first dividing line is determined; Repeat the above steps until all multi-level mapping nodes corresponding to the image acquisition slots and the text acquisition slots are determined, and optimize the dividing lines in the vertical node comparison sub-strategy.

5. The tax data processing method according to claim 4, characterized in that It also includes: If it is determined that after traversing all the multi-level mapping nodes corresponding to the last X-axis coordinate in the positive direction of the X-axis and determining another first dividing line in the positive direction of the Y-axis; Lock the smallest X-axis coordinate again and start traversing the corresponding multi-level mapping nodes from the first dividing line until another second dividing line is determined or stop traversing after traversing all the multi-level mapping nodes; After determining the second dividing line, traverse multiple multi-level mapping nodes with the next X-axis coordinate backward, and again sequentially traverse each multi-level mapping node in the positive direction of the Y-axis until another second dividing line is determined or stop traversing after traversing all the multi-level mapping nodes.

6. The tax data processing method according to claim 4, wherein Generating an attribute mapping network 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; Obtaining all associated multi-level mapping nodes to form an association chain, and adding corresponding sequence tags according to the order of each node in the association chain. There is at least one multi-level mapping node in the association chain; Counting the maximum value in the sequence tags to generate the corresponding number of X-axis coordinates, and counting the number of association chains to generate the corresponding number of multiple Y-axis coordinates; Receiving the positions configured by the user for each association chain to generate the corresponding attribute mapping network.

7. The tax data processing method according to claim 6, wherein The repeating the above steps until all multi-level mapping nodes corresponding to the image acquisition slots and the text acquisition slots are determined, and optimizing the dividing lines in the vertical node comparison sub-strategy, includes: After a preset time interval is determined, obtaining the traversal hit times of each multi-level mapping node within the first dividing line of each X-axis coordinate to obtain the first hit times, the traversal hit times of each multi-level mapping node between the first dividing line and the second dividing line to obtain the second hit times, and the traversal hit times of each multi-level mapping node above the second dividing line to obtain the third hit times; Extract the minimum second hit count, compare the third hit count of all multi-level mapping nodes with the minimum second hit count, extract the multi-level mapping nodes with a third hit count 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 above the second dividing line; Extract the minimum first hit count, compare the second hit count of all multi-level mapping nodes with the minimum first hit count, and extract the multi-level mapping nodes with a second hit count greater than the minimum first hit count below the first dividing line to obtain an attribute mapping network with optimized dividing line positions.

8. The tax data processing method according to claim 7, characterized in that It also includes: Count 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 first nodes is greater than or equal to the first preset number; Then reverse the order of the multi-level mapping nodes with the second hit count, and select the first fixed number of multi-level mapping nodes with the second hit count in the front part and move them above the second dividing line; Count the number of second nodes of all multi-level mapping nodes extracted below the first dividing line. If the number of second nodes is greater than or equal to the second preset number; Then reverse the order of the multi-level mapping nodes with the first hit count, and select the first fixed number of multi-level mapping nodes with the first hit count in the front part and move them between the first dividing line and the second dividing line.

9. The tax data processing method according to claim 1, characterized in that The server identifies and verifies the data in the data collection template, and performs tax verification on the target fixed assets based on the database to generate a corresponding verification link and feedback it to the user management terminal, including: After the server receives the data collection template filled with slot data from the user management terminal, it calls at least one of the character recognition module, barcode recognition module, QR code recognition module, and image recognition module to perform data identification and verification, and obtains the identity label information, verification value information, and verification year information of the corresponding target fixed assets; Perform tax verification by comparing with the database based on the identity label information, verification value information, and verification year information, and generate tax value information for tax verification. The tax value information is an interval value, and each identity label information, verification value information, and verification year information has a preset tax value information; Count all the compared data, identity label information, verification value information, verification year information, and tax value information in the database to generate a verification link.

10. The tax data processing method according to claim 9, characterized in that The user management terminal fills in the corresponding active tax return information with reference to the verification link. If the active tax return information does not meet the requirements of the verification link, the associated data collection slots in the data collection template are highlighted, including: If it is determined that the value of the active tax return information is not within the interval of the tax value information, the corresponding associated data collection slot is retrieved and the data collection slot is highlighted.

11. A tax data processing device corresponding to the tax data processing method described in claim 1, characterized in that, It includes: A request module for causing the server to generate a corresponding management plugin after obtaining the identity label of the user and send it to the user management terminal; A judgment module, which is used to enable the user management terminal to interact 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 conducts data collection; A feedback module, which is used to enable the server to identify and verify the data in the data collection template, and generate a corresponding verification link for tax verification of the target fixed asset based on the database and feedback it to the user management terminal; A verification module, which is used to enable the user management terminal to fill in the corresponding active tax filing information with reference to the verification link. If the active tax filing information does not meet the requirements of the verification link, the associated data collection slots in the data collection template are highlighted.

12. An electronic device, characterized in that, Including: A memory, a processor, and a computer program, where 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 10.

13. Storage medium, characterized in that, 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 method according to any one of claims 1 to 10.

Images