Information processing system and information processing method

Abstract

To provide an information processing system and an information processing method, etc., for appropriately evaluating the effective control relationship between entities. [Solution] The information processing system includes an entity network acquisition unit that acquires an entity network representing the mutual investment relationships of multiple nodes corresponding to multiple entities, and a controlled node identification unit that identifies controlled nodes that are effectively controlled by a dominating node among the multiple nodes based on the entity network.The controlled node identification unit identifies the controlled nodes by performing an update process to add to the controlled nodes nodes that are directly connected to a second node group, which is one or more nodes included in the first node group, and whose sum of the investment ratios assigned to edges between the nodes and each node of the second node group is greater than a first threshold value, when the dominating node and the already identified controlled nodes are defined as a first node group.

Description

[Technical field]

[0001] The present invention relates to an information processing system, an information processing method, and the like. [Background technology]

[0002] Conventionally, there has been a known method of quantifying and evaluating the influence of an entity over another entity by using the ownership ratio of stocks (shareholding ratio, investment ratio). Examples of entities include countries, companies, and individuals.

[0003] Non-Patent Document 1 proposes a method for quantifying the influence of an entity that indirectly exerts influence over another entity by simply accumulating the shareholding ratios.

[0004] Furthermore, Patent Document 1 proposes a method of quantifying the influence between entities after changing the investment ratio to 100% when the investment ratio exceeds half. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent No. 7121366 [Non-patent literature]

[0006] [Non-Patent Document 1] Mizuno T, Doi S, Kurizaki S (2020) The power of corporate control in the global ownership network. PLoS ONE 15(8): e0237862. https: / / doi.org / 10.1371 / journal.pone.0237862 Summary of the Invention [Problem to be solved by the invention]

[0007] With conventional methods, depending on the structure of the network being analyzed, there is a possibility that the effective dominance relationships between entities may diverge from the calculated value of influence.

[0008] According to some aspects of the present disclosure, it is possible to provide an information processing system, an information processing method, etc. that appropriately evaluates the effective dominance relationship between entities. [Means for solving the problem]

[0009] One aspect of the present disclosure relates to an information processing system including an entity network acquisition unit that acquires an entity network that represents the mutual investment relationships of multiple nodes corresponding to multiple entities by connecting lower nodes that are invested in and upper nodes that contribute with edges to which investment ratios are assigned, and a controlled node identification unit that identifies controlled nodes that are effectively controlled by a dominating node among the multiple nodes based on the entity network, wherein when the dominating node and the already identified controlled nodes are defined as a first node group, the controlled node identification unit relates to an information processing system that identifies the controlled nodes by performing an update process that adds to the controlled nodes nodes that are directly connected to a second node group that is one or more nodes included in the first node group among the multiple nodes, and for which the sum of the investment ratios assigned to the edges between the nodes and each node of the second node group is greater than a first threshold.

[0010] Another aspect of the present disclosure relates to an information processing method in which an information processing device acquires an entity network that represents mutual investment relationships between multiple nodes corresponding to multiple entities by connecting lower nodes that are invested in and upper nodes that contribute with edges to which investment ratios are assigned, and identifies controlled nodes that are effectively controlled by a dominating node among the multiple nodes based on the entity network. In identifying the controlled nodes, when the dominating node and the already identified controlled nodes are considered to be a first node group, an update process is performed to add to the controlled nodes a node among the multiple nodes that is directly connected to a second node group that is one or more nodes included in the first node group and has a sum of the investment ratios assigned to the edges between the nodes and each node of the second node group that is greater than a first threshold value, thereby identifying the controlled nodes. [Brief description of the drawings]

[0011] [Figure 1] 1 is a configuration example of a system including an information processing system. [Diagram 2] 1 is a configuration example of a server system. [Diagram 3] 2 is a configuration example of a terminal device. [Figure 4] FIG. 1 is an explanatory diagram of corporate holdings network analysis. [Diagram 5] This is an example of an entity network (sub-network). [Figure 6A] FIG. 11 is an explanatory diagram of a comparative example of the present embodiment. [Figure 6B] FIG. 11 is an explanatory diagram of a comparative example of the present embodiment. [Figure 7] 13 is a specific example of a network in which the influence degree in the comparative example is calculated to be excessively low. [Figure 8] 4 is a flowchart illustrating a process of the information processing system according to the present embodiment. [Figure 9] 13 is a flowchart illustrating a process of identifying a controlled node. [Figure 10]11 is a diagram for explaining the propagation of dominance by the process of identifying a dominated node; FIG. [Figure 11] 11 is a diagram for explaining the propagation of dominance by the process of identifying a dominated node; FIG. [Figure 12] 11 is a diagram for explaining the propagation of dominance by the process of identifying a dominated node; FIG. [Figure 13] 11 is a diagram for explaining the propagation of dominance by the process of identifying a dominated node; FIG. [Figure 14] 11 is a diagram for explaining the propagation of dominance by the process of identifying a dominated node; FIG. [Figure 15A] Another example of an entity network (sub-network). [Figure 15B] 1 is an example of an incidence matrix. [Figure 16] 11 is a flowchart illustrating a process using a matrix operation. [Figure 17A] FIG. 11 is a diagram illustrating a first step of the vector update process. [Figure 17B] FIG. 11 is a diagram illustrating a processing result of the first step. [Figure 18A] FIG. 11 is a diagram illustrating a second step of the vector update process. [Figure 18B] FIG. 11 is a diagram illustrating a processing result of the second step. [Figure 19A] FIG. 11 is a diagram illustrating a third step of the vector update process. [Figure 19B] FIG. 11 is a diagram illustrating a processing result of the third step. [Figure 20A] FIG. 13 is a diagram illustrating a fourth step of the vector update process. [Figure 20B] FIG. 13 is a diagram illustrating a processing result of the fourth step. [Figure 21A] FIG. 13 is a diagram illustrating a calculation process of an influence degree. [Figure 21B] 13 is a diagram illustrating a result of an influence degree calculation process. FIG. [Figure 22A] FIG. 11 is a diagram illustrating a first step of the vector update process. [Figure 22B] FIG. 11 is a diagram illustrating a processing result of the first step. [Figure 23A]FIG. 11 is a diagram illustrating a second step of the vector update process. [Figure 23B] FIG. 11 is a diagram illustrating a processing result of the second step. [Figure 24A] FIG. 13 is a diagram illustrating a calculation process of an influence degree. [Figure 24B] 13 is a diagram illustrating a result of an influence degree calculation process. FIG. [Diagram 25] 11A and 11B are diagrams illustrating processing results according to the embodiment. [Figure 26] 11A and 11B are diagrams illustrating processing results according to the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, the present embodiment will be described with reference to the drawings. In the drawings, the same or equivalent elements are given the same reference numerals, and duplicated explanations are omitted. Note that the present embodiment described below does not unduly limit the contents described in the claims. In addition, all of the configurations described in the present embodiment are not necessarily essential configurations of the present disclosure.

[0013] 1. OSINT Systems 1.1 System configuration example FIG. 1 is a configuration example of a system including an information processing system 10 according to the present embodiment. The system according to the present embodiment includes a server system 100 and a terminal device 200. However, the configuration of the system including the information processing system 10 is not limited to the example of FIG. 1, and various modifications such as omitting a part or adding other configurations are possible. For example, FIG. 1 illustrates two terminal devices 200, terminal device 200-1 and terminal device 200-2, but the number of terminal devices 200 is not limited to this. The fact that modifications such as omission or addition of configurations are possible is also true for FIG. 2 and FIG. 3 described later.

[0014] The information processing system 10 of the present embodiment corresponds to, for example, a server system 100. The server system 100 corresponds to a computer. However, the method of the present embodiment is not limited to this, and the processing of the information processing system 10 may be executed by distributed processing using the server system 100 and other devices. For example, the information processing system 10 of the present embodiment may be realized by distributed processing between the server system 100 and a terminal device 200. An example in which the information processing system 10 is the server system 100 will be described below.

[0015] The server system 100 may be one server or may include multiple servers. For example, the server system 100 may include a database server and an application server. The database server may store various data such as an entity network 121 described later. The application server may perform various processes according to this embodiment. The multiple servers may be physical servers or virtual servers. When a virtual server is used, the virtual server may be provided in one physical server or may be distributed and arranged in multiple physical servers. As described above, the specific configuration of the server system 100 in this embodiment can be modified in various ways.

[0016] The terminal device 200 is a device used by a user who uses the information processing system 10. The terminal device 200 may be a PC (Personal Computer), a mobile terminal device such as a smartphone, or another device.

[0017] The server system 100 is connected to terminal devices 200-1 and 200-2 via a network, for example. In the following, when there is no need to distinguish between multiple terminal devices, they will be simply referred to as terminal devices 200. The network will be described as a public communication network such as the Internet, for example, but may be a LAN (Local Area Network) or the like.

[0018] The information processing system 10 of this embodiment is an OSINT (Open Source Intelligence) system that uses public information to collect and analyze data related to a target. Public information includes various types of information that are widely disclosed and legally available, such as securities reports, input-output tables, official government announcements, and reports on countries and companies. Note that the information processing system 10 of this embodiment is not limited to an OSINT system.

[0019] The server system 100 generates nodes including various attributes based on the public information. The nodes represent entities. The entities may be people, companies, or countries. The attributes are information determined based on the public information, for example. The attributes include information about the entities and information about the shareholding ratio (investment ratio). The attributes may include various information such as nationality, business field, sales, number of employees, board members, and trade items.

[0020] If an attribute of a given node includes an attribute that includes a relationship with another node, the given node is connected to the other node by an edge having a direction. For example, assume that the shareholders of a given entity include another entity. In this case, the node corresponding to the other entity is connected to the node corresponding to the given entity by an edge representing the shareholding ratio. The edge is an edge having a direction from the influencing party to the receiving party. For example, the edge is an edge having a direction from the investing party to the invested party. However, the edge may also have a direction from the affected party to the donor.

[0021] In the method of this embodiment, the server system 100 acquires an entity network, which is a network in which multiple nodes representing multiple entities are connected by edges having a direction based on an attribute. In other words, the entity network is a directed graph. The server system 100 performs an analysis based on the entity network and performs a process of presenting the analysis result. For example, the terminal device 200 is a device used by a user who uses a service provided by the OSINT system. For example, the user uses the terminal device 200 to request some kind of analysis from the server system 100 (information processing system 10). The server system 100 performs an analysis based on the entity network and transmits the analysis result to the terminal device 200 as a response.

[0022] 2 is a block diagram showing a detailed configuration example of the server system 100. The server system 100 includes, for example, a processing unit 110, a storage unit 120, and a communication unit .

[0023] The processing unit 110 of this embodiment may be realized by predetermined hardware. The hardware may include at least one of a circuit for processing digital signals and a circuit for processing analog signals. For example, the hardware may be configured by one or more circuit devices or one or more circuit elements mounted on a circuit board. As the circuit device, an integrated circuit (IC) or a field-programmable gate array (FPGA) may be applied. The one or more circuit elements may be, for example, a resistor, a capacitor, etc.

[0024] The processing unit 110 may be realized by one or more processors. The server system 100 of the present embodiment includes, for example, a memory that stores information and a processor that operates based on the information stored in the memory. The information is, for example, a program and various data. The processor includes hardware. The processor can be various processors such as a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), etc. The memory may be a semiconductor memory such as a static random access memory (SRAM), a dynamic random access memory (DRAM), a flash memory, etc., or a register. The memory may be a magnetic storage device such as a hard disk drive (HDD), or an optical storage device such as an optical disk device. For example, the memory stores computer-readable instructions, and the processor executes the instructions to realize the function of the processing unit 110 as processing. The instructions may be instructions of an instruction set constituting a program, or instructions that instruct a hardware circuit of the processor to operate.

[0025] The processing unit 110 in the example of FIG. 2 includes an entity network acquisition unit 111, a target node acquisition unit 112, a sub-network extraction unit 113, a governed node identification unit 114, an influence degree calculation unit 115, and a display processing unit .

[0026] The entity network acquisition unit 111 is an acquisition unit that acquires the entity network 121. For example, the entity network acquisition unit 111 may generate the entity network 121 based on public information. The entity network acquisition unit 111 stores the generated entity network 121 in the storage unit 120. When executing the processing of this embodiment including the processing of identifying governed nodes, the entity network acquisition unit 111 performs a process of reading (acquiring) the entity network 121 stored in the storage unit 120.

[0027] The entity network 121 may be generated in a system other than the information processing system 10 according to this embodiment. In this case, the entity network acquisition unit 111 may acquire the entity network from the other system via the communication unit 130.

[0028] The entity network acquisition unit 111 acquires, for example, a network in which multiple entities are linked by investment relationships as the entity network 121. The entity network 121 includes multiple entities. As described above, each entity represents a node. The nodes are connected by edges based on the investment relationships. In addition, each edge is assigned an investment ratio. The investment ratio represents a shareholding ratio. Information on the shareholding ratio can also be obtained based on the public information described above.

[0029] The target node acquisition unit 112 performs a process of acquiring a target node from a plurality of nodes included in the entity network 121. The target node here refers to a node for which the degree of influence from other nodes is to be calculated. For example, the target node acquisition unit 112 may acquire the target node based on the result of a target node selection operation executed by the terminal device 200.

[0030] When any one of the multiple nodes in the entity network 121 is determined to be a target node, the subnetwork extraction unit 113 performs a process of extracting a subnetwork consisting of higher-level nodes that are directly or indirectly connected to the target node.

[0031] However, extraction of a subnetwork related to the target node is not essential. For example, a subnetwork related to a dominating node (a dominating node described below) may be extracted instead of the target node, which is a dominated node. Also, extraction of the subnetwork itself may be omitted, and the following processing may be performed for the entire entity network. In addition, various modifications of the specific processing flow are possible. The following mainly describes an example in which a target node is obtained, a subnetwork related to the target node is extracted, and processing is performed for the subnetwork.

[0032] The controlled node specification unit 114 performs a process of selecting a controlling node that effectively controls other nodes from the sub-network, and a process of specifying a controlled node that is a node that is effectively controlled by the controlling node. Here, effective control means that the behavior of other entities can be substantially controlled. For example, when an entity can determine the behavior of other entities based on an investment relationship, the entity effectively controls the other entities. More specifically, the behavior here means the behavior in a resolution of the other entities, and effective control may mean, for example, that the entity can determine whether the resolution is passed and / or rejected. In this case, effectively controlling another entity may mean directly or indirectly holding a majority of the voting stocks issued by the other entities. The processing of the controlled node specification unit 114 will be described later with reference to Figs. 9 to 14 and the like. In the entity network 121, since each node corresponds to an entity, the dominance relationship between entities is expressed as the dominance relationship between nodes. That is, in this specification, "an entity corresponding to a dominating node effectively dominates an entity corresponding to a dominated node" is simply expressed as "a dominating node effectively dominates a dominated node." Similarly, a node in the following description is not limited to a node itself in a network (directed graph), and may represent an entity corresponding to the node.

[0033] The influence calculation unit 115 calculates the influence, which is an index representing the degree of influence of a dominating node on other nodes. The influence in this embodiment is an index value that is a maximum value (e.g., 1) when the target node is a dominated node, a minimum value (e.g., 0) when the target node is not directly connected to either a dominating node or a dominated node, and an intermediate value (e.g., greater than 0 and less than 1) that changes according to the degree of domination when the target node is not a dominated node and the immediately upper node is a dominating node or a dominated node. Note that in this embodiment, other influences such as the influence shown in Patent Document 1 (hereinafter referred to as Power Index) may be used in combination.

[0034] The display processing unit 116 performs processing for displaying the processing results in this embodiment on a display unit. The display unit here is, for example, the display unit 240 of the terminal device 200. However, the display target of the display processing unit 116 may be the display unit of the server system 100 or a display unit of another device.

[0035] The display processing unit 116 performs processing to display the dominating nodes and the dominated nodes in the entity network in a manner that makes them distinguishable from other nodes. Details will be described later with reference to Figs. 13-14, 25-26, etc. Furthermore, the display processing unit 116 may perform processing to display a screen including the influence calculated by the influence calculation unit 115, or may perform processing to display other index values ​​such as the indirect shareholding ratio and the Power Index.

[0036] The storage unit 120 is a work area for the processing unit 110, and stores various information. The storage unit 120 can be realized by various types of memory. The memory may be a semiconductor memory such as an SRAM, a DRAM, a ROM, or a flash memory. The memory may be a register, a magnetic storage device such as a hard disk device, or an optical storage device such as an optical disk device.

[0037] The storage unit 120 stores, for example, the entity network 121 acquired by the entity network acquisition unit 111. The storage unit 120 is capable of storing various information related to the processing of this embodiment.

[0038] The communication unit 130 is an interface for performing communication via a network. The communication unit 130 includes, for example, an antenna, an RF (radio frequency) circuit, and a baseband circuit. The communication unit 130 may operate according to the control by the processing unit 110, or may include a processor for communication control different from the processing unit 110. The communication unit 130 is, for example, an interface for performing communication according to TCP / IP (Transmission Control Protocol / Internet Protocol). The specific communication method can be variously modified.

[0039] 3 is a block diagram showing a detailed configuration example of the terminal device 200. The terminal device 200 includes a processing unit 210, a storage unit 220, a communication unit 230, a display unit 240, and an operation unit 250.

[0040] The processing unit 210 is configured by hardware including at least one of a circuit for processing digital signals and a circuit for processing analog signals. The processing unit 210 may be realized by a processor. The processor may be various processors such as a CPU, a GPU, a DSP, etc. The processor executes instructions stored in the memory of the terminal device 200, whereby the function of the processing unit 210 is realized as processing.

[0041] The storage unit 220 is a work area for the processing unit 210, and is realized by various types of memory such as an SRAM, a DRAM, or a ROM.

[0042] The communication unit 230 is an interface for performing communication via a network. The communication unit 230 includes, for example, an antenna, an RF circuit, and a baseband circuit. The communication unit 230 performs communication with the server system 100 via, for example, the network.

[0043] The display unit 240 is an interface that displays various information. The display unit 240 may be a liquid crystal display, an organic EL display, or a display of another type. Based on the control from the display processing unit 116 of the server system 100, the display unit 240 displays, for example, a screen including an entity network in which the display mode of the dominating node and the dominated node is different from the display mode of the other nodes.

[0044] The operation unit 250 is an interface for the user to operate the terminal device 200. The operation unit 250 may be a button or the like provided on the terminal device 200. The display unit 240 and the operation unit 250 may be a touch panel integrally configured.

[0045] 1.2 Examples of services Next, a specific example of a service provided by the information processing system 10, which is an OSINT system, will be described. As a specific service, an example of corporate holdings network analysis will be described below.

[0046] Figure 4 is a diagram for explaining corporate holding network analysis, and is an example of an entity network showing investment relationships. As shown in Figure 4, a network showing the investment relationships of countries and companies is formed based on the information showing shareholders and investment ratios contained in public information.

[0047] For example, when any node in the network to be processed is designated as a dominating node, the controlled node identification unit 114 identifies the controlled node that is effectively controlled by the dominating node. The influence calculation unit 115 analyzes the influence of various countries and companies on other companies. In this case, the influence indicates the extent to which control by investment extends.

[0048] For example, when a specific country is considered as a dominating node, it is possible to grasp the degree to which the country controls the product supply of a given industry by determining the controlled nodes that are effectively controlled by the dominating node, or the influence that the dominating node has on companies in the given industry. For example, when a serious incident occurs in the country, it is possible to evaluate the impact of the incident on the stable supply of products. The controlled node identification unit 114 and the influence calculation unit 115 may determine the presence or absence of effective control and influence of each country on global companies. This makes it possible to grasp the power balance between countries. In addition, it is also possible to grasp the transition of the power balance by determining the time-series change in the influence of each country on global companies.

[0049] Alternatively, the controlled node specification unit 114 and the influence degree calculation unit 115 may obtain the presence or absence of effective control and influence of other countries on companies related to the infrastructure of a given country. Companies related to the infrastructure may be energy-related companies such as electric power companies, or companies that provide mobile communication networks. This makes it possible to evaluate the risk of the infrastructure stopping functioning.

[0050] Alternatively, the controlled node specification unit 114 and the influence degree calculation unit 115 may determine the presence or absence of effective control and the degree of influence over a company that has technology that can be diverted to military use. This makes it possible to detect security risks.

[0051] The controlled node specification unit 114 and the influence calculation unit 115 may determine the change in the target of effective control and the change in the influence when a country or a company takes a specific action. For example, assuming that a foreign policy of a given country is changed, it is possible to simulate the influence of the foreign policy on countries around the world by determining the scope of effective control and the influence before and after the change.

[0052] By using corporate holding network analysis, the controlled node specification unit 114 and the influence degree calculation unit 115 are able to perform analysis based on complex investment relationships that are difficult to detect manually.

[0053] In recent years, relationships between nations, companies, and important people have become more global and complex than ever before. This means that there are limitations to manual analysis. In this regard, the OSINT system described above is capable of analyzing networks that show corporate control through investment. OSINT systems are capable of deciphering complex relationships, enabling governments and companies to devise optimal strategies.

[0054] 2. Processing Details The process of this embodiment will be described in detail below. The method of this embodiment is, in the narrow sense, corporate holding network analysis. However, the method of this embodiment can be applied to any method other than corporate holding network analysis.

[0055] 2.1 Indicators of impact First, an index representing the degree of influence will be considered. Fig. 5 is a diagram showing an example of the entity network 121 acquired by the entity network acquisition unit 111, or an example of a sub-network extracted by the sub-network extraction unit 113. The network in Fig. 5 includes nine nodes, Node A to Node I, corresponding to Entities A to I, respectively. The root side of the edge in Fig. 5 is connected to a node (upper node, upstream node) corresponding to the contributing side, and the tip side is connected to a node (lower node, downstream node) corresponding to the contributing side.

[0056] In the network of Fig. 5, nodes E, F, G, and H are each connected to node I by an edge, and each edge is associated with a numerical value of 51% as an investment ratio (shareholding ratio). Therefore, entity I has acquired more than half of the shares in each of entities E to H, and therefore effectively controls entities E to H. As mentioned above, for the sake of simplicity, expressions such as "entity I corresponding to node I holds 51% of the shareholding ratio of entity E corresponding to node E" will be expressed as "node I holds 51% of node E."

[0057] Also, in the network of Figure 5, the shareholding ratio of node B is 30% by node E and 30% by node F. The shareholding ratio of node C is 30% by node E and 30% by node G. The shareholding ratio of node D is 30% by node F and 30% by node H. The shareholding ratio of node A is 25% by node B, 20% by node C, and 30% by node D.

[0058] For example, the widely known indirect shareholding ratio is determined based on the product of the shareholding ratios on the path connecting two nodes. For example, between node I and node A, there is a path from node I to node E to node B to node A. Hereinafter, the path between nodes will be expressed as path IEBA, etc., by simply listing the node names. Since the shareholding ratios assigned to the edges on this path are 0.51, 0.30, and 0.25, the indirect shareholding ratio of node I to node A via path IEBA is calculated as 0.51 x 0.30 x 0.25. Since there are other paths between node I and node A, the values ​​are calculated in the same way for all the paths, and the indirect shareholding ratio of node I to node A is determined by calculating the sum of the values ​​calculated for each path.

[0059] Furthermore, in the Power Index disclosed in Patent Document 1, when the shareholding ratio exceeds half, the shareholding ratio is changed to 1 and then a calculation similar to that for the indirect shareholding ratio is performed. FIG. 6A is a diagram explaining the method of Patent Document 1. In the example of FIG. 6A, consider the Power Index of node C for node A. In this case, the shareholding ratio of node D by node C exceeds half, so the value is replaced with 1. Therefore, the Power Index of node C for node A is 0.60 (60%), which is the sum of 0.30 in route CA and 1 x 0.30 in route CDA.

[0060] In the network of FIG. 6A, Node C holds the majority of Node D's shares and therefore effectively controls Node D. Therefore, Node C can freely exercise the 30% of Node A's shares directly held by Node C and the 30% held by Node D. As mentioned above, the Power Index is 60 percent, which is a suitable index value for indicating the degree of influence of Node C on Node A. In other words, the Power Index is a value that reflects the actual degree of influence compared to the previous indirect shareholding ratio.

[0061] FIG. 6B is an example of the case where the method of Patent Document 1 is applied to the network described above in FIG. 5. In this case, the shareholding ratios of nodes E to H of node I exceed half, so these shareholding ratios are replaced with 1. Therefore, the indirect shareholding ratio along route IEBA is corrected to 1 x 0.30 x 0.25. The same applies to other routes. When calculated for all routes, the Power Index, which represents the influence of node I on node A, is 45%. In this case, the Power Index is less than half, giving the impression that node I does not effectively control node A.

[0062] However, when considering the network in Figure 6B (Figure 5), such a judgment is not necessarily correct. For example, in this network, node I effectively controls nodes E to H because the shareholding ratio of node I in nodes E to H exceeds half.

[0063] In addition, node B is held by nodes E and F with a shareholding ratio of 30% each, and since nodes E and F are effectively controlled by node I, this is equivalent to node I holding the majority of the shares in node B. In other words, node I effectively controls node B. Similarly, nodes C and D are also effectively controlled by node I, since the total shareholding ratios of the nodes effectively controlled by node I are the majority.

[0064] Nodes B to D are effectively controlled by node I, and the sum of the shareholding ratios of node A held by these three nodes is 75%, so node A is also effectively controlled by node I. Thus, even though node I effectively controls node A in the network of Figure 6B (Figure 5), the Power Index, which indicates the degree of influence of node I on node A, is a relatively small value.

[0065] The method of Patent Document 1 has the advantage that if one node holds a majority of shares in another node, the effective control relationship can be reflected by updating the value to 1, but if multiple nodes jointly hold a majority of shares, the effective control relationship is difficult to reflect. For example, in FIG. 6B, nodes E and F jointly hold 60% of the shares of node B, but since their individual shareholding ratios do not exceed 50%, the value is not updated and the Power Index is calculated. Since nodes E and F are both effectively controlled by node I, they can cooperate in making decisions regarding node B, but this point is not taken into consideration in the method of Patent Document 1.

[0066] FIG. 7 is another example of a network in which the Power Index is likely to be calculated lower than the actual degree of influence. In the network of FIG. 7, node I effectively controls nodes J to M. Then, by combining the shareholding ratios of two of nodes J to M, node I effectively controls nodes E to H. Furthermore, by combining the shareholding ratios of two of nodes E to H, node I effectively controls nodes B to D. Then, similar to the example of FIG. 6B, node I effectively controls node A by combining the shareholding ratios of nodes B to D. Thus, in the example of FIG. 7, node I also effectively controls node A. However, downstream of nodes J to M, the shareholding ratios given to each edge do not exceed half, so the above-mentioned relationship of effective control is not taken into consideration, and the Power Index is calculated using the original value (30%). As a result, the Power Index, which represents the degree of influence of node I on node A, is lower than 50%.

[0067] For example, as shown in FIG. 7, when a network structure in which the combined shareholding ratio of multiple nodes effectively controlled by a specific node exceeds half is expressed as a damping unit, in a network in which the damping unit exists, the value of the Power Index is likely to be smaller than the actual degree of influence. In the example of FIG. 6B, the structure between nodes E to H and nodes B to D corresponds to the damping unit. Similarly, in the example of FIG. 6B, the structure between nodes B to D and node A corresponds to the damping unit. In the example of FIG. 7, since there are three stages of damping units between nodes J to M and nodes E to H, between nodes E to H and nodes B to D, and between nodes B to D and node A, the value of the Power Index becomes even smaller than that of the network of FIG. 6B.

[0068] In contrast, the information processing system 10 (for example, the server system 100) according to this embodiment includes an entity network acquisition unit 111 and a controlled node identification unit 114 as shown in Fig. 2. When the controlling node and the already identified controlled nodes are regarded as a first node group, the controlled node identification unit 114 identifies the controlled nodes by performing an update process of adding, to the controlled nodes, nodes that are directly connected to a second node group, which is one or more nodes included in the first node group, and have a sum of the investment ratios assigned to the edges between the nodes in the second node group that is greater than a first threshold value.

[0069] Here, the term "dominant node" refers to a node in an entity network or sub-network that may dominate other nodes based on an investment relationship (more specifically, a node that may dominate the target node). As described above, the first node group is a set of the dominating node and nodes that are known to be effectively controlled by the dominating node. In other words, the first node group is a set of nodes that cooperate with the dominating node when the dominating node tries to exert influence on a company (for example, when it tries to exercise voting rights on a company).

[0070] Moreover, the second node group refers to a node included in the first node group that is directly connected to a node other than the first node group (located directly above the node, i.e., one stage upstream). For example, in the example of FIG. 5, when the dominating node is node I and nodes E to H have been identified as controlled nodes, nodes E and F are directly above node B. In this case, the first node group is a set of nodes E to I, and the second node group for node B is a set of nodes I and F. A node other than the first node group that is the processing target here (e.g. node B) is not included in the controlled nodes at the stage when processing is being performed, but since it receives contributions from each node included in the second node group (e.g. nodes E and F), it can be considered that it is substantially contributed by the dominating node (node ​​I).

[0071] The first threshold is, for example, 0.50 (50%). In this case, the controlled node can be determined from the viewpoint of whether or not the controlling node has enough influence to pass an ordinary resolution at the general shareholders' meeting on its own. However, the first threshold may be 2 / 3 (66.7%), which corresponds to the shareholding ratio that allows the controlling node to pass a special resolution at the general shareholders' meeting on its own. Alternatively, it may be 1 / 3 (33.3%), which corresponds to the shareholding ratio that allows the controlling node to reject a special resolution at the general shareholders' meeting on its own. The first threshold may also be set to a value different from either of these.

[0072] In this embodiment, the controlled node identification unit 114 uses the sum of the investment ratios (sum of the shareholding ratios) of the second node group in the process of identifying the controlled node. Therefore, the method of this embodiment makes it possible to appropriately determine the dominance relationship. For example, as described above, it becomes possible to appropriately detect a dominance relationship in which multiple nodes effectively controlled by a dominance node jointly hold a majority of the shares. Specific processing will be described later. Note that the method of this embodiment does not prevent other influences, such as the Power Index, from being used in combination.

[0073] In addition, a part or all of the processing performed by the information processing system 10 of the present embodiment may be realized by a program. In a narrow sense, the processing performed by the information processing system 10 is processing performed by the processing unit 110 of the server system 100, but may also include processing executed by the processing unit 210 of the terminal device 200.

[0074] The program according to this embodiment can be stored in a non-transitory information storage medium (information storage device), which is a medium readable by a computer, for example. The information storage medium can be realized by, for example, an optical disk, a memory card, a HDD, or a semiconductor memory. The semiconductor memory is, for example, a ROM. The processing unit 110 and the like perform various processes of this embodiment based on the program stored in the information storage medium. That is, the information storage medium stores a program for making a computer function as the processing unit 110 and the like. A computer is a device equipped with an input device, a processing unit, a storage unit, and an output unit. Specifically, the program according to this embodiment is a program for making a computer execute each step described later with reference to FIG. 8, FIG. 9, FIG. 16, and the like.

[0075] The technique of this embodiment can also be applied to an information processing method including the following steps: In the information processing method, an information processing device (e.g., information processing system 10, server system 100) acquires an entity network that represents mutual investment relationships between a plurality of nodes corresponding to a plurality of entities by connecting a lower node that is invested in and a higher node that is investing in by edges to which an investment ratio is assigned, identifies a controlled node that is a node that is effectively controlled by a dominating node among the plurality of nodes based on the entity network, and, in identifying the controlled node, performs an update process to add to the controlled node a node that is directly connected to a second node group that is one or more nodes included in the first node group among the plurality of nodes and has a sum of investment ratios assigned to edges between the nodes and each node of the second node group that is greater than a first threshold value when the dominating node and the already identified controlled node are regarded as a first node group, thereby identifying the controlled node.

[0076] 2.2 Overall processing FIG. 8 is a flowchart outlining the processing executed in the information processing system 10 of this embodiment.

[0077] First, in step S101, the entity network acquisition unit 111 acquires the entity network 121. The entity network acquisition unit 111 stores the entity network 121 in the storage unit 120.

[0078] In step S102, the target node acquisition unit 112 acquires any node included in the entity network 121 as a target node. For example, in step S102, the display processing unit 116 may perform processing to prompt the user of the terminal device 200 to select a target node by displaying, on the display unit 240 of the terminal device 200, the entity network 121, a list screen of entities included in the entity network 121, or a search screen for entities. For example, the operation unit 250 of the terminal device 200 may accept an input of an entity of interest that the user wishes to investigate the degree of domination by other entities, and the target node acquisition unit 112 may acquire, via the communication unit 130, a node corresponding to the entity of interest as a target node.

[0079] In step S103, the subnetwork extraction unit 113 extracts a subnetwork including the target node. For example, the subnetwork extraction unit 113 first initializes the network N by the target node. Next, the subnetwork extraction unit 113 updates the network N by adding a node that directly invests in the target node and an edge that represents the investment relationship. Then, the subnetwork extraction unit 113 updates the network N by adding a node that directly invests in the node and an edge that represents the investment relationship to the newly added node. Thereafter, the subnetwork extraction unit 113 recursively repeats this process, and when the network N does not change, stores the network N at that time in the storage unit 120 as a subnetwork. As described above, the subnetwork here is a network composed of nodes upstream of the target node, and indicates a holding relationship, so it may be expressed as an upstream holding network.

[0080] In step S104, the controlled node identification unit 114 performs a process of identifying a controlled node that is effectively controlled by a dominant node when the dominant node is determined to be a node that may dominate the target node among multiple nodes included in the sub-network. This process is also referred to as a dominance propagation process because it is a process of propagating the dominance relationship by the dominant node to the downstream side. The process of identifying the controlled node will be described in detail later.

[0081] In step S105, the influence degree calculation unit 115 obtains an influence degree that indicates the degree of influence of the dominating node on other nodes based on the result of identifying the dominated node. The details of the calculation process of the influence degree will be described later.

[0082] In step S106, the display processing unit 116 performs processing to display the result of identifying the dominated node on the display unit 240 of the terminal device 200. The display processing unit 116 may also perform processing to display the calculation result of the influence degree on the display unit 240 of the terminal device 200. For example, the display processing unit 116 may display the determination result of whether or not a target node selected by a user is effectively dominated by another node, or may display the influence degree of the dominating node on the target node.

[0083] 2.3 Dominant Node Identification Processing (Dominance Propagation Processing) FIG. 9 is a flowchart illustrating the process of identifying a governed node shown in step S104 of FIG.

[0084] In step S201, the controlled node identification unit 114 selects a dominating node from a plurality of nodes included in the sub-network. For example, the controlled node identification unit 114 selects a node whose investment ratio to at least one node other than itself is greater than a first threshold value among the nodes other than the target node included in the sub-network as a dominating node. Specifically, the controlled node identification unit 114 determines whether or not there is an edge from the node other than the target node included in the sub-network to another node, the edge having an investment ratio that exceeds a first threshold value. The controlled node identification unit 114 selects a node that satisfies the condition as a candidate node for the dominating node. Then, the controlled node identification unit 114 sequentially selects one of the candidate nodes as a dominating node. Note that the first threshold value here is, for example, 0.50 (50%) as described above, but other values ​​may be used.

[0085] In the case of the network of FIG. 5, node I has a shareholding ratio exceeding the first threshold of 0.50 for each of nodes E to H other than itself. Therefore, node I is selected as a candidate for the dominating node. Node E has a shareholding ratio of 0.30 for node B, which does not exceed the first threshold, and has a shareholding ratio of 0.30 for node C, which does not exceed the first threshold. Therefore, node E is not a candidate for the dominating node. The same is true for the other nodes, and in FIG. 5, only node I is a candidate for the dominating node. Therefore, the controlled node identification unit 114 performs the following process for node I, thereby performing a process of identifying the controlled nodes that are effectively controlled by node I.

[0086] In step S202, the ruled node identification unit 114 initializes a set P of ruled nodes that are effectively ruled by the ruler node to an empty set.

[0087] In the following processing, the dominating node itself and the set of dominated nodes effectively dominated by the dominating node are referred to as the first node group. The first node group is the union of the dominating node and set P. Fig. 10 is a diagram showing the first node group after the processing of step S202. As shown in Fig. 10, since no dominated nodes are identified in step S202, only node I, which is the dominating node, is included in the first node group.

[0088] In step S203, the controlled node identification unit 114 performs a first update process to update the set P of controlled nodes. Specifically, the update process is performed to add nodes that are controlled by the controlling node with a shareholding ratio that exceeds a first threshold to the set P of controlled nodes.

[0089] 5, the node I has a shareholding ratio for each of the other nodes E to H that exceeds the first threshold value of 0.5. Therefore, in step S203, the controlled node identification unit 114 executes a process of adding the nodes E to H to the set P.

[0090] Fig. 11 is a diagram showing the first node group after the process of step S203. As shown in Fig. 11, by the first update process of step S203, nodes E to H, which are directly dominated by node I, the dominating node, with a shareholding ratio exceeding the first threshold, are added to the set P of dominated nodes. Therefore, the first node group becomes a set of five nodes, nodes E to I. In other words, by the first update process, the dominance relationship is propagated from the dominating node to the node one level downstream.

[0091] In step S204, the controlled node identification unit 114 performs a second update process to update the controlled node set P. Specifically, the controlled node identification unit 114 performs an update process to add to the controlled node set P any node that is controlled by a node included in the first node group, either alone or jointly, with a shareholding ratio exceeding a first threshold.

[0092] More specifically, the controlled node identification unit 114 identifies a node that is directly connected to the second node group of the first node group from the sub-network. In other words, the node identified here is a node one stage downstream of one or more nodes of the first node group. Then, the controlled node identification unit 114 calculates the sum of the shareholding ratios by the second node group for each identified node, and performs a process of adding the node to be processed to the set P of controlled nodes if the sum exceeds a first threshold value.

[0093] For example, the first node group immediately before the first second update process is five nodes E to I, as described above with reference to FIG. 11. In this case, nodes B to D are directly connected to the nodes included in the first node group. In other words, each of nodes B to D is a node immediately below (one stage downstream) a node included in the first node group. Therefore, the controlled node identification unit 114 calculates the sum of the shareholding ratio for each of nodes B to D.

[0094] Specifically, node B is directly connected to nodes E and F among the nodes included in the first node group (it is a node directly below nodes E and F). Therefore, the second node group for node B is nodes E and F. The controlled node identification unit 114 calculates the sum of node E's shareholding ratio in node B and node F's shareholding ratio in node B. In this case, since each shareholding ratio is 30%, the sum of the shareholding ratios is 60%. Since the sum of the shareholding ratios exceeds the first threshold value of 50%, the controlled node identification unit 114 performs a process of adding node B to the set P of controlled nodes.

[0095] Similarly, the second node group for node C is node E and node G. Because the sum of the shareholding ratios of node E and node G is 60%, which exceeds the first threshold, the controlled node identification unit 114 adds node C to the set P of controlled nodes. Also, the second node group for node D is node F and node H. Because the sum of the shareholding ratios of node F and node H is 60%, which exceeds the first threshold, the controlled node identification unit 114 adds node D to the set P of controlled nodes.

[0096] Fig. 12 is a diagram showing the first node group after the first second update process is performed. As shown in Fig. 12, the first second update process adds nodes B to D, which are jointly controlled by controlled nodes E to H with a shareholding ratio exceeding the first threshold, to the set P of controlled nodes. Therefore, the first node group becomes a set of eight nodes, nodes B to I. In other words, the second update process propagates the dominance relationship by the dominating node from the state before the process to the node one stage downstream. Note that, although an example is shown here in which the second node group for each node includes multiple nodes, the second node group may also be a single node.

[0097] After the second update process is executed, in step S205, the controlled node identification unit 114 determines whether the set P of controlled nodes has changed as a result of the second update process. In the above example, since nodes B to D have been added to the set P of controlled nodes, the set P has changed.

[0098] If the set P of controlled nodes has changed due to the second update process (step S205: Yes), the controlled node identification unit 114 returns to step S204 and recursively executes the second update process. For example, the first node group after the first second update process is performed is nodes B to I as shown in FIG. 12. In this case, node A is directly connected to the nodes included in the first node group (it is a node directly below the nodes included in the first node group). Therefore, in the second second update process, the controlled node identification unit 114 calculates the sum of the shareholding ratios for node A.

[0099] Specifically, node A is connected to nodes B to D among the nodes included in the first node group. Therefore, the second node group for node A is nodes B to D. The controlled node identification unit 114 calculates the sum of the shareholding ratio of node B to node A, the shareholding ratio of node C to node A, and the shareholding ratio of node D to node A. In this case, the sum of the shareholding ratios is 0.25+0.20+0.30=0.75 (75%). Because the sum of the shareholding ratios exceeds the first threshold value of 50%, the controlled node identification unit 114 performs a process of adding node A to the set P of controlled nodes.

[0100] Fig. 13 is a diagram showing the first node group after the second update process is performed for the second time. As shown in Fig. 13, the second update process adds node A, which is jointly controlled by controlled nodes B to D with a shareholding ratio exceeding the first threshold, to the set P of controlled nodes. Therefore, the first node group becomes a set of nine nodes, nodes A to I. In other words, the second update process propagates the dominance relationship by the dominating node from the state before the process to the node one level downstream.

[0101] In this manner, in this embodiment, the controlled node identification unit 114 performs an initialization process to initialize the controlled node with an empty set (step S202), and after the initialization process, performs a first update process to add to the controlled node, among the multiple nodes, those nodes that are directly connected to the dominating node and have an investment ratio assigned to the edge between the dominating node that is greater than a first threshold (step S203), and may identify the controlled node by repeatedly executing a second update process after the first update process (step S204). In this manner, it becomes possible to efficiently determine the domination path and domination range by the dominating node by a top-down process that propagates the domination relationship downstream from the dominating node.

[0102] After executing the second update process, in step S205, the controlled node identification unit 114 determines whether the set P of controlled nodes has changed as a result of the second update process. In the above example, node A has been added to the set P of controlled nodes, so the set P has changed. Therefore, the controlled node identification unit 114 returns to step S204 and executes the second update process for the third time.

[0103] As shown in Fig. 13, in the network illustrated here, all the nodes of the subnetwork are added to the first node group at the stage of the second update process for the second time. Therefore, even if the third update process is performed, the set P of the dominated nodes does not change.

[0104] Alternatively, the set P of dominated nodes does not change in the network shown in Fig. 14. The network shown in Fig. 14 has the same configuration as the networks described above using Figs. 10-13 with respect to nodes A to I, and has a configuration in which node J is added as a node immediately below node A. Node A's shareholding ratio in node J is 5%.

[0105] In this case, similarly to the above example, the second update process results in nodes A to I being included in the first node group. Since node J is directly connected to node A included in the first node group, the sum of the shareholding ratios is calculated. Since node A is the only node in the second node group for node J, the sum of the shareholding ratios is 5%. Since the sum of the shareholding ratios does not exceed the first threshold, the controlled node identification unit 114 does not add node J to the set P of controlled nodes. In this way, even if there are nodes that have not been added to the set P of controlled nodes, the set P of controlled nodes will not change unless there is a node whose sum of the shareholding ratios of the second node group exceeds the first threshold.

[0106] If the controlled node has not changed even after the second update process is performed (step S205: No), the controlled node identification unit 114 ends the second update process. In this way, it is possible to appropriately end the second update process that is executed recursively. The controlled node identification unit 114 identifies the nodes included in the set P at this stage as controlled nodes that are effectively controlled by the controlling node.

[0107] Then, in step S206, the controlled node identification unit 114 judges whether the processing has been completed for all candidate nodes of the dominating node. For example, if multiple candidate nodes are found in step S201 and there are still candidate nodes that have not been processed in steps S202-S205 (step S206: No), the controlled node identification unit 114 returns to step S201 and selects an unprocessed candidate node as a new dominating node. The processing in steps S202-S205 after the new dominating node is selected is the same as in the above example.

[0108] When the processes of S202-S205 are completed for all the candidate nodes (step S206: Yes), the governed node identification unit 114 ends the governed node identification process shown in FIG.

[0109] 2.4 Impact calculation process Next, a description will be given of the calculation process of the influence degree shown in step S105 of Fig. 8. The influence degree calculation unit 115 of this embodiment calculates, as the influence degree, an index value based on the state of effective domination of other nodes by a dominating node.

[0110] For example, the influence calculation unit 115 sets the influence of the dominating node on the dominated node to the maximum value. In this way, it becomes possible to set an appropriate value as the influence for the node that is effectively dominated by the dominating node. In the example of Fig. 14, node I effectively dominates nodes A to H. Therefore, the influence calculation unit 115 sets the influence of node I on each of nodes A to H to the maximum value (for example, 1).

[0111] Furthermore, when the target node among the multiple nodes is not included in the first node group after the process of identifying the controlled node is completed, the influence calculation unit 115 may obtain the influence of the dominating node on the target node based on the investment ratio given to the edge directly connecting the target node and the node included in the first node group. In this way, it is possible to set the influence based on the shareholding ratio for the target node whose shares are acquired by the group (first node group) consisting of the dominating node and the node group effectively controlled by the dominating node. In the example of FIG. 14, node J is connected to node A included in the first node group, and the shareholding ratio of node A to node J is 5%. Therefore, the influence calculation unit 115 sets 0.05 (5%) corresponding to the shareholding ratio as the influence of node I on node J. In this way, a value according to the voting rights (shareholding ratio) that the dominating node can actually exercise becomes the influence, so that an index value whose meaning is easy to understand can be set.

[0112] For example, under the Japanese Companies Act, shareholders with a shareholding ratio of over 1% are granted the right to request proposals at the general shareholders' meeting of a company with a board of directors. Furthermore, shareholders with a shareholding ratio of over 3% are granted the right to request the convening of a general shareholders' meeting, the right to inspect and copy accounting books, etc. By using the influence degree of this embodiment, it becomes possible to easily determine whether or not the controlling node can exercise these powers over the target node.

[0113] The influence calculation unit 115 also identifies one or more edges that directly connect the target node to any node included in the first node group, and calculates the sum of the investment ratios assigned to the identified edge or edges as the influence of the dominating node on the target node.

[0114] For example, in FIG. 14, node J is connected only to node A, but consider a network in which an edge from node B toward node J, which is associated with an investment ratio of 10%, is added to the network in FIG. 14. In this case, there are two edges directly connected to node J, which is the target node: an edge from node A toward node J, and an edge from node B toward node J. The influence calculation unit 115 sets the sum of the shareholding ratios given to each edge, 0.05+0.10=0.15 (15%), as the influence of node I on node J. Node I can exercise voting rights equivalent to 5% of all shares of node J (stocks with voting rights in the narrow sense) through node A, and can exercise voting rights equivalent to 10% of all shares of node J through node B. In other words, when multiple nodes included in the first node group are the immediate upper nodes of the target node, it is possible to set a value according to the voting rights (shareholding ratio) that the dominant node can substantially exercise as the influence by using the sum of the shareholding ratios of each edge.

[0115] Furthermore, when the target node is not directly connected to any node included in the first node group, the influence calculation unit 115 sets the influence of the governing node on the target node to the minimum value. For example, consider a network in which a node K directly below node J is added to the network shown in FIG. 14. In this case, node K is only connected to node A via node J that is not included in the first node group, and is not directly connected to any node included in the first node group. In this case, the influence calculation unit 115 sets the influence of node I on node K to the minimum value (for example, 0). As described above, node I can only exercise a voting right equivalent to 5% of node J via node A, and cannot control the behavior of node J in the resolution at node K. In other words, node I cannot definitively exercise influence in the resolution at node K, so by setting the influence to the minimum value, it becomes possible to set a value that is in line with the actual situation.

[0116] 2.5 Output Processing In step S106 of FIG. 8, the display processing unit 116 may perform a process of displaying the dominating node and the dominated node in the entity network in a manner that allows them to be distinguished from other nodes. For example, as shown in FIG. 13 or FIG. 14, the display processing unit 116 displays the first node group in a first manner at the stage where the process of identifying the dominated node (step S104) is completed, and displays the nodes other than the first node group in a second manner different from the first manner on the display unit 240 of the terminal device 200. In this way, it is possible to present to the user in an easy-to-understand manner what route is taken by the dominating node to effectively dominate other nodes. Note that the first and second manners are display manners in which the colors of the nodes are different, for example, but are not limited to this, and it is sufficient that the first manner has higher visibility than the second manner. For example, the size of the nodes in the first manner may be larger than that of the second manner. Alternatively, the display processing unit 116 may perform a process of displaying only the nodes in the first manner on the default screen, and displaying the nodes in the second manner when some user operation is received. In addition, various modifications of the specific display mode are possible. Furthermore, the display processing unit 116 may display the display mode of an edge whose both end nodes are included in the first node group in a mode with higher visibility than other edges (edges whose at least one end node is a node other than the first node group).

[0117] Furthermore, the display processing unit 116 may perform processing to display the value of the influence degree by the dominating node for nodes other than the first node group.

[0118] The display processing unit 116 may switch between a screen displaying the degree of influence according to this embodiment and a screen displaying other degrees of influence such as the Power Index. In addition, various modifications are possible for the specific screen displayed by the display processing unit 116.

[0119] 2.6 Matrix operations The process of identifying a controlled node and the process of calculating the influence degree described above may be performed by calculations using matrices and vectors. Specific examples will be described below.

[0120] Fig. 15A is an example of a network used for explanation. The network here is, for example, a sub-network extracted in step S103 of Fig. 8. Here, a network including nodes 1-7 corresponding to entities 1-7 is considered. The connection relationships of the nodes and the shareholding ratios assigned to the edges are as shown in the figure.

[0121] The controlled node specifying unit 114 sets a connectivity matrix that represents the connectivity relationships of a plurality of nodes included in the network. For example, when the first to Nth nodes (N is an integer of 2 or more) are included in a subnetwork that is directly or indirectly connected to the controlling node in the entity network, the controlled node specifying unit 114 obtains an N-row, N-column connectivity matrix in which the value of the component in the i-th row and the i-th column (i is an integer of 1 to N) is 1, and the value of the component in the i-th row and the j-th column (j is an integer of 1 to N and different from i) represents the investment ratio of the i-th node to the j-th node.

[0122] Fig. 15B is a diagram showing an example of a connectivity matrix for the sub-network of Fig. 15A. As shown in Fig. 15B, row elements of the connectivity matrix represent the dominating nodes, and column elements represent the dominated nodes. First, the dominated node identification unit 114 sets the values ​​of the diagonal elements of the connectivity matrix to 1.

[0123] The controlled node specification unit 114 also determines the values ​​of the other components based on the connection relationships between the nodes and the shareholding ratios assigned to the edges. For example, in the sub-network of FIG. 15A, the shareholding ratio of node 1 to node 3 is 0.6. Therefore, the value of the component in row 1, column 3 of the connection matrix is ​​set to 0.6. Similarly, the shareholding ratio of node 1 to node 4 is 0.9. Therefore, the value of the component in row 1, column 4 of the connection matrix is ​​set to 0.9. The same applies to the following, and values ​​representing the shareholding ratios are set for the components in row 2, column 4, row 3, column 5, row 4, column 5, column 6, and column 6 of the connection matrix based on the connection relationships of the sub-network shown in FIG. 15A. As for the other elements, the values ​​are set to 0 because the i-th node does not have a relationship of contributing to the j-th node.

[0124] 16 is a flowchart for explaining the process of identifying a governed node by a matrix operation and the process of calculating the influence degree. It is assumed that the connection matrix has been obtained before this process.

[0125] In step S301, the controlled node identification unit 114 selects node i as a dominating node. The process of step S301 is the same as the process of step S201 in FIG. 9. That is, the controlled node identification unit 114 selects, as a candidate node for the dominating node, a node other than the target node included in the sub-network and which dominates a node other than itself with a shareholding ratio exceeding a first threshold. Then, the controlled node identification unit 114 sequentially selects one of the candidate nodes as a dominating node. In the example of FIG. 15A, since node 1 and node 5 are candidate nodes for the dominating node, the controlled node identification unit 114 sequentially selects 1 and 5 as i. Here, an example in which i=1 is first considered.

[0126] In step S302, the dominated node identification unit 114 converts a dominating vector v, which is a vector representing a dominating relationship by a dominating node (node ​​i), into a vector e i Here, the vector e iis an N-dimensional row vector in which only the value of the i-th component is 1 and the values ​​of the other components are set to 0. When i=1, as shown in FIG. 17A, the dominating vector v is set to e1, and e1 is a row vector in which the first component is 1 and the other components are 0. The dominated node identification unit 114 performs a process of finding the dominated node by multiplying the dominating vector and the connection matrix. In this way, it becomes possible to realize the process of finding the dominated node by an operation using a matrix and a vector.

[0127] For example, the dominated node identification unit 114 performs a vector update process in which, for each component of the N-dimensional vector, which is the product of the dominating vector and the connection matrix, the values ​​of components whose values ​​are greater than a first threshold are updated to a first value, and the values ​​of components whose values ​​are equal to or less than the first threshold are updated to a second value smaller than the first value, and updates the dominating vector with the processed N-dimensional vector. In this way, it becomes possible to realize the dominance propagation process described above with reference to Figures 10 to 13 in the form of updating the dominating vector.

[0128] Specifically, in step S303, the dominated node identification unit 114 multiplies the dominating vector v by the connection matrix C from the right, and sets the row vector resulting from the multiplication as v'. As shown in Fig. 17A, in the first vector update process, since the dominating vector is e1, the multiplication result v' becomes v'=(1,0,0.6,0.9,0,0,0).

[0129] In step S304, the controlled node identification unit 114 applies a first function F to each component of the vector v', and defines the row vector resulting from the application as v''. The first function F here is a function that satisfies the following formula (1). θ in the following formula (1) is a value corresponding to the first threshold value described above. In other words, the first function F is a function that updates the values ​​of components greater than the first threshold value to a first value (e.g., 1), and updates the values ​​of components less than or equal to the first threshold value to a second value (e.g., 0).

[0130]

number

[0131] As shown in FIG. 17A, a first function F(F 0.5 ) gives us v'' = (1,0,1,1,0,0,0).

[0132] In step S305, the dominated node identification unit 114 judges whether the dominating vector v and the vector v'' are equal. This process corresponds to step S205 in FIG. 9, and corresponds to the judgment of whether the dominance propagation is continuing or not. If the dominating vector v and the vector v'' are not equal (step S305: No), in step S306, the dominated node identification unit 114 updates the dominating vector v with the vector v'', and then returns to step S303 to execute the vector update process again. Hereinafter, the xth vector update process will be referred to as the xth step.

[0133] As explained above, as a result of the first step, the dominance vector v is updated to v = (1, 0, 1, 1, 0, 0, 0). This indicates that the dominance of node 1 has propagated to nodes 3 and 4, which correspond to the third and fourth components of the dominance vector v, as shown in Figure 17B.

[0134] In the second step, as shown in FIG. 18A, the connection matrix is ​​multiplied by the dominating vector v=(1,0,1,1,0,0,0) updated in the first step (step S303). The multiplication result v' is v'=(1,0,1.6,1.9,0.6,0,0). Furthermore, by applying the first function F to the vector v', v''=(1,0,1,1,1,0,0) (step S304). In this case as well, since the dominating vector v and the vector v'' are not equal (step S305: No), in step S306, the dominated node identification unit 114 updates the dominating vector v by the vector v'', and then returns to step S303 to execute the vector update process again.

[0135] As a result of the second step, the dominance vector v is updated to v = (1, 0, 1, 1, 1, 0, 0), which indicates that the dominance of node 1 has propagated up to node 5, which corresponds to the fifth component of the dominance vector v, as shown in Figure 18B.

[0136] In the third step, as shown in FIG. 19A, v=(1,0,1,1,1,0,0) is multiplied to the connection matrix (step S303). The multiplication result v' is v'=(1,0,1.6,1.9,1.6,0.6,0). Furthermore, by applying the first function F to the vector v', v''=(1,0,1,1,1,1,0) (step S304). In this case as well, since the dominating vector v and the vector v'' are not equal (step S305: No), in step S306, the dominated node identification unit 114 updates the dominating vector v by the vector v'', and then returns to step S303 to execute the vector update process again.

[0137] As a result of the third step, the dominance vector v is updated to v = (1, 0, 1, 1, 1, 1, 0), which indicates that the dominance of node 1 has propagated up to node 6, which corresponds to the sixth component of the dominance vector v, as shown in Figure 19B.

[0138] In the fourth step, as shown in FIG. 20A, v=(1,0,1,1,1,1,0) is multiplied to the connection matrix (step S303). The multiplication result v' becomes v'=(1,0,1.6,1.9,1.6,1.6,0.3). Furthermore, by applying the first function F to the vector v', v''=(1,0,1,1,1,1,0) (step S304). In this case, the dominating vector v and the vector v'' become equal (step S305: Yes), so the dominated node identification unit 114 ends the vector update process.

[0139] As a result of the fourth step, the update process of the dominating vector v ends with v = (1, 0, 1, 1, 1, 1, 0). This indicates that the dominance of node 1 has propagated up to node 6, which corresponds to the sixth component of the dominating vector v, as shown in Figure 20B, and no further propagation has been performed.

[0140] The dominated node identification unit 114 identifies, as a dominated node, a node corresponding to a component whose value is a first value (for example, 1) in the dominating vector after the vector update process is completed. In this way, it becomes possible to efficiently find the dominated node that is effectively dominated by the dominating node by a matrix operation.

[0141] Furthermore, for each component of the N-dimensional vector, which is the product of the dominating vector and the connection matrix after the vector update process is completed, the influence calculation unit 115 performs a process of updating the value of the component whose value is greater than the first threshold to 1 and maintaining the value of the component whose value is equal to or less than the first threshold, and obtains the value of each component of the N-dimensional vector after the process as the influence of the dominating node on each node of the multiple nodes. In this way, it becomes possible to obtain the influence that takes into account the effective dominance relationship by matrix calculation.

[0142] Specifically, after the vector update process is completed, in step S307, influence calculation unit 115 obtains a row vector which is the product of dominating vector v and the connection matrix, and applies a second function G to each component of the row vector. Here, the second function G is a function that satisfies the following formula (2). θ in the following formula (2) is a value corresponding to the first threshold value described above. In other words, the second function G is a function that updates the values ​​of components whose values ​​are greater than the first threshold value to a first value (e.g., 1), and maintains the values ​​of components whose values ​​are equal to or less than the first threshold value as they are.

[0143]

number

[0144] As shown in Figure 21A, the dominant vector v = (1, 0, 1, 1, 1, 1, 0) at the end of the vector update process is multiplied by the incidence matrix. The row vector resulting from the multiplication is (1, 0, 1.6, 1.9, 1.6, 1.6, 0.3). Furthermore, the result o(i) of applying the second function G to this row vector is o(i) = (1, 0, 1, 1, 1, 0.3).

[0145] Here, each component of the vector o(i) represents the degree of influence of the node i, which is a dominating node, on other nodes. For example, since the values ​​of the third to sixth components of o(i) are 1, the degree of influence of the node 1 on the nodes 3 to 6 is 1 (maximum value), and it is understood that the nodes 3 to 6 are dominated nodes. Furthermore, since the value of the seventh component of o(i) is 0.3, the degree of influence of the node 1 on the node 7 is 0.3. This reflects the connection relationship in the area surrounded by the dashed line in FIG. 21B. That is, since the node immediately above the node 7 is the sixth node, which is a dominated node, there is a possibility that the node 1 will exercise voting rights equivalent to 30% through the sixth node. According to the method of this embodiment, it is possible to obtain an influence having a value that takes into account the dominance relationship as a result of the action of the second function G.

[0146] In step S308, the controlled node identification unit 114 determines whether or not all candidate nodes have been selected as dominating nodes. As described above, the candidate nodes here are two, node 1 and node 5, and node 5 is unprocessed. If an unprocessed candidate node remains (step S308: No), in step S309, the controlled node identification unit 114 updates the value of i to the value of the unprocessed candidate node. In this case, i is updated to 5. After that, the process returns to step S301, and the above-described process is executed for the new dominating node.

[0147] 22A to 24B are diagrams for explaining the flow of processing when node 5 is the dominant node. In this case, the initial value of the dominant vector v is a vector e5 whose fifth component has a value of 1 and whose other components have values ​​of 0. The connection matrix is ​​the same as in the above example.

[0148] In the first step, as shown in FIG. 22A, e5=(0,0,0,0,1,0,0) is multiplied to the connection matrix (step S303). The multiplication result v' is v'=(0,0,0,0,1,0.6,0). Furthermore, by applying the first function F to the vector v', v''=(0,0,0,0,1,1,0) (step S304). Since the dominating vector v(e5) and the vector v'' are not equal (step S305: No), in step S306, the dominated node identification unit 114 updates the dominating vector v by the vector v'', and then returns to step S303 to execute the vector update process again.

[0149] As a result of the second step, the dominance vector v is updated to v = (0, 0, 0, 0, 1, 1, 0), which indicates that the dominance of node 5 has propagated up to node 6, which corresponds to the sixth component of the dominance vector v, as shown in Figure 22B.

[0150] In the second step, as shown in FIG. 23A, v=(0,0,0,0,1,1,0) is multiplied to the connection matrix (step S303). The result of the multiplication, v', becomes v'=(0,0,0,0,1,1.6,0.3). Furthermore, by applying the first function F to the vector v', v''=(0,0,0,0,1,1,0) (step S304). Since the dominating vector v and the vector v'' become equal (step S305: Yes), the dominated node identification unit 114 ends the vector update process.

[0151] As a result of the second step, the update process ends with the dominating vector v in the state of v = (0, 0, 0, 0, 1, 1, 0). This indicates that the dominance of node 5 has propagated up to node 6, which corresponds to the sixth component of the dominating vector v, as shown in Figure 23B, and no further propagation has been performed.

[0152] After the vector update process is completed, in step S307, as shown in FIG. 24A, the dominant vector v=(0,0,0,0,1,1,0) at the end of the vector update process is multiplied by the incidence matrix. The row vector resulting from the multiplication is (0,0,0,0,1,1.6,0.3). Furthermore, the result o(i) of applying the second function G to this row vector is o(i)=(0,0,0,0,1,1,0.3).

[0153] Because the value of the sixth component of o(i) is 1, the influence of node 5 on node 6 is 1 (maximum value), and it is clear that node 6 is a dominated node. In addition, because the value of the seventh component of o(i) is 0.3, the influence of node 5 on node 7 is 0.3. This reflects the connection relationship in the area surrounded by the dashed line in FIG. 24B.

[0154] As a result, the processing for all the candidate nodes is completed (step S308: Yes), and the matrix calculation shown in FIG. 16 is completed.

[0155] In this example, it is known at the stage when the process for node 1 has been performed that node 5 is a dominated node that is effectively dominated by node 1. Therefore, the dominance relationship (FIG. 23B) and the influence (FIG. 24B) of node 5 are included in the process result for node 1, so the process for node 5 may be omitted.

[0156] 2.7 Examples 25 and 26 are diagrams illustrating processing results in a case where node X is a dominant node and node Y is a target node in a given network. In the example shown in FIG. 25, when the index described above in this embodiment is used as the degree of influence of node X on node Y, the value is 0.49. In other words, node X does not effectively dominate node Y. On the other hand, when the Power Index is used as the degree of influence, the value of the degree of influence of node X on node Y is 0.526. In other words, in the network shown in FIG. 25, the value of the Power Index may be excessively large, but the degree of influence in this embodiment can be set to a value that appropriately takes into account the dominance relationship.

[0157] In the example shown in FIG. 26, when the index described above in this embodiment is used as the degree of influence of node X on node Y, the value is 1. In other words, node X effectively dominates node Y. On the other hand, when the Power Index is used as the degree of influence, the value of the degree of influence of node X on node Y is 0.428. In other words, in the network shown in FIG. 26, the value of the Power Index may be excessively small, but the degree of influence in this embodiment can be a value that appropriately takes into account the dominance relationship. As described above, the method of this embodiment makes it possible to accurately determine the degree of influence that represents the dominance relationship.

[0158] Although the present embodiment has been described in detail as above, it will be easily understood by those skilled in the art that many modifications are possible that do not substantially deviate from the novel matters and effects of the present embodiment. Therefore, all such modifications are intended to be included in the scope of the present disclosure. For example, a term described at least once in the specification or drawings together with a different term having a broader meaning or synonymy can be replaced with that different term anywhere in the specification or drawings. In addition, all combinations of the present embodiment and modifications are also included in the scope of the present disclosure. In addition, the configurations and operations of the server system, terminal device, information processing system, etc. are not limited to those described in the present embodiment, and various modifications are possible. [Explanation of symbols]

[0159] 10 information processing system, 100 server system, 110 processing unit, 111 entity network acquisition unit, 112 target node acquisition unit, 113 subnetwork extraction unit, 114 governed node identification unit, 115 influence degree calculation unit, 116 display processing unit, 120 storage unit, 121 entity network, 130 communication unit, 200, 200-1, 200-2 terminal device, 210 processing unit, 220 storage unit, 230 communication unit, 240 display unit, 250 operation unit

Claims

1. an entity network acquisition unit that acquires an entity network that represents mutual investment relationships between a plurality of nodes corresponding to a plurality of entities by connecting a lower node that is invested in and a higher node that is investing in by an edge to which an investment ratio is assigned; A controlled node identification unit that identifies a controlled node that is effectively controlled by a dominating node among the plurality of nodes based on the entity network; Including, The controlled node identification unit, Perform an initialization process to initialize the ruled node with an empty set; performing a first update process after the initialization process, in which a node among the plurality of nodes that is directly connected to the dominating node and has an investment ratio assigned to the edge between the dominating node and the dominating node that is greater than a first threshold is added to the dominated node; An information processing system that identifies the controlled node by repeatedly executing a second update process in which, when the dominating node and the already identified controlled nodes are considered to be a first node group after the first update process, nodes among the multiple nodes that are directly connected to a second node group, which is one or more nodes included in the first node group, and whose sum of the contribution ratios assigned to the edges between each node of the second node group is greater than the first threshold, are added to the controlled node.

2. In claim 1, The controlled node identification unit, An information processing system that terminates the second update process if the controlled node does not change even after the second update process is performed.

3. In claim 1 or 2, an influence calculation unit for calculating an influence of the dominant node on other nodes; The influence degree calculation unit An information processing system that, if a target node among the multiple nodes is not included in the first node group after the process of identifying the controlled node is completed, determines the degree of influence of the controlling node on the target node based on the investment ratio assigned to the edge directly connecting the target node to a node included in the first node group.

4. In claim 3, The influence degree calculation unit An information processing system that sets the degree of influence of the dominating node on the dominated node to a maximum value.

5. In claim 3, The influence degree calculation unit An information processing system that identifies one or more edges that directly connect the target node to any node included in the first node group, and calculates the sum of the investment ratios assigned to the identified one or more edges as the influence of the dominant node on the target node.

6. In claim 3, The influence degree calculation unit An information processing system that sets the influence of the dominant node on the target node to a minimum value if the target node is not directly connected to any node included in the first node group.

7. an entity network acquisition unit that acquires an entity network that represents mutual investment relationships between a plurality of nodes corresponding to a plurality of entities by connecting a lower node that is invested in and a higher node that is investing in by an edge to which an investment ratio is assigned; a subnetwork extraction unit that extracts a subnetwork consisting of the upper nodes directly or indirectly connected to the target node when any of the plurality of nodes is determined as the target node; A controlled node identification unit that identifies a controlled node that is effectively controlled by a dominating node among the plurality of nodes based on the entity network; Including, The controlled node identification unit, Selecting, as the dominant node, a node whose investment ratio with respect to at least one other node among the nodes other than the target node included in the sub-network is greater than a first threshold; When the dominating node and the already specified dominated node are defined as a first node group, An information processing system that identifies the controlled nodes by performing an update process that adds to the controlled nodes those nodes among the plurality of nodes that are directly connected to a second node group, which is one or more nodes included in the first node group, and whose sum of the contribution ratios assigned to the edges between each node of the second node group is greater than the first threshold value.

8. In claim 1 or 2, The information processing system further includes a display processing unit that displays the dominating node and the controlled node in the entity network in a manner that makes them distinguishable from other nodes.

9. an entity network acquisition unit that acquires an entity network that represents mutual investment relationships between a plurality of nodes corresponding to a plurality of entities by connecting a lower node that is invested in and a higher node that is investing in by an edge to which an investment ratio is assigned; A controlled node identification unit that identifies a controlled node that is effectively controlled by a dominating node among the plurality of nodes based on the entity network; Including, The controlled node identification unit, When the dominating node and the already specified dominated node are defined as a first node group, Identifying the controlled node by performing an update process to add to the controlled node, a node among the plurality of nodes that is directly connected to a second node group that is one or more nodes included in the first node group and for which the sum of the investment ratios assigned to the edges between the nodes of the second node group is greater than a first threshold value; The controlled node identification unit, In the case where a subnetwork directly or indirectly connected to the dominant node in the entity network includes first to Nth nodes (N is an integer of 2 or more), a connection matrix of N rows and N columns, in which the value of the component in row i (i is an integer between 1 and N) and the value of the component in row j (j is an integer between 1 and N and different from i) are 1 and represent the investment ratio of the i-th node to the j-th node; A dominating vector, which is an N-dimensional vector whose components corresponding to the dominating node are 1 and whose components corresponding to other nodes are 0, is obtained; An information processing system that determines the dominated nodes by multiplying the dominating vector and the connection matrix.

10. In claim 9, The controlled node identification unit, For each component of an N-dimensional vector which is the product of the dominating vector and the connection matrix, a process is performed in which the values ​​of components which are greater than the first threshold value are updated to a first value, and the values ​​of components which are equal to or less than the first threshold value are updated to a second value which is smaller than the first value, and a vector update process is performed in which the dominating vector is updated by the processed N-dimensional vector; An information processing system that identifies, as the dominated node, a node corresponding to a component whose value is the first value in the dominating vector after the vector update process is completed.

11. In claim 10, The information processing system further includes an influence calculation unit that performs a process of updating the values ​​of components of an N-dimensional vector, which is the product of the dominating vector and the connection matrix after the vector update process is completed, to 1 if the values ​​of components are greater than the first threshold value, and maintaining the values ​​of components whose values ​​are equal to or less than the first threshold value, and calculates the values ​​of each component of the N-dimensional vector after the process as the influence of the dominating node on each node of the multiple nodes.

12. An information processing device, Obtaining an entity network that represents mutual investment relationships among a plurality of nodes corresponding to a plurality of entities by connecting a lower node that is invested in and a higher node that is investing in by an edge to which an investment ratio is assigned; Identifying a dominated node that is a node that is effectively dominated by a dominant node among the plurality of nodes based on the entity network; In identifying the controlled node, Perform an initialization process to initialize the ruled node with an empty set; performing a first update process after the initialization process, in which a node among the plurality of nodes that is directly connected to the dominating node and has an investment ratio assigned to the edge between the dominating node and the dominating node that is greater than a first threshold is added to the dominated node; After the first update process, when the dominating node and the already identified controlled nodes are regarded as a first node group, the controlled nodes are identified by repeatedly executing a second update process in which, among the plurality of nodes, a node that is directly connected to a second node group which is one or more nodes included in the first node group and has a sum of the investment ratios assigned to the edges between the nodes of the second node group that is greater than the first threshold value is added to the controlled nodes. An information processing method that performs processing.

13. An information processing device, Obtaining an entity network that represents mutual investment relationships among a plurality of nodes corresponding to a plurality of entities by connecting a lower node that is invested in and a higher node that is investing in by an edge to which an investment ratio is assigned; When any one of the plurality of nodes is determined as a target node, a subnetwork composed of the upper nodes directly or indirectly connected to the target node is extracted; Identifying a dominated node that is a node that is effectively dominated by a dominant node among the plurality of nodes based on the entity network; In identifying the controlled node, Selecting, as the dominant node, a node whose investment ratio with respect to at least one other node among the nodes other than the target node included in the sub-network is greater than a first threshold; When the dominating node and the already identified controlled nodes are regarded as a first node group, the controlled nodes are identified by performing an update process of adding to the controlled nodes, among the plurality of nodes, nodes that are directly connected to a second node group which is one or more nodes included in the first node group, and for which the sum of the investment ratios assigned to the edges between the nodes of the second node group is greater than the first threshold value; An information processing method that performs processing.

14. An information processing device, Obtaining an entity network that represents mutual investment relationships among a plurality of nodes corresponding to a plurality of entities by connecting a lower node that is invested in and a higher node that is investing in by an edge to which an investment ratio is assigned; Identifying a dominated node that is a node that is effectively dominated by a dominant node among the plurality of nodes based on the entity network; In identifying the controlled node, When the dominating node and the already identified controlled nodes are regarded as a first node group, an update process is performed to add to the controlled nodes, among the plurality of nodes, nodes that are directly connected to a second node group that is one or more nodes included in the first node group, and the sum of the investment ratios assigned to the edges between the nodes of the second node group is greater than a first threshold value, thereby identifying the controlled nodes; In the case where a subnetwork directly or indirectly connected to the dominant node in the entity network includes first to Nth nodes (N is an integer of 2 or more), a connection matrix of N rows and N columns, in which the value of the component in row i (i is an integer between 1 and N) and the value of the component in row j (j is an integer between 1 and N and different from i) are 1 and represent the investment ratio of the i-th node to the j-th node; A dominating vector, which is an N-dimensional vector whose components corresponding to the dominating node are 1 and whose components corresponding to other nodes are 0, is obtained; The dominated node is obtained by multiplying the dominating vector and the connection matrix. An information processing method that performs processing.

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