Information processing system

Abstract

This invention relates to an information processing technology for generating introductory content related to business succession cases. Conventionally, the creation of introductory materials for business succession cases relied on manual processes, resulting in challenges such as input burden and inconsistent quality. This invention selects the components of the introductory content based on the attribute information of the target business, owner intention information, and succession scheme information, and generates the introductory content by setting output parameters related to style, layout, and design. Furthermore, it performs generation that reflects the results of comparison with similar cases, inspection based on vocabulary rules and consistency rules, revision processing based on evaluation values, and anonymization or abstraction processing according to the disclosure level. As a result, it is possible to efficiently generate high-quality and reliable introductory content that is suited to the characteristics of the case and the succession form, thereby improving the convenience and security of business succession support.

Description

Technical Field

[0001] The present invention relates to an information processing system, a method, and a program for generating introduction content for business succession cases.

Background Art

[0002] In recent years, in order to solve the problem of the absence of successors due to the aging of business operators, matching for business succession through M&A platforms has become widespread. Patent Document 1 discloses a program for collating the information of sellers and buyers to calculate the degree of collation, aiming at efficient matching online. However, the creation of introduction materials and articles for the business to be presented to potential successors still largely depends on manual work by experts or the input of the sellers themselves, and the burden of creation and variations in quality have become issues. In particular, in business succession, not only quantitative information such as financial data but also qualitative information such as the owner's intention and the background of the business need to be appropriately reflected, and it is required to appeal in an appropriate composition according to the succession scheme such as share transfer or business transfer. Also, appropriate anonymization is necessary from the perspective of confidentiality, management of industry-specific terms, and ensuring the consistency of factual relationships is important. However, with existing general-purpose text generation technologies, it has been difficult to efficiently generate introduction content that fully meets these complex constraints and specialized requirements specific to business succession.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the field of business succession, the platform described in Patent Document 1 enables secure matching and calculation of matching degree using blockchain. However, the process of structuring the fragmented information held by sellers into appealing introductory content for buyers remains dependent on individual effort, resulting in high input workload and inconsistent content structure and quality.

[0005] The present invention aims to automatically generate introductory content by selecting the optimal components and parameters according to the attributes of the project and the owner's intentions. In particular, the central challenge to be addressed is to provide a system that can efficiently generate highly reliable, high-quality content by integrating content control to suit the succession scheme, inspection based on vocabulary rules, and reflection of comparison results with similar projects. [Means for solving the problem]

[0006] The information processing system of the present invention is Business succession cases Attribute information of the target business 、 Owner's intentions information, and Candidate attributes of successor candidates who show interest in the target business The information obtained will be used in the promotional content. Components Select and Related to style, layout, or design Output parameters and the level of disclosure of information regarding the target business presented to candidates. Set the parameters and generate the introductory content. Furthermore, Depending on the set disclosure level, the process involves anonymizing or abstracting the place names, company names, and financial information including sales or profit margins contained in the referral content into higher-level concepts or scope expressions, performing rule-based inspections of the generated referral content, or reflecting the results of comparisons with similar case information. By doing so, While ensuring confidentiality project characteristics and Candidate attributes We will efficiently create high-quality content tailored to the needs of the target audience and solve the aforementioned problems. [Effects of the Invention]

[0007] According to this invention, the content structure and output parameters are automatically controlled according to the attributes of the target business, the owner's intentions, and the succession scheme, thereby reducing the burden on individuals and efficiently generating high-quality introductory texts. In particular, by performing checks based on vocabulary rules, reflecting the results of comparisons with similar cases, and implementing revision loops based on evaluation values, it becomes possible to provide content with objective reliability and appeal. Furthermore, by integrating the recommendation of appropriate succession schemes in a chat format and anonymization processing for confidentiality, it achieves excellent technical and economic effects by simultaneously improving user convenience and supporting secure succession. [Brief explanation of the drawing]

[0008] [Figure 1] This is a block diagram showing the functional configuration of the information processing system according to this embodiment. [Figure 2] This flowchart shows the overall flow of the introductory content generation process in the information processing system of this embodiment. [Figure 3] This flowchart shows the procedure for obtaining information via chat and recommending the optimal succession scheme. [Figure 4] This is a conceptual diagram illustrating the process of calculating the similarity between a target project and similar case information based on multiple comparison axes. [Figure 5] This flowchart shows the procedure for inspecting and revising introductory content based on vocabulary rules and consistency rules. [Figure 6] This figure shows an example of an input screen for acquiring attribute information and owner intention information for the target business in the acquisition section. [Figure 7] This figure shows an example of a chat-based user interface for recommending succession schemes, provided by the recommendation department. [Figure 8] This figure shows an example of the evaluation results of the introductory content by the evaluation department and the proposed revisions by the revision department. [Figure 9] This figure shows an example of the output of introductory content where information has been anonymized or abstracted according to the set disclosure level. [Figure 10]A diagram showing variations in the layout and design of the introductory content switched according to the selected inheritance scheme and output parameters.

Best Mode for Carrying Out the Invention

[0009] Hereinafter, this embodiment will be described in detail with reference to the drawings.

[0010] FIG. 1 shows the functional configuration of the information processing system 10 according to this embodiment.

[0011] The information processing system 10 according to this embodiment supports information processing related to the succession of the target business.

[0012] The information processing system 10 is configured to be communicable with a user terminal via a communication network.

[0013] The user terminal is a terminal device used by an owner who wishes to succeed to the business or a supporter thereof.

[0014] Specific examples of the user terminal include a personal computer, a smartphone, a tablet terminal, and the like.

[0015] The information processing system 10 is realized by a computer including a communication unit, a processing unit, and a storage unit.

[0016] The communication unit is an interface for transmitting and receiving data to and from an external device.

[0017] The processing unit is an arithmetic device that controls the operation of the entire information processing system 10.

[0018] The processing unit is, for example, a central processing unit.

[0019] The storage unit is a medium that stores programs and various data executed by the processing unit.

[0020] The storage unit is composed of, for example, a hard disk drive or a solid-state drive.

[0021] The information processing system 10 includes an acquisition unit 100 as a functional unit.

[0022] The information processing system 10 includes a selection unit 110 as a functional unit.

[0023] The information processing system 10 includes a setting unit 120 as a functional unit.

[0024] The information processing system 10 includes a generation unit 130 as a functional unit.

[0025] The information processing system 10 includes a recommendation unit 180 as a functional unit.

[0026] The information processing system 10 may further include an inspection unit 140.

[0027] The information processing system 10 may further include a revision unit 150.

[0028] The information processing system 10 may further include a calculation unit 160 and an evaluation unit 170.

[0029] The information processing system 10 (see Figure 1) may further include an evaluation unit 170. The evaluation unit 170 outputs the evaluation results of the generated introductory content C (see Figure 8).

[0030] The acquisition unit 100 acquires at least one of the following: attribute information of the target business, owner intention information indicating the owner's intentions, and succession scheme information indicating the method of succession of the target business (see Figure 6).

[0031] The attribute information acquired by the acquisition unit 100 consists of quantitative data and factual information relating to the target business.

[0032] The owner intention information acquired by the acquisition unit 100 is information that indicates the owner's qualitative thoughts and desired conditions.

[0033] The succession scheme information acquired by the acquisition unit 100 is information that shows the specific methods for transferring the target business to another party.

[0034] The selection unit 110 selects the components to be used in the introductory content C according to the information acquired by the acquisition unit 100.

[0035] Introduction Content C is a collection of information intended to introduce the target business to potential successors.

[0036] The selection unit 110 controls at least one of the components and display content of the introduction content C according to the acquired succession scheme information.

[0037] The setting unit 120 sets various output parameters related to the introductory content C based on the information acquired by the acquisition unit 100.

[0038] The output parameters include settings related to the style, layout, and design of the introductory content C (see Figure 10).

[0039] The generation unit 130 generates the introduction content C based on the selected components of the introduction content C and the set output parameters. During this process, checks are performed based on vocabulary rules and consistency rules (see Figure 5), and anonymization is performed according to the disclosure level (see Figure 9).

[0040] The recommendation department 180 recommends candidate succession scheme L1, which is suitable for the target business succession case, based on the information obtained (see Figures 3 and 7). In making the recommendation, the similarity score calculated based on multiple comparison axes is referenced (see Figure 4).

[0041] Figure 2 shows the overall flow of the introductory content generation process in the information processing system 10 of this embodiment.

[0042] This process begins with acquisition step S1.

[0043] In acquisition step S1, the acquisition unit 100 acquires various information related to the target business from the user terminal.

[0044] Following the acquisition step S1, the selection step S2 is performed.

[0045] In selection step S2, the selection unit 110 selects information blocks to constitute the introductory content C based on the acquired information.

[0046] Following the selection step S2, the configuration step S3 is performed.

[0047] In setting step S3, the setting unit 120 shown in Figure 1 sets output parameters such as the writing style, layout, and design of the introductory content C.

[0048] As shown in Figure 2, the generation step S4 is executed after the setup step S3.

[0049] In generation step S4, the generation unit 130 generates the introductory content C using the selected components and output parameters.

[0050] Once the generation process by the generation unit 130 is complete, the series of processes ends and the generated introductory content C is output.

[0051] Next, with reference to Figure 6, the procedure for acquiring information by the acquisition unit 100 will be explained.

[0052] Figure 6 shows an example of input screen W2 for obtaining attribute information of the target business and owner's intentions.

[0053] The input screen W2 is displayed on the user terminal as a web page or application screen provided by the information processing system 10.

[0054] Input screen W2 includes attribute input field F1.

[0055] Attribute input field F1 is an interface for entering quantitative attribute information related to the target project.

[0056] The name and address of the target business are entered via the attribute input field F1.

[0057] The industry classification to which the target business belongs, as well as the year of establishment or founding of the target business, are entered via the attribute input field F1.

[0058] The most recent sales volume and profit level of the target business are entered via the attribute input field F1.

[0059] The number of employees of the target business and information on the main equipment owned by the target business are entered via the attribute input field F1.

[0060] The main customer base and debt status of the target business are entered via the attribute input field F1.

[0061] The attribute input field F1 can include a selection-based input interface such as a dropdown list or radio buttons.

[0062] Referring to Figure 6, the input screen W2 for which the acquisition unit 100 acquires attribute information of the target business and owner's intention information will be described. As shown in Figure 6, the input screen W2 includes an attribute input field F1 and an intention input field F2.

[0063] Attribute input field F1 can contain a text box for entering numerical values.

[0064] The intention input field F2 is an interface for entering the owner's intentions and qualitative anecdotes.

[0065] The user enters their thoughts on the business, the circumstances and story behind its establishment, the strengths and selling points of the target business, and the reasons for considering business succession through the input field F2.

[0066] Furthermore, via the intention input field F2, the user can input their desired conditions for the successor, their wishes regarding the retention of employee employment, their wishes regarding the continuation of the brand or company name, their desired succession timing, and their desired sale price and priority of conditions.

[0067] The intention input field F2 includes a text area where the owner can write free-form text.

[0068] In the intention input field F2, it is also possible to input text that has been converted from voice input.

[0069] The acquisition unit 100 receives each piece of information entered on the input screen W2 via the network and stores it in the storage unit.

[0070] By using input screen W2 in this way, it is possible to obtain all the basic information about the target business and the owner's qualitative thoughts without any omissions.

[0071] Next, referring to Figures 3 and 7, we will explain the procedure for interactive information acquisition using a chat format.

[0072] The acquisition unit 100 of the information processing system 10 can acquire information related to business succession cases in a chat format.

[0073] Figure 7 shows an example of a chat-based user interface for recommending succession schemes, provided by the Recommendation Department 180.

[0074] As shown in Figure 7, the chat screen W1 is displayed on the user's terminal screen.

[0075] The chat screen W1 (see Figure 7) displays the conversation history between user U and chatbot B.

[0076] User U is the owner or agent of the business in question.

[0077] Chatbot B is a virtual assistant controlled by the acquisition unit 100 and the recommendation unit 180 of the information processing system 10 (see Figure 1).

[0078] Chatbot B sends a message to user U with questions about business succession.

[0079] User U responds to a question from chatbot B by typing text or tapping on an option.

[0080] The acquisition unit 100 dynamically changes the order of subsequent questions according to the user U's answers in the conversation on the chat screen W1.

[0081] Figure 3 illustrates the procedure for obtaining information and recommending the optimal succession scheme using this chat format.

[0082] First, the acquisition unit 100 presents the first question to user U through chatbot B.

[0083] The first question is, for example, whether the current business structure is a corporation or a sole proprietorship.

[0084] If user U answers that they are a corporation, the acquisition unit 100 determines the second question.

[0085] The second question in this case would be, for example, whether or not the person wishes to transfer all of their shares.

[0086] On the other hand, if user U answers that they are a sole proprietor, the acquisition unit 100 determines a different second question.

[0087] A different second question in this case would be, for example, whether or not the tenant wishes to take over the existing store lease agreement as is.

[0088] The acquisition unit 100 analyzes the user U's previous response in this manner and selects the next question item according to a pre-set branching rule.

[0089] If user U provides a response regarding the presence or absence of debt, the acquisition unit 100 adds further questions based on that response to inquire about the user's financial situation in more detail.

[0090] If user U responds that they strongly desire the continued employment of the employee, the acquisition unit 100 will prioritize presenting questions that inquire about detailed information regarding the employee.

[0091] The acquisition unit 100 sequentially structures the information acquired during the dialogue process and stores it in the memory unit.

[0092] The acquisition unit 100 continues the conversation until all required questions have been answered.

[0093] If it is determined that all required questions have been covered, the acquisition unit 100 terminates the information acquisition phase.

[0094] By using a chat-style user interface, the input burden on user U can be reduced compared to static forms such as input screen W2 (see Figure 6).

[0095] By using the chat-style user interface, chat screen W1 (see Figure 7), even users U with limited knowledge of succession can provide necessary information to the information processing system 10 through natural dialogue.

[0096] Once information acquisition is complete, the recommendation department 180 (see Figure 1) begins the recommendation process for the succession scheme (see Figure 3).

[0097] Recommendation Department 180 recommends a succession scheme suitable for the business succession case based on information obtained via chat.

[0098] The recommendation unit 180 recommends the most suitable succession scheme from among several predefined succession schemes as succession scheme candidate L1.

[0099] Succession scheme options include stock transfer, business transfer, turnkey transfer, and employee succession.

[0100] In addition to these, variations of business transfer may include partial business transfers.

[0101] A stock transfer is a method of transferring management control of a company by transferring its shares to a buyer.

[0102] A business transfer is a method of transferring a company's business itself or its assets individually to a buyer.

[0103] "Turning over existing fixtures and equipment" is a method of transferring a store and its facilities to the next business operator in their original state.

[0104] Employee succession is a method of transferring a business to current employees or executives.

[0105] If the business entity acquired by the Acquisition Department 100 is a corporation and responds that it wishes to assume all liabilities, the Recommendation Department 180 will recommend a stock transfer as the top priority succession scheme candidate L1.

[0106] If the recommendation department 180 receives an indication that the company wishes to separate and transfer only a portion of the business, it will recommend the business transfer as succession scheme candidate L1.

[0107] Recommendation Department 180 recommends a turnkey business as succession scheme candidate L1 if the target business is a restaurant or retail store and the business responds that it wishes to close down early.

[0108] If user U responds that there is a capable person within the company who could be a successor, the recommendation department 180 will recommend employee succession as succession scheme candidate L1.

[0109] The recommendation unit 180 can use a logic that scores multiple succession schemes and recommends the one with the highest score.

[0110] The scoring by the recommendation department (180) is performed by calculating a weight for each response received.

[0111] For example, responses regarding the diversification of stock holdings significantly impact the stock transfer score.

[0112] For example, responses regarding the lease term of rental properties are used to calculate a score based on the comparison axis Ax (see Figure 4), and this affects the score for properties with existing fixtures and fittings.

[0113] The recommendation unit 180 can present the top multiple succession scheme candidates L1 on the chat screen W1 based on the calculated score (see Figure 7).

[0114] In Figure 3, the succession scheme candidate L1 recommended by the recommendation unit 180 is output to the chat screen W1 as a message from chatbot B.

[0115] Chatbot B presents succession scheme candidate L1, along with the reasons for its recommendation.

[0116] For example, chatbot B might present a message recommending the transfer of shares because it allows the company's history to be preserved as is.

[0117] User U performs the operation of selecting one of the presented succession scheme candidates L1.

[0118] Once user U confirms candidate succession scheme L1, that succession scheme is registered in the memory unit as succession scheme information for that case.

[0119] The selection unit 110 controls the components of the introduction content C according to the recommended succession scheme or the succession scheme selected by user U.

[0120] For example, if the succession scheme is a stock transfer, the selection unit 110 selects components that provide a detailed explanation of the financial information and history of the target company.

[0121] On the other hand, if the succession scheme involves taking over an existing business, the selection unit 110 prioritizes selecting components that describe the location, area, interior condition, and details of the kitchen equipment of the store.

[0122] Furthermore, if the succession scheme is employee succession, the selection unit 110 selects components that describe the current organizational structure and information about key employees.

[0123] Furthermore, the selection unit 110 controls the granularity of the displayed content and the structure of the headings according to the succession scheme.

[0124] The setting unit 120 sets the writing style of the introductory content C based on the owner intention information acquired by the acquisition unit 100 via the input screen W2 in Figure 6, etc.

[0125] For example, if the owner's intention information emphasizes enthusiasm or emotional episodes, the settings unit 120 sets a passionate and story-driven writing style as an output parameter.

[0126] On the other hand, if objective facts or logical reasons are emphasized in the owner's intention information, the setting unit 120 sets a calm and businesslike writing style as an output parameter.

[0127] The setting unit 120 sets the design proposal G1 for the introductory content C as an output parameter, according to the industry and target customer base of the business.

[0128] For example, if the target business is a beauty salon for young people, the setting unit 120 sets a bright and stylish design proposal G1.

[0129] For example, if the target business is a long-established manufacturing company, the setting unit 120 will set design proposal G1, which conveys a sense of reliability and solidity.

[0130] The settings unit 120 can also set output parameters for the layout proposal G2 of the introductory content C, such as a vertical layout proposal G2 suitable for smartphone screen sizes and a horizontal layout proposal G2 suitable for printing (see Figure 10).

[0131] The generation unit 130 integrates the components selected by the selection unit 110 and applies the writing style, layout proposal G2, and design proposal G1 set by the setting unit 120 to generate the final introductory content C (see Figures 1, 2, and 5). The generation result may be subject to evaluation results and revision candidates P1 as shown in Figure 8, or anonymization processing as shown in Figure 9.

[0132] The generation unit 130 formats the text data of attribute information and owner intention information acquired by the acquisition unit 100 using natural language processing to match the set writing style (see Figure 2).

[0133] The generation unit 130 supplements any missing conjunctions and adjusts the overall flow of the text to be smooth, while automatically generating appropriate headings for each selected element and arranging them according to the set layout plan G2 (see Figure 10).

[0134] The introductory content C generated by the generation unit 130 is displayed on the user terminal as a preview screen and awaits confirmation by the user U.

[0135] User U can review the preview screen and instruct the user to make minor adjustments to the content as needed.

[0136] If a correction instruction is input from user U, the generation unit 130 regenerates a portion of the introductory content C according to the instruction. At this time, the correction candidate P1 presented by the revision unit 150 based on the results of the inspection by the inspection unit 140 may be incorporated (see Figures 5 and 8).

[0137] The information processing system 10 can support both batch information acquisition using the input screen W2 and interactive information acquisition using the chat screen W1.

[0138] User U can choose one of the information acquisition methods according to their preference.

[0139] For example, in the initial stages, it is possible to easily input basic information in a chat format, and then later complete the detailed numerical values ​​on the input screen W2 (see Figures 6 and 7).

[0140] The acquisition unit 100 centrally manages the information acquired from both the input screen W2 and the chat screen W1, and integrates it to prevent duplication and inconsistencies.

[0141] The information acquired by the acquisition unit 100 is not limited to text information; for example, image information such as photos of the store's exterior or equipment uploaded from a user terminal can be acquired as part of the attribute information.

[0142] The selection unit 110 selects the uploaded image information as a component of the introductory content C, and the generation unit 130 arranges the image according to the set layout plan G2.

[0143] In generating the introductory content C, it is also possible to include a function that automatically adds specific notes for each succession scheme. For example, in the case of a turnkey property, notes regarding the transfer price of fixtures and fittings will be added, and in the case of a stock transfer, general notes regarding the risk of off-balance-sheet liabilities will be added.

[0144] This ensures that potential buyers are provided with the necessary information without being excessive or insufficient. Furthermore, the information may be anonymized or abstracted depending on the set disclosure level (see Figure 9).

[0145] The recommendation unit 180 can not only present a single succession scheme candidate L1, but can also present the first and second candidates in a comparable manner. In this case, the calculation unit 160 may utilize similarity scores V1, etc., calculated based on multiple comparison axes Ax (see Figures 3 and 4).

[0146] The advantages and disadvantages of both the first and second choices are displayed on the chat screen W1, supporting user U's decision-making.

[0147] These processes in the information processing system 10 can be executed in a cloud computing environment (see Figure 1).

[0148] Each functional unit of the information processing system 10 may be implemented as an independent service module in a microservices architecture.

[0149] The acquisition unit 100 may also have a function to acquire registration information and industry statistics data of the target business from an external database and to supplement the input of user U (see Figure 6).

[0150] The recommendation unit 180 can improve the accuracy of succession scheme recommendations by using a trained model that analyzes past transaction performance data (see Figure 7).

[0151] The generation unit 130 can generate higher quality and more natural-sounding text using a language model specialized for natural language generation (see Figure 2).

[0152] In this way, the information processing system 10 automates and optimizes a series of processes, from acquiring information to recommending succession schemes and generating introductory content C (see Figure 1).

[0153] This makes it possible to maximize the appeal of the target business and effectively appeal to potential successors.

[0154] Even business owners without specialized knowledge of business succession can easily prepare professional-quality introductory content C using this system.

[0155] By integrating the attribute information of the target business with the owner's intentions, a narrative-driven introductory content C is created, which is not merely a list of financial data. In this process, depending on the disclosure level, anonymization or abstraction of the anonymized section M1 may be performed (see Figure 9).

[0156] The dynamic reordering of questions in the chat format allows user U to complete information input via the shortest path without being bothered by unnecessary questions (see Figure 3).

[0157] By linking the recommendation of a succession scheme with the control of content structure based on it, introductory content C is created that perfectly matches the actual business and the form of transfer.

[0158] By adjusting the design proposal G1 and layout proposal G2 using the settings unit 120, it is possible to create a visual impression that is most suitable for the target customer group (see Figure 10).

[0159] The automatic generation function of the generation unit 130 significantly reduces the time and effort required to create the introductory content C.

[0160] The acquisition unit 100 constantly updates its internal status based on the latest input information, seamlessly supporting session interruptions and resumptions.

[0161] This allows user U to input information gradually during downtime in their work.

[0162] Chatbot B can have a function to send a reminder message if input is interrupted for a certain period of time.

[0163] Whenever additional information is obtained from user U, the recommendation unit 180 refers to the similarity score V1 (see Figure 4) calculated by the calculation unit 160 based on the comparison axis Ax, and re-evaluates the succession scheme recommendation results in real time.

[0164] If the recommended succession scheme candidate L1 changes as a result of the re-evaluation, user U will be promptly notified of this change.

[0165] In addition to the processing rules of the selection unit 110 and the setting unit 120, the logic related to the inspection by the inspection unit 140, the calculation of the evaluation value E1 by the evaluation unit 170, and the presentation of the revision candidate P1 by the revision unit 150 (see Figure 8) can be updated and optimized by the system administrator at any time (see Figure 5).

[0166] The series of processes described in this embodiment can be provided as a program for a computer to execute.

[0167] The program will be recorded and distributed on a non-transient, computer-readable storage medium.

[0168] The information processing system 10 can employ a scalable configuration in which multiple server computers cooperate to perform load balancing.

[0169] As described above, the basic configuration of the information processing system 10 is implemented as shown in Figure 1, the information acquisition procedure as shown in Figures 2 and 6, and the succession scheme recommendation process as shown in Figures 3 and 7. Furthermore, the inspection of the introduced content is implemented through the processes shown in Figure 5, evaluation as shown in Figure 8, anonymization as shown in Figure 9, and the variations in layout and design as shown in Figure 10.

[0170] The details of the processing performed by the calculation unit 160 will be explained with reference to Figure 4.

[0171] Figure 4 is a conceptual diagram illustrating the process of calculating the similarity between the target project and similar case information based on multiple comparison axes Ax.

[0172] The acquisition unit 100 acquires information on similar cases related to business succession cases that have already been concluded.

[0173] The information on similar cases includes various examples of business succession that have been successfully completed in the past.

[0174] The calculation unit 160 calculates the degree of similarity between the target project and the aforementioned similar project information based on multiple comparison axes Ax.

[0175] This similarity calculation quantitatively evaluates which past success stories the target project most closely resembles.

[0176] The multiple comparison axes Ax used by the calculation unit 160 include a variety of perspectives.

[0177] One example of multiple comparison axes Ax is the industry of the business being compared.

[0178] When using industry as the comparison axis Ax, hierarchical information such as major, medium, and minor classifications is referenced.

[0179] Similar projects with a high degree of industry similarity are considered likely to be operating under the same market environment and legal regulations.

[0180] A second example of multiple comparison axes Ax is the region of the project in question.

[0181] When using region as the comparison axis Ax, classifications ranging from broad areas at the prefectural level to detailed classifications at the municipal or specific commercial area level can be considered.

[0182] Similar projects with a high degree of regional similarity are considered to be located in environments with similar demographics and regional economic characteristics.

[0183] A third example of multiple comparison axes Ax is the scale of the business being considered.

[0184] When using business scale as the comparison axis Ax, quantitative indicators such as sales revenue, operating profit, and number of employees are referenced.

[0185] Similar projects with a high degree of similarity in scale are considered to have comparable levels of organizational maturity and financial risk.

[0186] A fourth example of multiple comparison axes Ax is the customer base of the target business.

[0187] When using customer segments as the comparison axis Ax, differences in transaction types, such as whether the business is aimed at individual consumers or corporations, are evaluated.

[0188] Furthermore, factors such as the age range, gender, and repeat purchase rate of the customer base also function as part of the comparison axis Ax.

[0189] Similar projects with a high degree of customer base similarity are considered to share common marketing strategies and ease of customer base transfer.

[0190] A fifth example of multiple comparison axes Ax is the equipment configuration of the project in question.

[0191] When using equipment configuration as the comparison axis Ax, tangible assets such as owned machinery and equipment, store interiors, and unique production lines are evaluated.

[0192] Similar projects with a high degree of similarity in equipment configuration are considered to have similar physical assets that the buyer will inherit.

[0193] A sixth example of the multiple comparison axis Ax is the succession scheme of the target business.

[0194] When using succession schemes as the comparison axis Ax, the commonality of the legal framework and practical procedures of the transactions is evaluated.

[0195] Similar cases with a high degree of similarity in succession schemes are considered to have similar challenges arising during contract negotiations and the handover process.

[0196] As shown in Figure 1, the calculation unit 160 quantifies the degree of agreement for each of these comparison axes Ax individually, as shown in Figure 4.

[0197] In quantifying each comparison axis Ax, methods such as semantic similarity derived from natural language processing or absolute error of numerical data are used.

[0198] Next, the calculation unit 160 assigns weights to the values ​​of each comparison axis Ax.

[0199] This weighting is dynamically adjusted according to the characteristics of the target business and the owner's intentions.

[0200] For example, if a particular specialized piece of equipment forms the core of a business, a larger weight will be assigned to the comparison axis Ax of the equipment configuration.

[0201] Alternatively, in the case of a locally focused retail business, a larger weight is assigned to the regional comparison axis Ax.

[0202] The calculation unit 160 aggregates the values ​​of each weighted comparison axis Ax and calculates an overall similarity score V1.

[0203] The similarity score V1 shown in Figure 4 is an indicator of the overall closeness between the target project and each similar project information. A higher score means that the target project is more strongly similar to the relevant similar project information.

[0204] The calculation unit 160 extracts from among multiple similar case information those in which the similarity score V1 exceeds a predetermined threshold.

[0205] The extracted information on similar cases will be treated as valuable reference data in subsequent processing.

[0206] The calculation unit 160 organizes the extracted similar case information and the comparison results with the target business as detailed data, and includes a detailed factor analysis of which comparison axis Ax shows the highest similarity.

[0207] The calculation unit 160 outputs the similarity score V1 and the comparison result to the generation unit 130 (see Figure 4).

[0208] In addition to the acquired information, the generation unit 130 acquires the similarity score V1 and comparison results received from the calculation unit 160.

[0209] The generation unit 130 directly incorporates the comparison results based on the calculated similarity score V1 into the generation of the introductory content C.

[0210] This processing transforms introductory content C from a mere list of facts into compelling content backed by past success stories.

[0211] As the first step in the reflection process, the generation unit 130 extracts the constituent elements of the introductory content C from the comparison results.

[0212] For example, if a particular information item attracted the buyer's interest in a successful transaction with a high similarity score V1, the generation unit 130 will adopt that information item as a component.

[0213] Similarly, the generation unit 130 excludes any information items deemed unnecessary in the case study from the introductory content C.

[0214] As the second step, the generation unit 130 extracts story elements from similar case information.

[0215] If stories about the founding process and overcoming difficulties in similar cases contributed to the closing of a deal, the generation unit 130 emphasizes similar episodes in the target business.

[0216] This makes it possible to tell stories that appeal to the emotions of potential buyers.

[0217] As the third step in the reflection process, the generation unit 130 extracts effective keywords that were used in similar case information.

[0218] The extracted keywords will be used as recommended vocabulary when generating introductory content C for the target business.

[0219] The generation unit 130 integrates these reflection procedures to construct a document structure that maximizes the appeal of the target business.

[0220] The processing of the selection unit 110 will be explained in detail.

[0221] The selection unit 110 has the function of selecting components to be used in the introduction content C according to the information acquired by the acquisition unit 100.

[0222] In particular, the selection unit 110 controls the components and display content of the introduction content C according to the recommended or selected succession scheme (see Figure 10).

[0223] Different succession schemes result in significantly different information and risk profiles that potential buyers prioritize.

[0224] Therefore, the selection unit 110 selects the information that best fits the succession scheme.

[0225] This scenario assumes that a stock transfer is envisioned as the succession scheme for the target business.

[0226] In the case of a stock transfer, the legal entity of the company is transferred as is, making it crucial to disclose the overall financial situation and legal risks.

[0227] The selection unit 110 selects components related to the trends in financial statements and potential liabilities in the case of a stock transfer.

[0228] Furthermore, the selection unit 110 gives greater weight to the displayed information regarding the composition of the board of directors and contractual relationships with existing business partners.

[0229] On the other hand, the priority of detailed information about the store's interior design is relatively lowered.

[0230] This scenario assumes that a business transfer is envisioned as the succession scheme for the target business.

[0231] In a business transfer, only specific business units or assets are separated and taken over.

[0232] In the case of a business transfer, the selection unit 110 prioritizes selecting components related to specific assets or personnel to be transferred.

[0233] Furthermore, the selection unit 110 differentiates assets that are not subject to transfer and gives greater weight to the display content regarding the profitability of the business unit alone.

[0234] This scenario assumes that the succession scheme for the target business involves taking over the existing premises.

[0235] In the case of a turnkey business, the location, interior design, and current state of the equipment are the most important factors in the transaction.

[0236] The selection unit 110, in the case of a store with existing fixtures and fittings, selects elements such as store floor plans, photographs, and information about pedestrian traffic in the surrounding area.

[0237] Furthermore, the selection unit 110 gives very high weight to the displayed content related to specific equipment lists such as kitchen equipment and air conditioning equipment.

[0238] This scenario assumes that employee succession is envisioned as the succession scheme for the target business.

[0239] In the case of employee succession, the focus becomes resolving internal interpersonal relationships and the personalization of tasks.

[0240] The selection unit 110 selects the skills of key employees and organizational structure components in the case of employee succession.

[0241] Furthermore, the selection unit 110 gives higher weight to the displayed content related to the plan for delegating authority from the owner to employees.

[0242] The selection unit 110 passes the list of components optimized for each succession scheme to the generation unit 130 (see Figure 2).

[0243] The weighting of the displayed content by the selection unit 110 also affects the order in which the information is arranged within the introductory content C (see Figure 10).

[0244] High-weight information is placed at the top of the featured content C to attract the viewer's attention early on.

[0245] Information with a lower weight is either collapsed and displayed as detailed information, or placed at the bottom.

[0246] Next, the process of setting output parameters by the setting unit 120 will be explained.

[0247] The setting unit 120 sets output parameters related to at least one of the following: style, layout, or design of the introductory content C, based on the information acquired by the acquisition unit 100 (see Figures 1, 2, and 6).

[0248] These output parameters serve as a blueprint for the generation unit 130 to determine the appearance and tone of the final introductory content C.

[0249] The first element of the output parameters is the writing style of the introductory content C.

[0250] The settings unit 120 sets the style parameters based on the taste preferences included in the owner's preference information.

[0251] For example, if a formal inter-company transaction is desired, the settings unit 120 sets objective and formal style parameters.

[0252] Conversely, if you want to emphasize approachability or a connection to the local community, the settings unit 120 can set warm, emotional writing style parameters.

[0253] Furthermore, stylistic parameters such as the overuse of technical jargon and the rewriting of text into simpler language are adjusted according to the attributes of the potential buyer.

[0254] The second element of the output parameters is the layout of the introductory content C.

[0255] Figure 10 shows variations of layout proposal G2 and design proposal G1 for introductory content C, switched according to the selected succession scheme and output parameters.

[0256] The setting unit 120 sets the optimal layout plan G2 according to the number and type of components selected by the selection unit 110 (see Figures 3 and 7).

[0257] In the case of a pre-existing property with many photos and diagrams, the settings unit 120 selects layout option G2, which places a large amount of visual elements.

[0258] In the case of a stock transfer case with a large amount of numerical data, the settings unit 120 selects layout option G2, which facilitates comparison in a table format.

[0259] The third element of the output parameters is the design of the introductory content C.

[0260] The setting unit 120 sets an appropriate design proposal G1 according to the industry and corporate colors of the target business.

[0261] For example, in the food and beverage industry, design proposal G1, which is based on warm colors, is often chosen.

[0262] For medical and welfare-related fields, design proposal G1, which uses cool colors to convey a sense of cleanliness and trustworthiness, is selected.

[0263] The setting unit 120 supplies output parameters, which integrate these writing styles, layout proposals G2, and design proposals G1, to the generation unit 130.

[0264] The generation unit 130 combines the components of the selected introductory content C with the set output parameters.

[0265] In addition to this information, the generation unit 130 generates the final introductory content C based on the calculated similarity score V1, inspection results, or evaluation value E1, etc. (See Figures 4, 5, 8, and 9).

[0266] The generation process performed by the generation unit 130 is an advanced information integration process designed to convey the appeal of the target business to the fullest extent.

[0267] The generation unit 130 spins the extracted information into natural language text according to the set style parameters (see Figure 2).

[0268] In this process, the generation unit 130 reflects the comparison results from the calculation unit 160 and incorporates persuasive expressions obtained from similar case information.

[0269] Furthermore, the generation unit 130 determines the structure and emphasis of the text according to the weighting assigned by the selection unit 110.

[0270] Once the text generation is complete, the generation unit 130 places each element on the screen according to the layout plan G2 specified by the setting unit 120 (see Figure 10).

[0271] The generation unit 130 then applies the specified design proposal G1 and makes visual adjustments such as font, color, and margins.

[0272] In this way, introductory content C is completed, which reflects the unique characteristics of the target business, is optimized for the succession scheme, and incorporates insights based on past success stories.

[0273] The completed introductory content C is highly appealing to potential buyers.

[0274] Through the above series of processes, the information processing system 10 automatically converts complex business succession case information into easy-to-understand and attractive content (see Figure 1).

[0275] The multi-axis comparison by the calculation unit 160 is a mechanism for grasping the essential value of a business, rather than just a keyword match (see Figure 4).

[0276] In the comparison axis Ax of industry types, objective criteria such as the Japanese Standard Industrial Classification may be used in some cases.

[0277] In the comparison axis Ax of regions, not only administrative divisions but also the connection of transportation networks and economic circles may be considered in some cases.

[0278] In the comparison axis Ax of business scale, not only the numerical values of a single year but also the growth rate and stability over the past few years may be evaluated in some cases.

[0279] In the comparison axis Ax of customer segments, the concentration and dispersion degree of customers may be used as the criteria for judging similarity in some cases.

[0280] In the comparison axis Ax of equipment configuration, the service life and degree of obsolescence of equipment may be considered in some cases.

[0281] In the comparison axis Ax of succession schemes, the asking price for transfer and the approximation of the transaction timeline may be taken into account in some cases.

[0282] In the calculation of the similarity score V1, these various factors are integrated by a complex calculation model.

[0283] The calculation model may adopt an algorithm that learns from past transaction results in some cases.

[0284] As a result, the similarity score V1 always becomes an accurate indicator that reflects the latest market trends.

[0285] When the generation unit 130 reflects the comparison results from the calculation unit 160 into the introductory content C, it does not simply copy the text of similar cases, but rather extracts abstract patterns that are factors for success from the information of similar cases and applies them to the specific information of the target business.

[0286] This allows for an effective appeal structure while maintaining originality.

[0287] Through the control of the selection unit 110, the featured content C has an information structure that is directly linked to the viewer's needs.

[0288] Financial information emphasized in the case of a stock transfer is presented in a visually easy-to-understand format using graphs and charts (see Figure 10).

[0289] In the case of a business transfer, the asset list is emphasized and presented in a tabular format that ensures comprehensiveness and accuracy (see Figure 10).

[0290] When a property is offered as a pre-existing, fully-equipped space, the store information is emphasized and presented in a realistic way, often incorporating panoramic photos and floor plans (see Figure 10).

[0291] In the case of employee succession, the organizational information emphasized is presented as a diagram that clearly shows the roles and collaborative structures of each department (see Figure 10).

[0292] The output parameters set by the setting unit 120 greatly influence the first impression of the introductory content C.

[0293] By fine-tuning stylistic parameters, the impression a reader receives can change significantly, even when conveying the same facts.

[0294] The appropriate selection of layout option G2 ensures that the reader's gaze is guided in a way that prevents eye strain even with a large amount of information (see Figure 10).

[0295] The appropriate selection of design proposal G1 ensures that the brand image of the target business is accurately conveyed (see Figure 10).

[0296] The generation unit 130 has a function of quickly generating the introduction content C that satisfies all these requirements simultaneously.

[0297] The generated introduction content C emits unique charm according to the characteristics of the case (see Figure 2).

[0298] By using a plurality of comparison axes Ax by the calculation unit 160, useful insights may be drawn from successful cases in different industries that seemingly appear unrelated (see Figure 4).

[0299] For example, the story development of cases in different industries determined to have high similarity on the customer layer comparison axis Ax may be adopted in the introduction content C of the target business.

[0300] The mechanism of multi-axis comparison by the calculation unit 160 presents a novel appeal method that cannot be obtained by conventional single-axis search (see Figure 4).

[0301] The generation unit 130 adjusts the text considering not only the height of the similarity score V1 but also which comparison axis Ax contributed to the similarity.

[0302] When the contribution degree of the regional comparison axis Ax is high, a story emphasizing the contribution to the local community and the local recognition is constructed.

[0303] [[ID=​​​​​​​​​​​​This collaboration seamlessly transforms the acquired raw information into strategic and engaging promotional content C (see Figure 2).

[0307] The processing performed by the calculation unit 160 (see Figure 1) functions as the core intelligence of the entire information processing system 10.

[0308] The advanced generation capabilities of the generation unit 130 are only fully realized through the precise output parameters provided by the setting unit 120.

[0309] The diversity of design proposals G1 and layout proposal G2 shown in Figure 10 demonstrates that the information processing system 10 can flexibly adapt to various industries and succession schemes.

[0310] In this way, by calculating similarity based on multi-axis comparison and dynamically setting output parameters based on that similarity, the introductory content C is always output in the optimal form.

[0311] Furthermore, clearly articulating the strengths of the target business facilitates a smoother evaluation process by potential buyers.

[0312] The analysis results for each comparison axis Ax in the calculation unit 160 provide guidance on which parts of the introductory content C should be persuasive and what kind of persuasive arguments should be made.

[0313] The generation unit 130 faithfully follows these guidelines and assembles introductory content C that is both logical and emotionally appealing.

[0314] The style parameters managed by the settings unit 120 include detailed specifications such as sentence length and the ratio of active to passive voice.

[0315] This allows for control over the rhythm and readability of introductory content C.

[0316] Layout proposal G2 also includes display optimization information for each device, such as for smartphones and personal computers.

[0317] Design proposal G1 may include specifications for contrast ratios that take accessibility into consideration.

[0318] The generation unit 130 outputs a complete introductory content C while satisfying all of these constraints (see Figure 9).

[0319] This series of advanced information processing provides a powerful tool for successfully guiding the succession of the target business.

[0320] The objectivity of the similarity score V1 (see Figure 4) calculated by the calculation unit 160 forms the basis for ensuring the reliability of the featured content C.

[0321] The weighting of information by the selection unit 110 reduces the cognitive load on the reader and prevents important information from being overlooked.

[0322] The output parameter settings by the setting unit 120 respect the individuality of each case and avoid uniform output.

[0323] By combining these processes, the information processing system 10 according to this embodiment achieves an extremely practical output.

[0324] When industry information is evaluated as a comparison axis Ax, the target business may operate across multiple industries.

[0325] In that case, the calculation unit 160 compares not only the main industry but also the secondary industry with similar case information.

[0326] In the regional comparison axis Ax, not only the location of the head office but also the main sales area and the distribution area of ​​customers are included in the comparison.

[0327] The Ax axis for comparing business scale takes into account not only the latest financial data but also trends from the past several years.

[0328] In the customer segment comparison axis Ax, risk factors such as the degree of dependence on specific high-value customers are also included as comparison elements.

[0329] In the equipment configuration comparison axis Ax, not only company-owned equipment but also the presence or absence of lease agreements are included in the evaluation.

[0330] In the comparison axis Ax of succession schemes, factors such as the owner's desired retirement date and the conditions for continued employment of employees are also taken into consideration.

[0331] The calculation unit 160 represents this detailed information as a multidimensional vector and derives a similarity score V1 (see Figure 4) by calculating the distance between the vectors.

[0332] The generation unit 130 is responsible for reconstructing these multidimensional comparison results into a one-dimensional sentence in natural language.

[0333] The selection unit 110 acts as the command center in this reconstruction process, determining the priority of which information should be presented first.

[0334] The setting unit 120 plays the role of a director, determining the embellishment and presentation of the text.

[0335] Through this functional division of labor among the various departments (see Figure 1), the attribute information of the target business acquired by the acquisition department 100 (see Figure 6), the owner's intention information, and the succession scheme information via the recommendation department 180 (see Figures 3 and 7) are converted into the most effective introduction content C.

[0336] In generating introductory content C (see Figure 2), the track record of successful deals for similar projects always serves as supporting evidence, ensuring consistent content quality.

[0337] The similarity score V1 calculated by the calculation unit 160 can be referenced not only for generating the introductory content C, but also for other functions of the system.

[0338] For example, the market value and strengths of a target business can be objectively redefined based on the results of comparing information on multiple similar projects.

[0339] The generation unit 130 places the redefined strengths of the target business in the most prominent position in the introductory content C (see Figure 9).

[0340] When the selection unit 110 selects components according to the succession scheme, legally required disclosure items are always included in the selection.

[0341] As a result, introductory content C is not only attractive, but also meets the practical requirements after being processed by the evaluation unit 170 (see Figure 8) and the revision unit 150 (see Figure 5).

[0342] The configuration unit 120 may also utilize a set of templates prepared in advance by the system operator when setting output parameters.

[0343] The template set includes the base models for design proposal G1 and layout proposal G2 shown in Figure 10.

[0344] The generation unit 130 infuses specific information into the template while applying dynamic transformations according to the output parameters.

[0345] As a result, a unique introductory content C, possessing a context specific to the target business, is created.

[0346] As described above, the process of generating introductory content C based on multi-axis comparison of similar cases and output parameters is completed (see Figure 2).

[0347] Next, we will describe in detail the quality check and revision loop process for the generated introductory content C.

[0348] The information processing system 10 in this embodiment includes a mechanism to mechanically guarantee the quality of the generated introductory content C (see Figure 1).

[0349] Specifically, the information processing system 10 includes an inspection unit 140 that inspects the contents of the introductory content C according to the rules.

[0350] Furthermore, the information processing system 10 includes an evaluation unit 170 that quantitatively evaluates the quality of the generated introductory content C.

[0351] The information processing system 10 also includes a revision unit 150 that prompts the modification or regeneration of the introductory content C based on the inspection results and evaluation results (see Figure 8).

[0352] Figure 5 is a flowchart showing the procedure for inspecting and revising introductory content C based on vocabulary rule R1 and consistency rule R2.

[0353] The introductory content C generated by the generation unit 130 is first handed over to the inspection unit 140.

[0354] The inspection unit 140 performs an automated inspection process on each component of the generated introductory content C.

[0355] This testing process is broadly divided into two stages: a vocabulary test and a content consistency test.

[0356] As the first step, the inspection unit 140 performs inspection processing based on vocabulary rule R1.

[0357] Vocabulary rule R1 is a set of rules for determining whether appropriate terminology is used in content C, which introduces business succession cases.

[0358] Vocabulary rule R1 includes rules to restrict the use of certain expressions.

[0359] Specifically, vocabulary rule R1 includes an NG word dictionary that specifies prohibited words that should be avoided.

[0360] The NG word dictionary contains pre-registered words that may give an inappropriate impression when introducing business succession.

[0361] For example, exaggerated language that implies excessive guarantees to buyers is included in the dictionary of prohibited words.

[0362] The dictionary of forbidden words also includes direct expressions that evoke legal disputes.

[0363] The inspection unit 140 performs morphological analysis on the text data of the introductory content C and compares it with the NG word dictionary.

[0364] If any prohibited words matching the NG word dictionary are found within the introductory content C, that section will be extracted as a non-compliant section.

[0365] Furthermore, vocabulary rule R1 includes a recommended word dictionary that specifies expressions that are desirable to use.

[0366] The recommended word dictionary contains positive expressions that effectively convey the appeal of the target business.

[0367] For example, specialized terms and adjectives that indicate technical capabilities or the stability of the customer base are defined in the recommended word dictionary (see Figure 5).

[0368] The inspection unit 140 checks whether the generated introductory content C appropriately includes terms from the recommended word dictionary.

[0369] If any recommended terminology is missing from a particular appeal block, that information is transmitted to the revision section 150.

[0370] Furthermore, vocabulary rule R1 is structured to allow the application of different dictionaries depending on the industry of the target business.

[0371] This is because the appropriate vocabulary differs between introductory content C for the manufacturing industry and introductory content C for the food and beverage industry.

[0372] The inspection unit 140 determines the industry attributes of the target business and selectively applies the NG word dictionary and recommended word dictionary corresponding to that industry.

[0373] This ensures that introductory content C is composed of vocabulary that aligns with the business practices and common expressions specific to each industry.

[0374] Once the check based on vocabulary rule R1 is complete, the second stage is performed by the check unit 140, which then performs a check based on consistency rule R2, as shown in Figure 5.

[0375] Consistency rule R2 is a set of rules for detecting whether there are any factual inconsistencies or logical inconsistencies within the introductory content C.

[0376] In business succession case introductions, quantitative and qualitative information are often mixed, leading to inconsistencies in the content.

[0377] The inspection unit 140 automatically detects this inconsistency using consistency rule R2.

[0378] Consistency rule R2 includes rules for detecting inconsistencies in numerical values.

[0379] For example, it is checked whether the sales figures and profit figures mentioned in the main text of introductory content C match the figures entered as attribute information.

[0380] If a numerical value in the text differs from a numerical value in the attribute information, the inspection unit 140 detects this as a numerical inconsistency.

[0381] Similarly, quantitative information such as the number of employees and the number of stores will also be checked for inconsistencies.

[0382] Consistency rule R2 also includes rules for detecting inconsistencies regarding dates and timelines.

[0383] For example, it is checked whether the founding year or the year indicating a turning point in the business is logically consistent with the owner's age or the company's founding year.

[0384] If the order of past events is unnaturally reversed, the inspection unit 140 detects this as a contradiction in the year numbers.

[0385] Furthermore, consistency rule R2 includes rules for detecting inconsistencies regarding place names.

[0386] The system verifies whether the place names indicating the location and main service area of ​​the target business match the acquired regional attribute information (see Figure 6).

[0387] If the name of a completely unrelated region is mistakenly generated in the main text of introductory content C, the inspection unit 140 (see Figure 1) identifies it as a place name inconsistency (see Figure 5).

[0388] Consistency rule R2 also includes rules for detecting inconsistencies in the succession scheme (see Figure 7).

[0389] For example, even if a stock transfer is selected, it will be checked whether the text uses language that suggests only a portion of the business is being transferred.

[0390] If the selected succession scheme (see Figure 3) does not match the wording in the text, the inspection unit 140 detects this as a contradiction in the succession scheme.

[0391] Furthermore, consistency rule R2 includes rules for detecting inconsistencies regarding person attributes.

[0392] The document will be checked to ensure that it does not contain any statements that contradict the owner's position, years of experience, or the persona of the expected candidate.

[0393] The inspection unit 140 applies these consistency rules R2 and performs inconsistency detection processing (see Figure 5) across all paragraphs of the introductory content C.

[0394] Sections where inconsistencies are detected are tagged as non-conforming sections and carried over to subsequent revision processes.

[0395] In this way, the testing unit 140 uses both the vocabulary rule R1 and the consistency rule R2 to perform a comprehensive test in accordance with the overall flow (see Figure 2).

[0396] The evaluation unit 170 (see Figure 1) performs processing in parallel with, or after, the inspection by the inspection unit 140.

[0397] Figure 8 shows an example of the evaluation results of the introductory content C by the evaluation unit 170 and the display of the proposed revision P1.

[0398] The evaluation unit 170 calculates an evaluation value E1 that indicates the overall quality of the generated introductory content C (see Figure 9).

[0399] Multiple evaluation axes are used comprehensively to calculate the evaluation score E1.

[0400] The primary evaluation criterion is the readability and fluency of the writing.

[0401] The evaluation unit 170 analyzes factors such as sentence length and the appropriate frequency of conjunction use, and scores the readability.

[0402] The second evaluation criterion is the comprehensiveness of the information (see Figure 4).

[0403] The system verifies whether important elements from the acquired attribute information and owner intention information are appropriately reflected in the introductory content C (see Figure 6).

[0404] The third evaluation criterion is the consistency of the message being conveyed.

[0405] The analysis will assess whether the strengths and appeal of the target business are consistently expressed throughout the entire introductory content C (see Figure 10).

[0406] The fourth evaluation criterion is the candidate's suitability.

[0407] The evaluation assesses whether the language and structure used are effective in resonating with the attributes of the assumed candidates.

[0408] The evaluation unit 170 calculates scores for each of these evaluation axes, weights them, and determines the final evaluation value E1.

[0409] The calculated evaluation value E1 is compared to a predetermined threshold.

[0410] If the evaluation value E1 is above the threshold, the generated introductory content C is determined to meet a certain quality standard.

[0411] If the evaluation value E1 is below the threshold, it is determined that the featured content C requires significant modification or regeneration.

[0412] The inspection results from the inspection unit 140 and the evaluation value E1 calculated by the evaluation unit 170 are sent to the revision unit 150.

[0413] Based on this information, the revision unit 150 performs processing to modify and regenerate the introductory content C according to the processing procedure in Figure 5.

[0414] The revision section 150 identifies non-compliant sections and areas with low ratings and presents them to user U or the system.

[0415] As shown in Figure 8, the revision unit 150 outputs the detected problematic areas along with the suggested corrections P1 on the screen.

[0416] Revision candidate P1 is a specific text proposal to replace the deemed unsuitable expressions with appropriate ones.

[0417] For example, if a prohibited word corresponding to the NG word dictionary of vocabulary rule R1 is detected, the revision unit 150 generates an alternative expression that does not include that word as a candidate for revision P1.

[0418] If a term is missing from the recommended word dictionary for vocabulary rule R1, a sentence incorporating that term in a natural way will be presented as a suggested revision P1.

[0419] If numerical inconsistencies are detected by consistency rule R2, the text with the numerical values ​​replaced based on the correct attribute information will be output as correction candidate P1.

[0420] Similarly, for inconsistencies in year names and place names, a corrected candidate P1 is created based on the correct facts, following consistency rule R2.

[0421] Revision section 150 not only presents candidate revisions P1 but also extracts candidates for regenerating introductory content C.

[0422] If there are so many inconsistencies that they cannot be addressed by local corrections, revision section 150 proposes regenerating the entire paragraph or the entire introductory content C.

[0423] If a candidate for regeneration is selected, the generation unit 130 is instructed to perform the generation process of the introductory content C again.

[0424] At this point, the revision unit 150 provides the generation unit 130 with additional parameters and constraints to avoid the inconsistencies that occurred in the previous generation.

[0425] For example, restrictions may be imposed to ensure that certain forbidden words are never included, or to ensure that specific recommended words are always included.

[0426] This increases the probability that the second generation process will produce higher quality introductory content C than the first time.

[0427] The regenerated introductory content C is again processed by the inspection unit 140 and the evaluation unit 170.

[0428] In other words, the processes carried out by the generation unit 130, inspection unit 140, evaluation unit 170, and revision unit 150 in the information processing system 10 (see Figure 1) do not follow a single linear flow, but rather form loops as shown in Figures 2 and 5.

[0429] It is also possible to configure the system so that this loop is repeated until no more defects are detected in the inspection unit 140 (see Figure 5).

[0430] Alternatively, the loop is automatically repeated until the evaluation value E1 calculated by the evaluation unit 170 exceeds a predetermined threshold.

[0431] This iterative process establishes a quality improvement loop for the featured content C.

[0432] User U can monitor the progress of this quality improvement loop through a screen like the one shown in Figure 8.

[0433] User U can choose whether or not to manually adopt the suggested revision P1 presented by the revision section 150.

[0434] The suggested revision P1 will be reflected in the main text based on the user U's selection.

[0435] Furthermore, user U can also instruct the generation unit 130 to perform regeneration.

[0436] The existence of a quality improvement loop reduces the risk (see Figure 9) of the generated, incomplete introductory content C being published externally as is.

[0437] In particular, in business succession cases, inappropriate language can damage the trust between the parties involved.

[0438] Such risks are avoided by the inspection unit 140 strictly eliminating prohibited words based on vocabulary rule R1.

[0439] Furthermore, factual inaccuracies can lead to distrust from potential buyers.

[0440] The accuracy of the information is ensured when the inspection unit 140 detects inconsistencies in factual information, including numerical values, using consistency rule R2.

[0441] Furthermore, the appeal of the target project is fully articulated through testing based on the recommended word dictionary included in vocabulary rule R1.

[0442] The calculation of the evaluation value E1 by the evaluation unit 170 serves to guarantee the overall balance and readability of the introductory content C, and is also applied to variations in layout and design as shown in Figure 10.

[0443] Even without local errors, if the text is unnatural as a whole, the evaluation score E1 will decrease.

[0444] Since the revision unit 150 uses the results of both the inspection by the inspection unit 140 and the evaluation by the evaluation unit 170, it becomes possible to differentiate between microscopic corrections and macroscopic regeneration.

[0445] The automatic generation of suggested revisions (P1) by revision section 150 dramatically reduces the burden of manual editing.

[0446] This is because, instead of rewriting the text from scratch, quality improvement can be achieved simply by selecting the suggested revision P1 provided by the system.

[0447] During regeneration, instead of simply repeating the same process, error information is fed back, allowing the information processing system 10 to perform intelligent regeneration.

[0448] Thus, the information processing system 10 of this embodiment does not end with generating the introductory content C (see Figures 1 and 2).

[0449] The generated introductory content C has a mechanism in which the inspection unit 140 strictly inspects it according to the rules.

[0450] Furthermore, the evaluation unit 170 has a mechanism that performs scoring based on multiple evaluation axes and calculates an evaluation value E1.

[0451] The revision unit 150 then has a mechanism to autonomously or interactively refine the introductory content C based on these results (see Figures 3 and 7).

[0452] By linking these processes, a practical introduction content C is provided, even in the area of ​​business succession, which requires a high level of accuracy and consideration (see Figures 9 and 10).

[0453] Further details of the internal processing of the inspection unit 140 are described below (see Figure 5).

[0454] The vocabulary rule R1 is maintained as a dictionary database that is updated regularly.

[0455] If new terms deemed inappropriate arise due to changes in laws and regulations or social conditions, they will be promptly added to the NG word dictionary and reflected in vocabulary rule R1.

[0456] Similarly, any new business terms that become trends or expressions specific to succession schemes will be added to the recommended word dictionary.

[0457] The consistency rule R2 involves not just simple text matching, but also analysis based on an understanding of the context (see Figure 5).

[0458] For example, not only the number immediately following the word "sales revenue," but also numbers linked to other expressions that mean "sales revenue" in context, are subject to consistency rule R2 inspection.

[0459] This allows for accurate detection of inconsistencies even if there are variations in spelling or wording.

[0460] The calculation logic for the evaluation value E1 by the evaluation unit 170 is continuously adjusted by the calculation unit 160 using data from past successful transactions (see Figures 4 and 8).

[0461] The linguistic characteristics of the introductory content C for successful deals are analyzed, and the parameters are adjusted to achieve a high evaluation score of E1.

[0462] As a result, the evaluation score E1 reflects not only the beauty of the writing but also a practical indicator of its likelihood of leading to a sale.

[0463] It is preferable that multiple revision candidates P1 presented by the revision section 150 be provided (see Figure 8).

[0464] This is to allow user U to select the optimal correction candidate P1 that matches their preferred tone and nuance (see Figure 6).

[0465] For example, for a particular non-conforming section, both a polite and a concise version of the suggested correction (P1) are output simultaneously.

[0466] When user U selects one of the suggested corrections P1, the selection result is stored as training data in the information processing system 10.

[0467] In the next revision process, revision candidate P1, which is similar to the trend previously selected by user U, will be presented preferentially.

[0468] Thus, the quality improvement loop evolves not only within a single generation process but also through the long-term use of the entire information processing system 10.

[0469] As shown in the flowcharts in Figures 1 and 5, the processing of the inspection unit 140 and the revision unit 150 is modularized.

[0470] Therefore, even if the specifications of the generation unit 130 are changed, the inspection and revision logic will continue to function independently.

[0471] Furthermore, even when using multiple different generation engines in parallel, applying the same vocabulary rule R1 and consistency rule R2 ensures uniform output quality for the featured content C.

[0472] The screen interface in Figure 8 displays the evaluation value E1 in a visual format such as a radar chart or score bar.

[0473] User U can intuitively grasp at a glance which parts of the featured content C are poorly rated and which parts need to be corrected.

[0474] Areas requiring correction are highlighted, and an interaction is provided where correction suggestions (P1) pop up when the mouse pointer is hovered over them.

[0475] This intuitive interface allows even owners without specialized knowledge to easily revise introductory content C.

[0476] As a result, the time and psychological hurdles required to create business succession introductory content C are significantly reduced.

[0477] The quality improvement loop established by this information processing system 10 plays the role of performing an initial audit before human visual checks.

[0478] The information processing system 10 meticulously picks up even slight discrepancies in year numbers and inconsistencies in notation that humans might easily overlook.

[0479] Humans can specialize in the role of reviewing the proposed corrections P1 presented by the information processing system 10 and making the final decision.

[0480] This dramatically improves the productivity of the entire production process for introductory content C (see Figure 2).

[0481] The revision section 150 may not only instruct regeneration by adjusting specific parameters, but may also propose changes to the structure of the introductory content C itself.

[0482] For example, this applies to cases where a paragraph has an extremely low evaluation score (E1) and applying the suggested revision (P1) does not lead to improvement.

[0483] In this case, revision section 150 presents a regeneration candidate that deletes the entire paragraph and inserts a new paragraph with a different approach extracted from another similar case.

[0484] The multiple versions of introductory content C generated during the quality improvement loop are saved as a version history.

[0485] User U can also revert to a previous version and try a different fix candidate P1.

[0486] Inconsistency detection using consistency rule R2 is cross-checked with all attribute information acquired by the acquisition unit 100 (see Figure 5).

[0487] If the entered attribute information itself contains inconsistencies, the errors in the original attribute information may be discovered through the inspection results of the introductory content C.

[0488] In this case, the revision section 150 outputs not only the suggested revision P1 for the introductory content C, but also an alert prompting revision of the original data.

[0489] Thus, the processing performed by the inspection unit 140 contributes not only to ensuring the quality of the introductory content C but also to ensuring the consistency of the entire case data.

[0490] The inspection unit 140 can also be equipped with a gatekeeper function that prevents the process from proceeding to the next stage if any non-conforming parts remain in the introductory content C.

[0491] This prevents information containing significant risks from being mistakenly released at the information processing system level 10.

[0492] Vocabulary Rule R1 can be customized to reflect the company's own internal regulations and compliance standards.

[0493] You can add your own custom dictionary of forbidden words that complies with the policies of specific intermediary companies or platforms as an add-on.

[0494] This allows the information processing system 10 to flexibly respond to the requirements of various businesses.

[0495] The evaluation unit 170 outputs both positive and negative evaluation reasons in text when calculating the evaluation value E1 (see Figure 8).

[0496] User U can understand not only the numerical score but also the reasoning behind why that rating of E1 was given.

[0497] By presenting the reasons for this evaluation along with the proposed revision P1, user U can proceed with the revision work with a sense of understanding.

[0498] When presenting candidates for regeneration, user U is given options regarding the approach to regeneration.

[0499] For example, you can choose to regenerate it in a more emotionally appealing tone or in a more logical and objective tone.

[0500] Based on the selected policy, the revision unit 150 dynamically changes the parameters for the generation unit 130.

[0501] This dynamic regeneration mechanism allows for the adjustment of the featured content C until it perfectly matches the user U's intent.

[0502] The existence of a quality improvement loop means that even if the information processing system 10 cannot produce perfect output in its initial state, it will guarantee the final output quality.

[0503] Through iterative revisions and evaluations, a sophisticated introductory content C is created that is adapted to the complex context of business succession.

[0504] As described above, inspections based on the vocabulary rule R1 and consistency rule R2 of the inspection department 140 play a central role in quality control.

[0505] The calculation of the evaluation value E1 in the evaluation unit 170 and the extraction of the revision candidate P1 and regeneration candidate in the revision unit 150 are the driving forces behind the loop.

[0506] Through this series of processes (see Figure 2), the information processing system 10 can stably supply safe and high-quality business succession case introduction content C (see Figure 1).

[0507] The coordination of these distinctive functions is key to improving content quality in this embodiment.

[0508] In the specific context of business succession, this rigorous cycle of review and revision provides extremely important value.

[0509] Thoroughly eliminating taboo words protects the psychological safety of those involved.

[0510] Appropriately assigning recommended keywords highlights the true value of a business without obscuring it.

[0511] Ensuring consistency strengthens the reliability of the information that forms the basis of transactions.

[0512] Automated evaluation and revision suggestions mean that the system compensates for the absence of professional editors.

[0513] As a result, every user U can obtain high-quality referral content C that meets or exceeds a certain standard.

[0514] This quality improvement loop demonstrates that this information processing system 10 is not merely a document creation tool, but an intelligent support system.

[0515] Through repeated processing, the featured content C becomes more refined and polished.

[0516] The steps shown in Figures 3, 4, 5, 7, and 8 are organically interconnected and function toward a single purpose.

[0517] The objective is to derive the optimal promotional content C that best conveys the appeal of the target business while minimizing risks.

[0518] The setting unit 120 sets candidate attributes and disclosure level as output parameters (see Figure 10).

[0519] These candidate attributes provide information that indicates the characteristics and background of candidates who are interested in the business to be taken over.

[0520] For example, candidate attributes include the candidate's industry, company size, location, business strategy, and financial strength, which are entered via attribute input field F1, etc.

[0521] On the other hand, the disclosure level is an indicator that defines how detailed the information regarding the target business will be made public.

[0522] The setting unit 120 determines the basic disclosure level based on the intention information obtained from the owner via the intention input field F2 on the input screen W2 (see Figure 6).

[0523] Furthermore, the settings unit 120 can dynamically change the disclosure level according to the attributes of each candidate who will be viewing the information.

[0524] The generation unit 130 controls the information to be included in the introductory content C according to the disclosure level set by the setting unit 120.

[0525] Specifically, the generation unit 130 performs anonymization processing on the anonymized section M1 of the information in the introductory content C that leads to the identification of the target business, according to the disclosure level (see Figure 9).

[0526] Furthermore, as shown in Figures 1 and 2, the generation unit 130 performs abstraction processing to replace information with higher-level concepts according to the disclosure level.

[0527] Figure 9 shows an example of the output of introductory content C, where information has been anonymized or abstracted according to the set disclosure level.

[0528] As shown in Figure 9, the introductory content C includes an anonymized section M1 in which the original information is concealed.

[0529] The anonymized section M1 serves to convey the appeal of the target business to viewers while preventing the identification of specific companies or stores.

[0530] Typical examples of information obtained through inputs such as those shown in Figure 6 that are subject to anonymization or abstraction include place names, store names, and sales ranges.

[0531] The generation unit 130 appropriately converts at least one of the pieces of information contained in the introductory content C according to the disclosure level.

[0532] First, I will explain the specific methods for anonymizing and abstracting place names.

[0533] The name of the location where the business is situated is important information for conveying the business's market area and location conditions.

[0534] However, disclosing detailed place names directly could easily identify the target projects.

[0535] Therefore, the generation unit 130 adjusts the granularity of the display of place names in stages according to the disclosure level.

[0536] When the disclosure level is at its highest, the generation unit 130 includes the city / town / village name as a place name in the introductory content C (see Figure 10).

[0537] In this case, detailed addresses and building names are either anonymized as section M1 or excluded from the output.

[0538] If the disclosure level is moderate, the generation unit 130 abstracts the place names to only the prefecture names.

[0539] For example, the original location information, "Shibuya Ward, Tokyo," is replaced with the broader expression, "Tokyo."

[0540] This allows us to present candidates with a general overview of the region while preventing them from narrowing their focus to a specific area.

[0541] If the level of disclosure is even lower, the generation unit 130 converts the place name into an abstract expression that indicates the characteristics of a local area or commercial area.

[0542] For example, expressions such as "the Tokyo metropolitan area," "the Kansai region," and "the area around train stations in government-designated cities" are used.

[0543] Through this abstraction, the physical location itself is kept secret, but the attractiveness of the location and the business environment are conveyed to the candidates.

[0544] The setting unit 120 shown in Figure 1 can determine that if the location of a candidate is close to the target business, the impact of information leakage will be significant.

[0545] In this case, the setting unit 120 controls the system to set a lower disclosure level for nearby competitors (see Figures 3, 4, 5, 7, and 8).

[0546] As a result, in the introductory content C for competitors, place names become anonymized sections M1, which are more highly abstracted.

[0547] Next, we will explain the specific methods for anonymizing and abstracting business names (see Figures 1, 2, and 9).

[0548] The company name or brand name is information that symbolizes the level of recognition and customer base of the business in question.

[0549] However, disclosing the company name directly leads to identifying the business, so it needs to be strictly controlled during the initial stages of inquiries.

[0550] Only certain candidates with a high level of disclosure are permitted to present the initials of their company name or general anecdotes about the origin of their company name.

[0551] In the default settings, the generation unit 130 performs a process of replacing the company name with a general noun that indicates the type of business or business model.

[0552] For example, a specific company name like "○○ Trading Co., Ltd." can be abstracted into expressions such as "a long-established specialized trading company" or "a locally-based wholesaler."

[0553] In this replacement process, the generation unit 130 extracts characteristic keywords from the attribute information of the target business (see Figure 6) and generates alternative names.

[0554] As a result, the company name portion on the introductory content C in Figure 9 is displayed as an anonymized section M1 that incorporates the strengths of the business.

[0555] In terms of candidate attributes, if a candidate belongs to the same niche market as the target business (see Figure 4), there is a risk that the target business can be inferred even from slight hints in the company name.

[0556] To prevent such a situation, the setting unit 120 instructs candidates in the same market to select a minimal abstract expression that excludes all modifiers related to the company name.

[0557] On the other hand, for candidates aiming to enter the market from a different industry, the company name is kept confidential, but the language is transformed to emphasize the brand's market share and historical value within the region (see Figure 10).

[0558] Next, we will explain the specific methods for anonymizing and abstracting sales data (see Figures 2, 3, and 7).

[0559] Financial information such as sales figures and profit margins are extremely important indicators when considering business succession.

[0560] However, disclosing accurate financial figures carries the risk of revealing the financial condition of the target business to a large, unspecified number of people.

[0561] The generation unit 130 converts specific financial figures into sales ranges with a defined scope, based on the disclosure level.

[0562] For example, if the actual sales are "125 million yen," the generation unit 130 rounds this to a range expression of "100 million to 300 million yen."

[0563] For candidates with a relatively high level of disclosure, a narrower sales range, such as "100 million to 150 million yen," is presented.

[0564] Conversely, candidates with a low level of disclosure are only presented with a rough estimate of the scale, such as "less than 100 million yen" or "several hundred million yen."

[0565] Furthermore, the setting unit 120 can also instruct the system to use an abstraction that employs alternative indicators such as the number of employees or the number of stores, instead of directly displaying the amount (see Figures 5 and 8).

[0566] As a result, the financial information in introductory content C will become an anonymized section M1 that conveys the scale of the business while ensuring security.

[0567] Thus, anonymizing or abstracting place names, company names, and sales ranges is essential to maximize the attractiveness of the business as a business succession opportunity while protecting the confidentiality of the target business.

[0568] The setting unit 120 can apply similar disclosure level controls not only to these three elements, but also to customer information, owned patents, and detailed age distribution of employees.

[0569] For example, if a company's main business partner is a single influential company, that fact alone can help identify the target business.

[0570] The generation unit 130 replaces the customer information with higher-level concepts such as "major automobile manufacturers" or "listed companies," depending on the disclosure level.

[0571] Next, we will describe in detail the content-level masking and automatic adjustment mechanisms for level of detail based on disclosure level control.

[0572] The information processing system 10 (see Figure 1) has the capability to dynamically generate multiple variations of introductory content C corresponding to different disclosure levels for a single target business.

[0573] The configuration unit 120 compares the basic rules specified by the owner of the target business with the candidate attributes and calculates the optimal level of disclosure to be presented to each candidate in real time (see Figures 4 and 7).

[0574] Based on these calculation results, the generation unit 130 automatically adjusts the presence or absence of masking and the level of detail of the description for each paragraph and information block that constitutes the introductory content C (see Figure 2).

[0575] For example, in a manufacturing project where the company has a strong technical advantage, there might be a block that explains the specialized processing know-how possessed by the target business.

[0576] If the candidate's attributes are "competitor in the manufacturing industry" and it is determined that there is a high risk of technology leakage, the setting unit 120 sets the disclosure level of this block to the lowest level.

[0577] The generation unit 130, in accordance with this setting, either completely masks the entire block in question or replaces it with an extremely short, abstract sentence such as "possesses unique precision machining technology."

[0578] On the other hand, if the candidate's attributes are "investment fund" or "trading company with a sales network," and it is determined that synergies can be evaluated by knowing the technical details, the setting unit 120 sets a higher disclosure level.

[0579] In this case, the generation unit 130 generates and outputs detailed content that explains the specific application fields of the processing technology and the advantages of the products realized thereby (see Figure 10).

[0580] This automatic adjustment mechanism allows the information processing system 10 to provide each candidate with the most appealing information while minimizing the risk of information leakage.

[0581] Furthermore, this mechanism can accommodate a gradual increase in the level of disclosure as negotiations with candidates progress.

[0582] In the initial consultation phase, an abstract introductory content C is presented.

[0583] Subsequently, when the conditions such as the signing of a confidentiality agreement are recorded via the acquisition unit 100 (see Figures 3 and 6), the setting unit 120 updates the disclosure level for the candidate.

[0584] Based on the updated disclosure level, the generator 130 (see Figures 5 and 8) regenerates a new version of the introductory content C with the masking removed and containing more detailed information.

[0585] As shown in Figure 9, the anonymized section M1 is not simply blacked out, but embedded as a readable and natural expression of text.

[0586] This makes it less likely for candidates who have read through introductory content C to feel unnatural or suspicious due to the concealment of information.

[0587] To generate natural abstract expressions, the generation unit 130 utilizes pre-prepared paraphrasing dictionaries and templates.

[0588] Next, we will explain how to adapt the final output format, which has undergone evaluation, modification, and anonymization of the generated introductory content C, to various display media.

[0589] The introductory content C generated by the generation unit 130 and automatically adjusted as needed is not used as is in a single format.

[0590] The information processing system 10 anticipates various display media and channels for delivering information to candidates and performs conversion to a format suitable for those media.

[0591] The display media covered include web pages of business succession matching sites, dedicated smartphone application screens, email bodies, and portable document formats for printing.

[0592] Each medium has different characteristics, such as the amount of information that can be displayed at once and how users view it.

[0593] For example, smartphone screens are not suitable for reading long texts due to their limited screen size.

[0594] Therefore, when adapting the output format for smartphones, the generation unit 130 either generates a summarized version of the introductory content C or reconfigures the layout, focusing on headings and short bullet points.

[0595] Even text containing anonymized sections like M1, as shown in Figure 9, is further compressed into more concise phrases for smartphones.

[0596] On the other hand, for print documents and websites designed for computer screens, it is effective to allow readers to carefully read detailed background information and the owner's story.

[0597] In this case, the generation unit 130 adopts a lengthy introductory content C, which describes the history and strengths of the target business in a polite style, as the output format.

[0598] Furthermore, design elements such as the placement of charts and graphs and font sizes are optimized to suit the characteristics of each medium (see Figure 10).

[0599] In initial email approaches, it's essential to grab the candidate's attention with the subject line and the first few lines.

[0600] The configuration unit 120 controls the output parameters for email so that the most appealing abstract information is placed at the beginning of the message.

[0601] In this way, the information processing system 10 optimizes information transmission under diverse circumstances by combining anonymization according to the disclosure level and formatting adaptation according to the medium.

[0602] This adaptation process also incorporates the results of prior evaluations and corrections.

[0603] When converting to media with strict character limits, the setting unit 120 controls the system so that important information blocks with a high evaluation value E1 are prioritized and retained.

[0604] This prevents the core appeal of the target business from being lost, even if the amount of information is reduced due to media limitations.

[0605] From here, we will provide a general overview of other embodiments and various modifications that enhance the effectiveness of the system.

[0606] The information processing system 10 in each of the embodiments described above (see Figure 1) may be implemented as a single server computer or as a distributed system in which multiple computers cooperate.

[0607] By utilizing a cloud computing environment and distributing data storage and computational processing across multiple nodes, high scalability can be ensured to handle access from a large number of candidates and a large number of simultaneous content generation requests.

[0608] Furthermore, the functions of the acquisition unit 100, selection unit 110, setting unit 120, and generation unit 130 (see Figures 1 and 2) may be implemented by dedicated hardware circuits, or they may be implemented as software processing by a processor executing a program.

[0609] In addition to the central processing unit, various types of computing accelerators can be used as the processor for executing the program.

[0610] The attribute information of the target business and the attribute information of the candidates may not only be entered manually by the user (see Figure 6), but may also be automatically retrieved and synchronized from external corporate databases or credit rating agency servers.

[0611] By linking with external data, data entry effort is reduced, and disclosure levels can be controlled based on more objective and accurate information.

[0612] The various dictionaries and templates used to generate the introductory content C (see Figure 5) should not be fixed, but should be continuously updated according to the system's operational history.

[0613] For example, it is possible to analyze what kinds of abstract expressions were used in deals that resulted in a sale and incorporate a feedback loop (see Figure 4) that increases the weight of expression patterns with a high probability of success.

[0614] This is expected to improve the quality of the introductory content C over time, leading to increased matching accuracy.

[0615] The disclosure level (see Figure 9) may be managed as a multi-dimensional parameter rather than a single indicator.

[0616] For example, the disclosure levels for financial information, technical information, and customer information could be set independently for each.

[0617] This allows for more granular information control, such as disclosing only information in specific areas based on candidate attributes, while strictly anonymizing information in other areas.

[0618] In the introductory content C shown in Figure 9, the anonymized section M1 is represented as text, but anonymization may also be performed by concealing parts of visual icons or graphs.

[0619] For example, removing the numerical values ​​on the vertical axis of a graph showing sales trends and converting it into a graph that only shows the trend can also be considered part of the anonymization process.

[0620] Furthermore, it is also useful to provide an interface that allows candidates to directly request the disclosure of additional information regarding anonymized data (see Figure 7).

[0621] If the request is approved, the system immediately displays the new, unmasked introductory content C on the candidate's screen (see Figure 10).

[0622] Such an interactive information disclosure process also serves as an indicator of candidates' level of interest and provides useful feedback information to the owners of the target projects (see Figure 8).

[0623] The aforementioned masking and automatic adjustment of detail levels can be applied not only to business succession cases, but also to various matching areas where there is a trade-off between the confidentiality of information and the need for disclosure, such as real estate transactions and personnel recruitment.

[0624] The order of the processes described herein (see Figures 2, 3, and 5) can be changed as long as no inconsistencies arise, and multiple processes may be executed in parallel.

[0625] The timing of when the acquisition unit 100 acquires information and the timing of when the setting unit 120 sets the disclosure level may be synchronous or asynchronous.

[0626] The generation unit 130 may generate a provisional introductory content C from the information it has acquired (see Figures 1 to 10) without waiting for all the information to be available, and then perform a differential generation process to update the content once the missing information has been completed.

[0627] Furthermore, in the embodiments described above, unless the word "only" is used, such as "based only," "according only," or "in the case only," it should be noted that in this specification, additional information may also be considered.

[0628] Furthermore, please note that, as an example, the statement "perform a specific action under certain conditions" does not necessarily mean "perform a specific action always under certain conditions" or "perform a specific action immediately after certain conditions occur," unless explicitly stated otherwise.

[0629] Furthermore, the phrase "each component" does not necessarily mean that the composition is composed of multiple elements; it can also mean that the component is singular.

[0630] Furthermore, for the sake of clarity, even if there are aspects of operation in some method, program, terminal, device, server, or system that differ from the operation described herein, each aspect of the present invention is intended to cover the same operation as any of the operations described herein, and the existence of operations different from those described herein does not mean that such methods, etc., fall outside the scope of each aspect of the present invention. [Explanation of symbols]

[0631] 10. Information Processing Systems 100 Acquisition Department 110 Selection Section 120 Setting section 130 Generation part 140 Inspection Department 150 Revised Section 160 Calculation Unit 170 Evaluation Department 180 Recommendation Department Ax comparison axis B Chatbot C Introduction Content E1 Evaluation Value F1 Attribute input field F2 Intention Input Field G1 Design Proposal G2 Layout Proposal L1 Succession Scheme Candidates M1 Anonymized section P1 Revision Proposal R1 Vocabulary Rules R2 consistency rules S1 Acquisition Steps S2 Selection Step S3 Setup Steps S4 Generation Step U users V1 Similarity Score W1 Chat Screen W2 Input Screen

Claims

1. An information processing system that generates introductory content for a business to be presented to a successor candidate, An acquisition unit that acquires attribute information of the target business, owner intention information indicating the owner's intentions, and candidate attributes of the successor candidate who shows interest in the target business, wherein the candidate attributes include at least one of the following: the successor candidate's industry, company size, location, business strategy, and financial strength. A selection unit selects components to be used in the introduction content according to the information acquired by the acquisition unit, A setting unit that sets output parameters relating to at least one of the writing style, layout, or design of the introductory content based on the information acquired by the acquisition unit, and sets the level of disclosure of information regarding the target business to be presented to the successor candidate as an output parameter based on the owner intention information and the candidate attributes, wherein the setting unit sets the disclosure level relatively lower when the candidate attributes indicate that the location of the successor candidate is close to the location of the target business and the successor candidate is in the same industry as the target business, or the successor candidate belongs to the same market as the target business. A generation unit that generates the introductory content based on the selected components and the set output parameters, Equipped with, The generation unit, in accordance with the set disclosure level, performs anonymization or abstraction processing on at least one of the place names, trade names, and financial information including sales or profit margins included in the introductory content, converting them into a higher-level concept or scope expression that indicates the attributes of the target business while suppressing the identification of the target business. The generation unit converts the place name into an expression of appropriate granularity from among city / ward / town / village names, prefecture names, regional names, and expressions indicating the characteristics of the trading area, the trade name into a general noun indicating the type of business or business form, and the financial information into a relatively narrow range expression for candidates with a relatively high level of disclosure, and into a relatively broad range expression or an expression indicating the scale for candidates with a relatively low level of disclosure. Information processing system.

2. The information processing system according to claim 1, The information processing system includes an inspection unit that performs an inspection on the generated introductory content based on at least one of vocabulary rules or consistency rules, The system includes a revision unit that outputs a candidate for modification or regeneration of the introductory content based on the results of the inspection, The aforementioned acquisition unit further acquires information on similar cases related to business succession cases that have already been concluded. The information processing system further comprises a calculation unit that calculates the degree of similarity between the target business and the similar case information based on a plurality of comparison axes, The generation unit reflects the comparison results based on the calculated similarity in the generation of the introductory content. Information processing system.

3. The information processing system according to claim 2, The aforementioned comparison axes include at least one of the following: industry, region, business scale, customer base, equipment configuration, and succession scheme. Information processing system.

4. An information processing system according to claim 2 or 3, The system further includes an evaluation unit that calculates an evaluation value for the generated introductory content, The revision unit outputs the correction candidate or the regeneration candidate based on both the results of the inspection and the calculated evaluation value. Information processing system.

5. The information processing system according to claim 1, The setting unit sets the disclosure level for each of the multiple successor candidates for a single target business, The generation unit generates multiple variations of the introductory content, corresponding to each of the multiple successor candidates, by automatically adjusting the presence or absence of masking or the level of detail of the description for each paragraph or information block that constitutes the introductory content. Information processing system.

6. The information processing system according to claim 2, The vocabulary rules used by the inspection unit include at least one of an NG word dictionary that defines prohibited terms and a recommended word dictionary that defines recommended terms. Information processing system.

7. The information processing system according to claim 2, The consistency rule used by the inspection unit is a rule for detecting at least one inconsistency selected from a group consisting of numerical values, years, place names, succession schemes, and personal attributes. Information processing system.

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