ANTV / G6-based visual data processing and interaction system

Abstract

The invention discloses a visual data processing and interaction system based on ANTV / G6, belongs to the technical field of data visual processing and interaction, and aims to solve the technical problem of how to realize flexible customized display of data, diversified interaction operation and efficient data management. According to the technical scheme, the system comprises a main system, an Antv / g6 data visualization controller, an interaction controller and a data export module, wherein the main system is used for receiving an operation instruction of a user, completing basic operations of selecting elements and establishing a hierarchy and an import relationship, and transmitting processed data to the Antv / g6 data visualization controller; and the Antv / g6 data visualization controller is connected with the main system and is used for receiving information of the main system, performing operations of node self-definition html, hierarchical self-definition html, recommendation of a topological node relationship and various linear representation relationships, and visually displaying a data relationship.

Description

Technical Field

[0001] The present invention relates to the field of data visualization processing and interactive technology, in particular to a visualization data processing and interactive system based on ANTV / G6. Background Art

[0002] In the era of data explosion, the amount of data generated by various industries is growing exponentially. When enterprises, scientific research institutions, etc. analyze complex data relationships, traditional data display methods such as tables and simple charts are difficult to intuitively present the complex relationships between data. Although there are some visualization tools, they have the following shortcomings:

[0003] ① The display of nodes and levels lacks flexibility and is difficult to meet the customized needs of different business scenarios;

[0004] ② The relationship connection interaction function is single and cannot provide diversified interaction based on different data characteristics;

[0005] ③ When processing large amounts of data, loading and saving efficiency is low, affecting user experience;

[0006] ④ Lack of comprehensive multi-format export function makes it inconvenient to proceed to the next step of analysis.

[0007] Therefore, how to achieve flexible and customized display of data, diversified interactive operations and efficient data management to meet the needs of different users in complex data visualization analysis is a technical problem that needs to be solved urgently. Summary of the invention

[0008] The technical task of the present invention is to provide a visual data processing and interaction system based on ANTV / G6 to solve the problem of how to achieve flexible customized display of data, diversified interactive operations and efficient data management to meet the needs of different users in complex data visualization analysis.

[0009] The technical task of the present invention is achieved in the following way: a visual data processing and interaction system based on ANTV / G6, the system comprising a main system, an Antv / g6 data visualization controller, an interaction controller and a data export module;

[0010] Among them, the main system is used to accept the user's operation instructions, complete the basic operations of selecting elements, establishing hierarchies and importing relationships, and transmit the processed data to the Antv / g6 data visualization controller;

[0011] Antv / g6 data visualization controller is connected to the main system to receive information from the main system, perform node custom HTML, level custom HTML, recommend topological node relationships, and multiple line types to represent relationships, and intuitively display data relationships;

[0012] The interaction controller is connected to the Antv / g6 data visualization controller, which is used to draw the legend of node element types and flexibly control node screening, relationship connection lines (different line types have different interaction algorithms), and distributed loading and saving of a large amount of data, improving the user interaction experience;

[0013] The data export module supports exporting data in multiple formats for further use and sharing of the data.

[0014] Preferably, the Antv / g6 data visualization controller includes:

[0015] The node custom html sub-module is used to customize the display style, content, and interaction behavior of the node by writing html code according to data attributes and user requirements;

[0016] The hierarchical custom html sub-module is used to flexibly customize the display form of the data hierarchy, and the customized content includes the appearance and layout of the hierarchy;

[0017] The recommended topological node relationship sub-module analyzes the input data using algorithms, and based on the internal connections and rules between the data, recommends the optimal topological relationship for the nodes, making the visualization result more clearly and reasonably present the data structure;

[0018] The multiple line type representation relationship sub-module is used to represent different relationship types between data with different line types (such as solid lines, dashed lines, lines with different thicknesses, etc.), helping users more intuitively distinguish and understand data associations.

[0019] More preferably, the specific implementation method of the recommended topological node relationship sub-module is as follows:

[0020] (1) Data input and preprocessing: Receive data input from the main system. The data covers numerous nodes and potential association information between the nodes. Before conducting in-depth analysis using algorithms, preprocess the data. Specifically: Clean the data to remove noise data and outliers to avoid interference factors affecting subsequent analysis results; Structurally process the data to organize node and relationship information into a format that algorithms can recognize and process, such as constructing a node list and a relationship matrix, providing a solid foundation for the operation of the algorithms;

[0021] (2) Application of algorithms and AI: Built-in classic graph algorithms such as the Dijkstra algorithm and the A* algorithm. The Dijkstra algorithm is used to find the shortest path between two nodes in a graph, and the A* heuristic search algorithm is used to combine a heuristic function to predict the future direction when finding a path, so as to more efficiently find the optimal path;

[0022] (3) Analyze the internal relationships and patterns in the data: During the process of applying the algorithm, deeply explore the internal relationships and patterns among the data, and analyze the attribute information of the nodes. The attribute information of the nodes includes the type, weight, and label of the nodes. For example, in asset data, the nodes may represent different assets, and their attributes include type, alarm status, vulnerability status, compromised status, etc. By analyzing the attribute information of the nodes, it is found that there may be closer connections between users with similar interests and hobbies. Therefore, when recommending the topological relationship, the user nodes are connected in a more direct way. At the same time, consider the relationship information between the connection times and connection strength of the nodes. There is a more important business or social relationship between the nodes with frequent connection times, and a higher priority will be given in the topological relationship recommendation.

[0023] (4) Recommend appropriate topological relationships: Based on the comprehensive analysis of the data and the operation results of the algorithm, the topological node relationship sub-module will recommend appropriate topological relationships for the nodes. The presentation forms of topological relationships are diverse, which may be simple linear connections or complex network structures. By recommending appropriate topological relationships, the visualization results can more accurately reflect the true structure of the data, helping users better understand and analyze the data and discover the hidden information and value in it.

[0024] More preferably, the application of the algorithm and AI is to perform the following analysis using AI tools:

[0025] ① Node feature extraction: Extract various features of the nodes from the original data;

[0026] ② Relationship representation: Represent the relationships between the nodes in a suitable form;

[0027] ③ Model training: Train the AI tool with the prepared data;

[0028] ④ Feature learning and pattern recognition: Let the AI tool automatically learn the complex interaction effects between the node features and identify the features that are most critical for determining the node relationships;

[0029] ⑤ Relationship prediction and recommendation: After training, for new data or cases with partial data missing, the AI tool can predict the possible relationships between the nodes, and based on the prediction results, recommend topological relationships for the nodes.

[0030] Preferably, the interaction controller includes:

[0031] The sub-module for drawing an example graph of node element types is used to generate a legend to display the meanings and styles of different types of nodes, facilitating users to quickly identify various nodes in the visualization graph;

[0032] The node filtering sub-module is used to quickly filter out nodes of interest according to specific conditions (such as node attributes, labels, etc.) so as to focus on analyzing specific parts of the data;

[0033] The flexible interactive control sub-module for relationship connections is used to implement interactive operations by adopting different interactive algorithms for different line types. For example, clicking on a connection line displays detailed relationship information, and dragging a connection line changes the relationship display, etc., enhancing the interactivity between the user and the visualization graph;

[0034] The large-scale data distributed loading and saving sub-module is used to efficiently load and distribute and save large amounts of data. Specifically: when dealing with large-scale data, it realizes the efficient loading of data through optimized algorithms to avoid system lag, and at the same time supports the distributed saving of the processed data to ensure data security and accessibility.

[0035] More preferably, in the flexible interactive control sub-module for relationship connections, when the user is in the visualization interface, different connection line types can be selected through a connection line type selector. The connection line types include dotted lines (representing recommended topological relationships), straight lines, arcs, and broken lines (default line type). The connection line type selector is in the form of a drop-down menu and a button group, facilitating quick switching by the user.

[0036] More preferably, the specific implementation method of the flexible interactive control sub-module for relationship connections is as follows:

[0037] (1) When the user selects a dotted line, the default dotted line represents the recommended topological relationship. At this time, the algorithm controller calls relevant algorithms to process the recommended topological relationship data, analyzes the potential connections and optimal paths between data nodes. After the processing is completed, the recommended topological relationship is converted into a real topological relationship and displayed on the visualization interface to help the user intuitively understand the recommended association structure between data;

[0038] (2) After selecting the straight line type, the algorithm controller starts the corresponding interactive algorithm. When the user operates the mouse, the straight line follows the movement of the mouse. At the same time, the user adjusts the new topological relationship through mouse operations, such as changing the positions of the nodes connected by the straight line, and the position and connection state of the straight line are updated in real time to reflect the new topological relationship, facilitating the user to flexibly adjust the data connection according to needs;

[0039] (3) Similar to the straight line, after selecting the arc type, the algorithm controller drives the interactive algorithm. When the mouse is operated, the arc will follow the mouse, and the user is supported to adjust the topological relationship represented by the arc through mouse operations, and the display is dynamically updated to present a new connection state, meeting the user's personalized settings for the arc connection relationship;

[0040] (4) As the default line type, when the broken line is selected, the algorithm controller executes the corresponding algorithm. When the mouse moves, the broken line will follow, and the user can adjust the position of the broken line through mouse operations. The user can also adjust the position of the broken line connected to the corresponding node by changing the position of the node, including the position of the turning point, etc. At the same time, the user can change the shape and connection of the broken line in real time according to the user's operation, which is convenient for the user to construct complex data connection relationships.

[0041] Preferably, the specific working process of the system is as follows:

[0042] S1. The user selects the data elements to be visualized in the main system, sets the hierarchical structure and imports the relationship data;

[0043] S2. The main system transmits the processed data to the Antv / g6 data visualization controller, and the Antv / g6 data visualization controller performs visualization rendering processing on the data to generate a preliminary visualization graph;

[0044] S3. The interaction controller monitors the user's operations in real time, and according to the user's interaction instructions (such as filtering, clicking on the connection line, etc.), calls the corresponding interaction algorithm to dynamically update the visualization graph;

[0045] S4. After the user completes the visualization analysis, the results are exported in a specified format through the data export module, or the data is transmitted to other analysis tools through the reserved interface.

[0046] The visualization data processing and interaction system based on ANTV / G6 of the present invention has the following advantages:

[0047] (1) The present invention realizes flexible customized display of data, diversified interactive operations and efficient data management to meet the needs of different users in complex data visualization analysis;

[0048] (2) The present invention has flexibility: through the custom html function of nodes and levels, the visualization display effect can be highly customized according to different business scenarios and user needs;

[0049] (3) The present invention has interactivity: diversified interactive functions, especially flexible interactive control for different line types, enable users to explore data relationships more deeply;

[0050] (4) The present invention has high efficiency: the distributed loading and saving technology of a large amount of data improves the performance of the system in processing large-scale data and reduces the user's waiting time;

[0051] (5) The present invention has compatibility: it supports export in multiple formats and connection with other analysis tools, enhancing the versatility and expandability of the system. Description of the Drawings

[0052] The present invention will be further described below in conjunction with the accompanying drawings.

[0053] Appendix Figure 1 is a schematic structural diagram of a visualization data processing and interaction system based on ANTV / G6;

[0054] Appendix Figure 2 is a flowchart of the recommended topological node relationship sub-module;

[0055] Appendix Figure 3 is a flowchart of the relationship connection flexible interaction sub-module. Specific Embodiments

[0056] A visualization data processing and interaction system based on ANTV / G6 of the present invention will be described in detail below with reference to the accompanying drawings of the specification and specific embodiments.

[0057] Embodiment:

[0058] As shown in the appendix Figure 1 This embodiment provides a visualization data processing and interaction system based on ANTV / G6, which includes a main system, an Antv / g6 data visualization controller, an interaction controller, and a data export module;

[0059] Among them, the main system is used to receive the operation instructions of the user, complete the basic operations of selecting elements, establishing hierarchies, and importing relationships, and transmit the processed data to the Antv / g6 data visualization controller; among them, completing the task of selecting elements, such as selecting the data items that need to be visualized from a large amount of data; establishing hierarchies, such as determining the department relationships at different levels in the visualization of organizational structure data;

[0060] The Antv / g6 data visualization controller is connected to the main system and is used to receive the main system information and perform operations such as node custom html, hierarchy custom html, recommended topological node relationships, and various line type representation relationships, and intuitively display the data relationships;

[0061] The interaction controller is connected to the Antv / g6 data visualization controller and is used to draw the legend of node element types and node filtering, relationship connection flexible interaction control (different line types and different interaction algorithms), distributed loading and saving of a large amount of data, and improve the user interaction experience;

[0062] The data export module supports exporting data in multiple formats for further use and sharing of the data.

[0063] The Antv / g6 data visualization controller in this embodiment includes:

[0064] The node custom HTML sub-module is used to customize the display style, content, and interaction behavior of nodes by writing HTML code according to data attributes and user requirements. For example, in asset graph visualization, different types of asset nodes can be set to different styles.

[0065] The hierarchical custom HTML sub-module is used to flexibly customize the display form of the data hierarchy. The customized content includes the appearance and layout of the hierarchy. For example, in the visualization of the progress of a security project, the hierarchical display of different stages can be personalized, and the interaction of drilling down and rolling up can be defined.

[0066] The recommended topological node relationship sub-module uses algorithms to analyze the input data. Based on the internal connections and rules between the data, it recommends the optimal topological relationship for the nodes, making the visualization result more clearly and reasonably present the data structure.

[0067] The multi-line type representation relationship sub-module is used to represent different relationship types between data with different line types (such as solid lines, dashed lines, lines with different thicknesses, etc.), helping users more intuitively distinguish and understand data associations.

[0068] As shown Figure 2 in the appendix, the specific implementation method of the recommended topological node relationship sub-module in this embodiment is as follows:

[0069] (1) Data input and preprocessing: Receive the data input from the main system. The data covers numerous nodes and potential association information between the nodes. Before using algorithms for in-depth analysis, preprocess the data. Specifically: Clean the data to remove noise data and outliers to avoid interference factors affecting the subsequent analysis results; Structurally process the data to organize the node and relationship information into a format that the algorithm can recognize and process, such as constructing a node list and a relationship matrix, providing a solid foundation for the operation of the algorithm.

[0070] (2) Application of algorithms and AI: Build-in classic graph algorithms such as Dijkstra algorithm and A* algorithm. The Dijkstra algorithm is used to find the shortest path between two nodes in a graph, and the A* heuristic search algorithm is used to combine a heuristic function to predict the future direction when finding a path, so as to find the optimal path more efficiently.

[0071] (3) Analyze the internal relationships and patterns in the data: During the process of applying the algorithm, deeply explore the internal relationships and patterns among the data, and analyze the attribute information of the nodes. The attribute information of the nodes includes the type, weight, and label of the nodes. For example, in asset data, the nodes may represent different assets, and their attributes include type, alarm status, vulnerability status, compromised status, etc. By analyzing the attribute information of the nodes, it is found that there may be closer connections among users with similar interests. Therefore, when recommending the topological relationship, the user nodes are connected in a more direct way. At the same time, consider the relationship information between the connection times and connection strength of the nodes. There are more important business or social relationships among nodes with frequent connection times, and higher priorities will be given in the topological relationship recommendation.

[0072] (4) Recommend appropriate topological relationships: Based on the comprehensive analysis of the data and the operation results of the algorithm, the topological node relationship sub-module will recommend appropriate topological relationships for the nodes. The presentation forms of topological relationships are diverse, which may be simple linear connections or complex network structures. By recommending appropriate topological relationships, the visualization results can more accurately reflect the real structure of the data, helping users better understand and analyze the data and discover the hidden information and value in it.

[0073] In this embodiment (2), the application of the algorithm and AI is to use the AI tool deepseek for the following analysis:

[0074] ① Node feature extraction: Extract various features of the nodes from the original data.

[0075] ② Relationship representation: Represent the relationships between the nodes in a suitable form.

[0076] ③ Model training: Use the prepared data to train the deepseek model.

[0077] ④ Feature learning and pattern recognition: Let deepseek automatically learn the complex interaction effects between the node features and identify the features that are most critical for determining the node relationships.

[0078] ⑤ Relationship prediction and recommendation: After training, for new data or cases with partial data missing, deepseek can predict the possible relationships between the nodes, and based on the prediction results, recommend topological relationships for the nodes.

[0079] The interaction controller in this embodiment includes:

[0080] The sub-module for drawing an example of the node element type diagram is used to generate a legend to show the meanings and styles of different types of nodes, facilitating users to quickly identify various nodes in the visualization graph.

[0081] Node filtering sub-module, which is used to quickly filter out nodes of interest according to specific conditions (such as node attributes, labels, etc.) so as to focus on analyzing specific parts of the data;

[0082] Flexible interactive control sub-module for relationship connections, which is used to implement interactive operations by using different interactive algorithms for different line types. For example, clicking on a connection line displays detailed relationship information, and dragging a connection line changes the relationship display, etc., enhancing the interactivity between the user and the visualization graph;

[0083] Massive data distributed loading and saving sub-module, which is used to efficiently load and distribute the saving of massive data. Specifically: when dealing with large-scale data, it realizes the efficient loading of data through optimized algorithms to avoid system lag, and at the same time supports the distributed saving of processed data to ensure data security and accessibility.

[0084] As shown in the appendix Figure 3 As shown, in this embodiment, the flexible interactive control sub-module for relationship connections is that in the visualization interface, the user selects different connection line types through a connection line type selector. The connection line types include dotted lines (representing recommended topological relationships), straight lines, arcs, and broken lines (default line type). The connection line type selector is in the form of a drop-down menu and a button group, which is convenient for the user to quickly switch; among them, the specific implementation method of the flexible interactive control sub-module for relationship connections is as follows:

[0085] (1) When the user selects a dotted line, the default dotted line represents the recommended topological relationship. At this time, the algorithm controller calls relevant algorithms to process the recommended topological relationship data, analyzes the potential connections and optimal paths between data nodes. After the processing is completed, the recommended topological relationship is converted into a real topological relationship and displayed on the visualization interface to help the user intuitively understand the recommended association structure between data;

[0086] (2) After selecting the straight line type, the algorithm controller starts the corresponding interactive algorithm. When the user operates the mouse, the straight line follows the mouse movement. At the same time, the user adjusts the new topological relationship through mouse operations, such as changing the positions of the nodes connected by the straight line, and the position and connection state of the straight line are updated in real time to reflect the new topological relationship, facilitating the user to flexibly adjust the data connection according to needs;

[0087] (3) Similar to the straight line, after selecting the arc type, the algorithm controller drives the interactive algorithm. When the mouse is operated, the arc will follow the mouse, and the user is supported to adjust the topological relationship represented by the arc through mouse operations, and the display is dynamically updated to present a new connection state, meeting the user's personalized settings for the arc connection relationship;

[0088] (4) As the default line type, when the polyline is selected, the algorithm controller executes the corresponding algorithm. When the mouse moves, the polyline will follow, and the user can adjust the position of the polyline through mouse operations. The user can also adjust the position of the polyline connected to the corresponding node by changing the position of the node, including the position of the turning point, etc. At the same time, the user can change the shape and connection of the polyline in real time according to the user's operations, which is convenient for the user to construct complex data connection relationships.

[0089] The specific working process of the system is as follows:

[0090] S1. The user selects the data elements to be visualized in the main system, sets the hierarchical structure, and imports the relationship data;

[0091] S2. The main system transmits the processed data to the Antv / g6 data visualization controller, and the Antv / g6 data visualization controller performs visualization rendering processing on the data to generate a preliminary visualization graph;

[0092] S3. The interaction controller monitors the user's operations in real time, and according to the user's interaction instructions (such as filtering, clicking on the connection line, etc.), calls the corresponding interaction algorithm to dynamically update the visualization graph;

[0093] S4. After the user completes the visualization analysis, the result is exported in a specified format through the data export module, or the data is transmitted to other analysis tools through the reserved interface.

[0094] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A visualization data processing and interaction system based on ANTV / G6, characterized in that, The system includes a main system, an Antv / g6 data visualization controller, an interaction controller, and a data export module; Among them, the main system is used to receive the operation instructions of the user, complete the basic operations of selecting elements, establishing hierarchies, and importing relationships, and transmit the processed data to the Antv / g6 data visualization controller; The Antv / g6 data visualization controller is connected to the main system and is used to receive the main system information, perform operations such as node custom html, hierarchy custom html, recommended topological node relationships, and various line type representation relationships, and intuitively display the data relationships; The interaction controller is connected to the Antv / g6 data visualization controller and is used for functions such as drawing node element type legends, node filtering, flexible interactive control of relationship connections, distributed loading and saving of large amounts of data; The data export module supports exporting data in multiple formats for further use and sharing of the data.

2. The visual data processing and interaction system based on ANTV / G6 according to claim 1, wherein The Antv / g6 data visualization controller includes: The node custom html sub-module is used to customize the display style, content, and interaction behavior of the node by writing html code according to the data attributes and user requirements; The hierarchy custom html sub-module is used to flexibly customize the display form of the data hierarchy, and the customized content includes the appearance and layout of the hierarchy; The recommended topological node relationship sub-module uses algorithms to analyze the input data, and based on the internal connections and rules between the data, recommends the optimal topological relationship for the nodes, so that the visualization results can more clearly and reasonably present the data structure; The multiple line type representation relationship sub-module is used to represent different relationship types between data with different line types, helping users to more intuitively distinguish and understand the data associations.

3. The visualization data processing and interaction system based on ANTV / G6 according to claim 2, characterized in that The specific implementation method of the recommended topological node relationship sub-module is as follows: (1) Data input and preprocessing: Receive the data input from the main system. The data covers numerous nodes and potential association information between the nodes. Before performing in-depth analysis using algorithms, preprocess the data. Specifically: Clean the data to remove the noise data and outliers; Structurally process the data to organize the node and relationship information into a format that the algorithm can recognize and process; (2) Application of algorithms and AI: Built-in classic graph algorithms such as Dijkstra algorithm and A* algorithm. The Dijkstra algorithm is used to find the shortest path between two nodes in a graph, and the A* heuristic search algorithm is used to combine a heuristic function to predict the future direction when finding a path, so as to more efficiently find the optimal path; (3) Analyze the internal relationships and patterns in the data: During the application of the algorithm, deeply explore the internal relationships and patterns among the data, and analyze the attribute information of the nodes. The attribute information of the nodes includes the type, weight, and label of the nodes. By analyzing the attribute information of the nodes, it is found that there may be closer connections among users with similar interests and hobbies. Therefore, when recommending the topological relationship, the user nodes are connected in a more direct way. At the same time, consider the relationship information between the connection times and connection strengths of the nodes. There are more important business or social relationships among the nodes with frequent connection times, and higher priorities will be given in the topological relationship recommendation. (4) Recommend appropriate topological relationships: Based on the comprehensive analysis of the data and the operation results of the algorithm, the topological node relationship sub-module for recommendation will recommend appropriate topological relationships for the nodes. By recommending appropriate topological relationships, the visualization results can accurately reflect the true structure of the data, helping users better understand and analyze the data and discover the hidden information and value in it.

4. The visualization data processing and interaction system based on ANTV / G6 according to claim 3, wherein, (2) The application of the algorithm and AI is to use AI tools for the following analysis: ① Node feature extraction: Extract various features of the nodes from the original data. ② Relationship representation: Represent the relationships between the nodes in a suitable form. ③ Model training: Use the prepared data to train the AI tools. ④ Feature learning and pattern recognition: Let the AI tools automatically learn the complex interaction effects among the node features and identify the features that are most critical for determining the node relationships. ⑤ Relationship prediction and recommendation: After training, for new data or cases with partial data missing, the AI tools can predict the possible relationships among the nodes. Based on the prediction results, recommend topological relationships for the nodes.

5. The visualization data processing and interaction system based on ANTV / G6 according to claim 1, characterized in that The interaction controller includes: The sub-module for drawing the example diagram of node element types, which is used to generate a legend to display the meanings and styles of different types of nodes. The node filtering sub-module, which is used to quickly filter out the interested nodes according to specific conditions. The flexible interaction control sub-module for relationship connection lines, which is used to implement interaction operations by adopting different interaction algorithms for different line types, enhancing the interactivity between the user and the visualization graph. The sub-module for distributed loading and saving of large amounts of data, which is used to efficiently load and distributively save large amounts of data. Specifically, when dealing with large-scale data, through optimized algorithms, the efficient loading of data is realized, and at the same time, the support for distributively saving the processed data is provided.

6. The visual data processing and interaction system based on ANTV / G6 according to claim 5, characterized in that, In the flexible interaction control sub-module for relationship connection lines, in the visualization interface, the user selects different connection line types through the connection line type selector. The connection line types include dashed lines, straight lines, arcs, and broken lines. The connection line type selector is in the form of a drop-down menu and a button group, which is convenient for the user to quickly switch.

7. The visualization data processing and interaction system based on ANTV / G6 according to claim 6, wherein The specific implementation method of the flexible interaction control sub-module for relationship connection lines is as follows: (1) When the user selects a dashed line, by default, the dashed line represents the recommended topological relationship. At this time, the algorithm controller calls the relevant algorithm to process the data of the recommended topological relationship, analyzes the potential connections and optimal paths among the data nodes. After the processing is completed, the recommended topological relationship is converted into a real topological relationship and displayed on the visualization interface to help the user intuitively understand the recommended association structure among the data. (2) After selecting the straight line type, the algorithm controller starts the corresponding interaction algorithm. When the user operates the mouse, the straight line moves following the mouse, and at the same time, the user adjusts the new topological relationship through mouse operations. (3) Similar to the straight line, after selecting the arc type, the algorithm controller drives the interaction algorithm. When the mouse is operated, the arc follows the mouse, and it supports the user to adjust the topological relationship represented by the arc through mouse operations, dynamically updates the display, presents the new connection state, and meets the user's personalized settings for the arc connection relationship. (4) As the default line type, when the polyline is selected, the algorithm controller executes the corresponding algorithm. When the mouse moves, the polyline follows, and the user can adjust the position of the polyline through mouse operations, and can also adjust the position of the polyline connected to the corresponding node by changing the node position. At the same time, the shape and connection of the polyline are changed in real time according to the user's operations, which is convenient for the user to construct complex data connection relationships.

8. The visual data processing and interaction system based on ANTV / G6 according to claim 1, wherein The specific working process of this system is as follows: S1. The user selects the data elements to be visualized in the main system, sets the hierarchical structure and imports the relationship data. S2. The main system transmits the processed data to the Antv / g6 data visualization controller, and the Antv / g6 data visualization controller performs visualization rendering processing on the data to generate preliminary visualization graphics. S3. The interaction controller monitors the user's operations in real time, and according to the user's interaction instructions, calls the corresponding interaction algorithm to dynamically update the visualization graphics. S4. After the user completes the visualization analysis, the results are exported in a specified format through the data export module, or the data is transmitted to other analysis tools through the reserved interface.

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