Similarity calculation device and similarity calculation system

Abstract

The similarity calculation device includes a synthesis unit that synthesizes a first and second information group to generate a synthesized information group, and a similarity calculation unit that calculates a similarity between a comparison source node and a comparison target node in the synthesized information group, the first and second information groups each including a node and attribute information indicating an attribute of the node, the synthesis unit synthesizes the attribute information in the first and second information groups by matching identical nodes in the first and second information groups, and the similarity calculation unit calculates the similarity by comparing the attribute information associated with the comparison source node and the attribute information associated with the comparison target node.

Description

[Technical field]

[0001] The technology disclosed in this specification relates to a technology for calculating similarity between nodes. [Background technology]

[0002] In the development of equipment or facilities such as plants, control logic diagrams, which describe operation plans that define the operating specifications of the equipment using flow charts and logical operators, are widely used. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2017 / 158926 Summary of the Invention [Problem to be solved by the invention]

[0004] Maintenance (repair, inspection, servicing, etc.) of equipment or facilities in a plant or the like is carried out, for example, taking into consideration a deterioration tendency estimated based on an operation plan for the equipment.

[0005] However, since the deterioration tendency of the above-mentioned devices or facilities varies depending not only on the attribute information of the devices or facilities themselves (e.g., the number of years since they started being used, the model number, or specifications) but also on the attribute information of the facility to which the devices or facilities belong, it may not be possible to carry out effective maintenance.

[0006] The technology disclosed in this specification has been made in consideration of the problems described above, and is a technology for performing effective maintenance of equipment. [Means for solving the problem]

[0007] A similarity calculation device according to a first aspect of the technology disclosed in the present specification includes a synthesis unit for synthesizing a first information group and a second information group different from the first information group to generate at least one synthesized information group, and a similarity calculation unit for calculating a similarity between a comparison source node and a comparison target node in the synthesized information group, wherein the first information group and the second information group each include a node and attribute information indicating an attribute of the node, the synthesis unit synthesizes the attribute information in the first information group and the second information group by matching identical nodes in the first information group and the second information group, and the similarity calculation unit calculates the similarity by comparing the attribute information associated with the comparison source node and the attribute information associated with the comparison target node. the synthesis unit generates a first synthesis information group and a second synthesis information group, which are the synthesis information groups; and the similarity calculation unit calculates the similarity by comparing the attribute information associated with the comparison source node in the first synthesis information group with the attribute information associated with the attribute of the comparison destination node in the second synthesis information group. . Effect of the Invention

[0008] According to at least the first aspect of the technology disclosed in the present specification, the accuracy of the calculation of the similarity between nodes can be improved by calculating the similarity between nodes using the combined attribute information. In this way, information that can be used for maintenance, etc. can be obtained from the attribute information associated with the comparison target node.

[0009] Furthermore, objects, features, aspects and advantages associated with the technology disclosed herein will become more apparent from the detailed description set forth below and the accompanying drawings. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram conceptually illustrating an example of the configuration of a similarity calculation system according to an embodiment. [Diagram 2] FIG. 11 is a diagram illustrating an example of heterogeneous system correspondence information. [Diagram 3] FIG. 11 is a diagram illustrating an example of heterogeneous system correspondence information. [Figure 4] 13 is a diagram showing an example of merging of attribute information in merged graph data; FIG. [Diagram 5] FIG. 13 is a diagram illustrating an example of calculating similarity between nodes in two combined graph data. [Figure 6] FIG. 13 is a diagram illustrating an example of calculating a similarity between related nodes. [Figure 7] 13A and 13B are diagrams illustrating examples of similarity lists of respective comparison target nodes with respect to a comparison source node for which similarity has been calculated. [Figure 8] 2 is a diagram illustrating a schematic example of a hardware configuration when the similarity calculation device illustrated in FIG. 1 is actually operated. FIG. [Figure 9] 2 is a diagram illustrating a schematic example of a hardware configuration when the similarity calculation device illustrated in FIG. 1 is actually operated. FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, the embodiments will be described with reference to the accompanying drawings. In the following embodiments, detailed features are shown for the purpose of explaining the technology, but they are merely examples and are not necessarily essential features for enabling the embodiments to be implemented.

[0012] The drawings are schematic, and for the sake of convenience, configurations may be omitted or simplified as appropriate. The size and positional relationship of the configurations shown in different drawings are not necessarily described accurately, and may be changed as appropriate. Hatching may be used in drawings such as plan views that are not cross-sectional views to facilitate understanding of the contents of the embodiments.

[0013] In the following description, the same components are denoted by the same reference numerals, and their names and functions are also the same. Therefore, detailed descriptions thereof may be omitted to avoid duplication.

[0014] Furthermore, in the description in this specification, when a certain component is described as "comprising," "including," or "having," unless otherwise specified, this is not an exclusive expression that excludes the presence of other components.

[0015] Furthermore, even if ordinal numbers such as "first" or "second" are used in the description of this specification, these terms are used for convenience to facilitate understanding of the contents of the embodiments, and the contents of the embodiments are not limited to the orders that may result from these ordinal numbers.

[0016] <Embodiment Mode> A similarity calculation device and a similarity calculation system according to this embodiment will be described below.

[0017] <Configuration of Similarity Calculation Device> FIG. 1 is a diagram conceptually showing an example of the configuration of a similarity calculation system according to this embodiment.

[0018] 1, the similarity calculation system 1 includes a similarity calculation device 10 that calculates the similarity between nodes. The similarity calculation system 1 further includes an input device 20 that performs input to the similarity calculation device 10, and a display device 30 that displays output from the similarity calculation device 10. The similarity calculation system 1 can further include a storage device 40 that stores data referenced by the similarity calculation device 10, and an attribute information storage device 50.

[0019] The similarity calculation device 10 includes an attribute information synthesis unit 12, a similarity calculation unit 14, a calculation parameter setting unit 17, and a similarity list display unit 18.

[0020] The attribute information synthesis unit 12 generates synthesized graph data by associating identical nodes in multiple graph data, and synthesizes attribute information associated with the nodes. Here, the attribute information is information belonging to a node (or edge) in the graph data. A node describes an object, such as equipment, an event, or a person. If the node is equipment, the information indicates the manufacturer, specifications, measurement data, output, output method, operation method, health, power consumption, etc., and if the node is a place, the information indicates weather conditions including temperature, etc. The attribute information synthesis unit 12 includes an identical node determination unit 13, which determines the identity between nodes in multiple graph data based on the heterogeneous system correspondence information 40A described later.

[0021] The similarity calculation unit 14 calculates the similarity between nodes based on their attribute information. The similarity calculation unit 14 includes an attribute information similarity calculation unit 15, which compares attribute information between target nodes. The similarity calculation unit 14 also includes an associated node extraction unit 16, which extracts associated nodes to be taken into consideration in the comparison of target nodes.

[0022] The calculation parameter setting unit 17 sets calculation parameters required for calculating the similarity between nodes in the similarity calculation unit 14. The calculation parameters may be set in advance or may be input from the input device 20 by a user or the like.

[0023] The similarity list display unit 18 displays a similarity list, which is a list showing the similarities between nodes. The similarity list may be further displayed on the display device 30.

[0024] The storage device 40 stores heterogeneous system correspondence information 40A. The attribute information storage device 50 stores attribute information of a plurality of system types (system type A attribute information 50A, system type B attribute information 50B, system type C attribute information 50C, and system type C attribute information 50D). The number of system type attribute information stored is not limited to the number shown in FIG.

[0025] In this embodiment, attribute information belongs to a node (or edge) in the graph data. The graph data is composed of nodes and edges indicating relationships between the nodes, and attribute information (properties) belongs to the nodes and edges. The graph data is stored in, for example, a graph database. Note that the attribute information is not limited to attribute information belonging to the nodes and edges in the graph data, and may be attribute information belonging to information groups (databases) in other formats.

[0026] <About attribute information synthesis> 2 and 3 are diagrams showing an example of the heterogeneous system correspondence information 40 A. As shown in the examples of Fig. 2 and Fig. 3, in the heterogeneous system correspondence information 40 A, definitions (such as names) of the same node in different systems are described in association with each other.

[0027] In the example of FIG. 2, "Facility A" in the inspection support system corresponds to the same object (node) as "Facility 1" in the monitoring and control system. Similarly, "Equipment A" in the inspection support system corresponds to the same object (node) as "Equipment 1" in the monitoring and control system. Similarly, "Equipment C" in the inspection support system corresponds to the same object (node) as "Equipment 2" in the monitoring and control system.

[0028] In the example of Figure 3, "Hyogo" in the weather information system includes "A Treatment Plant" in the inspection support system (the relationship is include). Similarly, "Osaka" in the weather information system includes "B Building" in the inspection support system (the relationship is include).

[0029] The same node determination unit 13 in Fig. 1 determines the identity between nodes in multiple graph data based on the heterogeneous system correspondence information 40A. Then, for nodes determined to be the same as shown in Fig. 2, the attribute information synthesis unit 12 overlaps the nodes on the graph data to generate synthesized graph data and adds up the attribute information. Also, for nodes determined to have a relationship as shown in Fig. 3, the nodes are connected by edges to generate synthesized graph data.

[0030] Fig. 4 is a diagram showing an example of merging of attribute information in the merged graph data. The merged graph data shown in Fig. 4 is generated by overlapping nodes determined to be the same by the same node determination unit 13 on the graph data, and is generated by merging system type A attribute information 50A, system type B attribute information 50B, system type C attribute information 50C, and system type C attribute information 50D stored in the attribute information storage device 50. The attribute information belonging to the same node in each of the multiple graph data is added together as the attribute information to which the node belongs in the merged graph data.

[0031] <About similarity calculation> Fig. 5 is a diagram showing an example of calculating the similarity between nodes in two combined graph data. In Fig. 5, each of the compared nodes is a node in the combined graph data, but only one of the compared nodes may be a node in the combined graph data, and the other may be a node in graph data that is not combined.

[0032] 5, a node 100 representing device A is compared with a node 102 representing device B to calculate the similarity between them. Node 100 and node 102 represent different devices and are not the same node.

[0033] In order to calculate the similarity between the node 100 (comparison source node) and the node 102 (comparison target node), the attribute information similarity calculation unit 15 compares the attribute information belonging to both nodes.

[0034] For example, if the node is a device, the similarity can be determined as 1 if the character strings of the information shown as the manufacturer, output, and output method are the same, 0 if they are different or there is no corresponding information, and 1 if the numerical values ​​of the information shown are the same, and 0 if they are different or there is no corresponding information, and the value obtained by adding these numerical values ​​can be determined as the similarity. Note that instead of 1 or 0, the similarity of the character strings or numerical values ​​may be calculated as a value between 0 and 1 and taken into account in the above similarity.

[0035] Also, for example, the commonality of the types of nodes connected via edges between the comparison source node and the comparison target node may be considered as attribute information. The similarity may be calculated by adding up the values, 1 if the types of directly connected nodes are common, 0.5 if the types of nodes indirectly connected via one node are common, and 0.25 if the types of nodes indirectly connected via two nodes are common.

[0036] As described above, the attribute information similarity calculation unit 15 calculates the similarity of the attribute information of the node 100 and the node 102, whereby the similarity between the node 100 and the node 102 can be calculated. Here, since at least one of the node 100 and the node 102 is a node in the combined graph data and the attribute information to which it belongs is combined, the accuracy of the similarity calculation is improved. By calculating the similarity between the nodes with high accuracy, it is possible to perform effective maintenance (repair, inspection, servicing, etc.) that takes into account, for example, a deterioration tendency, based on the attribute information of similar nodes.

[0037] In order to accurately calculate the similarity between node 100 (comparison source node) and node 102 (comparison target node), the attribute information similarity calculation unit 15 can further compare attribute information belonging to related nodes associated with the comparison source node (or comparison target node).

[0038] The associated node extraction unit extracts nodes connected to node 100 (comparison source node) and node 102 (comparison target node) via edges as associated nodes. Then, the attribute information similarity calculation unit 15 compares the attribute information of the extracted associated nodes to calculate an associated similarity.

[0039] Here, the calculation parameter setting unit 17 can set weighting (parameters) when considering the association similarity in the similarity between the node 100 (comparison source node) and the node 102 (comparison target node). The weighting may be set by a user or the like for a specific node (or a specific associated node) and its attribute information, or the weighting may be set so as to decrease according to the distance from the comparison source node or the comparison target node (the number of edges and nodes passed through). The specific associated node may be specified, for example, by the route from the comparison source node or the comparison target node (the edges passed through and the attribute information of the node), or may be specified by the type of node. Furthermore, the weighting may be set for each type of node and each purpose.

[0040] Fig. 6 is a diagram showing an example of calculating the similarity of related nodes. In Fig. 6, a node 100 (a comparison source node) and a node 102 (a comparison target node) are not the same node, but both of them include "type N" in their attribute information.

[0041] Node 100 is connected to edge 100A, node 100B is connected to edge 100A, edge 100C is connected to node 100C, and edge 100C is connected to node 100D. The attribute information of edge 100A includes "type E1", the attribute information of node 100B includes "type N2", the attribute information of edge 100C includes "type E2", and the attribute information of node 100D includes "type N3".

[0042] Node 102 is connected to edge 102A, node 102B is connected to edge 102A, edge 102C is connected to node 102B, and edge 102C is connected to node 102D. The attribute information of edge 102A includes "type E1", the attribute information of node 102B includes "type N2", the attribute information of edge 102C includes "type E2", and the attribute information of node 102D includes "type N3".

[0043] In this case, nodes 100B and 100D are extracted as related nodes of node 100. Similarly, nodes 102B and 102D are extracted as related nodes of node 102.

[0044] Since the attribute information of node 100B is identical to the attribute information of node 102B, and the attribute information of edge 100A connecting node 100B and node 100 is identical to the attribute information of edge 102A connecting node 102B and node 102, the attribute information is added to the calculation of the similarity between node 100 (comparison source node) and node 102 (comparison target node) as an associated similarity having a specific weight (for example, 0.2).

[0045] In addition, the attribute information of node 100D is identical to the attribute information of node 102D, and the attribute information of edges 100C and 100A connecting node 100D, node 100B, and node 100 is identical to the attribute information of edges 102C and 102A connecting node 102D, node 102B, and node 102, so they are added to the calculation of the similarity between node 100 (comparison source node) and node 102 (comparison target node) as an associated similarity having a specific weight (for example, 0.5).

[0046] 7 is a diagram showing an example of a similarity list of each comparison target node with respect to the comparison source node for which the similarity has been calculated. The similarity list is displayed on the similarity list display unit 18 and further on the display device 30.

[0047] As shown in the example in Figure 7, for each comparison source node (comparison source object), each comparison target node (comparison target object) is displayed with its corresponding similarity. As shown in Figure 7, it is preferable to display the similarities in descending order.

[0048] According to this embodiment, the attribute information similarity calculation unit 15 calculates the similarity between nodes using the combined attribute information, thereby improving the accuracy of the calculation of the similarity between nodes. In other words, since the nodes to be compared are described by the combined graph data, the amount of attribute information (including attribute information belonging to related nodes) taken into consideration when calculating the similarity increases, improving the accuracy of the calculation of the similarity.

[0049] In this way, information that can be used for maintenance and the like can be obtained not only from attribute information associated with the comparison source node, but also from attribute information associated with the comparison target node that has a high degree of similarity.

[0050] As a result, even if the specifications of the comparison source node and the comparison target node are different (even if nodes 100 and 102 are not directly similar in Figure 5), the similarity can be calculated with high accuracy based on the combined attribute information (including attribute information of related nodes such as those corresponding by dotted lines in Figure 5), and information that can be used for maintaining the comparison source node, etc. can be obtained from the attribute information (including attribute information of related nodes) corresponding to the comparison target node.

[0051] The deterioration tendency or repair method of a device or facility differs not only depending on the attribute information of the device itself, but also depending on the attribute information of the facility or facility to which the device belongs, and the devices and parts owned by the device. Furthermore, it also differs depending on the attribute information of the same node managed by a different type of system (other information group). Therefore, as shown in this embodiment, obtaining information on the deterioration tendency or repair method of the device by taking into account the combined attribute information is effective from the viewpoint of performing effective maintenance of the device.

[0052] <Hardware configuration of the similarity calculation device> 8 and 9 are diagrams each showing a schematic example of a hardware configuration when the similarity calculation device shown in FIG. 1 is actually operated.

[0053] Note that the hardware configurations illustrated in Figures 8 and 9 may not match the numbers, etc., of the configuration illustrated in Figure 1, but this is because the configuration illustrated in Figure 1 shows conceptual units.

[0054] Therefore, at least the following cases can be envisaged: a configuration illustrated in FIG. 1 is composed of multiple hardware configurations illustrated in FIG. 8 and FIG. 9; a configuration illustrated in FIG. 1 corresponds to a part of a hardware configuration illustrated in FIG. 8 and FIG. 9; and further, multiple configurations illustrated in FIG. 1 are provided in a single hardware configuration illustrated in FIG. 8 and FIG. 9.

[0055] FIG. 8 shows a processing circuit 1102A that performs calculations and a storage device 1103 that can store information as the hardware configuration for realizing the attribute information synthesis unit 12, the similarity calculation unit 14, the calculation parameter setting unit 17, the similarity list display unit 18, etc. in FIG. 1.

[0056] 9, a processing circuit 1102B for performing calculations is shown as a hardware configuration for realizing the attribute information synthesis unit 12, the similarity calculation unit 14, the calculation parameter setting unit 17, the similarity list display unit 18, and the like in FIG.

[0057] The storage device 1103 may be, for example, a memory (recording medium) including a hard disk drive (i.e., HDD), random access memory (i.e., RAM), read only memory (i.e., ROM), flash memory, volatile or non-volatile semiconductor memory such as erasable programmable read only memory (EPROM) and electrically erasable programmable read-only memory (EEPROM), a magnetic disk, a flexible disk, an optical disk, a compact disk, a mini disk, or a DVD, or any recording medium to be used in the future.

[0058] The processing circuit 1102A may execute a program stored in the storage device 1103, an external CD-ROM, an external DVD-ROM, or an external flash memory, etc. That is, it may be, for example, a central processing unit (CPU), a microprocessor, a microcomputer, or a digital signal processor (DSP).

[0059] When the processing circuit 1102A executes a program stored in the storage device 1103, an external CD-ROM, an external DVD-ROM, or an external flash memory, the attribute information synthesis unit 12, the similarity calculation unit 14, the calculation parameter setting unit 17, and the similarity list display unit 18 are realized by software, firmware, or a combination of software and firmware, in which the program stored in the storage device 1103 is executed by the processing circuit 1102A. Note that the functions of the attribute information synthesis unit 12, the similarity calculation unit 14, the calculation parameter setting unit 17, and the similarity list display unit 18 may be realized, for example, by a plurality of processing circuits working together.

[0060] The software and firmware may be written as a program and stored in the storage device 1103. In this case, the processing circuit 1102A realizes the above-mentioned functions by reading and executing the program stored in the storage device 1103. In other words, the storage device 1103 may store a program that, when executed by the processing circuit 1102A, results in the above-mentioned functions being realized.

[0061] The processing circuitry 1102B may also be dedicated hardware, i.e., a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a combination thereof, for example.

[0062] When the processing circuit 1102B is a dedicated hardware, the attribute information synthesis unit 12, the similarity calculation unit 14, the calculation parameter setting unit 17, and the similarity list display unit 18 are realized by the operation of the processing circuit 1102B. Note that the functions of the attribute information synthesis unit 12, the similarity calculation unit 14, the calculation parameter setting unit 17, and the similarity list display unit 18 may be realized by separate circuits or by a single circuit.

[0063] In addition, the functions of the attribute information synthesis unit 12, the similarity calculation unit 14, the calculation parameter setting unit 17, and the similarity list display unit 18 may be realized in part by a processing circuit 1102A that executes a program stored in a memory device 1103, and in part by a processing circuit 1102B that is dedicated hardware.

[0064] The similarity calculation system 1 is configured by connecting the input device 20, the display device 30, the storage device 40, and the attribute information storage device 50 to the similarity calculation device having the above hardware configuration via wired or wireless communication (see FIG. 1). However, the configuration of the similarity calculation system 1 may be entirely provided in a user's terminal device, or the user's terminal device may correspond only to the input device 20 and the display device 30, and the similarity calculation device 10, the storage device 40, and the attribute information storage device 50 may be provided in an external server (server 200 including the similarity calculation device 10, the storage device 40, and the attribute information storage device 50 in FIG. 1) or the like.

[0065] <Effects of the above-described embodiment> Next, examples of effects produced by the above-described embodiments are shown. In the following description, the effects are described based on the specific configurations shown as examples in the above-described embodiments, but they may be replaced with other specific configurations shown as examples in the present specification as long as the same effects are produced. In other words, for convenience, only one of the corresponding specific configurations may be described as a representative below, but the representatively described specific configuration may be replaced with another corresponding specific configuration.

[0066] According to the embodiment described above, the similarity calculation device includes a synthesis unit and a similarity calculation unit 14. Here, the synthesis unit corresponds to, for example, the attribute information synthesis unit 12. The attribute information synthesis unit 12 synthesizes a first information group and a second information group different from the first information group to generate at least one synthesis information group. The similarity calculation unit 14 calculates the similarity between the comparison source node and the comparison target node in the synthesis information group. Here, the first information group and the second information group each include a node and attribute information indicating the attribute of the node. Then, the attribute information synthesis unit 12 synthesizes the attribute information in the first information group and the second information group by associating the same nodes in the first information group and the second information group. Also, the similarity calculation unit 14 calculates the similarity by comparing the attribute information associated with the comparison source node and the attribute information associated with the comparison target node.

[0067] Furthermore, according to the embodiment described above, the similarity calculation device includes a processing circuit 1102A that executes a program, and a storage device 1103 that stores the program to be executed. The processing circuit 1102A executes the program to realize the following operations.

[0068] That is, at least one combined information group is generated by combining a first information group and a second information group different from the first information group, and the similarity between the comparison source node and the comparison target node in the combined information group is calculated. Here, the first information group and the second information group each include a node and attribute information indicating the attribute of the node. By matching identical nodes in the first information group and the second information group, the attribute information in the first information group and the second information group is combined, and the similarity is calculated by comparing the attribute information associated with the comparison source node and the attribute information associated with the comparison target node.

[0069] Furthermore, according to the embodiment described above, the similarity calculation device includes the processing circuit 1102B, which is dedicated hardware. The processing circuit 1102B, which is dedicated hardware, performs the following operations.

[0070] That is, the processing circuit 1102B, which is a dedicated hardware, generates at least one combined information group by combining a first information group and a second information group different from the first information group, and calculates the similarity between the comparison source node and the comparison target node in the combined information group. Here, the first information group and the second information group each include a node and attribute information indicating the attribute of the node. The processing circuit 1102B, which is a dedicated hardware, combines the attribute information in the first information group and the second information group by matching the same nodes in the first information group and the second information group. In addition, the similarity is calculated by comparing the attribute information associated with the comparison source node and the attribute information associated with the comparison target node.

[0071] According to this configuration, the accuracy of the calculation of the similarity between nodes can be improved by calculating the similarity between nodes using the combined attribute information. In this way, information that can be used for maintenance and the like can be obtained from the attribute information associated with the comparison target node having a high similarity.

[0072] Furthermore, the same effect can be achieved even if other configurations, examples of which are shown in this specification, are appropriately added to the above configuration, i.e., even if other configurations in this specification that were not mentioned as the above configuration are appropriately added.

[0073] According to the embodiment described above, the similarity calculation unit 14 calculates the similarity by comparing attribute information indicating the attribute of the comparison source node with attribute information indicating the attribute of the comparison target node. According to such a configuration, the attribute information of at least one of the comparison source node and the comparison target node is synthesized, so that the accuracy of the similarity calculation is improved. By calculating the similarity between nodes with high accuracy, it is possible to perform effective maintenance (repair, inspection, maintenance, etc.) that takes into account, for example, deterioration trends, based on the attribute information of similar nodes.

[0074] According to the embodiment described above, the attribute information synthesis unit 12 generates a first synthesis information group and a second synthesis information group, which are synthesis information groups. The similarity calculation unit 14 then calculates the similarity by comparing the attribute information associated with the comparison source node in the first synthesis information group with the attribute information associated with the attribute of the comparison target node in the second synthesis information group. According to this configuration, the attribute information of both the comparison source node and the comparison target node is synthesized, so that the accuracy of the similarity calculation is improved. By calculating the similarity between nodes with high accuracy, it is possible to perform effective maintenance (repair, inspection, maintenance, etc.) that takes into account, for example, deterioration trends, based on the attribute information of similar nodes.

[0075] According to the embodiment described above, the attribute information synthesis unit 12 includes an identical node determination unit 13 for determining whether the same node exists in the first information group and the second information group. The identical node determination unit 13 determines whether the same node exists based on correspondence information indicating the relationship between the first information group and the second information group. Here, the correspondence information corresponds to, for example, the heterogeneous system correspondence information 40A. Then, the attribute information synthesis unit 12 synthesizes the attribute information in the first information group and the second information group by associating the nodes determined to be identical by the identical node determination unit 13. According to this configuration, it is possible to synthesize graph data starting from the same node and generate synthesized graph data in which the attribute information in each graph data is synthesized. Therefore, it is possible to improve the accuracy of the similarity calculation based on the synthesized attribute information.

[0076] According to the embodiment described above, the similarity calculation unit 14 adds the related similarity, which is the similarity between the attribute information of the first related node related to the comparison source node and the attribute information of the second related node related to the comparison target node, to the similarity. According to such a configuration, the accuracy of the similarity calculation is improved by taking into account the attribute information belonging to the related nodes.

[0077] According to the embodiment described above, the first information group and the second information group each include an edge connecting a plurality of nodes. The first associated node is connected to the comparison source node via the first edge, which is an edge. The second associated node is connected to the comparison target node via the second edge, which is an edge. The similarity calculation unit 14 adds an associated similarity, which is a similarity between the attribute information of the first edge and the attribute information of the second edge, to the similarity. According to such a configuration, the accuracy of the similarity calculation is improved by considering the attribute information belonging to the edge connecting the associated node and the comparison source node (or the comparison target node).

[0078] Furthermore, according to the embodiment described above, the similarity calculation device includes a similarity list display unit 18 for displaying a list of the similarity of the comparison target node with respect to the comparison source node. With this configuration, the similarity between nodes can be easily confirmed.

[0079] According to the embodiment described above, the similarity calculation system includes an attribute information synthesis unit 12 for synthesizing a first information group and a second information group different from the first information group to generate at least one synthesized information group, and a similarity calculation unit 14 for calculating the similarity between a comparison source node and a comparison target node in the synthesized information group. The first information group and the second information group each include a node and attribute information indicating an attribute of the node. The attribute information synthesis unit 12 also synthesizes the attribute information in the first information group and the second information group by associating the same nodes in the first information group and the second information group. The similarity calculation unit 14 also calculates the similarity by comparing the attribute information associated with the comparison source node and the attribute information associated with the comparison target node.

[0080] According to this configuration, the accuracy of the calculation of the similarity between nodes can be improved by calculating the similarity between nodes using the combined attribute information. In this way, information that can be used for maintenance and the like can be obtained from the attribute information associated with the comparison target node having a high similarity.

[0081] Furthermore, even if other configurations, examples of which are shown in this specification, are appropriately added to the above configuration, i.e., even if other configurations in this specification that were not mentioned as the above configuration are appropriately added, the same effect can be produced.

[0082] Furthermore, according to the embodiment described above, the similarity calculation system includes a terminal device having an input device 20 and a display device 30, and a server 200 that communicates with the terminal device. The attribute information synthesis unit 12 and the similarity calculation unit 14 are provided in the server 200. With this configuration, it is possible to reduce the computational burden on the terminal device.

[0083] <Modifications of the above-described embodiments> In the embodiments described above, the dimensions, shapes, relative positional relationships, and implementation conditions of each component may be described, but these are merely examples in all aspects and are not limiting.

[0084] Thus, numerous variations and equivalents not shown are contemplated within the scope of the technology disclosed herein, including, for example, modifying, adding, or omitting at least one component.

[0085] Furthermore, unless a contradiction arises, when it is stated in the above-described embodiments that "one" component is provided, "one or more" of that component may be provided.

[0086] Furthermore, each component in the embodiments described above is a conceptual unit, and the scope of the technology disclosed in this specification includes cases where one component is made up of multiple structures, where one component corresponds to a part of a structure, and even where multiple components are provided in one structure.

[0087] Furthermore, each of the components in the embodiments described above includes structures having other structures or shapes as long as they perform the same function.

[0088] Furthermore, the descriptions in this specification are incorporated by reference for all purposes related to the present technology, and none of them are admitted to be prior art.

[0089] Furthermore, each of the components described in the above embodiments is envisioned as either software or firmware, or as corresponding hardware, and in the case of software, is referred to as, for example, a "unit", and in the case of hardware, is referred to as, for example, a "processing circuit" (circuitry).

[0090] Furthermore, the technology disclosed in this specification may also be in a form in which each component is distributed across multiple devices, that is, in a form such as a system that is a combination of multiple devices. [Explanation of symbols]

[0091] 1 similarity calculation system, 10 similarity calculation device, 12 attribute information synthesis unit, 13 same node determination unit, 14 similarity calculation unit, 15 attribute information similarity calculation unit, 16 related node extraction unit, 17 calculation parameter setting unit, 18 similarity list display unit, 20 input device, 30 display device, 40 storage device, 40A heterogeneous system correspondence information, 50 attribute information storage device, 50A system type A attribute information, 50B system type B attribute information, 50C system type C attribute information, 50D system type C attribute information, 100 node, 100A edge, 100B node, 100C edge, 100D node, 102 node, 102A edge, 102B node, 102C edge, 102D node, 200 server, 1102A processing circuit, 1102B processing circuit, 1103 storage device.

Claims

1. a synthesis unit for synthesizing a first information group and a second information group different from the first information group to generate at least one synthetic information group; a similarity calculation unit for calculating a similarity between a comparison source node and a comparison target node in the combined information group; the first information group and the second information group each include a node and attribute information indicating an attribute of the node; the synthesis unit synthesizes the attribute information in the first information group and the second information group by corresponding the same nodes in the first information group and the second information group; the similarity calculation unit calculates the similarity by comparing the attribute information associated with the comparison source node and the attribute information associated with the comparison target node; the synthesis unit generates a first synthesis information group and a second synthesis information group, which are the synthesis information groups; the similarity calculation unit calculates the similarity by comparing the attribute information associated with the comparison source node in the first combined information group with the attribute information associated with the attribute of the comparison destination node in the second combined information group; Similarity calculation device.

2. The similarity calculation device according to claim 1, the similarity calculation unit calculates the similarity by comparing the attribute information indicating an attribute of the comparison source node with the attribute information indicating an attribute of the comparison target node; Similarity calculation device.

3. 3. The similarity calculation device according to claim 1, the synthesis unit further includes an identical node determination unit for determining identical nodes in the first information group and the second information group; the same node determination unit determines whether the nodes are the same based on correspondence information indicating a relationship between the first information group and the second information group of the nodes; the combining unit combines the attribute information in the first information group and the second information group by matching the nodes determined to be identical by the identical node determining unit. Similarity calculation device.

4. 3. The similarity calculation device according to claim 1, the similarity calculation unit adds an associated similarity, which is a similarity between the attribute information of a first associated node related to the comparison source node and the attribute information of a second associated node related to the comparison target node, to the similarity; Similarity calculation device.

5. The similarity calculation device according to claim 4, the first information group and the second information group each include edges connecting a plurality of the nodes; the first related node is connected to the comparison source node via a first edge that is the edge; the second associated node is connected to the comparison target node via a second edge that is the edge; the similarity calculation unit adds the associated similarity, which is a similarity between the attribute information of the first edge and the attribute information of the second edge, to the similarity; Similarity calculation device.

6. 3. The similarity calculation device according to claim 1, a similarity list display unit for displaying a list of similarities of the comparison target node with respect to the comparison source node, Similarity calculation device.

7. a synthesis unit for synthesizing a first information group and a second information group different from the first information group to generate at least one synthetic information group; a similarity calculation unit for calculating a similarity between a comparison source node and a comparison target node in the combined information group; the first information group and the second information group each include a node and attribute information indicating an attribute of the node; the synthesis unit synthesizes the attribute information in the first information group and the second information group by corresponding the same nodes in the first information group and the second information group; the similarity calculation unit calculates the similarity by comparing the attribute information associated with the comparison source node and the attribute information associated with the comparison target node; the synthesis unit generates a first synthesis information group and a second synthesis information group, which are the synthesis information groups; the similarity calculation unit calculates the similarity by comparing the attribute information associated with the comparison source node in the first combined information group with the attribute information associated with the attribute of the comparison destination node in the second combined information group; Similarity calculation system.

8. A similarity calculation system according to claim 7, A terminal device having an input device and a display device, and a server that communicates with the terminal device, The synthesis unit and the similarity calculation unit are provided in the server. Similarity calculation system.