Tax Platform Cockpit Data Visualization Method, Device and Storage Medium

Abstract

The present invention provides a method, device and storage medium for visualizing tax platform cockpit data, which relates to data processing technology. It interacts with the configuration end to receive configured multi-level tax-paying entities, and constructs a corresponding first tax structure tree based on the structural level relationship of the tax-paying entities; obtains the financial data corresponding to each tax-paying entity, and constructs a second tax structure tree according to the category level relationship in the financial data; according to the tax-paying entity corresponding to each second tax structure tree, nests the second tax structure tree into the first tax structure tree to obtain a visualized structure tree, and generates a corresponding visualized key based on the level and connection relationship of each tax-paying entity in the first tax structure tree; after the cockpit of the tax-paying entity receives the visualized structure tree and the visualized key, it merges and renders them with the tax map in the cockpit to obtain a visualized tax structure interface, effectively organizing and analyzing tax data and realizing comprehensive data visualization.

Description

Technical Field

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

[0002] With the continuous increase in the number of various taxpaying entities, the volume of tax data has shown an explosive growth. For taxpaying entities at different levels, tax management needs to build a clear structural relationship to quickly grasp the basic information, financial status, and their mutual relevance of taxpaying entities. This not only helps the tax department manage better but also provides a more transparent tax environment for taxpaying entities.

[0003] Currently, many tax management systems still rely on traditional charts and reports in data visualization and cannot fully display complex tax structures. This leads to a situation where tax personnel face the dilemma of information overload in analysis and decision-making, making it difficult to intuitively understand the relationships and financial status among various taxpaying entities. Existing visualization tools often lack pertinence and are difficult to flexibly adapt to the levels of different taxpaying entities and the diversity of their financial data, resulting in low efficiency in data integration and extraction, which affects the business decisions of the tax department and the experience of taxpayers.

[0004] Therefore, how to effectively organize and analyze tax data to achieve efficient and comprehensive data visualization has become an urgent problem to be solved. Summary of the Invention

[0005] Embodiments of the present invention provide a method, device, and storage medium for visualizing data in a tax platform cockpit, which can effectively organize and analyze tax data to achieve efficient and comprehensive data visualization.

[0006] In a first aspect of embodiments of the present invention, a method for visualizing data in a tax platform cockpit is provided, including:

[0007] Interact with a configuration end to receive configured multi-level taxpaying entities, and construct a corresponding first tax structure tree based on the structural level relationship of taxpaying entities at each level;

[0008] Obtain the financial data corresponding to each taxpaying entity, and construct a corresponding second tax structure tree according to the type level relationship in the financial data;

[0009] According to the taxpaying entity corresponding to each second tax structure tree, nest the second tax structure tree into the first tax structure tree to obtain a visualization structure tree, and generate a corresponding visualization key based on the level and connection relationship of each taxpaying entity in the first tax structure tree;

[0010] After the cockpit of the taxpayer at any level receives the visual structure tree and the visual key, it will merge and render them based on the visual structure tree, the visual key and the tax map in the cockpit to obtain a visual tax structure interface.

[0011] Optionally, in a possible implementation manner of the first aspect, interacting with the configuration end to receive the configured multi-level taxpayers, and constructing a corresponding first tax structure tree based on the structural level relationship of each level of taxpayers, including:

[0012] Interact with the configuration end to receive the configured multi-level taxpayers, and determine the corresponding equity entities based on the equity information of each taxpayer;

[0013] If it is determined that any taxpayer is the equity entity of another taxpayer, then use the corresponding taxpayer as the first taxpayer, use the other taxpayer as the second taxpayer, and use the first taxpayer as the superior structure of the second taxpayer;

[0014] Sort all the multi-level taxpayers in ascending order of the establishment date to obtain a taxpayer sequence, and sequentially extract taxpayers based on the structural level relationship and establish a corresponding first tax structure tree.

[0015] Optionally, in a possible implementation manner of the first aspect, the sorting all the multi-level taxpayers in ascending order of the establishment date to obtain a taxpayer sequence, and sequentially extracting taxpayers based on the structural level relationship and establishing a corresponding first tax structure tree, includes:

[0016] Sequentially extract taxpayers and establish a corresponding first node. If it is determined that the next extracted taxpayer is the second taxpayer corresponding to the first node, then use the first node as the superior node of the second node of the next extracted taxpayer;

[0017] If it is determined that the first node is the second taxpayer of the next extracted taxpayer, then use the second node of the next extracted taxpayer as the superior node of the first node;

[0018] Connect all the first nodes and second nodes with superior-subordinate relationships to obtain a node connection structure. If the node connection structure meets the verification requirements, then use the node connection structure as the first tax structure tree.

[0019] Optionally, in a possible implementation manner of the first aspect, the connecting all the first nodes and second nodes with superior-subordinate relationships to obtain a node connection structure, and if the node connection structure meets the verification requirements, then using the node connection structure as the first tax structure tree, includes:

[0020] Traverse all nodes in the first tax structure tree in sequence as target nodes, and determine all other points directly and indirectly connected to the target nodes as review nodes;

[0021] If it is determined that each target node and the set of all other review nodes correspond to the entities within the taxpayer sequence, then use the said node connection structure as the first tax structure tree;

[0022] If it is determined that each target node and the set of all other review nodes do not correspond to the entities within the taxpayer sequence, then obtain the set of each target node and all other review nodes to get multiple sets to be compared;

[0023] Determine the tree structure to be improved based on the sets to be compared, and perform improvement processing on the tree structure to be improved to generate the corresponding first tax structure tree.

[0024] Optionally, in a possible implementation manner of the first aspect, the determining the tree structure to be improved based on the sets to be compared, and performing improvement processing on the tree structure to be improved to generate the corresponding first tax structure tree includes:

[0025] Compare the nodes within all the sets to be compared in sequence, and eliminate duplicate sets to be compared to obtain independent sets to be improved;

[0026] Obtain the number of nodes within each set to be improved to get the first improvement quantity, sort the sets to be improved in descending order based on the first improvement quantity to obtain an inter-set sequence, and add sorting labels to the sets to be improved within the inter-set sequence in descending order;

[0027] Perform improvement processing on the tree structure to be improved based on the sorting labels and the levels of the nodes within the sets to be improved to generate the corresponding first tax structure tree.

[0028] Optionally, in a possible implementation manner of the first aspect, the performing improvement processing on the tree structure to be improved based on the sorting labels and the levels of the nodes within the sets to be improved to generate the corresponding first tax structure tree includes:

[0029] Obtain the corresponding sub-structure trees based on all the nodes within each set to be improved, and obtain the tax entities of the highest-level nodes in each sub-structure tree;

[0030] Calculate the level similarity between the tax entity of the highest-level node and the tax entity of each other sub-structure tree. If there is a level similarity greater than or equal to the preset value, then use the level of the highest level similarity as the predicted level;

[0031] Based on the prediction levels of tax entities for each sub - structure tree, determine the nodes at the previous level of the prediction level in other sub - structure trees as prediction connection nodes, and connect the nodes at the highest level of the sub - structure tree with the prediction connection nodes of other sub - structure trees through prediction connection lines to obtain the first tax structure tree.

[0032] Optionally, in a possible implementation manner of the first aspect, the obtaining the financial data corresponding to each taxpayer, and constructing the corresponding second tax structure tree according to the category - level relationship in the financial data includes:

[0033] Extract the financial data corresponding to each taxpayer, and the financial information in the financial data at least includes tax category - level information and time category - level information;

[0034] Construct nodes corresponding to each financial information;

[0035] Establish the corresponding level association relationships for all nodes according to the tax category - level information and / or time category - level information in the financial data, and connect all nodes based on the level association relationships to obtain the second tax structure tree.

[0036] Optionally, in a possible implementation manner of the first aspect, the nesting the second tax structure tree into the first tax structure tree according to the taxpayer corresponding to each second tax structure tree to obtain a visual structure tree, and generating the corresponding visual key based on the level and connection relationship of each taxpayer in the first tax structure tree includes:

[0037] Establish corresponding first storage spaces for each node in the first tax structure tree, traverse each second tax structure tree in sequence to determine the corresponding taxpayer and fill it into the corresponding first storage space to obtain the initial visual structure tree;

[0038] Traverse the levels of taxpayers in sequence to extract the corresponding first - level information, determine the nodes in the first tax structure tree corresponding to each taxpayer and with the downward direction as the positive direction, and determine the second - level information of all directly - connected or indirectly - connected other nodes;

[0039] Extract information based on the first - level information of the node, the second - level information, and the second tax structure tree corresponding to the node with the first - level information to generate the visual key corresponding to each node with the first - level information.

[0040] Optionally, in a possible implementation manner of the first aspect, the extracting information based on the first - level information of the node, the second - level information, and the second tax structure tree corresponding to the node with the first - level information to generate the visual key corresponding to each node with the first - level information includes:

[0041] Obtain the first characters randomly assigned to each level in the first tax structure tree, count the first characters of the first-level information, the file values of the second tax structure tree within the nodes of the first-level information, and obtain a first string;

[0042] Count the first characters of each second-level information and the number of nodes of each second-level information to obtain a randomly selected encryption value, and determine the corresponding random encryption character in the randomly selected encryption list based on the randomly selected encryption value. Combine the first character and the random encryption character to obtain a second string;

[0043] Cross-set the first string and the second string in a preset cross form and then perform an encryption algorithm calculation to obtain the visual key corresponding to the node of the first-level information.

[0044] Optionally, in a possible implementation manner of the first aspect, the determining the corresponding random encryption character in the randomly selected encryption list based on the randomly selected encryption value includes:

[0045] The randomly selected encryption list includes a numerical dimension and an encryption character dimension. There are preset encryption characters within the encryption character dimension, and the encryption characters in the randomly selected encryption list are updated at preset time intervals;

[0046] Determine the encryption character corresponding to the value whose numerical dimension is equal to the randomly selected encryption value as the randomly selected encryption character determined this time.

[0047] Optionally, in a possible implementation manner of the first aspect, the performing an encryption algorithm calculation to obtain the visual key corresponding to the node of the first-level information based on cross-setting the first string and the second string in a preset cross form includes:

[0048] Calculate the multiple of the second string compared to the first string;

[0049] If the multiple is greater than 1, use the multiple as the first selection value. Then select the first selection characters with the number of the first selection value in the second string and place them in front of the first character of the first string. Delete the first selection characters from the second string to obtain an updated second string;

[0050] Select the second selection characters with the number of the first selection value in the second string again and place them in front of the second character of the first string, and repeat the above steps until the updated second string is empty.

[0051] Optionally, in a possible implementation manner of the first aspect, the visual key corresponding to the node of the first-level information obtained by performing an encryption algorithm calculation after cross-setting the first string and the second string in a preset cross form includes:

[0052] Calculate the multiple of the second string compared to the first string;

[0053] If the multiple is less than 1, convert it to a fraction, convert the numerator of the fraction to 1, and perform ceiling processing on the denominator to obtain the fictionalized denominator quantity;

[0054] Select 1 first selected character in the second string and place it before the first character of the first string, and delete the first selected character from the second string to obtain an updated second string;

[0055] Select 1 first selected character in the second string again, determine a new inserted character after skipping the fictionalized denominator quantity of characters in the first string, place the newly selected first selected character after the new inserted character, and repeat the above steps until the updated second string is empty.

[0056] In a second aspect of the embodiments of the present invention, there is provided a tax platform cockpit data visualization device, including:

[0057] A configuration module, configured to interact with a configuration end to receive configured multi-level taxpaying entities, and construct a corresponding first tax structure tree based on the structural level relationship of each level of taxpaying entities;

[0058] An acquisition module, configured to acquire the financial data corresponding to each taxpaying entity, and construct a corresponding second tax structure tree according to the type level relationship in the financial data;

[0059] A visualization module, configured to nest the first tax structure tree into the first tax structure tree according to the taxpaying entity corresponding to each second tax structure tree to obtain a visualization structure tree, and generate a corresponding visual key based on the level and connection relationship of each taxpaying entity in the first tax structure tree;

[0060] A rendering module, configured to, after a cockpit of any level of taxpaying entity receives the visualization structure tree and the visual key, merge and render them with the tax map in the cockpit to obtain a visualized tax structure interface.

[0061] In a fourth aspect of the embodiments of the present invention, there is provided a storage medium, in which a computer program is stored, and when the computer program is executed by a processor, it is used to implement the method described in the first aspect and various possible designs of the first aspect of the present invention.

[0062] The beneficial effects of the present invention are as follows:

[0063] 1. The present invention can integrate tax information from different sources by constructing a tax structure tree and a financial data structure tree for multi-level taxpayers, achieving efficient and comprehensive data visualization. The present invention can not only accurately model the structural relationships between taxpayers, but also deeply extract and analyze financial data, and finally form a visual tax structure interface, so as to effectively improve the scientificity and transparency of tax management, provide data support for decision-making, and improve the user experience of taxpayers, fundamentally solving the problem of insufficient data integration and visualization in the prior art.

[0064] 2. The present invention can systematically construct a tax structure tree and intelligently extract financial data to obtain a second tax structure tree for nested association with the first tax structure tree, facilitating the intuitive display of tax data and improving the efficiency of tax data processing. First, the present invention can receive configured multi-level taxpayer information and construct a first tax structure tree based on the equity relationship, realizing a systematic display of the relationships between taxpayers. Among them, by sorting the establishment dates of taxpayers, nodes are established in sequence and the corresponding superior-subordinate relationships are connected, making the entire tax structure clearer, so that tax administrators can quickly understand the hierarchical relationships of each taxpayer, thereby improving the efficiency and accuracy of management. At the same time, the present invention can also obtain the financial data corresponding to each taxpayer and construct a second tax structure tree based on the category-level relationship of the financial data, making the extraction and analysis of financial data more accurate. In the implementation process, the present invention can automatically establish financial data nodes and perform level association according to tax types and time types to form a clear financial data structure. Through intelligent data extraction and association technologies, it can effectively improve the work efficiency of the tax department in financial analysis and provide timely data support for decision-making.

[0065] 3. The present invention can generate a visual structure tree and a key to enhance the security and confidentiality of data. Among them, the present invention can generate a visual structure tree by nesting the second tax structure tree into the first tax structure tree and generate a corresponding visual key based on the level information of the nodes, not only providing an intuitive tax structure view, but also enhancing the security of data through the encryption process of the key. In the implementation process, tax personnel can conveniently access and operate the visual structure tree and obtain a dynamic and interactive tax map. This combined visual display method not only improves the user experience, but also enhances the security and confidentiality of data. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 is a flowchart of a method for visualizing data in a tax platform cockpit provided by the present invention;

[0067] Figure 2Schematic diagram of the structure of a data visualization device for a tax platform cockpit provided by the present invention. Detailed implementation manners

[0068] 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 rather than all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0069] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such used data may be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order different from those illustrated or described herein.

[0070] 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.

[0071] 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 that includes a series of steps or units does not necessarily have to be 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.

[0072] 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 three relationships may exist. For example, A and / or B may 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", "including A, B, C" means that all of A, B, and C are included, "including A, B, or C" means including any one of A, B, and C, and "including A, B, and / or C" means including any one or any two or all three of A, B, and C.

[0073] 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 is that the similarity between A and B is greater than or equal to a preset threshold.

[0074] Depending on the context, as used herein, "if" can be interpreted as "when...", "when...", "in response to determining", or "in response to detecting".

[0075] The technical solution 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 again in some embodiments.

[0076] As Figure 1 shown, the present invention provides a flowchart of a method for visualizing tax platform cockpit data. The method for visualizing tax platform cockpit data includes:

[0077] S1, interacting with the configuration end to receive the configured multi-level tax payers, and constructing a corresponding first tax structure tree based on the structural level relationship of each level of tax payers.

[0078] It should be noted that cockpit data visualization is a data product that integrates and displays key business indicators (KPIs) and other key data. It presents data in a visual way to help users quickly understand and analyze the business situation. Cockpit data visualization is usually presented in the form of a dashboard, including charts, tables, indicators and other information, enabling users to comprehensively understand business performance on one page.

[0079] It can be understood that since the types and quantities of tax data are relatively complex, in order to construct a clear structural relationship for tax data, so as to quickly master the basic information, financial status of tax payers and their mutual relevance, improve the efficiency of personnel in processing tax data, and make tax data management more convenient, it is possible to receive multi-level tax payers input by the configuration end, so as to construct a corresponding first tax structure tree according to the result level relationship of each level of tax payers, which is convenient for subsequent nested association of corresponding data and convenient for processing tax data.

[0080] Among them, the configuration terminal is an information terminal for configuring tax data. For example, it can be the mobile phone or computer of the personnel in the group responsible for tax management. The tax-paying entity is the main unit for tax payment. For example, the head office corresponding to Group A, Branch A1, Branch A2, Branch A3 corresponding to Group A, and then there are multiple levels of tax-paying main units such as Subsidiary A11 and Subsidiary A12. Since within the same group, the headquarters can have corresponding branches in different places, and when the branches develop well, there may be subsidiaries for business distribution. Therefore, there are different levels of tax-paying entities such as headquarters, branches, and subsidiaries. Therefore, a corresponding first tax structure tree can be constructed according to the shareholder management corresponding to each tax-paying entity, so as to subsequently associate and display the financial and tax information corresponding to each tax-paying entity, facilitating the processing of the tax data of the corresponding group.

[0081] It is not difficult to understand that the structural level relationship is the organizational hierarchical structure relationship, that is, the level arrangement relationship of power and decision-making levels within the organization. For example, Subsidiary A11 reports to Branch A1, and Branch A1 reports to Group A, etc. The first tax structure tree is the level structure distribution tree of each company in the corresponding group.

[0082] In some embodiments, the specific implementation manner in step S1 (interacting with the configuration terminal to receive the configured multi-level tax-paying entities, and constructing a corresponding first tax structure tree based on the structural level relationship of each level of tax-paying entity) includes:

[0083] S11, interacting with the configuration terminal to receive the configured multi-level tax-paying entities, and determining the corresponding equity entity based on the equity information of each tax-paying entity.

[0084] It can be understood that multiple tax-paying entities corresponding to different levels sent by the configuration terminal are received, so as to determine the equity entity corresponding to the lower-level tax-paying entity according to the equity information existing among the tax-paying entities.

[0085] Among them, the equity information is the equity distribution relationship corresponding to each branch and subsidiary in the group. For example, Group A has full ownership of the equity of Branch A1 and Branch A2, and Branch A1 has ownership of Subsidiary A11. Therefore, it can be determined that the headquarters of Group A is the corresponding equity entity, that is, it holds the decision-making power of all companies. The equity entity is the entity that holds the unit shares, such as the headquarters of Group A.

[0086] S12, if it is determined that any tax-paying entity is the equity entity of another tax-paying entity, then the corresponding tax-paying entity is taken as the first tax-paying entity, the other tax-paying entity is taken as the second tax-paying entity, and the first tax-paying entity is taken as the superior structure of the second tax-paying entity.

[0087] It can be understood that when a taxpaying entity is selected and it is determined that the taxpaying entity has the power to make decisions, it can be shown that the selected taxpaying entity is the equity entity of other taxpaying entities. Thus, the selected taxpaying entity can be taken as the first taxpaying entity, and the regional taxpaying entity can be taken as the second taxpaying entity. Therefore, the hierarchical structural relationship between the first taxpaying entity and the second taxpaying entity can be determined.

[0088] Among them, the first taxpaying entity is a taxpaying entity with equity decision-making power. For example, when the A1 branch is the equity entity of the A11 subsidiary and the A12 subsidiary, when the selected taxpaying entity is the A1 branch, the A1 branch can be taken as the first taxpaying entity, and the A11 subsidiary and the A12 subsidiary can be taken as the second taxpaying entities. The superior structure is the corresponding entity structure of the higher level. Thus, the first taxpaying entity can be taken as the superior structure of the second taxpaying entity, so as to generate the corresponding first tax structure tree subsequently.

[0089] S13. Sort all multi-level taxpaying entities in ascending order of the establishment date to obtain a taxpaying entity sequence, and sequentially extract taxpaying entities based on the structural level relationship and establish the corresponding first tax structure tree.

[0090] It can be understood that different companies have corresponding establishment times, and the establishment time of a lower-level subsidiary must be later than that of the higher-level decision-making company. However, a subsidiary may be earlier than other companies at the same level of the corresponding parent company. The establishment times corresponding to different levels are disordered. Thus, the establishment date of the taxpaying entity can be obtained to determine the arrangement order of the taxpaying entities according to the establishment date, so as to obtain the taxpaying entity sequence, and then sequentially extract from the taxpaying entity sequence according to the corresponding structural level relationship to construct the first tax structure tree.

[0091] It is not difficult to understand that since different branches are at the same level, the establishment dates among the same level may also have a sequence. However, the first tax structure tree cannot be constructed based on the establishment date. It is necessary to construct the structure tree in combination with the establishment date according to the structural level relationship, so that the hierarchical information of each taxpaying unit corresponding to the group can be intuitively viewed subsequently.

[0092] Among them, the establishment date is the time and date when the taxpaying entity is established, and the taxpaying entity sequence is the information sequence obtained by arranging the taxpaying entities in order.

[0093] In some embodiments, the specific implementation manner in step S13 (sorting all multi-level taxpaying entities in ascending order of the establishment date to obtain a taxpaying entity sequence, and sequentially extracting taxpaying entities based on the structural level relationship and establishing the corresponding first tax structure tree) includes:

[0094] S131. Sequentially extract taxpaying entities and establish corresponding first nodes. If it is determined that the next taxpaying entity to be extracted is the second taxpaying entity corresponding to the first node, then use the first node as the superior node of the second node of the next taxpaying entity to be extracted.

[0095] It can be understood that the first node is the node corresponding to the taxpaying entity currently selected from the sequence of taxpaying entities, and the second node is the node corresponding to the next taxpaying entity to be extracted.

[0096] It is not difficult to understand that if the next taxpaying entity to be extracted is the second taxpaying entity corresponding to the first node, it can be explained that the taxpaying entity corresponding to the currently extracted first node is the superior structure of the next taxpaying entity to be extracted. Thus, the first node can be used as the superior node of the second node of the next taxpaying entity to be extracted.

[0097] Among them, the superior node is the node that is structurally superior to other nodes.

[0098] S132. If it is determined that the first node is the second taxpaying entity of the next taxpaying entity to be extracted, then use the second node of the next taxpaying entity to be extracted as the superior node of the first node.

[0099] It can be understood that when it is determined that the first node is the second taxpaying entity of the next taxpaying entity to be extracted, it can be explained that the next taxpaying entity to be extracted is the first taxpaying entity of the first node, that is, the superior structure of the first node. Furthermore, the next taxpaying entity to be extracted can be used as the superior node of the first node, so as to subsequently connect the nodes according to the structural relationship to obtain the first tax structure tree.

[0100] S133. Connect all the first nodes and second nodes with a superior-subordinate relationship to obtain a node connection structure. If the node connection structure meets the verification requirements, then use the node connection structure as the first tax structure tree.

[0101] It can be understood that the server can connect the first nodes and second nodes with a superior-subordinate relationship, thereby obtaining a node connection structure with a node connection relationship. When it is determined that the obtained node connection structure after connection meets the verification requirements, the corresponding node connection structure can be used as the first tax structure tree.

[0102] Among them, the node connection structure is a connection structure obtained by directly or indirectly connecting multiple different nodes.

[0103] In some embodiments, the specific implementation of step S133 (connecting all the first nodes and second nodes with a superior-subordinate relationship to obtain a node connection structure, and if the node connection structure meets the verification requirements, then using the node connection structure as the first tax structure tree) includes:

[0104] S1331. Traverse all the nodes in the first tax structure tree in sequence as target nodes, and determine all other points directly and indirectly connected to the target nodes as review nodes.

[0105] It should be noted that when the taxpayer entity is input, there may be a name error, resulting in the failure to match the shareholder information during automatic data comparison, so that there is no connection between the nodes in the generated first tax structure tree. Therefore, the corresponding nodes can be reviewed and verified to be modified in time to improve the accuracy of the first tax structure tree.

[0106] Among them, the target node is the selected node in the traversed first tax structure tree, and the review node is all other nodes directly and indirectly connected to the target node.

[0107] It is not difficult to understand that the target nodes and review nodes are determined to verify the information associated with the corresponding nodes subsequently.

[0108] S1332. If it is determined that the set of each target node and all other review nodes corresponds to the entities in the taxpayer entity sequence, then the node connection structure is used as the first tax structure tree.

[0109] It can be understood that when it is determined that the set of each target node and all other review nodes corresponds to the entities in the taxpayer entity sequence, it can be explained that the current target node and other review nodes are all consistent with the taxpayers in the statistically obtained taxpayer entity sequence without omission. Therefore, it shows that the node connection structure is normal, that is, it can be used as the first tax structure tree.

[0110] S1333. If it is determined that the set of each target node and all other review nodes does not correspond to the entities in the taxpayer entity sequence, then obtain the set of each target node and all other review nodes to get multiple sets to be compared.

[0111] It can be understood that when it is determined that the set of each target node and all other review nodes does not correspond to the entities in the taxpayer entity sequence, it can be explained that there is a mismatch between the constructed nodes and the initially statistically obtained taxpayer entity sequence, indicating that the constructed nodes are segmented. Furthermore, the set of each target node and all other review nodes can be obtained to get multiple sets to be compared, so as to perform entity matching subsequently, so as to screen out error information in time for modification in time to obtain the first tax structure tree.

[0112] Among them, the set to be compared is the node information set of the corresponding combination of each target node and the remaining review nodes.

[0113] It is not difficult to understand that since nodes are selected one by one as target nodes, each target node and the remaining review nodes will form a set to be compared, so that multiple sets to be compared can be obtained.

[0114] S1334, determining a tree structure to be improved based on the set to be compared, and improving the tree structure to be improved to generate a corresponding first tax structure tree.

[0115] It can be understood that when there is a set to be compared, it can be said that there are divisions between the nodes and a complete and connected structure tree has not been formed. Therefore, the tree structure to be improved can be determined based on the set to be compared, so that the corresponding tree structure to be improved can be subsequently improved and connected to obtain the first tax structure tree.

[0116] The tree structure to be improved is a structure tree that needs to be improved and connected.

[0117] In some embodiments, the specific implementation of step S1334 (determining the tree structure to be improved based on the set to be compared, and improving the tree structure to be improved to generate a corresponding first tax structure tree) includes:

[0118] S13341, compare all nodes in the set to be compared in turn, remove duplicate sets to be compared and obtain independent sets to be improved.

[0119] It can be understood that each set to be compared has a corresponding node. When the corresponding traversed target nodes are connected to each other, the corresponding sets to be compared are also consistent. For example, when A, B, C, and D are respectively used as target nodes and the nodes are connected to each other, the four sets to be compared are obtained (A, B, C, D). Therefore, the duplicate sets to be compared can be eliminated in order to obtain a separate set to be perfected, so as to facilitate the subsequent perfect connection of the tree structure to be perfected.

[0120] The set to be improved is a set of nodes to be improved and connected to the tree structure to be improved.

[0121] S13342, obtaining the number of nodes in each to-be-perfected set to obtain a first perfection number, sorting the to-be-perfected set in descending order based on the first perfection number to obtain an inter-set sequence, and adding sorting labels to the to-be-perfected sets in the inter-set sequence in descending order.

[0122] It can be understood that the first improvement number is the number of nodes in the set to be improved, the inter-set sequence is the set sequence after sorting the set to be improved in descending order according to the first improvement number, and the sorting label is the label of the corresponding sorting position of the set to be improved.

[0123] For example, when there are 2 sets to be improved, namely (A, B, C, D) and (E, F, G), it indicates that there is no connection line between the 2 trees to be improved to form a complete first tax structure tree. Therefore, these 2 sets to be improved can be sorted in descending order according to the number of nodes to obtain the sequence between sets [(A, B, C, D), (E, F, G)], and sorting labels, such as label 1 and label 2, are added to the sets to be improved so that the trees to be improved can be connected and improved according to the sorting labels subsequently.

[0124] S13343. Based on the sorting labels and the levels of the nodes in the sets to be improved, perform improvement processing on the trees to be improved to generate corresponding first tax structure trees.

[0125] It can be understood that according to the sorting labels and the levels of the nodes in the sets to be improved, the nodes in the tree results to be improved are connected to obtain corresponding first tax structure trees.

[0126] In some embodiments, the specific implementation manner in step S13343 (performing improvement processing on the trees to be improved based on the sorting labels and the levels of the nodes in the sets to be improved to generate corresponding first tax structure trees) includes:

[0127] S133431. Based on all the nodes in each set to be improved, obtain corresponding sub-structure trees, and obtain the tax subjects of the highest-level nodes in each sub-structure tree.

[0128] It can be understood that the sub-structure tree is the structure tree after all the nodes in the set to be improved are connected, and the tax subject is the tax-paying subject corresponding to the highest-level node in each sub-structure tree.

[0129] Through the above implementation manner, the present invention can determine the tax subjects corresponding to each sub-structure tree, so as to subsequently connect and improve the divided sub-structure trees to obtain the first tax structure tree.

[0130] S133432. Calculate the level similarity between the tax subject of the highest-level node and the tax subjects of each other sub-structure tree. If there is a level similarity greater than or equal to the preset value, then use the level of the highest level similarity as the predicted level.

[0131] It can be understood that in order to determine the connection relationship between the unconnected sub-structure trees, thus, the level similarity between the tax subject and the tax subjects of other sub-structure trees can be calculated. When there is a level similarity greater than or equal to the preset value, it indicates that the similarity degree between the corresponding two sub-structure trees is relatively high and there may be a probability of connection. Furthermore, the level of the highest level similarity can be used as the predicted level.

[0132] Among them, the level similarity is the similarity of the node information corresponding to the levels of different sub-structure trees. The preset value is the benchmark value for judging similarity set in advance. The predicted level is the level of the connected nodes set in advance, that is, the level with the highest level similarity.

[0133] For example, when it is determined that the similarity between the tax entity of the highest-level node in tag 1 and the tax entity in tag 2 is higher than the preset value, the level with the highest level similarity can be used as the predicted level.

[0134] It is not difficult to understand that the similarity can be obtained according to the proportion of the same characters and shareholder information in the names of the tax-paying entities corresponding to the nodes. For example, the name similarity between branch A1 and subsidiary A11 is relatively high, and when the shareholder information is also the same, these two nodes are not connected, indicating that there may be omissions during information input. Therefore, the level corresponding to branch A1 can be used as the predicted level.

[0135] S133433, based on the predicted levels of the tax entities of each sub-structure tree, determine the nodes at the level above the predicted level in other sub-structure trees as the predicted connection nodes, and connect the highest-level nodes of the sub-structure tree with the predicted connection nodes of other sub-structure trees through predicted connection lines to obtain the first tax structure tree.

[0136] It can be understood that the predicted connection node is the node at the level above the predicted level in other sub-structure trees. Thus, the highest-level node of the sub-structure tree can be connected with the predicted connection node of other sub-structure trees through the predicted connection line to connect the multiple divided sub-structure trees and obtain the first tax structure tree.

[0137] Among them, the predicted connection line is the line segment connecting the predicted nodes.

[0138] It is worth mentioning that when human beings discover information errors, they can make active modifications and actively determine the predicted connection lines to connect the corresponding nodes to obtain the first tax structure tree.

[0139] S2, obtain the financial data corresponding to each tax-paying entity, and construct the corresponding second tax structure tree according to the category-level relationship in the financial data.

[0140] It should be noted that the financial data corresponding to each tax-paying entity needs to be extracted to generate the corresponding tax reports, and then the second tax structure tree is obtained, which is convenient for subsequent nesting of the second tax structure tree in the first tax structure tree, thereby improving the viewing efficiency of personnel for tax data information, saving tax data viewing time, and improving the processing efficiency of tax data.

[0141] It is understandable that financial data includes a variety of data types. For example, it can be a cash flow statement, a balance sheet, a financial statement. Among them, the financial statement may further include the first quarter, the second quarter, the third quarter, etc. Thus, according to the hierarchical relationship of types in the financial data, a second tax structure tree can be constructed to quickly view the corresponding tax data information subsequently and improve tax management efficiency.

[0142] Among them, the second tax structure tree is the information structure tree corresponding to the financial data, and each taxpayer has a corresponding second tax structure tree.

[0143] In some embodiments, the specific implementation manner of step S2 (obtaining the financial data corresponding to each taxpayer and constructing a corresponding second tax structure tree according to the hierarchical relationship of types in the financial data) includes:

[0144] S21, extracting the financial data corresponding to each taxpayer. The financial information in the financial data at least includes tax type level information and time type level information.

[0145] It is understandable that the financial information is the financial-related data information corresponding to the taxpayer, including tax type level information and time type level information.

[0146] Among them, the tax type level information is the data information corresponding to the tax type level. For example, tax type information, tax payment information, etc. The time type level information is the information of the time level corresponding to the financial data. For example, the financial statements of the first quarter, the financial statements of the second quarter, etc., which are convenient for subsequent personnel to trigger and view.

[0147] S22, constructing nodes corresponding to each financial information.

[0148] It is understandable that after extracting the financial data of each taxpayer, corresponding data nodes can be constructed according to the financial information, so as to subsequently associate and bind the information of the corresponding type levels, which is convenient for personnel to view and analyze the data in a timely manner.

[0149] S23, establishing a corresponding level association relationship for all nodes according to the tax type level information and / or time type level information in the financial data, and connecting all nodes based on the level association relationship to obtain the second tax structure tree.

[0150] It is understandable that after constructing the nodes, a corresponding level association relationship can be established for all nodes according to the tax type level information and / or time type level information in the financial data, so as to connect the nodes according to the level association relationship subsequently, thereby obtaining the second tax structure tree.

[0151] Among them, the level association relationship is the inclusion relationship of levels directly corresponding to data. For example, the tax type information includes various tax category information such as individual income tax.

[0152] S3. According to the taxpaying entity corresponding to each second tax structure tree, nest the second tax structure tree into the first tax structure tree to obtain a visual structure tree, and generate a corresponding visual key based on the level and connection relationship of each taxpaying entity in the first tax structure tree.

[0153] It should be noted that since each second tax structure tree has a corresponding taxpaying entity, in order to facilitate subsequent acquisition of all taxpaying entity information and financial and tax information in the same structure tree, the second tax structure tree can be nested in the first tax structure tree to obtain a visual structure tree, improving the subsequent acquisition efficiency of financial and tax information. Also, when personnel view data, they can trigger the corresponding node for retrieval and display, facilitating intuitive viewing by personnel. At the same time, in order to improve the security of financial information viewing by each company in the group, a corresponding visual key can be generated according to the level and connection relationship of each taxpaying entity in the first tax structure tree. Thus, each taxpaying entity can only view information within the permitted level range, so as to improve the security of information in the state of information integration.

[0154] Among them, the visual structure tree is a structure tree that can perform data visualization, that is, a structure tree that contains all information nodes of the first tax structure tree and the second tax structure tree, and the visual key is an information key for data viewing.

[0155] In some embodiments, the specific implementation manner of step S3 (nesting the second tax structure tree into the first tax structure tree according to the taxpaying entity corresponding to each second tax structure tree to obtain a visual structure tree, and generating a corresponding visual key based on the level and connection relationship of each taxpaying entity in the first tax structure tree) includes:

[0156] S31. Establish a corresponding first storage space for each node in the first tax structure tree, traverse each second tax structure tree in turn to determine the corresponding taxpaying entity and fill it into the corresponding first storage space to obtain an initial visual structure tree.

[0157] It can be understood that in order to facilitate nesting the second tax structure tree into the first tax structure tree and realizing the combination of taxpaying entities and financial data, a corresponding storage space can be constructed for the corresponding nodes in the first tax structure tree, so as to store the second tax structure tree corresponding to the node in the storage space, facilitating direct retrieval and display when viewing financial and tax information subsequently, and improving the data viewing efficiency.

[0158] Among them, the first storage space is the data storage space corresponding to the nodes in the first tax structure tree. Thus, the second tax structure tree can be traversed to fill the second tax structure tree into the matching first storage space to obtain an initial visual structure tree.

[0159] S32. Sequentially traverse the levels of the tax entity to extract the corresponding first-level information, determine the nodes in the first tax structure tree corresponding to each tax entity, and with the downward direction as the positive direction, determine the second-level information of all other directly or indirectly connected nodes.

[0160] It can be understood that the first-level information is the level information of the tax entity. When the superior of the tax entity has one structural node and the inferior has one structural node, the level of the tax entity is 2. Starting from the current tax entity and with the downward direction as the positive direction, determine the second-level information of all other directly or indirectly connected nodes.

[0161] Among them, the second-level information is the level information of the nodes in the positive downward direction of the tax entity. For example, when the first-level information of the target tax entity is 2, the second-level information can be 3. When the first-level information of the target tax entity is 1, the corresponding second-level information is the directly connected 2 and the indirectly connected 3.

[0162] S33. Based on the first-level information, second-level information of the nodes, and the second tax structure tree corresponding to the nodes of the first-level information, perform information extraction to generate a visual key corresponding to each node of the first-level information.

[0163] It can be understood that information extraction is performed through the first-level information, second-level information of the nodes corresponding to the tax entity, and the second tax structure tree corresponding to the nodes of the first-level information, so as to generate a visual key corresponding to each node of the first-level information according to the extracted information, which is convenient for improving the security of tax data when viewing data later.

[0164] In some embodiments, the specific implementation manner in step S33 (performing information extraction based on the first-level information, second-level information of the nodes, and the second tax structure tree corresponding to the nodes of the first-level information to generate a visual key corresponding to each node of the first-level information) includes:

[0165] S331. Obtain the first characters randomly assigned to each level in the first tax structure tree, count the first characters of the first-level information, the file values of the second tax structure tree in the nodes of the first-level information, and obtain a first string.

[0166] It can be understood that the first character is a randomly assigned character for each level in the first tax structure tree. For example, the randomly assigned character corresponding to the 1st level in the first tax structure tree is 12, the randomly assigned character corresponding to the 2nd level is DF, and the randomly assigned character corresponding to the 3rd level is 23. The file value is the storage space value of the financial and tax data file corresponding to the second tax structure tree, which can be, for example, 256KB.

[0167] It is not difficult to understand that the first string is obtained by statistically combining the first character of the first-level information and the file value of the second tax structure tree within the node of the first-level information. For example, when the first character of the first-level information is 12 and the file value is 256KB, the corresponding first string can be obtained as 12256.

[0168] Among them, the first string is the string formed by combining the character information corresponding to the selected node.

[0169] It is not difficult to understand that when determining the visual key corresponding to each level node, if a certain level is selected, the nodes of that corresponding level are used as the nodes of the first level, and all the nodes in its positive direction are the nodes corresponding to the second level.

[0170] S332, count the first character of each second-level information and the number of nodes of each second-level information to obtain a randomly selected encryption value. Based on the randomly selected encryption value, determine the corresponding random encryption character in the randomly selected encryption list, and combine the first character and the random encryption character to obtain the second string.

[0171] It can be understood that since the second-level information is the information of all other directly or indirectly connected nodes, thus, the second-level information may include multiple levels. Furthermore, it is possible to count the first character of each second-level information and the number of nodes of each second-level information in order to obtain a randomly selected encryption value. For example, when the first characters of the second-level information are DF and 23, and the number of nodes corresponding to DF at the 2nd level is 2, and the number of nodes corresponding to 23 at the 3rd level is 1, then the randomly selected encryption value can be obtained as DF2231. Furthermore, it is possible to determine the corresponding random encryption character in the randomly selected encryption list according to the randomly selected encryption value, which is convenient for subsequently combining the first character and the random encryption character to obtain the second string, and is convenient for subsequently obtaining the visual key.

[0172] Among them, the randomly selected encryption value is the value for encrypting information corresponding to the randomly selected level, the randomly selected encryption list is the encryption information list for performing random encryption, which can be randomly generated, and the second string is the string formed by combining the first character and the random encryption character.

[0173] In some embodiments, the specific implementation of step S332 (determining the corresponding random encryption character in the random selection encryption list based on the randomly selected encryption value) includes:

[0174] S3321, the random selection encryption list includes a numerical dimension and an encryption character dimension. There are preset encryption characters within the encryption character dimension, and the encryption characters in the random selection encryption list are updated at preset time intervals.

[0175] It can be understood that the random selection encryption list includes a numerical dimension and an encryption character dimension. Among them, the numerical dimension is the information dimension corresponding to the number of nodes, and the encryption character dimension is the character dimension for generating random encryption characters. Moreover, the random selection encryption list has an update time period, that is, it will be updated after reaching the preset time period. For example, it is updated once an hour.

[0176] Among them, the encryption character is the character for encrypting financial and tax data, which can be preset.

[0177] S3322, determining the encryption character corresponding to the value whose numerical dimension is equal to the randomly selected encryption value as the randomly selected encryption character determined this time.

[0178] It can be understood that taking the encryption character corresponding to the value whose numerical dimension is equal to the randomly selected encryption value as the randomly selected encryption character determined this time, so as to subsequently determine the visualization key corresponding to the information node at this level.

[0179] S333, encrypting the first string and the second string after cross-setting them in a preset cross form to obtain the visualization key corresponding to the node of the first-level information through an encryption algorithm calculation.

[0180] It can be understood that after obtaining the first string and the second string, in order to improve the security of the information, the first string and the second string can be cross-set in a preset cross form and then encrypted algorithm calculation can be performed to obtain the visualization key corresponding to the node of the first-level information.

[0181] Among them, the preset cross form is the form of character crossing set in advance to improve the security of the subsequent obtained visualization key.

[0182] In some embodiments, the specific implementation of step S333 (encrypting the first string and the second string after cross-setting them in a preset cross form to obtain the visualization key corresponding to the node of the first-level information through an encryption algorithm calculation) includes:

[0183] S3331, calculating the multiple of the second string compared to the first string.

[0184] It can be understood that the characters of the second string are compared with those of the first string to calculate how many times the number of characters in the second string is that of the first string. Based on the calculated multiple, it is convenient to determine the crossover form of the first string and the second string subsequently.

[0185] S3332, if the multiple is greater than 1, take the multiple as the first selection value. Then, select the first selection characters with the number of the first selection value in the second string and place them in front of the first character of the first string. Delete the first selection characters from the second string to obtain the updated second string.

[0186] It can be understood that when the calculated multiple is greater than 1, the multiple greater than 1 can be taken as the first selection value, so as to subsequently select the first selection characters with the same number as the first selection value in the second string, and place the selected first selection characters in front of the first character of the first string. At the same time, delete and update the first selection characters inserted in front of the first string in the second string to obtain the updated second string, which is convenient for subsequent continued character crossover display.

[0187] Among them, the first selection characters are the characters selected with the number corresponding to the first selection value in the second string.

[0188] For example, when the first selection value is 2, the first string is 12256, and the second string is 12256DFBBCA, then 12 in the second string can be used as the first selection characters and placed in front of the first character of the first string, and 12 in the second string is deleted to obtain the updated second string 256DFBBCA.

[0189] S3333, again select the second selection characters with the number of the first selection value in the second string and place them in front of the second character of the first string, and repeat the above steps until the updated second string is empty.

[0190] It can be understood that repeat the above implementation steps of selection and placement, that is, again select the second selection characters with the number of the first selection value in the second string and place them in front of the second character of the first string, and repeat the above steps until the updated second string is empty.

[0191] Among them, the second selection characters are the characters selected again in the second string.

[0192] For example, again select the same number of characters as the first selection value and place them in front of the second character of the first string. That is, insert 25 in front of the first string 2, and the new string obtained can be 121252256. Stop selecting characters until the characters of the second string are updated to be empty. For example, until all characters are inserted into the first string, the crossed string obtained is 1212526D2FB5BC6A, which can be used as the visualization key for the corresponding node.

[0193] It is not difficult to understand that when, during the cross-placement process, if all characters in the first string have new characters inserted in front of them and there are still characters in the updated second string, the remaining characters can be placed at the end of the new string to obtain the visualization key for the corresponding node.

[0194] In some other embodiments, the specific implementation manner in step S333 (wherein the visualization key of the node corresponding to the first-level information is obtained by performing an encryption algorithm calculation after cross-setting the first string and the second string in a preset cross form) further includes:

[0195] A1. Calculate the multiple of the second string compared to the first string.

[0196] It can be understood that by calculating the ratio of the characters of the second string to the first string, the multiple of the number of characters of the second string to the first string can be obtained. According to the calculated multiple, it is convenient to subsequently determine the cross form of the first string and the second string.

[0197] A2. If the multiple is less than 1, convert it to a fraction, and after converting the numerator of the fraction to 1, perform ceiling processing on the denominator to obtain the fictionalized denominator quantity.

[0198] It can be understood that when the calculated multiple is less than 1, the calculated decimal can be converted to a fraction, and after converting the numerator of the fraction to 1, perform ceiling on the denominator to obtain the fictionalized denominator quantity.

[0199] Among them, the fictionalized denominator quantity is the denominator quantity after fictionalizing the non-integer denominator to an integer. For example, 0.3 can be converted to the fraction 3 / 10, and the numerator is adjusted to 1, that is, both the numerator and denominator are divided by 3, then 1 / 3.33 can be obtained. Furthermore, the denominator 3.33 can be rounded up to 4, and 1 / 4 can be obtained as the fictionalized denominator quantity to facilitate subsequent determination of the cross-placement position of the characters according to the fictionalized denominator quantity and facilitate subsequent character cross-setting of the string.

[0200] A3. Select one first selected character from the second string and place it before the first character of the first string. Delete the first selected character from the second string to obtain an updated second string.

[0201] It can be understood that since the number of fictionalized denominators is less than 1, thus, one first selected character can be selected from the second string and placed before the first character of the first string, and the first selected character is deleted from the second string to obtain an updated second string.

[0202] A4. Select one first selected character from the second string again. After the characters in the first string are separated by the number of fictionalized denominators, determine the new inserted character. Place the newly selected first selected character after the new inserted character, and repeat the above steps until the updated second string is empty.

[0203] It can be understood that by repeating the above implementation steps of selection and placement, that is, selecting one first selected character from the second string again and placing it after the character separated by the number of fictionalized denominators from the first character, and determining the character separated by the number of fictionalized denominators from the first character in the first string as the new inserted character. Thus, place the newly selected first selected character after the new inserted character, and repeat the above steps until the updated second string is empty, which means that all the characters in the second string are cross - set in the first string to obtain the visual key corresponding to the node.

[0204] S4. After the cockpit of any level of taxpayer receives the visual structure tree and the visual key, a visual tax structure interface is obtained by merging and rendering based on the visual structure tree, the visual key and the tax map in the cockpit.

[0205] It can be understood that when the display board of the cockpit corresponding to any level of taxpayer receives the corresponding visual structure tree and visual key, the visual structure tree, the visual key and the tax map in the cockpit can be merged and rendered to obtain a visual tax structure interface, which is convenient for intuitive viewing by personnel and improves the processing efficiency of tax data by tax personnel.

[0206] Among them, the tax map is the address map corresponding to the location of the taxpayer, and the visual tax structure interface is the visual structure interface corresponding to the tax data.

[0207] As Figure 2 shown, the present invention provides a schematic structural diagram of a tax platform cockpit data visualization device. The tax platform cockpit data visualization device includes:

[0208] A configuration module, configured to interact with a configuration terminal to receive configured multi - level taxpayers, and construct a corresponding first tax structure tree based on the structural level relationship of each level of taxpayer.

[0209] An acquisition module, configured to acquire the financial data corresponding to each tax subject, and construct a corresponding second tax structure tree according to the type-level relationship in the financial data.

[0210] A visualization module, configured to nest the first tax structure tree into the first tax structure tree according to the tax subject corresponding to each second tax structure tree to obtain a visualization structure tree, and generate a corresponding visualization key based on the level and connection relationship of each tax subject in the first tax structure tree.

[0211] A rendering module, configured to, after receiving the visualization structure tree and the visualization key by the cockpit of any level of tax subject, merge and render them with the tax map in the cockpit to obtain a visualized tax structure interface.

[0212] The present invention also provides a storage medium, in which a computer program is stored, and when the computer program is executed by a processor, it is used to implement the methods provided by the above various embodiments.

[0213] Wherein, the storage medium can be a computer storage medium or a communication medium. The communication medium includes any medium facilitating the transmission of a computer program from one place to another. The computer storage medium can be any available medium accessible by a general or special 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). Additionally, the ASIC can be located in a user device. Of course, the processor and the storage medium can also exist as discrete components in a 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.

[0214] 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.

[0215] In the above embodiments of the terminal or the server, it should be understood that the processor may be a central processing unit (CPU for short), or other general-purpose processors, digital signal processors (DSP for short), application specific integrated circuits (ASIC for short), etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the method disclosed in combination with the present invention can be directly embodied as being executed by a hardware processor, or executed by a combination of hardware and software modules in the processor.

[0216] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended 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 described 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 embodiments of the present invention.

Claims

1. A method for visualizing data in a tax platform cockpit, characterized in that, Including: Interact with the configuration end to receive the configured multi-level tax entities, and construct corresponding first tax structure trees based on the structural level relationships of tax entities at each level, including: Sort all multi-level tax entities in descending order according to the establishment date to obtain a tax entity sequence, and sequentially extract tax entities based on the structural level relationships and establish corresponding first tax structure trees, including: Sequentially extract tax entities and establish corresponding first nodes. If it is determined that the next extracted tax entity is the second tax entity corresponding to the first node, then use the first node as the superior node of the second node of the next extracted tax entity; If it is determined that the first node is the second tax entity of the next extracted tax entity, then use the second node of the next extracted tax entity as the superior node of the first node; Connect all first nodes and second nodes with superior-subordinate relationships to obtain a node connection structure. If the node connection structure meets the verification requirements, then use the node connection structure as the first tax structure tree; Obtain the financial data corresponding to each tax entity, and construct a corresponding second tax structure tree according to the category level relationships in the financial data; According to the tax entities corresponding to each second tax structure tree, nest the second tax structure tree into the first tax structure tree to obtain a visual structure tree, and generate corresponding visual keys based on the levels and connection relationships of each tax entity in the first tax structure tree, including: Establish corresponding first storage spaces for each node in the first tax structure tree, sequentially traverse each second tax structure tree to determine the corresponding tax entity and fill it into the corresponding first storage space to obtain an initial visual structure tree; Sequentially traverse the levels of the tax entities to extract corresponding first level information, determine the nodes in the first tax structure tree corresponding to each tax entity and use the downward direction as the positive direction, and determine the second level information of all other directly or indirectly connected nodes; Extract information based on the first level information of the nodes, the second level information, and the second tax structure trees corresponding to the nodes of the first level information, and generate visual keys corresponding to the nodes of each first level information, including: Obtain the first characters randomly assigned to each level in the first tax structure tree, count the first characters of the first level information, the file values of the second tax structure trees in the nodes of the first level information, and obtain a first string; Count the first characters of each second level information and the number of nodes of each second level information to obtain a randomly selected encryption value, and determine the corresponding random encryption character in the randomly selected encryption list based on the randomly selected encryption value. Combine the first character and the random encryption character to obtain a second string, including: The randomly selected encryption list includes a numerical dimension and an encryption character dimension. The encryption character dimension has preset encryption characters, and the encryption characters in the randomly selected encryption list are updated at preset time intervals; Determine the encryption character corresponding to the value with the same numerical dimension as the randomly selected encryption value as the randomly selected encryption character determined this time; The first character string and the second character string are cross-arranged in a preset cross-form, and then an encryption algorithm is used to calculate to obtain a visual key of a node corresponding to the first level information; After receiving the visualization structure tree and visualization key, the cockpit of any level of tax subject will render the visualization structure tree and visualization key together with the tax map in the cockpit to obtain a visualization tax structure interface.

2. The tax platform cockpit data visualization method according to claim 1 is characterized in that: The step of interacting with the configuration end to receive the configured multi-level tax payers and constructing a corresponding first tax structure tree based on the structural level relationship of each level of the tax payers includes: Interact with the configuration end to receive the configured multi-level tax payers, and determine the corresponding equity entity based on the equity information of each tax payer; If it is determined that any tax subject is the equity subject of other tax subjects, the corresponding tax subject shall be regarded as the first tax subject, the other tax subjects shall be regarded as the second tax subject, and the first tax subject shall be regarded as the superior structure of the second tax subject.

3. The tax platform cockpit data visualization method according to claim 1 is characterized in that: The node connection structure is obtained by connecting all first nodes and second nodes having a superior-subordinate relationship. If the node connection structure meets the validation requirements, the node connection structure is used as the first tax structure tree, including: Traversing all nodes in the first tax structure tree in sequence as target nodes, and determining all other points directly and indirectly connected to the target node as review nodes; If it is determined that each target node and the set of all other review nodes correspond to a subject in the tax subject sequence, the node connection structure is used as the first tax structure tree; If it is determined that the set of each target node and all other review nodes does not correspond to the subject in the tax subject sequence, then the set of each target node and all other review nodes is obtained to obtain multiple sets to be compared; A tree structure to be improved is determined based on the set to be compared, and the tree structure to be improved is improved to generate a corresponding first tax structure tree.

4. The tax platform cockpit data visualization method according to claim 3 is characterized in that: The step of determining a tree structure to be improved based on the set to be compared, and improving the tree structure to be improved to generate a corresponding first tax structure tree includes: Compare all nodes in the set to be compared in turn, remove duplicate sets to be compared and obtain independent sets to be improved; Obtaining the number of nodes in each to-be-perfected set to obtain a first perfection number, sorting the to-be-perfected sets in descending order based on the first perfection number to obtain an inter-set sequence, and adding sorting labels to the to-be-perfected sets in the inter-set sequence in descending order; Based on the sorting labels and the levels of the nodes in the set to be improved, the tree structure to be improved is improved to generate a corresponding first tax structure tree.

5. The tax platform cockpit data visualization method according to claim 4 is characterized in that: The method for perfecting the to-be-perfected tree structure based on the sorting tags and the levels of the nodes in the to-be-perfected set to generate a corresponding first tax structure tree includes: Obtaining a corresponding sub-structure tree based on all the nodes in each to-be-perfected set, and obtaining the tax entity of the node with the highest level in each sub-structure tree; Calculating the level similarity between the tax entity of the node with the highest level and each tax entity of other sub-structure trees. If there exists a level similarity greater than or equal to a preset value, then taking the level with the highest level similarity as the predicted level; Based on the predicted levels of the tax entities of each sub-structure tree, determining the node at the previous level of the predicted level in other sub-structure trees as the predicted connection node, and connecting the node with the highest level of the sub-structure tree and the predicted connection nodes of other sub-structure trees through predicted connection lines to obtain the first tax structure tree.

6. The method for visualizing tax platform cockpit data according to claim 2, wherein The method for obtaining the financial data corresponding to each tax entity and constructing a corresponding second tax structure tree according to the type level relationship in the financial data includes: Extracting the financial data corresponding to each tax entity, and the financial information in the financial data at least includes tax type level information and time type level information; Constructing nodes corresponding to each financial information; According to the tax type level information and / or time type level information in the financial data, establishing corresponding level association relationships for all the nodes, and connecting all the nodes based on the level association relationships to obtain the second tax structure tree.

7. The method for visualizing tax platform cockpit data according to claim 1, wherein The method for obtaining the visualization key of the node corresponding to the first level information by performing an encryption algorithm calculation after cross-setting the first string and the second string in a preset cross form includes: Calculating the multiple of the second string compared to the first string; If the multiple is greater than 1, taking the multiple as the first selection value, then selecting the first selection value number of first selection characters in the second string and placing them in front of the first character of the first string, and deleting the first selection characters from the second string to obtain an updated second string; Again selecting the first selection value number of second selection characters in the second string and placing them in front of the second character of the first string, and repeating the above steps until the updated second string is empty.

8. The method for visualizing tax platform cockpit data according to claim 1, wherein The method for obtaining the visualization key of the node corresponding to the first level information by performing an encryption algorithm calculation after cross-setting the first string and the second string in a preset cross form includes: Calculating the multiple of the second string compared to the first string; If the multiple is less than 1, converting it into a fraction, and performing a ceiling operation on the denominator after converting the numerator of the fraction to 1 to obtain the fictive denominator quantity; Selecting 1 first selection character in the second string and placing it in front of the first character of the first string, and deleting the first selection character from the second string to obtain an updated second string; Again, select 1 first selected character within the second string, determine the newly inserted character after spacing out the number of characters equal to the denominator of the simulation within the first string, place the newly selected first selected character after the newly inserted character, and repeat the above steps until the updated second string is empty.

9. A tax platform cockpit data visualization device corresponding to the tax platform cockpit data visualization method according to any one of claims 1-8, characterized in that, Including: A configuration module, configured to interact with a configuration terminal to receive the configured multi-level tax subjects, and construct a corresponding first tax structure tree based on the structural level relationship of each level of tax subjects; An acquisition module, configured to acquire the financial data corresponding to each tax subject, and construct a corresponding second tax structure tree according to the type level relationship in the financial data; A visualization module, configured to nest the first tax structure tree into the first tax structure tree according to the tax subject corresponding to each second tax structure tree to obtain a visualized structure tree, and generate a corresponding visualization key based on the level and connection relationship of each tax subject in the first tax structure tree; A rendering module, configured to, after the cockpit of any level of tax subject receives the visualized structure tree and the visualization key, merge and render them with the tax map in the cockpit to obtain a visualized tax structure interface.

10. 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 8.

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