Tax platform cockpit data visualization method and device and storage medium

Abstract

The invention provides a tax platform cockpit data visualization method and device and a storage medium, and relates to a data processing technology, the method interactively receives configured multi-level tax payment subjects with a configuration end, and constructs a corresponding first tax structure tree based on the structure level relationship of the tax payment subjects; obtaining financial data corresponding to each tax payment subject, and constructing a second tax structure tree according to a category level relationship in the financial data; according to the tax payment main body corresponding to each second tax structure tree, nesting the second tax structure tree into the first tax structure tree to obtain a visual structure tree, and generating a corresponding visual key based on the level and the connection relationship of each tax payment main body in the first tax structure tree; after the cockpit of the tax payment subject receives the visual structure tree and the visual secret key, the visual structure tree, the visual secret key and the tax map in the cockpit are merged and rendered to obtain a visual tax structure interface, tax data are effectively sorted and analyzed, and comprehensive visualization of the data is achieved.

Description

Technical Field

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

[0002] As the number of various taxpayers continues to increase, the amount of tax data has exploded. For taxpayers at different levels, tax management needs to build clear structural relationships in order to quickly grasp the basic information, financial status and mutual correlation of taxpayers. This not only helps the tax department to better manage, but also provides a more transparent tax environment for taxpayers.

[0003] At present, many tax management systems still rely on traditional charts and reports for data visualization, which cannot fully display complex tax structures. This causes tax personnel to face the dilemma of information overload when analyzing and making decisions, and it is difficult to intuitively understand the relationship and financial status of various taxpayers. Existing visualization tools often lack specificity and are difficult to flexibly adapt to the levels of different taxpayers and the diversity of their financial data, resulting in inefficient data integration and extraction, which affects the business decisions of the tax department and the taxpayers' experience.

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

[0005] The embodiments of the present invention provide a tax platform cockpit data visualization method, device and storage medium, which can effectively organize and analyze tax data and realize efficient and comprehensive data visualization.

[0006] A first aspect of an embodiment of the present invention provides a tax platform cockpit data visualization method, comprising: 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; Obtain the financial data corresponding to each tax subject, and construct a corresponding second tax structure tree according to the category and level relationship in the financial data; According to the tax subject corresponding to each second tax structure tree, the second tax structure tree is nested into the first tax structure tree to obtain a visualization structure tree, and a corresponding visualization key is generated based on the level and connection relationship of each tax subject in the first tax structure tree; 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.

[0007] Optionally, in a possible implementation of the first aspect, the interactively receiving the configured multi-level tax payers from the configuration end, and constructing a corresponding first tax structure tree based on the structural level relationship of the tax payers at each level, 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 payer is the equity holder of other tax payers, the corresponding tax payer shall be regarded as the first tax payer, the other tax payers shall be regarded as the second tax payer, and the first tax payer shall be regarded as the superior structure of the second tax payer; All multi-level tax paying entities are sorted from earliest to latest according to their establishment date to obtain a tax paying entity sequence. Tax paying entities are extracted in sequence based on the structural level relationship and a corresponding first tax structure tree is established.

[0008] Optionally, in a possible implementation of the first aspect, all multi-level tax payers are sorted from earliest to latest according to the establishment date to obtain a tax payer sequence, and the tax payers are sequentially extracted based on the structural level relationship and a corresponding first tax structure tree is established, including: Extracting tax subjects in sequence and establishing corresponding first nodes. If it is determined that the next tax subject extracted is the second tax subject corresponding to the first node, the first node is used as the parent node of the second node of the next tax subject extracted. If it is determined that the first node is the second tax subject of the next tax subject to be extracted, the second node of the next tax subject to be extracted is used as the parent node of the first node; All first nodes and second nodes having a superior-subordinate relationship are connected to obtain a node connection structure. If the node connection structure meets the verification requirements, the node connection structure is used as the first tax structure tree.

[0009] Optionally, in a possible implementation of the first aspect, all first nodes and second nodes having a superior-subordinate relationship are connected to obtain a node connection structure, and if the node connection structure meets the verification 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.

[0010] Optionally, in a possible implementation manner of the first aspect, 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: 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.

[0011] Optionally, in a possible implementation of the first aspect, the generating a corresponding first tax structure tree by perfecting the tree structure to be perfected based on the sorting labels and the levels of the nodes in the set to be perfected includes: Based on all nodes in each set to be completed, a corresponding substructure tree is obtained, and the tax subject of the highest-level node in each substructure tree is obtained; Calculate the level similarity between the tax subject of the highest level node and each tax subject of other substructure trees. If there is a level similarity greater than or equal to the preset value, the level with the highest level similarity is used as the predicted level. Based on the prediction level of the tax subject of each substructure tree, the nodes of the previous level of the prediction level in other substructure trees are determined as prediction connection nodes, and the highest level nodes of the substructure tree are connected with the prediction connection nodes of other substructure trees through prediction connection lines to obtain the first tax structure tree.

[0012] Optionally, in a possible implementation of the first aspect, the acquiring financial data corresponding to each tax subject and constructing a corresponding second tax structure tree according to a category-level relationship in the financial data includes: Obtaining and extracting financial data corresponding to each tax paying entity, wherein the financial information in the financial data at least includes tax category level information and time category level information; Construct nodes corresponding to each piece of financial information; According to the tax category level information and / or time category level information in the financial data, corresponding level association relationships are established for all nodes, and all nodes are connected based on the level association relationships to obtain a second tax structure tree.

[0013] Optionally, in a possible implementation of the first aspect, the step of nesting the second tax structure tree into the first tax structure tree to obtain a visualization structure tree according to the tax subject corresponding to each second tax structure tree, and generating a corresponding visualization key based on the level and connection relationship of each tax subject in the first tax structure tree includes: 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 tax payer and fill the corresponding first storage space to obtain an initial visual structure tree; Traverse the levels of the tax subject in sequence to extract the corresponding first-level information, determine the node in the first tax structure tree corresponding to each tax subject and determine the second-level information of all other directly or indirectly connected nodes with the downward direction as the positive direction; Information is extracted based on the first level information of the node, the second level information, and the second tax structure tree corresponding to the node of the first level information, and a visualization key corresponding to each node of the first level information is generated.

[0014] Optionally, in a possible implementation of the first aspect, 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 of the first level information to generate a visualization key corresponding to each node of the first level information includes: Obtaining the first character randomly assigned to each level in the first tax structure tree, counting the first character of the first level information and the file value of the second tax structure tree in the node of the first level information to obtain a first character string; Counting the first character of each second level information and the number of nodes of each second level information to obtain a randomly selected encrypted value, determining a corresponding random encrypted character in a randomly selected encrypted list based on the randomly selected encrypted value, and combining the first character and the random encrypted character to obtain a second character string; 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 visualization key of a node corresponding to the first level information.

[0015] Optionally, in a possible implementation manner of the first aspect, determining a corresponding random encryption character in a randomly selected encryption list based on the randomly selected encryption value includes: The randomly selected encryption list includes a numerical dimension and an encryption character dimension, the encryption character dimension contains preset encryption characters, and the encryption characters in the randomly selected encryption list are updated at preset time intervals; Determine the encrypted character corresponding to the value whose numerical dimension is equal to the randomly selected encrypted value as the random encrypted character determined this time.

[0016] Optionally, in a possible implementation manner of the first aspect, the step of calculating the visualization key of the node corresponding to the first level information based on performing encryption algorithm calculation after cross-setting the first character string and the second character string in a preset cross-form includes: Calculate the multiple of the second string compared to the first string; If the multiple is greater than 1, the multiple is used as the first selection value, and the first selection characters of the first selection value are selected from the second string and placed before the first character of the first string, and the first selection characters are deleted from the second string to obtain an updated second string; Select the second selected characters of the first selected value quantity in the second string again and place them before the second character of the first string, and repeat the above steps until the updated second string is empty.

[0017] Optionally, in a possible implementation manner of the first aspect, the step of calculating the visualization key of the node corresponding to the first level information based on performing encryption algorithm calculation after cross-setting the first character string and the second character string in a preset cross-form includes: Calculate the multiple of the second string compared to the first string; If the multiple is less than 1, it is converted into a fraction, the numerator of the fraction is converted to 1, and the denominator is rounded up to obtain the number of the simulated denominator; Selecting a first selected character in the second string and placing it before the first character of the first string, and deleting the first selected character from the second string to obtain an updated second string; Select a first selected character in the second string again, determine the new insertion character after the number of characters of the simulated denominator in the first string, place the newly selected first selected character after the new insertion character, and repeat the above steps until the updated second string is empty.

[0018] A second aspect of an embodiment of the present invention provides a tax platform cockpit data visualization device, including: A configuration module, configured to interact with the configuration terminal to receive the configured multi-level tax payers, and to construct a corresponding first tax structure tree based on the structural level relationship of each level of the tax payers; An acquisition module, used to acquire the financial data corresponding to each tax subject, and construct a corresponding second tax structure tree according to the category and level relationship in the financial data; A visualization module, for nesting the first tax structure tree into the first tax structure tree to obtain a visualization structure tree according to the tax subject corresponding to each second tax structure tree, and generating a corresponding visualization key based on the level and connection relationship of each tax subject in the first tax structure tree; The rendering module is used for the cockpit of any level of tax payers to receive the visualization structure tree and visualization key, and then render the visualization structure tree, visualization key and the tax map in the cockpit to obtain a visualization tax structure interface.

[0019] According to a fourth aspect of an embodiment of the present invention, a storage medium is provided, in which a computer program is stored. When the computer program is executed by a processor, it is used to implement the method of the first aspect of the present invention and various possible designs of the first aspect.

[0020] The beneficial effects of the present invention are as follows: 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, and realize efficient and comprehensive data visualization. The present invention can not only accurately model the structural relationship between various 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 taxpayer's user experience, fundamentally solving the problem of insufficient data integration and visualization in the prior art.

[0021] 2. The present invention can systematically construct a tax structure tree, and intelligently extract financial data to obtain a second tax structure tree, so as to perform nested association with the first tax structure tree, facilitate intuitive display of tax data, and improve tax data processing efficiency. First, the present invention can receive the configured multi-level tax subject information, construct the first tax structure tree based on the equity relationship, and realize the systematic display of the relationship between the tax subjects. Among them, by sorting the establishment date of the tax subject, sequentially establishing nodes and connecting the corresponding superior and subordinate relationships, the entire tax structure is clearer, so that the tax management personnel can quickly understand the hierarchical relationship of each tax subject, thereby improving the efficiency and accuracy of management. At the same time, the present invention can also obtain the financial data corresponding to each tax subject, and construct the second tax structure tree according to the type and level relationship of the financial data, so that the extraction and analysis of the financial data are more accurate. In the implementation process, the present invention can automatically establish financial data nodes, and perform level association according to the tax type and time type to form a clear financial data structure. Through intelligent data extraction and association technology, it can effectively improve the work efficiency of the tax department in financial analysis and provide timely data support for decision-making.

[0022] 3. The present invention can generate a visual structure tree and a key to enhance the security and confidentiality of data. 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 node, which not only provides an intuitive tax structure view, but also enhances the security of data through key encryption. During the implementation process, tax personnel can easily 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

[0023] Figure 1 A flowchart of a tax platform cockpit data visualization method provided by the present invention; Figure 2 A structural schematic diagram of a tax platform cockpit data visualization device provided by the present invention. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] The terms "first", "second", "third", "fourth", etc. (if any) in the description and claims of the present invention and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in sequences other than those illustrated or described herein.

[0026] It should be understood that in various embodiments of the present invention, the size of the sequence number of each process does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0027] It should be understood that in the present invention, "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products or apparatuses.

[0028] It should be understood that in the present invention, "plurality" refers to two or more than two. "And / or" is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "Contains A, B and C", "Contains A, B, C" means that A, B, and C are all included, "Contains A, B or C" means that one of A, B, and C is included, and "Contains A, B and / or C" means that any one, any two, or any three of A, B, and C are included.

[0029] It should be understood that in the present invention, "B corresponding to A", "B corresponding to A", "A corresponds to B" or "B corresponds to A" means that B is associated with A and B can be determined based on A. Determining B based on A does not mean determining B based only on A, but B can also be determined based on A and / or other information. A and B match when the similarity between A and B is greater than or equal to a preset threshold.

[0030] Depending on the context, "if" as used herein may be interpreted as "when" or "when" or "in response to determining" or "in response to detecting."

[0031] The technical solution of the present invention is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0032] like Figure 1 As shown, the present invention provides a flow chart of a tax platform cockpit data visualization method, and the tax platform cockpit data visualization method includes: 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 the tax payers.

[0033] 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 business conditions. Cockpit data visualization is usually presented in the form of a dashboard, containing charts, tables, indicators and other information, allowing users to fully understand business performance on a single page.

[0034] It is understandable that due to the complexity of the types and quantities of tax data, in order to be able to construct a clear structural relationship for the tax data, so as to quickly grasp the basic information, financial status and mutual correlation of the taxpayer, improve the efficiency of personnel in processing tax data, and make tax data management more convenient, it is possible to receive multi-level taxpayers input by the configuration end, so as to construct the corresponding first tax structure tree according to the result level relationship of the taxpayers at each level, so as to facilitate the subsequent nesting and association of the corresponding data and facilitate the processing of the tax data.

[0035] Among them, the configuration end is an information terminal for tax data configuration, such as the mobile phone or computer of the group's tax management personnel, and the tax subject is the main unit for tax payment, such as the head office corresponding to Group A, the A1 branch, A2 branch, A3 branch, etc. corresponding to Group A, followed by A11 subsidiary, A12 subsidiary and other multi-level tax subject units. Because in the same group, the headquarters can have corresponding branches in different places, and when the branch develops well, there may be subsidiaries with business distribution, thus, there are different levels of tax subjects such as headquarters, branches, and subsidiaries. Therefore, the corresponding first tax structure tree can be constructed according to the shareholder management corresponding to each tax subject, so that the financial and tax information of the corresponding tax subjects can be associated and displayed later, which is convenient for processing the tax data of the corresponding group.

[0036] It is not difficult to understand that the structural level relationship is the organizational hierarchy relationship, that is, the level arrangement relationship of power and decision-making levels within the organization. For example, A11 subsidiary reports to A1 branch, A1 branch reports to A group, and so on. The first tax structure tree is the level structure distribution tree of each company in the corresponding group.

[0037] In some embodiments, the specific implementation of step S1 (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: S11, interacting with the configuration end to receive the configured multi-level tax payers, and determining the corresponding equity entity based on the equity information of each tax payer.

[0038] It can be understood that multiple tax paying entities corresponding to different levels sent by the configuration end are received so as to determine the equity entity corresponding to the tax paying entity at a lower level according to the equity information existing between the tax paying entities.

[0039] 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 subject, that is, it holds the decision-making power of all companies. The equity subject is the subject that holds the unit shares, for example, the headquarters of Group A.

[0040] S12: 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.

[0041] It can be understood that when a tax subject is selected and it is determined that the tax subject has the power to make decisions, it can be explained that the selected tax subject is the equity subject of other tax subjects, so that the selected tax subject can be regarded as the first tax subject, and the regional tax subject can be regarded as the second tax subject, thereby determining the hierarchical structural relationship between the first tax subject and the second tax subject.

[0042] Among them, the first tax subject is the tax subject with equity decision-making. For example, when Branch A1 is the equity subject of Subsidiaries A11 and A12, and the selected tax subject is Branch A1, Branch A1 can be used as the first tax subject, and Subsidiaries A11 and A12 can be used as the second tax subject. The superior structure is the subject structure corresponding to the previous level, so that the first tax subject can be used as the superior structure of the second tax subject, so as to generate the corresponding first tax structure tree later.

[0043] S13, sorting all multi-level tax paying entities from earliest to latest according to the establishment date to obtain a tax paying entity sequence, extracting the tax paying entities in sequence based on the structural level relationship and establishing a corresponding first tax structure tree.

[0044] It is understandable that different companies have corresponding establishment times, and the establishment time of the subordinate subsidiaries must be later than that of the superior decision-making company. However, the subsidiary may be established earlier than other companies at the same level of the corresponding parent company. The establishment times corresponding to different levels are disordered. Therefore, the establishment date of the tax subject can be obtained, so as to determine the arrangement order of the tax subject according to the establishment date, and thus obtain the tax subject sequence, so as to extract the tax subject sequence in sequence according to the corresponding structural level relationship, so as to construct the first tax structure tree.

[0045] It is not difficult to understand that since different branches are at the same level, the establishment dates of 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 upper and lower level information of each tax unit corresponding to the group can be intuitively viewed later.

[0046] The establishment date is the date when the tax subject is established, and the tax subject sequence is the information sequence obtained by arranging the tax subjects in sequence.

[0047] In some embodiments, the specific implementation of step S13 (the step of sorting all multi-level tax payers from earliest to latest according to the establishment date to obtain a tax payer sequence, extracting the tax payers in sequence based on the structural level relationship and establishing the corresponding first tax structure tree) includes: S131, extract the tax subject in sequence and establish the corresponding first node. If it is determined that the next tax subject extracted is the second tax subject corresponding to the first node, the first node is used as the parent node of the second node of the next tax subject extracted.

[0048] It can be understood that the first node is the node corresponding to the tax subject currently extracted and selected from the tax subject sequence, and the second node is the node corresponding to the next tax subject extracted.

[0049] It is not difficult to understand that when the next tax subject extracted is the second tax subject corresponding to the first node, it can be said that the tax subject corresponding to the currently extracted first node is the parent structure of the next tax subject extracted, and thus, the first node can be used as the parent node of the second node of the next tax subject extracted.

[0050] The upper-level node is a node that is structurally located above other nodes.

[0051] S132: If it is determined that the first node is the second tax subject of the next tax subject to be extracted, the second node of the next tax subject to be extracted is used as the parent node of the first node.

[0052] It can be understood that when the first node is determined to be the second taxpayer of the next extracted taxpayer, it can be explained that the next extracted taxpayer is the first taxpayer of the first node, that is, the parent structure of the first node, and then the next extracted taxpayer can be used as the parent node of the first node, so that the nodes can be connected according to the structural relationship later to obtain the first tax structure tree.

[0053] S133, connecting all first nodes and second nodes having a superior-subordinate relationship to obtain a node connection structure, and if the node connection structure meets the validation requirements, the node connection structure is used as the first tax structure tree.

[0054] It can be understood that the server can connect the first node and the second node having superiors and subordinates to obtain a node connection structure having a node connection relationship. When it is determined that the node connection structure obtained after the connection meets the verification requirements, the corresponding node connection structure can be used as the first tax structure tree.

[0055] The node connection structure is a connection structure obtained by directly or indirectly connecting multiple different nodes.

[0056] In some embodiments, the specific implementation of step S133 (connecting all first nodes and second nodes having a superior-subordinate relationship to obtain a node connection structure, and using the node connection structure as the first tax structure tree if the node connection structure meets the validation requirements) includes: S1331, traverse all nodes in the first tax structure tree in turn as target nodes, and determine all other points directly and indirectly connected to the target node as review nodes.

[0057] It should be noted that since name errors may occur when the taxpayer inputs the information, the shareholder information cannot be matched when the data is automatically compared, resulting in the first tax structure tree being generated with nodes that are not connected to each other. Therefore, the corresponding nodes can be reviewed and verified so that modifications can be made in a timely manner to improve the accuracy of the first tax structure tree.

[0058] The target node is the node selected in the traversed first tax structure tree, and the review node is all other nodes directly and indirectly connected to the target node.

[0059] It is not difficult to understand that the target node and the review node are determined so that the information associated with the corresponding nodes can be subsequently verified.

[0060] S1332: 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.

[0061] It can be understood that when it is determined that each target node and the set of all other review nodes correspond to the subjects in the tax subject sequence, it can be said that the current target node and other review nodes are consistent with the tax subjects in the counted tax subject sequence without omissions, thereby indicating that the node connection structure is normal, that is, it can be used as the first tax structure tree.

[0062] S1333, 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.

[0063] 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 subject in the tax subject sequence, it can be explained that the constructed node does not match the initially counted tax subject sequence, indicating that the constructed node is split. Then, each target node and the set of all other review nodes can be obtained to obtain multiple sets to be compared, so as to facilitate subsequent subject matching, thereby timely filtering out error information so that timely modifications can be made to obtain the first tax structure tree.

[0064] The set to be compared is a set of node information corresponding to each target node and the remaining review nodes.

[0065] 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.

[0066] 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.

[0067] 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.

[0068] The tree structure to be improved is a structure tree that needs to be improved and connected.

[0069] 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: 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.

[0070] 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.

[0071] The set to be improved is a set of nodes to be improved and connected to the tree structure to be improved.

[0072] 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.

[0073] 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.

[0074] For example, when there are two sets to be improved, namely (A, B, C, D) and (E, F, G), it means that there is no connecting line between the two tree structures to be improved to form a complete first tax structure tree. Therefore, the two 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 can be added to the sets to be improved, for example, label 1, label 2, so that the tree structures to be improved can be improved and connected later according to the sorting labels.

[0075] S13343, 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.

[0076] It can be understood that the nodes in the tree result to be improved are connected according to the sorting labels and the levels of the nodes in the set to be improved, so as to obtain the corresponding first tax structure tree.

[0077] In some embodiments, the specific implementation of step S13343 (generating the corresponding first tax structure tree by performing the tree structure improvement processing based on the sorting labels and the levels of the nodes in the set to be improved) includes: S133431, based on all nodes in each set to be completed, a corresponding substructure tree is obtained, and the tax subject of the highest-level node in each substructure tree is obtained.

[0078] It can be understood that the substructure tree is a structure tree after all nodes in the set to be completed are connected, and the tax subject is the tax subject corresponding to the highest level node in each substructure tree.

[0079] Through the above implementation, the present invention can determine the tax subject corresponding to each substructure tree, so as to subsequently connect and improve the divided substructure trees to obtain the first tax structure tree.

[0080] S133432, calculate the level similarity between the tax subject of the highest level node and each tax subject in other substructure trees. If there is a level similarity greater than or equal to a preset value, the level with the highest level similarity is used as the predicted level.

[0081] It can be understood that in order to determine the connection relationship between each unconnected substructure tree, the level similarity between the tax subject and the tax subject of other substructure trees can be calculated. When the level similarity is greater than or equal to the preset value, it means that the degree of similarity between the corresponding two substructure trees is high and there may be a probability of connection. Then, the level with the highest level similarity can be used as the prediction level.

[0082] Among them, the level similarity is the similarity of node information at corresponding levels of different substructure trees, the preset value is a pre-set benchmark value for judging similarity, and the predicted level is the level of pre-connected nodes, that is, the level with the highest level similarity.

[0083] For example, when it is determined that the similarity between the tax subject of the highest level node in label 1 and the tax subject in label 2 is higher than a preset value, the level with the highest level similarity can be used as the prediction level.

[0084] 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 entities corresponding to the nodes. For example, the names of Branch A1 and Subsidiary A11 are highly similar, and when the shareholder information is also the same, the two nodes are not connected, indicating that there may be omissions in the information input. Therefore, the level corresponding to Branch A1 can be used as the prediction level.

[0085] S133433, based on the prediction level of the tax subject of each substructure tree, determine the node of the previous level of the prediction level in other substructure trees as the prediction connection node, connect the highest level node of the substructure tree with the prediction connection nodes of other substructure trees through prediction connection lines, and obtain the first tax structure tree.

[0086] It can be understood that the predicted connection node is the node of the previous level of the prediction level in other substructure trees. Therefore, the highest level node of the substructure tree can be connected to the predicted connection nodes of other substructure trees through prediction connection lines, so as to connect the multiple divided substructure trees to obtain the first tax structure tree.

[0087] The prediction connection line is a line segment connecting the prediction nodes.

[0088] It is worth mentioning that when information errors are discovered manually, they can be actively modified and the predicted connection lines can be actively determined to connect the corresponding nodes to obtain the first tax structure tree.

[0089] S2, obtaining the financial data corresponding to each tax paying entity, and constructing a corresponding second tax structure tree according to the category and level relationship in the financial data.

[0090] It should be noted that it is necessary to extract the financial data corresponding to each taxpayer in order to generate the corresponding tax report, and then obtain the second tax structure tree, so as to facilitate the subsequent nesting of the second tax structure tree in the first tax structure tree, thereby improving the efficiency of personnel viewing tax data information, saving tax data viewing time, and improving tax data processing efficiency.

[0091] It is understandable that financial data contains many types of data, for example, it may be a cash flow statement, a balance sheet, and a financial declaration form, among which the financial declaration form may also include the first quarter, the second quarter, the third quarter, etc., so that a second tax structure tree can be constructed based on the type-level relationship in the financial data, so that the corresponding tax data information can be quickly viewed later, thereby improving tax management efficiency.

[0092] The second tax structure tree is an information structure tree corresponding to the financial data, and each tax paying entity has a corresponding second tax structure tree.

[0093] In some embodiments, the specific implementation of step S2 (obtaining the financial data corresponding to each tax subject and constructing a corresponding second tax structure tree according to the category-level relationship in the financial data) includes: S21, obtaining and extracting financial data corresponding to each tax paying entity, wherein the financial information in the financial data at least includes tax category level information and time category level information.

[0094] It can be understood that financial information refers to the financial-related data information corresponding to the tax payer, including tax category level information and time category level information.

[0095] Among them, the tax type level information is the data information corresponding to the tax type level, such as tax type information, tax fee information, etc., and the time type level information is the time level information corresponding to the financial data, such as the first quarter financial statements, the second quarter financial statements, etc., to facilitate subsequent personnel to trigger and view.

[0096] S22, constructing a node corresponding to each financial information.

[0097] It is understandable that after the financial data of each taxpayer is extracted, the corresponding data nodes can be constructed based on the financial information, so that the information of the corresponding category levels can be associated and bound later, making it easier for personnel to view and analyze the data in a timely manner.

[0098] S23, establishing 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 connecting all nodes based on the level association relationships to obtain a second tax structure tree.

[0099] It is understandable that after the nodes are constructed, corresponding level association relationships can be established for all nodes according to the tax type level information and / or time type level information in the financial data, so that the nodes can be connected according to the level association relationship to obtain a second tax structure tree.

[0100] Among them, the level association relationship is the level inclusion relationship that the data directly corresponds to. For example, the tax type information includes various tax information such as personal income tax.

[0101] S3, according to the tax subject corresponding to each second tax structure tree, the second tax structure tree is nested into the first tax structure tree to obtain a visualization structure tree, and a corresponding visualization key is generated based on the level and connection relationship of each tax subject in the first tax structure tree.

[0102] It should be noted that, since each second tax structure tree has a corresponding taxpayer, in order to facilitate the subsequent acquisition of all taxpayer 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, thereby improving the efficiency of subsequent acquisition of financial and tax information. Moreover, when personnel view data, they can also retrieve and display it by triggering the corresponding node, which is convenient for personnel to view intuitively. At the same time, in order to improve the security of financial information viewing by various companies in the group, a corresponding visual key can be generated according to the level and connection relationship of each taxpayer in the first tax structure tree. Thus, each taxpayer can only view information within the level allowed, so as to improve the security of information under the state of information integration.

[0103] The visualization structure tree is a structure tree that can be used for data visualization, that is, a structure tree that includes all information nodes of the first tax structure tree and the second tax structure tree, and the visualization key is an information key for viewing data.

[0104] In some embodiments, the specific implementation of step S3 (the step of nesting the second tax structure tree into the first tax structure tree to obtain a visualization structure tree according to the tax subject corresponding to each second tax structure tree, and generating a corresponding visualization key based on the level and connection relationship of each tax subject in the first tax structure tree) includes: S31, establishing a corresponding first storage space for each node in the first tax structure tree, traversing each second tax structure tree in turn to determine the corresponding tax payer and fill the corresponding first storage space to obtain an initial visual structure tree.

[0105] It can be understood that in order to facilitate the nesting of the second tax structure tree within the first tax structure tree and realize the combination of tax subjects and financial data, a corresponding storage space can be constructed for the corresponding nodes in the first tax structure tree, so that the second tax structure tree corresponding to the node can be stored in the storage space, so that when the financial and tax information is viewed later, it can be directly retrieved and displayed, thereby improving data viewing efficiency.

[0106] The first storage space is the data storage space corresponding to the node in the first tax structure tree, so that the second tax structure tree can be traversed to fill the second tax structure tree in the matching first storage space to obtain the initial visual structure tree.

[0107] S32, traverse the levels of the tax subject in turn to extract the corresponding first-level information, determine the node in the first tax structure tree corresponding to each tax subject and determine the second-level information of all other directly or indirectly connected nodes with the downward direction as the positive direction.

[0108] It can be understood that the first-level information is the level information of the tax subject. When the tax subject has a structural node at the superior level and a structural node at the subordinate level, the level of the tax subject is 2. Taking the current tax subject as the starting point and downward as the positive direction, the second-level information of other directly or indirectly connected nodes is determined.

[0109] Among them, the second-level information is the level information of the node in the positive downward direction of the tax subject. For example, when the first-level information of the target tax subject is 2, the second-level information can be 3. When the first-level information of the target tax subject is 1, the corresponding second-level information is 2 for direct connection and 3 for indirect connection.

[0110] S33, 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 of the first level information, and generating a visualization key corresponding to each node of the first level information.

[0111] It can be understood that information is extracted through the first-level information of the nodes corresponding to the taxpayer, the second-level information and the second tax structure tree corresponding to the nodes of the first-level information, so as to generate a visualization key for each node corresponding to the first-level information based on the extracted information, so as to improve the security of tax data when viewing the data later.

[0112] In some embodiments, the specific implementation of step S33 (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 of the first level information, and generating a visualization key corresponding to each node of the first level information) includes: S331, obtaining the first character randomly assigned to each level in the first tax structure tree, counting the first character of the first level information and the file value of the second tax structure tree in the node of the first level information to obtain a first character string.

[0113] It can be understood that the first character is the randomly assigned character for each level in the first tax structure tree. For example, the randomly assigned character corresponding to the first level in the first tax structure tree is 12, the randomly assigned character corresponding to the second level is DF, and the randomly assigned character corresponding to the third 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, for example, it can be 256KB.

[0114] It is not difficult to understand that the first character of the first level information and the file value of the second tax structure tree in the node of the first level information are statistically combined to obtain the first string. For example, when the first character of the first level information is 12 and the file value is 256KB, the corresponding first string is 12256.

[0115] The first character string is a character string composed of character information corresponding to the selected nodes.

[0116] It is not difficult to understand that when determining the visualization key corresponding to each level of nodes, the node of the corresponding level is selected as the node of the first level, and all the nodes located in the positive direction are the corresponding nodes of the second level.

[0117] S332, counting 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, determining a corresponding random encryption character in a randomly selected encryption list based on the randomly selected encryption value, and combining the first character and the random encryption character to obtain a second character string.

[0118] It can be understood that since the second-level information is the information of all other directly or indirectly connected nodes, the second-level information may include multiple levels. Furthermore, the first character of each second-level information and the number of nodes of each second-level information can be counted to obtain a randomly selected encryption value. For example, when the first character of the second-level information is DF and 23, and the number of nodes at the second level corresponding to DF is 2, and the number of nodes at the third level corresponding to 23 is 1, the randomly selected encryption value can be DF2231. Furthermore, the corresponding random encryption character can be determined in the randomly selected encryption list according to the randomly selected encryption value, so as to facilitate the subsequent combination of the first character and the random encryption character to obtain the second character string, so as to facilitate the subsequent acquisition of the visual key.

[0119] Among them, the randomly selected encryption value is a value corresponding to the randomly selected level for information encryption, the randomly selected encryption list is an encrypted information list for random encryption, which can be randomly generated, and the second character string is a character string formed by combining the first character and the randomly encrypted character.

[0120] In some embodiments, a specific implementation of step S332 (determining a corresponding random encrypted character in a randomly selected encryption list based on the randomly selected encryption value) includes: S3321, the randomly selected encryption list includes a numerical dimension and an encryption character dimension, the encryption character dimension contains preset encryption characters, and the encryption characters in the randomly selected encryption list are updated at preset time intervals.

[0121] It can be understood that the randomly selected encryption list includes a numerical dimension and an encrypted character dimension, wherein the numerical dimension is the information dimension corresponding to the number of nodes, and the encrypted character dimension is the character dimension for generating random encrypted characters. In addition, the randomly selected encryption list has an update time period, that is, it will be updated after reaching a preset time period, for example, once an hour.

[0122] The encryption characters are characters used to encrypt financial and tax data and may be preset.

[0123] S3322, determine the encryption character corresponding to the value whose numerical dimension is equal to the randomly selected encryption value, as the random encryption character determined this time.

[0124] It can be understood that the encrypted character corresponding to the value whose numerical dimension is equal to the randomly selected encrypted value is used as the random encrypted character determined this time, so as to subsequently determine the visualization key corresponding to the information node at this level.

[0125] S333: The first character string and the second character string are cross-arranged in a preset cross-arrangement form, and then an encryption algorithm is used to calculate to obtain a visualization key of a node corresponding to the first level information.

[0126] It is understandable 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 calculated by an encryption algorithm to obtain a visualization key of the node corresponding to the first level information.

[0127] The preset cross form is a pre-set character cross form, so as to improve the security of the subsequently obtained visual key.

[0128] In some embodiments, the specific implementation of step S333 (the method of calculating the visualization key of the node corresponding to the first level information by performing encryption algorithm calculation after cross-setting the first character string and the second character string in a preset cross-form) includes: S3331, calculating the multiple of the second character string compared to the first character string.

[0129] It is understandable that the ratio of the characters of the second string to the characters of the first string is calculated to obtain how many times the number of characters of the second string is the number of characters of the first string. The calculated multiple is convenient for subsequently determining the intersection form of the first string and the second string.

[0130] S3332, if the multiple is greater than 1, take the multiple as the first selection value, select the first selection value number of first selection characters in the second string and place them before the first character of the first string, delete the first selection characters from the second string to obtain an updated second string.

[0131] It can be understood that when the calculated multiple is greater than 1, the multiple greater than 1 can be used as the first selection value, so that the same number of first selection characters as the first selection value can be selected in the second string subsequently, and the selected first selection characters can be placed before the first character of the first string. At the same time, the first selection characters inserted before the first string are deleted and updated in the second string to obtain an updated second string, which is convenient for the subsequent cross-display of characters.

[0132] The first selected characters are characters corresponding to the first selected value selected from the second character string.

[0133] For example, when the first selection value is 2, the first string is 12256, and the second string is 12256DFBBCA, 12 in the second string can be placed as the first selection character before the first character of the first string, and 12 in the second string can be deleted, and the updated second string is 256DFBBCA.

[0134] S3333, again select the second selected characters of the first selected value quantity in the second string and place them before the second character of the first string, and repeat the above steps until the updated second string is empty.

[0135] It can be understood that the above selection and placement implementation steps are repeated, that is, the second selected characters of the first selected value quantity are selected again in the second string and placed before the second character of the first string, and the above steps are repeated until the updated second string is empty.

[0136] The second selected character is a character selected again from the second character string.

[0137] For example, select the same number of characters as the first selected value again and place them before the second character of the first string, that is, insert 25 in front of the first string 2, and you can get a new string of 121252256. Until the characters of the second string are updated to empty, then stop selecting characters, for example, until all the characters are inserted into the first string, and the crossed string is 1212526D2FB5BC6A, which can be used as the visualization key of the corresponding node.

[0138] It is not difficult to understand that, during the cross placement process, if new characters have been inserted in front of all characters in the first string and there are still characters in the updated second string, the remaining characters can be placed after the new string to obtain the visual key of the corresponding node.

[0139] In some other embodiments, the specific implementation of step S333 (the step of calculating the visualization key of the node corresponding to the first level information by performing encryption algorithm calculation after cross-setting the first character string and the second character string in a preset cross-form) further includes: A1 calculates the multiple of the second string compared to the first string.

[0140] It is understandable that by calculating the ratio of the characters of the second string to the characters of the first string, the second string is obtained as a multiple of the number of characters of the first string. The calculated multiple facilitates the subsequent determination of the crossover form of the first string and the second string.

[0141] A2, if the multiple is less than 1, convert it into a fraction, convert the numerator of the fraction into 1, and then round up the denominator to obtain the number of the simulated denominator.

[0142] It can be understood that when the calculated multiple is less than 1, the calculated decimal can be converted into a fraction, and after the numerator of the fraction is converted to 1, the denominator is rounded up to obtain the simulated denominator number.

[0143] Among them, the number of simulated denominators is the number of denominators after the denominators that are not integers are simulated as integers. For example, 0.3 can be converted into a fraction of 3 / 10, and the numerator is planned to be 1, that is, the numerator and denominator are both divided by 3, then 1 / 3.33 can be obtained, and then the denominator of 3.33 can be rounded up to 4, and 1 / 4 can be obtained as the number of simulated denominators, so that the cross placement position of the characters can be determined according to the number of simulated denominators, which is convenient for the subsequent cross setting of characters in the string.

[0144] A3, selecting a first selected character in the second character string and placing it before the first character of the first character string, and deleting the first selected character from the second character string to obtain an updated second character string.

[0145] It can be understood that, since the number of simulated denominators is less than 1, a first selected character can be selected in the second string and placed before the first character of the first string, and the first selected character can be deleted from the second string to obtain an updated second string.

[0146] A4, again selects a first selected character in the second character string, determines a new insertion character after the number of characters of the simulated denominator in the first character string, places the newly selected first selected character after the new insertion character, and repeats the above steps until the updated second character string is empty.

[0147] It can be understood that the above-mentioned implementation steps of selection and placement are repeated, that is, after selecting a first selected character in the second string and placing it at the number of characters of the simulated denominator of the first character interval, the character of the first character interval of the simulated denominator is determined as the newly inserted character in the first string, and thus, after the newly selected first selected character is placed at the newly inserted character, the above steps are repeated until the updated second string is empty, indicating that all the characters in the second string are cross-set in the first string to obtain the visual key corresponding to the node.

[0148] S4, after receiving the visualization structure tree and visualization key, the cockpit of any level of tax payer will render the visualization structure tree and visualization key together with the tax map in the cockpit to obtain a visualization tax structure interface.

[0149] It can be understood that when the cockpit display panel corresponding to any level of taxpayer receives the corresponding visualization structure tree and visualization key, the visualization structure tree, visualization key and the tax map in the cockpit can be combined and rendered to obtain a visualization tax structure interface, which is convenient for personnel to view intuitively and improves the efficiency of tax personnel in processing tax data.

[0150] Among them, the tax map is the address map corresponding to the taxpayer, and the visual tax structure interface is the visual structure interface corresponding to the tax data.

[0151] like Figure 2 As shown, the present invention provides a structural schematic diagram of a tax platform cockpit data visualization device, and the tax platform cockpit data visualization device includes: The configuration module is used to interact with the configuration end to receive the configured multi-level tax payers, and to construct a corresponding first tax structure tree based on the structural level relationship of each level of the tax payers.

[0152] The acquisition module is used to acquire the financial data corresponding to each tax subject and construct a corresponding second tax structure tree according to the category and level relationship in the financial data.

[0153] The visualization module is used to nest the first tax structure tree into the first tax structure tree to obtain a visualization structure tree according to the tax subject corresponding to each second tax 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.

[0154] The rendering module is used for the cockpit of any level of tax payers to receive the visualization structure tree and visualization key, and then render the visualization structure tree, visualization key and the tax map in the cockpit to obtain a visualization tax structure interface.

[0155] The present invention also provides a storage medium, in which a computer program is stored. When the computer program is executed by a processor, it is used to implement the methods provided by the various embodiments described above.

[0156] Among them, the storage medium can be a computer storage medium or a communication medium. The communication medium includes any medium that facilitates the transmission of a computer program from one place to another. The computer storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer. For example, the storage medium is coupled to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an application-specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). In addition, the ASIC can be located in a user device. Of course, the processor and the storage medium can also exist in a communication device as discrete components. The storage medium can be a read-only memory (ROM), a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0157] The present invention also provides a program product, which includes an execution instruction, which is stored in a storage medium. At least one processor of a device can read the execution instruction from the storage medium, and at least one processor executes the execution instruction so that the device implements the methods provided in the above various embodiments.

[0158] In the above-mentioned terminal or server embodiments, it should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly implemented as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0159] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. The tax platform cockpit data visualization method is characterized by: include: 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; Obtain the financial data corresponding to each tax subject, and construct a corresponding second tax structure tree according to the category and level relationship in the financial data; According to the tax subject corresponding to each second tax structure tree, the second tax structure tree is nested into the first tax structure tree to obtain a visualization structure tree, and a corresponding visualization key is generated based on the level and connection relationship of each tax subject in the first tax structure tree; After receiving the visualization structure tree and visualization key, the cockpit of any level of tax payers 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 payer is the equity holder of other tax payers, the corresponding tax payer shall be regarded as the first tax payer, the other tax payers shall be regarded as the second tax payer, and the first tax payer shall be regarded as the superior structure of the second tax payer; All multi-level tax paying entities are sorted from earliest to latest according to their establishment date to obtain a tax paying entity sequence. Tax paying entities are extracted in sequence based on the structural level relationship and a corresponding first tax structure tree is established.

3. The tax platform cockpit data visualization method according to claim 2 is characterized in that: The step of sorting all multi-level tax payers from earliest to latest date of establishment to obtain a tax payer sequence, extracting tax payers in sequence based on the structural level relationship and establishing a corresponding first tax structure tree includes: Extracting tax subjects in sequence and establishing corresponding first nodes. If it is determined that the next tax subject extracted is the second tax subject corresponding to the first node, the first node is used as the parent node of the second node of the next tax subject extracted. If it is determined that the first node is the second tax subject of the next tax subject to be extracted, the second node of the next tax subject to be extracted is used as the parent node of the first node; All first nodes and second nodes having a superior-subordinate relationship are connected to obtain a node connection structure. If the node connection structure meets the verification requirements, the node connection structure is used as the first tax structure tree.

4. The tax platform cockpit data visualization method according to claim 3 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.

5. The tax platform cockpit data visualization method according to claim 4 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.

6. The tax platform cockpit data visualization method according to claim 5 is characterized in that: The process of generating a corresponding first tax structure tree based on the sorting labels and the levels of the nodes in the set to be improved includes: Based on all nodes in each set to be completed, a corresponding substructure tree is obtained, and the tax subject of the highest-level node in each substructure tree is obtained; Calculate the level similarity between the tax subject of the highest level node and each tax subject of other substructure trees. If there is a level similarity greater than or equal to the preset value, the level with the highest level similarity is used as the predicted level. Based on the prediction level of the tax subject of each substructure tree, the nodes of the previous level of the prediction level in other substructure trees are determined as prediction connection nodes, and the highest level nodes of the substructure tree are connected with the prediction connection nodes of other substructure trees through prediction connection lines to obtain the first tax structure tree.

7. The tax platform cockpit data visualization method according to claim 2 is characterized in that: The step of obtaining the financial data corresponding to each tax subject and constructing a corresponding second tax structure tree according to the category and level relationship in the financial data includes: Obtaining and extracting financial data corresponding to each tax paying entity, wherein the financial information in the financial data at least includes tax category level information and time category level information; Construct nodes corresponding to each piece of financial information; According to the tax category level information and / or time category level information in the financial data, corresponding level association relationships are established for all nodes, and all nodes are connected based on the level association relationships to obtain a second tax structure tree.

8. The tax platform cockpit data visualization method according to claim 2 is characterized in that: The method of nesting the second tax structure tree into the first tax structure tree to obtain a visualization structure tree according to the tax subject corresponding to each second tax structure tree, and generating a corresponding visualization key based on the level and connection relationship of each tax subject in the first tax structure tree includes: 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 tax payer and fill the corresponding first storage space to obtain an initial visual structure tree; Traverse the levels of the tax subject in sequence to extract the corresponding first-level information, determine the node in the first tax structure tree corresponding to each tax subject and determine the second-level information of all other directly or indirectly connected nodes with the downward direction as the positive direction; Information is extracted based on the first level information of the node, the second level information, and the second tax structure tree corresponding to the node of the first level information, and a visualization key corresponding to each node of the first level information is generated.

9. The tax platform cockpit data visualization method according to claim 8 is characterized in that: The information extraction based on the first level information of the node, the second level information, and the second tax structure tree corresponding to the node of the first level information, and the generation of a visualization key corresponding to each node of the first level information includes: Obtaining the first character randomly assigned to each level in the first tax structure tree, counting the first character of the first level information and the file value of the second tax structure tree in the node of the first level information to obtain a first character string; Counting the first character of each second level information and the number of nodes of each second level information to obtain a randomly selected encrypted value, determining a corresponding random encrypted character in a randomly selected encrypted list based on the randomly selected encrypted value, and combining the first character and the random encrypted character to obtain a second character string; 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 visualization key of a node corresponding to the first level information.

10. The tax platform cockpit data visualization method according to claim 9 is characterized in that: The determining a corresponding random encryption character in a randomly selected encryption list based on the randomly selected encryption value comprises: The randomly selected encryption list includes a numerical dimension and an encryption character dimension, the encryption character dimension contains preset encryption characters, and the encryption characters in the randomly selected encryption list are updated at preset time intervals; Determine the encrypted character corresponding to the value whose numerical dimension is equal to the randomly selected encrypted value as the random encrypted character determined this time.

11. The tax platform cockpit data visualization method according to claim 9, characterized in that: The step of performing encryption algorithm calculation after cross-setting the first character string and the second character string in a preset cross-form to obtain a visualization key of a node corresponding to the first level information includes: Calculate the multiple of the second string compared to the first string; If the multiple is greater than 1, the multiple is used as the first selection value, and the first selection characters of the first selection value are selected from the second string and placed before the first character of the first string, and the first selection characters are deleted from the second string to obtain an updated second string; Select the second selected characters of the first selected value quantity in the second string again and place them before the second character of the first string, and repeat the above steps until the updated second string is empty.

12. The tax platform cockpit data visualization method according to claim 9, characterized in that: The method of calculating the visualization key of the node corresponding to the first level information by performing encryption algorithm calculation after cross-setting the first character string and the second character string in a preset cross-form includes: Calculate the multiple of the second string compared to the first string; If the multiple is less than 1, it is converted into a fraction, the numerator of the fraction is converted to 1, and the denominator is rounded up to obtain the number of the simulated denominator; Selecting a first selected character in the second string and placing it before the first character of the first string, and deleting the first selected character from the second string to obtain an updated second string; Select a first selected character in the second string again, determine the new insertion character after the number of characters of the simulated denominator in the first string, place the newly selected first selected character after the new insertion character, and repeat the above steps until the updated second string is empty.

13. Tax platform cockpit data visualization equipment, characterized in that: include: A configuration module, configured to interact with the configuration terminal to receive the configured multi-level tax payers, and to construct a corresponding first tax structure tree based on the structural level relationship of each level of the tax payers; An acquisition module, used to acquire the financial data corresponding to each tax subject, and construct a corresponding second tax structure tree according to the category and level relationship in the financial data; A visualization module, for nesting the first tax structure tree into the first tax structure tree to obtain a visualization structure tree according to the tax subject corresponding to each second tax structure tree, and generating a corresponding visualization key based on the level and connection relationship of each tax subject in the first tax structure tree; The rendering module is used for receiving the visualization structure tree and visualization key in the cockpit of any level of tax payers, and then merging the visualization structure tree, visualization key and the tax map in the cockpit to obtain a visualization tax structure interface.

14. A storage medium, characterized in that The storage medium stores a computer program, 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 12.

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