Data processing device, data processing method, and data processing program

Abstract

To provide a device, method and program, which facilitate acquisition of vector data for use in RAG.SOLUTION: A data processing device disclosed herein performs processes of vectorizing book data into a data format usable by a generative model in RAG to generate vectorized book data, storing the vectorized book data in a database, selling the vectorized book data according to user instructions, collecting usage fees from users for selling the vectorized book data, and distributing the usage fees to rights holders of the book data.SELECTED DRAWING: Figure 4

Description

Technical Field

[0001] The technology of the present disclosure relates to a data processing apparatus, a data processing method, and a data processing program.

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, due to the remarkable progress of AI (Artificial Intelligence), various generative AIs that generate content using generative models have emerged. However, generative models have problems such as not containing the latest data or outputting plausible lies (hallucinations). Therefore, a technique for improving the output accuracy and reliability of a generative model by using RAG (Retrieval Augmented Generation) is known. However, there is a problem that it is difficult to obtain the vector data used in RAG.

[0005] Therefore, the present invention aims to provide an apparatus, method, and program that can facilitate the acquisition of vector data used in RAG. [Means for solving the problem]

[0006] A first aspect of the technology of this disclosure includes a process of creating vectorized book data by vectorizing book data into a data format usable in RAG by a generation model, a process of storing the vectorized book data in a database, a process of selling the vectorized book data based on user instructions, a process of collecting usage fees from users for the sale of the vectorized book data, and a process of distributing the usage fees to the rights holders of the book data. This is a data processing device that performs the following actions.

[0007] When a search instruction is received from the user for purchasing the vectorized book data stored in the database, the system may execute a process to output the search results.

[0008] The aforementioned vectorized book data and related book data vectorized to the vectorized book data may be sold together.

[0009] The vectorized book data sold to the user may be stored for each user, and the user may be allowed to add or delete the stored vectorized book data.

[0010] The sale of the aforementioned vectorized book data may be carried out only for the portion of the vectorized book data desired by the user.

[0011] The aforementioned usage fee may be calculated based on the amount used in RAG.

[0012] The system may perform the following steps: obtain a prompt input from the user to the generative model; search the database for the vectorized book data related to the prompt input from the user to the generative model; and output the search results to the user.

[0013] A second aspect of the technology of this disclosure is a data processing method in which a computer performs the following processes: vectorizing book data into a data format usable in RAG by a generation model to create vectorized book data; storing the vectorized book data in a database; selling the vectorized book data based on user instructions; collecting usage fees from users for the sale of the vectorized book data; and distributing the usage fees to the rights holders of the book data.

[0014] A third aspect of the technology of this disclosure is a data processing program that causes a computer to perform the following processes: vectorizing book data into a data format usable in RAG by a generation model to create vectorized book data; storing the vectorized book data in a database; selling the vectorized book data based on user instructions; collecting usage fees from users for the sale of the vectorized book data; and distributing the usage fees to the rights holders of the book data. [Brief explanation of the drawing]

[0015] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a user terminal. [Figure 3] This outlines the specific processing steps. [Figure 4] The functional configuration of a specific processing unit of a data processing device is shown in general terms. [Figure 5] This diagram outlines an example of the operation flow of a specific process performed by a data processing device. [Figure 6]An example of the operation flow of a specific process by a data processing device is schematically shown.

Embodiments for Carrying Out the Invention

[0016] Hereinafter, an example of embodiments of a data processing device, a data processing method, and a data processing program according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit), etc.

[0019] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the embodiment.

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a user terminal 14. An example of the data processing device 12 is a server. An example of the user terminal 14 is a personal computer, a smartphone, etc. The data processing device 12 is an example of a "data processing device" related to the technology of this disclosure.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The user terminal 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the user terminal 14.

[0031] As shown in Figure 2, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "data processing program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 contains the database 59. The database 59 stores vectorized book data created when the book data generation model 58 vectorizes the book data into a data format usable in RAG. The database 59 is used by the specific processing unit 290.

[0033] At the user terminal 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 62. The reception output program 62 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 62 from the storage 50 and executes the read reception output program 62 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 62 executed on the RAM 48.

[0034] Next, we will explain the processing of the specific processing unit 290 when the data processing device 12 performs specific processing for selling vectorized book data. Here, "book data" refers to so-called "e-books" that are composed in digital format. It should be noted that the items sold by the data processing device 12 are not limited to book data, but may also be other data, such as audio data or movie data.

[0035] Figure 3 shows an overview of a specific process for selling vectorized book data created by the generation model 58 vectorizing book data into a data format usable in RAG (Retrieval Augmented Generation). Generally, the process involves the author sending a manuscript to a publisher, the publisher creating manuscript data based on the manuscript and sending it to Vector Bookstore, Vector Bookstore's data processing unit 12 vectorizing the manuscript data to create vectorized book data, registering the created vectorized book data in a database and selling it, and the user searching for and purchasing the vectorized book data registered and sold in the database. The process also involves the user paying a usage fee for the vectorized book data, Vector Bookstore paying a usage fee to the publisher, and the publisher paying the author a manuscript fee or royalties based on the usage fee. The vectorized book data purchased by the user may be stored (embedded) in the vector database of the user terminal 14's storage 50. Alternatively, the vectorized book data purchased by the user may be stored (embedded) in the vector database set up for each user in the data processing unit 12's storage 32. It is desirable that the vector database set up for each user allows the user to add or delete stored vectorized book data. Then, when a user uses the generative model 58, the generative model 58 references the purchased vectorized book data from the vector database and outputs the generation result.

[0036] In recent years, with the remarkable progress of AI, various generation tools 16 have emerged that take user-generated text, voice, and image data as input into a generation model 58 and produce generation results. The generation model 58 is an example of a "generation model" related to the technology disclosed herein.

[0037] Here, generative model 58 is what is known as generative AI (Artificial Intelligence). An example of generative model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include the following. The generative model 58 is obtained by performing deep learning on a neural network. The generative model 58 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images. The generative model 58 infers from the input inference data according to the instructions shown by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. Furthermore, by using RAG during inference, the accuracy and reliability of the inference results are improved using vectorized book data.

[0038] Furthermore, the vector bookstore may be integrated with the generation tool 16 via an API (Application Programming Interface). API integration refers to data exchange with external applications or systems using an API. In this case, users can log in to the vector bookstore and select the generation tool 16, which is integrated as an extension, to use the generation AI as if they were accessing it directly. Also, since all communication between the user and the generation model 58 will be via the API, the data processing device 12 implemented in the vector bookstore can grasp the usage status (including usage amount) of the vectorized book data. This makes it possible to calculate the usage fee for vectorized book data collected from users based on the actual usage amount in RAG.

[0039] Figure 4 schematically shows the functional configuration of the identification processing unit 290 of the data processing device 12. The identification processing unit 290 includes a book data receiving unit 291, a creation unit 292, a storage unit 293, a sales unit 294, a collection unit 295, a distribution unit 296, and an interface unit 297.

[0040] The book data reception unit 291 receives book data from publishers and authors.

[0041] The creation unit 292 vectorizes the book data received by the book data reception unit 291 into a data format usable by the generation model 58 in RAG to create vectorized book data. Here, vectorization can be performed using known techniques. Note that the vectorization of book data is not limited to creating one vector data for each book data; the book data may be divided into multiple parts, for example, by chapter. In addition, a summary of the book data may be vectorized and saved together with the vectorized book data, and this summary may be used as the target for searching the vectorized book data by the user.

[0042] The memory unit 293 stores the vectorized book data created by the creation unit 292 in the sales database 59.

[0043] The sales department 294 sells vectorized book data based on user instructions. Before selling, the sales department 294 outputs to the user the results of a search for vectorized book data stored in the database 59, for example, a keyword search for the title or part of the content of a book related to the inference results the user wants to output to the generative model 58. Then, based on the search results, the sales department 294 sells the vectorized book data based on the user's instruction to purchase the vectorized book data.

[0044] Furthermore, the sale of vectorized book data may include not only the sale of all parts of the vectorized book data, but also the sale of only the parts of the vectorized book data that the user desires. For example, if the vectorized book data consists of multiple chapters, only the chapters that the user desires may be sold.

[0045] Furthermore, the sale of vectorized book data is not limited to the sale of a single vectorized book data; multiple vectorized book data sets may be sold together. For example, a vectorized book data output by a user's search may be sold together with vectorized related book data, which is created by vectorizing related book data associated with that vectorized book data. Here, related book data may include, for example, the complete works of the author of the vectorized book data, or the literature listed as references in the vectorized book data.

[0046] Furthermore, the process is not limited to outputting the results of a search instruction for vectorized book data stored in the database 59 to the user before selling the vectorized book data. Specifically, the sales unit 294 may obtain a prompt input from the user to the generation model 58, search the database 59 for vectorized book data related to that prompt, and output the search results to the user. Here, whether the vectorized book data is related to the prompt may be determined by whether the vectorized book data contains more than a certain threshold of words included in the prompt, or whether the title of the vectorized book data contains words included in the prompt, etc.

[0047] The Collection Department 295 collects usage fees from users for the sale of vectorized book data by the Sales Department 294. Here, the usage fee may be a flat rate regardless of how many times the vectorized book data is used, or it may be a fee paid per use. Alternatively, the usage fee may be calculated based on the amount of vectorized book data used within RAG.

[0048] The distribution unit 296 distributes the usage fees collected by the collection unit 295 to the rights holders of the book data, such as publishers and authors.

[0049] The interface unit 297 supplies user instructions to the generative model 58 via the API and obtains inference results from the generative model 58 via the API.

[0050] Next, the operation of the data processing system 10 will be explained.

[0051] Figures 5 and 6 schematically show an example of the operation flow of a specific process performed by the data processing device 12. Note that the processes in Figure 5 and Figure 6 are not limited to being performed by the same data processing device 12; they may be performed by other data processing devices 12.

[0052] First, the specific processing flow for vectorizing book data will be explained with reference to Figure 5. Note that the specific processing flow shown in Figures 5 and 6 is an example of a "data processing method" related to the technology of this disclosure.

[0053] In step S300, the book data receiving unit 291 receives the book data to be vectorized.

[0054] In step S301, the creation unit 292 vectorizes the book data received in step S300 to create vectorized book data.

[0055] In step S302, the vectorized book data created in step S301 is stored in the sales database 59. Then, the specific processing shown in Figure 5 is terminated.

[0056] Next, referring to Figure 6, we will explain the specific processing flow related to the sale of vectorized book data.

[0057] In step S310, the sales department 294 receives a search instruction from the user to purchase vectorized book data stored in the database 59, and outputs the search results.

[0058] In step S311, the sales department 294 sells vectorized book data from the search results output in step S310, based on the user's instructions.

[0059] In step S312, the collection unit 295 collects a usage fee from the user for the vectorized book data sold in step S311.

[0060] In step S313, the distribution unit 296 distributes the usage fees for the vectorized book data collected in step S312 to the rights holders. Then, the identification process shown in Figure 6 is completed.

[0061] As described above, the data processing device 12 according to this embodiment vectorizes book data into a data format usable in RAG by the generation model 58 to create vectorized book data, stores the vectorized book data in the database 59, sells the vectorized book data based on user instructions, collects usage fees from users for the sale of the vectorized book data, and distributes the usage fees to the rights holders of the book data. This makes it possible to enrich the vectorized book data and make it easier to obtain vector data used in RAG. Furthermore, by using vectorized book data, the output accuracy and reliability of the generation model 58 can be improved. In addition, it becomes possible to prevent illegal copying of book data, and the rights holders of the book data can obtain appropriate profits.

[0062] Furthermore, when a user requests a search for vectorized book data stored in database 59 to purchase, the system may execute a process to output the search results. This allows the user to find the appropriate vectorized book data.

[0063] Vectorized book data and related book data vectorized from that vectorized book data may be sold together. This reduces the effort required for users to search for vectorized book data.

[0064] The vectorized book data sold to each user may be stored separately for each user, and users may be allowed to add or delete the stored vectorized book data. This allows users to obtain inference results from a generative model 58 that are specific to them.

[0065] The sale of vectorized book data may be limited to only the portions of the vectorized book data that the user desires. This prevents users from paying for portions that are irrelevant to them.

[0066] The usage fee may be calculated based on the amount used in RAG. This prevents users from paying for parts of the inference results generated by generative model 58 that they do not use.

[0067] The system may also perform the following steps: retrieve the prompt entered by the user into the generative model 58; search the database 59 for vectorized book data related to the prompt entered by the user into the generative model 58; and output the search results to the user. This prevents the user from purchasing book data that is not related to the prompt.

[0068] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0069] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0070] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0071] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0072] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0073] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0074] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0075] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0076] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0077] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0078] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0079] In relation to the above, the following additional information is disclosed.

[0080] <Note 1> The process involves the generative model vectorizing book data into a data format usable in RAG to create vectorized book data, and The process of storing the aforementioned vectorized book data in a database, The process of selling the aforementioned vectorized book data based on user instructions, The process of collecting usage fees from users for the sale of the aforementioned vectorized book data, The process of distributing the aforementioned usage fees to the rights holders of the aforementioned book data, A data processing device that performs this operation. <Note 2> The data processing device described in Appendix 1, which, upon receiving a search instruction from the user for purchasing the vectorized book data stored in the database, executes a process to output the search results. <Note 3> A data processing device according to Appendix 1 or Appendix 2, which sells together the aforementioned vectorized book data and vectorized related book data obtained by vectorizing related book data associated with the said vectorized book data. <Note 4> The vectorized book data sold to the aforementioned users is stored for each user, A data processing device according to any one of the appendices 1 to 3, which allows the user to add or delete the vectorized book data stored. <Note 5> The sale of the vectorized book data is carried out using the data processing device described in any one of the appendices 1 to 4, which is performed for the portion of the vectorized book data desired by the user. <Note 6> The aforementioned usage fee is calculated based on the amount used in RAG. Data processing device as described in any one of Appendix 1 to Appendix 5. <Note 7> The process of obtaining the prompt input from the user to the generation model, The process of searching the database for the vectorized book data related to the prompt input by the user to the generation model, A data processing device according to any one of the appendices 1 to 6, which performs the process of outputting the aforementioned search results to the user. <Note 8> Computers The process involves the generative model vectorizing book data into a data format usable in RAG to create vectorized book data, and The process of storing the aforementioned vectorized book data in a database, The process of selling the aforementioned vectorized book data based on user instructions, The process of collecting usage fees from users for the sale of the aforementioned vectorized book data, The process of distributing the aforementioned usage fees to the rights holders of the aforementioned book data, A data processing method that performs the following. <Note 9> On the computer, The process involves the generative model vectorizing book data into a data format usable in RAG to create vectorized book data, and The process of storing the aforementioned vectorized book data in a database, The process of selling the aforementioned vectorized book data based on user instructions, The process of collecting usage fees from users for the sale of the aforementioned vectorized book data, The process of distributing the aforementioned usage fees to the rights holders of the aforementioned book data, A data processing program to execute. [Explanation of symbols]

[0081] 10 Data Processing Systems 12 Data Processing Devices 14 User terminals 58 Generative Models 290 Specific Processing Unit 291 Book Data Reception Department 292 Creation Department 293 Storage section 294 Sales Department 295 Collection Department 296 Distribution section

Claims

1. The process involves the generation model vectorizing book data into a data format usable in RAG to create vectorized book data, and The process of storing the aforementioned vectorized book data in a database, The process of selling the aforementioned vectorized book data based on user instructions, The process of collecting usage fees from users for the sale of the aforementioned vectorized book data, The process of distributing the aforementioned usage fees to the rights holders of the aforementioned book data, The process of obtaining the prompt input from the user to the generation model, The process of searching the database for the vectorized book data related to the prompt input by the user to the generation model, The process of outputting search results to the user, A data processing device that performs this operation.

2. The data processing device according to claim 1, which, when it receives a search instruction from the user for purchasing the vectorized book data stored in the database, performs a process to output the search results.

3. The data processing device according to claim 1, which sells together the vectorized book data and vectorized related book data obtained by vectorizing related book data associated with the vectorized book data.

4. The vectorized book data sold to the aforementioned users is stored for each user, The data processing device according to claim 1, which allows the user to add or delete the stored vectorized book data.

5. The data processing device according to claim 1, wherein the sale of the vectorized book data is performed only for the portion of the vectorized book data desired by the user.

6. Computers The process involves the generation model vectorizing book data into a data format usable in RAG to create vectorized book data, and The process of storing the aforementioned vectorized book data in a database, The process of selling the aforementioned vectorized book data based on user instructions, The process of collecting usage fees from users for the sale of the aforementioned vectorized book data, The process of distributing the aforementioned usage fees to the rights holders of the aforementioned book data, The process of obtaining the prompt input from the user to the generation model, The process of searching the database for the vectorized book data related to the prompt input by the user to the generation model, The process of outputting search results to the user, A data processing method that performs the following.

7. On the computer, The process involves the generation model vectorizing book data into a data format usable in RAG to create vectorized book data, and The process of storing the aforementioned vectorized book data in a database, The process of selling the aforementioned vectorized book data based on user instructions, The process of collecting usage fees from users for the sale of the aforementioned vectorized book data, The process of distributing the aforementioned usage fees to the rights holders of the aforementioned book data, The process of obtaining the prompt input from the user to the generation model, The process of searching the database for the vectorized book data related to the prompt input by the user to the generation model, The process of outputting search results to the user, A data processing program to execute.

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