Information processing device system, information processing method, and program

Abstract

The present invention comprises: a generation unit that generates a connector for content corresponding to details selected or input by a user; and a display control unit that causes a user terminal to display the content in response to an operation performed on the connector by the user.

Description

Information Processing Apparatus System, Information Processing Method, and Program

[0001] The present invention relates to an information processing apparatus system, an information processing method, and a program. This application claims priority based on Japanese Patent Application No. 2024-196177 filed in Japan on November 8, 2024, Japanese Patent Application No. 2024-196185 filed in Japan on November 8, 2024, and Japanese Patent Application No. 2024-196195 filed in Japan on November 8, 2024, and incorporates the contents thereof herein.

[0002] Services that respond to questions input by users are known. For example, Patent Document 1 discloses a technique for sending a question to an appropriate response device among a plurality of response devices that output answers to the question so as to quickly obtain an answer to the question.

[0003] Japanese Patent No. 7468654

[0004] However, the technique of Patent Document 1 had room for improvement in terms of providing an appropriate answer tailored to each individual user. In Patent Document 1, an answer can be obtained from an appropriate response device among a plurality of response devices, but the case where the content of the question is not clear is not considered. For example, for the question "App A cannot be found", there can be cases such as "I installed App A but don't know where the icon is" and "I'm about to install App A but don't know where the file to be installed is located". In order to appropriately answer the user's question of "App A cannot be found", it is better to be able to clarify the content of the question.

[0005] The present invention has been made in view of such a situation, and one of its purposes is to provide an information processing apparatus system, an information processing method, and a program that can clarify the content of a question. Another purpose of the present invention is to provide an information processing system, an information processing method, and a program that can suppress the occurrence of ambiguous answers to questions.

[0006] To solve the above-mentioned problems of the present invention, the present invention is an information processing system comprising: a generation unit that generates content connectors corresponding to content selected or entered by a user; and a display control unit that displays the content on a user terminal in response to the user operating the connector.

[0007] Furthermore, the present invention relates to an information processing method performed by a computer used in an information processing system, wherein a generation unit generates content connectors corresponding to content selected or input by a user, and a display control unit displays the content on a user terminal in response to the user operating the connectors.

[0008] Furthermore, the present invention is a program for operating a computer as the information processing system described above, and is a program for causing the computer to function as each part of the information processing system.

[0009] According to the present invention, the content of a question can be clarified. Alternatively, it is possible to provide an accurate and unambiguous answer to a question, and an answer that is easy to visually confirm.

[0010] This is a block diagram showing an example configuration of the customer support system 1 according to the embodiment. This is a block diagram showing an example configuration of the information processing device 10 according to the embodiment. This is a diagram illustrating the flow experienced by a user in the customer support system 1 according to the embodiment. This is a sequence diagram showing the flow of processing performed by the customer support system 1 according to the embodiment. This is a diagram showing an example of the UI displayed on the user terminal 20 according to the embodiment. This is a diagram showing an example of the UI displayed on the user terminal 20 according to the embodiment.

[0011] The embodiments of the invention will be described below with reference to the drawings. In the following description, an example will be given of a case where a company receives questions from its customers and provides video content that answers those questions. The embodiments can be applied to various tasks such as customer support, call center support, customer service, and sales where video content is used. In addition, the following description will be an example of a case where video content is provided, but the invention is not limited to this. In this embodiment, content may be provided consisting of any or a combination thereof of text content such as text, image content such as still images and moving images including illustrations and photographs, and sound content such as music, voice, and electronic sounds.

[0012] (Regarding Customer Support System 1) Figure 1 is a block diagram showing an example configuration of Customer Support System 1 according to an embodiment. Customer Support System 1 includes, for example, an information processing device 10, a user terminal 20, a corporate server 30, a large-scale language model 40, a vector DB 50, and a content DB 60. Note that Customer Support System 1 may be configured to include multiple user terminals 20. Also, the functions of the information processing device 10 in the example of Figure 1 may be realized by multiple information processing devices.

[0013] The information processing device 10 is a computer managed by a business operator that has received a customer support request from a company. The information processing device 10 can be, for example, a server or a PC (Personal Computer). The information processing device 10 is connected to the user terminal 20, the company server 30, and the large-scale language model 40 via a communication network NW. The communication network NW includes, for example, some or all of the following: the internet, a WAN (Wide Area Network), a LAN (Local Area Network), provider equipment, a wireless base station, or a dedicated line.

[0014] Furthermore, the information processing device 10 is connected to the vector DB 50 and content DB 60 via wired or wireless communication, without using a communication network NW. By connecting the vector DB 50 and content DB 60 to the information processing device 10 without using a communication network NW, it is possible to suppress the leakage of information stored in the vector DB 50 and content DB 60 to the outside. Highly accurate answers can be generated by using confidential information within a limited scope, such as within the company's own system. However, if confidentiality of the information stored in the vector DB 50 and content DB 60 is not required, the information processing device 10 may be connected to the vector DB 50 and content DB 60 via a communication network NW.

[0015] The user terminal 20 is a computer operated by the user. The user terminal 20 can be a smartphone, tablet, PC, mobile phone, touchpad, wearable device, etc. The user terminal 20 communicates with the corporate server 30 and the information processing device 10 via a communication network NW.

[0016] The corporate server 30 is a computer managed by a company. The corporate server 30 can be a server, a PC, or the like. The corporate server 30 communicates with the user terminal 20 and the information processing device 10 via a communication network NW.

[0017] The large-scale language model 40 is a language model specialized for natural language processing (NLP) and is a type of so-called generative AI (Artificial Intelligence). When an instruction sentence called a prompt is input to the large-scale language model 40, it outputs a sentence generated based on that instruction. As the large-scale language model 40, an LLM (Large Language Model) can be used, for example, Claude® 3.5 sonnet, GPT-4®, Llama2, PaLM2, etc. can be used. However, the large-scale language model 40 does not have to be an LLM; any model capable of performing natural language processing tasks is acceptable, and small-scale language models or multimodal language models that can handle images and other formats can be applied. Furthermore, in this embodiment, the large-scale language model 40 is configured as a server that aggregates data from terminal devices such as user terminals 20 and performs natural language processing on the aggregated data, but it is not limited to this configuration. For example, an LLM may be provided on a terminal device such as a user terminal 20, and natural language processing may be performed using the LLM provided on the terminal device.

[0018] Content DB60 is a database that stores information related to video content prepared in advance as answers to questions. The video content stored in Content DB60 includes, for example, video content related to technical support, troubleshooting, manuals, frequently asked questions, or answers to anticipated questions that users are expected to ask.

[0019] All or part of these video contents may be generated by so-called generative AI. For example, by notifying the generative AI with a hypothetical question as a prompt, the generative AI can generate an answer to that hypothetical question, and a solution video based on the answer generated by the generative AI can be created. The generative AI here may be the large-scale language model 40 or a different model. When the generative AI is made to generate an answer, so-called hallucination may occur, where the generated answer contains errors, logical inconsistencies, or information that is not factual. From the viewpoint of suppressing such hallucination, it is desirable for a person in charge (human) to perform a quality check in advance to confirm the output generated by the generative AI. In this case, only video content that has been confirmed not to contain hallucination after the quality check by the person in charge (human) is stored in the content DB 60 as video content to be notified to the user.

[0020] The video content stored in the content DB 60 may be personalized videos. Personalized videos are video content that is structured to be original for each viewer, such as displaying and explaining the viewer's name, contract status, etc. For example, when the information processing device 10 delivers content to the user terminal 20, the user's personal information held by the company is notified to the user terminal 20 from the company server 30 or the like. This allows the personalized video to be displayed on the user terminal 20 even if the information processing device 10 does not hold the user's personal information.

[0021] Furthermore, the video content stored in the content DB60 may be interactive videos. An interactive video is a video that has input fields for selecting options, and is configured so that the video to be played is selected based on the options entered in those input fields.

[0022] The video content stored in the content database 60 may include narration that explains the content's content. Furthermore, the content stored in the content database 60 may also include subtitles or explanatory text.

[0023] Vector DB 50 is a database that stores vector data referenced when searching for video content stored in Content DB 60. For example, Vector DB 50 can be generated by applying a technique called RAG (Retrieval-Augmented Generation), which generates responses by referencing external information when generating responses in a large-scale language model 40. Vector data is data in which the information stored in Content DB 60 has been vectorized. Vector data is multidimensional data in which the words and sentences contained in the content are converted into numerical values ​​based on the feature quantities of each dimension, corresponding to the meaning and relationships of each dimension.

[0024] For example, the information processing device 10 generates a summary text using a generation AI or the like, which is a summary of all or part of the text corresponding to the narration, etc., contained in the content stored in the content DB 60.

[0025] For example, the following summary can be generated: • How to download app A on iPhone® • Steps to use the App Store® • Points to note when downloading apps

[0026] When such text is vectorized, it becomes high-dimensional vector data in which numerical values ​​corresponding to feature quantities in each dimension are listed, such as (1.0546875, 0.318359375, 0.2578125, -0.0534667969, ...). Vector DB50 stores such high-dimensional vector data. When two texts are related, the vector data generated from them is mapped to be close to each other in the vector space. Therefore, related texts or texts with similar meanings can be clustered in the vector space. Vector DB50 can be used to search for texts that correspond to vector data mapped to be close to the vectorized data of the target text, as texts related to the search target.

[0027] (About the Information Processing Device 10) Here, the information processing device 10 will be described using Figure 2. Figure 2 is a block diagram showing an example configuration of the information processing device 10 according to the embodiment. The information processing device 10 comprises a communication unit 11, a storage unit 12, a display control unit 13, a response control unit 14, and a generation unit 15.

[0028] The communication unit 11 communicates with the enterprise server 30 and the large-scale language model 40 via the communication network NW. The communication unit 11 also communicates with the vector DB 50 and the content DB 60 via wired or wireless connections.

[0029] The storage unit 12 is an HDD (Hard Disk Drive), flash memory, RAM (Random Access Memory), etc. The storage unit 12 stores programs that are executed by the functional units (display control unit 13, response control unit 14, and generation unit 15) of the information processing device 10 in order to perform their functions, as well as data used when the programs are executed.

[0030] The display control unit 13 controls the image to be displayed on the user terminal 20. For example, in response to an operation performed on the user terminal 20 to access customer support, the display control unit 13 displays a screen for providing customer support on the user terminal 20.

[0031] A screen for providing customer support is, for example, an interactive chat screen. By providing an interactive chat screen as a screen for providing customer support, if an unclear question is entered, it becomes easy to notify the user of additional questions to clarify the question and to obtain answers to those additional questions. Therefore, even if an unclear question is entered, the content of the question can be clarified. An interactive chat screen is an example of an "interactive send / receive form."

[0032] Furthermore, customer support is not limited to being conducted through an interactive chat screen. In customer support system 1, multiple methods (multi-channel) can be applied as ways for users to ask questions. For example, customer support may be provided through inquiries made by telephone to a customer support center established by the company. Alternatively, customer support may be provided by notifying the company of questions entered into an inquiry form on the company's website, or by sending question emails to an inquiry email address.

[0033] The response control unit 14 generates answers to user questions. The response control unit 14 generates answers by extracting content videos that answer user questions from the content DB 60. The specific method by which the response control unit 14 generates answers will be explained in detail later.

[0034] The generation unit 15 generates a connector corresponding to the answer. Here, a connector is information that allows the user to obtain the answer. The connector is, for example, a URL (Uniform Resource Locator) that indicates the location where the video content corresponding to the answer is stored. Alternatively, the connector may be identification information that identifies the video content corresponding to the answer.

[0035] The generation unit 15 generates connectors according to the form of customer support. For example, customer support may be provided via an interactive chat screen. In this case, the generation unit 15 generates a URL (a URL indicating the location where the video content corresponding to the answer is stored) as a connector. By generating a URL as a connector, the location of the video content corresponding to the answer can be notified via the customer support chat.

[0036] Alternatively, customer support may be provided through a webpage used by a company to manage customer contract status and change procedures, such as a My Page. Some such My Pages have a pre-embedded video player, and various services are provided when a video is played on that video player. In this case, the generation unit 15 generates identification information for video content that corresponds to the answer and is playable on the video player, as a connector. By generating identification information for video content playable on the video player as a connector, the video content corresponding to the answer can be played on the My Page video player.

[0037] Here, we will explain the processing flow of the customer support system 1 from the user's perspective using Figure 3. Figure 3 is a diagram illustrating the flow experienced by the user in the customer support system 1 according to this embodiment.

[0038] Step S1: User inquiry is received. The user accesses the inquiry reception and enters their inquiry. The inquiry reception is a form on a chat screen set up for customer support, or a customer support inquiry form provided on a web page, etc. For example, the user enters the question "I can't find app A" into the form by voice or text. The user's inquiry is received when the question entered by the user into the form is notified to the customer support system 1.

[0039] Step S2: User inquiries are handled via the UI (User Interface). The UI is an interface for providing users with answers to their questions. If a chat screen for customer support is provided, that chat screen corresponds to the UI. Alternatively, if a user's question is received through a customer support inquiry form on a web page, the email address or phone number entered by the user as contact information corresponds to the UI. For example, in customer support system 1, in response to a user's question, "I can't find app A," additional questions such as "Is your smartphone an iPhone® or an Android®?" and "Please tell us specifically how you 'can't find' app A. For example, you can't find the icon for app A, or app A doesn't respond when you try to open it, etc." are handled via the UI.

[0040] Step S3: A search of the DB (Content DB 60) is performed. In the customer support system 1, the DB is searched according to the user's issue identified through the interaction shown in step S2 above. For example, through multiple (in this case, two) additional questions asked in step S2 above, the user's issue is identified, and the issue of the question "I can't find app A" notified by the user is identified as "I installed app A on my OS-A (e.g., Android®) smartphone, but I don't know where the icon is." The DB is searched according to the user's issue identified in this way.

[0041] Step S4: Question and answer matching takes place. In customer support system 1, video content (solution content) that resolves the question notified by the user is extracted by searching the database in step S3 described above. If no video content corresponding to the answer is found as a result of searching the database, the system may switch to human support by linking with a call center or inquiry form.

[0042] Step S5: Present a solution video (video content that solves the question notified by the user) to the user. In the customer support system 1, the content extracted in step S4 described above is transmitted to the user terminal 20 as a solution video. In the DB (content DB 60), only content videos whose quality has been pre-checked by a person in charge (human) from the viewpoint of suppressing hallucination are registered. Therefore, it is possible to present solution content produced and confirmed by a person in charge (human) to the user. Note that an interactive video may be provided as the solution video presented to the user. By providing an interactive video, only an appropriate video as an answer to the user's question can be played.

[0043] Here, the processing flow performed by the customer support system 1 will be described using FIGS. 4 and 5. FIGS. 4 and 5 are sequence diagrams showing the processing flow performed by the customer support system 1 according to the embodiment. Here, using FIGS. 4 and 5, mainly, a specific method for the answer control unit 14 to generate an answer will be described. In generating an answer, the answer control unit 14 performs a problem estimation process for clarifying the question and a matching process for extracting content videos that match the question. The processes shown in steps S105 to S112 in FIG. 4 correspond to the problem estimation process. The processes shown in steps S113 to S116 in FIG. 5 correspond to the matching process.

[0044] Step S101: The user terminal 20 accesses a website or a page for performing customer support. In response to the user's operation of accessing a website or a page for performing customer support, the user terminal 20 transmits a notification indicating that the operation has been performed to the enterprise server 30.

[0045] Step S102: In response to the access from the user terminal 20 to a page for performing a website or customer support, the enterprise server 30 transmits an interface display request to the information processing device 10. The interface display request is a notification requesting to display an interface for receiving questions in the customer support on the user terminal 20. This interface is, for example, an interactive chat screen or a customer support inquiry form. The enterprise server 30 notifies the information processing device 10 that the user has accessed a page for performing a website or customer support, and requests to display an interface for receiving questions in the customer support on the user terminal 20.

[0046] Step S103: In response to the request from the enterprise server 30, the display control unit 13 of the information processing device 10 causes the user terminal 20 to display an interface, for example, an interactive chat screen or a customer support inquiry form.

[0047] Step S104: The user inputs a question in voice or text into the interface displayed on the user terminal 20, for example, an interactive chat screen or a customer support inquiry form. In response to an operation indicating that a question has been sent from the user, the user terminal 20 transmits the question input by the user to the information processing device 10.

[0048] Step S105: The response control unit 14 of the information processing device 10 transmits a text analysis request to the large language model 40. The text analysis request is a notification requesting to generate a more specific question based on the natural language indicating the question notified from the user. The response control unit 14 outputs the text sentence of the question notified from the user to the large language model 40, and requests the large language model 40 to generate a more specific question from the question notified from the user.

[0049] Here, when the response control unit 14 receives an inquiry from a user via telephone or other means, it converts the received voice into text (natural language) by speech recognition and notifies the large-scale language model 40 of the textualized question. Even when a question is received via voice, by converting the voice into text, it becomes possible to request the large-scale language model 40, which handles natural language, to generate a more specific question.

[0050] First, the response control unit 14 notifies the large-scale language model 40 of the text of the question (first text) notified by the user, and causes it to generate a second text from the notified first text. The second text is a search text for obtaining similarity with the vector DB 50, and is a formatted text that summarizes the content of the first text, corrects inaccurate expressions and typos in the first text as needed, and removes words irrelevant to the search. Next, the response control unit 14 converts the second text into vector data, and extracts data from the vector DB 50 that has a similarity to the vector data of the second text above a threshold, as vector data of text similar to the second text (third text). Then, the response control unit 14 notifies the large-scale language model 40 of the text (third text) corresponding to the vector data extracted from the vector DB 50, and causes it to generate a more specific question.

[0051] Step S106: The response control unit 14 obtains the analysis results from the large-scale language model 40. The analysis results are the results of the analysis corresponding to the text analysis request in step S105, and are more specific questions generated based on the questions notified by the user. The large-scale language model 40 generates more specific questions in response to prompts notified by the information processing device 10. For example, the large-scale language model 40 generates questions that make the question "I can't find app A" more specific, such as "The icon for app A is not displayed on the smartphone screen" and "The chat history for app A is not displayed." The large-scale language model 40 sends the generated products (more specific questions) to the information processing device 10. The response control unit 14 of the information processing device 10 obtains the generated products (more specific questions) generated by the large-scale language model 40 as analysis results.

[0052] Step S107: The response control unit 14 searches for relevant information from the vector DB 50. Relevant information is information related to the product (more specific question) generated by the large-scale language model 40. The response control unit 14 searches the vector DB 50 using the product (more specific question) obtained from the large-scale language model 40 and the conversation history as input. The conversation history here is the history of conversations exchanged between the user and customer support. For example, the conversation history is the history of chats conducted via an interactive chat screen related to customer support. The response control unit 14 searches all the data stored in the vector data stored in the vector DB 50 and extracts vector data as relevant information whose similarity to the vectorized data of the input string (string corresponding to the more specific question and conversation history) is above a threshold.

[0053] Step S108: The response control unit 14 obtains vector data retrieved from the vector DB 50 as search results for related information. The response control unit 14 obtains content corresponding to strings such as "How to use App A", "How to use App A on devices other than smartphones", and "How to download App A on iPhone (registered trademark)" as search results.

[0054] Step S109: The response control unit 14 sends an additional question generation request to the large-scale language model 40. An additional question generation request is a notification requesting the generation of additional questions. Additional questions are questions to clarify the content of questions asked by the user in the conversation history, and questions to identify which content video corresponding to the vector data obtained by the search is the appropriate answer for the user. The response control unit 14 makes an additional question generation request by sending the search results of the vector DB 50 to the large-scale language model 40 and requesting the large-scale language model 40 to generate additional questions based on the search results. Here, the response control unit 14 may also notify the large-scale language model 40 of the conversation history and a summary of the conversation history along with the search results of the vector DB 50 and request the generation of additional questions. Alternatively, instead of the conversation history and a summary of the conversation history, other attribute information or information selected by the user in the video may be notified to the large-scale language model 40 along with the search results of the vector DB 50. For example, the response control unit 14 retrieved answer A, answer B, and answer C as candidate answers to the question "I can't find app A". The large-scale language model 40 is notified with a prompt such as, "Generate an additional question that will allow the user to determine which of these answer candidates is the appropriate answer," and is requested to generate an additional question.

[0055] Step S110: The response control unit 14 receives additional questions generated by the large-scale language model 40. The large-scale language model 40 generates additional questions in response to prompts notified by the response control unit 14 of the information processing device 10 and sends the generated additional questions back to the information processing device 10. For example, the large-scale language model 40 generates additional questions to better understand the question "I can't find app A": "Is your smartphone an iPhone® or an Android®?" and "Please tell us specifically how you 'can't find' app A. For example, you can't find the icon for app A, or app A doesn't respond when you try to open it." The large-scale language model 40 sends the generated products (additional questions) to the information processing device 10. The response control unit 14 receives the generated products (additional questions) generated by the large-scale language model 40.

[0056] Step S111: The response control unit 14 asks additional questions to the user terminal 20. The response control unit 14 sends the generated product (additional questions) obtained from the large-scale language model 40 to the user terminal 20 and asks additional questions. The response control unit 14 asks additional questions in a format that continues the conversation that has been exchanged with the user so far in customer support, for example, by sending the additional questions to the user terminal 20 via an interactive chat related to customer support.

[0057] Step S112: The response control unit 14 obtains answers to additional questions from the user terminal 20. The user terminal 20 displays the additional questions notified by the information processing device 10, "Is your smartphone an iPhone® or an Android®?" and "Please tell us specifically how you cannot find app A. For example, you cannot find the icon for app A, or app A does not respond when you try to open it, etc." on the chat screen related to customer support. The user views the additional questions displayed on the chat screen of the user terminal 20 and enters answers to the additional questions into the chat screen. For example, the user enters an answer such as "It's an Android®. I can't find the icon for app A," into the chat screen and taps the send button. In response to the tap of the send button, the user terminal 20 sends the information entered by the user (answers to the additional questions) to the information processing device 10. When the information processing device 10 receives information (answers to additional questions) from the user terminal 20, the answer control unit 14 obtains the answers to the additional questions.

[0058] Step S113: As shown in Figure 5, the response control unit 14 searches for content that solves the problem (video content that solves the question notified by the user). Based on the answers to the additional questions, the response control unit 14 identifies the problem of the question notified by the user. For example, suppose the additional questions are, "Is your smartphone an iPhone® or an Android®?" and "Please tell us specifically how you 'cannot find' app A. For example, you can't find the icon for app A, or app A doesn't respond when you try to open it." and the response is, "It's an Android®. I can't find the icon for app A." In this case, the response control unit 14 identifies the problem of the question "I can't find app A" notified by the user as "I installed app A on my Android® smartphone, but I don't know where the icon is." Based on the identified problem, the response control unit 14 searches the vector DB 50 and searches for information related to the identified problem. The response control unit 14 searches all the data stored in the vector DB 50, and extracts vector data whose similarity to the vectorized string representing the problem is above a threshold as information related to the problem.

[0059] Step S114: The answer control unit 14 obtains a content ID corresponding to the vector data retrieved from the vector DB 50. The content ID is identification information that identifies the content. In steps S115 to S116, described later, the content corresponding to the solution video is retrieved from the content DB 60, and the retrieved solution video content is transmitted to the user terminal 20 in step S117. For this reason, in this step, the content ID corresponding to the vector data retrieved from the vector DB 50 in step S113 is obtained as identification information for information related to the problem. Furthermore, since providing the user with multiple content videos as solution videos makes it easier for the user to obtain an answer that matches their question, it is desirable for the answer control unit 14 to obtain multiple (one or more) content IDs in this step.

[0060] Step S115: The response control unit 14 refers to the content DB 60 and requests the content DB 60 to send the content corresponding to the content ID obtained in step S114.

[0061] Step S116: In response to the request from the response control unit 14 notified in step S114, the content DB 60 transmits the content corresponding to the content ID notified by the response control unit 14 to the information processing device 10.

[0062] Step S117: The information processing device 10 transmits content to the user terminal 20. The communication unit 11 of the information processing device 10 acquires the content transmitted from the content DB 60 in step S116. The generation unit 15 of the information processing device 10 generates a connector for the content transmitted from the content DB 60. The display control unit 13 of the information processing device 10 displays the connector for the content corresponding to the solution video on the chat screen of the user terminal 20. As a result, the information processing device 10 transmits the content corresponding to the solution video to the user terminal 20.

[0063] Step S118: The user views the content. The user taps the connector (the connector for the content corresponding to the solution video) displayed on the chat screen of the user terminal 20. In response to the user's tap, the user terminal 20 transmits to the information processing device 10 that an operation to play the content corresponding to the solution video has been performed. The communication unit 11 of the information processing device 10 receives information from the user terminal 20 (information that an operation to play the content corresponding to the solution video has been performed). The display control unit 13 of the information processing device 10 displays the solution video (an example of content) on the user terminal 20 based on the information received by the communication unit 11. As a result, the content corresponding to the solution video is played on the user terminal 20. The user views the content.

[0064] Step S119: The information processing device 10 requests feedback from the user terminal 20. Feedback here refers to areas for improvement and evaluations of customer support. For example, the display control unit 13 of the information processing device 10 displays phrases such as "Has the problem been resolved?" along with options such as "Resolved," "Resolved but not satisfactory," and "Not resolved" on the chat screen of the user terminal 20. This allows the information processing device 10 to request feedback from the user terminal 20. Here, the information processing device 10 may also notify the user terminal 20 of an interactive video or an interactive image as the feedback it requests. An interactive video is an interactive video in which feedback options are displayed, and user feedback is obtained when the user performs an operation (e.g., touch operation) to select one of the displayed options. An interactive image is an image in which feedback options are displayed, and user feedback is obtained when the user performs an operation (e.g., touch operation) to select one of the displayed options.

[0065] Step S120: The user terminal 20 sends feedback to the information processing device 10. The user performs an operation to select an option displayed on the chat screen of the user terminal 20 and performs an operation to send feedback. In response to the selection of an option and the sending operation, the user terminal 20 sends the option selected by the user to the information processing device 10. In this way, the user terminal 20 sends feedback to the information processing device 10. If a touchable video or touchable image is notified as feedback, the user terminal 20 sends the option selected by the user to the information processing device 10 in response to the selection of an option in the touchable video or touchable image.

[0066] If the user is notified of options indicating dissatisfaction with customer support, such as "resolved but not satisfactory" or "not resolved," the information processing device 10 may request more specific feedback from the user terminal 20. More specific feedback could include, for example, displaying a message on the chat screen such as "Please describe specifically how the issue was not resolved." This allows the information processing device 10 to request more specific feedback from the user terminal 20. The information processing device 10 may also request more specific feedback using video or audio.

[0067] Step S121: The information processing device 10 refers to the vector DB 50 based on the information fed back from the user terminal 20. The communication unit 11 of the information processing device 10 receives information indicating the options sent from the user terminal 20 in step S120. If the options sent from the user terminal 20 indicate that the user is not satisfied with customer support, the display control unit 13 of the information processing device 10 causes the user terminal 20 to display wording requesting more specific feedback. The user sees the wording displayed on the user terminal 20 (wording requesting specific feedback) and, in response to this wording, inputs wording that specifically explains the perspective from which the user is asking the question. In response to the input of the specific explanation and the transmission operation being performed, the user terminal 20 transmits to the information processing device 10 wording that specifically explains what aspects the user is dissatisfied with. The communication unit 11 of the information processing device 10 receives information indicating the wording sent from the user terminal 20 (wording that specifically explains the perspective from which the user is asking the question). The information processing device 10 refers to the vector DB 50 based on the wording (wording that specifically describes the perspective from which the user is asking the question) that is fed back from the user terminal 20. The answer control unit 14 searches all the vector data stored in the vector DB 50 and extracts vector data whose similarity to the vectorized data of the input wording (wording that specifically describes the perspective from which the user is asking the question) is above a threshold. Alternatively, in this step, the information processing device 10 may generate search feedback via the large-scale language model 40 from the feedback notified from the user terminal 20, and then search the vector DB 50 using the search feedback. In this case, the answer control unit 14 notifies the large-scale language model 40 of the feedback (first feedback) notified from the user terminal 20, and causes it to generate second feedback from the notified first feedback. The second feedback is a search text sentence for obtaining similarity with the vector DB 50, and is a formatted text sentence that corrects inaccurate expressions and typographical errors contained in the first feedback and deletes words that are irrelevant to the search.The response control unit 14 then converts the second feedback into vector data and extracts data from the vector DB 50 whose similarity to the vector data of the second feedback is above a threshold as vector data of text (third feedback) related to the second feedback.

[0068] Step S122: The information processing device 10 displays hints for creating new content. The information processing device 10 obtains a content ID corresponding to the vector data retrieved from the vector DB 50 in step S121. The information processing device 10 displays the text feedbacked from the user terminal 20 (text that specifically explains the perspective from which the question is being asked), the content ID corresponding to the vector data retrieved from the vector DB 50 based on that text, and the summary text corresponding to the content ID. This allows the user's question to be displayed in association with the content ID and summary text of the content related to that question. This makes it easy to verify whether the user's problem was correctly identified through additional questions, and whether an appropriate solution video for solving the user's problem was selected. For example, if it is determined that the user's problem was not correctly identified through additional questions, measures can be taken to review each step of the problem estimation process, such as modifying the prompt notified to the large-scale language model 40 in step S105. Alternatively, if it is determined that the user's problem has been correctly identified but an appropriate solution video has not been selected, the matching process can be reviewed, and measures can be taken, such as pre-producing video content that corresponds to the user's problem notified in this instance. Furthermore, in this step, the system may be configured to display not only the text provided as feedback from the user terminal 20, but also the content of the question entered by the user in step S104, the answer to the additional question entered by the user in step S112, and the content ID identified from the vector DB 50 in step S114. By displaying these as targets for analysis when creating new content, it becomes possible to produce solution videos with greater accuracy.

[0069] Here, an example of a chat screen (UI) displayed on the user terminal 20 will be explained using Figures 6 and 7. Figures 6 and 7 are diagrams showing examples of the UI displayed on the user terminal 20 according to this embodiment.

[0070] Figure 6 shows the interaction related to the problem estimation process. First, the user notifies customer support with the question, "I can't find app A." In response to this question, customer support notifies the user with additional questions such as, "...we would like to ask you the following questions... Is your smartphone an OS-A device (for example, Android®) or an OS-B device (for example, iPhone®)?" In response to the additional questions, the user notifies customer support with the question, "It's an OS-A device (for example, Android®)..." In response to this answer, customer support notifies the user with a second additional question, "Could you please answer the following questions?"

[0071] In this way, multiple additional questions may be asked in the customer support system 1. For example, if the number of generated products (specific questions) in step S106 exceeds a threshold, the system may be configured to divide the generated products (specific questions) into multiple groups and ask additional questions appropriate to each group.

[0072] Figure 7 shows the interactions involved in the matching process. Once the user's problem is identified through the interactions shown in Figure 6, customer support notifies the user with their opinion, "...I understand the situation well. ...We estimate that the user's initial concern is that the icon is not being displayed." Subsequently, customer support notifies the user of solutions in text form, such as "We recommend that you try the following methods..." Furthermore, customer support states, "...We have prepared a solution video..." and the link (in this case, a URL) to the solution video content is displayed on the chat screen of the user terminal 20.

[0073] As described above, the customer support system 1 of the embodiment (an example of an information processing system) comprises a generation unit 15 and a display control unit 13. The generation unit 15 generates a connector for a solution video (an example of content) corresponding to a question from the user (an example of content selected or entered by the user). The display control unit 13 displays the solution video (an example of content) on the user terminal 20 in response to the user operating the connector. The customer support system 1 embodies the content of the question in a large-scale language model 40 (an example of a language model) in response to the input of a question from the user. The customer support system 1 searches for related information related to the analysis result in which the content of the question has been embodied in a vector DB 50 (an example of a vector database). The customer support system 1 transmits an additional question generated based on the related information retrieved from the vector DB 50 and the content of the question to the user terminal 20. As a result, the customer support system 1 of this embodiment can notify the user terminal 20 of additional questions generated using the analysis results that embody the content of the question and related information, and the content of the question can be clarified by obtaining answers to the additional questions from the user.

[0074] Furthermore, in the customer support system 1 of this embodiment, the content of the question is selected or entered into an interactive chat screen (an example of an interactive send / receive form). This allows for interactive additional questions to be asked in response to the question.

[0075] As described above, the customer support system 1 of this embodiment comprises a generation unit 15, a communication unit 11 (an example of a transmission unit), and a display control unit 13. The generation unit 15 generates a connector for a solution video (an example of content) corresponding to a question from the user (an example of content selected or entered by the user). The communication unit 11 transmits the connector to the user terminal 20. The display control unit 13 displays the solution video (an example of content) on the user terminal 20 in response to the connector being operated on the user terminal 20. The connector is a connector for content identified from related information obtained by quantifying the content of the question in a large-scale language model 40 (language model), searching for related information associated with the analysis result in which the content of the question has been quantified from the vector DB 50 (vector database). As a result, the customer support system 1 of this embodiment can identify a solution video using the analysis result in which the content of the question has been quantified and related information, and can identify a solution video that resolves the question after clarifying the content of the question.

[0076] Furthermore, in the customer support system 1 of this embodiment, the content of the question is selected or entered into an interactive chat screen (an example of an interactive sending and receiving form). This makes it possible to interactively present a video solution to the question.

[0077] As described above, the customer support system 1 of this embodiment comprises a generation unit 15 and a display control unit 13. The generation unit 15 generates connectors for solution videos (examples of image or video content as answers) that correspond to the content selected or entered by the user on an interactive chat screen (an example of an interactive send / receive form). The display control unit 13 displays the solution video (examples of image or video content as answers) on the user terminal 20 in response to the user's operation of the connector. As a result, the customer support system 1 of this embodiment can use an interactive chat screen (an example of an interactive send / receive form), so if the content of the user's question is unclear, the system can interactively confirm with the user and clarify the content of the question. Because the question can be clarified before providing an answer, an accurate and error-free answer can be provided. Furthermore, since a solution video (examples of image or video content as answers) is provided as the answer, the answer can be visually easy to confirm. Therefore, it is possible to suppress ambiguous answers to questions.

[0078] The customer support system 1 or information processing device 10 in the above-described embodiment may be implemented in whole or in part using a computer. In that case, the program for implementing this function may be recorded on a computer-readable recording medium, and the program recorded on this recording medium may be loaded into the computer system and executed. Here, "computer system" includes hardware such as the OS and peripheral devices. Furthermore, "computer-readable recording medium" refers to portable media such as flexible disks, magneto-optical disks, ROMs, CD-ROMs, and storage devices such as hard disks built into the computer system. Moreover, "computer-readable recording medium" may also include those that dynamically hold programs for a short period of time, such as communication lines used when transmitting programs via networks such as the Internet or communication lines such as telephone lines, and those that hold programs for a certain period of time, such as volatile memory inside the computer system that acts as a server or client in that case. Furthermore, the above-mentioned program may be for implementing a part of the above-mentioned function, or it may be a program that can implement the above-mentioned function in combination with a program already recorded in the computer system, or it may be implemented using a programmable logic device such as an FPGA.

[0079] Although embodiments of this invention have been described in detail above with reference to the drawings, the specific configuration is not limited to these embodiments and includes designs and the like that do not depart from the spirit of this invention.

[0080] 1...Customer support system (information processing system) 10...Information processing device 11...Communication unit 12...Storage unit 13...Display control unit 14...Response control unit 15...Generation unit 20...User terminal 30...Corporate server 40...Large-scale language model 50...Vector DB 60...Content DB

Claims

1. An information processing system comprising: a generation unit that generates content connectors corresponding to content selected or entered by a user; and a display control unit that displays the content on a user terminal in response to the user operating the connector.

2. The information processing system according to claim 1, which obtains the content to be displayed on the user terminal by searching a vector database in which the content has been vectorized, based on related information relating to the analysis results obtained by concretizing the content using a language model.

3. The information processing system according to claim 1, wherein the generation unit generates connectors for image or video content that serve as responses corresponding to the content selected or entered by the user in an interactive transmission / reception form, and the display control unit displays the image or video content on the user terminal in response to the user operating the connector.

4. The information processing system according to claim 2, wherein, in response to the user selecting or inputting the content, the system embodies the content in a language model, retrieves related information from a vector database that relates to the analysis result in which the content has been embodied, and transmits additional questions generated based on the related information and the content to the user terminal.

5. The information processing system according to claim 2, wherein the connector is the connector of the content identified from the content, which is used to embody the content in a language model, retrieves related information from a vector database that is associated with the analysis result in which the content has been embodyed, and which is the connector of the content identified from the related information.

6. The information processing system according to claim 4 or claim 5, wherein the contents are selected or entered into an interactive transmission / reception form.

7. An information processing method performed by a computer used in an information processing system, wherein a generation unit generates content connectors corresponding to content selected or entered by a user, and a display control unit displays the content on a user terminal in response to the user operating the connectors.

8. A program for operating a computer as an information processing system as described in claim 1, the program for causing the computer to function as a component of the information processing system.

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