Information processing system, information processing method and program

Abstract

An information processing system, method, and program are provided that improve convenience when considering M&A. [Solution] The method includes displaying a first input format for inputting first project information related to a transaction between an organization and a trading partner, accepting input of the first project information into the first input format from a seller of the organization or an entity acting on its behalf, controlling the display so that the first project information is not displayed to a buyer of the organization, and accepting input of second project information into a second input format for inputting second project information from the seller. The second input format is capable of accepting input of information relating to items not included in the first input format as at least part of the second project information, displaying the second input format with at least part of the first project information transcribed into corresponding input fields in the second input format, and controlling the display so that at least part of the second project information is displayable to the buyer after the second project information is input.

Description

[Technical Field]

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

[0002] Conventionally, techniques have been developed to support mergers and acquisitions (M&A) of organizations, etc. For example, Patent Document 1 discloses a device for realizing an M&A matching service. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2017-78985 A Summary of the Invention [Problem to be solved by the invention]

[0004] On the other hand, there is room for improvement in convenience when considering such M&A.

[0005] In view of the above circumstances, the present invention provides an information processing system and the like that can improve convenience when considering M&A. [Means for solving the problem]

[0006] According to one aspect of the present invention, there is provided an information processing system, comprising at least one processor, the processor being configured to execute the following steps by reading a program: a first reception step displays a first input format for inputting first project information relating to a transaction of an organization that is a trading target, and receives input of the first project information into the first input format from a seller of the organization or an entity acting on behalf of the seller; a first display control step controls so that the first project information is not displayed to a buyer of the organization; and a second reception step displays a second input format for inputting second project information. An information processing system is provided which accepts input of second project information into a second input format from a seller of an organization or an entity acting on behalf of the seller, wherein the second input format is capable of accepting input of information relating to items not included in the first input format as at least part of the second project information, and in a second reception step, displays the second input format in a manner in which at least part of the first project information is transcribed into corresponding input fields of the second input format, and in a second display control step, controls so that after the second project information has been input, at least part of the second project information can be displayed to a buyer.

[0007] According to this aspect, an information processing system or the like is provided that can improve convenience when considering M&A. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a configuration diagram illustrating an information processing system 1. FIG. [Figure 2] 2 is a block diagram showing the hardware configuration of the server device 10. FIG. [Figure 3] FIG. 2 is a block diagram showing the hardware configuration of the user terminal 20. [Figure 4] 1 is a block diagram showing functions realized by a server device 10 (controller 11) and a user terminal 20 (controller 21). [Figure 5] FIG. 2 is an activity diagram for explaining information processing according to the present embodiment. [Figure 6]10 is an example of a screen displayed on a seller agent terminal. [Figure 7] 10 is an example of a screen displayed on a seller agent terminal. [Figure 8] 10 is an example of a screen displayed on a seller agent terminal. [Figure 9] 10 is an example of a screen displayed on a seller agent terminal. [Figure 10] 10 is an example of a screen displayed on a seller agent terminal. [Figure 11] 10 is an example of a screen displayed on a seller agent terminal. [Figure 12] 10 is an example of a screen displayed on a seller agent terminal. [Figure 13] 10 is an example of a screen displayed on a seller agent terminal. [Figure 14] 10 is an example of a screen displayed on a seller agent terminal. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, embodiments of the present invention will be described. Note that various features shown in the following embodiments can be combined with each other.

[0010] That is, the information processing system of this embodiment is as follows. An information processing system, at least one processor; The processor is configured to execute the following steps by reading the program: In the first receiving step, a first input format for inputting first case information relating to a transaction of an organization that is a transaction target is displayed, and input of the first case information into the first input format is received from a seller of the organization or an entity acting on behalf of the seller; In the first display control step, the first project information is controlled so as not to be displayed to buyers of the organization; In the second receiving step, a second input format for inputting second project information is displayed, and input of the second project information into the second input format is received from a seller of the organization or an entity acting on behalf of the seller; wherein the second input format is capable of accepting input of information relating to items not included in the first input format as at least a part of the second case information; In the second receiving step, the second input format is displayed in a state in which at least a part of the first case information is transcribed into a corresponding input field of the second input format; In the second display control step, after the second project information is input, the information processing system controls so that at least a part of the second project information can be displayed to the buyer.

[0011] Incidentally, the program for realizing the software appearing in one embodiment may be provided as a non-transitory computer-readable medium, or may be provided so that it can be downloaded from an external server, or may be provided so that the program is started on an external computer and its functions are realized on a client terminal (so-called cloud computing).

[0012] Furthermore, various information processing according to an embodiment may realize input and output corresponding to the input. Here, the form of information referenced in such information processing (hereinafter referred to as reference information) is not limited as long as an output is obtained as a result of the input. The reference information may be, for example, rule-based information such as a database, a lookup table, or a predetermined function (including a decision formula such as a regression formula constructed using a statistical method), a trained model that has previously learned the correlation between input and output, or a generative AI such as a large-scale language model (these models include parameters that establish the correlation between input and output) or a visual language model that can output a desired result in response to a prompt.

[0013] In one embodiment, a "unit" may include, for example, a combination of hardware resources implemented by a circuit in the broad sense and software information processing that can be specifically realized by these hardware resources. In one embodiment, various information is handled, and this information is represented, for example, by physical values ​​of signal values ​​representing voltage and current, high and low signal values ​​as a binary bit set consisting of 0 or 1, or quantum superposition (so-called quantum bits), and communication and calculations can be performed on a circuit in the broad sense.

[0014] Furthermore, a circuit in the broad sense is a circuit realized by at least an appropriate combination of a circuit, circuitry, processor, memory, etc. The processor may be a general-purpose processor or a dedicated circuit. That is, it includes an application specific integrated circuit (ASIC), a programmable logic device (e.g., a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA)), etc.

[0015] 1. Hardware Configuration This section explains the hardware configuration.

[0016] Fig. 1 is a configuration diagram showing an information processing system 1. Fig. 1 shows an information processing system 1 including a communication line 2, a server device 10, and a plurality of user terminals 20. The server device 10 and each user terminal 20 are configured to be able to communicate with each other via the communication line 2. The connection between the server device 10 and each user terminal 20 may be wired or wireless.

[0017] The information processing system 1 may constitute at least a part of an M&A (Merger & Acquisitions) system used by, for example, the seller and buyer of a transaction target organization. In this specification, the term "seller" may be used to refer to both the seller of the organization and the person acting on behalf of the seller (seller agent). In addition, in a transaction involving an organization, both the buyer and the person acting on behalf of the buyer (buyer agent) may be involved. In this specification, unless otherwise specified, these are collectively referred to as "buyers." In the example shown in FIG. 1, seller U1 and seller agent U2 are shown as users involved in the information processing system 1, and these users correspond to users on the "seller side." In the example shown in FIG. 1, first buyer U3 and second buyer U4 are shown as users involved in the information processing system 1, and these users correspond to users on the "buyer side." As an example, the second buyer U4 will be described herein as an entity acting on behalf of a specific buyer (buyer U3). In this embodiment, the information processing system 1 mainly performs functions such as registering organizations with which a seller user is to transact, searching for organizations with which a buyer user is to transact, and mediating communication between buyer and seller users. For example, the information processing system 1 provides and manages an M&A matching platform (which may be referred to as an "organization transaction platform") and M&A matching services used by buyer and seller users.

[0018] In one embodiment, the information processing system 1 is comprised of one or more devices or components. For example, the information processing system 1 may include a server device (e.g., server device 10) having a processor (e.g., control unit 11) and a terminal (e.g., user terminal 20) that can access the server. These components will be described below.

[0019] <Server device 10> Fig. 2 is a block diagram showing the hardware configuration of server device 10. As shown in Fig. 2, server device 10 includes a control unit 11, a storage unit 12, a communication unit 13, and a communication bus 14. Control unit 11, storage unit 12, and communication unit 13 are electrically connected within server device 10 via communication bus 14.

[0020] <Control unit 11> The control unit 11 processes and controls the overall operations related to the server device 10. The control unit 11 is, for example, a central processing unit (CPU). The control unit 11 realizes various functions related to the server device 10 by reading out predetermined programs stored in the storage unit 12. In other words, information processing by software stored in the storage unit 12 is specifically realized by the control unit 11, which is an example of hardware, and can be executed as each functional unit included in the control unit 11. These will be described in more detail in the next section. Note that the control unit 11 is not limited to being a single unit, and the server device 10 may have multiple control units 11 for each function. Furthermore, the server device 10 may be configured with a combination of these.

[0021] <Storage section 12> The memory unit 12 stores various pieces of information defined above. This can be implemented, for example, as a storage device such as a solid state drive (SSD) that stores various programs and the like related to the server device 10 executed by the control unit 11, or as a memory such as a random access memory (RAM) that stores temporarily required information (arguments, arrays, etc.) related to the program operations. The memory unit 12 stores various programs, variables, etc. related to the server device 10 executed by the control unit 11.

[0022] <Communications Department 13> The communication unit 13 is preferably a wired communication means such as USB, IEEE1394, Thunderbolt (registered trademark), or wired LAN network communication, but may also include wireless LAN network communication, mobile communication such as LTE / 5G, or BLUETOOTH (registered trademark) communication as needed. That is, it is more preferable to implement it as a collection of multiple communication means. That is, the server device 10 may communicate various information from the outside via the communication unit 13 and the network.

[0023] The server device 10 may be an on-premise server or a cloud server. The cloud server device 10 may provide the above-described functions and processes in the form of, for example, SaaS (Software as a Service) or cloud computing.

[0024] <User terminal 20> Fig. 3 is a block diagram showing the hardware configuration of user terminal 20. This user terminal 20 is a terminal used by the various users (buyer users and seller users) mentioned above. As shown in Fig. 3, user terminal 20 includes a control unit 21, a memory unit 22, a communication unit 23, an input unit 24, an output unit 25, and a communication bus 26. Control unit 21, memory unit 22, communication unit 23, input unit 24, and output unit 25 are electrically connected via communication bus 26 inside user terminal 20. Description of control unit 21, memory unit 22, and communication unit 23 will be omitted as they are the same as the descriptions of the respective units in server device 10.

[0025] <Input section 24> The input unit 24 accepts operation inputs made by the user. The operation inputs are transferred as command signals to the control unit 21 via the communication bus 26. The control unit 21 can execute predetermined control or calculations based on the transferred command signals as necessary. The input unit 24 may be included in the housing of the user terminal 20 or may be attached externally. For example, the input unit 24 may be implemented as a touch panel integrated with the output unit 25. When the input unit 24 is implemented as a touch panel, the user can input tap operations, swipe operations, etc. to the input unit 24. Instead of a touch panel, a switch button, a mouse, a trackpad, a QWERTY keyboard, etc. can be used as the input unit 24.

[0026] <Output section 25> The output unit 25 displays a screen of a graphical user interface (GUI) that can be operated by the user. The output unit 25 may be included in the housing of the user terminal 20 or may be attached externally. Specifically, the output unit 25 may be implemented as a display device such as a CRT display, a liquid crystal display, an organic EL display, or a plasma display. It is preferable that these display devices are used appropriately depending on the type of user terminal 20.

[0027] 1 shows an example in which the user terminal 20 is a laptop PC (Personal Computer), but in this embodiment, there is no particular limitation on the type of terminal of the user terminal 20. That is, each user terminal 20 may be various information processing terminals such as a desktop PC, a laptop PC, a smartphone, a tablet terminal, etc.

[0028] 2. Functional configuration This section describes the functional configuration of this embodiment. Information processing by software stored in the storage unit 12 is specifically realized by the control unit 11, which is an example of hardware, and can be executed as each functional unit included in the control unit 11 (a processor provided in the information processing system 1).

[0029] FIG. 4 is a block diagram showing functions realized by the server device 10 (controller 11) and the user terminal 20 (controller 21).

[0030] 4A, the server device 10 (control unit 11) may include a registration unit 110, a reception unit 111, a display control unit 112, an information generation unit 113, a notification unit 114, a presentation unit 115, a memory management unit 116, and an artificial intelligence unit 117. As shown in FIG. 4B, the user terminal 20 (control unit 21) may include a display control unit 210 and an operation reception unit 211.

[0031] <Registration Unit 110> The registration unit 110 is configured to be able to execute a registration step. In the registration step, the registration unit 110 performs user registration and case registration for the platform (organization transaction platform) provided by the information processing system 1. In the example of this embodiment, the registration unit 110 registers one or more of the seller U1, seller agent U2, first buyer U3, and second buyer U4 as users of the platform (organization transaction platform). Also, in the example of this embodiment, the registration unit 110 registers information about the organization to be traded as a "(transaction) case." The information registered by the registration unit 110 may be stored in a predetermined memory area by the function of the memory management unit 116, which will be described later.

[0032] <Reception Department 111> The reception unit 111 is configured to execute a reception step. In the reception step, the reception unit 111 receives various pieces of information related to the information processing system 1. In the example of this embodiment, in the first reception step, the reception unit 111 displays a first input format for inputting first project information related to a transaction of an organization that is a trading target, and receives input of the first project information into the first input format from a seller U1 of the organization or an entity acting on behalf of the seller (seller agent U2). In addition, in the example of this embodiment, in the second reception step, the reception unit 111 displays a second input format for inputting second project information and receives input of the second project information into the second input format from a seller U1 of the organization or an entity acting on behalf of the seller (seller agent U2). Here, the second input format can receive input of information related to items not included in the first input format as at least part of the second project information. In addition, in the second reception step, the second input format is displayed in a manner in which at least part of the first project information is transcribed into corresponding input fields of the second input format. Details of these various reception steps will be explained later.

[0033] <Display control unit 112> The display control unit 112 is configured to execute a display control step. In the display control step, the display control unit 112 controls whether visual information is displayed on each user terminal 20. In addition, in the display control step, the display control unit 112 generates various display information and controls the display content visible to the user. Note that the display information may be information itself generated in a form visible to the user, such as a screen, image, icon, text, etc., or may be rendering information for displaying a screen, image, icon, text, etc. on various terminals. In this embodiment, the display control unit 112 controls the first project information so that it is not displayed to buyers (first buyer U3 and second buyer U4) of the organization. In this embodiment, after second project information is input, the display control unit 112 controls the second project information so that at least a portion of the second project information is displayable to buyers (first buyer U3 and second buyer U4). The content that can be displayed on the user terminal 20 will be explained later.

[0034] <Information generation unit 113> The information generation unit 113 is configured to be able to execute an information generation step. In the information generation step, the information generation unit 113 generates various pieces of information based on the information acquired by the server device 10. As an example, the information generation unit 113 generates sentences, documents, etc. based on the acquired information. The specific content generated by the information generation unit 113 will be explained later.

[0035] <Notification section 114> The notification unit 114 is configured to be able to execute a notification step. In the notification step, the notification unit 114 issues various notifications to the various user terminals 20, etc. Specific aspects of the notifications will be described later.

[0036] <Presentation part 115> The presentation unit 115 is configured to be able to execute a presentation step. In the presentation step, the presentation unit 115 presents predetermined information to various users. In this embodiment, when content is entered into the first input field by a seller U1 of the organization or an entity acting on behalf of the seller (seller agent U2), one or more options related to the content are presented. Details of the presented content will be explained later.

[0037] <Storage management section 116> The memory management unit 116 is configured to be able to execute a memory management step. In the memory management step, the memory management unit 116 manages various pieces of information related to the information processing system 1 that should be stored. Typically, the memory management unit 116 is configured to store information handled by the server device 10, various terminals, etc. in a memory area. This memory area is exemplified by the memory area (memory unit 12) provided in the server device 10 or the memory areas of various devices, but this memory area does not necessarily have to be within the system shown in FIG. 1, and the memory management unit 116 can also manage various pieces of information to be stored in an external storage device, etc.

[0038] <Artificial Intelligence Department 117> The artificial intelligence unit 117 is configured to receive input from each functional unit and return the instructed output. The artificial intelligence used by the server device 10 in each functional unit may be a common one, or may be prepared individually for each functional unit.

[0039] The artificial intelligence unit 117 is an AI (Artificial Intelligence) equipped with a learning model such as a language model such as a Transformer including GPT (Generative Pretrained Transformer, including GPT-1, GPT-2, GPT-3, and GPT-4), BERT (Bidirectional Encoder Representations from Transformers), BART (Bidirectional and Auto-regressive Transformer), or a Recurrent Neural Network (RNN), and may include a generative AI or an AI agent. The learning model may also be called an artificial intelligence model, a machine learning model, or a trained model.

[0040] The language model is an example of a learning model based on a machine learning algorithm. Specific examples of machine learning algorithms include nearest neighbor methods, naive Bayes methods, decision trees, support vector machines, and deep learning using neural networks. The artificial intelligence unit 117 can apply the above algorithms as appropriate.

[0041] The artificial intelligence unit 117 may have a trained model constructed by a learning method such as supervised learning, unsupervised learning, or self-supervised learning. In supervised learning, machine learning is performed using training data (training data). The training data consists of pairs of input data for learning and output data (correct answer data). In addition, the language model may not only be trained for a specific task, but also be a general-purpose model that can be used for a wide range of tasks.

[0042] The artificial intelligence unit 117 may use a natural language model as the artificial intelligence, or may include a general-purpose natural language processing trained model such as a large-scale language model (LLM) trained on a huge amount of data. An LLM is a learning model trained in advance on a large amount of data, such as text data (e.g., (i) web content on the Internet, or (ii) data stored in a specified database). It can perform various language processing tasks when given a task, and can perform a wide range of natural language processing tasks, such as understanding sentence patterns and context, answering questions, and generating sentences, according to given prompts. Such a general-purpose learning model may include a language model that can handle various tasks without fine-tuning, using one-shot learning or few-shot learning. Furthermore, a general-purpose learning model can also handle various tasks using zero-shot learning. The artificial intelligence used in each functional unit of the control unit 11 may be a separate learning model, or a common general-purpose learning model. A large-scale language model is a type of generative AI and includes models provided by services such as OpenAI's GPT, Google's Gemini, and Microsoft's Azure AI Studio. Furthermore, the artificial intelligence unit 117 may include, as artificial intelligence, a small-scale language model or a medium-scale language model that is smaller in scale than a large-scale language model. The small-scale language model and the medium-scale language model are natural language processing models that are trained based on less data than the large-scale language model. In addition, the artificial intelligence unit 117 may include any machine learning model, deep learning model, artificial intelligence model, etc. The artificial intelligence unit 117 may be constructed in a system external to the information processing system 1. Furthermore, the artificial intelligence unit 117 may be of an interactive type (which may be interpreted as a chat type or a conversation type) that alternately receives input for performing instructed output and generates and outputs information.

[0043] The learning model included in the artificial intelligence unit 117 can perform additional learning using techniques such as transfer learning or fine tuning. For example, the artificial intelligence unit 117 learns whether the output content has been modified by a user or the like. That is, the artificial intelligence unit 117 may perform additional learning and fine tuning based on modifications to the content output by the learning model. Furthermore, for example, each time new data is registered, the artificial intelligence unit 117 may perform additional learning and fine tuning using the new data as new training data. This improves the accuracy of the information output from the learning model.

[0044] The learning model included in the artificial intelligence unit 117 may be a learning model (distilled model) obtained by knowledge distillation using an original trained model. In knowledge distillation, a trained model such as a large-scale language model is used as a teacher model, and the parameters of the student model are adjusted to reduce the output loss (Soft Target Loss) of the student model (distilled model) relative to the output (Soft Target) of the teacher model, thereby learning the student model, which becomes the distilled model. Alternatively, the student model may be trained to reduce the output loss (Hard Target Loss) of the student model relative to the correct label (Hard Target) of the teacher data (a combination of input data and output data of the learning model). Compared to the original trained model (teacher model), the distilled model has a smaller number of parameters and a smaller processing load while maintaining performance close to that of the trained model. Therefore, using a distilled model can reduce the cost of the information processing system 1.

[0045] For example, the learning model used in each functional unit may be a distilled model trained using a combination of input data and output data in a large-scale language model as training data. Furthermore, when the information processing system 1 is introduced, a large-scale language model may be used as the learning model used in each functional unit, and when training data from the large-scale language model is accumulated, a distilled model obtained by knowledge distillation using the training data may be used as the learning model used in each functional unit.

[0046] AI agents may also be called autonomous agents. An "AI agent" is a model that, when given a goal (purpose, objective, etc.) such as "teach me XX" or a task such as "output XX," breaks down the processing required to reach the goal or accomplish the task into subtasks, actions, etc., and performs tasks such as collecting and analyzing necessary data, generating and executing programs, etc. AI agents target information and instructions input by a user, autonomously select and execute tasks and actions according to the goal, and output information according to the goal, without requiring user intervention (operational input). AI agents may also autonomously learn to achieve their goals by autonomously creating and executing plans and evaluating the results. For example, an AI agent may be autonomously updated based on the results of subtask execution (e.g., collected information, information analysis results, etc.).

[0047] <Display control unit 210> The display control unit 210 of the user terminal 20 controls the display of a screen indicated by the screen data transmitted from the server device 10.

[0048] <Operation Reception Unit 211> The operation reception unit 211 of the user terminal 20 receives operations by users who use the user terminal 20 (seller U1, seller agent U2, first buyer U3, second buyer U4, etc.).

[0049] 3. Information Processing Method In this section, an information processing method for the server device 10 will be described with examples. This information processing method may be executed as each step by each unit of the server device 10. Note that the various features described in this section can be combined with each other as long as no technical contradiction occurs.

[0050] 5 is an activity diagram for explaining information processing of this embodiment. As described above, in the information processing method of this embodiment, input of first project information into a first input format is accepted from a seller U1 of the organization or an entity acting on behalf of the seller (seller agent U2). When accepting such first project information, the server device 10 displays a first input format for inputting the first project information to the seller U1 of the organization or an entity acting on behalf of the seller (seller agent U2).

[0051] The display of such a first input format is performed, for example, when seller U1 or seller agent U2 makes a display request for the first input format (activities A101 to A104). Then, predetermined information (first project information) is input into the first input format displayed to seller U1 or seller agent U2, and the receiving unit 111 of server device 10 receives the first project information (activities A105 to A106). Note that in FIG. 5, the terminal used to request the display of the first input format and input the first project information is referred to as a "seller agent terminal," but the terminal here may be appropriately interpreted as a "seller terminal" operated by seller U1.

[0052] An example of the first input format displayed on a seller agent terminal or the like will be described with reference to the accompanying drawings. FIG. 6 is an example of a screen displayed on a seller agent terminal. In a typical embodiment, the first input format may be configured to allow various items to be input. The first case information may include input items for items that can be input in this first input format. The items that can be input in the first input format may be selected as appropriate, and may include, for example, the following items. That is, the reception unit 111 of this embodiment may receive input of at least one of information on the transaction summary, the location of the organization, the status of acceptance of the transaction, and the person in charge of the transaction as the first case information.

[0053] The screen shown in FIG. 6 is configured so that various items such as "Project Title," "Industry," "Location (Prefecture)," and "Contact Person" can be input as forms F1 to F4. Furthermore, in the "Assignment" item, it is possible to select whether or not to accept the assignment for the sale of the organization based on the operation of object OBJ1. Furthermore, in the "Request for Information Creation" item, it is possible to select whether or not to create predetermined information based on whether or not check box CB1 is checked. Details of the various items provided in this first input format will be explained in conjunction with the explanation of FIG. 7 below. A user (such as seller's agent U2) viewing the screen shown in FIG. 6 can enter information into the various items and then press button BT1 to proceed with the operation of having the first project information accepted by the accepting unit 111.

[0054] Fig. 7 is an example of a screen displayed on the seller agent terminal. The screen shown in Fig. 7 is the screen to which the screen transitions when button BT1 is pressed after various information has been entered into the first input format shown in Fig. 6. A user (seller agent U2, etc.) who sees Fig. 7 can have the information entered into the first input format accepted by the accepting unit 111 as first case information by pressing button BT2 after checking the various information shown on the screen of Fig. 7.

[0055] The item "Project Title" shown in Figure 7 corresponds to the item for form F1 on the screen of Figure 6. Here, the "Project Title" is entered as a title or the like to describe the organization to be sold. Note that such a "Project Title" does not necessarily have to be information that indicates a specific organization, but may indicate an overview of the organization to be sold. The "Transaction Overview" that may be included in the first project information may correspond, for example, to the input information for this "Project Title" item.

[0056] The "Industry" item shown in FIG. 7 corresponds to the item for Form F2 on the screen of FIG. 6. Here, "Industry" may be information indicating the category or attributes of the organization to be sold. This "Industry" item may be entered by the user in text format, or may be entered (selected) using pre-prepared tags (e.g., tag TG1), as shown in FIG. 7. For example, when Form F2 is operated, a group of such tags may be presented to the seller U1 or the seller's agent U2, and the tags to be entered into Form F2 may be determined based on the seller U1 or the seller's agent U2's selection of a portion of this group of tags. When entering the "Industry" item using such tags, a means for assisting such input may be employed as appropriate; this point will be explained later.

[0057] The item "Location (Prefecture)" shown in Figure 7 corresponds to the item for form F3 on the screen of Figure 6. The "Location of organization" that may be included in the first case information may correspond, for example, to the input item for this "Location (Prefecture)" item. Note that Figures 6 and 7 show a mode in which input is requested on a prefecture-by-prefecture basis for the location of the organization, but input may be requested in a different unit. As an example, a mode in which input is requested on a city, ward, town, or village basis for the "Location of organization" in the first case information may be adopted.

[0058] The item "Assigned" shown in Figure 7 corresponds to the item associated with object OBJ1 on the screen of Figure 6. Here, "Assigned" may indicate, for example, if the person entering the first input format is seller's agent U2, whether or not he or she has been entrusted by the organization that is the subject of the sale with selling the organization. The "Assigned status for the transaction" that may be included in the first case information may correspond, for example, to the input item (selection item) for this "Assigned" item.

[0059] The "Contact Person" field in FIG. 7 corresponds to the field for form F4 on the screen in FIG. 6. For example, this "Contact Person" may refer to a specific person at seller's agent U2 who is responsible for the sale of the organization. The "Contact Person" that may be included in the first case information may correspond to, for example, the input information for this "Contact Person" field.

[0060] The item "Request for information creation" shown in Fig. 7 corresponds to the item associated with check box CB1 on the screen of Fig. 6. As will be described in detail later, in this embodiment, various information may be created after the first case information is accepted. The person entering the first input format can choose whether or not to accept such information as appropriate.

[0061] The "Project Page" item shown in FIG. 7 may indicate the URL (Uniform Resource Locator) of a web page created upon receiving the first project information. Such a URL may include a parameter for identifying the project registered by the seller U1 or the seller's agent U2. In other words, the server device 10 may generate a URL corresponding to the first project information upon receiving the first project information from the seller U1 or the seller's agent U2. The web page corresponding to such a URL may contain information about the organization that is the subject of the transaction (e.g., input items in the first input format, etc.). Such a web page may be configured so that the information displayed can be edited when accessed by the seller U1 or the seller's agent U2. Meanwhile, such a web page may be configured so that various buyers can view it under certain conditions.

[0062] In this way, the first project information received by the server device 10 is appropriately associated with the user who input the information and registered (activity A107). In an exemplary embodiment, the registration unit 110 of the server device 10 associates the received first project information with the user who input the first project information (seller U1 or seller agent U2) and stores the data in a predetermined storage area. The registered information may then be appropriately displayed on the seller agent terminal, etc. (activity A108).

[0063] In this embodiment, the display control unit 112 controls the first project information so that it is not displayed to buyers of the organization. That is, although it was previously mentioned that the input items to be entered into the first input format may be posted on the web page indicated in the "Project Page" item, such a web page may be made inaccessible to buyers (first buyer U3, second buyer U4, etc.) at the time the first project information is accepted.

[0064] In one aspect, when the first case information is received, the registration unit 110 of the server device 10 can register the case related to the first case information as a case in a first status. The first status here may be a status in which the first case information has been received and the second case information, which will be described later, has not been received. In a typical example, when the seller U1 or the seller's agent U2 registers a case regarding an organization that is the subject of a transaction as a case in this first status, the information about the case may be made inaccessible to the buyer.

[0065] Due to the effort and burden of registering a transaction target organization as a transaction in the information processing system 1, the seller U1 or seller agent U2 may not register the transaction target organization or may take a long time to register the transaction target organization. In contrast, in this embodiment, as described below, even when the transaction target organization is registered as a transaction target with a first status, the seller U1 or seller agent U2 may be configured to acquire various information. By registering a relatively small amount of information, the seller U1 or seller agent U2 can enjoy the benefits of registering the transaction target organization, thereby increasing their motivation to register the organization as a transaction target organization. More typically, by registering the transaction target organization as a transaction target organization, the seller U1 or seller agent U2 may obtain information useful for considering the sale of the organization. This allows the seller U1 or seller agent U2 to more efficiently proceed with the consideration of the organization sale.

[0066] Note that when accepting the first project information using the first input format, various functions for supporting input may be employed. For example, in this embodiment, the following aspect may be employed. That is, the first input format may have a first input field. When content is entered into the first input field by a seller U1 of the organization or an entity acting on behalf of the seller (seller agent U2), the accepting unit 111 of the server device 10 may present one or more options related to the content. Then, when the seller U1 of the organization or an entity acting on behalf of the seller (seller agent U2) selects one of the one or more options, the accepting unit 111 of the server device 10 may accept information related to the selected option as at least part of the first project information.

[0067] This input support function will be explained using FIG. 8. FIG. 8 is an example of a screen displayed on a seller agent terminal. In FIG. 8, the content to be entered as "industry" is displayed in form F2 as a group of tags TG1. The content to be entered as industry may be specified by having the seller agent select at least a portion of the tags TG1. In the example shown in FIG. 8, the tag TG1 to be registered as the "industry" item is shown in form F2, but for example, the seller agent U2 can operate a portion of the tag TG1 to exclude the content corresponding to the operated tag TG1 from being registered.

[0068] The tag TG1 here may be presented based on the content entered by the seller U1 or the seller's agent U2 in the first input field. That is, in the example of Fig. 8, when the seller's agent U2 enters information in the "Project Title" field, the tag TG1 with content correlated to the entered information may be presented in the form F2.

[0069] More specifically, the following process may be performed. That is, the presentation unit 115 of the server device 10 may be configured to extract the tag TG1 from a predetermined business master. Then, the presentation unit 115 may present the extracted tag TG1 in a predetermined area of ​​the first input format (another input field such as form F2). In a typical embodiment, the efficiency of such tag extraction process can be improved by the function of an artificial intelligence module (artificial intelligence unit 117). That is, the presentation unit 115 may extract the tag TG1 by inputting at least the input content in the first input field and the business master into the artificial intelligence module (artificial intelligence unit 117).

[0070] That is, the server device 10 can prepare a plurality of keywords related to various industries in a predetermined storage area (typically, the storage unit 12) and store them as an industry master. In this state, the presentation unit 115 may input the content entered in the first input field and the industry master to an artificial intelligence module (artificial intelligence unit 117) and instruct the artificial intelligence module (artificial intelligence unit 117) to extract keywords correlated with the content entered in the first input field. Although not necessarily limited to this, such extraction processing may be performed as follows. First, the presentation unit 115 instructs the artificial intelligence module (artificial intelligence unit 117) to convert the content entered in the first input field into vector data. Meanwhile, the presentation unit 115 instructs the artificial intelligence module (artificial intelligence unit 117) to similarly convert keywords present in the industry master into vector data. Then, the presentation unit 115 causes the artificial intelligence module (artificial intelligence unit 117) to extract keywords correlated with the content entered in the first input field from among the keywords present in the industry master, based on the proximity of the distance between both vector data. The closeness of the distance between the vector data here may be evaluated by various methods, but typically may be evaluated by the angle between the two vectors (cosine similarity). The correlation here may also be scored. Form F2 may then display keywords in descending order of their scores.

[0071] In the example shown in Fig. 8, the first input field is a field for inputting the case title (case summary), and the presented options (tags) are related to the industry, but the input items in the first input field may be different from the case title (case summary). The presented options (tags) may also be options related to content different from the industry. That is, although the above description was given as a process for extracting keywords stored in an "industry master," it may also be configured so that a different master is prepared and various options are extracted from that master.

[0072] Although the above describes a mode in which options are presented for a field different from the first input field, the field in which options are presented may be the first input field itself.

[0073] 9 is an example of a screen displayed on the seller agent terminal. The example screen shown in FIG. 9 shows a mode in which options to be inserted into the first input field are presented based on the content entered into the first input field, form F1. From one perspective, the content entered into the first input field by seller U1 or seller agent U2 may be fragmentary information about the project or organization, and the options to be presented to seller U1 or seller agent U2 may be based on such fragmentary information.

[0074] In the example shown in FIG. 9, various candidate CDs are presented as options based on input of predetermined information ("sports goods" in the figure) into form F1 in FIG. 9(i) (see FIG. 9(ii)). The following process may be performed to present such candidate CDs. Specifically, the presentation unit 115 of the server device 10 may be configured to extract candidate CDs from a predetermined summary master. The presentation unit 115 may then present the extracted candidate CDs in a predetermined area of ​​the first input format (an area associated with form F1). In a typical embodiment, the efficiency of such candidate CD extraction processing can be improved by the function of an artificial intelligence module (artificial intelligence unit 117). Specifically, the presentation unit 115 may extract candidate CDs by inputting at least the input content in the first input field and the summary master into the artificial intelligence module (artificial intelligence unit 117).

[0075] That is, the server device 10 can prepare a plurality of keywords related to various project summaries in a predetermined storage area (typically, the storage unit 12) and store them as a summary master. In this state, the presentation unit 115 inputs the content entered in the first input field and the summary master to the artificial intelligence module (artificial intelligence unit 117) and instructs the artificial intelligence module (artificial intelligence unit 117) to extract keywords correlated with the content entered in the first input field. Although not necessarily limited to this, such extraction processing may be performed as follows. First, the presentation unit 115 instructs the artificial intelligence module (artificial intelligence unit 117) to convert the content entered in the first input field into vector data. Meanwhile, the presentation unit 115 instructs the artificial intelligence module (artificial intelligence unit 117) to similarly convert keywords present in the summary master into vector data. Then, the presentation unit 115 causes the artificial intelligence module (artificial intelligence unit 117) to extract keywords correlated with the content entered in the first input field from among the keywords present in the summary master, based on the proximity of the distance between both vector data. The closeness of the distance between the vector data here may be evaluated by various methods, but typically may be evaluated by the angle between the two vectors (cosine similarity). The correlation here may also be scored. Keywords may be displayed as candidate CDs in descending order of their scores.

[0076] Here, the first input field is a field for inputting a case summary, and the presented options (candidate CD) are related to the case summary, but the items input into the first input field may be different from the case summary. Also, the presented options (candidate CD) may be options regarding different content from the case summary. That is, although the above description was given as a process for extracting keywords stored in an "overview master," it may also be configured so that a different master is prepared and various options are extracted from that master.

[0077] After the first project information is received in this manner, the receiving unit 111 of the server device 10 displays a second input format for inputting the second project information, and receives input of the second project information into the second input format from the seller U1 of the organization or an entity acting on behalf of the seller (seller agent U2). This second input format is capable of receiving input of information relating to items not included in the first input format as at least part of the second project information. When receiving such second project information, the server device 10 displays the second input format in a manner in which at least part of the first project information is transcribed into the corresponding input fields of the second input format.

[0078] The display of the second input format here is performed, for example, based on a request for display of the second input format made by the seller U1 or the seller agent U2 (activities A109 to A112). Then, predetermined information (second case information) is input into the second input format displayed to the seller U1 or the seller agent U2, and the receiving unit 111 of the server device 10 receives the second case information (activities A113 to A114).

[0079] An example of the second input format shown to the seller U1 and the seller agent U2 will be described with reference to the accompanying drawings. FIG. 10 shows an example of a screen displayed on the seller agent terminal. In a typical embodiment, the second input format may be configured to allow various items to be input. Here, the number of input items in the second input format may be set to be greater than the number of input items in the first input format. Furthermore, the input items in the second input format may include the input items in the first input format and additional input items may be set. The second project information may include input items for the items that can be input in the second input format. The items that can be input in the second input format may be selected as appropriate, and may include, for example, the following items. That is, the receiving unit 111 of this embodiment may accept, as at least part of the second project information, one or more of the organization's industry, business content, size of the organization, intentions regarding the transaction, and financial information of the organization, which are not included in the first project information.

[0080] The screen displaying the second input format may be displayed based on various terminal operations by the seller U1 or the seller's agent U2. Typically, after logging in to the organizational trading platform, a transition to the screen displaying the second input format may be performed through a predetermined operation. The source of such screen transition may be set as appropriate, and may be, for example, the screen displaying the first input format described above. For example, the screen shown in FIG. 6 may be provided with a link for transitioning to the screen displaying the second input format, and by operating the link, transition to the screen displaying the second input format may be performed. Of course, the screen on which such a link is set may be various screens other than the screen displaying the first input format.

[0081] 10, forms F5 to F10 are configured to allow input of various items such as "project title," "industry," "location (prefecture)," "sales amount for the previous year," "number of employees," and "person in charge." A user (seller agent U2, etc.) who comes across the screen shown in Fig. 10 can proceed with the operation of having the reception unit 111 accept the second project information by inputting information into the various items and then pressing button BT3.

[0082] As shown in FIG. 10 , when accepting second case information, the server device 10 may display the second input format in a manner in which at least a portion of the first case information is transcribed into the corresponding input fields of the second input format. In other words, in the previously described input mode of the first case information, predetermined information is entered into the fields "Case Title," "Industry," "Location (Prefecture)," and "Contact Person," and then the case is registered. However, the content entered as the first case information in this manner may be transcribed into the corresponding fields in the second input format. In other words, FIG. 10 shows the content entered into forms F1, F2, F3, and F4 of FIG. 6 transcribed into forms F5, F6, F7, and F10, respectively, in FIG. 10. A user viewing FIG. 10 can enter additional information to be accepted as second case information in addition to the transcribed information, and then press button BT3. This allows the accepting unit 111 of the server device 10 to accept the second case information. The content entered as the first project information and transcribed into the second input format may be editable by the seller U1 or the seller's agent U2 as appropriate. Typically, the various contents transcribed into forms F5, F6, F7, and F10 shown in FIG. 10 may be changed by the seller U1 or the seller's agent U2 operating their terminals. FIG. 10 also shows a configuration in which the second input format includes input fields with the same names as the input fields in the first input format, and the content of the first project information is transcribed into the corresponding fields in the second input format. However, the transcribing configuration may be as follows: That is, when there is a first field in the first input format and a second field in the second input format, and the content entered as the first field is transcribed into the field related to the second field, the first and second fields do not necessarily have to have the same content. As an example, the first item and the second item may be related (similar) items to each other, and even in such a case, the input burden on seller U1 and seller agent U2 can be reduced by transcribing the content entered as the first item into the column related to the second item.When receiving the second case information, a screen for confirming the entered items may also be displayed as appropriate, similar to the screen shown in FIG.

[0083] The item "Sales for the Previous Year" associated with Form F8 in Figure 10 is an example of "financial information of the organization" that can be accepted as second project information. However, the "financial information of the organization" that can be accepted as second project information is not limited to this and may include, for example, a balance sheet, cash and deposits, total liabilities, net assets, a profit and loss statement, executive compensation, etc.

[0084] The item "Number of employees" associated with form F9 in Figure 10 is an example of "organization size" that can be accepted as second case information. Note that "organization size" may include information such as the number of offices and stores in addition to the number of employees.

[0085] Additionally, the "organization's industry" that can be accepted as the second project information corresponds to the item "industry" associated with form F6. Note that, in the example of this embodiment, the "organization's industry" is input as part of the first project information, but in cases where the "organization's industry" is not included in the first project information, information on the "organization's industry" can also constitute part of the second project information.

[0086] Furthermore, the "organization's business details" that can be accepted as second project information may indicate, for example, details of the business that the organization may conduct. Such business details may be entered, for example, in text format, into a second input format by the seller U1 or the seller's agent U2. Furthermore, the "transaction intentions" that can be accepted as second project information may include, for example, information such as the reason for the sale, the key points to consider in the sale, the purpose of the sale, the background to the sale, the desired conditions for the sale, and the desired timing of the sale. Of course, the second project information may also include various other information that is useful to the buyer when acquiring the organization, but is not shown here.

[0087] In this way, the second project information received by the server device 10 is appropriately associated with the user who input the information and registered (activity A115). In an exemplary embodiment, the registration unit 110 of the server device 10 associates the received second project information with the user who input the second project information (seller U1 or seller agent U2) and stores the data in a predetermined storage area. Typically, the second project information may be registered (stored) as a project related to the same organization as the first project information. The registered information may then be appropriately displayed on the seller agent terminal, etc.

[0088] In this embodiment, after the second project information is input, the display control unit 112 controls so that at least a part of the second project information can be displayed to the buyer (activity A116). That is, although it was previously mentioned that a web page about the organization to be traded can be created as a "project page," after the input of the second project information is accepted, such a web page may be made viewable by the buyers (first buyer U3, second buyer U4, etc.).

[0089] In one aspect, upon receiving the input of the second case information, the registration unit 110 of the server device 10 can register the case related to the second case information as a case in a second status. The second status here may be a status in which the second case information has been received. In a typical embodiment, when the seller U1 or the seller's agent U2 registers a case regarding an organization that is the subject of a transaction as a case in this second status, the information about the case may be made available to the buyer.

[0090] In this way, after receiving the input of the second project information, various buyers may be able to view information about the organization that will be the subject of the transaction. Also, buyers who are interested in the organization that will be the subject of the transaction may be able to send messages to the seller U1 or the seller's agent U2 as appropriate. This allows various users to more efficiently proceed with M&A considerations regarding the organization.

[0091] In addition, in this embodiment, the following aspects may be adopted.

[0092] That is, the information generating unit 113 of the server device 10 may generate value information that indicates the potential value of the transaction based on the first case information, the registered information of the buyer, and the first reference information.

[0093] In a typical embodiment, the seller U1 or the seller agent U2 can obtain predetermined value information based on the first project information after having the first project information accepted by the accepting unit 111. The value information here may be various information that represents the potential value of a transaction related to an organization, but typically, the value here may be information related to a (potential) buyer of the organization that is the subject of the transaction.

[0094] Such information may be generated based on various information processing methods, but may typically be generated as follows. That is, the first reference information in this embodiment may include a value information generation model, which is a learning model or a generation AI that has been machine-learned to input the first case information and the registered information and be capable of outputting value information. If the value information generation model includes a learning model, the information generation unit 113 may input the first case information and the registered information into the value information generation model and execute a process to cause the value information generation model to output the value information. On the other hand, if the value information generation model includes a generation AI, the information generation unit 113 may input an instruction to create value information based on the first case information and the registered information, as well as the first case information and the registered information, into the generation AI and execute a process to cause the generation AI to output the value information. Note that, in a typical embodiment, the registered information here may be registration information regarding multiple buyers registered in the organized trading platform provided by the information processing system 1.

[0095] FIG. 11 is an example of a screen displayed on a seller agent terminal. FIG. 12 is an example of a screen displayed on a seller agent terminal. FIG. 13 is an example of a screen displayed on a seller agent terminal. As an example, the information generation unit 113 of the server device 10 of this embodiment can create a list of users who are potential buyers for the organization being traded. Such a list may be referred to as a "long list" or the like. In the example shown in FIG. 6, an aspect is shown in which the user selects whether or not to request the creation of such a long list in the "Request for information creation" item. Here, such a long list may be presented to a user (seller U1 or seller agent U2) who checks the checkbox CB1 to request the creation of the list.

[0096] The value information included in such a long list may include, for example, the following. That is, the value information may include information about buyers whose information about transaction needs included in the registration information correlates with the first project information. Specifically, in the example shown in FIG. 11, the number of buyers whose transaction needs correlate with the first project information is shown as "XXX Company" as the "Total Number of Buyers with Needs." From one perspective, when a buyer registers as a user of the organized transaction platform, the buyer may register information about their transaction needs as part of the registration information. In response to this, the information generation unit 113 can extract buyers whose information about such transaction needs correlates with the first project information and present this to the seller U1 or the seller's agent U2.

[0097] When performing such extraction processing, the following mode may be adopted. That is, the first reference information may include a first buyer extraction model, which is a learning model trained to input the first case information and registered information and output information about buyers correlated with the first case information. For example, the first buyer extraction model may be a learning model trained using the first case information, registered information, and corresponding buyers as training data. The information generation unit 113 may input the first case information and registered information into the first buyer extraction model included in the artificial intelligence module (artificial intelligence unit 117) and cause the first buyer extraction model to output buyers whose transaction needs correlated with the first case information are registered. Note that the first buyer extraction model may be, for example, a learning model such as a language model or a large-scale language model, or may be an AI including a generation AI. In this case, the information generating unit 113 may input, to the first buyer extraction model, an instruction to extract buyers whose information on transaction needs correlates with the first project information based on the first project information and the registered information, and a prompt into which the first project information and the registered information are inserted, and cause the first buyer extraction model to output buyers whose information on transaction needs correlates with the first project information. Furthermore, the information generating unit 113 may input, to the first buyer extraction model, in addition to the buyer extraction instruction, the first project information, and the registered information, a prompt into which, for example, one or more samples of the first project information and the registered information and one or more corresponding samples of information on buyers are inserted.

[0098] Meanwhile, the extraction process for buyers may be performed as follows. First, the information generation unit 113 instructs the artificial intelligence module (artificial intelligence unit 117) to convert the first project information into vector data. Meanwhile, the information generation unit 113 instructs the artificial intelligence module (artificial intelligence unit 117) to similarly convert the buyer's registration information (particularly information related to the buyer's transaction needs) into vector data. Then, the information generation unit 113 may cause the artificial intelligence module (artificial intelligence unit 117) to extract, from among multiple buyers, buyers that have a correlation with the first project information, based on the proximity of the distance between both sets of vector data. Note that the proximity of the distance between the vector data here may be evaluated using various methods, but typically may be evaluated by the angle between both vectors (cosine similarity), etc.

[0099] The number of buyers extracted in this manner may be displayed to the seller U1 or seller agent U2. In the example shown in FIG. 11, this number is displayed as the "total number of buyers in need." When button BT4 is pressed, the extracted buyers may be displayed. The manner in which such display is performed may be set as appropriate, but as an example, the extracted buyers are displayed in list form.

[0100] The information generating unit 113 of the server device 10 may generate, as value information, information regarding the synergies anticipated in the first project information, as well as information regarding buyers matching the synergies. Regarding this generation process, in the example shown in FIG. 11, when one of buttons BT6 to BT8 is pressed, a synergy corresponding to the value information may be generated as text. Note that "synergy" here may refer to the effect that would be achieved if the organization being traded were purchased by a specific buyer. The generated text may be displayed in a field associated with each button, as shown in FIG. 11. From another perspective, the information generating unit 113 of the server device 10 can generate synergies that can be derived from both the first project information regarding the organization being traded and the registered information of the buyer on the organization trading platform, and can then present the generated synergies to the seller U1 or the seller's agent U2. In the example shown in FIG. 11, synergies from three perspectives are shown as synergies SN. When any of the buttons BT6 to BT8 is pressed again, such text may be generated again, and the text in the column may be updated as appropriate.

[0101] A sentence expressing synergy in this embodiment may be generated as follows. That is, the first reference information may have a synergy generation model, which is a learning model trained to input the first case information and the registered information and output information related to the synergy expected in the first case information. For example, the synergy generation model may be a learning model trained using the first case information, the registered information, and information related to the corresponding synergy as training data. The information generation unit 113 may input the first case information and the registered information to the synergy generation model included in the artificial intelligence module (artificial intelligence unit 117), and cause the synergy generation model to output information related to the synergy expected in the first case information. Note that the synergy generation model may be, for example, a learning model such as a language model or a large-scale language model, or may be an AI including a generation AI. In this case, the information generation unit 113 may input, to the synergy generation model, an instruction to generate information on the synergy expected in the first case information based on the first case information and the registration information, and a prompt in which the first case information and the registration information are inserted, and cause the synergy generation model to output the information on the synergy expected in the first case information. Furthermore, the information generation unit 113 may input, to the synergy generation model, a prompt in which, in addition to the instruction to generate synergy, the first case information, and the registration information, for example, one or more samples of the first case information and the registration information and one or more corresponding samples of information on the synergy are inserted.

[0102] Furthermore, the information generating unit 113 may generate information about buyers that match the synergies along with the generated synergies. In one aspect, the information about buyers that match the synergies may indicate buyers that have a correlation with the synergies generated by the information generating unit 113, and may be appropriately extracted by the information generating unit 113 from among users registered in the organizational trading platform.

[0103] 11, the number of buyers that match the synergy generated by the organization of the transaction target is shown as "YYY Company" as the "total number of synergy buyers." In this way, the information generating unit 113 of this embodiment may generate, as value information, information on buyers that match the synergy, along with the synergy (information on the synergy).

[0104] Such buyer extraction processing may be realized by various methods, but as an example, the information generation unit 113 may extract buyers that match the synergy based on the functions of an artificial intelligence module (artificial intelligence unit 117).

[0105] When performing such an extraction process, the first reference information may include a second buyer extraction model, which is a learning model trained to input information about synergies and registered information and output information about buyers that match the synergies. For example, the second buyer extraction model may be a learning model trained using information about synergies, registered information, and information about corresponding buyers as training data. The information generation unit 113 may input the generated information about synergies and registered information into the second buyer extraction model of the artificial intelligence module (artificial intelligence unit 117), and cause the second buyer extraction model to output information about buyers that match the synergies. Note that the second buyer extraction model may be, for example, a learning model such as a language model or a large-scale language model, or may be an AI including a generation AI. In this case, the information generation unit 113 may input, to the second buyer extraction model, an instruction to extract buyers that match the synergies based on the information about synergies and registered information, and a prompt containing the information about synergies and registered information, and cause the second buyer extraction model to output information about buyers that match the synergies. In addition, the information generation unit 113 may input a prompt into the second buyer extraction model that includes, in addition to buyer extraction instructions, information about synergies, and registration information, for example, samples of information about one or more synergies and registration information, and samples of information about one or more corresponding buyers.

[0106] Meanwhile, the extraction process for buyers may be performed as follows. First, the information generation unit 113 instructs the artificial intelligence module (artificial intelligence unit 117) to convert the generated information about synergies into vector data. Meanwhile, the information generation unit 113 instructs the artificial intelligence module (artificial intelligence unit 117) to similarly convert the buyer's registration information (information about the buyer) into vector data. Then, the information generation unit 113 may cause the artificial intelligence module (artificial intelligence unit 117) to extract, from among multiple buyers, those buyers that have a correlation with the information about synergies, based on the proximity of the distance between both sets of vector data. Note that the proximity of the distance between the vector data here may be evaluated by various methods, but typically may be evaluated by the angle between both vectors (cosine similarity), etc.

[0107] The synergy generation model shown above may extract (identify) buyers who match the synergy, along with a sentence describing the synergy, as part of the information about the synergy. By utilizing such a synergy generation model, it is possible to efficiently extract (identify) buyers (buyer-side users) who match the synergy.

[0108] The above-mentioned various extraction processes may be performed, for example, for each item shown as synergy SN in Fig. 11. In other words, it is possible to extract buyers that have a correlation with each synergy (match each synergy), and by adding these up, it is possible to display the number of buyer users who match the synergy as "YYY Company."

[0109] Note that when button BT5 shown in FIG. 11 is pressed, the screen may transition to, for example, the screens shown in FIGS. 12 and 13. That is, for each synergy shown in FIG. 11, FIG. 12 summarizes the industries of buyers that could potentially achieve the synergy, the number of relevant companies (number of buyers), and an overview of the synergy. Furthermore, FIG. 13 displays in list form details of buyers that match each synergy (location, industry, annual sales volume, business details, etc.). That is, the seller U1 or seller's agent U2, upon seeing these displays, can imagine the buyers for the organization they are trying to sell and the synergies that could be achieved if the buyers purchase the organization.

[0110] In addition, in this embodiment, the following aspects may be adopted.

[0111] That is, the information generation unit 113 of the server device 10 may generate reference information for the organization's seller U1 or an entity acting on behalf of the seller (seller agent U2) to conduct a transaction based on the first case information and the second reference information.

[0112] In a typical embodiment, the seller U1 or the seller agent U2 can obtain predetermined reference information based on the first project information after having the first project information received by the receiving unit 111. The reference information here may be various information that can be referred to when conducting a transaction related to the organization, and as an example, the reference information may include information related to at least one of the business flow related to the organization, the value chain related to the organization, the industry environment related to the organization, and transaction history of organizations similar to the organization that is the target of the transaction.

[0113] While the above describes a mode in which value information representing the potential value of a transaction is generated based on the first project information and the buyer's registered information, the reference information does not necessarily have to be generated based on such buyer's registered information. In another mode, the reference information may be generated based on both the first project information and the buyer's registered information.

[0114] Such reference information may be generated based on various information processes, but may typically be generated as follows. That is, the second reference information in this embodiment may include a reference information generation model, which is a learning model that has been machine-learned to receive the first case information as input and be capable of outputting reference information, or a generation AI. When the reference information generation model includes a learning model, the information generation unit 113 may input at least the first case information into the reference information generation model and execute a process of causing the reference information generation model to output the reference information. On the other hand, when the reference information generation model includes a generation AI, the information generation unit 113 may execute a process of issuing an instruction to create reference information based on at least the first case information and inputting the first case information into the generation AI and causing the generation AI to output the reference information.

[0115] In the example shown in Fig. 11, the item "Project Axis" shows "Transaction Performance of Organizations Similar to the Organization That is the Target of Transactions," which can be used as reference information. Note that the information generated by the information generation unit 113 is not limited to the statistical data shown in Fig. 11, but may be various texts, graphs, etc. For example, the information generation unit 113 of this embodiment may generate information that expresses, in text, graphs, figures, keywords, etc., information related to at least one of the business flow of the organization, the value chain of the organization, the industry environment of the organization, and transaction performance of organizations similar to the organization That is the target of transaction.

[0116] In addition, the present embodiment can also employ the following aspects.

[0117] That is, after receiving the first case information, the notification unit 114 of the server device 10 may notify the seller U1 of the organization or an entity acting on behalf of the seller (seller agent U2) of notification information related to the transaction object.

[0118] FIG. 14 is an example of a screen displayed on the seller agent terminal. This FIG. 14 shows the screen when seller agent U2 is logged in to the organization transaction platform. In the example screen shown in FIG. 14, a message is displayed as a notification NT (notification information) to the effect that a buyer with affinity (correlation) with the organization being the subject of the transaction has been registered. Note that the screen shown in FIG. 14 has a button BT9 associated with this notification NT. When button BT9 is pressed, the screen may be configured to transition to a screen showing detailed information regarding the notification NT.

[0119] In this embodiment, the notification information may be displayed to the seller U1 or the seller agent U2 by a notification such as a pop-up notification or a push notification. Alternatively, the notification information may be sent to the seller U1 or the seller agent U2 as a predetermined message (email). Such a message (email) may be stored in a message box (mailbox) of the seller U1 or the seller agent U2 in the above-mentioned organizational transaction platform, and may be configured to be openable by the seller U1 or the seller agent U2 as appropriate.

[0120] Furthermore, such notifications NT (notification information) may be sent at various times. In one embodiment, such notification information may be sent based on an operation by an operator of the organizational trading platform. Meanwhile, in another embodiment, the notification unit 114 of the server device 10 may send notification information based on a buyer action taken in relation to the transaction target. The buyer action here may be set as appropriate, and may be, for example, the buyer registering as a platform user, searching for a project by the buyer, sending a message by the buyer, etc. In other words, when these actions are correlated with the organization that is the transaction target, the notification unit 114 may be configured to notify the seller U1 or the seller agent U2 of the specified notification information.

[0121] As described above, according to this embodiment, the seller U1 or the seller agent U2 can have the server device 10 accept the first project information in a manner that hides it from buyers. According to an exemplary embodiment, by accepting the first project information in this manner, the seller U1 or the seller agent U2 can obtain information, such as information about the potential value in the market, based on the functions of the server device 10. Furthermore, the seller U1 or the seller agent U2 can have the server device 10 accept the second project information in a manner that displays at least a portion of the information to buyers. In this case, at least a portion of the first project information is transcribed into the input field of the second input format for accepting the second project information. In other words, by adopting this embodiment, the seller U1 or the seller agent U2 can efficiently have the server device 10 accept the second project information, thereby smoothly progressing the process for selling the organization.

[0122] 4.Other Although the embodiment of the present invention has been described above, the present invention is not limited to this and can be modified as appropriate within the scope of the technical idea of ​​the invention.

[0123] In the above embodiment, the server device 10 performs various storage and control functions. However, multiple external devices may be used instead of the server device 10. That is, various information and programs may be distributed and stored in multiple external devices using blockchain technology or the like. The artificial intelligence unit 117 may be an external component of the server device 10. In this case, the external artificial intelligence unit 117 may be provided, for example, by an artificial intelligence service server and configured to receive input from each functional unit of the server device 10, receive requests to execute an artificial intelligence service, and return the instructed output as a processing result to the server device 10. The artificial intelligence service server may provide a service using a language model as a learning model, or may perform language processing tasks using a language model, and may provide an LLM, a generative AI, or an AI agent. The artificial intelligence service server may receive prompt input, for example, in the form of text, image, or voice, and generate and respond to the prompt. The server device 10 may also cooperate with an application programming interface (API) of a service server that provides the generative AI, etc., to use the generative AI, etc.

[0124] At least one of the devices included in the information processing system 1 may be installed outside the country in which the functions of the information processing system 1 are performed.

[0125] The aspect of this embodiment is not limited to the information processing system 1, and may be an information processing method or a program. The information processing method includes steps executed by the information processing system 1. The program causes a computer to execute the steps of the information processing system 1.

[0126] It may be provided in the following manner.

[0127] (1) An information processing system, comprising at least one processor, configured to execute the following steps by reading a program: a first reception step displays a first input format for inputting first case information relating to a transaction of an organization that is a trading target, and receives input of the first case information into the first input format from a seller of the organization or an entity acting on behalf of a seller; a first display control step controls so that the first case information is not displayed to a buyer of the organization; a second reception step displays a second input format for inputting second case information, and receives input of the first case information into the first input format from a seller of the organization or an entity acting on behalf of a seller; an information processing system that accepts input of the second project information into the second input format from an entity acting on behalf of a seller, wherein the second input format is capable of accepting input of information relating to items not included in the first input format as at least part of the second project information, wherein the second receiving step displays the second input format in a manner in which at least part of the first project information is transcribed into corresponding input fields of the second input format, and wherein the second display control step controls so that after the second project information has been input, at least part of the second project information can be displayed to the buyer.

[0128] (2) In the information processing system described in (1) above, in the first reception step, at least one of information on the summary of the transaction, the location of the organization, the status of acceptance of the transaction, and the person in charge of the transaction is input as the first case information.

[0129] (3) In the information processing system described in (1) or (2) above, in the first information generation step, value information representing the potential value of the transaction is generated based on the first case information, the buyer's registration information, and the first reference information.

[0130] (4) In the information processing system described in (3) above, the first reference information includes a value information generation model which is a learning model or a generation AI that has been machine-learned to input the first case information and the registered information so as to be able to output the value information, and in the first information generation step, if the value information generation model includes the learning model, the first case information and the registered information are input into the value information generation model and a process is executed to cause the value information generation model to output the value information, and if the value information generation model includes the generation AI, an instruction to create the value information based on the first case information and the registered information, the first case information and the registered information, are input into the generation AI and a process is executed to cause the generation AI to output the value information.

[0131] (5) In the information processing system described in (3) or (4) above, the value information includes information about buyers whose trading needs included in the registration information are correlated with the first case information.

[0132] (6) In the information processing system described in any one of (3) to (5) above, in the first information generation step, the value information is generated as information regarding the synergies expected in the first project information, and information regarding buyers that match the synergies is generated.

[0133] (7) An information processing system according to any one of (3) to (6) above, wherein the registration information is registration information relating to multiple buyers registered on an organized trading platform provided by the information processing system.

[0134] (8) In the information processing system described in any one of (1) to (7) above, in the second information generation step, reference information is generated based on the first case information and the second reference information for the seller of the organization or an entity acting on behalf of the seller to use when conducting the transaction.

[0135] (9) In the information processing system described in (8) above, the reference information includes information related to at least one of the business flow related to the organization, the value chain related to the organization, the industry environment related to the organization, and transaction history with organizations similar to the organization that is the subject of the transaction.

[0136] (10) In the information processing system described in (8) or (9) above, the second reference information includes a reference information generation model that is a learning model that has been machine-learned to input the first case information and be capable of outputting the reference information, or a generation AI, and in the second information generation step, if the reference information generation model includes the learning model, at least the first case information is input into the reference information generation model and a process is executed to cause the reference information generation model to output the reference information, and if the reference information generation model includes the generation AI, at least an instruction to create the reference information based on the first case information and the first case information are input into the generation AI and a process is executed to cause the generation AI to output the reference information.

[0137] (11) In the information processing system described in any one of (1) to (10) above, in the second reception step, as at least part of the second project information, one or more pieces of information among the industry of the organization, the business content of the organization, the size of the organization, the intention regarding the transaction, and the financial information of the organization are received, which are not included in the first project information.

[0138] (12) In the information processing system described in any one of (1) to (11) above, in the notification step, after receiving the first case information, notification information related to the trading object is notified to the seller of the organization or an entity acting on behalf of the seller.

[0139] (13) In the information processing system described in (12) above, in the notification step, the notification information is notified based on the buyer's action taken in relation to the subject of the transaction.

[0140] (14) In the information processing system described in any one of (1) to (13) above, the first input format has a first input field, and in the first receiving step, when content is entered into the first input field by a seller of the organization or an entity acting on behalf of the seller, one or more options related to the content are presented, and when the seller of the organization or an entity acting on behalf of the seller selects one of the one or more options, information related to the selected option is accepted as at least part of the first case information.

[0141] (15) The information processing system according to any one of (1) to (14) above, further comprising: a server device having the processor; and a terminal that can access the server device.

[0142] (16) An information processing method, comprising steps executed by the information processing system according to any one of (1) to (15) above.

[0143] (17) A program for causing a computer to execute each step of the information processing system described in any one of (1) to (15) above. Of course, this is not the case.

[0144] Finally, while various embodiments of the present disclosure have been described, they are presented as examples and are not intended to limit the scope of the invention. The novel embodiments may be embodied in various other forms, and various omissions, substitutions, and modifications may be made without departing from the spirit of the invention. Such embodiments and modifications are intended to be included within the scope and spirit of the invention, as well as within the scope of the inventions and their equivalents as defined in the claims. [Explanation of symbols]

[0145] 1: Information processing system 2: Communication line 10: Server device 11: Control section 12: Storage section 13: Communications Department 14: Communication bus 20: User terminal 21: Control unit 22: Storage section 23: Communications Department 24: Input section 25: Output section 26: Communication bus 110: Registration Department 111: Reception 112: Display control unit 113: Information generation section 114: Notification Department 115: Presentation part 116: Memory management department 117: Artificial Intelligence Department 210: Display control unit 211: Operation reception unit BT1~BT9: Buttons CB1: Checkbox CD: Candidate F1~F10: Form NT:Notification OBJ1: Object SN: Synergy TG1 : Tag U1: Seller U2: Seller's Agent U3: First Buyer U4: Second Buyer

Claims

1. An information processing system, at least one processor; The processor is configured to execute the following steps by reading the program: In the first receiving step, a first input format for inputting first case information related to a transaction of an organization that is a transaction target is displayed, and input of the first case information into the first input format is received from a seller of the organization or an entity acting on behalf of the seller; In the first receiving step, based on the input to the first input format, at least one of information on an outline of the transaction, a location of the organization, an acceptance status of the transaction, and a person in charge of the transaction is input as the first case information; In the first registration step, based on the acceptance of the first case information, a case related to the first case information is registered as a case in a first status; In the first display control step, the first project information about the project in the first status is controlled so as to be hidden from buyers of the organization; In a second receiving step, after the first display control step, a second input format for inputting second case information about the case in the first status is displayed, and input of the second case information into the second input format is received from a seller of the organization or an entity acting on behalf of the seller; wherein the second input format is capable of accepting input of information relating to items not included in the first input format as at least a part of the second case information; In the second receiving step, based on the input to the second input format, one or more pieces of information among the organization's industry, the organization's business content, the organization's size, the intention regarding the transaction, and the organization's financial information are received as at least part of the second project information, and the information is not included in the first project information; In the second receiving step, the second input format is displayed in a manner in which at least a part of the first case information is transcribed into a corresponding input field of the second input format; In the second registration step, based on the acceptance of the second case information, the case related to the second case information is registered as a case in a second status; In the second display control step, after the second case information is input, the information processing system controls so that at least a portion of the second case information for cases in the second status can be displayed to the buyer.

2. An information processing system, at least one processor; The processor is configured to execute the following steps by reading the program: In the first receiving step, a first input format for inputting first case information related to a transaction of an organization that is a transaction target is displayed, and input of the first case information into the first input format is received from a seller of the organization or an entity acting on behalf of the seller; In the first receiving step, at least one of information on an outline of the transaction, a location of the organization, a status of acceptance of the transaction, and a person in charge of the transaction is input and received as the first case information; In the first display control step, the first case information is controlled so as not to be displayed to buyers of the organization; In the first information generation step, value information representing a potential value of the transaction is generated based on the first case information, the registered information of the buyer, and the first reference information; Here, the first reference information includes a value information generation model that is a learning model or a generation AI that is machine-learned to input the first case information and the registration information and output the value information, In the first information generating step, When the value information generation model includes the learning model, the first case information and the registered information are input into the value information generation model, and a process is executed to output the value information from the value information generation model; If the value information generation model includes the generation AI, an instruction to create the value information based on the first case information and the registered information, and the first case information and the registered information are input to the generation AI, and a process is executed to cause the generation AI to output the value information; The buyer's registration information includes information regarding the buyer's trading needs; the value information includes information about a buyer whose transaction needs included in the registration information correlate with the first project information; In the second receiving step, a second input format for inputting second project information is displayed, and input of the second project information into the second input format is received from a seller of the organization or an entity acting on behalf of the seller; wherein the second input format is capable of accepting input of information relating to items not included in the first input format as at least a part of the second case information; In the second receiving step, the second input format is displayed in a manner in which at least a part of the first case information is transcribed into a corresponding input field of the second input format; In the second display control step, after the second project information is input, the information processing system controls so that at least a part of the second project information can be displayed to the buyer.

3. An information processing system, at least one processor; The processor is configured to execute the following steps by reading the program: In the first receiving step, a first input format for inputting first case information related to a transaction of an organization that is a transaction target is displayed, and input of the first case information into the first input format is received from a seller of the organization or an entity acting on behalf of the seller; In the first receiving step, at least one of information on an outline of the transaction, a location of the organization, a status of acceptance of the transaction, and a person in charge of the transaction is input and received as the first case information; In the first display control step, the first case information is controlled so as not to be displayed to buyers of the organization; In the first information generation step, value information representing a potential value of the transaction is generated based on the first case information, the registered information of the buyer, and the first reference information; Here, the first reference information includes a value information generation model that is a learning model or a generation AI that is machine-learned to input the first case information and the registration information and output the value information, In the first information generating step, When the value information generation model includes the learning model, the first case information and the registered information are input into the value information generation model, and a process is executed to output the value information from the value information generation model; If the value information generation model includes the generation AI, an instruction to create the value information based on the first case information and the registered information, and the first case information and the registered information are input to the generation AI, and a process is executed to cause the generation AI to output the value information; The buyer's registration information includes information regarding the buyer's trading needs; In the first information generation step, information regarding synergies expected in the first project information is generated as the value information, and information regarding buyers that match the synergies is generated; In the second receiving step, a second input format for inputting second project information is displayed, and input of the second project information into the second input format is received from a seller of the organization or an entity acting on behalf of the seller; wherein the second input format is capable of accepting input of information relating to items not included in the first input format as at least a part of the second case information; In the second receiving step, the second input format is displayed in a manner in which at least a part of the first case information is transcribed into a corresponding input field of the second input format; In the second display control step, after the second project information is input, the information processing system controls so that at least a part of the second project information can be displayed to the buyer.

4. 3. The information processing system according to claim 2, An information processing system, wherein the registration information is registration information relating to a plurality of buyers registered on an organized trading platform provided by the information processing system.

5. An information processing system, at least one processor; The processor is configured to execute the following steps by reading the program: In the first receiving step, a first input format for inputting first case information related to a transaction of an organization that is a transaction target is displayed, and input of the first case information into the first input format is received from a seller of the organization or an entity acting on behalf of the seller; In the first receiving step, at least one of information on an outline of the transaction, a location of the organization, a status of acceptance of the transaction, and a person in charge of the transaction is input and received as the first case information; In the first display control step, the first case information is controlled so as not to be displayed to buyers of the organization; In the second information generation step, reference information is generated based on the first case information and the second reference information for a seller of the organization or an entity acting on behalf of the seller to conduct the transaction; Here, the second reference information includes a reference information generation model that is a learning model or a generation AI that is machine-learned to input the first case information and output the reference information, In the second information generating step, When the reference information generation model includes the learning model, at least the first case information is input into the reference information generation model, and a process of outputting the reference information from the reference information generation model is executed; When the reference information generation model includes the generation AI, an instruction to create the reference information based on at least the first case information is executed, and the first case information is input to the generation AI, and the reference information is output by the generation AI; The reference information includes information related to at least one of a commercial flow related to the organization, a value chain related to the organization, an industry environment related to the organization, and transaction records of organizations similar to the organization that is the target of the transaction; In the second receiving step, a second input format for inputting second project information is displayed, and input of the second project information into the second input format is received from a seller of the organization or an entity acting on behalf of the seller; wherein the second input format is capable of accepting input of information relating to items not included in the first input format as at least a part of the second case information; In the second receiving step, the second input format is displayed in a manner in which at least a part of the first case information is transcribed into a corresponding input field of the second input format; In the second display control step, after the second project information is input, the information processing system controls so that at least a part of the second project information can be displayed to the buyer.

6. 3. The information processing system according to claim 2, In the second reception step, an information processing system receives, as at least part of the second project information, one or more of the organization's industry, the organization's business content, the organization's size, the intention regarding the transaction, and the organization's financial information, which is information not included in the first project information.

7. 2. The information processing system according to claim 1, In the notification step, after receiving the first case information, the information processing system notifies the seller of the organization or an entity acting on behalf of the seller of notification information related to the transaction object.

8. 8. The information processing system according to claim 7, In the notification step, the notification information is notified based on an action taken by a buyer in relation to the transaction object.

9. 2. The information processing system according to claim 1, the first input format has a first input field; In the first receiving step, when content is input into the first input field from a seller of the organization or an entity acting on behalf of the seller, one or more options related to the content are presented; An information processing system in which a seller of the organization or an entity acting on behalf of the seller selects one of the one or more options, and information related to the selected option is accepted as at least part of the first case information.

10. 2. The information processing system according to claim 1, a server device having the processor; and a terminal that can access the server device.

11. An information processing method, comprising: An information processing method comprising the steps executed by the information processing system according to any one of claims 1 to 10.

12. A program, A program for causing a computer to execute each step of the information processing system according to any one of claims 1 to 10.

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