Method, medium and equipment for generating multi-level user incidence relation based on SVG (Scalable Vector Graphics) vector diagram

Abstract

The invention relates to a method for generating a multilevel user association relationship based on an SVG vector diagram, a computer readable storage medium and electronic equipment, and the method comprises the steps: obtaining the interaction data of a plurality of users in a digital audio-visual place, carrying out the behavior similarity calculation of the interaction data, obtaining the user feature vectors corresponding to the plurality of users, and obtaining the user feature vectors corresponding to the plurality of users; an SVG vector diagram is constructed according to the user feature vectors of the multiple users, the SVG vector diagram comprises nodes and connecting lines, and the SVG vector diagram is dynamically updated according to changes of the user feature vectors. The visual chart generated based on the SVG vector diagram can maintain definition under any resolution, and a user is supported to carry out zoom-in or zoom-out operation on the chart according to needs without distortion.

Description

Technical Field

[0001] The present invention relates to the field of graphic visualization, and in particular to a method for generating multi-level user association relationships based on SVG vector graphics, a computer-readable storage medium and an electronic device. Background Art

[0002] Existing user relationship graph visualization technologies mostly use static or two-dimensional representations, which are difficult to effectively present the complex interactive relationships between multi-level users. Especially when a large number of users and their relationships are involved, traditional two-dimensional graphs have limited expressiveness and poor interactivity, and cannot intuitively and clearly display the hierarchical structure and interaction frequency between different users. In addition, although many Canvas-based solutions can achieve interactive graphs, their performance is limited under complex data, and graphics rendering is time-consuming, making it difficult to dynamically display and update relationship graphs.

[0003] SVG vector graphics are widely used in Web development and have good scalability, interactivity and rendering performance. However, how to combine the characteristics of SVG to achieve the generation of three-dimensional, interactive, multi-level user network relationship charts is still a problem that needs to be solved in current technology. Summary of the invention

[0004] Therefore, it is necessary to provide a method for generating multi-level user association relationships based on SVG vector graphics, so as to solve the problems of poor interactivity, low display complexity and low dynamic update performance of multi-level user relationship graphs in the prior art.

[0005] To achieve the above object, in a first aspect, the present invention relates to a method for generating a multi-level user association relationship based on an SVG vector graph, the method comprising the following steps:

[0006] Acquire interaction data of multiple users in a digital audio-visual venue, wherein the interaction data includes user identifications and interaction frequencies between users;

[0007] Calculating the behavior similarity of the interaction data to obtain user feature vectors corresponding to multiple users, wherein the user feature vectors include user level, user identification, and association relationships between the current user and other users;

[0008] Constructing an SVG vector map according to user feature vectors of multiple users, wherein the SVG vector map includes nodes and connecting lines, wherein the nodes are used to represent user identifiers and user levels, and the connecting lines are used to represent association relationships between the current user and other users;

[0009] The SVG vector image is dynamically updated according to changes in the user feature vector.

[0010] Furthermore, the method further comprises:

[0011] An operation instruction for the SVG vector image is received, and a corresponding user feature vector is displayed according to the operation instruction.

[0012] Furthermore, the method further comprises:

[0013] Implementing 3D projection of the SVG vector image through JavaScript scripts, so that the SVG vector image has a three-dimensional effect;

[0014] Furthermore, the method further comprises:

[0015] The SVG vector image is rendered layer by layer according to the user level and the association relationship between the current user and other users according to the preset data volume.

[0016] Furthermore, the method further comprises:

[0017] After detecting a user's reservation instruction for the digital audio-visual venue, actively sending first promotion information to a first user group, the first user group includes a number of users who are at a first level of association with the current user, and the first promotion information includes the identification information of the current user and the location information of the digital audio-visual venue;

[0018] Receive first feedback results from several users who are closely associated with the current user regarding the first promotion information, determine the number of participating users based on the first feedback results, and if the determined number of participating users is less than a lower limit of the recommended number of users corresponding to the digital audio-visual venue reserved by the current user, send second promotion information to a second user group, the second user group including several users who are at a second level of association with the current user, or several users who are at a first level of association with users in the first user group, the second level being less than the first level, the second promotion information including identification information of the current user and location information of the digital audio-visual venue, or also including identification information of users in the first user group.

[0019] Furthermore, the method further comprises:

[0020] If the number of users associated with a certain user exceeds a preset threshold, the user will be listed as a seed user;

[0021] The third promotion information is sent to the seed user regularly according to a preset period, and the third promotion information includes an activity content introduction and activity address information.

[0022] Furthermore, the method further comprises:

[0023] Get the historical consumption amount of each user;

[0024] A second feedback result of the seed user in response to the third promotion information is received, and fourth promotion information is sent to several users with the highest historical consumption amounts in the seed node relationship topology according to the second feedback result, wherein the fourth promotion information includes identification information of the seed user and the third promotion information.

[0025] Furthermore, the method further comprises:

[0026] Setting a promotion score for each user, the promotion score is determined based on the historical consumption amount of each user, the closeness of the relationship with the seed user, and the promotion impact factor;

[0027] constructing an initial set of users to be promoted according to the promotion scores, and sending the fourth promotion information to user identifiers in the initial set of users to be promoted;

[0028] counting the third feedback results of each user on the fourth promotion information, adaptively updating and replacing the user identifiers in the set of users to be promoted according to the third feedback results, and sending fifth promotion information to the corresponding users with the adjusted user identifiers, wherein the fifth promotion information includes the fourth promotion information and the user identifiers that have been confirmed to participate and have the deepest association with the users in the current set of users to be promoted;

[0029] The user identifiers of the user set to be promoted that is finally determined are recorded, and the promotion influence factor corresponding to each user in the next promotion is adjusted according to the recording result.

[0030] In a second aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for generating multi-level user association relationships based on an SVG vector image as described in the first aspect of the present application.

[0031] In a third aspect, the present application also provides an electronic device, including a processor and a storage medium, wherein a computer program is stored on the storage medium, and when the computer program is executed by the processor, the method for generating a multi-level user association relationship based on an SVG vector diagram as described in the first aspect of the present application is implemented.

[0032] Different from the prior art, the method, computer-readable storage medium and electronic device for generating multi-level user association relationships based on SVG vector graphics described in the above technical solution include: obtaining interaction data of multiple users in a digital audio-visual venue, calculating the behavioral similarity of the interaction data, obtaining user feature vectors corresponding to the multiple users, constructing an SVG vector graphics according to the user feature vectors of the multiple users, the SVG vector graphics including nodes and connecting lines, and dynamically updating the SVG vector graphics according to changes in the user feature vectors. The visualization chart generated based on the SVG vector graphics can maintain clarity at any resolution, and supports users to zoom in or out on the chart as needed without distortion. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A flowchart of a method for generating a multi-level user association relationship based on an SVG vector graph according to a first exemplary embodiment of the present invention;

[0034] Figure 2 A flowchart of a method for generating a multi-level user association relationship based on an SVG vector graph according to a second exemplary embodiment of the present invention;

[0035] Figure 3 A flowchart of a method for generating a multi-level user association relationship based on an SVG vector graph according to a third exemplary embodiment of the present invention;

[0036] Figure 4 A flowchart of a method for generating a multi-level user association relationship based on an SVG vector graph according to a fourth exemplary embodiment of the present invention;

[0037] Figure 5 A schematic diagram of a module of a video-on-demand device according to the present invention;

[0038] Reference numerals:

[0039] 10. Electronic equipment;

[0040] 101. Processor;

[0041] 102. Storage medium. DETAILED DESCRIPTION

[0042] In order to explain in detail the possible application scenarios, technical principles, specific schemes that can be implemented, and the purposes and effects that can be achieved, the following is a detailed description of the specific embodiments listed in conjunction with the accompanying drawings. The embodiments described herein are only used to more clearly illustrate the technical solutions of the present application, and are therefore only used as examples, and cannot be used to limit the scope of protection of the present application.

[0043] Reference to "embodiment" herein means that the specific features, structures or characteristics described in conjunction with the embodiment may be included in at least one embodiment of the present application. The term "embodiment" appearing in various places in the specification does not necessarily refer to the same embodiment, nor does it particularly limit its independence or association with other embodiments. In principle, in the present application, as long as there is no technical contradiction or conflict, the various technical features mentioned in the embodiments can be combined in any way to form a corresponding implementable technical solution.

[0044] Unless otherwise defined, the technical terms used in this document have the same meanings as those generally understood by those skilled in the art to which this application belongs; the use of relevant terms in this document is only for describing specific embodiments and is not intended to limit this application.

[0045] In the description of this application, the term "and / or" is an expression used to describe the logical relationship between objects, indicating that three relationships may exist, for example, A and / or B, which means: A exists, B exists, and A and B exist at the same time. In addition, the character " / " in this article generally indicates that the objects before and after are in an "or" logical relationship.

[0046] In the present application, terms such as “first” and “second” are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship of quantity, priority or sequence between these entities or operations.

[0047] Without further limitations, in this application, the words "include", "comprises", "has" or other similar expressions used in sentences are intended to cover non-exclusive inclusion. These expressions do not exclude the presence of additional elements in the process, method or product including the elements, so that the process, method or product including a series of elements may include not only those limited elements, but also other elements not explicitly listed, or also include elements inherent to such process, method or product.

[0048] In this application, expressions such as "greater than", "less than", "exceed" and the like are understood to exclude the number itself; expressions such as "above", "below", "within" and the like are understood to include the number itself. In addition, in the description of the embodiments of this application, "multiple" means more than two (including two), and similar expressions related to "multiple" are also understood in this way, such as "multiple groups", "multiple times", etc., unless otherwise clearly and specifically limited.

[0049] In the first aspect, Figure 1 As shown, the present application provides a method for generating a multi-level user association relationship based on an SVG vector graph, the method comprising the following steps:

[0050] Step S101: Acquire interaction data of multiple users in a digital audio-visual venue;

[0051] Step S102: Calculating the behavior similarity of the interaction data to obtain user feature vectors corresponding to multiple users, wherein the user feature vectors include user level, user identification, and association relationships between the current user and other users;

[0052] Step S103: constructing an SVG vector map according to user feature vectors of multiple users;

[0053] Step S104: dynamically updating the SVG vector image according to changes in the user feature vector.

[0054] In step S101, the digital audio-visual venue may be a KTV, a karaoke room, a home song request machine, etc. The interaction data includes a user identifier and the frequency of interaction between users. Specifically, the user identifier may include information such as the user's name, bound mobile phone number, whether the user is a member (if so, the member number may also be included), and ID number. The frequency of interaction between users may be the frequency of jointly requesting songs in the same time period in the same digital audio-visual venue, the number of games played together in the same time period in the same digital audio-visual venue, or the number of songs of the same style requested.

[0055] In step S102, the behavioral similarity calculation of the interactive data can be performed using a cosine similarity algorithm. The cosine similarity algorithm is an algorithm for measuring the similarity between two vectors. It measures their similarity by calculating the cosine value of the angle between the two vectors. In the vector space model, each dimension of a vector can represent a feature. For application scenarios such as text, these features can be the frequency of words, etc. By analyzing the user's interactive data using the cosine similarity algorithm, users with similar behaviors can be grouped together to obtain user feature vectors corresponding to multiple users.

[0056] Among them, the user level is the level corresponding to the user. For example, users can be divided into level 1, level 2, level 3, etc. according to the frequency of song requests or interactive games. Different topological diagrams can also be designed for each user. The current user itself is at level 0, and users who interact with the current user more frequently (such as users whose number of interactions exceeds the first preset frequency) are set to level 1, and users who interact with the current user less frequently (such as users whose number of interactions is between the first preset frequency and the second preset frequency) are set to level 2, and so on. The association relationship between the current user and other users can be divided into levels according to the frequency of interaction, such as deep association, medium association, low association, etc.

[0057] In step S103, the SVG vector image includes nodes and connecting lines, wherein the nodes are used to represent user identifiers and user levels, and the connecting lines are used to represent the association relationship between the current user and other users. SVG (Scalable Vector Graphics) is a vector graphics format based on XML (Extensible Markup Language). It uses text format to describe graphics, which makes it essentially different from pixel-based bitmap formats (such as JPEG, PNG).

[0058] In step S104, the condition for updating data can be triggered based on the user's consumption behavior, or a predetermined update cycle can be set. When the time from the last update reaches a preset time interval, the user feature vector is automatically updated based on the newly generated interactive data during this period, thereby generating a new SVG image.

[0059] The above solution can clearly and intuitively display the multi-level relationships between users through SVG diagrams, and supports real-time dynamic updates, which is particularly suitable for scenarios with complex user relationships.

[0060] In some embodiments, the method further includes: receiving an operation instruction for the SVG vector image, and displaying a corresponding user feature vector according to the operation instruction. In other embodiments, the method further includes: implementing 3D projection of the SVG vector image through a JavaScript script, so that the SVG vector image has a three-dimensional effect.

[0061] The operation instructions may be instructions for rotating, scaling, dragging, etc. the user node on the 3D effect, and the user can intuitively observe the connections of different levels through the above operation instructions. The user can also display the player's detailed information and relationship data with other players by clicking or floating the event response of the node.

[0062] In some embodiments, the method further includes: rendering the SVG vector map layer by layer according to the preset data volume based on the user level and the association relationship between the current user and other users. Using lazy loading technology to gradually render each level of the user relationship map can reduce the performance pressure of drawing a large number of nodes and connections at one time. By optimizing the rendering efficiency of SVG and D3.js, it is ensured that the loading speed of the chart and the interactive response are smooth when processing large-scale user relationship data.

[0063] In some embodiments, when implementing the above method of the present application, the user's interactive data can be obtained through a database query or through a data interface, and then the interactive data is processed, the users are divided into multiple levels, and different depths of relationship data sets are divided according to the levels. Then the processed data is converted into a format suitable for SVG rendering, including defining the attributes of nodes and links, defining nodes including user ID, user level, user related information, etc., and the links represent the interactive relationship and number of interactions between users. The D3.js library is used to calculate the force-directed layout algorithm, determine the distribution position of the user node on the two-dimensional plane, and determine the weight of the link according to the interactive relationship. Then the 3D projection of the multi-level relationship is realized through JavaScript scripts, so that the two-dimensional SVG graphics have a three-dimensional effect. Based on the aforementioned layout data, SVG elements are used to generate nodes and links, the nodes are displayed through circles or other graphic elements, and the links represent the interactive relationship between users with lines. Dynamically update the SVG graphics to respond to changes in user relationship data to ensure real-time display of the latest personal connections.

[0064] Compared with the prior art, the present invention has the following advantages:

[0065] (1) Strong scalability: Visual charts generated based on SVG vector graphics can maintain clarity at any resolution, allowing users to zoom in or out on the chart as needed without distortion.

[0066] (2) Three-dimensional sense: Through the force-directed layout algorithm and three-dimensional projection technology of D3.js, the user's network relationship diagram is upgraded from two-dimensional to three-dimensional, making the representation of multi-level relationships more three-dimensional and intuitive.

[0067] (3) Real-time dynamic update: This method supports dynamic updating of relationship data, which can reflect changes in relationships between users in real time and ensure that users obtain the latest relationship diagram.

[0068] (4) Strong interactivity: By supporting interactive operations such as zooming, rotating, and clicking, users can gain a deeper understanding of complex interpersonal relationships and easily switch between different levels of observation.

[0069] (5) Superior performance: In the processing of large-scale user relationship data, performance optimization and lazy loading technology are used to ensure smooth chart rendering and fast interactive response.

[0070] In some embodiments, Figure 2 As shown, the method also includes:

[0071] Step S201: after detecting a user's reservation instruction for the digital audio-visual venue, actively sending a first promotion message to a first user group;

[0072] In step S201, the first user group includes several users who are at the first level of association with the current user, and the first promotion information includes the identification information of the current user and the location information of the digital audio-visual venue. In short, if user A has reserved a certain private room, the first promotion information can be sent to several users who have the closest relationship with user A, informing them that user A has reserved the private room and the location of the private room.

[0073] Step S202: receiving first feedback results from a number of users who are closely associated with the current user regarding the first promotion information, and determining the number of participating users based on statistics of the first feedback results.

[0074] In step S202, the first feedback result includes a reply of whether the first user group agrees to participate in the party. When a confirmation reply is received, the user status in the first user group can be marked as "agree to participate". If the feedback received is that the user disagrees to participate or no feedback is received for a long time, the user status can be marked as "disagree to participate".

[0075] Step S203: If the number of users determined to participate is less than the lower limit of the recommended number of users corresponding to the digital audio-visual venue reserved by the current user, the second promotion information is sent to the second user group.

[0076] In step S203, the second user group includes several users who are at the second level of association with the current user, or several users who are at the first level of association with users in the first user group, the second level is lower than the first level, and the second promotion information includes identification information of the current user and location information of the digital audio-visual venue, or also includes identification information of users in the first user group.

[0077] Assume that user A has booked a private room. The first user group with the closest relationship to user A includes user B, user C and user D. The closest relationship to user B is user E. The closest relationship to user C is user F and user G. The closest relationship to user D is user H. Assuming that the recommended minimum number of participants for the private room currently booked by user A is 4, after user A books the private room, the system will automatically obtain user A's network and send invitations to users B-user D. Assuming that user B and user C agree, but user D refuses, the number of participants is 3 at this time, and invitations will be sent to users E, user F, and user G. If two of users E, user F, and user G agree to the above requirements, the next promotion information will be stopped. Otherwise, the promotion information will continue to be sent to the next user group (that is, the users with the closest relationship to users E, user F, and user G will be informed in the promotion information which users among users E, user F, and user G have attended the meeting).

[0078] Furthermore, when sending invitations to users at the next level, the association between the users at the next level and the users who currently booked the box is also evaluated, and the weights are comprehensively calculated to screen out the options that need to be pushed the most. For example, when sending invitations to user E, user F, and user G, the association between user E, user F, and user G can also be evaluated separately. Assuming that after evaluation, the associations from strong to weak are user G, user E, and user F, the second promotion information will be sent to user G first. If user G refuses, the second promotion information will continue to be sent to user E. If user G agrees to participate, because the number of people has reached the lower limit of the current box capacity, the second promotion information can be stopped from being sent to user E. User A or user B can invite user E to participate in other ways. If both user G and user E do not agree to participate, the second promotion information will be sent to user F accordingly, and so on.

[0079] Through this promotion method, after user A has booked a private room, even if user A is relatively unfamiliar with user E, user F, etc., user E has a close relationship with user B, user F has a close relationship with user C, and user A, user B, and user C are all confirmed participants. Therefore, among all other participants in this party, there is at least one close friend with whom they have a close relationship, making it easier for participants to accept the arrangement of this private room party and increasing the success rate.

[0080] Of course, if the box is booked by user A, after other users express their willingness to participate, the system will automatically obtain the user's basic information (that is, the user is a close friend of XXX) and send it to user A. User A also has the right to screen and approve the people who agree to participate, and feedback the approval results to other participating users.

[0081] In some embodiments, the method further includes: if the number of users associated with a certain user exceeds a preset threshold, the user is listed as a seed user; and third promotion information is regularly sent to the seed user according to a preset period, wherein the third promotion information includes an activity content introduction and activity address information.

[0082] In short, if the system detects that there are a large number of users associated with a certain user, it will send third-party promotional information containing invitations to activities with newly launched content to this user group in a targeted manner to collect feedback from this user group on new features to facilitate subsequent improvements.

[0083] like Figure 3 As shown, in some embodiments, the method further includes:

[0084] Step S301: Obtain the historical consumption amount of each user;

[0085] Step S302: receiving the second feedback result of the seed user for the third promotion information, and sending fourth promotion information to several users with the highest historical consumption amount in the seed node relationship topology according to the second feedback result. The fourth promotion information includes the identification information of the seed user and the third promotion information.

[0086] In short, if the seed user agrees to participate in an event, invitations can be sent to the consumer groups whose historical consumption records show a higher amount of consumption and who have an associated relationship with the seed user, so as to promote the merchant's operating efficiency and subsequent event promotion.

[0087] In some embodiments, Figure 4 As shown, the method also includes:

[0088] Step S401: Setting a promotion score for each user.

[0089] In step S401, the promotion score is determined according to the historical consumption amount of each user, the closeness of the association with the seed user, and the promotion influence factor.

[0090] Step S402: constructing an initial set of users to be promoted according to the promotion scores, and sending the fourth promotion information to user identifiers in the initial set of users to be promoted.

[0091] Step S403: Count the third feedback results of each user on the fourth promotion information, adaptively update and replace the user identifiers in the set of users to be promoted according to the third feedback results, and send a fifth promotion letter to the user corresponding to the adjusted user identifier.

[0092] In step S403, the fifth promotion information includes the fourth promotion information and the user identifiers of the users who have been confirmed to participate and have the deepest association with the users in the current set of users to be promoted.

[0093] Step S404: Record the user identifiers in the set of users to be promoted that are finally determined, and adjust the promotion influence factor corresponding to each user in the next promotion according to the recording result.

[0094] In short, for the user group that needs to be promoted for the activity, the historical consumption amount of each user, the closeness of the relationship with the seed user, and the promotion influence factor can be comprehensively considered to determine it. It can also be determined based on the feedback results of each user on this activity. For example, if a user is in the set of users to be promoted, but the user refuses the next such activity, the influence factor of this activity type corresponding to the user will be lowered. When promoting this type of activity subsequently, it will be recommended to other users first.

[0095] In a second aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for generating multi-level user association relationships based on an SVG vector diagram as described in the first aspect of the present invention.

[0096] The computer-readable storage medium may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories.

[0097] The non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a ferromagnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD ROM); the magnetic surface memory can be a disk memory or a tape memory.

[0098] The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), direct memory bus random access memory (DRRAM). The computer-readable storage medium described in the embodiments of the present invention is intended to include these and any other suitable types of memory.

[0099] like Figure 5 As shown, in a third aspect, the present invention provides an electronic device 10, comprising a processor 101 and a storage medium 102, wherein a computer program is stored on the storage medium, and when the computer program is executed by the processor, the method for generating multi-level user association relationships based on an SVG vector diagram as described in the first aspect of the present invention is implemented.

[0100] In some embodiments, the processor can be implemented by software, hardware, firmware or a combination thereof, and can use a circuit, a single or multiple application specific integrated circuits (Application Specific Integrated Circuit, ASIC), a digital signal processor (Digital Signal Processor, DSP), a digital signal processing device (Digital Signal Processing Device, DSPD), a programmable logic device (Programmable Logic Device, PLD), a field programmable gate array (Field Programmable Gate Array, FPGA), a central processing unit (Central Processing Unit, CPU), a controller, a microcontroller, and at least one of a microprocessor, so that the processor can execute some or all of the steps or any combination of the steps in the method for generating multi-level user association relationships based on SVG vector graphics described in the various embodiments of the present application.

[0101] It should be noted that, although the above embodiments have been described in this article, the patent protection scope of the present invention is not limited thereby. Therefore, based on the innovative concept of the present invention, changes and modifications made to the embodiments described herein, or equivalent structures or equivalent process changes made using the contents of the present invention specification and drawings, directly or indirectly applying the above technical solutions to other related technical fields, are all included in the patent protection scope of the present invention.

Claims

1. A method for generating multi-level user association relationships based on SVG vector graphics, characterized in that: The method comprises the following steps: Acquire interaction data of multiple users in a digital audio-visual venue, wherein the interaction data includes user identifications and interaction frequencies between users; Calculating the behavior similarity of the interaction data to obtain user feature vectors corresponding to multiple users, wherein the user feature vectors include user level, user identification, and association relationships between the current user and other users; Constructing an SVG vector map according to user feature vectors of multiple users, wherein the SVG vector map includes nodes and connecting lines, wherein the nodes are used to represent user identifiers and user levels, and the connecting lines are used to represent association relationships between the current user and other users; The SVG vector image is dynamically updated according to changes in the user feature vector.

2. The method for generating multi-level user association relationships in an SVG vector map according to claim 1, characterized in that: The method further comprises: An operation instruction for the SVG vector image is received, and a corresponding user feature vector is displayed according to the operation instruction.

3. The method for generating multi-level user association relationships in an SVG vector map according to claim 1, characterized in that: The method further comprises: The 3D projection of the SVG vector image is realized by JavaScript script, so that the SVG vector image has a three-dimensional effect.

4. The method for generating multi-level user association relationships in an SVG vector map as claimed in claim 3, characterized in that: The method further comprises: The SVG vector image is rendered layer by layer according to the user level and the association relationship between the current user and other users according to the preset data volume.

5. The method for generating multi-level user association relationships in an SVG vector map according to claim 1, characterized in that: The method further comprises: After detecting a user's reservation instruction for the digital audio-visual venue, actively sending first promotion information to a first user group, the first user group includes a number of users who are at a first level of association with the current user, and the first promotion information includes the identification information of the current user and the location information of the digital audio-visual venue; Receive first feedback results from several users who are closely associated with the current user regarding the first promotion information, determine the number of participating users based on the first feedback results, and if the determined number of participating users is less than a lower limit of the recommended number of users corresponding to the digital audio-visual venue reserved by the current user, send second promotion information to a second user group, the second user group including several users who are at a second level of association with the current user, or several users who are at a first level of association with users in the first user group, the second level being less than the first level, the second promotion information including identification information of the current user and location information of the digital audio-visual venue, or also including identification information of users in the first user group.

6. The method for generating multi-level user association relationships in an SVG vector map according to claim 1, characterized in that: The method further comprises: If the number of users associated with a certain user exceeds a preset threshold, the user will be listed as a seed user; The third promotion information is sent to the seed user regularly according to a preset period, and the third promotion information includes an activity content introduction and activity address information.

7. The method for generating multi-level user association relationships in an SVG vector map according to claim 6, characterized in that: The method further comprises: Get the historical consumption amount of each user; A second feedback result of the seed user in response to the third promotion information is received, and fourth promotion information is sent to several users with the highest historical consumption amounts in the seed node relationship topology according to the second feedback result, wherein the fourth promotion information includes identification information of the seed user and the third promotion information.

8. The method for generating multi-level user association relationships in an SVG vector map according to claim 7, characterized in that: The method further comprises: Setting a promotion score for each user, the promotion score is determined based on the amount of historical consumption of each user, the closeness of the relationship with the seed user, and the promotion impact factor; constructing an initial set of users to be promoted according to the promotion scores, and sending the fourth promotion information to user identifiers in the initial set of users to be promoted; counting the third feedback results of each user on the fourth promotion information, adaptively updating and replacing the user identifiers in the set of users to be promoted according to the third feedback results, and sending fifth promotion information to the corresponding users with the adjusted user identifiers, wherein the fifth promotion information includes the fourth promotion information and the user identifiers that have been confirmed to participate and have the deepest association with the users in the current set of users to be promoted; The user identifiers of the user set to be promoted that is finally determined are recorded, and the promotion influence factor corresponding to each user in the next promotion is adjusted according to the recording result.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for generating multi-level user association relationships based on an SVG vector graph as described in any one of claims 1 to 8 is implemented.

10. An electronic device, characterized in that: It includes a processor and a storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by the processor, the method for generating multi-level user association relationships based on an SVG vector graph as described in any one of claims 1 to 8 is implemented.

Images