Distribution ratio derivation device, distribution ratio derivation method, and distribution ratio derivation program

Abstract

When deriving the distribution rate of compensation to the rights holders for each of the multiple components that make up the presented content, a reasonable distribution rate is derived. [Solution] In the content trading system (10) according to the present invention, quests in the historical exploration app (516a) are traded as content. The quests are presented as a quest screen 110, and components such as text and images are appropriately arranged on this quest screen 110. In presenting this quest screen 110, a presentation degree P[j] is derived, which is the degree to which each component is presented. Then, based on the presentation degree P[j] of each component, a distribution rate RY[j] of compensation to the creator as the rights holder who was involved in the production of each component is derived.

Description

Technical Field

[0001] The present invention relates to a distribution rate derivation device, a distribution rate derivation method, and a distribution rate derivation program, and particularly to a distribution rate derivation device, a distribution rate derivation method, and a distribution rate derivation program for deriving a distribution rate of remuneration to the right holders related to each of a plurality of components constituting the presented digital content.

Background Art

[0002] In recent years, transactions of digital content (hereinafter simply referred to as "content") via a network have been actively carried out. Conventionally, when content is transacted, a part of its sales (profits) is appropriately distributed as remuneration to the right holders related to the content. For example, Patent Document 1 discloses a technique in which profits are distributed (allocated) according to predetermined transaction rules.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] By the way, many contents include a plurality of components as their constituent elements. For example, when the content is visual content displayed as a screen on a smartphone or the like, visual components such as text and images (illustrations, photos, moving images, etc.) are included in the content. Also, there may be cases where auditory components such as voices and music are included in the content. And these plurality of components may be created by different creators, so-called creators, respectively. That is, a plurality of creators may be involved in the production of one content.

[0005] When such content is traded, depending on the terms and conditions, each creator has the right to receive a share of the compensation. When distributing this compensation, it is crucial that the distribution rate is determined in a way that is satisfactory to each creator, that is, to the rights holders who have the right to receive such a share. In other words, it is essential that a reasonable distribution rate is established.

[0006] Therefore, the present invention aims to provide a novel distribution rate derivation device, distribution rate derivation method, and distribution rate derivation program that can derive a reasonable distribution rate when deriving the distribution rate of remuneration to the rights holders for each of the multiple components constituting the presented content. [Means for solving the problem]

[0007] To achieve this objective, the present invention includes a first invention relating to a distribution ratio derivation device, a second invention relating to a distribution ratio derivation method, and a third invention relating to a distribution ratio derivation program.

[0008] The first invention relating to the distribution rate derivation device is a device for deriving the distribution rate of remuneration to the rights holders for each of the multiple components that constitute the presented content, and comprises a presentation degree derivation unit and a distribution rate derivation unit. The presentation degree derivation unit derives the presentation degree, which is the degree to which each component is presented in the presentation of the content. The distribution rate derivation unit then derives the distribution rate based on the presentation degree derived by the presentation degree derivation unit.

[0009] The content may also be content in a visual form that is presented visually as a screen. In this case, the content includes multiple visual form components, either as part of or as part of multiple components. The presentation degree derivation unit then derives the presentation degree of each visual form component based on the proportion that each visual form component occupies on the screen.

[0010] Furthermore, in this case, the presentation degree derivation unit may weight the presentation degree of each visual aspect component based on the position of each visual aspect component on the screen.

[0011] Furthermore, the presentation degree deriving unit may derive the presentation degree of each component based on the length of time each component is presented.

[0012] In this case, the presentation degree derivation unit may weight the presentation degree of each component based on the type of component.

[0013] The second invention of the present invention relates to a method for deriving a distribution rate, and is a method for deriving the distribution rate of compensation to the rights holders for each of a plurality of components constituting the presented content, and includes a presentation degree derivation step and a distribution rate derivation step. In the presentation degree derivation step, a presentation degree is derived that represents the degree of presentation occupied by each component in the presentation of the content. Then, in the distribution rate derivation step, a distribution rate is derived based on the presentation degree derived in the presentation degree derivation step.

[0014] The third invention of the present invention relates to a distribution rate derivation program, which is a program for deriving the distribution rate of compensation to the rights holders for each of a plurality of components constituting the presented content, and causes a computer to execute a presentation degree derivation procedure and a distribution rate derivation procedure. In the presentation degree derivation procedure, a presentation degree is derived, which represents the degree of presentation occupied by each component in the presentation of the digital content. Then, in the distribution rate derivation procedure, the distribution rate is derived based on the presentation degree derived in the presentation degree derivation procedure. [Effects of the Invention]

[0015] According to the present invention, when deriving the distribution rate of rewards to the rights holders for each of the plurality of components constituting the presented content, a reasonable distribution rate, that is, a distribution rate that each rights holder can fully accept, can be derived. This is extremely beneficial for the smooth operation of the content, including content transactions.

Brief Description of the Drawings

[0016] [Figure 1] It is a diagram schematically showing the overall configuration of a content transaction system according to an embodiment of the present invention. [Figure 2] It is a block diagram showing the electrical configuration of a content registration device in the same embodiment. [Figure 3] It is a block diagram showing the electrical configuration of a content management server in the same embodiment. [Figure 4] It is a block diagram showing the electrical configuration of a user terminal in the same embodiment. [Figure 5] It is a diagram showing an example of a quest screen as content in the same embodiment. [Figure 6] It is a diagram conceptually showing the data structure of content in the same embodiment. [Figure 7] It is a diagram showing details of human data in the same embodiment. [Figure 8] It is a diagram showing details of mono data in the same embodiment. [Figure 9] It is a diagram showing details of components in the same embodiment. [Figure 10] It is a diagram showing details of money data in the same embodiment. [Figure 11] It is a diagram conceptually showing the configuration of hierarchical data in the same embodiment. [Figure 12] It is a diagram showing the organized information about money in the hierarchical data in the same embodiment. [Figure 13] It is a diagram showing the transition of information about money in the hierarchical data in the same embodiment. [Figure 14]It is a diagram conceptually showing the data structure of quasi-NFT content in the same embodiment. [Figure 15] It is a sequence diagram showing the flow of processing when the content in the same embodiment is released. [Figure 16] It is a sequence diagram showing the flow of processing when the quasi-NFT content in the same embodiment is traded. [Figure 17] It is a sequence diagram following FIG. 16. [Figure 18] It is a sequence diagram following FIG. 17. [Figure 19] It is a sequence diagram showing the flow of processing when the quasi-NFT content in the same embodiment is used n times. [Figure 20] It is a sequence diagram following FIG. 19. [Figure 21] It is a diagram showing an example of the presentation mode of each component in the same embodiment with the passage of time. [Figure 22] It is a diagram showing the relationship between the degree of modification and the contribution degree of the component before modification to the component after modification when the component in the same embodiment is modified. [Figure 23] It is a diagram showing an example of a modification of text as a component in the same embodiment. [Figure 24] It is a diagram showing an example of the input / output of a generative AI for deriving the degree of modification for the modification example shown in FIG. 23. [Figure 25] It is a diagram showing another example of the input / output of a generative AI for deriving the degree of modification for the modification example shown in FIG. 23. [Figure 26] It is a diagram showing an example of a modification of an image as a component in the same embodiment. [Figure 27] It is a diagram showing an example of the input / output of a generative AI for deriving the degree of modification for the modification example shown in FIG. 26. [Figure 28] It is a diagram showing another example of the input / output of a generative AI for deriving the degree of modification for the modification example shown in FIG. 26. [Figure 29] It is a flowchart showing the flow of the new distribution rate derivation setting task in the same embodiment. [Figure 30] This is a flowchart showing the flow of the modification-time distribution rate derivation and setting task in the same embodiment. [Figure 31] This figure shows another example of the relationship between the degree of modification when a component in the same embodiment is modified and the contribution of the pre-modified component to the modified component. [Figure 32] This figure shows another example of the changes in the financial information within the hierarchical data in the same embodiment. [Modes for carrying out the invention]

[0017] One embodiment of the present invention will be described using the content trading system 10 shown in Figure 1 as an example.

[0018] The content trading system 10 in this embodiment is a system that trades content via a network 100, and is a system that trades content in an application software called the historical exploration app 516a (see Figure 4). The historical exploration app 516a is an application software that guides users to historical buildings and ruins. This historical exploration app 516a is for smartphones, but can also be used on tablets or personal computers (hereinafter referred to as "PCs"). The historical exploration app 516a is distributed free of charge and can be obtained from a distribution service not shown, i.e., it can be downloaded. The content consists of quests such as quizzes and missions. This content is paid and can be purchased from a content market described later, i.e., it can be downloaded.

[0019] As shown in Figure 1, the content trading system 10 comprises a content registration device 20, a content management server 30, a market management server 40, a user terminal 50, a blockchain connection server 60, a community management server 70, and an account management server 80. These elements are connected to a network 100. The content trading system 10 also utilizes the blockchain network 90 as a database for recording transaction information when content transactions occur, or more precisely, when quasi-NFT content transactions occur, as will be described later.

[0020] The content registration device 20 is a device for registering content that is the subject of trading, and is, for example, a PC. A more detailed explanation will follow, but the destination for content registration is the content management server 30. Content registered with the content management server 30 is sent to the market management server 40. Content sent to the market management server 40 is then deployed to the content market formed by the market management server 40, and is, so to speak, released.

[0021] The released content will contain information about people, things, and money related to that content, and the money information in particular will include information about various rights, including ownership of the content. In addition, there are two types of content. One of these two types of content is quasi-NFT (Non-Fungible Token) content. Quasi-NFT content is content that is structured so that ownership can be purchased by applying the mechanism of a well-known NFT (e.g., ERC721), and it has the property of being unique. The other type of content is what is called regular content, which does not go so far as to allow for the purchase of ownership. This regular content is, of course, not unique. Therefore, the price of quasi-NFT content will be set higher than the price of regular content.

[0022] For example, when quasi-NFT content is purchased, that is, when quasi-NFT content is traded, ownership of the quasi-NFT content is transferred to the purchaser, and more specifically, the ownership information of the quasi-NFT content is updated accordingly. This updating of ownership information is handled by the content management server 30. Therefore, when quasi-NFT content is purchased, the market management server 40 notifies the content management server 30 of this, and in response, the content management server 30 transfers ownership of the quasi-NFT content to the purchaser and updates the ownership information accordingly. Then, the updated quasi-NFT content is transferred to the purchaser via the market management server 40 and more specifically, downloaded to the user terminal 50 owned by the purchaser. Furthermore, the quasi-NFT content downloaded to the user terminal 50 is stored in a wallet (not shown) prepared in advance by the purchaser. The user terminal 50 is, for example, a smartphone, but it may also be a tablet or a PC.

[0023] In addition, the content management server 30 records transaction information representing the transaction details of the quasi-NFT content on the blockchain network 90. ​​This recording of transaction information on the blockchain network 90 is performed via the blockchain connection server 60. This grants the quasi-NFT content the aforementioned unique property.

[0024] In addition, a portion of the sales (profits) from the trading of quasi-NFT content is distributed as compensation to the rights holders of the quasi-NFT content. The rights holders here include the owner who owned the quasi-NFT content before the transfer of ownership, the manager who was responsible for the planning and composition (assembly and compilation) of the quasi-NFT content, and the creators who were involved in the production (creation) of the components that make up the quasi-NFT content, as described below. These rights holders form a community, which is managed by community management server 70. Managers and creators are also referred to as members.

[0025] The distribution of rewards to each rights holder is carried out using fungible designated tokens (FT). To this end, the market management server 40 pays tokens corresponding to the rewards to the community management server 70. The community management server 70 distributes the tokens received from the market management server 40 to each rights holder, specifically sending them to each rights holder's individual wallet.

[0026] Furthermore, purchasers of quasi-NFT content, or users, possess both ownership rights to the quasi-NFT content and the right to reuse it. In other words, a user who purchases quasi-NFT content has the right to modify (adapt) the content and release the modified version. Moreover, the reused quasi-NFT content can be reused again, up to n (n; an integer greater than or equal to 2) times. Therefore, strictly speaking, a user who purchases quasi-NFT content possesses both ownership rights to the quasi-NFT content and the right to reuse it n times.

[0027] In order for a user who has purchased quasi-NFT content to use that quasi-NFT content n times, they must join the aforementioned community. To this end, the user who purchased the quasi-NFT content uses their user terminal 50 to apply to the account management server 80 for account registration, which is a prerequisite for joining the community. Once this account registration application is approved, the user uses their user terminal 50 to apply to join the community using the community management server 70. Upon approval of this application to join the community, the user can use the quasi-NFT content they own n times, meaning they become a member of the aforementioned community and can modify the quasi-NFT content and release the modified quasi-NFT content.

[0028] As a modification of this quasi-NFT content, users can post quizzes, images, and other content. In particular, when posting photos or videos, users can also associate these images with location information derived by the aforementioned positioning satellite radio wave receiver 514 (see Figure 4).

[0029] Modification of this quasi-NFT content can be done relatively easily by the user terminal 50, meaning that the quasi-NFT content is configured in such a way. The modified quasi-NFT content is then reviewed to ensure there are no issues with its content, and upon passing this review, the modified quasi-NFT content becomes available for release. The review of the modified quasi-NFT content is performed by the content registration device 20, or more precisely, by a specific authorized person who has the authority to use the content registration device 20. For example, AI may be used in this review. The content registration device 20 then registers the modified quasi-NFT content that has passed the review with the content management server 30 as an item for transaction (release), and from there the processing proceeds in the same manner as described above.

[0030] On the other hand, when regular content is purchased from the content marketplace, that is, when a transaction for regular content takes place, the regular content is downloaded to the user terminal 50 of the purchaser. Then, in the same manner as when a transaction for quasi-NFT content takes place, a portion of the sales from the transaction of the regular content is distributed to each rights holder.

[0031] Now, focusing on the content registration device 20, as mentioned above, this content registration device 20 is, for example, a PC. That is, the PC as the content registration device 20 has a control unit 202, an input / output interface (I / F) 204, an input device 206, a display device 208, an auxiliary storage unit 210, a communication unit 212, etc., as shown in Figure 2. The content registration device 20 also has various other elements, but in Figure 2, elements not directly related to the present invention are omitted from the illustration.

[0032] The control unit 202 is the element responsible for controlling the entire content registration device 20. This control unit 202 has a computer, such as a CPU 202a, as a control execution unit. In addition, the control unit 202 has a main memory unit 202b that the CPU 202a can directly access. The main memory unit 202b includes, for example, ROM and RAM. The ROM stores firmware, including the BIOS. The RAM constitutes a work area and buffer area when the CPU 202a executes processing based on various programs contained in the firmware and various software.

[0033] The input / output interface (I / F) unit 204 acts as a bridge between the control unit 202, particularly the CPU 202a, and various elements such as the input device 206, and includes, for example, a chipset. Therefore, the control unit 202 is connected to the input / output interface unit 204, as are various elements such as the input device 206, the display device 208, the auxiliary storage unit 210, the communication unit 212, and so on.

[0034] The input device 206 is an element that accepts operation by the aforementioned authorized person who is the operator of the content registration device 20, and includes, for example, a keyboard and a mouse.

[0035] The display device 208 is an element that displays various types of information. This display device 208 is, for example, a flat panel display such as a liquid crystal display or an organic EL display, but is not limited to these.

[0036] The auxiliary storage unit 210 has large-capacity storage, such as a hard disk drive. The operating system is stored in this auxiliary storage unit 210, as well as various software, and in particular, application software called content registration software 210a is stored in it. That is, the PC functions as a content registration device 20 when the content registration program contained in the content registration software 210a is executed. The auxiliary storage unit 210 may have rewritable non-volatile memory such as flash memory instead of, or in addition to, the hard disk drive.

[0037] The communication unit 212 is the element responsible for connecting to the network 100. The connection to the network 100 may be made by wire, for example, but it may also be made by wireless.

[0038] Referring again to Figure 1, and focusing on the content management server 30, the content management server 30 includes a control unit 302, an input / output interface (I / F) unit 304, an input device 306, a display device 308, an auxiliary storage unit 310, a communication unit 312, and the like, as shown in Figure 3. The content management server 30 also has various other elements, but in Figure 3, elements not directly related to the present invention are omitted from the illustration.

[0039] The control unit 302 is the element responsible for controlling the entire content management server 30. This control unit 302 has a computer, such as a CPU 302a, as a control execution unit. In addition, the control unit 302 has a main memory unit 302b that the CPU 302a can directly access. Although detailed illustrations are omitted, the main memory unit 302b includes, for example, ROM and RAM. The ROM stores firmware, including the BIOS. The RAM constitutes a work area and buffer area when the CPU 302a executes processing based on various programs contained in the firmware and various software.

[0040] The input / output interface 304 acts as a bridge between the control unit 302, particularly the CPU 302a, and various elements such as the input device 306, and includes, for example, a chipset. Therefore, the control unit 302 is connected to the input / output interface 304, as are various elements such as the input device 306, specifically the input device 306, the display device 308, the auxiliary storage unit 310, the communication unit 312, and so on.

[0041] The input device 306 is an element that accepts operation by the operator of the content management server 30, and includes, for example, a keyboard and mouse. The operator of the content management server 30 is a designated authorized person who has the authority to manage the content management server 30. The input device 306 is used only at designated times, such as when the content management server 30 including the input device 306 is installed or maintained, and is not used at all times.

[0042] The display device 308 is an element that displays various information. This display device 308 is, for example, a flat panel display such as a liquid crystal display or an organic EL display, but is not limited to these. Like the input device 306, this display device 308 is also used only at predetermined times, such as when the content management server 30 is installed or maintained, and is not used at all times.

[0043] The auxiliary storage unit 310 has a large-capacity storage, such as a hard disk drive. The operating system is stored in this auxiliary storage unit 310, as well as various software, and in particular, the content management software 310a is stored there. In addition, the auxiliary storage unit 410 stores a database called the content management database 310b. That is, when the content management program included in the content management software 310a is executed, the content management server 30 performs its intended function, for example, by accepting content registration from the content registration device 20 as described above. The registered content is then stored in the content management database 310b.

[0044] The communication unit 312 is the element responsible for connecting to the network 100. The connection to the network 100 may be made by wire, for example, but it may also be made by wireless.

[0045] Referring again to Figure 1, and focusing on the market management server 40, for example, a detailed diagram of its configuration is omitted, but the market management server 40, in particular, has a hardware configuration that is largely the same as that of the content management server 30. Therefore, the market management server 40 also has an auxiliary storage unit similar to that of the content management server 30, but the market management software and the market management database are stored in the auxiliary storage unit of the market management server 40. That is, when the market management program included in the market management software is executed, the market management server 40 performs its intended function, for example, forming the content market described above. In this process, the content stored in the market management database is deployed to the content market.

[0046] Turning our attention to the blockchain connection server 60, although a detailed diagram of its configuration is omitted here, the hardware configuration of the blockchain connection server 60 is also largely the same as that of the content management server 30. Therefore, the blockchain connection server 60 also has an auxiliary storage unit similar to that of the content management server 30, but the blockchain connection software is stored in the auxiliary storage unit of the blockchain connection server 60. In other words, when the blockchain connection program contained in the blockchain connection software is executed, the blockchain connection server 60 performs its intended function, that is, it receives instructions from the content management server 30 and stores transaction information representing the transaction details of the aforementioned quasi-NFT content in the blockchain network 90.

[0047] Furthermore, focusing on the community management server 70, although a detailed diagram of its configuration is omitted, the hardware configuration of the community management server 70 is also largely the same as that of the content management server 30. Therefore, the community management server 70 also has an auxiliary storage unit similar to that of the content management server 30, but the auxiliary storage unit of the community management server 70 stores community management software and a community management database. That is, when the community management program included in the community management software is executed, the community management server 70 performs its intended function, for example, managing the aforementioned communities. The community management database stores information about the rights holders who constitute the communities.

[0048] In addition, focusing on the account management server 80, although a detailed diagram of its configuration is omitted, the account management server 80, in particular, has a hardware configuration that is largely the same as that of the content management server 30. Therefore, the account management server 80 also has an auxiliary storage unit similar to that of the content management server 30, but the auxiliary storage unit of the account management server 80 stores account management software and an account management database. That is, when the account management program included in the account management software is executed, the account management server 80 performs its intended function, for example, by accepting account registration requests from users who have purchased the aforementioned quasi-NFT content. The account management database stores information about the registered accounts.

[0049] Note that the blockchain network 90 will utilize a publicly known model, such as polygons, but will not be limited to this. A detailed explanation, including a diagram, of this publicly known blockchain network 90 will be omitted.

[0050] Turning our attention to the user terminal 50, as mentioned above, this user terminal 50 is, for example, a smartphone. That is, the smartphone as the user terminal 50 has, as shown in Figure 4, a control unit 502, an input / output interface (I / F) unit 504, an operation display unit 506, a camera 508, a microphone 510, a speaker 512, a positioning satellite radio wave receiving unit 514, an auxiliary storage unit 516, a communication unit 518, and so on. The user terminal 50 also has various other elements, but the illustration of elements not directly related to the present invention has been omitted here.

[0051] The control unit 502 is responsible for controlling the entire user terminal 50, and this control unit 502 has a computer, such as an application processor (hereinafter referred to as "APP") 502a, as a control execution unit. In addition, the control unit 502 has a main memory unit 502b that the APP 502a can directly access. The main memory unit 502b includes, for example, ROM and RAM. The ROM stores firmware such as a boot loader and operating system. The RAM constitutes a work area and buffer area when the APP 502a executes processing based on various programs contained in the firmware and various software.

[0052] The input / output interface unit 504 acts as a bridge between the control unit 502, particularly the APP 502a, and various elements such as the operation display unit 506, and includes, for example, a chipset. Therefore, the control unit 502 is connected to the input / output interface unit 504, as well as various elements such as the operation display unit 506, specifically the operation display unit 506, camera 508, microphone 510, speaker 512, positioning satellite radio wave receiver 514, auxiliary storage unit 516, and communication unit 518.

[0053] The operation display unit 506 has a touch panel 506a. Although detailed illustrations are omitted, the touch panel 506a is a combination product in which a transparent sheet-like pointing device is attached to the display surface of a flat panel display such as a liquid crystal display or an organic EL display. Such a touch panel 506a is both an operation reception unit that accepts user operations and a display unit that displays various information. The operation display unit 506 also has hardware buttons such as a power button (not shown) and light-emitting components such as LEDs (not shown).

[0054] There is no need to explain the camera 508, microphone 510, and speaker 512 in detail, so I will omit their descriptions.

[0055] The positioning satellite radio wave receiving unit 514 is an element that receives radio waves from a positioning satellite (not shown) and derives its own position (user terminal 50). The positioning satellite referred to here is, for example, a GPS satellite or a GNSS satellite. Naturally, the positioning satellite radio wave receiving unit 514 also has a receiving antenna (not shown). The position information (GEO information) derived by this positioning satellite radio wave receiving unit 514 can be linked to, for example, an image captured by the camera 508.

[0056] The auxiliary storage unit 516 is a so-called internal storage, and for example, it has flash memory (not shown). Various application software is stored in this auxiliary storage unit 516. One example of this is the historical exploration application 516a mentioned above.

[0057] The communication unit 518 is the element responsible for connecting to the network 100. The connection to the network 100 is made, for example, wirelessly, but it can also be made by wire.

[0058] As mentioned above, in the content trading system 10 according to this embodiment, quests are traded as content. These quests are displayed on the touch panel 506a of the user terminal 50 as a quest screen 110, as shown in Figure 5, and are therefore presented to the user.

[0059] The quest screen 110 appropriately arranges multiple visual components, such as text and images. Images here include both still images like illustrations and photographs, and moving images. Although not apparent from the figures, including Figure 5, auditory components such as voices, music, sound effects, and beeps—so-called sounds—may also be output from the speaker 512, i.e., presented. In short, the content includes a variety of multiple components.

[0060] Such content has a data structure as shown in Figure 6. That is, the content includes header data, human data, object data, and monetary data.

[0061] Header data is supplementary data about the content, and this header data includes hierarchical data 120. Hierarchical data 120 will be explained in detail later, but it aggregates information representing the interrelationships of people / things / money related to the content.

[0062] Human data refers to data about the people involved in the content. Specifically, as shown in Figure 7, human data includes production information about the people involved in the creation of the content, and this production information includes, for example, information about the team, which is the group of people involved. The team information includes information about the people who make up the team, more specifically the members mentioned above. Furthermore, if the content is an nth-th generation content created through nth-th generation use, then information about the members involved in the creation of the previous generation (n-1th generation) of content, or more precisely, information about the members who directly contributed to the nth-th generation use of the nth-1th generation content, is attached to the information about the members to whom they contributed. In addition, the production information includes information about the role of each member (person). For example, for a manager as a member, information about the manager's role, such as planning, structuring (content assembly), course creation, and public relations, is included. And for a creator as a member, information about the creator's role, such as scenario writer, illustrator, photographer, or videographer, is included.

[0063] Next, the object data is data related to the object, which is the content. Specifically, as shown in Figure 8, the object data includes work information related to the object, which includes information such as the title, version, scenario, and course of the content. In particular, the version includes information about the revision history. Furthermore, various components are included as parts of the scenario. If a component is an nth-th degree reuse component created through nth-th degree reuse, information about the (n-1)th degree component from which it originated is attached to the nth-th degree component.

[0064] Now, focusing on each component, each component contains information as shown in Figure 9. That is, in addition to the component itself, such as text, images, or sounds, a component also includes information such as the title and version. For example, if the component is a photograph, GEO information indicating the location where it was taken may be included as optional information. In addition, other information such as supplementary explanations about the component may also be included as optional information. Furthermore, if the component is text, key phrases extracted from the text by AI may be attached to it.

[0065] Furthermore, financial data is data related to money concerning content, or in other words, data related to rights. Specifically, as shown in Figure 10, financial data includes rights information concerning the rights to the content. This rights information includes information on the usage status of the content, information on ownership (certificate of ownership), generation information, price information, and the aforementioned information on the distribution of compensation. In particular, if the content is n-th derivative content created through n-th derivative use, information on the original n-1-th derivative content (n-1-th derivative work) is attached to the generation information.

[0066] Furthermore, focusing on the hierarchical data 120, this hierarchical data 120 aggregates the interrelationships of people / things / money regarding content, based on the aforementioned people data, thing data, and money data. Specifically, as shown in Figure 11, information is organized appropriately by the three categories of people / things / money, as well as by the roles of manager, creator, and owner, and hierarchically with the previous generation (n-1th generation) of content, and this information is aggregated in a way that links it to each other.

[0067] For example, focusing on a manager in the category of "Human," this hierarchical data 120 reveals that the manager's role includes planning, structuring, and public relations. Furthermore, according to the hierarchical data 120 shown in Figure 11, the content is n-th

[0068] 《Formula 1》 RX = ΣRX[i] where i = 1, 2, ...

[0069] Furthermore, focusing on creators within the category of "people," we can see that multiple creators are involved in the production of content, and from the information about objects, we can identify the components produced by each creator. In addition, according to the hierarchical data 120 shown in Figure 11, we can see that some components are n-th order components produced using n-1-th order components, and we can identify the creators involved in the production of those n-1-th order components. From the information about money, we can see that creators involved in the production of n-th order components hold n-th order copyrights, and creators involved in the production of n-1-th order components hold n-1-th order copyrights. In addition, from the information about money, we can find the distribution rate RY of compensation to all creators, as well as the distribution rate RY[j] to each creator (component) (where j is an index that identifies the creator (component), and is, for example, an integer of 1 or greater). Furthermore, the sum of the distribution rates RY[j] to each creator equals the total distribution rate RY for all creators, and that is, the total distribution rate RY for all creators is expressed by the following equation 2.

[0070] 《Formula 2》 RY = ΣRY[j] where j = 1, 2, ...

[0071] Furthermore, focusing on the owner in the category of "human," we can see that the owner is a licensee who possesses the right to use the nth-order content. When this right is granted from the owner to the manager, the manager acquires the nth-order usage rights, as mentioned above. From the financial information, we can see that the owner possesses not only the nth-order ownership but also the right to grant the n+1th-order usage rights, which is the right to permit purchasers of the nth-order content (quasi-NFT content) to use the content n+1 times. In addition, from the financial information, we can determine the distribution rate RZ of the compensation to the owner.

[0072] Furthermore, the total distribution rate RX to the manager, the distribution rate RY to all creators, and the distribution rate RZ to the owner are related by the following equation 3.

[0073] 《Formula 3》 RX + RY + RZ = 100 (%)

[0074] Here, the total distribution rate RX to the manager and the distribution rate RY to all creators are predetermined (arbitrarily). Therefore, the distribution rate RZ to the owner is necessarily determined by the following equation 4, which is a variation of equation 3.

[0075] 《Formula 4》 RY = 100 (%) - {RX + RY}

[0076] Furthermore, the distribution rates RX[i] for each manager's role are predetermined and artificially set. In contrast, the distribution rates RY[j] for each creator are automatically determined according to the procedure described later.

[0077] Focusing on the financial information within this hierarchical data 120, particularly the information regarding each right, and organizing and illustrating it, we get something like Figure 12. Specifically, information regarding the nth-order use rights of content includes information regarding the nth-order use rights. Furthermore, information regarding copyright includes information regarding the nth-order copyright, and this information regarding the nth-order copyright includes information regarding the (n-1)th-order copyright. In addition, information regarding ownership includes information regarding the nth-order ownership, and this information regarding the nth-order ownership includes information regarding the (n-1)th-order ownership. Furthermore, information regarding ownership includes information regarding the (n+1)th-order use license rights.

[0078] Based on this, when content is traded, or more precisely when quasi-NFT content is repeatedly used for nth-order purposes, the information regarding each right included in the hierarchical data 120 of the quasi-NFT content changes as shown in Figure 13. For primary content, the information regarding usage rights includes information regarding the original usage rights, the information regarding copyright includes information regarding the original copyright, and the information regarding ownership includes information regarding the original ownership, as well as information regarding secondary usage licensing rights.

[0079] As mentioned above, quasi-NFT content applies the mechanism of known NFTs, and like known NFT content, it has a data structure as shown in Figure 14. That is, NFT content has the content itself, index data, and metadata. The index data contains location information for the metadata, and the metadata contains location information for the content itself. Therefore, by sequentially referring to the index data and metadata, it is possible to reach the content itself. As mentioned above, when a transaction of quasi-NFT content takes place, the transaction information is recorded on the blockchain network 90, but only the index data of the NFT content is recorded on the blockchain network 90 (on-chain). The metadata and the content itself are recorded off-chain, for example, on the IPFS (InterPlanetary File System) not shown.

[0080] Here, we will explain the processing flow when content is released, referring to Figure 15. Note that the code starting with "t" shown in Figure 15 is a code that identifies a point in time, and from here on, each point in time will be represented by this code. The same applies to Figures 16 to 20.

[0081] As shown in Figure 15, first, the content registration device 20 generates the content subject to the transaction at t1, that is, content with the data structure shown in Figure 6 is generated. At this time, the information regarding people / things / money in the hierarchical data 120 is also set (input) as appropriate, but the distribution rate RY[j] to each creator is automatically derived and set according to the procedure described later.

[0082] Then, at t3, the content registration device 20 performs an operation to instruct the registration of content, in other words, a content registration instruction is issued. This content registration instruction is sent from the content registration device 20 to the content management server 30. In addition, the content generated at t1, that is, the content to be released, is attached to the content registration instruction.

[0083] When the content management server 30 receives a content registration instruction from the content registration device 20 in t5, if the content registration instruction, which specifically includes the content to be released, satisfies the predetermined content registration conditions, the content management server 30 then submits a content release application to the market management server 40 in the subsequent t7. This content release application is accompanied by the content to be released that was received in t5.

[0084] When the market management server 40 receives a content release request from the content management server 30 along with the content to be released at t9, if the content release request, including the content to be released, satisfies the predetermined release conditions, the content is deployed to the content market, i.e., released, at the subsequent t11. As a result, the released content enters a "awaiting purchase" state, waiting to be purchased (traded) by any user.

[0085] Next, we will explain the processing flow when released content, particularly quasi-NFT content, is traded, referring to Figures 16 to 18.

[0086] In other words, the user terminal 50 performs an operation on t101 to request the purchase of quasi-NFT content, so to speak, a quasi-NFT purchase request is made. This quasi-NFT purchase request is sent from the user terminal 50 to the market management server 40. In addition, the quasi-NFT purchase request is accompanied by information about the user who initiated the quasi-NFT purchase request, that is, purchaser information about the person who wishes to purchase the quasi-NFT content.

[0087] When the market management server 40 receives a quasi-NFT purchase request from the user terminal 50 at t103, if the quasi-NFT purchase request, including the prospective buyer, satisfies the predetermined purchase conditions, the market management server 40 then sends a notification of the quasi-NFT purchase request to the content management server 30 at t105. This notification of the quasi-NFT purchase request includes information to identify the quasi-NFT content to be purchased, such as the ID of the quasi-NFT content and the prospective buyer's information.

[0088] When the content management server 30 receives a notification of a quasi-NFT purchase request from the market management server 40 at t107, the content management server 30 then changes the owner of the quasi-NFT content that is the target of the purchase request at t109, meaning that the quasi-NFT content is updated accordingly. In other words, based on the information of the prospective buyer, the owner information in the hierarchical data 120 of the quasi-NFT content that is the target of the purchase request is rewritten, and the ownership information in the money data (see Figure 10) is also rewritten.

[0089] Subsequently, at t111, the content management server 30 sends a quasi-NFT update completion notification to the market management server 40, informing it that the update of the quasi-NFT content has been completed. This quasi-NFT update completion notification is accompanied by the updated quasi-NFT content.

[0090] At time t113, the market management server 40 receives a notification from the content management server 30 that the quasi-NFT update has been completed. Subsequently, at time t115, the market management server 40 sends the updated quasi-NFT content to the user terminal 50 of the person who wishes to purchase the quasi-NFT content. Around the same time, although not shown in the diagram, the purchase price of the quasi-NFT content is paid from the wallet of the person who wishes to purchase the quasi-NFT content to the market management server 40.

[0091] When the updated quasi-NFT content is received, i.e., downloaded, from the market management server 40 by the user terminal 50 of the person wishing to purchase the quasi-NFT content at t117, then at the subsequent t119, the quasi-NFT content is stored in the wallet of the person wishing to purchase it. This completes the transaction for the quasi-NFT content.

[0092] Furthermore, in the subsequent t121, the market management server 40 sends a quasi-NFT transaction completion notification to the content management server 30, informing it that the transaction of the quasi-NFT content has been completed. This quasi-NFT transaction completion notification is accompanied by the ID of the traded quasi-NFT content.

[0093] When the content management server 30 receives a notification from the market management server 40 that a quasi-NFT transaction has been completed at t123, the market management server 40 then issues a transaction information recording instruction to the blockchain connection server 60 at 125. This transaction information recording instruction includes transaction information, including the index data of the traded quasi-NFT content.

[0094] When the blockchain connection server 60 receives a transaction information recording instruction from the content management server 30 at time 127, if the transaction information recording instruction satisfies predetermined recording conditions, the blockchain connection server 60 then connects to the blockchain network 90 at time 129. Then, at time 131, the blockchain connection server 60 transmits the transaction information to the blockchain network 90.

[0095] When transaction information from the blockchain connection server 60 is received by the blockchain network 90 at time t133, the transaction information is recorded in the blockchain network 90 at the subsequent time t135. This grants the traded quasi-NFT content the property of being unique.

[0096] Furthermore, in the subsequent t137, the market management server 40 pays the community management server 70 a reward for the content transaction. As mentioned above, this reward is paid in a predetermined token. This token payment is accompanied by distribution rate information, which is information regarding the distribution rates RX (RX[i]), RY (RY[j]), and RZ to each rights holder (manager, creator, and owner) to whom the reward is distributed.

[0097] At t139, when the community management server 70 receives the reward from the market management server 40, at the following t139, the community management server 70 distributes the reward to each rights holder (manager, creator, and owner), and in detail, tokens corresponding to the distribution rate of RX (RX[i]), RY (RY[j]), and RZ are sent to each rights holder's respective wallet.

[0098] Similarly, when regular content is traded, the market management server 40 pays a reward to the community management server 70, and the community management server 70 then distributes that reward to each rights holder.

[0099] Next, we will explain the process for a user who has purchased quasi-NFT content to use that quasi-NFT content for the nth time, referring to Figures 19 to 20.

[0100] In other words, an account registration request is made on t201 by the user terminal 50 of the user who purchased the quasi-NFT content, meaning that the necessary operations are performed. This account registration request is sent from the user terminal 50 to the account management server 80. The account registration request is also accompanied by information about the user who initiated the request, that is, information about the person who wishes to register an account.

[0101] When the account management server 80 receives an account registration request from the user terminal 50 in t203, if the account registration request, which includes information about the person wishing to register an account, satisfies the prescribed account registration conditions, the account management server 80 registers the account of the person wishing to register an account in the subsequent t205. Then, in the subsequent t207, the account management server 80 sends an account registration notification to the user terminal 50 of the person wishing to register an account, informing them that their account has been registered.

[0102] When the user terminal 50 of the person wishing to register an account receives an account registration notification from the account management server 80 at time t209, the user terminal 50 then submits a community membership application to the community management server 70 at an appropriate time t211. This community membership application is accompanied by information about the user who submitted the application, that is, community membership applicant information, which is information about the person wishing to join the community.

[0103] When the community management server 70 receives a community membership application from the user terminal 50 at t213, if the community membership application, which includes information about the community member, satisfies the prescribed community membership conditions, then at the subsequent t215, the community member's membership to the community is approved, meaning the community member is registered with the community. Then, at the subsequent t217, the community management server 70 sends a community membership registration notification to the user terminal 50 of the registered user.

[0104] When the user terminal 50 receives a community membership registration notification from the community management server 70 at time t219, the user terminal 50 modifies the quasi-NFT content at an appropriate time t221 thereafter. Then, at the subsequent time t223, the user terminal 50 submits a modified content registration application to the community management server 70 to request registration of the modified quasi-NFT content. This modified content registration application is accompanied by modification information that describes the modifications made to the quasi-NFT content.

[0105] When the community management server 70 receives a modified content registration application from the user terminal 50 at t225, if the modified content registration application, which includes modification information, satisfies the predetermined modification conditions, the community management server 70 then sends a notification of the modified content registration application to the content registration device 20 at t227. This notification of the modified content registration application is accompanied by the modification information received at t227.

[0106] At t229, when the content registration device 20 receives the notification of the modified content registration application from the community management server 70, at t231, the content registration device 20, or more precisely, the aforementioned authorized person who is the operator of the content registration device 20, conducts a review of the modified information, that is, the modified quasi-NFT content. Then, at t233, the content registration device 20 notifies the community management server 70 of the review results.

[0107] When the community management server 70 receives the review result notification from the content registration device 20 at t235, the community management server 70 then sends another review result notification to the user terminal 50 of the user who submitted the modified content registration application at t237. This review result notification is received by the user terminal 50 at t239.

[0108] If the review result notification indicates approval, the modified quasi-NFT content will be released in the same manner as described above. The released modified quasi-NFT content will also be released as regular content. On the other hand, if the review result notification indicates rejection, the modification of the quasi-NFT content will be attempted again, or the modification of the quasi-NFT content will be postponed.

[0109] As mentioned earlier, the distribution rate RY[j] to the creators responsible for producing each component that makes up the content is determined automatically.

[0110] To do this, the presentation degree P[j] of each component is first derived (calculated). The presentation degree P[j] is the degree to which each component is presented in the presentation of the content. This presentation degree P[j] includes the spatial presentation degree PS[j] and the temporal presentation degree PT[j], and is derived based on the following equation 5.

[0111] 《Formula 5》 P[j]=α·PS[j]+β·PT[j] where α+β=1

[0112] Here, spatial presentation PS[j] is the proportion of space occupied by visual components such as text and images on the quest screen 110 (see Figure 5). More precisely, it is the ratio of the area A[j] occupied by each visual component to the sum ΣA[j] of the areas A[j] occupied by all visual components excluding the blank areas of the quest screen 110. In other words, the spatial presentation PS[j] is the ratio of the area A[j] occupied by each visual component when the sum ΣA[j] of the areas A[j] occupied by all visual components excluding the blank areas of the quest screen 110 is set to 1 (100%). This spatial presentation PS[j] is derived based on the following equation 6. Note that the spatial presentation PS[j] of auditory components (sounds) such as voice and music is 0 (zero)%.

[0113] 《Formula 6》 PS[j]=A[j] / ΣA[j] where j=1,2,…

[0114] On the other hand, the time presentation degree PT[j] is the ratio of the time T[j] that each component is presented to the total time T[j] of all components (total time) ΣT[j]. In other words, the time presentation degree PT[j] is the ratio of the time T[j] that each component is presented to, given that the total time T[j] of all components ΣT[j] is set to 1 (100%). This time presentation degree PT[j] is derived based on the following equation 7.

[0115] 《Formula 7》 PT[j]=T[j] / ΣT[j] where j=1,2,…

[0116] Furthermore, some components are presented continuously, as shown in Figure 21(A). Examples of components presented continuously include visual components such as text and images, or auditory components such as background music (BGM). Additionally, some components are presented intermittently, as shown in Figure 21(B). Examples of components presented intermittently include visual components such as images that are sequentially switched and presented over time, or auditory components such as narration and sound effects. Moreover, some components are presented temporarily, as shown in Figure 21(C). Examples of components presented temporarily include visual components such as images that are temporarily presented in response to a predetermined event, or auditory components such as narration and sound effects. The time presentation degree PT[j] of components presented in these various ways is derived based on Equation 7.

[0117] Furthermore, in Equation 5 mentioned above, α is an adjustment coefficient for spatial presentation PS[j], and β is an adjustment coefficient for temporal presentation PT[j]. These adjustment coefficients are set artificially as appropriate, provided that the sum of both is 1.

[0118] Specifically, for each component, the spatial presentation degree PS[j] is derived based on Equation 6, the temporal presentation degree PT[j] is derived based on Equation 7, and furthermore, the presentation degree P[j] is derived based on Equation 5. Then, based on the following Equation 8, the distribution rate RY[j] to the creators responsible for producing each component is derived.

[0119] 《Formula 8》 RY[j]=P[j]·RY

[0120] The content registration device 20 is responsible for deriving the distribution rate RY[j] to each creator in this manner. As mentioned above, when the content registration device 20 generates the content subject to transaction (at t1 in Figure 15), it derives the distribution rate RY[j] to each creator and sets it in the hierarchical data 120 of the content.

[0121] In addition, if any component constituting the content is an nth-order component created through nth-order use, compensation will be distributed to the creators involved in the production of that nth-order component, as well as to the creators involved in the production of the n-1th-order component from which that nth-order component originated. From this point forward, the nth-order component may be referred to as the "modified component," and the creators involved in the production of the modified component (nth-order component) may be referred to as the "modified creator." Furthermore, the n-1st-order component from which the nth-order use (modification) originated may be referred to as the "pre-modification component," and the creators involved in the production of the pre-modification component (n-1st-order component) may be referred to as the "pre-modification creator."

[0122] When distributing rewards to the original creator and the modified creator, a portion of the reward that would normally be distributed to the modified creator (assuming the modified component has not been modified) is distributed to the original creator. That is, if the original distribution rate to the modified creator is RY[j], the actual distribution rate to the modified creator is RYa[j], and the distribution rate to the original creator is RYb[j], then these relationships are expressed by the following equation 9.

[0123] 《Formula 9》 RY[j]=RYa[j]+RYb[j]

[0124] The original distribution rate RY[j] to the modified creator in Equation 9 is derived in accordance with the method described above based on Equations 5 to 8. Then, the distribution rate RYb[j] to the modified creator is derived based on the following Equation 10.

[0125] 《Formula 10》 RYb[j]=C[j']·RY[j]

[0126] In equation 10, C[j'] represents the degree of contribution (influence) of the original component in the creation of the modified component. This contribution C[j'] is derived based on the degree of modification M[j], which is the degree of modification of the modified component relative to the original component. These degree of modification M[j] and contribution C[j'] have a negative linear correlation, as shown in Figure 22, for example.

[0127] According to the relationship shown in Figure 22, the higher the degree of modification M[j], the lower the contribution C[j'], and therefore the lower the distribution rate RYb[j] to the original creator based on Equation 10. On the other hand, the lower the degree of modification M[j], the higher the contribution C[j'], and therefore the higher the distribution rate RYb[j] to the original creator based on Equation 10.

[0128] Here, if the component subject to modification (n-th secondary use) is text, the forms of such modification include proofreading, adding words or sentences, deleting words or sentences, replacing words or sentences, changing the style, changing the tone, etc. The degree of modification M[j] when such text modifications are made can be derived, for example, by a known generative AI.

[0129] As an example, suppose that text with the content shown in Figure 23(A) is modified to text with the content shown in Figure 23(B). In this case, when a prompt like the one shown in Figure 24(A) is input to the generative AI, the output shown in Figure 24(B) is obtained from the generative AI as the result of the derivation of the modification degree M[j].

[0130] Furthermore, the degree of modification M[j] correlates with the similarity S[j], which is the degree of similarity between the modified component and the original component, and more specifically, there is a negative linear correlation between the two. Therefore, the similarity S[j] may be derived instead of the degree of modification M[j], and the degree of modification M[j] may be derived indirectly based on this similarity S[j]. The similarity S[j] referred to here can also be derived, for example, by a known generative AI system.

[0131] For example, if text with the content shown in Figure 23(A) is modified to text with the content shown in Figure 23(B), the prompt shown in Figure 25(A) is input to the generative AI, and the output shown in Figure 25(B) is obtained from the generative AI as the result of the derivation of the similarity S[j]. Incidentally, Figure 25 shows an example of derivation using a known TF-IDF_Cos similarity estimation method.

[0132] Furthermore, the degree of modification M[j] may be derived by methods other than those mentioned above. For example, the degree of modification M[j] may be derived based on the known Levenshtein distance. Alternatively, the degree of modification M[j] may be derived individually by multiple methods, and then, based on the individual derivation results from these multiple methods, the degree of modification M[j] may be derived based on appropriate statistical indicators such as their mean or median.

[0133] On the other hand, if the component to be modified (n-th secondary use) is an image, the forms of such modification include color correction (hue, brightness, saturation), contrast correction, image or text compositing, cropping, resizing, rotation, and filtering. The degree of modification M[j] when such image modifications are performed can also be derived, for example, by a known generative AI.

[0134] As an example, suppose an image (still image) as shown in Figure 26(A) is modified into an image as shown in Figure 26(B). In this case, by inputting a prompt as shown in Figure 27(A) into the generative AI, the generative AI will produce an output as shown in Figure 27(B) as the result of deriving the modification degree M[j].

[0135] For example, when a prompt like the one shown in Figure 28(A) is input to a generative AI, the output shown in Figure 28(B) is obtained from the generative AI as the result of the derivation of the modification degree M[j]. Incidentally, Figure 28 shows examples of derivation using known feature matching techniques and convolutional neural networks.

[0136] Furthermore, other methods may be used to derive the degree of modification M[j] for an image. Also, the degree of modification M[j] may be derived individually using multiple methods, or it may be derived based on the individual derivation results from these multiple methods.

[0137] In addition, if the component subject to modification (n-th order use) is a sound such as voice or music, the form of such modification may include changes to the score or rhythm. Although a detailed explanation including illustrations is omitted, the degree of modification M[j] when sound is modified can also be derived, for example, by a known generative AI.

[0138] After the degree of modification M[j] is derived in this way, the contribution C[j'] corresponding to the degree of modification M[j] is derived based on the relationship (or predetermined formula) shown in Figure 22, and furthermore, the distribution rate RYb[j] to the pre-modification creator is derived based on Equation 10 which includes the contribution rate C[j']. Then, the distribution rate RYa[j] to the post-modification creator is derived based on the following Equation 11, which is a variation of Equation 9.

[0139] 《Formula 11》 RYa[j]=RY[j]-RYb[j]

[0140] The content registration device 20 is also responsible for deriving the distribution rate RYa[j] to the modified creator and the distribution rate RYb[j] to the original creator using this method. That is, when the modified content (quasi-NFT content for n-th use) including the modified component is released (at t1 in Figure 15), the information regarding people / things / money in the hierarchical data 120 of the modified content is artificially set as appropriate. Then, the (original) distribution rate RY[j] to each creator is derived using the method based on the aforementioned equations 5 to 8 and set in the hierarchical data 120. Furthermore, the distribution rate RYa[j] to the modified creator and the distribution rate RYb[j] to the original creator are derived and set in the hierarchical data 120. For example, in the hierarchical data 120 shown in Figure 11, the distribution rate RY[2] corresponds to the distribution rate RYa[j] to the modified creator, and the distribution rate RY[3] corresponds to the distribution rate RYb[j] to the modified creator.

[0141] As mentioned above, the content registration device 20 is responsible for deriving and setting the distribution rate RY[j] to each creator, as well as deriving and setting the distribution rate RYa[j] to the modified creator and the distribution rate RYb[j] to the original creator for the modified content.

[0142] In particular, when the distribution rate RY[j] for each creator of new content is derived and set, the CPU 202a of the content registration device 20 executes a new distribution rate setting task according to the new distribution rate derivation and setting program included in the content registration software 210a. The flow of this new distribution rate derivation and setting task is shown in Figure 29. The code starting with "S" shown in Figure 29 is a code that identifies each step (process), and from here on, each step will be represented by this code. The same applies to Figure 30, which will be explained later. In addition, before the new distribution rate derivation and setting task is executed, the total distribution rate RX for manager rewards, the distribution rate RX[i] for each role of the manager, the distribution rate RY for all creators, the distribution rate RZ for owner, the adjustment coefficient α for spatial presentation level PS[j], and the adjustment coefficient β for temporal presentation level PT[j] are set as appropriate.

[0143] According to this new distribution rate derivation setting task, CPU202a first accepts new content input in S1. Then, in the following S3, CPU202a derives the spatial presentation degree PS[j] of each component based on the aforementioned equation 6. Note that the spatial presentation degree PS[j] of auditory components is 0%.

[0144] Furthermore, in the following step S5, CPU202a derives the time presentation degree PT[j] of each component based on the aforementioned equation 7. Then, in the following step S7, CPU202a derives the presentation degree P[j] of each component based on the aforementioned equation 5. Subsequently, in the following step S9, CPU202a derives the distribution rate PY[j] of each component and sets the derived distribution rate RY[j] in the hierarchical data 120. With this, CPU202a completes the new distribution rate derivation and setting task.

[0145] Furthermore, when the distribution rate RY[j] for each creator of the modified content is derived and set, the CPU 202a of the content registration device 20 executes a modification distribution rate setting task according to the modification distribution rate derivation and setting program included in the content registration software 210a. The flow of this modification distribution rate derivation and setting task is shown in Figure 30. Note that even before the modification distribution rate derivation and setting task is executed, the total distribution rate RX for managers, the distribution rate RX[i] for each role of the manager, the distribution rate RY for all creators, the distribution rate RZ for owners, the adjustment coefficient α for spatial presentation PS[j], and the adjustment coefficient β for temporal presentation PT[j] are set as appropriate.

[0146] According to this modification-time distribution rate derivation setting task, CPU 202a first accepts the modified content (quasi-NFT content) as input in S101. Then, in the following S103-S109, CPU 202a performs the same processing as in S3-S9 of the new distribution rate derivation setting task to derive the distribution rate RY[j] for each component and sets these distribution rates RY[j] in the hierarchical data 120.

[0147] Then, in the following S111, CPU202a accepts an operation to specify the modified component from among the components that make up the modified content. Then, in the following S113, CPU202a accepts input of the original component from which the modified component specified in S111 was derived. Furthermore, in the following S115, CPU202a derives the degree of modification M[j]. In deriving this degree of modification M[j], the generative AI is used as described above, and appropriate prompts are input to this generative AI.

[0148] Subsequently, in S117, CPU202a derives a contribution C[j'] corresponding to the degree of modification M[j] based on the relationship shown in Figure 22. Then, in S119, CPU202a derives the distribution rate RYb[j] to the pre-modification creator based on the aforementioned equation 10, and sets the derived distribution rate RYb[j] in the hierarchical data 120. Furthermore, in the following S121, CPU202a derives the distribution rate RYa[j] to the post-modification creator based on the aforementioned equation 11, and sets the derived distribution rate RYa[j] in the hierarchical data 120.

[0149] Then, in the following S123, CPU202a determines whether the derivation and setting of the distribution rate RYa[j] for all modified creators and the distribution rate RYb[j] for the original creators is complete. If the derivation and setting of the distribution rate RYa[j] for all modified creators and the distribution rate RYb[j] for the original creators is not complete (S123:NO), CPU202a returns to S111 to accept an operation to specify a different modified component. On the other hand, if the derivation and setting of the distribution rate RYa[j] for all modified creators and the distribution rate RYb[j] for the original creators is complete (S123:YES), CPU202a terminates the modification distribution rate derivation and setting task.

[0150] As described above, according to this embodiment, the distribution rate RY[j] for compensation to the creators responsible for producing each component that makes up the content is automatically determined, and more specifically, the distribution rate RY[j] is derived based on the degree of presentation P[j] of each component in the presentation of the content. The distribution rate RY[j] derived in this way is extremely reasonable and can be fully accepted by each creator. This is extremely beneficial for the smooth operation of the content, including the trading of the content.

[0151] Furthermore, according to this embodiment, if any of the components constituting the content is an nth-degree reuse component produced through nth-degree reuse, the modified creator who was involved in the production of this nth-degree reuse component will receive a reward, and the original creator who was involved in the production of the original component from which the modified component originated will also receive a reward. The reward distribution rate RYb[j] for the modified creator and the reward distribution rate RYa[j] for the original creator are derived based on the degree of modification M[j] of the modified component relative to the original component, or in other words, based on the contribution C[j'] of the original component to the modified component. The distribution rates RYa[j] and RYb[j] derived in this way are also very reasonable and are fully acceptable to both the modified creator and the original creator. This is extremely beneficial for facilitating and promoting the nth-stage reuse of content.

[0152] Furthermore, according to this embodiment, the content itself contains information about people, goods, and money, and in particular, it has hierarchical data 120 in which such information about people, goods, and money is aggregated. Therefore, detailed information about people, goods, and money (so to speak, attribute information) including the hierarchical data 120 of the content can be checked at any time and arbitrarily, including when the content is traded. For example, the content can be managed even without a server for managing the content, and it can also be applied to so-called Web3. In addition, since the hierarchical data 120 of the nth-th generation content contains information about the previous generation, the n-1th generation content, by checking the hierarchical data 120 of the previous generations, it is possible to recognize the details of all generations of content, including the first released (1st generation) content.

[0153] In this embodiment, the content registration device 20, or more precisely, the CPU 202a of the content registration device 20, is responsible for deriving the reward distribution rate RY[j] to each creator. The CPU 202a responsible for deriving this distribution rate RY[j], specifically the CPU 202a that executes S9 of the new distribution rate derivation setting task (see Figure 29) and S109 of the modification distribution rate derivation setting task (see Figure 30), is an example of the distribution rate derivation unit according to the present invention. Furthermore, when deriving the distribution rate RY[j], the CPU 202a derives the presentation degree P[j] of each component. The CPU 202a responsible for deriving this presentation degree P[j], specifically the CPU 202a that executes S3 to S7 of the new distribution rate derivation setting task and S103 to S107 of the modification distribution rate derivation setting task, is an example of the presentation degree derivation unit according to the present invention.

[0154] In addition, the CPU 202a of the content registration device 20 is also responsible for deriving the distribution rate RYa[j] for the modified creator and the distribution rate RYb[j] for the original creator of the content produced through n-th use. The CPU 202a responsible for deriving these distribution rates RYa[j] and RYb[j], and more specifically the CPU 202a that executes S119 and S121 of the modification distribution rate derivation setting task, also functions as a distribution rate derivation unit. When deriving these distribution rates RYa[j] and RYb[j], the CPU 202a derives the degree of modification M[j] of the modified component relative to the original component. The CPU 202a responsible for deriving this degree of modification M[j] functions, so to speak, as a modification degree derivation unit.

[0155] This embodiment is merely one specific example of the present invention and does not limit the scope of the invention. The present invention can be applied to various situations other than those described in this embodiment.

[0156] For example, the spatial presentation degree PS[j] based on Equation 6 may be weighted according to the position of each component on the quest screen 110, that is, it may be multiplied by a weighting coefficient γ[j] for each component. As an example, components placed higher on the quest screen 110 may be weighted more heavily, that is, multiplied by a larger weighting coefficient γ[j], and components placed lower on the quest screen 110 may be weighted less heavily, that is, multiplied by a smaller weighting coefficient γ[j]. This improves the rationality of the spatial presentation degree PS[j], and consequently, further improves the rationality of the distribution rate RY[j]. In this case, it is important that each weighting coefficient γ[j] is determined such that the sum of the weighting coefficients Σγ[j] equals 1. Note that the spatial presentation degree PS[j] may be derived by methods other than Equation 6.

[0157] Furthermore, the time presentation degree PT[j] based on Equation 7 may be weighted according to the type of component, that is, it may be multiplied by a weighting coefficient δ[j] for each component. The type of component here refers to the type of aspect, such as whether the component is visual or auditory. Visual components can be further categorized by form, such as illustrations, photographs, and moving images. Auditory components can be categorized by purpose, such as voices, music, background music, sound effects, and beeps. By applying such weighting, the rationality of the time presentation degree PT[j] is improved, and consequently, the rationality of the distribution rate RY[j] is further improved. In this case as well, it is important that the weighting coefficients δ[j] are determined such that the sum of the weighting coefficients Σδ[j] equals 1. Note that the time presentation degree PT[j] may also be derived by methods other than Equation 7.

[0158] Furthermore, the contribution C[j'] included in Equation 10 was derived based on the relationship shown in Figure 22, but it may be derived instead based on the relationship shown in Figure 31, for example. That is, if the modification of a component is a minor correction such as fixing a typographical error, the degree of modification M[j] is small, and therefore the contribution C[j'] is large. Even in such cases, it is appropriate for a certain reward to be distributed to the creator after the modification. Therefore, a predetermined first threshold Ma is set for the degree of modification M[j]. When the degree of modification M[j] falls below the first threshold Ma, the relationship is such that the contribution C[j'] (=Ca) that would be equivalent to the degree of modification [j] being equal to the first threshold Ma is maintained. As a result, even when the degree of modification M[j] falls below the first threshold Ma, the creator after the modification is distributed a reward corresponding to a contribution C[j'] of at least Ca. The first threshold Ma is, for example, 5% to 10%, but may be set (changed) as appropriate depending on the type of component.

[0159] Furthermore, in the relationship shown in Figure 31, a second threshold Mb is set for the degree of modification M[j], which is greater than the first threshold Ma. When the degree of modification M[j] exceeds the second threshold Mb, the relationship is such that the contribution C[j'] (=Cb) that would be equivalent to the degree of modification M[j] being equal to the second threshold Mb is maintained. In other words, empirically (from experiments), when the degree of modification M[j] exceeds a certain degree, the impression of the original component that appears in the modified component tends to become weaker. Even in such cases, it is appropriate to distribute a certain amount of compensation to the original creator, and the second threshold Mb is set to guarantee this. The second threshold Mb is set to 50%, for example, but it may be set appropriately depending on the type of component.

[0160] In addition, in this embodiment, the content registration device 20 is responsible for deriving the distribution rate RY[j] to each creator. In other words, the content registration device 20 is an example of a distribution rate derivation device according to the present invention, but other elements may also function as a distribution rate derivation device. Furthermore, a dedicated element for deriving the distribution rate RY[j], that is, as a distribution rate derivation device, may be provided. The same applies to the derivation of the distribution rate RYa[j] to the modified creator and the distribution rate RYb[j] to the original creator.

[0161] Furthermore, in this embodiment, the blockchain network 90 was used as a database for recording transaction information of quasi-NFT content, but this is not limited to this. For example, a database for recording transaction information of quasi-NFT content may be provided on a suitable server other than the blockchain network 90.

[0162] Furthermore, if the blockchain network 90 is not used, it is possible to configure the system so that, for example, multiple secondary content is created individually based on primary content, and then multiple tertiary content is created individually based on each of these secondary content, and so on, with the nth-order use being repeated. In this case, transaction information for each content may be recorded using a graph structure as shown in Figure 32. According to the graph structure shown in Figure 32, for example, tertiary content can be created based on multiple secondary content, that is, it can accommodate such a configuration. In other words, nth-order content can be created based on multiple n-1th-order content, and even more so, it can be created based on multiple content of different dimensions (for example, n-1th and n-2nd-order) that are earlier than the nth-order.

[0163] In this embodiment, quests in the historical exploration app 516a were given as an example of content, but the content may be something other than quests.

[0164] In addition, although the content trading system 10 shown in Figure 1 was used as an example in this embodiment, the present invention can also be applied to other applications.

[0165] Furthermore, the present invention is not limited to the form of a distribution ratio derivation device, but can also be provided in the form of a distribution ratio derivation method or a distribution ratio derivation program.

[0166] Furthermore, the present invention can also be provided in the form of a computer-readable, non-transient recording medium on which a distribution rate derivation program is recorded. The recording medium in this context may include semiconductor media or disk media. Alternatively, embedded (internal) media, such as ROMs or hard disk drives, which are not portable media, can also be used as recording media in this context. [Explanation of Symbols]

[0167] 10… Content trading system 20… Content registration device 30… Content management server 40… Market management server 50 ... User terminal 60… Blockchain connection server 70 … Community Management Server 80… Account management server 90… Blockchain Network 100 … Network 110... Quest screen 120 … Hierarchical data 202 ... Control Unit 202a ... CPU 202b… Main memory section

Claims

1. A distribution rate derivation device for deriving the distribution rate of remuneration to the rights holders for each of the multiple components that constitute the presented digital content, A presentation degree derivation unit that derives a presentation degree representing the degree to which each of the multiple components is presented in the presentation of the digital content, A distribution rate derivation device comprising a distribution rate derivation unit that derives the distribution rate based on the presentation degree derived by the presentation degree derivation unit.

2. The aforementioned digital content is content in a visual form that is visually presented as a screen, and includes a plurality of visual form components as part or all of the plurality of components. The distribution ratio derivation device according to claim 1, wherein the presentation degree derivation unit derives the presentation degree of each of the plurality of visual mode components based on the proportion that each of the plurality of visual mode components occupies on the screen.

3. The distribution ratio derivation device according to claim 2, wherein the presentation degree derivation unit weights the presentation degree of each of the plurality of visual mode components based on the position of each of the plurality of visual mode components on the screen.

4. The distribution rate derivation device according to claim 1, wherein the presentation degree deriving unit derives the presentation degree of each of the plurality of components based on the length of time each of the plurality of components is presented.

5. The distribution rate derivation device according to claim 4, wherein the presentation degree derivation unit weights the presentation degree of each of the plurality of components based on the type of each of the plurality of components.

6. A method for deriving distribution rates for determining the distribution rate of remuneration to rights holders for each of the multiple components constituting the presented digital content, A presentation degree derivation step for deriving a presentation degree that represents the degree to which each of the multiple components is presented in the presentation of the digital content, A method for deriving a distribution rate, comprising: a distribution rate derivation step of deriving the distribution rate based on the presentation degree derived by the presentation degree derivation step.

7. A distribution rate derivation program that derives the distribution rate of remuneration to the rights holders for each of the multiple components that constitute the presented digital content, A presentation degree derivation procedure for deriving a presentation degree that represents the degree to which each of the multiple components is presented in the presentation of the aforementioned digital content, A distribution rate derivation program that causes a computer to execute a distribution rate derivation procedure for deriving the distribution rate based on the distribution degree derived by the distribution degree derivation procedure.

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