Token sales method, token sales device, and program

Abstract

To provide a token sale method, a token sale apparatus, and a program for enabling highly convenient security token offerings to be realized.SOLUTION: The token sale method includes an acquisition step of acquiring creator information about a creator, an estimation step of estimating a future return that the creator can obtain based on the creator information, a determination step of determining a token value based on a result of the estimation in the estimation step, and a sale processing step of performing processing related to sale of the token including displaying the sale price set based on the token price.SELECTED DRAWING: Figure 5

Description

Technical Field

[0001] The present disclosure relates to a token sales method, a token sales apparatus, and a program.

Background Art

[0002] In recent years, the use of a system for soliciting investments on the Internet called crowdfunding has been increasing. In crowdfunding, a proposer (supported person) sets a return for the investment by a supporter. The supporter makes an investment for the purpose of supporting the proposer and obtaining a return. In Patent Document 1, a system for efficiently performing such a mechanism has been proposed.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, the concept of Security Token Offering has become known. Security Token Offering is a concept of raising funds by issuing securities (securities) as digital securities in the form of tokens. As a usage method of Security Token Offering, for example, it is assumed that a popular artist, writer, athlete, or sports team issues tokens by themselves to raise funds for the next production or future activities.

[0005] However, conventional systems do not necessarily allow for the operation of security token offerings in a convenient manner. For example, in security token offerings, the tokens are expected to represent various things, such as the future annual salary of an athlete. In such cases, it is expected that setting a token price will be difficult due to the lack of precedents for transactions, and as a result, the introduction of security token offerings will be difficult. Even if a price can be set, in many cases the price setting will be determined by the intentions of the token issuer. In this case, it is quite possible that the token issuer will hide information that is unfavorable to them in order to maintain a high token price. If the conventional security token offering mechanism is simply introduced, it is expected that prospective token buyers will hesitate to purchase the tokens because they will not be able to obtain sufficient information to make an informed decision.

[0006] Therefore, this disclosure proposes a token sales method, token sales device, and program that enable the realization of highly convenient security token offerings. [Means for solving the problem]

[0007] To solve the above problems, one form of token sales method relating to this disclosure comprises: an acquisition step of acquiring initiator information relating to the initiator; an estimation step of estimating the future returns that the initiator may receive based on the initiator information; a determination step of determining the token price based on the estimation result in the estimation step; and a sales processing step of performing a process relating to the sale of tokens, including displaying a sales price set based on the token price. [Brief explanation of the drawing]

[0008] [Figure 1] This figure shows an example of a token sales page. [Figure 2] This figure shows an example configuration of a token sales system according to the embodiment of this disclosure. [Figure 3] This figure shows an example of a server configuration according to the embodiments of this disclosure. [Figure 4] This figure shows an example configuration of a terminal device according to the embodiments of this disclosure. [Figure 5] This is a flowchart showing the token setting process in this embodiment. [Figure 6] This is a flowchart showing the token sales process in this embodiment. [Figure 7] This is a flowchart showing the token transaction management process of this embodiment. [Modes for carrying out the invention]

[0009] The embodiments of this disclosure will be described in detail below with reference to the drawings. In the following embodiments, the same parts will be denoted by the same reference numerals to avoid redundant descriptions.

[0010] Furthermore, in this specification and drawings, multiple configurations having substantially the same functional configuration may be distinguished by adding different numbers after the same reference numeral. For example, multiple configurations having substantially the same functional configuration may be distinguished as server 101 and 102 as needed. However, if there is no need to particularly distinguish each of multiple components having substantially the same functional configuration, only the same reference numeral will be used. For example, if there is no need to particularly distinguish between server 101 and 102, they will simply be referred to as server 10.

[0011] Furthermore, this disclosure will be explained in the order of the items shown below. 1. Outline of this embodiment 2. Configuration of the token sales system 2-1. Server Configuration 2-2. Configuration of the terminal device 2-3. Learning Models 3. Operation of the token sales system 3-1. Overview of Operation 3-2. Specific examples of actions for each category 3-3. Managing Token Transactions 3-4. Other Features 3-5. Token Setting Process 3-6. Token Sale Processing 3-7. Token Transaction Management Processing 4. Variation 5. Conclusion

[0012] <<1. Overview of This Embodiment>> In recent years, the use of a system for soliciting investments on the Internet called crowdfunding has been increasing. In crowdfunding, the originator (supported person) sets a return for the investment by the supporter. The supporter makes an investment for the purpose of supporting the originator and receiving a return.

[0013] Generally, in crowdfunding, the originator receives financial support (investment) from the supporter and conducts activities based on the support funds, and in many cases, the supporter receives the resulting product (for example, a new product) as a return from the originator. Also, there are cases where the supporter receives a return from the originator in the form of a gift instead of a product resulting from the support funds.

[0014] However, in this method, the supporter side cannot transfer or sell the return itself to others. Also, the merit of being able to buy the received product (new product) at a discounted price is assumed to be a burden for the originator because it is at the limit of the cost. Also, when receiving the product, it is assumed that the product may not seem attractive or may be clumsier than the initial explanation, and the result may not be as expected for the supporter. Furthermore, for projects where there is no physical product such as a new product, there is a difficult-to-receive support aspect. That is, the value of the return may vary for the supporter.

[0015] Therefore, the concept of a security token offering has been proposed. This enables the supporter to securitize the return received as a token (securities), so that the supporter can also sell the token. As a result, the supporter can buy and sell the token when the value of the return fluctuates, reducing the investment risk.

[0016] For example, assume that a sports player, such as a soccer player or a basketball player, tokenizes the right to receive their contract salary three years later and sells it. If it is assumed that they will receive 10 million yen as the contract salary three years later, then at the time of token issuance, the value of one token is calculated as 10 million yen divided by the number of tokens. By selling this token, the sports player can receive the reward that they will receive three years later immediately, and furthermore, they can increase their contract salary three years later by using the money obtained from selling the token to conduct intensive training. Instead of selling all the tokens, the sports player can sell only half of them, so that they can receive the profit when the contract salary increases while dispersing the financial risk.

[0017] Supporters can also do it not only in the sense of supporting sports players but also in the sense of investment. For example, by purchasing tokens when a sports player is not yet famous, not only can they support the sports player, but they can also make a financial investment to promote the growth of the player, and when the player grows, they can receive a large return.

[0018] However, the conventional security token offering is not necessarily a highly convenient mechanism, either for the token issuer (hereinafter also referred to as the proposer) or for the potential token purchaser (hereinafter also referred to as the supporter).

[0019] For example, in a security token offering, it is assumed that the tokens will be of various types, such as the future annual salary of a sports player. Then, due to the lack of transaction precedents, it is difficult for the proposer to set the token price, and as a result, it is assumed that it will be difficult for the proposer to introduce a security token offering.

[0020] Even if the creator of a token is able to set a price, in most cases, that price will be determined by the creator's intentions. In this case, it is quite conceivable that the creator will hide information that is unfavorable to them in order to maintain a high token price. For example, even if it is already known that an athlete has suffered a career-ending injury and will lose their contract money in three years, it is concealed by the creator when setting the token price. Simply introducing the conventional security token offering mechanism is likely to cause supporters to hesitate to purchase tokens because they will not have enough information to make an informed decision.

[0021] Therefore, this embodiment makes it possible to realize a security token offering that is convenient for both the initiator and the supporter. Specifically, the token sales system of this embodiment obtains initiator information necessary to estimate the token price from the initiator. Then, based on the initiator information, the token sales system estimates the rewards (returns) that the initiator will receive in the future and determines the token price based on the estimation result.

[0022] The token sales system processes token sales based on the determined token price (hereinafter also referred to as the determined token price). For example, it allows users such as supporters to purchase tokens on a website. Figure 1 shows an example of a token sales page. In the example in Figure 1, the tokens represent the contract fees for soccer player A, tennis player B, and baseball player C three years from now. The token sales system then displays the sales price set based on the determined token price to users such as supporters. In the example in Figure 1, the token sales system displays the sales price per token (shown as ¥30,000, ¥20,000, and ¥80,000 in Figure 1, indicated as "Pricing") set for soccer player A, tennis player B, and baseball player C based on the determined token price on the web page.

[0023] Furthermore, the token sales system may display both the sales price set by the project creator and the judgment token price on its webpage. In the example in Figure 1, the token sales system displays the judgment token price (¥25,000 shown as "Market Price" in Figure 1) on its webpage in addition to the sales price indicated as "Pricing".

[0024] This makes it easier for project creators to set token prices and easier for supporters to purchase tokens. As a result, a highly convenient security token offering is realized for both project creators and supporters.

[0025] Furthermore, a security is a security that represents a private right with monetary value, and the creation, transfer, and exercise of that right are carried out based on the security. An example of a security is a check. In other words, in this embodiment, a right is created when the token is generated, the right is transferred by the transfer of the token, and the right is exercised by the use of the token. A token is a security that has monetary value (recorded electronically on electronic devices or other objects) that can be transferred using an electronic data processing system.

[0026] Having outlined the basics of this embodiment, the token sales system 1 according to this embodiment will now be described in detail.

[0027] <<2. Configuration of the Token Sales System>> First, let's explain the overall structure of token sales system 1.

[0028] Figure 2 shows an example configuration of a token sales system 1 according to an embodiment of this disclosure. The token sales system 1 is an information processing system that performs processing for the sale and management of tokens. The token sales system 1 comprises a server 10 and a terminal device 20. Note that the devices in the figure may be considered as devices in a logical sense. In other words, some of the devices in the figure may be implemented as virtual machines (VMs), containers, Docker, etc., and these may be implemented on the same physical hardware.

[0029] Server 10 and terminal device 20 each have communication capabilities and are connected via network N. Server 10 and terminal device 20 can be rephrased as communication devices. Although only one network N is shown in the example in Figure 2, there may be multiple networks N.

[0030] Here, network N is a communication network such as a LAN (Local Area Network), WAN (Wide Area Network), cellular network, fixed telephone network, regional IP (Internet Protocol) network, or the Internet. Network N may include wired networks or wireless networks. Network N may also include a core network. A core network is, for example, an EPC (Evolved Packet Core) or a 5GC (5G Core network). Network N may also include data networks other than the core network. A data network may be a service network of a telecommunications carrier, for example, an IMS (IP Multimedia Subsystem) network. Alternatively, a data network may be a private network, such as an internal corporate network.

[0031] Server 10 and terminal device 20 may be configured to connect to network N or other communication devices using radio access technologies (RATs) such as LTE (Long Term Evolution), NR (New Radio), Wi-Fi, and Bluetooth (registered trademark). In this case, the communication device may be configured to use different radio access technologies. For example, the communication device may be configured to use NR and Wi-Fi. Also, the communication device may be configured to use different cellular communication technologies (e.g., LTE and NR). LTE and NR are types of cellular communication technologies that enable mobile communication of communication devices by arranging multiple base stations in a cell-like structure over the area they cover. Furthermore, server 10 and terminal device 20 may be able to connect to network N or other communication devices using radio access technologies other than LTE, NR, Wi-Fi, and Bluetooth.

[0032] The configuration of each device constituting Token Sales System 1 is described below in detail. Note that the configurations of each device shown below are merely examples. The configuration of each device may differ from those shown below.

[0033] <2-1. Server Configuration> First, let's describe the configuration of server 10.

[0034] Server 10 is an information processing device (computer) that performs processing related to the sale and management of tokens. For example, Server 10 performs processing for issuing tokens and processing related to the trading of issued tokens. Token trading includes not only the sale of issued tokens (primary transaction) but also the resale of sold tokens (secondary transaction). These processes may be performed by one Server 10 or by different Servers 10.

[0035] Server 10 can utilize any form of computer. For example, Server 10 may be a PC server, a midrange server, or a mainframe server. Furthermore, Server 10 may be an information processing device that performs data processing near users or terminals (edge ​​processing). For example, Server 10 may be an information processing device (computer) installed alongside or built into a base station. Of course, Server 10 may also be an information processing device that performs cloud computing.

[0036] Figure 3 shows an example configuration of a server 10 according to the present disclosure. The server 10 comprises a communication unit 11, a storage unit 12, and a control unit 13. Note that the configuration shown in Figure 3 is a functional configuration, and the hardware configuration may differ. Furthermore, the functions of the server 10 may be distributed and implemented across multiple physically separated configurations. For example, the server 10 may be composed of multiple server devices.

[0037] The communication unit 11 is a communication interface for communicating with other devices. For example, the communication unit 11 is a LAN (Local Area Network) interface such as a NIC (Network Interface Card). The communication unit 11 may be a wired interface or a wireless interface. The communication unit 11 communicates with terminal devices 20, etc., according to the control of the control unit 13.

[0038] The memory unit 12 is a data read / write storage device such as DRAM (Dynamic Random Access Memory), SRAM (Static Random Access Memory), flash memory, or hard disk. The memory unit 12 functions as a storage means for the server 10. The memory unit 12 stores various types of information, such as initiator information, token price information, and learning models. This information will be described later.

[0039] The control unit 13 is a controller that controls various parts of the server 10. The control unit 13 is implemented by a processor such as a CPU (Central Processing Unit), MPU (Micro Processing Unit), or GPU (Graphics Processing Unit). For example, the control unit 13 is implemented by the processor executing various programs stored in the internal storage device of the server 10 using RAM (Random Access Memory) or the like as a working area. The control unit 13 may also be implemented by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or FPGA (Field Programmable Gate Array). CPUs, MPUs, GPUs, ASICs, and FPGAs can all be considered controllers.

[0040] The control unit 13 comprises an acquisition unit 131, an estimation unit 132, a determination unit 133, a sales processing unit 134, a display control unit 135, a request unit 136, and a management unit 137. Each block constituting the control unit 13 (acquisition unit 131 to management unit 137) is a functional block that represents the function of the control unit 13. These functional blocks may be software blocks or hardware blocks. For example, each of the above-mentioned functional blocks may be a single software module implemented in software (including microprograms), or a single circuit block on a semiconductor chip (die). Of course, each functional block may also be a single processor or a single integrated circuit. The control unit 13 may be composed of functional units different from the above-mentioned functional blocks. The configuration method of the functional blocks is arbitrary.

[0041] The control unit 13 may be composed of functional units different from the functional blocks described above. Furthermore, some or all of the operations of each block constituting the control unit 13 (acquisition unit 131 to management unit 137) may be performed by other devices. For example, some or all of the operations of each block constituting the control unit 13 may be performed by the control unit 23 of the terminal device 20. The operations of each block constituting the control unit 13 will be described later.

[0042] <2-2. Terminal Device Configuration> Next, the configuration of the terminal device 20 will be described.

[0043] Terminal device 20 is an information processing device (computer) owned by the user. Terminal device 20 is configured to communicate with server 10 via network N. The user uses terminal device 20 to perform token-related processing. For example, the user uses terminal device 20 to sell tokens, trade tokens, or perform various token-related settings.

[0044] The terminal device 20 can be any form of computer. The terminal device 20 may be a mobile device such as a mobile phone, smart device (smartphone or tablet), PDA (Personal Digital Assistant), or notebook PC. Alternatively, the terminal device 20 may be a wearable device such as a smartwatch. Furthermore, the terminal device 20 may be an xR device such as an AR (Augmented Reality) device, VR (Virtual Reality) device, or MR (Mixed Reality) device. In addition, the terminal device 20 may be a portable IoT (Internet of Things) device.

[0045] Figure 4 shows an example configuration of a terminal device 20 according to an embodiment of the present disclosure. The terminal device 20 comprises a communication unit 21, a storage unit 22, a control unit 23, an input unit 24, and an output unit 25. Note that the configuration shown in Figure 4 is a functional configuration, and the hardware configuration may differ. Furthermore, the functions of the terminal device 20 may be implemented in a distributed manner across multiple physically separated configurations.

[0046] The communication unit 21 is a communication interface for communicating with other devices. For example, the communication unit 21 is a LAN interface such as a NIC. The communication unit 21 may be a wired interface or a wireless interface. If the communication unit 21 has a wireless interface, it may be configured to connect to the network N or other communication devices using radio access technology (RAT) such as LTE (Long Term Evolution), NR (New Radio), Wi-Fi, or Bluetooth (registered trademark). The communication unit 21 communicates with the server 10, etc., according to the control of the control unit 23.

[0047] The memory unit 22 is a data read / write storage device such as DRAM, SRAM, flash memory, or hard disk. The memory unit 22 functions as a storage means for the terminal device 20.

[0048] The control unit 23 is a controller that controls various parts of the terminal device 20. The control unit 23 is implemented by a processor such as a CPU, MPU, or GPU. For example, the control unit 23 is implemented by the processor executing various programs stored in the memory device inside the terminal device 20 using RAM or the like as a working area. The control unit 23 may also be implemented by an integrated circuit such as an ASIC or FPGA. A CPU, MPU, GPU, ASIC, and FPGA can all be considered as controllers.

[0049] The input unit 24 is an input device that receives various inputs from the outside. For example, the input unit 24 is an operating device for the user to perform various operations, such as a keyboard, mouse, or operation keys. If the terminal device 20 employs a touch panel, the touch panel is also included in the input unit 24. In this case, the user performs various operations by touching the screen with their finger or stylus.

[0050] The output unit 25 is a device that outputs various types of information to the outside, such as sound, light, vibration, and images. The output unit 25 is equipped with a display device that displays various types of information. The display device is, for example, a liquid crystal display or an organic EL (Electro-Luminescence) display. If a touch panel is used in the terminal device 20, the display device may be an integrated device with the input unit 24. The output unit 25 outputs various types of information to the user according to the control of the control unit 23.

[0051] <2-3. Learning Models> Next, I will explain the learning model.

[0052] As described above, the memory unit 12 of the server 10 stores a learning model. The learning model is, for example, a trained model that has learned the relationship between the initiator's information and the return that the initiator is estimated to receive in the future. The server 10 then uses this learning model to estimate, for example, the return that the initiator is estimated to receive in the future.

[0053] A learning model is a machine learning model, such as a neural network model. A neural network model consists of layers called an input layer, hidden layers (or hidden layers), and an output layer, each containing multiple nodes, with each node connected via an edge. Each layer has a function called an activation function, and each edge is weighted. A learning model has one or more hidden layers (or hidden layers). When the learning model is a neural network model, learning the learning model means setting, for example, the number of hidden layers (or hidden layers), the number of nodes in each layer, or the weights of each edge.

[0054] Here, the neural network model may be a deep learning model. In this case, the neural network model may be a model of the form known as DNN (Deep Neural Network). Alternatively, the neural network model may be a model of the form known as CNN (Convolutional Neural Network), RNN (Recurrent Neural Network), or LSTM (Long Short-Term Memory). Of course, the neural network model is not limited to these forms.

[0055] Furthermore, the learning model is not limited to a neural network model. For example, the learning model may be a reinforcement learning model. In reinforcement learning, actions (settings) that maximize value are learned through trial and error. In addition, the learning model may be a logistic regression model.

[0056] Furthermore, the learning model may consist of multiple models. For example, the learning model may consist of multiple neural network models. More specifically, the learning model may consist of multiple neural network models selected from, for example, CNN, RNN, and LSTM. When the learning model consists of multiple neural network models, these multiple neural network models may be in a dependent relationship or a parallel relationship.

[0057] As described above, the memory unit 12 of the server 10 stores the learning model. The learning model is used in the token setting process described later. The token setting process is a process for making various settings related to the token. In the token setting process, the token price is determined and the return that the initiator is expected to receive in the future is estimated. The learning model will be explained in detail below.

[0058] The learning model is a pre-trained model that has learned the relationship between the initiator's information and the estimated returns the initiator is expected to receive in the future. For example, the learning model takes initiator information for token issuance as input and outputs information about the estimated returns the initiator is expected to receive in the future (hereinafter simply referred to as return information).

[0059] In Figure 3, textual information such as "learning model" is shown as the information stored in the memory unit 12, but in reality, the memory unit 12 stores strings of characters and numerical values ​​that indicate the structure of the model and connection coefficients.

[0060] The learning model may be a model that uses data of a pair of initiator information and return information as training data, and when initiator information is input, it is trained to output information of the return that the initiator is estimated to receive in the future. In this case, the first learning model may include an input layer for inputting initiator information, an output layer for outputting return information, a first element belonging to any layer from the input layer to the output layer other than the output layer, and a second element whose value is calculated based on the first element and the weight of the first element, and may be a model that causes the computer to function so that, when information is input to the input layer, stress information is output from the output layer based on the schedule information input to the input layer, by performing calculations based on the first element and the weight of the first element (i.e., connection coefficient) with respect to the information input to the input layer, with each element belonging to each layer other than the output layer as the first element.

[0061] Here, we assume that the learning model is implemented as a neural network having one or more hidden layers, such as a DNN. In this case, the first element included in the learning model corresponds to one of the nodes in the input layer or hidden layer. The second element corresponds to the next node, which is the node to which values ​​are transmitted from the node corresponding to the first element. Furthermore, the weights of the first element correspond to connection coefficients, which are weights considered for the values ​​transmitted from the node corresponding to the first element to the node corresponding to the second element.

[0062] Furthermore, let's assume that the learning model is implemented as a regression model represented by "y = a1*x1 + a2*x2 + ... + ai*xi". In this case, the first element included in the learning model corresponds to the input data (xi) such as x1 and x2. Also, the weights of the first element correspond to the coefficient ai that corresponds to xi. Here, the regression model can be considered as a simple perceptron having an input layer and an output layer. When each model is considered as a simple perceptron, the first element can be considered as one of the nodes in the input layer, and the second element can be considered as a node in the output layer.

[0063] Server 10 calculates the output information using a model with an arbitrary structure, such as a neural network or a regression model. Specifically, the first learning model is configured to output stress information when schedule information is input. For example, Server 10 sets the coefficients based on the similarity between the first measured data and the value obtained by inputting schedule information into the learning model. Server 10 generates stress information from schedule information using such a learning model.

[0064] In the example above, a model was shown that outputs this return information when the initiator information is input, as an example of a learning model. However, the learning model according to the embodiment may also be a model that is generated based on the results obtained by repeatedly inputting and outputting data to the learning model.

[0065] Furthermore, if server 10 performs learning or output information generation using GAN (Generative Adversarial Network), the learning model may be a model that constitutes a part of the GAN.

[0066] The learning device that trains the learning model (for example, the learning model) may be the server 10 or another information processing device. For example, suppose the server 10 trains the learning model. In this case, the server 10 trains the learning model and stores the trained learning model in the storage unit 12. More specifically, the server 10 sets the connection coefficient of the learning model so that when the initiator information is input to the learning model, the learning model outputs return information.

[0067] For example, Server 10 inputs the initiator information into the input layer node of the learning model, propagates the data through each intermediate layer to the output layer of the learning model, and outputs the return information. Then, Server 10 modifies the connection coefficient of the learning model based on the difference between the initiator information actually output by the learning model and the return information. For example, Server 10 may use a method such as backpropagation to modify the connection coefficient. In this case, Server 10 may also modify the connection coefficient based on the cosine similarity between the vector representing the first measured data and the vector representing the value actually output by the learning model.

[0068] Server 10 may use any learning algorithm to train the learning model. For example, Server 10 may use learning algorithms such as neural networks, support vector machines, clustering, or reinforcement learning to train the learning model.

[0069] <<3. Operation of the Token Sales System>> The configuration of Token Sales System 1 has been described above; next, we will explain how Token Sales System 1 works.

[0070] <3-1. Overview of Operation> First, let's explain the basic operation of token sales system 1.

[0071] The token sales system 1 performs processing related to the sale of tokens. This processing is performed by the server 10. The user (initiator and / or supporter) transmits information (for example, various configuration information such as initiator information) via the terminal device 20 for the server 10 to perform processing related to the sale of tokens.

[0072] Server 10 may be configured to allow users (initiators and / or supporters) to exchange information about tokens using a website. However, the means for exchanging information about tokens are not limited to a website. For example, Server 10 may be configured to allow users to exchange information about tokens using a dedicated application. In the following description, as an example, it will be assumed that users exchange information about tokens with Server 10 using a website.

[0073] The processes performed by token sales system 1 can be broadly categorized into the following (1) to (5). (1) Obtaining information on the category of the draft content (2) Obtaining information on the drafter (3) Estimation of the return that the proposer may receive in the future (4) Determination of token price (5) Sale of tokens

[0074] The following explains each of the above (1) to (5).

[0075] (1) Obtaining information on the category of the draft content When the initiator accesses the website for token proposal using terminal device 20, server 10 sends a web page to the initiator's terminal device 20 for inputting the category of the proposal content. The proposal content is, for example, a description of what kind of project the initiator will undertake. The category is a code that indicates the outline of the proposal content, for example, entrepreneurship, research, sports activities, music artist activities, manga artist activities, fine arts artist activities. The initiator enters the category of the proposal content on the web page. To make it easier for the initiator to select a category, the web page may be configured so that the user can select a category using a pull-down menu or the like. The initiator's terminal device 20 sends the information of the category of the proposal content selected by the initiator to server 10. Server 10 retrieves the category information from the initiator's terminal device 20.

[0076] (2) Obtaining information on the drafter Server 10 displays items that the user (proposer) must input on the user's terminal device 20, based on the category determined by the user. Specifically, Server 10 controls the display of the terminal device 20 via the network N to display input items determined based on the acquired category information on the web page. If the category is sports activities, input items may include, for example, current contract amount (annual salary), match results, health status, etc. The proposer inputs information into these input items. The information entered into these input items constitutes the proposer's information. The proposer's terminal device 20 sends the proposer's information to Server 10. Server 10 retrieves the proposer's information from Terminal Device 20.

[0077] (3) Estimation of the return that the proposer may receive in the future Server 10 estimates the return that the proposer will receive in the future based on the proposer information. At this time, Server 10 may estimate the return based on a learning model that has learned the relationship between proposer information and the return. For example, the developer of the learning model prepares multiple training data sets in advance, each linked to proposer information and the return. The developer then generates parameters by inputting these multiple training data sets (training data sets) into a learning model (for example, a machine learning model with a multilayer neural network structure or a logistic regression model). At this time, the developer may prepare training data sets for each proposer category and generate parameters for each proposer category. This generates a learning model for return estimation for each proposer category. Based on the category entered by the proposer, Server 10 selects a learning model associated with that category. Then, Server 10 estimates the return by inputting the proposer information into the selected learning model.

[0078] (4) Determination of token price Server 10 determines the token price based on the estimated return (hereinafter referred to as the estimated return). Specifically, Server 10 determines the token price based on the estimated return and the number of tokens issued. In this case, Server 10 may determine the token price by dividing the estimated return by the number of tokens issued. Alternatively, Server 10 may determine the token price by dividing the estimated return plus a certain fee (for example, a fee for using the token sales service or a commission for an intermediary) by the number of tokens issued. The number of tokens issued may be set by the project creator.

[0079] (5) Sale of tokens Server 10 performs processing related to the sale of tokens. Server 10 sends a web page for the sale of tokens to the user (supporter), for example, as shown in Figure 1. At this time, Server 10 may display on the web page the selling price set based on the determined token price. The selling price may be the same as or different from the token price. For example, Server 10 may be configured to allow the project creator to set the selling price. In this case, Server 10 may display on the web page both the token price determined by Server 10 and the selling price set by the project creator in order to give the supporter information to make a decision. In the example in Figure 1, for example, the price indicated as "Pricing" is the selling price, and for example, the price indicated as "Market Price" is the estimated token price. When a supporter selects the desired token and presses, for example, the purchase button on the web page, Server 10 performs processing to sell the token to the supporter. The processing for the sale of tokens will be described in detail in <3-3. Token Transaction Management> below.

[0080] <3-2. Specific examples of actions for each category> The above outlines the operation of Token Sales System 1. Next, we will explain specific examples of how Token Sales System 1 operates for each category. Examples of categories used below include sports activities, entrepreneurship, and manga artist activities.

[0081] (1) Sports activities "Sports activities" is, for example, a category for fundraising related to sports activities. If the project creator selects "Sports activities" as the category, server 10 displays at least one of the following input fields on the project creator information input page: "Project creator's current contract amount," "Match results," and "Health status." Server 10 retrieves the information entered in the input field as project creator information.

[0082] The server 10 then retrieves a learning model related to the selected category from the storage unit 12 and estimates the return the initiator can expect to receive in the future by inputting at least one of the information entered in the input fields into the learning model. The server 10 retrieves at least one of these pieces of information as initiator information. The server 10 then estimates the return the initiator can expect to receive in the future by inputting at least one of the retrieved pieces of information into the learning model. The server 10 then determines the token price based on the estimation result and performs processing related to the sale of the token, including displaying the price set based on the token price.

[0083] (2) Starting a business "Startup" is a category for, for example, fundraising before or after starting a business. If the proposer selects "Startup" as the category, server 10 displays at least one of the following input fields on the proposer information input page: "Maximum feasible market size," "Operating revenue," "Revenue per user," "Gross profit," "Sales rate," "Inventory turnover rate," "Network effect," "Virality (speed of word-of-mouth spread)," "Scalability (change in profitability due to increased production)," "Number of registered users," and "Number of active users." Server 10 retrieves the information entered in the input fields as proposer information.

[0084] The server 10 then retrieves a learning model related to the selected category from the storage unit 12 and estimates the return the initiator can expect to receive in the future by inputting at least one of the retrieved pieces of information entered into the input fields into the learning model. The server 10 retrieves at least one of these pieces of information as initiator information. The server 10 then estimates the return the initiator can expect to receive in the future by inputting at least one of the retrieved pieces of information into the learning model. The server 10 then determines the token price based on the estimation result and performs processing related to the sale of the token, including displaying the sales price set based on the token price.

[0085] (3) Manga artist activities "Manga Artist Activities" is, for example, a category for fundraising related to manga artist activities. If "Manga Artist Activities" is selected as the category, server 10 displays at least one input field for "Manga Genre" on the project creator information input page. Server 10 retrieves the information entered in the input fields as project creator information. Server 10 may also display information on the page regarding the process for the project creator to publish a sample manga. The process for publishing a sample manga is, for example, the process for the project creator to upload a sample manga to a site for viewing sample manga. In this case, server 10 may display a link to the site on the project creator information input page, or it may display a user interface for uploading (for example, a file upload screen). The site for viewing sample manga may be managed by server 10, or it may be managed by a server other than server 10.

[0086] Server 10 can obtain information such as the number of views from the site for viewing sample comics. Server 10 obtains the information entered in the input fields on the creator information input page as creator information. Furthermore, after a certain period has passed since the sample comics were published, Server 10 obtains information from the site regarding the number of views of the published sample comics and the growth rate of the number of views over a predetermined period.

[0087] Server 10 then estimates the future number of views or future publications of the manga created by the creator, based on at least one piece of information: the number of views of the sample manga, the growth rate of the number of views, and the genre of the manga. For example, Server 10 estimates the future number of views or future publications using machine learning such as logistic regression, based on the number of views of the sample manga, the growth rate of the number of views over a predetermined period, and the genre of the manga. Server 10 then estimates the return that the creator can expect to receive in the future, based on the information regarding the future number of views or future publications. For example, Server 10 estimates the future return by estimating the types of advertisements that can be set based on the genre of the manga, and by estimating the revenue that can be obtained from those advertisements based on the information regarding the future number of views or future publications. Server 10 then determines the token price based on the estimation results and performs processing related to the sale of the token, including displaying the price set based on that token price.

[0088] <3-3. Managing Token Transactions> Having explained specific operational examples for each category, I will now explain how Server 10 manages token transactions.

[0089] Server 10 is configured to handle the management of token transactions. This management includes not only the management of token sales (primary transactions) but also the management of token resales (secondary transactions). Server 10 may manage token transactions using blockchain and smart contracts.

[0090] (Overview of token trading management) Server 10 issues the number of tokens set by the project creator. At this time, Server 10 may determine the token price as described above and recommend a price to the project creator when the creator sets the token price. This eliminates concerns that the project creator may significantly increase or decrease the token price from the estimated value and disrupt the market. Furthermore, Server 10 may set upper and / or lower limits on the selling price that the project creator can set based on the determined token price. For example, Server 10 may be configured so that the project creator can only set the token price within ±20% of the determined token price.

[0091] Server 10 issues tokens in response to a request from a terminal device 20 operated by a user (e.g., a supporter). At this time, Server 10 may obtain, for example, a wallet address as identification information of the requesting user. Server 10 may also use smart contracts for token transactions. In this case, Server 10 may configure the smart contract for the issued token to allow transactions of that token only to be completed between users who have a history of receiving tokens from the same issuer. After settlement, Server 10 transfers ownership of the token to the user.

[0092] The server 10 then executes processing related to managing the resale of tokens in response to a request from a terminal device 20 operated by a user (e.g., a reseller / buyer). At this time, the server 10 obtains the user's wallet address according to the conditions set in the token's smart contract and verifies whether the wallet address belongs to a user who has a history of receiving tokens from the same issuer. The server 10 completes the token transaction only if the conditions are met.

[0093] Server 10 may issue and manage tokens using blockchain technology, where transaction history is managed in a decentralized manner. Examples of blockchain-based platforms include Bitcoin, NEM, and Ethereum. Server 10 may use a platform using distributed ledger technology, not limited to blockchain, for managing token transactions. A token resale transaction (a transaction in the secondary market) refers to a series of processes in which users determine the price of the token as the object of the transaction and transfer ownership of the token to another party at the determined price. This allows users to resell tokens after issuing them, taking into account their future value. This enables the tokens to function as securities.

[0094] (Details on managing token transactions) When server 10 receives a token issuance request, it sets the issuer based on the issuer information and issues the token. The issuer information is information that proves that the token issuer is a specific issuer. After settlement, server 10 transfers ownership of the issued token to the requesting user. Server 10 may also be configured to request cryptocurrency or fiat currency from the user as consideration for settlement.

[0095] Server 10 obtains the wallet address of the user requesting the token as an example of user identification information. Note that Server 10 does not only obtain the wallet address at the time of token issuance. Server 10 may obtain the wallet address in advance before issuing the token. Furthermore, if the user has registered their wallet address with other services that interact with the services provided by Server 10, Server 10 may obtain this as the wallet address related to the token transaction. Server 10 may also obtain the wallet address after issuing the token. Server 10 only needs to obtain the wallet address before the token is resold at the latest. Also, user identification information is not limited to a wallet address; it may be a uniquely issued ID, as long as it can identify the user.

[0096] Server 10 creates instruction information that instructs the system to allow token transactions only between the wallet address of the user requesting the token and the wallet address of a user who has previously received tokens from the same issuer. Server 10 then sets the created instruction information as the smart contract for the issued token. Server 10 may set the smart contract at the time of token issuance or afterward. Server 10 only needs to set the smart contract no later than before the token is resold.

[0097] As a result, transactions can be executed, and tokens can be bought and sold.

[0098] <3-4. Other Features> Having described the management of token transactions, we will now explain the other functions of Token Sales System 1.

[0099] (1) Request for additional information Server 10 may determine whether additional information is needed from the proposer based on the proposer information. If Server 10 determines that additional information is needed, it may determine what additional information should be obtained from the proposer and request the proposer to provide that additional information. For example, Server 10 may analyze the items entered by the proposer and, if certain words are used, may request additional input from the user. For example, if the proposer enters "obese" in the health status input field, Server 10 may request the BMI (Body Mass Index) value as additional information. Based on the proposer information and the additional information, Server 10 estimates the return that the proposer can expect to receive in the future. This improves the accuracy of the return estimation.

[0100] (2) Restrictions on the modification of information Server 10 may be configured to restrict modifications to the information presented by the initiator at the time of proposal. For example, Server 10 may be configured so that the information presented by the initiator at the time of proposal cannot be modified without review and approval from the token trading service operator. This prevents investors from changing their decision-making information midway through the process. Server 10 may also be configured to notify token owners of any modifications. For example, if tokens are managed using blockchain, Server 10 will notify the current token owner of the modification via the email address associated with their wallet. This enables Server 10 to ensure reliable transactions.

[0101] (3) Reporting to the management Server 10 may be configured to notify the token operator (the operator of the token trading service) if it determines that the information provided by the initiator at the time of initiation is false. For example, if the operator of the token trading service determines that the falsehood is significant, Server 10 may be configured to notify the token owner that the information provided by the initiator was false. For example, if the token is managed using blockchain, Server 10 will notify the current token owner of the falsehood in the information provided by the initiator via the email address associated with their wallet. This enables Server 10 to achieve highly reliable transactions.

[0102] (4) Calculation of the drafter's credibility Server 10 may be configured to calculate the confidence level of the project creator based on the information entered by the project creator or information about the project creator's past history. Machine learning techniques may be used to calculate the confidence level. Server 10 may then estimate the token price based on the estimated return and the project creator's confidence level. For example, Server 10 may calculate a reduction or increase rate of the token price according to the confidence level and estimate the token price based on the reduction or increase rate. This enables Server 10 to realize highly reliable transactions.

[0103] (5) Prediction of changes in token price Server 10 may adjust the token price based on historical information about the project creator after the token price has been estimated. For example, Server 10 may adjust the token price based on information such as the team's win / loss record or current sales after the token price has been estimated. In other words, after estimating the token price using project creator information, Server 10 re-estimates the token price based on historical information. This is difficult with machine learning. Therefore, Server 10 may mathematically calculate this based on a calculation formula that is based on the category of the project content. This enables Server 10 to achieve highly reliable transactions.

[0104] (6) Dealing with misconduct If misconduct by the project creator is discovered, the token price is expected to plummet. Therefore, if the token price changes by more than a predetermined amount, server 10 may display "Purchase Defect" along with the token price. This allows server 10 to alert potential buyers, thereby enabling more reliable transactions.

[0105] <3-5. Token Setting Process> The functions of Token Sales System 1 have been described above. Next, we will explain the operation of Token Sales System 1 using a flowchart.

[0106] First, let's explain the token setting process. The token setting process is the process by which the user (initiator) sets up (initiates) a token. Figure 5 is a flowchart of the token setting process in this embodiment. When the user uses the terminal device 20 to perform an operation to start initiating a token, the control unit 13 of the server 10 starts the token setting process. The token setting process will be explained below with reference to the flowchart in Figure 5.

[0107] The acquisition unit 131 of the server 10 acquires information about the category of the proposal from the proposer (step S101). For example, the display control unit 135 of the server 10 displays a web page for inputting the category of the proposal on the terminal device 20 held by the proposer. The acquisition unit 131 then acquires the category information entered on the web page from the terminal device 20.

[0108] The display control unit 135 of the server 10 displays a web page containing input fields that the drafter should fill in on the terminal device 20 (step S102). The input fields display input items determined based on the category of the draft content decided by the drafter. The acquisition unit 131 of the server 10 acquires the information entered in the displayed input items (information entered by the drafter based on the input items) as drafter information (step S103).

[0109] The request unit 136 of server 10 determines whether additional information is needed (step S104). For example, if the initiator has entered "obese" in the health status input field, it determines that the BMI (Body Mass Index) value is needed as additional information. If no additional information is needed (step S104: No), the request unit 136 proceeds to step S107.

[0110] If additional information is needed (Step S104: Yes), the request unit 136 requests the additional information from the initiator (Step S105). For example, the display control unit 135 of the server 10 displays a web page for inputting additional information on the terminal device 20 held by the initiator. Then, the acquisition unit 131 of the server 10 acquires the additional information entered on the web page from the terminal device 20 (Step S106). Note that the additional information can be considered as part of the initiator's information.

[0111] The estimation unit 132 of the server 10 estimates the return that the initiator will receive in the future based on the initiator information obtained in step S103 (step S107). For example, the estimation unit 132 estimates the return by inputting the initiator information into a learning model that has learned the relationship between initiator information and the return. If additional information has been obtained in step S105, the estimation unit 132 may estimate the return based on the initiator information and the additional information. The additional information may be considered as part of the initiator information.

[0112] The determination unit 133 of the server 10 determines the token price based on the estimation result in step S107 (step S108). For example, the server 10 may determine the token price as the price obtained by dividing the return estimated in step S107 by the number of tokens issued set by the initiator.

[0113] The determination unit 133 of the server 10 records the determined token price in the storage unit 12 (step S109). The determination unit 133 may also record the token sales price set based on the token price in the storage unit 12. In this case, the sales price may be a price determined by the server 10, for example, by adding a certain amount to the token price. Alternatively, the sales price may be a price determined by the initiator based on the token price. In this case, the sales processing unit 134 of the server 10 may set an upper limit and / or lower limit on the sales price that the initiator can set.

[0114] Once the recording of the token price is complete, the control unit 13 of the server 10 terminates the token setting process.

[0115] <3-6. Token Sales Processing> Next, the token sales process will be explained. The token sales process is the process of selling tokens to users (those who wish to purchase tokens). Figure 6 is a flowchart of the token sales process in this embodiment. When a user (for example, a supporter) uses the terminal device 20 to perform an operation to purchase tokens, the control unit 13 of the server 10 starts the token sales process. The token sales process will be explained below with reference to the flowchart in Figure 6.

[0116] The display control unit 135 of the server 10 displays the token sales page on the user's terminal device 20 (step S201). For example, the display control unit 135 displays a sales page on the user's terminal device 20 as shown in Figure 1.

[0117] The sales processing unit 134 of the server 10 determines on the sales page whether the user has performed an operation related to purchasing tokens (step S202). In the example in Figure 1, the sales processing unit 134 determines whether the user has pressed the purchase button. If the user has not performed a purchase operation (step S202: No), the sales processing unit 134 repeats step S202 until the user performs a purchase operation.

[0118] When a user performs a purchase operation (step S202: Yes), the sales processing unit 134 of the server 10 executes the processing related to the sale of tokens (step S203). In this processing, the server 10 may use blockchain and smart contracts as shown in <3-3. Management of Token Transactions> above.

[0119] Once the processing in step S203 is complete, the control unit 13 of the server 10 terminates the token sales process.

[0120] <3-7. Token Transaction Management Processing> Next, we will explain the token sales process. The token sales process is a process for managing token transactions (secondary transactions) between users.

[0121] Figure 7 is a flowchart of the token transaction management process in this embodiment. When a user uses the terminal device 20 to perform an operation for a token transaction, the control unit 13 of the server 10 starts the token sales process. In the following flowchart explanation, the transaction will be assumed to be a secondary transaction of tokens (resale of tokens) as an example, but the concept of a transaction includes not only secondary transactions of tokens but also primary transactions of tokens. The token transaction management process will be explained below with reference to the flowchart in Figure 7.

[0122] The display control unit 135 of server 10 displays the token trading page (step S301). Then, the management unit 137 of server 10 determines on the trading page whether the user has performed an operation related to token trading (step S302). If the user has not performed a trading operation (step S302: No), the management unit 137 repeats step S302 until the user performs a purchase operation. If the user performs a purchase operation (step S202: Yes), the management unit 137 of server 10 performs processing for token trading (step S303). Once the processing in step S303 is completed, the control unit 13 of server 10 terminates the token sales process.

[0123] <<4. Variation>> The above-described embodiment is merely an example, and various modifications and applications are possible.

[0124] For example, in the embodiment described above, the token recipient, such as a sports player, was assumed to be the initiator of the proposal. However, the initiator is not limited to the token recipient. For example, the initiator may be someone related to the token recipient, such as the sports player's manager (e.g., a management company).

[0125] Furthermore, token purchasers do not necessarily have to be supporters. Token purchasers may be ordinary investors who are not supporters. The term "supporter" in the above embodiments can be replaced with other words that indicate a prospective / considering token purchaser, such as "investor."

[0126] In the embodiment described above, the server 10 estimates the return that the initiator can expect to receive in the future by inputting initiator information into a learning model, and then determines the token price based on that estimation. However, the server 10 may also directly determine the token price by inputting initiator information into a learning model that has learned the relationship between initiator information and token price. In this case, a separate learning model may be prepared for each category.

[0127] The control device for controlling the server 10 or terminal device 20 in this embodiment may be implemented by a dedicated computer system or by a general-purpose computer system.

[0128] For example, a communication program for performing the above-described operations is stored in a computer-readable recording medium such as an optical disc, semiconductor memory, magnetic tape, or flexible disk and distributed. Then, for example, the control device is configured by installing the program on a computer and executing the above-described process. In this case, the control device may be an external device (e.g., a personal computer) of the server 10 or terminal device 20. Alternatively, the control device may be an internal device (e.g., control unit 13 or control unit 23) of the server 10 or terminal device 20.

[0129] Alternatively, the above communication program may be stored on a disk device provided by a server on a network such as the Internet, and made available for download to a computer. Furthermore, the above functions may be realized through the cooperation of an OS (Operating System) and application software. In this case, the parts other than the OS may be stored on a medium and distributed, or the parts other than the OS may be stored on a server device and made available for download to a computer.

[0130] Furthermore, among the processes described in the above embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically by known methods. In addition, the processing procedures, specific names, and information including various data and parameters shown in the above document and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each figure is not limited to the information shown.

[0131] Furthermore, the components of each illustrated device are functionally conceptual and do not necessarily need to be physically configured as shown. In other words, the specific forms of distribution and integration of each device are not limited to those shown, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads and usage conditions.

[0132] Furthermore, the above-described embodiments can be combined as appropriate in areas where the processing content is not contradictory. Also, the order of each step shown in the flowchart of the above-described embodiments can be changed as appropriate.

[0133] Furthermore, for example, this embodiment can also be implemented as any configuration that makes up a device or system, such as a processor as a system LSI (Large Scale Integration), a module using multiple processors, a unit using multiple modules, or a set with additional functions added to a unit (i.e., a configuration of a part of a device).

[0134] In this embodiment, a system refers to a collection of multiple components (devices, modules (parts), etc.), regardless of whether all components are located in the same enclosure. Therefore, multiple devices housed in separate enclosures and connected via a network, and a single device containing multiple modules within a single enclosure, are both considered systems.

[0135] Furthermore, for example, this embodiment can adopt a cloud computing configuration in which a single function is shared and processed collaboratively by multiple devices via a network.

[0136] <<5. Conclusion>> As described above, according to one embodiment of this disclosure, the token sales system 1 estimates the future returns that the initiator can receive based on initiator information about the initiator, and determines the token price based on the estimation result. The token sales system 1 then performs processing related to the sale of tokens, including displaying the sales price set based on the token price. This makes it easy to set and purchase tokens, thus realizing a highly convenient security token offering.

[0137] Although the embodiments of this disclosure have been described above, the technical scope of this disclosure is not limited to the embodiments described above, and various modifications are possible without departing from the gist of this disclosure. Furthermore, components from different embodiments and modifications may be combined as appropriate.

[0138] Furthermore, the effects described in each embodiment of this specification are merely illustrative and not limiting, and other effects may also occur.

[0139] Furthermore, this technology can also be configured as follows. (1) Steps to obtain information about the proposer, An estimation step in which the proposer estimates the return that the proposer will be able to obtain in the future based on the proposer information, A determination step to determine the token price based on the estimation results in the estimation step, A sales processing step includes performing a process related to the sale of tokens, including displaying a sales price set based on the aforementioned token price, A token sales method that includes the following features. (2) It includes a display control step that displays input items determined based on the category of the draft content decided by the previous drafter, The acquisition step involves acquiring the information entered in the displayed input fields as the originator information. The token sales method described in (1) above. (3) The aforementioned categories include at least one of the following: entrepreneurship, research, sports activities, music artist activities, manga artist activities, and visual artist activities. The token sales method described in (2) above. (4) The aforementioned category includes at least sports activities, The display control step, when the sports activity is selected as the category, displays at least one of the following items as the input item: the initiator's current contract amount, match results, and health status. The token sales method described in (2) or (3) above. (5) The aforementioned categories include, at least, entrepreneurship. The display control step, when the category "entrepreneurship" is selected, displays at least one of the following items as input items: maximum feasible market size, operating revenue, revenue per user, gross profit, sales rate, inventory turnover rate, network effect, virality, scalability, number of registered users, and number of active users. The token sales method described in any of (2) to (4) above. (6) The aforementioned categories include at least manga artist activities, The display control step, when the category "manga artist activity" is selected, displays at least the input field for the manga genre as an input field, and also displays information regarding the process for the initiator to publish a sample manga. The token sales method described in any of (2) to (5) above. (7) In addition to displaying the input items, the display control step also displays information regarding the process by which the creator publishes the sample manga. The acquisition step involves acquiring information on the number of views of the published sample manga and the growth rate of the number of views over a predetermined period. The estimation step estimates the future number of views or future publications of the manga created by the creator based on the number of views of the sample manga, the growth rate of the number of views, and the genre of the manga, and estimates the return based on the information of the future number of views or future publications. The token sales method described in (6) above. (8) The estimation step estimates the return that the initiator is expected to receive in the future, based on a learning model that has learned the relationship between initiator information and the return. The token sales method described in any of (1) to (7) above. (9) The acquisition step involves acquiring information on the number of tokens to be issued set by the initiator, The determination step determines the token price based on the return information and the number of issued tokens estimated in the estimation step. The token sales method described in any of (1) to (8) above. (10) The acquisition step involves acquiring information on the token price set by the initiator. The sales processing step displays both the token price determined in the determination step and the sales price set by the initiator. The token sales method described in any of (1) to (9) above. (11) The sales processing step, when the initiator sets the sales price of the token, sets an upper limit on the sales price that the initiator can set, based on the token price. The token sales method described in any of (1) to (10) above. (12) The sales processing step, when the initiator sets the sales price of the token, sets a minimum sales price that the initiator can set based on the token price. The token sales method described in any of (1) to (11) above. (13) The system includes a request step to request additional information from the drafter if it is determined that additional information is needed from the drafter based on the drafter information, The estimation step estimates the return based on the initiator information and the additional information. The token sales method described in any of (1) to (12) above. (14) The determination step calculates the reliability of the proposer based on the content entered by the proposer or information on the proposer's past career, and estimates the return based on the estimation result in the estimation step and the reliability of the proposer. The token sales method described in any of (1) to (13) above. (15) The system includes a management step for managing transactions of the tokens, including the sale of the tokens. The token sales method described in any of (1) to (14) above. (16) The aforementioned management step manages the trading of the tokens using blockchain and smart contracts. The token sales method described in (15) above. (17) The aforementioned management step involves notifying the token operator if it determines that the information provided by the initiator at the time of initiation is false. The token sales method described in (15) or (16) above. (18) The aforementioned transaction includes the resale of the aforementioned tokens. The token sales method described in any of (15) to (17) above. (19) An acquisition unit that acquires information about the person who initiated the proposal, An estimation unit that estimates the return that the proposer will be able to obtain in the future based on the proposer information, A determination unit that determines the token price based on the estimation results from the estimation unit, A sales processing unit that performs processing related to the sale of tokens, including displaying a sales price set based on the aforementioned token price, A token sales device equipped with the following features. (20) Computers, Acquisition unit for obtaining information about the proposer, An estimation unit that estimates the return that the proposer will be able to obtain in the future based on the proposer information. A determination unit that determines the token price based on the estimation result from the estimation unit. A sales processing unit that performs processing related to the sale of tokens, including displaying a sales price set based on the aforementioned token price. A program designed to function as such. [Explanation of Symbols]

[0140] 1. Token sales system 10 servers 20 Terminal devices 11, 21 Communications Department 12, 22 Storage section 13, 23 Control Unit 24 Input section 25 Output section 131 Acquisition Department 132 Estimation Department 133 Judgment section 134 Sales Processing Department 135 Display Control Unit 136 Request part 137 Management Department

Claims

1. A token sales method executed by one or more information processing devices, A display control step that displays input items determined based on the category of the proposal content decided by the proposer, An acquisition step in which the information entered in the displayed input fields is acquired as initiator information about the initiator, An estimation step in which the proposer estimates the return that the proposer will be able to obtain in the future based on the proposer information, A determination step to determine the token price based on the estimation results in the estimation step, The system includes a sales processing step which includes processing related to the sale of tokens, including displaying a sales price set based on the aforementioned token price, The aforementioned category includes at least sports activities, The display control step, when the sports activity is selected as the category, displays at least one of the following items as the input item: the initiator's current contract amount, match results, and health status. The estimation step estimates the return that the initiator is expected to receive in the future, based on a learning model that has learned the relationship between initiator information and the return. The acquisition step involves acquiring information on the number of tokens to be issued set by the initiator, The determination step determines the token price as the price obtained by dividing the return estimated in the estimation step by the number of issued tokens, or the price obtained by dividing the amount obtained by adding a certain fee to the return by the number of issued tokens. The sales processing step, when the initiator sets the sales price of the token, sets an upper or lower limit on the sales price that the initiator can set, based on the token price. Token sales method.

2. A token sales method executed by one or more information processing devices, A display control step that displays input items determined based on the category of the proposal content decided by the proposer, An acquisition step in which the information entered in the displayed input fields is acquired as initiator information about the initiator, An estimation step in which the proposer estimates the return that the proposer will be able to obtain in the future based on the proposer information, A determination step to determine the token price based on the estimation results in the estimation step, The system includes a sales processing step which includes processing related to the sale of tokens, including displaying a sales price set based on the aforementioned token price, The aforementioned categories include, at least, entrepreneurship. The display control step, when "entrepreneurship" is selected as the category, displays at least one of the following items as the input item: maximum feasible market size, operating revenue, revenue per user, gross profit, sales rate, inventory turnover rate, network effect, virality, scalability, number of registered users, and number of active users. The estimation step estimates the return that the initiator is expected to receive in the future, based on a learning model that has learned the relationship between initiator information and the return. The acquisition step involves acquiring information on the number of tokens to be issued set by the initiator, The determination step determines the token price as the price obtained by dividing the return estimated in the estimation step by the number of issued tokens, or the price obtained by dividing the amount obtained by adding a certain fee to the return by the number of issued tokens. The sales processing step, when the initiator sets the sales price of the token, sets an upper or lower limit on the sales price that the initiator can set, based on the token price. Token sales method.

3. A token sales method executed by one or more information processing devices, A display control step that displays input items determined based on the category of the proposal content decided by the proposer, An acquisition step in which the information entered in the displayed input fields is acquired as initiator information about the initiator, An estimation step in which the proposer estimates the return that the proposer will be able to obtain in the future based on the proposer information, A determination step to determine the token price based on the estimation results in the estimation step, The system includes a sales processing step which includes processing related to the sale of tokens, including displaying a sales price set based on the aforementioned token price, The aforementioned categories include at least manga artist activities, If the category "manga artist activity" is selected, the display control step will display at least the manga genre input item as an input item, and will also display information regarding the process for the initiator to publish a sample manga. The estimation step estimates the return that the initiator is expected to receive in the future, based on a learning model that has learned the relationship between initiator information and the return. The acquisition step involves acquiring information on the number of tokens to be issued set by the initiator, The determination step determines the token price as the price obtained by dividing the return estimated in the estimation step by the number of issued tokens, or the price obtained by dividing the amount obtained by adding a certain fee to the return by the number of issued tokens. The sales processing step, when the initiator sets the sales price of the token, sets an upper or lower limit on the sales price that the initiator can set, based on the token price. Token sales method.

4. A token sales method executed by one or more information processing devices, A display control step that displays input items determined based on the category of the proposal content decided by the proposer, An acquisition step in which the information entered in the displayed input fields is acquired as initiator information about the initiator, An estimation step in which the proposer estimates the return that the proposer will be able to obtain in the future based on the proposer information, A determination step to determine the token price based on the estimation results in the estimation step, The system includes a sales processing step which includes processing related to the sale of tokens, including displaying a sales price set based on the aforementioned token price, The aforementioned categories include at least manga artist activities, If the category "manga artist activity" is selected, the display control step will display at least the manga genre input item as an input item, and will also display information regarding the process for the initiator to publish a sample manga. The acquisition step involves acquiring information on the number of views of the published sample manga and the growth rate of the number of views over a predetermined period. The estimation step estimates the future number of views or future publications of the manga created by the creator based on the number of views of the sample manga, the growth rate of the number of views, and the genre of the manga, and estimates the return based on the information of the future number of views or future publications. The acquisition step involves acquiring information on the number of tokens to be issued set by the initiator, The determination step determines the token price as the price obtained by dividing the return estimated in the estimation step by the number of issued tokens, or the price obtained by dividing the amount obtained by adding a certain fee to the return by the number of issued tokens. The sales processing step, when the initiator sets the sales price of the token, sets an upper or lower limit on the sales price that the initiator can set, based on the token price. Token sales method.

5. The estimation step estimates the return that the initiator is expected to receive in the future, based on a learning model that has learned the relationship between initiator information and the return. The token sales method according to claim 4.

6. The aforementioned category includes at least sports activities, The display control step, when the sports activity is selected as the category, displays at least one of the following items as the input item: the proposer's current contract amount, match results, and health status. The token sales method according to any one of claims 2 to 5.

7. The aforementioned categories include, at least, entrepreneurship. The display control step, when the category "entrepreneurship" is selected, displays at least one of the following items as input items: maximum feasible market size, operating revenue, revenue per user, gross profit, sales rate, inventory turnover rate, network effect, virality, scalability, number of registered users, and number of active users. The token sales method according to claim 1, 3, 4, or 5.

8. The system includes a management step for managing transactions of the tokens, including the sale of the tokens. The token sales method according to any one of claims 1 to 7.

9. The aforementioned management step manages the trading of the tokens using blockchain and smart contracts. The token sales method according to claim 8.

10. The aforementioned management step involves notifying the token operator if it determines that the information provided by the initiator at the time of initiation is false. The token sales method according to claim 8 or 9.

11. The aforementioned transaction includes the resale of the aforementioned tokens. The token sales method according to any one of claims 8 to 10.

12. A display control unit that displays input items determined based on the category of the draft content decided by the drafter, An acquisition unit that acquires the information entered in the displayed input fields as information about the initiator, An estimation unit that estimates the return that the proposer will be able to obtain in the future based on the proposer information, A determination unit that determines the token price based on the estimation results from the estimation unit, The system includes a sales processing unit which performs processing related to the sale of tokens, including displaying a sales price set based on the aforementioned token price, The aforementioned category includes at least sports activities, When the sports activity is selected as the category, the display control unit displays at least one of the following items as the input item: the current contract amount of the proposer, match results, and health status. The estimation unit estimates the return that the initiator is expected to receive in the future, based on a learning model that has learned the relationship between initiator information and the return. The acquisition unit acquires information on the number of tokens to be issued set by the initiator, The determination unit determines the token price to be the price obtained by dividing the return estimated by the estimation unit by the number of issued tokens, or the price obtained by dividing the amount obtained by adding a certain fee to the return by the number of issued tokens. The sales processing unit, when the initiator sets the sales price of the token, sets an upper or lower limit on the sales price that the initiator can set, based on the token price. Token sales device.

13. A display control unit that displays input items determined based on the category of the draft content decided by the drafter, An acquisition unit that acquires the information entered in the displayed input fields as information about the initiator, An estimation unit that estimates the return that the proposer will be able to obtain in the future based on the proposer information, A determination unit that determines the token price based on the estimation results from the estimation unit, The system includes a sales processing unit which performs processing related to the sale of tokens, including displaying a sales price set based on the aforementioned token price, The aforementioned categories include, at least, entrepreneurship. When "startup" is selected as the category, the display control unit displays at least one of the following items as input items: maximum feasible market size, operating revenue, revenue per user, gross profit, sales rate, inventory turnover rate, network effect, virality, scalability, number of registered users, and number of active users. The estimation unit estimates the return that the initiator is expected to receive in the future, based on a learning model that has learned the relationship between initiator information and the return. The acquisition unit acquires information on the number of tokens to be issued set by the initiator, The determination unit determines the token price to be the price obtained by dividing the return estimated by the estimation unit by the number of issued tokens, or the price obtained by dividing the amount obtained by adding a certain fee to the return by the number of issued tokens. The sales processing unit, when the initiator sets the sales price of the token, sets an upper or lower limit on the sales price that the initiator can set, based on the token price. Token sales device.

14. A display control unit that displays input items determined based on the category of the draft content decided by the drafter, An acquisition unit that acquires the information entered in the displayed input fields as information about the initiator, An estimation unit that estimates the return that the proposer will be able to obtain in the future based on the proposer information, A determination unit that determines the token price based on the estimation results from the estimation unit, The system includes a sales processing unit which performs processing related to the sale of tokens, including displaying a sales price set based on the aforementioned token price, The aforementioned categories include at least manga artist activities, When the category "manga artist activity" is selected, the display control unit displays at least the manga genre as an input item, and also displays information regarding the process for the creator to publish a sample manga. The estimation unit estimates the return that the initiator is expected to receive in the future, based on a learning model that has learned the relationship between initiator information and the return. The acquisition unit acquires information on the number of tokens to be issued set by the initiator, The determination unit determines the token price to be the price obtained by dividing the return estimated by the estimation unit by the number of issued tokens, or the price obtained by dividing the amount obtained by adding a certain fee to the return by the number of issued tokens. The sales processing unit, when the initiator sets the sales price of the token, sets an upper or lower limit on the sales price that the initiator can set, based on the token price. Token sales device.

15. A display control unit that displays input items determined based on the category of the draft content decided by the drafter, An acquisition unit that acquires the information entered in the displayed input fields as information about the initiator, An estimation unit that estimates the return that the proposer will be able to obtain in the future based on the proposer information, A determination unit that determines the token price based on the estimation results from the estimation unit, The system includes a sales processing unit which performs processing related to the sale of tokens, including displaying a sales price set based on the aforementioned token price, The aforementioned categories include at least manga artist activities, When the category "manga artist activity" is selected, the display control unit displays at least the manga genre as an input item, and also displays information regarding the process for the creator to publish a sample manga. The acquisition unit acquires information on the number of views of the publicly released sample manga and the growth rate of the number of views over a predetermined period. The estimation unit estimates the future number of views or future publications of the manga created by the creator based on the number of views of the sample manga, the growth rate of the number of views, and the genre of the manga, and estimates the return based on the information of the future number of views or future publications. The acquisition unit acquires information on the number of tokens to be issued set by the initiator, The determination unit determines the token price to be the price obtained by dividing the return estimated by the estimation unit by the number of issued tokens, or the price obtained by dividing the amount obtained by adding a certain fee to the return by the number of issued tokens. The sales processing unit, when the initiator sets the sales price of the token, sets an upper or lower limit on the sales price that the initiator can set, based on the token price. Token sales device.

16. Computers, A display control unit that displays input items determined based on the category of the proposal content decided by the proposer. An acquisition unit that acquires the information entered in the displayed input fields as information about the initiator of the proposal. An estimation unit that estimates the return that the proposer will be able to obtain in the future based on the proposer information. A determination unit that determines the token price based on the estimation result from the estimation unit. It functions as a sales processing unit that performs processing related to the sale of tokens, including displaying the sales price set based on the aforementioned token price. The aforementioned category includes at least sports activities, When the sports activity is selected as the category, the display control unit displays at least one of the following items as the input item: the current contract amount of the proposer, match results, and health status. The estimation unit estimates the return that the initiator is expected to receive in the future, based on a learning model that has learned the relationship between initiator information and the return. The acquisition unit acquires information on the number of tokens to be issued set by the initiator, The determination unit determines the token price to be the price obtained by dividing the return estimated by the estimation unit by the number of issued tokens, or the price obtained by dividing the amount obtained by adding a certain fee to the return by the number of issued tokens. The sales processing unit, when the initiator sets the sales price of the token, sets an upper or lower limit on the sales price that the initiator can set, based on the token price. program.

17. Computers, A display control unit that displays input items determined based on the category of the proposal content decided by the proposer. An acquisition unit that acquires the information entered in the displayed input fields as information about the initiator of the proposal. An estimation unit that estimates the return that the proposer will be able to obtain in the future based on the proposer information. A determination unit that determines the token price based on the estimation result from the estimation unit. It functions as a sales processing unit that performs processing related to the sale of tokens, including displaying the sales price set based on the aforementioned token price. The aforementioned categories include, at least, entrepreneurship. When "startup" is selected as the category, the display control unit displays at least one of the following items as input items: maximum feasible market size, operating revenue, revenue per user, gross profit, sales rate, inventory turnover rate, network effect, virality, scalability, number of registered users, and number of active users. The estimation unit estimates the return that the initiator is expected to receive in the future, based on a learning model that has learned the relationship between initiator information and the return. The acquisition unit acquires information on the number of tokens to be issued set by the initiator, The determination unit determines the token price to be the price obtained by dividing the return estimated by the estimation unit by the number of issued tokens, or the price obtained by dividing the amount obtained by adding a certain fee to the return by the number of issued tokens. The sales processing unit, when the initiator sets the sales price of the token, sets an upper or lower limit on the sales price that the initiator can set, based on the token price. program.

18. Computers, A display control unit that displays input items determined based on the category of the proposal content decided by the proposer. An acquisition unit that acquires the information entered in the displayed input fields as information about the initiator of the proposal. An estimation unit that estimates the return that the proposer will be able to obtain in the future based on the proposer information. A determination unit that determines the token price based on the estimation result from the estimation unit. It functions as a sales processing unit that performs processing related to the sale of tokens, including displaying the sales price set based on the aforementioned token price. The aforementioned categories include at least manga artist activities, When the category "manga artist activity" is selected, the display control unit displays at least the manga genre as an input item, and also displays information regarding the process for the creator to publish a sample manga. The estimation unit estimates the return that the initiator is expected to receive in the future, based on a learning model that has learned the relationship between initiator information and the return. The acquisition unit acquires information on the number of tokens to be issued set by the initiator, The determination unit determines the token price to be the price obtained by dividing the return estimated by the estimation unit by the number of issued tokens, or the price obtained by dividing the amount obtained by adding a certain fee to the return by the number of issued tokens. The sales processing unit, when the initiator sets the sales price of the token, sets an upper or lower limit on the sales price that the initiator can set, based on the token price. program.

19. Computers, A display control unit that displays input items determined based on the category of the proposal content decided by the proposer. An acquisition unit that acquires the information entered in the displayed input fields as information about the initiator of the proposal. An estimation unit that estimates the return that the proposer will be able to obtain in the future based on the proposer information. A determination unit that determines the token price based on the estimation result from the estimation unit. It functions as a sales processing unit that performs processing related to the sale of tokens, including displaying the sales price set based on the aforementioned token price. The aforementioned categories include at least manga artist activities, When the category "manga artist activity" is selected, the display control unit displays at least the manga genre as an input item, and also displays information regarding the process for the creator to publish a sample manga. The acquisition unit acquires information on the number of views of the publicly released sample manga and the growth rate of the number of views over a predetermined period. The estimation unit estimates the future number of views or future publications of the manga created by the creator based on the number of views of the sample manga, the growth rate of the number of views, and the genre of the manga, and estimates the return based on the information of the future number of views or future publications. The acquisition unit acquires information on the number of tokens to be issued set by the initiator, The determination unit determines the token price to be the price obtained by dividing the return estimated by the estimation unit by the number of issued tokens, or the price obtained by dividing the amount obtained by adding a certain fee to the return by the number of issued tokens. The sales processing unit, when the initiator sets the sales price of the token, sets an upper or lower limit on the sales price that the initiator can set, based on the token price. program.

Images