Problem evaluation device and problem evaluation method

Abstract

This problem evaluation device: retains a problem organization tree defined by a tree structure including problem-related nodes arranged in each of a plurality of problem layers and edges connecting nodes of the adjacent problem layers; retrieves, for each of the plurality of problem layers and from a retrieval target database associated with the problem layers in advance, a document including a similar problem that is similar to the problem indicated by the node included in the problem layer; calculates a first degree of importance for each problem on the basis of the result of retrieving the document; and generates data for displaying a problem organization tree in which the first degrees of importance are associated with the nodes.

Description

Assignment evaluation device and assignment evaluation method Incorporation by Reference

[0001] This application claims priority from Japanese Patent Application No. 2024-093168, filed on June 7, 2024, the contents of which are incorporated herein by reference.

[0002] The present invention relates to an assignment evaluation device and an assignment evaluation method.

[0003] Japanese Patent Laid-Open Publication No. 2023-135499 (Patent Document 1) is a background technology in this technical field. This publication states that "in a solution proposal support system, a solution proposal support server includes a problem / solution information table that stores problem-solution information that associates multiple problems with multiple solutions for solving each of the multiple problems and implementation result information that shows the implementation results of each solution, a similarity calculation program that calculates the similarity between a search keyword and a problem included in the problem / solution information table, a problem importance calculation program that calculates the importance of the problem, a solution implementation result calculation program that calculates an index of the solution implementation result, and a problem-solving effect calculation program that calculates the problem-solving effect" (see Abstract).

[0004] Japanese Patent Application Laid-Open No. 2023-135499

[0005] The technology described in Patent Literature 1 calculates the importance of a problem using information indicating solutions that have already been implemented. Here, problems fall into multiple different layers, and the technology described in Patent Literature 1 leaves room for improvement in calculating the importance according to the layer. Therefore, one aspect of the present invention appropriately calculates the importance of a problem according to the problem layer.

[0006] In order to solve the above problem, one aspect of the present invention employs the following configuration: a task evaluation device includes a processor and a memory, the memory holds a task organization tree defined by a tree structure including nodes related to tasks arranged in each of a plurality of task layers and edges connecting nodes in the adjacent task layers, the task evaluation device is connected to a plurality of search target databases, each of which includes a plurality of documents, each of the plurality of task layers being pre-associated with one of the plurality of search target databases, and at least some of the task layers being associated with a different search target database, the processor, for each of the plurality of task layers, searches the search target database associated with that task layer for documents including tasks similar to tasks indicated by nodes included in that task layer, calculates a first importance of each of the tasks based on the search results for the documents, and generates data for displaying the task organization tree in which the first importance is linked to the node.

[0007] According to one aspect of the present invention, the importance of a task can be calculated appropriately according to the task layer.

[0008] Problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments.

[0009] 1 is a block diagram showing an example of the configuration of an assignment evaluation device in Example 1. FIG. 2 is an explanatory diagram showing an example of an assignment sorting tree in Example 1. FIG. 3 is a flowchart showing an example of assignment evaluation processing in Example 1. FIG. 4 is an explanatory diagram showing an example of an assignment sorting tree including information indicating first importance, second importance, and correlation in Example 1. FIG. 5 is an explanatory diagram showing another example of an assignment sorting tree including information indicating first importance, second importance, and correlation in Example 1. FIG. 6 is an explanatory diagram showing another example of correlation calculation processing in Example 1. FIG. 7 is an explanatory diagram showing an example of an assignment sorting tree including information regarding first importance, second importance, and date in Example 1. FIG. 8 is an explanatory diagram showing an example of processing in which indicators related to advancement and importance are assigned in Example 1. FIG. 9 is an explanatory diagram showing another example of processing in which indicators related to advancement and importance are assigned in Example 1. FIG. 10 is an example of information showing an analysis result of the impact of a solution on assignments of each layer in Example 1. FIG. 11 is an explanatory diagram showing an example of an assignment sorting tree displayed on a display device in Example 1. FIG. 12 is a diagram showing an example of a screen configuration of a display screen for comparing assignments of different industries in Example 1.

[0010] Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. In this embodiment, the same components are generally designated by the same reference numerals, and repeated explanations will be omitted. It should be noted that this embodiment is merely an example for realizing the present invention, and does not limit the technical scope of the present invention.

[0011] 1 is a block diagram showing an example of the configuration of an assignment evaluation device 100. The assignment evaluation device 100 is configured by a computer having, for example, a CPU (Central Processing Unit) 110, a memory 120, an auxiliary storage device 130, an input device 140, a display device 150, and a communication device 160.

[0012] The problem evaluation device 100 is connected to a problem / solution database (DB) 181 and a product DB 182 on an in-house network (internal to the company where the problem evaluation device 100 is installed) via, for example, an intranet 170. The problem / solution DB 181 holds, for example, information on the problems, measures, and solutions described in the problem organization tree 131. The product DB 182 holds, for example, information on the products (examples of solutions) described in the problem organization tree 131. Details of the problem organization tree 131 will be described later.

[0013] The issue evaluation device 100 is also connected to a patent DB 191 and a company DB 192 on an external network, for example, via the Internet 171. The patent DB 191 stores, for example, patent documents (e.g., publications and registered publications) of the company and other companies (the company where the issue evaluation device 100 is installed and other companies). The company DB 192 stores, for example, management information such as company websites, investor relations (IR) materials, medium- to long-term business plans, and integration plans of other companies, as well as information such as product catalogs of other companies. The information stored in the patent DB 191 and the company DB 192 is used to calculate the importance, which will be described later.

[0014] The CPU 110 is an example of a processor and executes programs stored in the memory 120. The memory 120 includes a non-volatile storage element, Read Only Memory (ROM), and a volatile storage element, Random Access Memory (RAM). The ROM stores unchanging programs (e.g., a Basic Input / Output System (BIOS)). The RAM is a high-speed, volatile storage element such as Dynamic Random Access Memory (DRAM), and temporarily stores programs executed by the CPU 110 and data used when the programs are executed.

[0015] The auxiliary storage device 130 is a large-capacity, non-volatile storage device such as a magnetic storage device (HDD (Hard Disk Drive)) or a flash memory (SSD (Solid State Drive)), and stores programs to be executed by the CPU 110 and data to be used when the programs are executed. In other words, the programs are read from the auxiliary storage device 130, loaded into the memory 120, and executed by the CPU 110.

[0016] The input device 140 is a device such as a keyboard or mouse that receives input from an operator. The display device 150 is a device such as a display or printer that outputs the results of program execution in a format that can be viewed by the operator.

[0017] The communication device 160 is a network interface device that controls communication with other devices in accordance with a predetermined protocol. The communication device 160 may also include a serial interface such as a USB (Universal Serial Bus).

[0018] A part or all of the program executed by the CPU 110 may be provided to the assignment evaluation device 100 from a removable medium (CD-ROM, flash memory, etc.) which is a non-transitory storage medium, or from an external computer equipped with a non-transitory storage device via a network, and may be stored in a non-volatile auxiliary storage device 130 which is a non-transitory storage medium. For this reason, the assignment evaluation device 100 should preferably have an interface for reading data from removable media.

[0019] The assignment evaluation device 100 is a computer system configured on one physical computer or on multiple logically or physically configured computers, and may operate in separate threads on the same computer, or on a virtual computer constructed on multiple physical computer resources.

[0020] The CPU 110 includes, for example, a search unit 111, a similarity calculation unit 112, an importance calculation unit 113, a correlation calculation unit 114, and a task sorting tree creation unit 115, all of which are functional units. The search unit 111 identifies search target information corresponding to each task layer included in the task sorting tree 131, and searches the identified information to extract similar tasks. The similarity calculation unit 112 calculates the similarity between tasks. The importance calculation unit 113 calculates the importance of the tasks. The correlation calculation unit 114 calculates the correlation between tasks. The task sorting tree creation unit 115 creates the task sorting tree 131.

[0021] For example, the CPU 110 functions as a search unit 111 by operating in accordance with a search program loaded into the memory 120, and functions as a similarity calculation unit 112 by operating in accordance with a similarity calculation program loaded into the memory 120. The same applies to the other functional units included in the CPU 110 and their relationships with the programs.

[0022] Note that some or all of the functions of the functional units included in the CPU 110 may be realized by hardware such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field-Programmable Gate Array).

[0023] The auxiliary storage device 130 stores, for example, an issue organization tree 131, a search target DB 132, an importance table 133, a correlation table 134, and a product table 135. The issue organization tree 131 and the search target DB 132 are predefined search target DBs so that the search unit 111 can effectively acquire necessary information. However, the DBs searched by the search unit 111 are not limited to the search target DB 132. The importance table 133 stores the importance calculated by the importance calculation unit 113. The correlation table 134 stores the correlation calculated by the correlation calculation unit 114. The product table 135 stores some or all of the information stored in the product DB 182.

[0024] In addition, some or all of the information stored in the auxiliary storage device 130 may be stored in the memory 120, or may be stored in an external database connected to the assignment evaluation device 100.

[0025] In this embodiment, the information used by the assignment assessment device 100 does not depend on the data structure and may be expressed in any data structure. For example, the information can be stored in a data structure appropriately selected from a table, a list, a database, or a queue.

[0026] 2 is an explanatory diagram showing an example of a task organization tree 131. The task organization tree 131 is represented by a tree structure in which multiple task-related nodes are connected by edges. Each node in the task organization tree 131 is placed in one of multiple layers that have a hierarchical relationship. Note that in FIG. 2 and other drawings described later, the depiction of some nodes in the task organization tree 131 is omitted due to space limitations.

[0027] In this example, the multiple layers are described as consisting of, from top to bottom, a social issue layer 210, a management issue layer 220, a business issue layer 230, a policy layer 240, and a solution layer 250. However, the multiple layers may not include some of these layers, or may further include other layers. The characters written inside each illustrated node (for example, "Social Issue 1," "Management Issue 1-1," and "Business Issue 1-1-n") indicate an identifier for identifying the node.

[0028] The social issue layer 210 contains nodes that indicate issues faced by society (for example, the world as a whole, or a specific country or region). The business issue layer 220 contains nodes that indicate business issues faced by companies in society (for example, a specific company or multiple companies in a specific industry). The business issue layer 230 contains nodes that indicate issues that arise in the business operations of companies.

[0029] The policy layer 240 contains nodes representing policies implemented in business operations. The solution layer 250 contains nodes representing solutions (e.g., commercial products) introduced in the policies. Because policies are examples of means for solving problems that are more subdivided (detailed) than business problems, the policy layer can also be said to be a layer representing such subdivided problems. Similarly, because solutions are examples of means for solving problems that are even more subdivided than the problems solved by the policies, the solution layer can also be said to be a layer representing such even more subdivided problems. Therefore, not only the social problem layer 210, the business problem layer 220, and the business problem layer 230, which directly represent the problems themselves, but also the policy layer 240 and the solution layer 250 can be said to be layers representing problems (hereinafter simply referred to as problem layers).

[0030] Furthermore, in the problem layer of the problem organization tree 131, the lower the layer, the more subdivided (detailed) the problem is. Therefore, layers that indirectly indicate problems (layers that indicate means for solving problems) are placed lower than layers that directly indicate the problems themselves (social problem layer 210, business problem layer 220, and business problem layer 230).

[0031] Each node included in the problem organization tree 131 can be connected by an edge only to a node belonging to a layer adjacent to the layer to which the node belongs. Furthermore, each node belonging to any of the layers (i.e., the management problem layer 220, the business problem layer 230, the policy layer 240, and the solution layer 250) except for the top layer, the social problem layer 210, is always connected by an edge to a node in the layer one layer above the layer to which the node belongs. Note that a single node may be connected by edges to multiple nodes in the layer above the node, or may be connected by edges to multiple nodes in the layer of the node.

[0032] Among the nodes connected by edges in the problem organization tree 131, achieving the issues related to the nodes in the lower layer contributes to achieving the issues indicated by the nodes in the higher layer. In the example of FIG. 3, "Social Issue 1" is connected by edges to "Management Issue 1-1," "Management Issue 1-2," and "Management Issue 1-3." Therefore, it is shown that solving each of "Management Issue 1-1," "Management Issue 1-2," and "Management Issue 1-3" will contribute to solving "Social Issue 1." It can also be said that this shows that in order to solve "Social Issue 1," it is useful to solve "Management Issue 1-1," "Management Issue 1-2," and "Management Issue 1-3."

[0033] In the example of Figure 2, "Business problem 2-2-1" is connected to "Measure 2-2-1-1" and "Measure 2-2-1-2" by edges. Therefore, it is shown that implementing "Measure 2-2-1-1" and "Measure 2-2-1-2" will contribute to solving "Business problem 2-2-1." It can also be said that it is shown that implementing "Measure 2-2-1-1" and "Measure 2-2-1-2" is useful for solving "Business problem 2-2-1."

[0034] In addition, in the example of Figure 2, "Measure 1-2-1-1" is connected to "Solution 1-2-1-1-S1" by an edge. Therefore, it is shown that "Measure 1-2-1-1" is realized by introducing "Solution 1-2-1-1-S1." It can also be said that it is shown that introducing "Solution 1-2-1-1-S1" is useful for realizing "Measure 1-2-1-1."

[0035] In this way, in the problem organization tree 131, nodes related to issues of society, industry, and / or companies are arranged in each layer, and the relationships between issues are expressed by connecting nodes between adjacent layers with edges. The problem organization tree 131 allows the user to visually grasp the sub-issues that need to be solved, the measures that should be implemented, and the solutions that should be used in order to solve the sub-issues, and ultimately how the sub-issues affect the sub-issues.

[0036] Therefore, the issue sorting tree 131 allows the user to grasp the impact that the introduction of a lower-level solution will have on measures, business, management, society, etc., such as, for example, introducing a certain solution will realize a specific measure, that specific realization measure will solve a specific business issue, that solving that specific business issue will solve a specific management issue, and that solving that specific management issue will solve a specific social issue. This allows the user to estimate the effects of introducing a solution and further obtain reference information when developing a business plan.

[0037] On the other hand, the issue consolidation tree 131 in Figure 2 does not express the importance of each issue or the specific impact that resolving that issue will have on higher-level issues. This makes it difficult for users to determine which of the lower-level nodes linked to a higher-level node is particularly effective in achieving the content indicated by that node. Furthermore, for example, if a specific measure or solution affects multiple higher-level issues, it becomes even more difficult for users to predict the impact. Furthermore, because of limitations such as the screen size on which the issue consolidation tree 131 is displayed, it may be difficult for users to visually display all of the nodes included in the issue consolidation tree 131. Therefore, it is desirable to select and display nodes with higher importance so that users can get an overview of important issues. Therefore, the issue assessment device 100 of this embodiment appropriately assigns importance to the nodes (i.e., issues) included in the issue consolidation tree 131 using the process described below.

[0038] 3 is a flowchart showing an example of the problem evaluation process. The problem organization tree creation unit 115 creates the problem organization tree 131 using, for example, information on problems, measures, and solutions stored in the problem / solution DB 181, and information on products (examples of solutions) stored in the product DB 182 (S301).

[0039] Specifically, for example, the problem sorting tree creation unit 115 may create the problem sorting tree 131 in accordance with user input to the input device 140, or may create the problem sorting tree 131 using artificial intelligence (AI). Also, the problem sorting tree 131 may be created in advance.

[0040] The search unit 111 identifies the information to be searched corresponding to each problem layer of the problem organization tree 131, and searches for documents containing similar problems (similar problems include the same problem) to each of the problems (social problems, management problems, business problems, measures, or solutions) indicated by the nodes included in each problem layer from the information to be searched corresponding to that problem layer (S302).

[0041] The search unit 111 may use a generation AI or the like to create a group of similar tasks for each task indicated by a node included in each task layer. The search unit 111 also searches for documents containing similar tasks using a predetermined algorithm such as text mining including synonym search and / or co-occurrence analysis.

[0042] The search target information corresponding to each issue layer is, for example, predetermined. For example, the search target information corresponding to the social issue layer 210 is management information such as corporate investor relations (IR) for the entire target industry stored in the company DB 192. The search target information corresponding to the social issue layer 210 may also include domestic and international public conference materials (not shown) such as government policies (Society 5.0), COPs (Conferences of the Parties), and materials related to the Sustainable Development Goals (SDGs), as well as corporate IR and consulting materials of major companies stored in the company DB 192. The search target information corresponding to the management issue layer 220 is management information such as corporate websites, corporate IR materials, medium- to long-term management plans, and integrated plans of one or more specific companies included in the target industry stored in the company DB 192. Furthermore, for example, the information to be searched corresponding to the business problem layer 230 and the policy layer 240 is patent documents stored in the patent DB 191. Also, for example, the information to be searched corresponding to the solution layer 250 is product catalogs of the company and / or other companies stored in the company DB 192 and / or product DB 182. Management information, patent documents, and product catalogs are all publicly available information that is easily accessible, and the problem assessment device 100 can use this public information to assess the importance of problems with high accuracy using the method described below.

[0043] Note that the information to be searched may be different for all task layers, or may be the same for some task layers, but the information to be searched for is assumed to be different for at least some task layers (i.e., the information to be searched for is not the same for all task layers).By making the information to be searched differently depending on the task layer in this way, it is possible to search an appropriate DB when searching for tasks similar to the tasks indicated by the nodes included in each task layer.

[0044] Furthermore, the information to be searched for corresponding to each issue layer may be expanded or limited, for example, according to conditions input by the user. Specifically, for example, the information to be searched for corresponding to the social issue layer 210 and the business issue layer 220 may be, for example, business information of a company belonging to a specific industry, and the information to be searched for corresponding to the business issue layer 230 and the policy layer 240 may be, for example, registered patent publications of patents whose applicants are companies belonging to a specific industry.

[0045] The importance calculation unit 113 calculates the first importance of each task based on the search results of step S302 (S303). Specifically, for each task, the importance calculation unit 113 may determine the number of documents containing similar tasks as the first importance of the task, the ratio of the number of documents containing similar tasks to the total number of documents included in the search target information as the first importance of the task, or the total number of occurrences of the similar tasks in documents containing the similar tasks as the first importance of the task. Documents from the same company may be counted as a single document when counting the number of documents containing similar tasks (i.e., they may not be counted twice). In this way, the first importance can be said to indicate an importance that can be calculated independently of relationships with other tasks, i.e., the importance of a single task.

[0046] In addition, the importance calculation unit 113 may extract information indicating the time period related to each similar task from documents containing similar tasks to each task using a predetermined algorithm such as text mining, and reflect the extracted information indicating the time period in the first importance.

[0047] Specifically, for example, if the document containing the similar problem is a document related to management information, the importance calculation unit 113 extracts the expected target date for solving the similar problem (or for starting measures to solve the problem) or the publication date of the document as the period related to the similar problem. Furthermore, for example, if the document containing the similar problem is a patent document, the importance calculation unit 113 extracts the patent application date or the like as the period related to the similar problem. Furthermore, for example, if the document containing the similar problem is a product catalog, the importance calculation unit 113 extracts the release date of the product catalog or the release date of the product as the period related to the similar problem. Furthermore, for example, a score according to the period is predefined, and the closer the period is to the current date and time, the higher the score assigned. The importance calculation unit 113 acquires a score according to each of the extracted periods and reflects the extracted periods in the first importance by, for example, adding up the total of the acquired scores in calculating the first importance.

[0048] Furthermore, the importance calculation unit 113 may reflect the reliability of a document including a similar problem in the first importance. Specifically, for example, a score indicating reliability according to the type of document (e.g., a high score if the document type is a company's official website, investor relations materials, or patent registration bulletin, and a low score if the document type is a social networking service (SNS)) is predefined. For example, the importance calculation unit 113 acquires a score according to each document type and adds up the total of the acquired scores in calculating the first importance, thereby reflecting the extraction time in the first importance.

[0049] In addition, the importance calculation unit 113 may analyze documents containing similar issues using a predetermined algorithm such as text mining to identify at least one of the marketability of the similar issues, customer acceptability of the similar issues, return on investment of the similar issues, feasibility of the similar issues, the company's advantage in relation to the similar issues, social significance of the similar issues, and novelty of the similar issues, and may score the at least one identified item and reflect it in the first importance.

[0050] The correlation calculation unit 114 calculates the correlation between tasks indicated by nodes (upper node and lower node) directly connected by edges (S304). Specifically, for example, the correlation calculation unit 114 extracts documents in which both a task similar to the task indicated by the upper node and a task similar to the task indicated by the lower node appear, from the search target information corresponding to the task layer to which the upper node belongs and the search target information corresponding to the task layer to which the lower node belongs.

[0051] In other words, for example, if a node in the management issue layer 220 and a node in the business issue layer 230 are directly connected by an edge, the correlation calculation unit 114 extracts documents from the management information and patent documents in which both a similar issue to the issue indicated by the node in the management issue layer 220 and a similar issue to the issue indicated by the node in the business issue layer 230 appear.

[0052] The correlation calculation unit 114 may extract documents in which both a similar task to the task indicated by the upper node and a similar task to the task indicated by the lower node appear only from the search target information corresponding to the task layer to which the upper node belongs, or may extract documents in which both similar tasks appear together from the search target information corresponding to the task layer to which the lower node belongs.The correlation calculation unit 114 may also extract documents in which both similar tasks appear together.

[0053] The correlation calculation unit 114 may determine the number of documents extracted as documents in which both similar tasks appear as the correlation between the upper node and the lower node, or may determine the total number of occurrences of both similar tasks in the extracted documents as the correlation between the upper node and the lower node.

[0054] The correlation calculation unit 114 may convert the determined correlation into a relative value of the number of documents or the total number of occurrences. Specifically, for example, when N lower nodes are directly connected to one upper node by edges, the correlation calculation unit 114 may normalize the correlations between the one upper node and the N lower nodes so that the sum of the correlations between the one upper node and the N lower nodes is 1.0 (i.e., divide each of the N correlations by the sum of the N correlations).

[0055] The importance calculation unit 113 calculates the second importance of each task based on the first importance of the task and the correlation between the task and the higher-level task (S305). Note that if one node is directly connected to multiple higher-level nodes by edges, the second importance of the node is calculated based on its relationship with each of the multiple higher-level nodes (i.e., multiple second importances are calculated for the node).

[0056] In step S305, the importance calculation unit 113 calculates, for each task, the second importance, for example, by multiplying the first importance of the task by the correlation between the task and the higher-level task that is directly connected to the task by an edge. In this case, the second importance becomes higher the higher the first importance of the task and the higher the correlation.

[0057] In this way, the second importance level can be said to reflect the importance of the individual issue and the strength of its relationship with the higher-level issue. In other words, an issue with a high second importance level is not only important in itself, but also likely to have a high impact on the higher-level issue if it is resolved (the degree to which it will contribute to the resolution of the higher-level issue).

[0058] For example, the importance calculation unit 113 may calculate a value for each task by adding the first importance of the task to the first importance of the higher-level task that is directly connected to the task by an edge, and then multiplying this calculated value by the correlation between the task and the higher-level task to calculate the second importance. In this case, the higher the first importance of the task and the higher-level task, the higher the second importance will be, and the higher the correlation will be. Therefore, in this case, the second importance also reflects the importance of the higher-level task as a standalone task.

[0059] The importance calculation unit 113 stores the information linking the first importance calculated in step S303 with the node and the information linking the second importance calculated in step S305 with the node in the importance table 133, and stores the information linking the correlation calculated in step S304 with the edge in the correlation table 134 (S306).

[0060] The problem sorting tree creation unit 115 displays the problem sorting tree 131 on the display device 150 (S307) in accordance with display guidelines set in accordance with user input via the input device 140, for example, and then ends the problem evaluation process. Note that, for example, the user can specify, as display guidelines, which range of the problem sorting tree 131 to display, which range of nodes to display the first importance corresponding to, which range of nodes to display the second importance corresponding to, and which range of edges to display the correlation degree corresponding to.

[0061] 4 is an explanatory diagram showing an example of a problem organization tree 131 including information indicating first importance, second importance, and correlation. In the figures from FIG. 4 onward, "1st DoI" (Degree of Importance) indicates the first importance, and "2nd DoI" indicates the second importance. In the examples from FIG. 4 onward, descriptions of first importance, second importance, and correlation for some nodes and edges are omitted for simplicity.

[0062] In the example of Figure 4, the first importance of "Business Issue 1-2-1" in the business issue layer 230 is 42, and "Business Issue 1-2-1" is directly connected by edges to "Measure 1-2-1-1," "Measure 1-2-1-2," and "Measure 1-2-1-3" in the policy layer 240, which is the layer one level below the business issue layer 230. The correlations between "Business Issue 1-2-1" and "Measure 1-2-1-1," "Measure 1-2-1-2," and "Measure 1-2-1-3" are 0.1, 0.6, and 0.3, respectively (as indicated on the edges connecting these node combinations). In the example of Figure 4, the correlations are expressed as relative values ​​whose sum is 1.0. The first importances of "Measure 1-2-1-1," "Measure 1-2-1-2," and "Measure 1-2-1-3" are 23, 14, and 5, respectively.

[0063] 4, the first importance of the issues in the business issue layer 230 is not used to calculate the second importance of the issues in the policy layer 240. In the example of Fig. 4, the second importance of "Measure 1-2-1-1" in relation to "Business Issue 1-2-1" is 23 x 0.1 = 2.3, the second importance of "Measure 1-2-1-2" in relation to "Business Issue 1-2-1" is 14 x 0.6 = 8.4, and the second importance of "Measure 1-2-1-3" in relation to "Business Issue 1-2-1" is 5 x 0.3 = 1.5.

[0064] As described above, the value of the first importance of "business issue 1-2-1," which is 42, may be reflected in the second importance of each of "measure 1-2-1-1," "measure 1-2-1-2," and "measure 1-2-1-3" in relation to "business issue 1-2-1." Specifically, for example, the second importance of "measure 1-2-1-1" in relation to "business issue 1-2-1" may be calculated as (23 + 42) × 0.1 = 6.5, the second importance of "measure 1-2-1-2" in relation to "business issue 1-2-1" may be calculated as (14 + 42) × 0.6 = 39.6, and the second importance of "measure 1-2-1-3" in relation to "business issue 1-2-1" may be calculated as (5 + 42) × 0.3 = 14.1.

[0065] In the example of Figure 4, of "Measure 1-2-1-1," "Measure 1-2-1-2," and "Measure 1-2-1-3," "Measure 1-2-1-1" has the highest first importance, which indicates that "Measure 1-2-1-1" is important as a standalone issue. On the other hand, of "Measure 1-2-1-1," "Measure 1-2-1-2," and "Measure 1-2-1-3," "Measure 1-2-1-2" has the highest second importance in relation to "Business Issue 1-2-1," which indicates that "Measure 1-2-1-2" will contribute to the resolution of "Business Issue 1-2-1" to a large extent.

[0066] 4 may be displayed on the display device 150. Therefore, in FIG. 4, for example, edges connecting combinations of tasks that show a correlation degree equal to or greater than a predetermined value and borders of nodes corresponding to tasks that have a second importance equal to or greater than a predetermined value are represented by thick lines, and therefore such representations using thick lines may also be used when displaying the task sorting tree 131 on the display device 150.

[0067] 5 is an explanatory diagram showing another example of the problem organization tree 131 including information indicating the first importance, the second importance, and the correlation degree. The first importance, the second importance, and the correlation degree for "Business Problem 1-2-1" in the business problem layer 230 and "Measure 1-2-1-1," "Measure 1-2-1-2," and "Measure 1-2-1-3" in the measure layer 240 are the same as those in FIG. 4. However, the (11), (65), and (32) attached to the correlation degrees expressed as relative values ​​of 0.1, 0.6, and 0.3, respectively, indicate the correlation degrees expressed as absolute values ​​before normalization.

[0068] 5, "Business Problem 1-3-1" in the business problem layer 230 is directly connected by edges to "Measure 1-2-1-1" and "Measure 1-2-1-2" in the measure layer 240, which is the layer below the business problem layer 230. Here, the first importance of "Business Problem 1-3-1" is the highest value (73) among the issues in the same layer, so "Business Problem 1-3-1" is considered to be a more important issue (an issue that needs to be resolved) than other issues in the same layer. However, if the correlation (absolute value before normalization) between "Business Problem 1-3-1" and each of "Measure 1-2-1-1" and "Measure 1-2-1-2" is small, it is considered that "Business Problem 1-3-1" is difficult to achieve, or that measures to achieve "Business Problem 1-3-1" have not yet been thought of, so "Business Problem 1-3-1" can also be considered to be a new issue that needs to be resolved.

[0069] 5, a score indicating the company's superiority ("superiority" in the figure) is written in each node of the solution layer 250. As described above, the score indicating the company's superiority may be reflected in the calculation of the first importance, and the score used in the calculation of such first importance may be managed in association with the node.

[0070] In the example of FIG. 5 , each node in the solution layer 250 is described as either "OK" or "NG" for "Delivery." A solution with "OK" for "Delivery" can be provided to the region and time period specified by the user, while a solution with "NG" for "Delivery" cannot be provided to the region and / or time period specified by the user. Information regarding "Delivery" can be obtained, for example, by the search unit 111 applying a predetermined algorithm, such as text mining, to search target information (e.g., a product catalog) for searching for documents containing similar issues corresponding to the nodes in the solution layer 250 in step S302. It is preferable that the nodes in the solution layer 250 and information regarding "Delivery" be linked and managed.

[0071] In the example of Figure 5, the node with the highest second importance in relation to "Business Issue 1-2-1" is "Measure 1-2-1-2." Therefore, to resolve "Business Issue 1-2-1," it is desirable to implement "Measure 1-2-1-2." However, since the "Delivery" of "Solution 1-2-1-2-S1," which is directly connected to "Measure 1-2-1-2" by an edge, is "NG," "Solution 1-2-1-2-S1" cannot be provided in the region and / or at the time specified by the user, making it difficult to implement "Measure 1-2-1-2." Therefore, in this example, it is desirable to implement "Measure 1-2-1-1" and / or "Measure 1-2-1-3" to resolve "Business Issue 1-2-1." The issue organization tree 131 shown in Figure 5 may be displayed on the display device 150.

[0072] 6 is an explanatory diagram showing another example of the correlation calculation process in step S304. It is assumed that the correlation between nodes in the problem consolidation tree 1311 is known, and the correlation between nodes in the problem consolidation tree 1314 is unknown. In FIG. 6, layers other than the management problem layer 220 and the business problem layer 230 are omitted.

[0073] An example will be described in which the correlation calculation unit 114 calculates the correlation between a node 1315 in the management problem layer 220 and a node 1316 in the business problem layer 230 in the problem sorting tree 1314. The correlation calculation unit 114 sequentially selects combinations of nodes in the management problem layer 220 and nodes in the business problem layer 230 connected by edges in the problem sorting tree 1311 for which the correlation is known, and calculates a similarity c between the node 1315 (both of which are higher-level problem nodes) and the nodes in the management problem layer 220 in the selected combination, and a similarity d between the node 1316 (both of which are lower-level problem nodes) and the nodes in the business problem layer 230 in the selected combination. Note that the similarity c and the similarity d may be, for example, similarities between the problems indicated by the nodes (for example, similarities in the meanings of the problems or similarities in the character strings of the problems).

[0074] The correlation calculation unit 114 identifies, from among the combinations, the combination with the largest sum (which may be a weighted sum using a predetermined weight) of the calculated similarity c and similarity d. Here, it is assumed that the identified combination is node 1312 in the management issue layer 220 and node 1313 in the business issue layer, and that the similarity between node 1312 and node 1315 is c1, and the similarity between node 1313 and node 1316 is d1. It is also assumed that the correlation between node 1312 and node 1313 is "a-1-10."

[0075] At this time, the correlation calculation unit 114 calculates, for example, "b-1-21", which is the correlation between the node 1315 and the node 1316, by c1×c2×"a-1-10".

[0076] 6 illustrates an example in which the correlation between a node in the management issue layer 220 and a node in the business issue layer 230 is calculated, but the correlation between nodes in other adjacent layers can also be calculated in a similar manner. Also, in the example in FIG. 6, a known correlation between a node in the management issue layer 220 and a node in the business issue layer 230 is used to calculate the unknown correlation between the node in the management issue layer 220 and a node in the business issue layer 230. However, a known correlation between a layer other than the node for which the correlation is to be calculated may also be used, such as a known correlation between a node in the social issue layer 210 and a node in the management issue layer 220.

[0077] 7A to 7C, an example of calculating an index assigned to an assignment, which is different from the first and second importance levels, will be described. Fig. 7A is an explanatory diagram showing an example of an assignment organization tree 131 including information on the first and second importance levels and dates.

[0078] 7A omits layers other than the business problem layer 230, the policy layer 240, and the solution layer 250. In the example of FIG. 7A , information about the time period ("filing date" in the figure) is assigned to each node in the business problem layer 230. Here, it is assumed that patent documents are used as the information to be searched for corresponding to the business problem layer 230 in step S302.

[0079] As described above, in step S302, the search unit 111 searches for documents (here, patent documents) containing similar issues for each issue indicated by a node in the business issue layer 230. The importance calculation unit 113 extracts the earliest filing date of the patent related to the searched patent document for each issue and assigns it as information indicating the time period corresponding to the issue ("filing date" in the figure). Note that the importance calculation unit 113 may extract the latest filing date of the patent related to the extracted patent document for each issue instead of the earliest filing date, or may calculate the average filing date of the patent related to the extracted patent document.

[0080] FIG. 7B is an explanatory diagram showing an example of a process for assigning indicators related to advancedness and importance. An example of assigning the indicators will be explained using the information of the issue organization tree 131 in FIG. 7A. In the example of FIG. 7A, the first importance level of "Business Issue 1-2-2" is "19," and the application date assigned is "2023 / 1 / 3." Also, in the example of FIG. 7A, the first importance level of "Business Issue 1-3-1" is "73," and the application date assigned is "2012 / 12 / 25."

[0081] The importance calculation unit 113 determines that a task whose first importance is equal to or greater than a predetermined threshold is an important task (a task of high importance), and determines that a task whose first importance is less than the predetermined threshold is an ordinary task (a task of low importance). Here, for example, if the threshold is 50, then "Business Task 1-2-2" is an ordinary task, and "Business Task 1-3-1" is an important task.

[0082] Furthermore, the importance calculation unit 113 determines that an issue whose filing date is after a predetermined date is an advanced issue (an issue with high advancedness), and determines that an issue whose filing date is before the predetermined date is a conventional issue (an issue with low advancedness). Here, for example, if the predetermined date is 10 years before the current date and the current date is May 1, 2024, then "Business Issue 1-2-2" is an advanced issue and "Business Issue 1-3-1" is a conventional issue.

[0083] The importance calculation unit 113 may store information indicating whether each business task is an important task or an ordinary task, and information indicating whether each business task is an advanced task or a conventional task, in the memory 120 and / or the auxiliary storage device 130. When the task organization tree 131 is displayed on the display device 150, this information may also be displayed, for example, in association with the node corresponding to each business task.

[0084] 7C is an explanatory diagram showing another example of a process for assigning indicators related to advancedness and importance. An example of assigning the indicators will be described using the information in the issue organization tree 131 in FIG. 7A. In the example of FIG. 7A, the first importance level of "Measure 1-2-2-2," a sub-issue directly connected to "Business Issue 1-2-2" via an edge, is "41." Also, in the example of FIG. 7A, the first importance level of "Measure 1-3-1-1," a sub-issue directly connected to "Business Issue 1-3-1" via an edge, is "11."

[0085] At this time, the importance calculation unit 113 divides the importance of the target sub-task by the importance of the target super-task and calculates the value as an index indicating the advancedness and importance of the super-task in relation to the target sub-task. If the number of documents containing similar tasks to the target sub-task is large and the number of documents containing similar tasks to the target super-task is small, the value of this index will be large. In this case, it is likely that many people are trying to solve the sub-task in order to solve the super-task, so the larger the value of this index, the more important the super-task is considered to be in relation to the sub-task.

[0086] Furthermore, if the number of documents containing similar tasks to the target subtask is small and the number of documents containing similar tasks to the target super-task is large, the value of this index will be small. In this case, although the super-task is recognized by many people, it is highly likely that the sub-tasks that contribute to solving the super-task are not widely recognized. Therefore, the smaller the value of this index, the more advanced the super-task is considered to be in relation to the sub-tasks.

[0087] In this example, the index value of "Business issue 1-2-2" in relation to "Measure 1-2-2-2" is 2.2, and the index value of "Business issue 1-3-1" in relation to "Measure 1-3-1-1" is 0.15.

[0088] Furthermore, the importance calculation unit 113 may determine that the target higher-level task is an important task in relation to the target lower-level task when the value of the index is equal to or greater than a predetermined value, and may determine that the target higher-level task is an advanced task in relation to the target lower-level task when the value of the index is less than the predetermined value. For example, if the predetermined threshold is 1.0, then "Business Task 1-2-2" is an important task in relation to "Measure 1-2-2-2," and "Business Task 1-3-1" is an advanced task in relation to "Measure 1-3-1-1."

[0089] The importance calculation unit 113 may store information indicating the index value of the business issue in relation to the target measure, and information indicating whether the business issue is an important issue or an advanced issue in relation to the target measure, in the memory 120 and / or the auxiliary storage device 130. When the issue organization tree 131 is displayed on the display device 150, this information may also be displayed, for example, in association with the node corresponding to each business issue.

[0090] In addition, in the examples of Figures 7B and 7C, information regarding importance and advanced nature is assigned to business tasks in the business task layer 230, but indicators regarding importance and advanced nature can also be assigned to tasks in other layers using a similar method.

[0091] 8 is an example of information showing the analysis results of the impact that solutions in the solution layer 250 have on the issues in each layer. The search unit 111 may use a predetermined algorithm, such as text mining, to analyze the impact (e.g., effect) that each solution (product A to product C) in the solution layer 250 has on each issue in the social issue layer 210, the business issue layer 220, the business issue layer 230, and the policy layer 240 from a product catalog, which is information to be searched for corresponding to the solution layer 250, and then write the analysis results in a table such as that shown in FIG. 8 and store the results in the memory 120 or the auxiliary storage device 130.

[0092] 9 is an explanatory diagram showing an example of the issue organization tree 131 displayed on the display device 150 in step S308. In the example of FIG. 9, in accordance with the user's display guidelines, the first importance level is displayed only for the nodes in the business issue layer 230 and the policy layer 240, and the second importance level is displayed only for the nodes in the policy layer 240. Also, in accordance with the user's display guidelines, the display of the correlation value is omitted, but the correlation value may also be displayed. Furthermore, in the solution layer 250 node, a score indicating the company's superiority and whether "delivery" is OK or NG are displayed.

[0093] In the example of Figure 9, a node in the business issue layer 230 with a high first importance (for example, a node that is equal to or greater than a predetermined value, or the node that is the largest in the business issue layer 230) is displayed in a larger size than the other nodes in the business issue layer 230. Also, a node in the policy layer 240 with a high second importance (for example, a node that is equal to or greater than a predetermined value, or the node that is the largest in the policy layer 240) is displayed in a larger size than the other nodes in the policy layer 240. This allows the user to easily recognize which nodes in the business issue layer 230 and the policy layer 240 correspond to important issues. Also, for example, edges connecting nodes with a correlation degree equal to or greater than a predetermined value are displayed with thick lines, allowing the user to easily recognize which nodes have a high correlation degree.

[0094] Furthermore, in the solution layer 250, the borders of nodes for which "Delivery" is not possible are displayed with dotted lines, allowing the user to easily distinguish and recognize between solutions that can be provided in the area and / or time period specified by the user and those that cannot be provided.

[0095] Furthermore, in the solution layer 250, the borders of nodes where "Delivery" is OK and where the score indicating the company's superiority is high (for example, this may be above a predetermined value, or may be the highest score among the nodes in the solution layer 250 where "Delivery" is OK) are displayed in bold, so that the user can easily recognize the solutions that have a high company advantage among the solutions that can be provided in the region and / or time period specified by the user.

[0096] In addition, the first importance, second importance, and correlation level, as well as whether the ``delivery'' is OK or NG, may be expressed using any means, such as the thickness or color of the border lines of the nodes and edges, or the display size of the nodes.

[0097] Furthermore, the maximum number of subtasks that can be displayed for one higher-level task may be predetermined. If the maximum number is three, the number of nodes increases by a power of three for each subsequent layer, so that a maximum of three nodes in the business task layer 220 are displayed for one node in the social task layer 210. In this case, a first threshold value for the first importance and / or a second threshold value for the second importance may be predetermined, and the task organization tree 131 may display only nodes whose first importance is equal to or greater than the first threshold value and / or whose second importance is equal to or greater than the second threshold value. This reduces the number of nodes displayed on the display device 150, and only important nodes are displayed.

[0098] 10 is a diagram showing an example of the screen configuration of a display screen for comparing issues in different industries. Display screen 1000 is displayed on display device 150 by issue organization tree creation unit 115. Display screen 1000 includes, for example, display area 1001, display area 1002, and display area 1003.

[0099] Display area 1001 displays some of the nodes and edges of the problem sorting tree for industry A. Display area 1002 displays nodes included in the problem sorting tree for industry B, which is different from industry A, that indicate the same problem (or a similar problem) as the problem indicated by the node in the problem sorting tree for industry A.

[0100] An edge displayed with a thick line on the display screen 1000 is, for example, an edge with a high correlation (e.g., higher than a predetermined value), and a node displayed with a thick border is a node with a high first importance and / or second importance (e.g., higher than a predetermined value).

[0101] In addition, within each node of the display screen 1000, the number of documents containing similar issues used to calculate the first importance (here, the number of patent applications), information regarding the timing of the similar issues (here, the most recent application year (an indicator of the newness of the issue)), and information regarding the company's superiority (here, the proportion of the company's documents among documents containing similar issues) are displayed.

[0102] As described above, the display screen 1000 displays nodes related to the same issue in different industries, allowing the user to understand the higher-level and lower-level issues of the same issue in other industries, thereby providing hints for the company's expansion into other industries. For example, in the example of FIG. 10 , the issue indicated by node "A1-1" is the same as the issue indicated by node "B1-1." However, since there are many patent applications related to the issue in industry A, the first importance of node "A1-1" is high. However, since there are few patent applications related to the issue in industry B, the first importance of node "B1-1" is low. Therefore, the user can understand that the issue indicated by node "B1-1," which is the same as node "A1-1" and is considered an important issue in industry A, is not currently considered an important issue in industry B, but is likely to be considered an important issue in the future.

[0103] Furthermore, by displaying the display area 1001, the user can easily compare the number of patent applications related to the higher-level issue with the number of patent applications related to the lower-level issue. For example, if the number of patent applications related to the higher-level issue is greater than the number of patent applications related to the lower-level issue, it is likely that not many specific issues, measures, solutions, etc. for solving the higher-level issue have been provided. Also, for example, if the number of patent applications related to the lower-level issue is greater than the number of patent applications related to the higher-level issue, it is likely that many people are working on solving the higher-level issue and that the higher-level issue is perceived as a major issue.

[0104] Furthermore, the search unit 111 may acquire the annual change in the number of documents containing the similar task used in calculating the first importance, and the annual change is displayed in the display area 1002. Furthermore, when a node is selected on the display screen 1000, a radar chart may be displayed. In the example of Fig. 10, a node in the display area 1003 is selected and a radar chart is displayed. The radar chart shows, for example, various scores used in calculating the first importance.

[0105] The present invention is not limited to the above-described embodiments, but includes various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, or to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is possible to add, delete, or replace part of the configuration of each embodiment with other configurations.

[0106] Furthermore, the above-described configurations, functions, processing units, processing means, etc. may be partially or entirely implemented in hardware, for example, by designing them as integrated circuits. The above-described configurations, functions, etc. may also be implemented in software, with a processor interpreting and executing a program that implements each function. Information such as the program, table, and file that implements each function can be stored in a memory, a recording device such as a hard disk or SSD (Solid State Drive), or a recording medium such as an IC card, SD card, or DVD.

[0107] In addition, the control lines and information lines shown are those that are considered necessary for the explanation, and do not necessarily show all the control lines and information lines in the product. In reality, it can be assumed that almost all components are interconnected.

Claims

1. A task evaluation device comprising a processor and memory, wherein the memory holds a task organization tree defined by a tree structure including nodes related to tasks arranged in each of a plurality of task layers and edges connecting nodes in adjacent task layers, wherein the task evaluation device is connected to a plurality of search target databases, each of which includes a plurality of documents, wherein each of the plurality of task layers is pre-assigned to one of the plurality of search target databases, and wherein at least some of the task layers are assigned to different search target databases, wherein the processor, for each of the plurality of task layers, searches the search target database associated with that task layer for documents including tasks similar to tasks indicated by nodes included in that task layer, calculates a first importance of each of the tasks based on the search results of the documents, and generates data for displaying the task organization tree in which the first importance is linked to the nodes.

2. An assignment evaluation device as described in claim 1, wherein the processor calculates the first importance based on the number of documents containing the similar assignment or the total number of occurrences of the similar assignment in documents containing the similar assignment.

3. An assignment evaluation device as described in claim 1, wherein the processor, for a combination of nodes connected by the edges, searches a search target database associated with the assignment layer in which each of the nodes included in the combination is located for documents that include both of the similar assignments to the assignment indicated by the nodes included in the combination, calculates the correlation of the nodes included in the combination based on the search results for documents that include both of the similar assignments to the assignment included in the combination, calculates a second importance of each of the assignments based on the first importance and the correlation, and generates data for displaying the assignment organization tree in which the correlation is linked to the edges and the second importance is linked to the nodes.

4. An assignment evaluation device as described in claim 3, wherein the processor calculates the degree of correlation based on the number of documents that contain both of the similar assignments to the assignments included in the combination, or the total number of occurrences of the similar assignments in documents that contain both of the similar assignments to the assignments included in the combination.

5. An assignment evaluation device as described in claim 3, wherein the memory holds information indicating known degrees of correlation between combinations of nodes included in other assignment organization trees, calculates the similarity between the combinations and combinations of nodes indicating the known degrees of correlation, and calculates the degrees of correlation based on the calculated similarity and the known degrees of correlation.

6. An assignment evaluation device as described in claim 3, wherein the processor, in the data for displaying the assignment organization tree, draws the assignment organization tree so that the relative magnitude of the first importance and the second importance is indicated by at least one of the display size, border thickness, and border color of the nodes, and draws the assignment organization tree so that the relative magnitude of the correlation is indicated by at least one of the border thickness and color of the edges.

7. An assignment evaluation device as described in claim 3, wherein the processor draws, in the data for displaying the assignment organization tree, nodes whose first importance is equal to or greater than a first threshold and / or whose second importance is equal to or greater than a second threshold, and edges connecting the nodes.

8. An assignment evaluation device as described in claim 1, wherein the processor: acquires information indicating the time period related to the similar assignment from a document containing the similar assignment; compares the time period indicated by the acquired information with a predetermined time period to determine whether each of the assignments is an advanced assignment or a conventional assignment; and compares the first importance level with a predetermined value to determine whether each of the assignments is an important assignment or an ordinary assignment.

9. A task evaluation device as described in claim 1, wherein the processor calculates a value by dividing the first importance of the task indicated by the node placed in the lower task layer in the combination of nodes connected by the edges by the first importance of the task indicated by the node placed in the higher task layer, and if the calculated value is equal to or greater than a predetermined value, determines that the task indicated by the node placed in the higher task layer is an important task, and if the calculated value is less than the predetermined value, determines that the task indicated by the node placed in the higher task layer is an advanced task.

10. A task evaluation device as described in claim 1, which indicates that the achievement of a task indicated by a node in the task organization tree contributes to the achievement of a task indicated by a node located in the task layer above the node and connected to the node by the edge.

11. A problem evaluation device as described in claim 10, wherein the multiple problem layers include: a social problem layer indicating social problems; a management problem layer which is the problem layer one level below the social problem layer and indicates management problems; a business problem layer which is the problem layer one level below the management problem layer and indicates business problems; a policy layer which is the problem layer one level below the business problem layer and indicates measures for the business problems; and a solution layer which is the problem layer one level below the policy layer and indicates solutions to be introduced in the measures.

12. A problem evaluation device as described in claim 11, wherein the search target databases associated with the social problem layer and the management problem layer include databases in which documents indicating management information are stored, the search target databases associated with the business problem layer and the measures include databases in which patent documents are stored, and the search target databases associated with the solution layer include databases in which product catalogs are stored.

13. A method of evaluating tasks using a task evaluation device, wherein the task evaluation device comprises a processor and memory, the memory holds a task organization tree defined by a tree structure including nodes related to tasks arranged in each of a plurality of task layers and edges connecting nodes in adjacent task layers, the task evaluation device is connected to a plurality of search target databases, each of which includes a plurality of documents, and each of the plurality of task layers is pre-assigned to one of the plurality of search target databases, and at least some of the task layers are assigned to different search target databases, the task evaluation method comprising the steps of: the processor, for each of the plurality of task layers, searches the search target database associated with that task layer for documents containing tasks similar to tasks indicated by nodes included in that task layer; the processor calculates a first importance of each of the tasks based on the search results for the documents; and the processor generates data for displaying the task organization tree in which the first importance is linked to the nodes.

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