Message control method, product, electronic device and medium

Abstract

The present invention discloses a message control method, product, electronic device and medium, and relates to the field of data processing technology. The purpose of controlling the propagation of messages is achieved by removing nodes in the process of message propagation, and in the process of removing nodes, a first preset number of root nodes selected from a tree structure and a second preset number of child nodes selected from a subtree corresponding to the root node are removed. In a complex message propagation network, the nodes to be removed are selected from the root node and the subtree corresponding to the root node as units, that is, the nodes to be removed are determined in units of a local subtree structure. Since the local subtree structure is divided from the entire network structure, the scale of the local subtree structure is smaller than the scale of the entire network. Therefore, compared with the method of analyzing the global information of the entire network as a unit, the method provided by the present invention reduces the computational complexity, has a fast response speed, improves the efficiency of determining the removal method, and improves the efficiency of controlling the propagation of messages.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a message control method, product, electronic equipment and medium. Background Art

[0002] With the development of technology, social networking platforms have become an important channel for people to communicate and share information. These platforms have built a huge network composed of users and their connections. Users can not only share positive content through these networks, but there are also some users who spread false information or even rumors, causing negative effects.

[0003] In practice, the structure of rumor networks is relatively large. In order to control the spread of rumors, related technologies use centralized processing methods to remove key connections (i.e., remove edges) or remove nodes in social networks. In the method of removing edges, since there are usually multiple propagation paths between nodes, the computational complexity is higher than that of removing nodes. In addition, in the process of removing edges or nodes using centralized processing methods, since each calculation considers the global information of the entire network, the computational complexity is high and the response speed is slow.

[0004] It can be seen that in the process of controlling rumor information, how to reduce the complexity of calculations and improve the efficiency of rumor control is a technical problem that people in this field urgently need to solve. Summary of the invention

[0005] The purpose of the present invention is to provide a message control method, product, electronic device and medium to solve the technical problems of high computational complexity and low rumor control efficiency in the process of controlling the spread of rumors by using a centralized processing method to remove key connections in a social network (i.e., removing edges) or removing nodes in a social network.

[0006] In order to solve the above technical problems, the present invention provides a message control method, comprising:

[0007] Get the tree structure corresponding to the current message propagation;

[0008] Selecting a first preset number of root nodes from the tree structure and selecting a second preset number of child nodes from the subtrees corresponding to the root nodes;

[0009] Get the situation of the remaining nodes on the subtree activated by the seed node after removing the selected node;

[0010] When it is detected that the situation of the remaining nodes on the subtree activated by the seed node meets the preset requirements, the nodes are removed according to the corresponding removal method when the preset requirements are met;

[0011] The tree structure after removing nodes is used to control the transmission of messages.

[0012] On the one hand, the case where the seed node activates the remaining nodes on the subtree is the sum of the probabilities of the seed node activating the remaining nodes on the subtree; before selecting a first preset number of root nodes from the tree structure and selecting a second preset number of child nodes from the subtree corresponding to the root node, the method further includes:

[0013] Obtaining the total number of selected nodes; wherein the sum of the first preset number and the second preset number is equal to the total number;

[0014] The transmission of the control message using the tree structure after removing the node includes:

[0015] The transmission of the message is controlled by using the tree structure after the total number of nodes are removed.

[0016] On the other hand, determining the probability that the seed node activates the current node on the tree structure includes:

[0017] Obtaining the current message propagation path, the activation probability of the directed edges between nodes, and the situation of the current node; wherein the current node is any node on the tree structure; the situation of the current node includes whether the current node is a root node or a seed node, and all the seed nodes activate the current node;

[0018] The probability of the seed node activating the current node on the tree structure is determined according to the situation of the current node and / or the activation probability of the current message propagation path and the directed edges between nodes.

[0019] On the other hand, determining the probability of the seed node activating the current node on the tree structure according to the situation of the current node and / or the activation probability of the directed edge between the current message propagation path and the node includes:

[0020] In the case where it is detected that the current node is the seed node, determining that the probability that the seed node activates the current node on the tree structure is 1;

[0021] In the case where it is detected that all the seed nodes are not transmitted to the current node, determining that the probability of the seed node activating the current node on the tree structure is 0;

[0022] When it is detected that the current node is not the seed node and there is at least one seed node transmitting to the current node, the probability of the seed node activating the current node on the tree structure is determined based on the activation probability corresponding to all paths of the current message transmitted to the current node and the directed edges between the nodes on each path.

[0023] On the other hand, determining the probability of the seed node activating the current node on the tree structure according to all paths of the current message transmitted to the current node and the activation probabilities corresponding to the directed edges between the nodes on each path includes:

[0024] Obtain the number of all paths for transmitting the current message to the current node;

[0025] When it is detected that the number of the paths is less than or equal to the first number, taking the sum of the activation probabilities corresponding to the directed edges between the nodes on each path as the probability of the seed node activating the current node on the tree structure;

[0026] When it is detected that the number of the paths is greater than the first number, the opposite probability of the probability that all the seed nodes do not transmit to the current node is obtained; wherein the probability that the current seed node does not transmit to the current node is the difference between 1 and the sum of the activation probabilities corresponding to the directed edges between the upper nodes of all the paths; all the paths are all the paths from the current seed node to the current node and each path includes multiple directed edges;

[0027] The opposition probability is used as the probability of the seed node activating the current node on the tree structure.

[0028] On the other hand, the first preset number is 0, and removing the selected second preset number of child nodes from the subtree corresponding to the root node includes:

[0029] Using different removal methods to remove a second preset number of child nodes selected from the subtree corresponding to the root node; wherein the number of child nodes selected from the subtree corresponding to the root node under different removal methods is different;

[0030] The sum of the probabilities of the seed node activating the remaining nodes on the subtree after removing the selected nodes using the current removal method includes:

[0031] Obtaining a first sum obtained by adding the sum of the probabilities of the seed node activating the remaining child nodes on each subtree after removing the second preset number of child nodes selected from the subtree corresponding to the root node using the current removal method and the first sum obtained by adding the first probability of the seed node activating the root node;

[0032] The first sum is taken as the sum of probabilities of the seed node activating the remaining nodes on the subtree under the current removal mode.

[0033] On the other hand, after obtaining the node selected by removing the node in the current removal mode, the first probability that the seed node activates the root node includes:

[0034] Obtaining a first initial probability that the seed node activates the root node after the selected node is removed using the current removal method;

[0035] When it is detected that the root node is an actual node and the root node is not the seed node, determining a first probability that the seed node activates the root node as the first initial probability;

[0036] When it is detected that the root node is a virtual node, it is determined that the first probability of the seed node activating the root node is 0.

[0037] On the other hand, the first preset number is not 0, and the sum of the probabilities of the seed node activating the remaining nodes on the subtree after removing the selected node using the current removal method includes:

[0038] Obtaining a second sum obtained by adding the sum of the probabilities of the seed node activating the remaining child nodes on each subtree after the selected node is removed by using the current removal method and the second probability of the seed node activating the root node;

[0039] The second sum is taken as the sum of probabilities of the seed node activating the remaining nodes on the subtree under the current removal mode.

[0040] On the other hand, after obtaining the node selected by removing the node in the current removal mode, the second probability that the seed node activates the root node includes:

[0041] Obtaining a second initial probability that the seed node activates the root node after the selected node is removed using the current removal method;

[0042] In the case where it is detected that the root node is not the seed node, determining that a second probability of the seed node activating the root node is 0;

[0043] In the case where it is detected that the root node is the seed node, the second probability of the seed node activating the root node is determined to be a probability obtained by multiplying the second initial probability by a preset value.

[0044] On the other hand, before selecting a first preset number of root nodes from the tree structure and selecting a second preset number of child nodes from the subtree corresponding to the root node, the method further includes:

[0045] Determining whether the tree structure is a binary tree structure;

[0046] If yes, then enter the step of selecting a first preset number of root nodes from the tree structure and selecting a second preset number of child nodes from the subtree corresponding to the root node;

[0047] If not, the tree structure is converted into a binary tree structure, and the process returns to the step of determining whether the tree structure is a binary tree structure.

[0048] On the other hand, converting the tree structure into a binary tree structure comprises:

[0049] Keeping the root node of the binary tree structure the same as the root node of the tree structure;

[0050] Get a target node whose number of child nodes is greater than the second number;

[0051] A subtree is established according to the number of child nodes corresponding to the target node to replace the corresponding target node; wherein the leaf nodes on the subtree are the same as the leaf nodes corresponding to the target node, and the probability of the leaf nodes on the subtree is the same as the activation probability of the directed edges between the nodes, and the probability of the virtual edges corresponding to the newly introduced virtual nodes is 1.

[0052] On the other hand, when it is detected that the sum of the probabilities of the seed node activating the remaining nodes on the subtree meets the preset requirement, removing the total number of nodes according to the corresponding removal method when the preset requirement is met includes:

[0053] When it is detected that the sum of the probabilities of the seed node activating the remaining nodes on the subtree is the smallest sum of the probabilities corresponding to all removal methods, the total number of nodes are removed according to the removal method corresponding to the smallest sum of the probabilities corresponding to all removal methods.

[0054] In order to solve the above technical problem, the present invention also provides a computer program product, including a computer program / instruction, which implements the steps of the above message control method when executed by a processor.

[0055] In order to solve the above technical problem, the present invention further provides an electronic device, comprising:

[0056] Memory for storing computer programs;

[0057] A processor is used to implement the steps of the above-mentioned message control method when executing the computer program.

[0058] In order to solve the above technical problem, the present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above message control method are implemented.

[0059] The beneficial effect of the present invention is that, in the message control method, first, a first preset number of root nodes are selected from the tree structure and a second preset number of child nodes are selected from the subtree corresponding to the root node; after removing the selected nodes, the situation of the seed node activating the remaining nodes on the subtree is obtained, and when it is detected that the situation of the seed node activating the remaining nodes on the subtree meets the preset requirements, the node is removed according to the corresponding removal method when the preset requirements are met, and finally the tree structure after the node is removed is used to control the transmission of the message. That is, the purpose of controlling the propagation of the message is achieved by removing the nodes in the message propagation process, and in the process of removing the nodes, the first preset number of root nodes selected from the tree structure and the second preset number of child nodes are removed from the subtree corresponding to the root node. In a complex message propagation network, the nodes to be removed are selected from the root node and the subtree corresponding to the root node as units, that is, the nodes to be removed are determined in units of the local subtree structure. Since the local subtree structure is divided from the entire network structure, the scale of the local subtree structure is smaller than the scale of the entire network. Therefore, compared with the method of analyzing the global information of the entire network as a unit, the method provided by the present invention reduces the computational complexity, has a fast response speed, and improves the efficiency of determining the removal method. , which improves the efficiency of controlling message propagation; secondly, compared with the method of removing edges, the method of removing nodes provided by the present invention does not consider the impact of removing multiple propagation paths between nodes on message control, but considers the impact of removing nodes on message control. Since in a complex message propagation network, the number of nodes is much smaller than the number of paths, the method provided by the present invention can reduce the amount of calculation when controlling information propagation and improve the efficiency of controlling message propagation; thirdly, the value of the first preset number and the value of the second preset number can be adjusted, so that a variety of removal methods can be provided, and then the final method of removing the node is selected from the multiple removal methods, that is, comprehensive consideration of multiple removal methods makes the determined removal method more accurate.

[0060] In addition, the situation where the seed node activates the remaining nodes on the subtree is the sum of the probabilities of the seed node activating the remaining nodes on the subtree, that is, the removal method adopted by the quantitative analysis, which improves the accuracy of the determined removal method; compared with the method of determining the probability of the seed node activating the current node on the tree structure without distinguishing the situation of the current node, the method provided by the present invention determines the probability of the seed node activating the current node on the tree structure according to the situation of the current node, and / or the current message propagation path and the activation probability of the directed edges between the nodes, and the situation of the current node includes the situation where the current node is a root node or a seed node, and the situation where all seed nodes activate the current node, which improves the efficiency and accuracy of determining the probability of the seed node activating the current node on the tree structure.

[0061] When determining the probability of a seed node activating the current node on a tree structure according to all paths of the current message transmitted to the current node and the activation probabilities corresponding to the directed edges between the nodes on each path, when there are multiple paths, the opposite probability of the probability that all seed nodes are not transmitted to the current node is obtained, and the opposite probability is used as the probability of the seed node activating the current node on the tree structure. Compared with the method of frontal calculation, the method provided by the present invention greatly reduces the amount of calculation and improves the efficiency of determining the probability of a seed node activating the current node on the tree structure.

[0062] When the first preset number is 0, all nodes are removed from the subtree corresponding to the root node. When determining the sum of the probabilities of the seed node activating the remaining nodes on the subtree in the removal mode, the method provided by the present invention considers whether the root node is an actual node or a virtual node. If the root node is a virtual node, the first probability of the seed node activating the root node is directly determined to be 0, which avoids the influence of the virtual node on the determined sum of probabilities, improves the accuracy of determining the sum of the probabilities of the seed node activating the remaining nodes on the subtree, and thus improves the accuracy of the determined removal mode and the accuracy of information control.

[0063] When the first preset number is not 0, the node is removed from the root node and the subtree corresponding to the root node. In the removal mode, when determining the sum of the probabilities of the seed node activating the remaining nodes on the subtree, whether the root node is a seed node is considered. When the root node is a seed node, the second probability of the seed node activating the root node is directly determined to be 0, which improves the efficiency of determining the seed node activating the root node; when the root node is not a seed node, the second probability of the seed node activating the root node is determined to be the probability obtained by multiplying the second initial probability and the preset value, that is, it is determined that the root node is a point that cannot be removed.

[0064] When the tree structure is not a binary tree structure, it needs to be converted into a binary tree structure. The removal method is determined based on the binary tree structure. Compared with the traditional general tree structure, the converted binary tree has advantages in simplified operation, space efficiency, recursive implementation, and scalability. For example, in terms of simplified operation, the structure of the binary tree is simpler, which makes tree operations (such as search, insertion, and deletion) more intuitive and easy to implement. In terms of space efficiency, since each node has at most two child nodes, the binary tree is usually more compact than the general tree, which helps to reduce the waste of storage space. In terms of recursive implementation, the recursive nature of the binary tree allows many operations to be implemented recursively, which is a natural and concise method in programming. In addition, in terms of scalability, the binary tree can be expanded to a multi-way tree to adapt to more complex data structure requirements while maintaining high efficiency of the operation. Moreover, in the process of converting to a binary tree, the probability of the virtual edge corresponding to the newly introduced virtual node is 1, which ensures the equivalence of message propagation.

[0065] When it is detected that the sum of the probabilities of the remaining nodes on the seed node activating the subtree is the smallest sum of the probabilities corresponding to all removal methods, the total number of nodes is removed according to the removal method corresponding to the smallest sum of the probabilities corresponding to all removal methods. The effective control of messages is achieved through the removal method corresponding to the smallest sum of the probabilities corresponding to all removal methods.

[0066] In addition, the present invention also provides a message control device, a computer program product, an electronic device and a computer-readable storage medium, which have the same or corresponding technical features as the message control method mentioned above and have the same effects as above. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0068] Figure 1 A flow chart of a message control method provided by an embodiment of the present invention;

[0069] Figure 2 A schematic diagram of a local subtree provided by an embodiment of the present invention;

[0070] Figure 3 A schematic diagram of a simple network message transmission provided by an embodiment of the present invention;

[0071] Figure 4 A framework diagram of dynamic programming for tree-type network rumor control provided by the present invention;

[0072] Figure 5 A schematic diagram of converting a general tree network provided by an embodiment of the present invention into a corresponding binary tree;

[0073] Figure 6 A schematic diagram of left and right child nodes of a binary tree provided by an embodiment of the present invention;

[0074] Figure 7 A structural diagram of an electronic device provided in another embodiment of the present invention. DETAILED DESCRIPTION

[0075] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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.

[0076] The core of the present invention is to provide a message control method, product, electronic device and medium to solve the technical problems of high computational complexity and low rumor control efficiency in the process of controlling the spread of rumors by using centralized processing to remove key connections in social networks (i.e., removing edges) or removing nodes in social networks.

[0077] The topological structure of social networks has an important impact on the spread and control of rumor information. A social network can be regarded as a complex network consisting of nodes (representing individual users) and edges (representing relationships or interactions between users). The messages in the present invention can be rumors or normal information. Taking the prevention of rumor propagation as an example, the relevant rumor prevention strategies can be divided into the method of removing network edges by changing the network topology and the method of removing network nodes. The following is a brief introduction to the relevant technologies of each of the above categories.

[0078] (1) Network edge removal method. This method uses centralized processing (considering the entire network each time) and focuses on the connections between users. It reduces the spread of rumor information by strategically removing key connections (edges) in the social network. Imagine a scenario: User A spreads a piece of false information, and user B, as a follower of A, chooses to unfollow, then the rumor cannot continue to spread in the network through B. This strategy of preventing the spread of rumors by disconnecting key connections usually adopts a centralized processing method to adjust the network structure under limited budget or cost constraints in order to achieve the purpose of curbing rumors.

[0079] In this method, first of all, it is necessary to accurately identify and remove those connections that are critical to the spread of rumors. Since there are usually multiple propagation paths between nodes, the computational complexity is high, and since centralized processing takes time to analyze and execute operations, the response speed may not be fast enough. In addition, due to the dynamics and complexity of social networks, this method may not be ideal in actual control effects, and sometimes it may not be able to effectively prevent the spread of rumors in a timely manner.

[0080] (2) Network node removal method. The core strategy of this method is to identify and remove key nodes in the social network, thereby creating "breakpoints" in the network structure and effectively blocking the spread of rumors. By removing nodes that play a pivotal role in the spread of rumors, the spread of rumors in the network can be weakened. For example, if the spread of a rumor mainly depends on a few highly active and widely connected users, then by removing these users, the further spread of the rumor can be greatly limited. The advantage of this method is that its implementation is relatively simple and direct, and does not require complex calculations or in-depth analysis of the network structure.

[0081] However, in the existing centralized processing methods, each calculation takes into account the global information of the entire network, so the computational complexity is high and the response speed is slow. It is not easy to determine which nodes are critical, because a set of evaluation indicators need to be developed to measure the influence of nodes. These indicators may include network metrics such as node connectivity, centrality, and betweenness. If the identification of key nodes is inaccurate, the removal operation may not achieve the desired effect, and may even inadvertently weaken the connectivity of the network and affect the normal function of the network.

[0082] In order to solve the problems of high computational complexity and low rumor control efficiency in the existing centralized rumor processing methods, the present invention proposes a new message control method.

[0083] In order to enable those skilled in the art to better understand the solution of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1 A flow chart of a message control method provided by an embodiment of the present invention, such as Figure 1 As shown, the method includes:

[0084] S10: Obtain the tree structure corresponding to the current message propagation;

[0085] S11: Selecting a first preset number of root nodes from the tree structure and selecting a second preset number of child nodes from the subtree corresponding to the root node;

[0086] S12: obtaining the situation of the remaining nodes on the subtree activated by the seed node after removing the selected node;

[0087] S13: when it is detected that the situation of the seed node activating the remaining nodes on the subtree meets the preset requirements, remove the nodes according to the corresponding removal method when the preset requirements are met;

[0088] S14: Utilize the tree structure after removing the nodes to control the transmission of the message.

[0089] The tree structure corresponding to the message propagation includes a set of all nodes (such as a set of each individual user) and edges (relationships or interactions between users). The tree structure corresponding to the message propagation is not limited and is determined according to the specific message propagation situation. In the present invention, the initial publisher of the message is called the seed node of the network message. In order to solve the problem of large amount of calculation and slow response speed in centralized control message propagation, the embodiment of the present invention removes nodes in units of local subtrees. There is no limitation on the divided local subtrees, which are also determined according to the specific message propagation situation. Figure 2 A schematic diagram of a local subtree provided by an embodiment of the present invention, such as Figure 2 As shown in the figure, the seed node contains two root nodes. Taking the left root node as an example, the left root node includes the left subtree (the left subtree has child nodes 1, 2, 3, 4, and 5), and the left root node includes the right subtree (the right subtree has child nodes 6, 7, 8, and 9). The message propagation direction is the seed node, the root node, and the child node corresponding to the root node.

[0090] In order to make the nodes on the local subtree to be removed more appropriate, in the embodiment of the present invention, a first preset number of root nodes are selected from the tree structure and a second preset number of child nodes are selected from the subtree corresponding to the root node for removal. The first preset number and the second preset number can be randomly selected. Adjusting the value of the first preset number and the value of the second preset number can provide multiple removal methods.

[0091] Obtain the situation in which the seed node activates the remaining nodes on the subtree after removing the selected node. For example, the situation in which the seed node activates the remaining nodes on the subtree may include the sum of the probabilities that the seed node activates the remaining nodes on the subtree. It is worth noting that when the first preset number is 0 and the second preset number is not 0, the removal method is to remove the second preset number of child nodes from the subtree corresponding to the root node, that is, all the removed nodes are from the child nodes on the subtree; if the first preset number is not 0 and the second preset number is not 0, the removal method is to remove the first preset number of root nodes and the second preset number of child nodes from the subtree corresponding to the root node, that is, the removed nodes include the child nodes from the subtree and the root node.

[0092] Still Figure 2 For example, when the first preset number is 0 and the second preset number is 2 (assuming that child node 2 on the left subtree and node 6 on the right subtree are removed), the situation in which the seed node activates the remaining nodes (including the left root node, child nodes 1, 3, 4 and 5 on the left subtree, and child nodes 7, 8 and 9 on the right subtree) after removing child node 2 is obtained.

[0093] When it is detected that the situation of the remaining nodes on the seed node activating the subtree meets the preset requirements, the nodes are removed according to the removal method corresponding to the situation of meeting the preset requirements. There is no limitation on the preset requirements, and it can be that when the sum of the probabilities of the remaining nodes on the seed node activating the subtree is less than or equal to the preset probability, the total number of nodes are removed according to the removal method corresponding to the situation when the sum of the probabilities is less than or equal to the preset probability. It can also be that when the sum of the probabilities of the remaining nodes on the seed node activating the subtree is the smallest sum of the probabilities corresponding to all removal methods, the total number of nodes are removed according to the removal method corresponding to the smallest sum of the probabilities corresponding to all removal methods. It is worth noting that all removal methods refer to the removal methods obtained after setting different first preset numbers and second preset numbers.

[0094] In the message control method provided in this embodiment, first, a first preset number of root nodes are selected from the tree structure and a second preset number of child nodes are selected from the subtree corresponding to the root node; after removing the selected node, the situation of the seed node activating the remaining nodes on the subtree is obtained, and when it is detected that the situation of the seed node activating the remaining nodes on the subtree meets the preset requirements, the node is removed according to the corresponding removal method when the preset requirements are met, and finally the tree structure after the node is removed is used to control the transmission of the message. That is, the purpose of controlling the propagation of the message is achieved by removing the nodes in the message propagation process, and in the process of removing the nodes, the first preset number of root nodes selected from the tree structure and the second preset number of child nodes selected from the subtree corresponding to the root node are removed. In a complex message propagation network, the nodes to be removed are selected from the root node and the subtree corresponding to the root node as units, that is, the nodes to be removed are determined in units of the local subtree structure. Since the local subtree structure is divided from the entire network structure, the scale of the local subtree structure is smaller than the scale of the entire network. Therefore, compared with the method of analyzing the global information of the entire network as a unit, the method provided by the present invention reduces the computational complexity, has a fast response speed, and improves the efficiency of determining the removal method. rate, thereby improving the efficiency of controlling message propagation; secondly, compared with the method of removing edges, the method of removing nodes provided by the present invention does not consider the impact of removing multiple propagation paths between nodes on message control, but considers the impact of removing nodes on message control. Since in a complex message propagation network, the number of nodes is much smaller than the number of paths, the method provided by the present invention can reduce the amount of calculation when controlling information propagation and improve the efficiency of controlling message propagation; thirdly, the value of the first preset number and the value of the second preset number can be adjusted, so that a variety of removal methods can be provided, and then the final method of removing the node is selected from the multiple removal methods, that is, comprehensive consideration of multiple removal methods makes the determined removal method more accurate.

[0095] In order to improve the accuracy of the determined removal method, the case where the seed node activates the remaining nodes on the subtree is set to the sum of the probabilities of the seed node activating the remaining nodes on the subtree. At the same time, the total number of nodes to be removed can be set in advance. Before selecting a first preset number of root nodes from the tree structure and selecting a second preset number of child nodes from the subtree corresponding to the root node, it also includes:

[0096] Obtaining the total number of selected nodes; wherein the sum of the first preset number and the second preset number is equal to the total number;

[0097] The transmission of control messages using the tree structure after removing the nodes includes:

[0098] The message transmission is controlled by using the tree structure after removing the total number of nodes.

[0099] There is no limit on the total number of nodes selected. You can obtain the size of the subtree corresponding to the root node and determine the total number of nodes selected based on the size of the subtree corresponding to the root node. For example, if the size of the left subtree corresponding to the root node is 10 nodes and the size of the right subtree is 20 nodes, you can take the average of the nodes of the left subtree and the nodes of the right subtree, which is 15, as the total number of nodes selected.

[0100] When the case where the seed node activates the remaining nodes on the subtree is the sum of the probabilities of the seed node activating the remaining nodes on the subtree, it is first necessary to determine the probability of the seed node activating the current node (single node) on the tree structure. In implementation, determining the probability of the seed node activating the current node on the tree structure includes:

[0101] Obtain the current message propagation path, the activation probability of the directed edges between nodes, and the status of the current node; wherein the current node is any node on the tree structure; the status of the current node includes whether the current node is a root node or a seed node, and whether all seed nodes activate the current node;

[0102] The probability of the seed node activating the current node on the tree structure is determined according to the situation of the current node and / or the activation probability of the current message propagation path and the directed edges between the nodes.

[0103] In order to make the activation probability of the directed edges between the determined nodes more accurate, in implementation, the number of current messages and the number of messages received by each node are obtained; the ratio between the number of messages received by each node and the number of current messages is taken; and the ratio is used as the activation probability of the directed edges between the nodes.

[0104] In addition, the probability of the seed node activating the current node on the tree structure is determined according to the current node situation and / or the activation probability of the directed edge between the current message propagation path and the nodes, including:

[0105] When the current node is detected as a seed node, the probability of the seed node activating the current node on the tree structure is determined to be 1;

[0106] When it is detected that all seed nodes are not transmitted to the current node, the probability of the seed node activating the current node on the tree structure is determined to be 0;

[0107] When it is detected that the current node is not a seed node and there is at least one seed node transmitted to the current node, the probability of the seed node activating the current node on the tree structure is determined based on all paths of the current message transmitted to the current node and the activation probabilities corresponding to the directed edges between the nodes on each path.

[0108] Among them, determining the probability of the seed node activating the current node on the tree structure according to all paths of the current message transmitted to the current node and the activation probabilities corresponding to the directed edges between the nodes on each path includes:

[0109] Get the number of all paths that the current message is transmitted to the current node;

[0110] When it is detected that the number of paths is less than or equal to the first number, the sum of activation probabilities corresponding to the directed edges between the nodes on each path is used as the probability of the seed node activating the current node on the tree structure;

[0111] When it is detected that the number of paths is greater than the first number, the opposite probability of the probability that all seed nodes do not transmit to the current node is obtained; wherein the probability that the current seed node does not transmit to the current node is the difference between 1 and the sum of the activation probabilities corresponding to the directed edges between the upper nodes of all paths; all paths are all paths from the current seed node to the current node and each path includes multiple directed edges;

[0112] The opposition probability is used as the probability of the seed node activating the current node on the tree structure.

[0113] The first number is not limited and is determined according to actual conditions. In order to enable those skilled in the art to better understand the probability of the seed node activating each node of the present invention, the following is a given directed social network. Take this as an example. represents the set of all nodes in the network, represents the set of all edges, and Represents the set of propagation probabilities of all edges. Represents any network node, Representation Node With Node The directed edges between Indicates the node Activate Node The probability that the message is sent by the node Propagate to nodes probability of ).

[0114] make The seed node that represents the network message (the original publisher of the message). Network nodes include active and inactive states. The active state refers to the node Received node The information sent (i.e. the node Activated the node ). The inactive state refers to the node No information is received from any other nodes.

[0115] Information is expanded using the following discrete time slice rule: If a node exist becomes active at any moment, it has one and only one chance to try to activate its inactive neighbor node Through directed edges And the activation probability is . And the node The status is The above process is repeated for the nodes in the network until there are no more nodes that can be activated. In addition, the state of a node can only be changed from an inactive state to an active state, and cannot be changed from an active state to an inactive state. The symbol M is used to represent the message propagation model of the present invention.

[0116] In order to understand the message propagation rules proposed by the present invention, a specific message propagation example is provided below. Figure 3 A simple network message propagation diagram provided by an embodiment of the present invention. In this example, the network includes 5 nodes, each node is connected by a directed edge, and the activation probability (weight) of each directed edge is given synchronously. Figure 3 In the first figure, assume that At this moment, node 1 is the initial seed node (the source node of the message), that is, At this point, the message starts to spread from node 1 to the network, while other nodes are inactive. According to the propagation rules and network connection relationship, node 1 will activate node 2 with a probability of 0.5. At the moment node 2 is activated (from inactive state to active state, such as Figure 3 The message continues to spread, and At this time, node 1 does not need to activate node 2, it only needs to remain active. At this time, node 2 tries to activate its inactive neighbors node 4 and node 5 with probabilities of 0.6 and 0.2 respectively. The result is At this moment, node 4 is activated and node 5 is not activated (e.g. Figure 3 According to the network topology connection relationship, the message cannot be propagated further, so the message propagation process ends.

[0117] In summary, in the process of message propagation, given the network topology and seed nodes, the message diffuses in the network according to the propagation law proposed by the present invention.

[0118] Consider the message control strategy of tree networks. Compared with general non-tree network structures, tree networks have the following advantages: first, it is relatively easy to calculate the activation probability between nodes; second, general non-tree networks are difficult to solve, while tree networks can effectively implement dynamic programming strategies.

[0119] A formal definition of the activation probability between nodes is given. Specifically, when a tree network , a collection of rumor messages , a message propagation model M, then for the network Any node in , the probability that it can be activated by the seed set Defined as:

[0120] ; (1)

[0121] Among them, if the node is a member of the seed set, then the probability that it can be activated by the seed set In addition, if all members of the seed set cannot reach the node , then it can never be activated by the seed set, so In addition, the node Can be seeded The probability of activation is equivalent to the probability of all members of the seed set Cannot activate nodes The opposite of probability is probability, which is:

[0122] .

[0123] in Represents a seed set Any seed node in To Node All paths of and each path includes multiple side.

[0124] The above describes that when the first preset number is 0 and the second preset number is not 0, the removed nodes are all from the child nodes on the subtree (this method is called method one); if the first preset number is not 0 and the second preset number is not 0, the removed nodes include the child nodes from the subtree and the root node (this method is called method two).

[0125] When the first method is adopted, removing the selected second preset number of child nodes from the subtree corresponding to the root node includes:

[0126] Using different removal methods to remove the selected second preset number of child nodes from the subtree corresponding to the root node; wherein the number of child nodes selected from the subtree corresponding to the root node under different removal methods is different;

[0127] The sum of the probabilities of the seed node activating the remaining nodes on the subtree after removing the selected nodes using the current removal method includes:

[0128] Obtaining a first sum obtained by adding the sum of the probabilities of the seed node activating the remaining child nodes on each subtree after removing a second preset number of child nodes selected from the subtree corresponding to the root node using the current removal method and the first sum obtained by adding the first probability of the seed node activating the root node;

[0129] The first sum is taken as the sum of the probabilities of the seed node activating the remaining nodes on the subtree under the current removal method.

[0130] In practice, in order to make the tree structure more standardized and simplify calculations, the tree structure will be converted into a standard tree structure, such as a standard binary tree structure. After the tree structure is converted, some virtual nodes may be set artificially. In the present invention, nodes that are not virtual are called actual nodes. In order to avoid the influence of virtual nodes on the accuracy of the calculated probability of seed nodes activating root nodes, a first indicator function is defined: , used to characterize the value under specific conditions. The specific definition is:

[0131] ; (2)

[0132] Therefore, in the first method, after obtaining the node selected by removing the node in the current removal method, the first probability of the seed node activating the root node includes:

[0133] Obtaining a first initial probability of the seed node activating the root node after the selected node is removed using the current removal method;

[0134] When it is detected that the root node is an actual node and the root node is not a seed node, determining a first probability that the seed node activates the root node as a first initial probability;

[0135] When it is detected that the root node is a virtual node, it is determined that the first probability of the seed node activating the root node is 0.

[0136] In order to effectively control the propagation of the message, in the following method, when it is detected that the sum of the probabilities of the remaining nodes on the seed node activating the subtree meets the preset requirements, the total number of nodes removed according to the corresponding removal method when the preset requirements are met includes:

[0137] When it is detected that the sum of the probabilities of the seed node activating the remaining nodes on the subtree is the minimum value among all the first sums, the total number of nodes are removed in a removal manner corresponding to the minimum value among the first sums.

[0138] That is, when only method 1 is used, the removal method with the smallest sum of probabilities of the seed node activating the remaining nodes on the subtree in method 1 is selected as the final removal method.

[0139] When the second method is adopted, after the selected node is removed by the current removal method, the sum of the probabilities of the seed node activating the remaining nodes on the subtree includes:

[0140] Obtaining a second sum obtained by adding the sum of the probabilities of the seed node activating the remaining child nodes on each subtree after the selected node is removed by the current removal method and the second probability of the seed node activating the root node;

[0141] The second sum is taken as the sum of the probabilities of the seed node activating the remaining nodes on the subtree under the current removal method.

[0142] In order to avoid removing the seed node, a second indicator function is defined , used to characterize the value under specific conditions. The specific definition is:

[0143] ; (3)

[0144] Therefore, in the second method, after obtaining the node selected by removing the node using the current removal method, determining the second probability that the seed node activates the root node includes:

[0145] Obtaining a second initial probability of the seed node activating the root node after the selected node is removed using the current removal method;

[0146] In the case where it is detected that the root node is not a seed node, determining that the second probability of the seed node activating the root node is 0;

[0147] In the case where it is detected that the root node is a seed node, the second probability of determining that the seed node activates the root node is a probability obtained by multiplying the second initial probability by a preset value.

[0148] The default value here is .

[0149] In order to effectively control the spread of messages, in mode 2, when it is detected that the sum of the probabilities of the remaining nodes on the seed node activating the subtree meets the preset requirements, the total number of nodes removed according to the corresponding removal method when the preset requirements are met includes:

[0150] When it is detected that the sum of the probabilities of the seed node activating the remaining nodes on the subtree is the minimum value among all the second sums, the total number of nodes are removed according to the removal method corresponding to the minimum value in the second sum. That is, when only method 2 is used, the removal method with the minimum sum of the probabilities of the seed node activating the remaining nodes on the subtree in method 2 is selected as the final removal method.

[0151] However, when using method one and method two for removal, in order to more effectively control the propagation of messages, when it is detected that the sum of the probabilities of the seed node activating the remaining nodes on the subtree is the minimum of the minimum of the first sum and the minimum of the second sum, the total number of nodes is removed using the removal method corresponding to the minimum of the minimum of the first sum and the minimum of the second sum.

[0152] In order to enable those skilled in the art to better understand the message control method of the present invention and improve the efficiency of calculation, the process of the message control method of the present invention is described below using a binary tree structure as an example. Figure 4 The present invention provides a framework diagram for dynamic programming of rumor control in tree-type networks. Figure 4 As shown in Figure 1, the input of the dynamic programming solution for tree-based network rumor control is a given social network, and the output is the optimal controller set (i.e., the set of key nodes to be removed). The solution includes the following three main modules: network message propagation module, binary tree construction module, and dynamic programming strategy construction module.

[0153] The network message propagation module is mainly responsible for describing the propagation mode of network information, defining the rules of information in the network, determining which nodes are the initial publishers or sources of information, simulating the propagation range of information in the network over time, etc.

[0154] The binary tree module is constructed to transform the general tree network topology into an equivalent binary tree network. The purpose is that the binary tree provides a unified interface so that all tree operations can be implemented through the concepts of left subtree and right subtree, which facilitates the design of the algorithm and dynamic programming strategy.

[0155] A dynamic programming strategy is constructed to adaptively and dynamically select the optimal set of controllers that meet the conditions from the constructed binary tree network, avoiding manual intervention and improving algorithm efficiency.

[0156] Specifically, the network message propagation module is a directed social network as described above. The process of formally defining the message propagation instances and the activation probabilities between nodes will not be described here.

[0157] The following is an explanation of the binary tree construction module. Before selecting a first preset number of root nodes from the tree structure and selecting a second preset number of child nodes from the subtree corresponding to the root node, the method further includes:

[0158] Determine whether the tree structure is a binary tree structure;

[0159] If yes, then proceed to the step of selecting a first preset number of root nodes from the tree structure and selecting a second preset number of child nodes from the subtree corresponding to the root node;

[0160] If not, the tree structure is converted into a binary tree structure, and the process returns to the step of determining whether the tree structure is a binary tree structure.

[0161] That is, the nodes to be removed are selected based on the binary tree structure. Converting the tree structure into a binary tree structure includes:

[0162] Keep the root node of the binary tree structure the same as the root node of the tree structure;

[0163] Get a target node whose number of child nodes is greater than the second number;

[0164] A subtree is established according to the number of child nodes corresponding to the target node to replace the corresponding target node; wherein the leaf nodes on the subtree are the same as the leaf nodes corresponding to the target node, and the probability of the leaf nodes on the subtree is the same as the activation probability of the directed edges between the nodes, and the probability of the virtual edges corresponding to the newly introduced virtual nodes is 1.

[0165] The original tree network given below Convert to the corresponding standard binary tree ,in, represents the set of all nodes in the network, represents the set of all edges, and Represents the propagation probability set of all edges. Since the node set, edge set, and weight set are changed after the transformation, a new symbolic representation is used.

[0166] The binary tree transformation rules are as follows:

[0167] Rule 1: If the original tree network is given The root node is , then the root node of the network obtained after conversion to a binary tree is still .

[0168] Rule 2: For any node on the original tree network ,if have child nodes, and these child nodes are recorded as . Then use a tree with a height no greater than Subtree replacement node , and the leaf nodes of the subtree are still Note that the conversion process will introduce additional virtual nodes and virtual edges.

[0169] Rule 3: The above transformation process is only performed for nodes whose out-degree values ​​(edges emitted by nodes) of the original tree network nodes are greater than 2.

[0170] Figure 5 A schematic diagram of converting a general tree network provided in an embodiment of the present invention into a corresponding binary tree. Figure 5 The left figure shows a general tree network structure, where some nodes have more than 2 children. Figure 5 The figure on the right in the middle represents the corresponding binary tree structure, where the virtual nodes and virtual edges represent the introduced equivalent operations.

[0171] According to Rule 1, Figure 5 The root node in the left graph is , then the root node of the transformed binary tree is still (like Figure 5 as shown in the figure on the right).

[0172] Observe that the nodes in the original network There are four child nodes, namely , and also indicates that the parameters According to Rule 2, use a ball with a height no greater than Sub-binary tree replaces node , and the leaf nodes of the subtree are In this process, two virtual nodes are introduced and , and two virtual edges are added as well as In order to ensure the equivalence of message propagation, the probabilities (weights) of the above two virtual edges are set to 1.

[0173] In addition, note that the node The number of children of is also more than 2, so the same is true for node Execute the above transformation process. Considering the principle of minimal transformation, additional virtual points are introduced and a virtual edge And the weight is 1, the result is Figure 5 As shown in the figure on the right.

[0174] In summary, according to Rules 1 and 2, the original general tree network topology can be transformed into the corresponding binary tree network topology.

[0175] Compared with the traditional general tree structure, the converted binary tree has advantages in simplified operation, space efficiency, recursive implementation, and scalability. For example, in terms of simplified operation, the structure of the binary tree is simpler, which makes tree operations (such as search, insertion, and deletion) more intuitive and easy to implement. In terms of space efficiency, since each node has at most two child nodes, the binary tree is usually more compact than the general tree, which helps to reduce the waste of storage space. In terms of recursive implementation, the recursive nature of the binary tree allows many operations to be implemented recursively, which is a natural and concise method in programming. In terms of scalability, the binary tree can be expanded to a multi-way tree to adapt to more complex data structure requirements while maintaining high efficiency of the operation.

[0176] Based on the binary tree structure provided above, a dynamic programming module is then constructed. The main purpose of constructing the dynamic programming module is to filter out the transformed binary tree network. nodes, remove the blocker set formed by these nodes After that, some important propagation paths of rumor information were switched, which hindered the spread of rumor information and caused network users to be attracted by rumor seeds. The probability of activation is minimal.

[0177] For a node in a binary tree ,make and Respectively represent the left child node and right child node of the node, Figure 6 A schematic diagram of left and right child nodes of a binary tree provided by an embodiment of the present invention.

[0178] definition For: In the node Select the subtree of the root node Nodes form a collection , when removed After that, other nodes in the tree structure network can be seeded The sum of the activation probabilities.

[0179] definition When removing After that, the node Can be seeded The probability of activation.

[0180] Further analysis, There are only two modes for node filtering:

[0181] Method 1: Select this nodes, excluding the root node of the subtree, which means that All nodes are child nodes.

[0182] Method 2: Select this nodes, including the root node of the subtree, and Child nodes.

[0183] The mathematical expressions of method 1 and method 2 are discussed below. Specifically, the process of determining the mathematical formula for minimizing the sum of activation probabilities of method 1 is as follows:

[0184] First, as defined in formula (2) above, avoid the influence of virtual nodes.

[0185] Secondly, for method 1 The distributed mode of each node includes the following two cases:

[0186] ① Node in the left subtree superior;

[0187] ②Other Nodes in the right subtree superior.

[0188] For ①, the left subtree filter Nodes can be grouped The probability of activation is:

[0189] ; (4)

[0190] For ②, right subtree filter Nodes can be grouped The probability of activation is:

[0191] ; (5)

[0192] In addition, combined with formula (2), for the subtree root node, it can be collected The probability of activation is:

[0193] ; (6)

[0194] in, Indicates removal from the left subtree The set of nodes, Indicates removal from the right subtree The set of nodes, , Indicates The subtree of the root node. The meanings are similar and will not be repeated here.

[0195] In summary, the mathematical formula for minimizing the sum of activation probabilities in method 1 is:

[0196] ; (7)

[0197] The process of determining the mathematical formula for minimizing the sum of activation probabilities in method 2 is as follows:

[0198] First, as defined in formula (3) above, avoid removing seed nodes.

[0199] Secondly, for method 2 The distributed mode of each node includes the following three situations:

[0200] ① Node in the left subtree superior;

[0201] ② Nodes in the right subtree superior;

[0202] ③A node is on the root node.

[0203] For ①, the left subtree filter Nodes can be grouped The probability of activation is:

[0204] ; (8)

[0205] For ②, right subtree filter Nodes can be grouped The probability of activation is:

[0206] ; (9)

[0207] In addition, combined with formula (3), for the subtree root node, it can be aggregated The probability of activation is:

[0208] ; (10)

[0209] in, .

[0210] In summary, the mathematical formula for minimizing the sum of activation probabilities in method 2 is:

[0211] ; (11)

[0212] When using Method 1 and Method 2, the optimal solution of the overall solution is defined as follows: According to Formula (7) defined in Method 1 and Formula (11) defined in Method 2, the optimal solution is The minimum value of formula (7) and formula (11) should be taken, and the expression is as follows:

[0213] ; (12)

[0214] In order to solve the problems of existing rumor prevention strategies such as untimely rumor detection, high computational complexity, large response delay, and poor control effect, this embodiment proposes an information control method for tree-type network topology, which mainly includes three key modules: a network message propagation module, a binary tree construction module, and a dynamic programming module.

[0215] In the network message propagation module, firstly, the message propagation rules between nodes are designed. Secondly, an example of message propagation is provided. Finally, a specific definition of the activation probability between nodes is given.

[0216] In constructing a binary tree module, the present invention defines the basic principles and specific examples of converting a general tree into a binary tree. Applying this strategy improves the execution efficiency of subsequent algorithms and reduces the search range of the solution space.

[0217] In constructing the dynamic programming module, the distribution of candidate nodes on the binary tree is analyzed, and a mathematical description method of the impact is given for specific situations. In each case, a recursive method is used to implement the solution process.

[0218] In summary, compared to the general tree structure, the solution of the present invention adopts a binary tree-based approach to screen the optimal control node (i.e., the set of nodes to be removed from the network) with a dynamic programming strategy. During the algorithm calculation process, only the local subtree structure of the target node needs to be considered, which makes the present invention better in terms of computational complexity and running time. In the traditional general tree structure, in the process of calculating the removal of the target node, each calculation needs to consider the global information of the entire network, which makes its computational complexity higher. It can be seen that the present invention effectively reduces the computational overhead and reduces the response time, thereby improving the rumor prevention effect, that is, the number of network users who receive rumor information in the network is minimized.

[0219] In the above embodiments, the message control method is described in detail, and the present invention also provides corresponding embodiments of a message control device and an electronic device. It should be noted that the present invention describes the embodiments of the device part from two perspectives, one is based on the functional module perspective, and the other is based on the hardware perspective.

[0220] A message control device provided by an embodiment of the present invention includes, based on the perspective of functional modules:

[0221] The first acquisition module is used to obtain the tree structure corresponding to the current message propagation;

[0222] A selection module, used to select a first preset number of root nodes from the tree structure and a second preset number of child nodes from the subtree corresponding to the root node;

[0223] The second acquisition module is used to obtain the situation of the remaining nodes on the subtree activated by the seed node after removing the selected node;

[0224] A removal module, used to remove nodes according to a corresponding removal method when it is detected that the situation of the remaining nodes on the seed node activating the subtree meets the preset requirements;

[0225] The control module is used to control the transmission of messages by using the tree structure after removing the nodes.

[0226] In some embodiments, the message control device further includes:

[0227] A third acquisition module is used to acquire the total number of selected nodes; wherein the sum of the first preset number and the second preset number is equal to the total number;

[0228] The control module is specifically used to control the transmission of the message by using the tree structure after removing the total number of nodes.

[0229] In some embodiments, the message control device further includes:

[0230] A judgment module is used to judge whether the tree structure is a binary tree structure; if so, the selection module is triggered; if not, the conversion module is triggered;

[0231] The conversion module is used to convert the tree structure into a binary tree structure and return it to the trigger judgment module.

[0232] Since the embodiments of the apparatus part correspond to the embodiments of the method part, please refer to the description of the embodiments of the method part for the embodiments of the apparatus part, which will not be repeated here.

[0233] An embodiment of the present invention further provides a computer program product, including a computer program / instruction, which implements the steps of the above-mentioned message control method when executed by a processor.

[0234] Figure 7 This is a structural diagram of an electronic device provided by another embodiment of the present invention. This embodiment is based on the hardware perspective, such as Figure 7 As shown, the electronic equipment includes:

[0235] A memory 20, used for storing computer programs;

[0236] The processor 21 is used to implement the steps of the message control method mentioned in the above embodiment when executing the computer program.

[0237] Among them, the processor 21 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 21 can be implemented in at least one hardware form of a digital signal processor (DSP), a field-programmable gate array (FPGA), and a programmable logic array (PLA). The processor 21 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a central processing unit (CPU); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 21 may be integrated with a graphics processing unit (GPU), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 21 may also include an artificial intelligence (AI) processor, which is used to process computing operations related to machine learning.

[0238] The memory 20 may include one or more non-volatile storage media, which may be non-transitory. The memory 20 may also include a high-speed random access memory, and a non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In this embodiment, the memory 20 is at least used to store the following computer program 201, wherein, after the computer program is loaded and executed by the processor 21, it can implement the relevant steps of the message control method disclosed in any of the aforementioned embodiments. In addition, the resources stored in the memory 20 may also include an operating system 202 and data 203, etc., and the storage method may be temporary storage or permanent storage. Among them, the operating system 202 may include Windows, Unix, Linux, etc. The data 203 may include, but is not limited to, the data involved in the above-mentioned message control method, etc.

[0239] In some embodiments, the electronic device may further include a display screen 22 , an input / output interface 23 , a communication interface 24 , a power source 25 , and a communication bus 26 .

[0240] Those skilled in the art will understand that Figure 7 The structure shown in the figure does not constitute a limitation on the electronic device, and may include more or fewer components than shown in the figure.

[0241] The electronic device provided by the embodiment of the present invention includes a memory and a processor. When the processor executes the program stored in the memory, it can implement the following method: a message control method, and the effect is the same as above.

[0242] An embodiment of the present invention further provides a computer program product, including a computer program / instruction, which implements the steps of the above-mentioned message control method when executed by a processor.

[0243] Finally, the present invention also provides an embodiment corresponding to a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps recorded in the above method embodiment are implemented.

[0244] It is understandable that if the method in the above embodiment is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc. Various media that can store program codes.

[0245] The computer-readable storage medium provided by the present invention includes the message control method mentioned above, and the effect is the same as above.

[0246] The above is a detailed introduction to a message control method, product, electronic device and medium provided by the present invention. The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same and similar parts between the embodiments can be referenced to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description. It should be pointed out that for ordinary technicians in this technical field, without departing from the principle of the present invention, several improvements and modifications can be made to the present invention, and these improvements and modifications also fall within the scope of protection of the present invention.

[0247] It should also be noted that, in this specification, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device including the element.

Claims

1. A message control method, characterized in that: include: Get the tree structure corresponding to the current message propagation; Selecting a first preset number of root nodes from the tree structure and selecting a second preset number of child nodes from the subtrees corresponding to the root nodes; Obtaining the situation in which the seed node activates the remaining nodes on the subtree after removing the selected node; wherein the situation in which the seed node activates the remaining nodes on the subtree is the sum of the probabilities of the seed node activating the remaining nodes on the subtree; When it is detected that the situation of the remaining nodes on the subtree activated by the seed node meets the preset requirements, the nodes are removed according to the corresponding removal method when the preset requirements are met; The tree structure after removing nodes is used to control the transmission of messages; Determining the probability that the seed node activates the current node on the tree structure includes: Obtaining the current message propagation path, the activation probability of the directed edges between nodes, and the situation of the current node; wherein the current node is any node on the tree structure; the situation of the current node includes whether the current node is a root node or a seed node, and all the seed nodes activate the current node; The probability of the seed node activating the current node on the tree structure is determined according to the situation of the current node and / or the activation probability of the current message propagation path and the directed edges between nodes.

2. The message control method according to claim 1, characterized in that: Before selecting a first preset number of root nodes from the tree structure and selecting a second preset number of child nodes from the subtree corresponding to the root node, the method further includes: Obtaining the total number of selected nodes; wherein the sum of the first preset number and the second preset number is equal to the total number; The transmission of the control message using the tree structure after removing the node includes: The transmission of the message is controlled by using the tree structure after the total number of nodes are removed.

3. The message control method according to claim 2, characterized in that: Determining the probability of the seed node activating the current node on the tree structure according to the situation of the current node and / or the activation probability of the directed edge between the current message propagation path and the node includes: In the case where it is detected that the current node is the seed node, determining that the probability that the seed node activates the current node on the tree structure is 1; In the case where it is detected that all the seed nodes are not transmitted to the current node, determining that the probability of the seed node activating the current node on the tree structure is 0; When it is detected that the current node is not the seed node and there is at least one seed node transmitting to the current node, the probability of the seed node activating the current node on the tree structure is determined based on the activation probability corresponding to all paths of the current message transmitted to the current node and the directed edges between the nodes on each path.

4. The message control method according to claim 3, characterized in that: The determining the probability of the seed node activating the current node on the tree structure according to all paths of the current message transmitted to the current node and the activation probabilities corresponding to the directed edges between the nodes on each path includes: Obtain the number of all paths for transmitting the current message to the current node; When it is detected that the number of the paths is less than or equal to the first number, taking the sum of the activation probabilities corresponding to the directed edges between the nodes on each path as the probability of the seed node activating the current node on the tree structure; When it is detected that the number of the paths is greater than the first number, the opposite probability of the probability that all the seed nodes do not transmit to the current node is obtained; wherein the probability that the current seed node does not transmit to the current node is the difference between 1 and the sum of the activation probabilities corresponding to the directed edges between the upper nodes of all the paths; all the paths are all the paths from the current seed node to the current node and each path includes multiple directed edges; The opposition probability is used as the probability of the seed node activating the current node on the tree structure.

5. The message control method according to claim 2, characterized in that: The first preset number is 0, and removing the selected second preset number of child nodes from the subtree corresponding to the root node includes: Using different removal methods to remove a second preset number of child nodes selected from the subtree corresponding to the root node; wherein the number of child nodes selected from the subtree corresponding to the root node under different removal methods is different; The sum of the probabilities of the seed node activating the remaining nodes on the subtree after removing the selected nodes using the current removal method includes: Obtaining a first sum obtained by adding the sum of the probabilities of the seed node activating the remaining child nodes on each subtree after removing the second preset number of child nodes selected from the subtree corresponding to the root node using the current removal method and the first sum obtained by adding the first probability of the seed node activating the root node; The first sum is taken as the sum of probabilities of the seed node activating the remaining nodes on the subtree under the current removal mode.

6. The message control method according to claim 5, characterized in that: After obtaining the node selected by removing the node in the current removal mode, the first probability that the seed node activates the root node includes: Obtaining a first initial probability that the seed node activates the root node after the selected node is removed using the current removal method; When it is detected that the root node is an actual node and the root node is not the seed node, determining a first probability that the seed node activates the root node as the first initial probability; When it is detected that the root node is a virtual node, it is determined that the first probability of the seed node activating the root node is 0.

7. The message control method according to claim 5, characterized in that: The first preset number is not 0, and the sum of the probabilities of the seed node activating the remaining nodes on the subtree after removing the selected node using the current removal method includes: Obtaining a second sum obtained by adding the sum of the probabilities of the seed node activating the remaining child nodes on each subtree after the selected node is removed by using the current removal method and the second probability of the seed node activating the root node; The second sum is taken as the sum of probabilities of the seed node activating the remaining nodes on the subtree under the current removal mode.

8. The message control method according to claim 7, characterized in that: After obtaining the node selected by removing the node in the current removal mode, the second probability that the seed node activates the root node includes: Obtaining a second initial probability that the seed node activates the root node after the selected node is removed using the current removal method; In the case where it is detected that the root node is not the seed node, determining that a second probability of the seed node activating the root node is 0; In the case where it is detected that the root node is the seed node, the second probability of the seed node activating the root node is determined to be a probability obtained by multiplying the second initial probability by a preset value.

9. The message control method according to any one of claims 2 to 7, characterized in that: Before selecting a first preset number of root nodes from the tree structure and selecting a second preset number of child nodes from the subtree corresponding to the root node, the method further includes: Determining whether the tree structure is a binary tree structure; If yes, then enter the step of selecting a first preset number of root nodes from the tree structure and selecting a second preset number of child nodes from the subtree corresponding to the root node; If not, the tree structure is converted into a binary tree structure, and the process returns to the step of determining whether the tree structure is a binary tree structure.

10. The message control method according to claim 9, characterized in that: The converting the tree structure into a binary tree structure comprises: Keeping the root node of the binary tree structure the same as the root node of the tree structure; Get a target node whose number of child nodes is greater than the second number; A subtree is established according to the number of child nodes corresponding to the target node to replace the corresponding target node; wherein the leaf nodes on the subtree are the same as the leaf nodes corresponding to the target node, and the probability of the leaf nodes on the subtree is the same as the activation probability of the directed edges between the nodes, and the probability of the virtual edges corresponding to the newly introduced virtual nodes is 1.

11. The message control method according to claim 2, characterized in that: When it is detected that the sum of the probabilities of the seed node activating the remaining nodes on the subtree meets a preset requirement, removing the total number of nodes according to a corresponding removal method when the preset requirement is met includes: When it is detected that the sum of the probabilities of the seed node activating the remaining nodes on the subtree is the smallest sum of the probabilities corresponding to all removal methods, the total number of nodes are removed according to the removal method corresponding to the smallest sum of the probabilities corresponding to all removal methods.

12. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the steps of the message control method according to any one of claims 1 to 11 are implemented.

13. An electronic device, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of the message control method according to any one of claims 1 to 11 when executing the computer program.

14. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the message control method according to any one of claims 1 to 11 are implemented.

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