Method and device for determining service range in service network

Abstract

The embodiment of the invention provides a method and a device for determining a service range in a service network. The method for determining the service range in the service network comprises the following steps of: generating the service network by using a scale-free network model; wherein the service network comprises a plurality of nodes; assigning the behavior characteristics of each node in the service network, and determining target behavior characteristics; determining propagation probabilities among the nodes based on the target behavior characteristics; and determining a seed node from the nodes, performing simulation information propagation based on the seed node and the propagation probability, and determining a service range. Influence behavior features are introduced, features of two dimensions of network structure and behavior are considered at the same time, the key nodes in the network are identified, the propagation effect of the key nodes is finally verified, and the service range of the service network is widened.

Description

Technical Field

[0001] The present specification relates to the technical field of network communication dynamics, and in particular to a method for determining a service scope in a service network. Background Art

[0002] A service network refers to an interconnected and interactive network system consisting of service providers and users. In this network, each participant provides and obtains services through cooperation, coordination and resource sharing. The service network optimizes the quality, efficiency and effectiveness of services through these connections, interactions and collaborations. In a service network, the service scope refers to the number of users that a service provider can serve. In this context, the goal of a service network is to select service providers and maximize the service scope when the number of service providers is limited. This problem corresponds to the problem of maximizing information dissemination in the field of network science, that is, selecting a fixed number of seed nodes in a specified network to maximize the scope of information dissemination. According to the node selection strategy, the existing algorithms and technologies for maximizing information dissemination mainly include but are not limited to the following: greedy algorithm, heuristic algorithm, community detection algorithm, etc. The main idea of ​​the greedy algorithm is that in the process of selecting seed nodes, each time the node that can maximize the influence is selected until the limit of the number of seed nodes is reached. The idea of ​​the heuristic algorithm is to use heuristic rules to select nodes, usually combining the network attributes such as the degree and influence of the node to decide which nodes to select. The main idea of ​​the community detection algorithm is to select nodes located at the center of the community in order to maximize the dissemination effect inside and outside the community. However, these methods only consider network structural features, such as node degree, core number, and betweenness centrality. In addition, many current studies use network structural features to identify key nodes in the network, which often have strong communication capabilities. Related studies believe that the more central the network structural features of a node are, the more likely it is to have high communication capabilities. For example, a study published in the journal Science proposed an indicator called Collective Influence to identify key nodes in the network. This indicator only considers the structural characteristics of the node. Another study found that the larger the k-core value of a node, the more likely it is to have high communication capabilities. However, in real scenarios, the behavioral characteristics of the node itself will also affect the spread of information. Here, the behavioral characteristics of the node are divided into two types: influence and susceptibility. The influence of a node refers to the ability of a user to influence neighboring nodes. It belongs to the node's own ability and has nothing to do with the network structure in which the node is located; susceptibility refers to the susceptibility of a node, that is, the degree to which a node is easily affected by neighboring nodes. These two behavioral characteristics determine the probability of communication between nodes. Therefore, in practical applications, it is more reasonable to consider both the structural and behavioral characteristics of nodes and use them to design centrality indicators to identify key nodes in the network.

[0003] Existing technologies only consider identifying key nodes in the network through network structure characteristics. These technologies assume that the larger the centrality index value of a node, the more likely it is to have high communication capabilities. However, in actual scenarios, it is necessary to consider the closeness of the connection between nodes in the network, which represents the probability of information transmission between nodes. The closer the connection between two nodes, the more likely information transmission will occur between them. Identifying key nodes only through network structure characteristics may overestimate the node's communication capabilities. Therefore, a better solution is urgently needed. Summary of the invention

[0004] In view of this, the embodiments of this specification provide a method for determining a service range in a service network. One or more embodiments of this specification also relate to an apparatus for determining a service range in a service network, a computing device, a computer-readable storage medium, and a computer program to solve the technical defects existing in the prior art.

[0005] According to a first aspect of an embodiment of this specification, a method for determining a service range in a service network is provided, including: Generate a service network using a scale-free network model; wherein the service network includes a plurality of nodes; Assign values ​​to the behavior characteristics of each node in the service network and determine the target behavior characteristics; Determine the propagation probability between nodes based on the target behavior characteristics; Determine the seed nodes from the nodes, and simulate information propagation based on the seed nodes and propagation probability to determine the service scope.

[0006] In a possible implementation, a scale-free network model is used to generate a service network, including: Determining an initial network; wherein the initial network includes a set number of nodes; Add new nodes to the initial network, connect nodes to the new nodes based on the priority connection mechanism, and determine the target number of nodes; When the target number of nodes reaches the preset number of nodes, the initial network is used as the service network.

[0007] In a possible implementation, assigning a value to a behavior feature of each node in the service network to determine a target behavior feature includes: Determine the influence behavior characteristics and susceptibility behavior characteristics of each node; Based on the random assignment method, the influence behavior characteristics and susceptibility behavior characteristics are assigned to determine the target behavior characteristics.

[0008] In a possible implementation, determining the propagation probability between nodes based on the target behavior characteristics includes: The propagation probability between nodes is determined by performing a product operation based on the influence behavior characteristics and the susceptibility behavior characteristics.

[0009] In a possible implementation, determining a seed node from a node includes: Determine the node degree of each node in the service network; Determine the DI index value based on node degree and influence behavior characteristics; The seed node is determined based on the DI index value.

[0010] In a possible implementation, information propagation is simulated based on seed nodes and propagation probabilities to determine a service scope, including: Determine the time step, activate nodes based on the time step, seed nodes and propagation probability, and determine the activated nodes; The service scope is determined based on the activated nodes and seed nodes.

[0011] In a possible implementation, node activation is performed based on the time step, the seed node, and the propagation probability, and the activation node is determined, including: Activate the seed node at the first time step of the time step; Perform node activation based on the seed node and the propagation probability corresponding to the seed node at a second time step of the time step to determine a first activated node; In the third time step of the time step, node activation is continued based on the first activated node and the propagation probability corresponding to the first activated node until no other nodes are activated in any time step; wherein the other nodes are nodes that have not been activated.

[0012] According to a second aspect of an embodiment of this specification, a device for determining a service range in a service network is provided, including: A network generation module is configured to generate a service network using a scale-free network model; wherein the service network includes a plurality of nodes; A feature assignment module is configured to assign a value to the behavior feature of each node in the service network to determine a target behavior feature; a propagation probability module, configured to determine propagation probabilities between nodes based on target behavior characteristics; The range determination module is configured to determine the seed node from the nodes, and simulate information propagation based on the seed node and the propagation probability to determine the service range.

[0013] According to a third aspect of an embodiment of this specification, a computing device is provided, including: Memory and processor; The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the method for determining the service scope in the service network are implemented.

[0014] According to a fourth aspect of the embodiments of this specification, a computer-readable storage medium is provided, which stores computer-executable instructions, and when the instructions are executed by a processor, the steps of the method for determining a service scope in a service network are implemented.

[0015] According to a fifth aspect of the embodiments of this specification, a computer program is provided, wherein when the computer program is executed in a computer, the computer is caused to execute the steps of the above-mentioned method for determining a service scope in a service network.

[0016] The embodiments of this specification provide a method and device for determining the service scope in a service network, wherein the method for determining the service scope in a service network includes: generating a service network using a scale-free network model; wherein the service network includes multiple nodes; assigning values ​​to the behavior characteristics of each node in the service network to determine the target behavior characteristics; determining the propagation probability between each node based on the target behavior characteristics; determining the seed node from the node, and simulating information propagation based on the seed node and the propagation probability to determine the service scope. By introducing influential behavior characteristics and considering the characteristics of the two dimensions of network structure and behavior at the same time, it is used to identify key nodes in the network, and finally verifies its propagation effect, thereby improving the service scope of the service network. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a flow chart of a method for determining a service scope in a service network provided by an embodiment of this specification; Figure 2 It is a propagation schematic diagram of a method for determining a service range in a service network provided by an embodiment of this specification; Figure 3 It is a schematic diagram of the propagation effect of a method for determining a service range in a service network provided by an embodiment of this specification; Figure 4 It is a schematic diagram of a DI indicator of a method for determining a service scope in a service network provided by an embodiment of this specification; Figure 5 It is a structural diagram of a device for determining a service range in a service network provided by an embodiment of this specification; Figure 6 It is a structural block diagram of a computing device provided by an embodiment of this specification. DETAILED DESCRIPTION

[0018] Many specific details are described in the following description to facilitate a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of this specification, so this specification is not limited to the specific implementation disclosed below.

[0019] The terms used in one or more embodiments of this specification are only for the purpose of describing specific embodiments, and are not intended to limit one or more embodiments of this specification. The singular forms of "a" and "the" used in one or more embodiments of this specification and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0020] It should be understood that although the terms first, second, etc. may be used to describe various information in one or more embodiments of this specification, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of this specification, the first may also be referred to as the second, and similarly, the second may also be referred to as the first. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0021] In this specification, a method for determining a service scope in a service network is provided. This specification also relates to an apparatus for determining a service scope in a service network, a computing device, and a computer-readable storage medium, which are described in detail one by one in the following embodiments.

[0022] See also Figure 1 , Figure 1 A flow chart of a method for determining a service scope in a service network provided according to an embodiment of the present specification is shown, which specifically includes the following steps.

[0023] Step 101: Generate a service network using a scale-free network model; wherein the service network includes a plurality of nodes.

[0024] In one possible implementation, a service network is generated using a scale-free network model, including: determining an initial network; wherein the initial network includes a set number of nodes; adding new nodes to the initial network, connecting the nodes to the new nodes based on a priority connection mechanism, and determining a target number of nodes; when the target number of nodes reaches a preset number of nodes, using the initial network as a service network.

[0025] In practical applications, in service networks (such as telecommunications networks and logistics distribution networks), there are usually a small number of highly connected "hub" nodes and a large number of low-connectivity nodes. In order to meet this characteristic of the service network, a scale-free network model is used to generate the service network. The scale-free network model has three parameters, namely the number of nodes N in the generated network, the number of connections added to each node m, and the number of initial network nodes. , in the initial network, The nodes are fully connected. The steps of generating a service network from a scale-free network model are as follows.

[0026] Initialize the network and select a The initial network is a fully connected network of nodes. It must be greater than or equal to the number of nodes m to which the subsequent new node is to connect; Gradually add new nodes to the network, each time adding a new node, connect it to the m nodes in the existing network; Priority connection mechanism, new nodes are more inclined to connect to existing high-degree nodes, that is, the higher the degree of the existing node, the greater the probability of being selected by the new node. Specifically, the probability of existing node i being selected by the new node is The degree of the node Proportional to:

[0027] in is the degree of node i, is the sum of the degrees of all nodes; The two steps of "adding new nodes" and "prioritized connection" are repeated continuously until the number of nodes in the generated service network reaches the predetermined total number N.

[0028] For example, first, a service network with parameters of 1000 nodes, an initial network size of 5, and 4 edges when adding new nodes is generated through the BA network model.

[0029] Step 102: Assign values ​​to the behavior characteristics of each node in the service network to determine the target behavior characteristics.

[0030] In a possible implementation, the behavior characteristics of each node in the service network are assigned values ​​to determine the target behavior characteristics, including: determining the influence behavior characteristics and susceptibility behavior characteristics of each node; assigning values ​​to the influence behavior characteristics and susceptibility behavior characteristics based on a random assignment method to determine the target behavior characteristics.

[0031] In practical applications, after the generated service network is obtained in the above steps, the random assignment method is used to obtain the influence and susceptibility of each user. Specifically, for the N users in the network, the influence and susceptibility of the users in the network are randomly assigned using a uniform distribution between [0,1], and finally, the influence feature I and susceptibility feature S of each user are obtained.

[0032] Using the above example, we assign values ​​to the two behavioral characteristics of the user through a uniform distribution of [0,1], and calculate the propagation probability p of each edge in the network based on the user's behavioral characteristics. * , taking nodes i and j as an example, if the influence characteristic of node i is 0.3 and the susceptibility characteristic of node j is 0.5, then =0.15.

[0033] Step 103: Determine the propagation probability between nodes based on the target behavior characteristics.

[0034] In a possible implementation, the propagation probability between nodes is determined based on the target behavior characteristics, including: performing a product operation based on the influence behavior characteristics and the susceptibility behavior characteristics to determine the propagation probability between nodes.

[0035] In practical applications, influence I represents the ability of a node to influence its neighboring nodes, and susceptibility S represents the degree to which a node is influenced by its neighboring nodes. These two behavioral characteristics together determine the probability p of information propagation between nodes. In a service network, given the network adjacency matrix A and the influence I and susceptibility S of all users, the probability p of information propagation between nodes in the network is calculated according to the following definition. For users i and j, the probability of information propagation between the two is Influenced by node i and the susceptibility of node j The impact is calculated as follows: *

[0036] The above formula is used to calculate the information propagation probability of all edges in the service network.

[0037] For example, the propagation probability is determined by the influence characteristic of the seed node and the susceptibility characteristic of the neighbor node. Assuming that node i is a seed node with an influence characteristic of 0.5 and the susceptibility characteristic of its neighbor node j is 0.6, node i affects node j with a probability of 0.3. If node j is affected, its state changes from an unactivated state to an activated state. Otherwise, j will no longer be affected by node i.

[0038] Step 104: Determine the seed node from the nodes, and simulate information propagation based on the seed node and the propagation probability to determine the service scope.

[0039] In a possible implementation, determining a seed node from nodes includes: determining the node degree of each node in the service network; determining a DI index value based on the node degree and influence behavior characteristics; and determining a seed node based on the DI index value.

[0040] In practical applications, for the service network obtained in the above steps, calculate the degree of each node , that is, the node degree, is calculated as follows:

[0041] in is the element that generates the network adjacency matrix A, =1 means there is an edge between nodes i and j. =0 means there is no edge between nodes i and j. Then, the following index DI (degree and influence) is constructed to consider both the network structure characteristics (node ​​degree) and behavior characteristics (influence). For node i, its The value is the node degree and behavioral characteristics The product of = * .

[0042] Furthermore, all nodes are sorted according to the size of the DI index value, and the nodes with higher DI index values ​​are selected as seed nodes.

[0043] In a possible implementation, information propagation is simulated based on seed nodes and propagation probabilities to determine a service range, including: determining a time step, activating nodes based on the time step, seed nodes, and propagation probabilities, and determining activated nodes; and determining a service range based on activated nodes and seed nodes.

[0044] In practical applications, the independent cascade model is used to simulate the service coverage behavior of the server in the service network. In the independent cascade model, nodes have two states, activated state and inactive state, and any node is in one of these two states. The activation process of the independent cascade model is as follows: Figure 2 As shown in the figure, i is in the active state, and it has different probabilities (depending on the influence of node i and the susceptibility S of the neighboring nodes) to activate the neighboring nodes, and finally its neighbor node j is successfully activated.

[0045] In a possible implementation, node activation is performed based on time steps, seed nodes, and propagation probabilities to determine activated nodes, including: activating the seed node at the first time step of the time step; activating the node based on the seed node and the propagation probability corresponding to the seed node at the second time step of the time step to determine the first activated node; and continuing to perform node activation based on the first activated node and the propagation probability corresponding to the first activated node at the third time step of the time step until no other nodes are activated in any time step; wherein the other nodes are nodes that have not been activated.

[0046] In practical applications, the specific propagation rules and steps are as follows: Selection of initial infected nodes, based on the DI values ​​of nodes in the service network, select the nodes with the top 1% DI values ​​as the initial activated nodes, recorded as set , called seed nodes, these nodes are the starting point of information propagation and are activated at time t=0; The propagation iteration process, time step t=1,2,3,..., at each time step t, the newly activated node will try to activate its neighboring nodes. The specific propagation rules are as follows: For each node u activated at time t, it will try to activate each neighboring node v, and each edge (u,v) has a propagation probability ; If the activation attempt on edge (u, v) succeeds, node v is activated at the next time step t+1. If the activation attempt fails, node u will not try v again, that is, each edge has only one propagation opportunity; The stopping condition of the propagation process is that when no new nodes are activated in a certain time step t, the propagation process ends, and the final set of activated nodes is the coverage of information propagation.

[0047] For example, calculate the DI index value of each node. For node i, its DI index value is = * , if the degree of node i is 10 and the influence behavior characteristic is 0.5, then its =5. Select the nodes with the highest scores as seed nodes according to the DI index value of the nodes, input them into the independent cascade model to start propagation, and the information starts from the seed nodes. When there are no new activated nodes in the network, stop propagation and count the nodes in the activated state.

[0048] In order to verify that the proposed DI index can effectively cover the largest range compared with traditional indicators based on network structure characteristics, we also select seed nodes based on three other classic network structure indicators, node degree, Collective Influence (CI), and k-core, and calculate the final propagation range. The propagation ability of seed nodes under the DI index is compared with the propagation ability under the three classic network structure indicators. Figure 3 As shown in the figure, it can be seen that when different numbers of seed nodes are selected, the final propagation range of the seed node group selected by the DI indicator is always the largest.

[0049] In summary, in this scheme, first, a service network dataset is constructed through the Barabási-Albert network model, in which nodes represent users and edges represent that connected users can communicate. Then, two behavioral characteristics of users are defined, influence and susceptibility. The probability of information propagation between users is affected by the influence of the source user and the susceptibility of the target user. Subsequently, seed nodes are selected by considering a variety of centrality indicators based on network structure and user behavior attributes. Finally, under the condition of a fixed number of seed nodes, the independent cascade model in information propagation dynamics is used to analyze the propagation range of seed node groups under different methods. The effectiveness of the node selection method that considers both network structure and behavioral characteristics is verified by numerical simulation.

[0050] The embodiments of this specification provide a method and device for determining the service scope in a service network, wherein the method for determining the service scope in a service network includes: generating a service network using a scale-free network model; wherein the service network includes multiple nodes; assigning values ​​to the behavior characteristics of each node in the service network to determine the target behavior characteristics; determining the propagation probability between each node based on the target behavior characteristics; determining the seed node from the node, and simulating information propagation based on the seed node and the propagation probability to determine the service scope. By introducing influential behavior characteristics and considering the characteristics of the two dimensions of network structure and behavior at the same time, it is used to identify key nodes in the network, and finally verifies its propagation effect, thereby improving the service scope of the service network.

[0051] In another embodiment, see Figure 4 , a numerical case study is provided to compare the proposed DI index with the traditional centrality index (taking node degree as an example). Consider Figure 4 The network shown includes 7 nodes and 8 edges. The influence and susceptibility of the nodes are assigned as follows Figure 4As shown in the figure, for node a, (0.3, 0.4) means that the node's influence characteristic is 0.3 and the susceptibility characteristic is 0.4, and the rest of the nodes are similar. According to the calculation method of the node degree centrality index, the degrees of nodes a, b, c, d, e, f, and g can be calculated as 1, 4, 1, 1, 4, 2, and 3 respectively; the corresponding influence characteristics of these 7 nodes in the network are 0.3, 0.2, 0.1, 0.5, 0.2, 0.8, and 0.9 respectively. According to the calculation formula of the DI index = * , the DI index values ​​of nodes a to g can be calculated as 0.3, 0.8, 0.1, 0.5, 0.8, 1.6, 2.7 respectively. By sorting the importance of nodes according to the degree centrality index, the node sequence b, e, g, f, a, c, d can be obtained; if the importance of nodes is sorted according to the DI index, the node sequence g, f, b, e, d, a, c can be obtained. If only the most important node is selected, node b or e will be selected according to the degree centrality index, but node g will be selected according to the DI index.

[0052] The key nodes identified by the existing centrality indicators based on network structure characteristics may have their propagation capabilities overestimated. This is because these indicators, when designed, do not take into account that the closeness of connections between users will affect information dissemination, that is, only the number of adjacent users is considered, but not the quality of the connection. The embodiment of this specification specifically proposes the DI indicator, and verifies the effectiveness of the proposed indicator under the independent cascade model through numerical experiments. The specific idea is as follows: first, a service network is generated through a generative model, and then user behavior characteristics are randomly assigned, and the DI index values ​​of all nodes are calculated based on the network structure characteristics and behavior characteristics, and the nodes ranked by the DI index value are selected as seed nodes. After the probability of propagation between users is calculated through user behavior characteristics, information propagation is started under the independent cascade model, and the propagation range of the key nodes identified by the DI indicator is counted, and compared with the results under multiple classic network structure centrality indicators.

[0053] Corresponding to the above method embodiment, this specification also provides an embodiment of a device for determining a service range in a service network. Figure 5 FIG. 1 is a schematic diagram showing a structure of a device for determining a service range in a service network provided by an embodiment of the present specification. Figure 5 As shown, the device comprises: The network generation module 501 is configured to generate a service network using a scale-free network model; wherein the service network includes a plurality of nodes; The feature assignment module 502 is configured to assign a value to the behavior feature of each node in the service network to determine a target behavior feature; A propagation probability module 503 is configured to determine the propagation probability between nodes based on the target behavior characteristics; The range determination module 504 is configured to determine a seed node from the nodes, and simulate information propagation based on the seed node and the propagation probability to determine the service range.

[0054] In a possible implementation, a scale-free network model is used to generate a service network, including: Determining an initial network; wherein the initial network includes a set number of nodes; Add new nodes to the initial network, connect nodes to the new nodes based on the priority connection mechanism, and determine the target number of nodes; When the target number of nodes reaches the preset number of nodes, the initial network is used as the service network.

[0055] In a possible implementation, assigning a value to a behavior feature of each node in the service network to determine a target behavior feature includes: Determine the influence behavior characteristics and susceptibility behavior characteristics of each node; Based on the random assignment method, the influence behavior characteristics and susceptibility behavior characteristics are assigned to determine the target behavior characteristics.

[0056] In a possible implementation, determining the propagation probability between nodes based on the target behavior characteristics includes: The propagation probability between nodes is determined by performing a product operation based on the influence behavior characteristics and the susceptibility behavior characteristics.

[0057] In a possible implementation, determining a seed node from a node includes: Determine the node degree of each node in the service network; Determine the DI index value based on node degree and influence behavior characteristics; The seed node is determined based on the DI index value.

[0058] In a possible implementation, information propagation is simulated based on seed nodes and propagation probabilities to determine a service scope, including: Determine the time step, activate nodes based on the time step, seed nodes and propagation probability, and determine the activated nodes; The service scope is determined based on the activated nodes and seed nodes.

[0059] In a possible implementation, node activation is performed based on the time step, the seed node, and the propagation probability, and the activation node is determined, including: Activate the seed node at the first time step of the time step; Perform node activation based on the seed node and the propagation probability corresponding to the seed node at a second time step of the time step to determine a first activated node; In the third time step of the time step, node activation is continued based on the first activated node and the propagation probability corresponding to the first activated node until no other nodes are activated in any time step; wherein the other nodes are nodes that have not been activated.

[0060] The embodiments of this specification provide a method and device for determining the service scope in a service network, wherein the device for determining the service scope in a service network includes: generating a service network using a scale-free network model; wherein the service network includes multiple nodes; assigning values ​​to the behavior characteristics of each node in the service network to determine the target behavior characteristics; determining the propagation probability between each node based on the target behavior characteristics; determining the seed node from the node, and simulating information propagation based on the seed node and the propagation probability to determine the service scope. By introducing influential behavior characteristics and considering the characteristics of the two dimensions of network structure and behavior at the same time, it is used to identify key nodes in the network, and finally verifies its propagation effect, thereby improving the service scope of the service network.

[0061] The above is a schematic scheme of a device for determining a service scope in a service network of this embodiment. It should be noted that the technical scheme of the device for determining a service scope in a service network and the technical scheme of the method for determining a service scope in a service network described above belong to the same concept, and the details not described in detail in the technical scheme of the device for determining a service scope in a service network can be referred to the description of the technical scheme of the method for determining a service scope in a service network described above.

[0062] Figure 6 The block diagram of a computing device 600 according to an embodiment of the present specification is shown. The components of the computing device 600 include but are not limited to a memory 610 and a processor 620. The processor 620 is connected to the memory 610 via a bus 630, and the database 650 is used to store data.

[0063] The computing device 600 also includes an access device 640 that enables the computing device 600 to communicate via one or more networks 660. Examples of these networks include a public switched telephone network (PSTN), a local area network (LAN), a wide area network (WAN), a personal area network (PAN), or a combination of communication networks such as the Internet. The access device 640 may include one or more of any type of network interface (e.g., a network interface card (NIC)) that is wired or wireless, such as an IEEE 802.11 wireless local area network (WLAN) wireless interface, a world-wide interoperability for microwave access (Wi-MAX) interface, an Ethernet interface, a universal serial bus (USB) interface, a cellular network interface, a Bluetooth interface, and a near field communication (NFC).

[0064] In one embodiment of the present specification, the above components of the computing device 600 and Figure 6 Other components not shown in the figure may also be connected to each other, for example, via a bus. It should be understood that Figure 6 The computing device structure block diagram shown is only for the purpose of illustration, and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0065] The computing device 600 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., a tablet computer, a personal digital assistant, a laptop computer, a notebook computer, a netbook, etc.), a mobile phone (e.g., a smart phone), a wearable computing device (e.g., a smart watch, smart glasses, etc.), or other types of mobile devices, or a stationary computing device such as a desktop computer or a personal computer (PC). The computing device 600 may also be a mobile or stationary server.

[0066] The processor 620 is used to execute the following computer executable instructions, which, when executed by the processor, implement the steps of the method for determining the service scope in the service network. The above is a schematic scheme of a computing device of this embodiment. It should be noted that the technical scheme of the computing device and the technical scheme of the method for determining the service scope in the service network are of the same concept. For details not described in detail in the technical scheme of the computing device, please refer to the description of the technical scheme of the method for determining the service scope in the service network.

[0067] An embodiment of the present specification further provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the above-mentioned method for determining a service scope in a service network.

[0068] The above is a schematic scheme of a computer-readable storage medium of this embodiment. It should be noted that the technical scheme of the storage medium and the technical scheme of the method for determining the service scope in the service network described above belong to the same concept, and the details not described in detail in the technical scheme of the storage medium can be referred to the description of the technical scheme of the method for determining the service scope in the service network described above.

[0069] An embodiment of the present specification further provides a computer program, wherein when the computer program is executed in a computer, the computer is instructed to execute the steps of the above-mentioned method for determining a service range in a service network.

[0070] The above is an illustrative solution of a computer program of this embodiment. It should be noted that the technical solution of the computer program and the technical solution of the method for determining the service scope in the service network described above are of the same concept, and the details not described in detail in the technical solution of the computer program can be found in the description of the technical solution of the method for determining the service scope in the service network described above.

[0071] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0072] The computer instructions include computer program codes, which may be in source code form, object code form, executable files or some intermediate forms, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0073] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the embodiments of this specification are not limited by the order of the actions described, because according to the embodiments of this specification, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the embodiments of this specification.

[0074] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0075] The preferred embodiments of this specification disclosed above are only used to help explain this specification. The optional embodiments do not describe all the details in detail, nor do they limit the invention to only the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of the embodiments of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the embodiments of this specification, so that technicians in the relevant technical field can well understand and use this specification. This specification is only limited by the claims and their full scope and equivalents.

Claims

1. A method for determining a service range in a service network, characterized in that: include: Generate a service network using a scale-free network model; wherein the service network includes a plurality of nodes; Assigning a value to the behavior characteristics of each of the nodes in the service network to determine a target behavior characteristic; Determining the propagation probability between each of the nodes based on the target behavior characteristics; A seed node is determined from the nodes, and information propagation is simulated based on the seed node and the propagation probability to determine a service range.

2. The method according to claim 1, characterized in that: The method of using a scale-free network model to generate a service network includes: Determining an initial network; wherein the initial network includes a set number of nodes; Adding a new node to the initial network, connecting the node with the new node based on a priority connection mechanism, and determining a target number of nodes; When the target node number reaches a preset node number, the initial network is used as the service network.

3. The method according to claim 1, characterized in that The assigning a value to the behavior characteristic of each node in the service network to determine a target behavior characteristic includes: Determining the influence behavior characteristics and susceptibility behavior characteristics of each of the nodes; The influence behavior characteristics and the susceptibility behavior characteristics are assigned values ​​based on a random assignment method to determine the target behavior characteristics.

4. The method according to claim 3, characterized in that The determining the propagation probability between the nodes based on the target behavior characteristics includes: A propagation probability between the nodes is determined based on a multiplication operation of the influence behavior feature and the susceptibility behavior feature.

5. The method according to claim 3, characterized in that: The step of determining a seed node from the nodes comprises: Determining the node degree of each of the nodes in the service network; Determine a DI index value based on the node degree and the influence behavior characteristics; A seed node is determined based on the DI index value.

6. The method according to claim 1, characterized in that The simulating information propagation based on the seed node and the propagation probability to determine the service scope includes: Determine a time step, perform node activation based on the time step, the seed node and the propagation probability, and determine an activated node; A service range is determined based on the activated nodes and the seed nodes.

7. The method according to claim 6, characterized in that The step of performing node activation based on the time step, the seed node, and the propagation probability to determine the activated node includes: activating the seed node at a first time step of the time steps; Perform node activation based on the seed node and the propagation probability corresponding to the seed node at a second time step of the time step to determine a first activated node; In a third time step of the time steps, node activation continues to be performed based on the first activated node and the propagation probability corresponding to the first activated node until no other nodes are activated in any of the time steps; wherein the other nodes are nodes that have not been activated.

8. A device for determining a service range in a service network, characterized in that: include: A network generation module is configured to generate a service network using a scale-free network model; wherein the service network includes a plurality of nodes; A feature assignment module is configured to assign a value to the behavior feature of each of the nodes in the service network to determine a target behavior feature; A propagation probability module, configured to determine the propagation probability between each of the nodes based on the target behavior characteristics; The range determination module is configured to determine a seed node from the nodes, and simulate information propagation based on the seed node and the propagation probability to determine a service range.

9. A computing device, characterized in that include: Memory and processor; The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the method for determining the service scope in the service network according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the method for determining a service scope in a service network according to any one of claims 1 to 7.

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