system

Abstract

We provide the system. [Solution] A means for users to input their desired reservation conditions, An analysis means that automatically analyzes multiple reservation targets based on the desired conditions received from the information input means, A reservation execution means that automatically executes the reservation process based on the results of the analysis performed by the aforementioned analysis means, A notification method to determine whether the reservation process was successful or not and notify the user, If the aforementioned reservation process is unsuccessful, a means for presenting options to the user to offer alternative reservation candidates, A specialized tool for managing and automating the booking of security-related events and programs, A system that includes this.

Description

Technical Field

[0001] The technology of the present disclosure relates to a system.

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 in 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] It is intended to solve the problem that people need to keep manually accessing many times when making reservations for popular events or restaurants. Such reservation activities take a great deal of time and effort, and it is particularly difficult to respond without missing the moment when a vacancy occurs, especially when waiting for cancellations. As a result, whether a reservation can be made is uncertain, which burdens the user.

Means for Solving the Problems

[0005] This invention provides an information input means for users to input their desired reservation conditions, thereby enabling the system to communicate the user's preferences. Furthermore, it includes an analysis means for automatically analyzing multiple reservation targets based on that information, and a reservation execution means for automatically executing the reservation process based on the analysis. This enables the rapid and effective acquisition of reservations. In addition, it includes a notification means for determining and notifying the user of the success or failure of a reservation, and a choice presentation means for providing alternative candidates if the reservation is unsuccessful, thereby expanding the user's options and creating a system that supports the securing of reservations to the greatest extent possible.

[0006] A "user" is an individual or group that uses the system to make a desired reservation.

[0007] "Information input means" refers to a function or interface that allows a user to input their desired reservation conditions into the system.

[0008] The "analysis means" is a component that has the function of automatically analyzing the reservation target based on the user's desired conditions received through the information input means.

[0009] A "reservation execution means" is a component equipped with the function to automatically perform reservation processing based on the results of analysis.

[0010] "Notification means" refers to a function or interface for notifying the user of the success or failure of a reservation and its outcome.

[0011] A "means of presenting options" is a component that generates alternative options and suggests them to the user if the desired reservation cannot be obtained.

[0012] A "system" is a computer program that integrates multiple functions, handling everything from information input and reservation acquisition to notifications and presentation of options. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0014] An example of an embodiment of the system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, the labeled 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), and the like.

[0017] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0019] 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).

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] 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).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises 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.

[0026] 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.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, a 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 "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.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 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 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This system automates the process of booking events and joining waiting lists for restaurants. Users first input their desired booking criteria into the system via a terminal. These criteria include information such as the destination, desired date and time, and type of event.

[0035] Once information is entered into the terminal, the terminal sends that data to the server. The server analyzes this data and prepares the necessary steps to execute the reservation. In this process, the server automatically searches for available reservation options and selects the one that best suits the criteria.

[0036] The server accesses the reservation site at the specified date and time and automatically checks whether a reservation is available based on the conditions set by the user. Furthermore, in the case of a waiting list, the system is configured to repeatedly check at specific intervals until a reservation becomes available.

[0037] If the reservation is successful, the server notifies the terminal, and the terminal displays the result to the user. If the reservation is unsuccessful, the server generates other suitable options and presents them to the user via the terminal.

[0038] A concrete example is booking tickets for the Japan Series. When a user enters the game date, time, and desired seat into the system, the server attempts to access the tickets based on that information and determines whether the reservation will be successful. If the reservation is successful, the user is immediately notified of the result; if it is unsuccessful, the user is provided with information on similar games and seats. Similarly, in the case of restaurant reservations, if a user is on a waiting list, the server checks based on pre-registered conditions and processes the reservation as soon as a seat becomes available.

[0039] As described above, users can easily obtain their desired reservations and then efficiently take their next actions based on the results obtained.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The user accesses the reservation system on their device and logs in with their account. After logging in, they fill in the detailed reservation conditions, such as the desired event or restaurant, date and time, location, and seating type, in the input form. The device then sends the entered information to the server.

[0043] Step 2:

[0044] The server analyzes the reservation conditions received from the terminal and stores them in a database. Based on the analysis results, it prepares to identify which reservation system to access and what API keys or authentication are required.

[0045] Step 3:

[0046] The server initiates access to the target booking site or service based on stored conditions, timed to coincide with the start date and time of the booking. If the booking site provides an API, it uses the API; otherwise, it collects information through web scraping.

[0047] Step 4:

[0048] The server automatically checks the availability of the accessed destination and determines whether it matches the user's criteria. If there is a possibility of a match, it attempts to make a reservation. It also automatically registers the user to a waiting list if necessary.

[0049] Step 5:

[0050] The server determines whether the reservation is successful and sends the result to the terminal. If the reservation is confirmed, it sends the result including details; if the reservation is unsuccessful, it provides a statement to that effect and offers alternative options.

[0051] Step 6:

[0052] The device receives the results from the server and notifies the user via push notifications, etc. Information is displayed on the user interface so that the user can review the results and take additional actions as needed.

[0053] Step 7:

[0054] The user reviews the booking results and chooses whether to attempt a new booking from the other options presented or to restart the process by entering additional preferences. Once this step is complete, the terminal can send the new information to the server and restart the processing flow.

[0055] (Example 1)

[0056] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0057] Manually making reservations for desired events and restaurants is time-consuming and laborious, and securing a reservation for popular items is extremely difficult. Furthermore, even for those on waiting lists, reconfirmation is necessary. There is a need to automate these tasks appropriately and efficiently.

[0058] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0059] In this invention, the server includes information input means, analysis means, reservation execution means, automatic access means, and monitoring means. This enables the automation of reservation processing based on conditions desired by the user, and allows for the rapid and efficient notification of successful reservations and the presentation of alternative candidates.

[0060] "Information input means" refers to an interface or device used by a user to input reservation conditions, and is a means of inputting necessary information through a user interface.

[0061] "Analysis means" refers to a means for automatically analyzing multiple reservation targets based on reservation conditions entered by the user and performing processing to select the optimal reservation target.

[0062] A "reservation execution means" is a means of performing a procedure to execute a reservation based on the analyzed results and confirming the reservation.

[0063] A "notification method" is a means of informing the user of the results of the reservation process, and plays the role of transmitting information of success or failure to the terminal.

[0064] A "means for presenting options" refers to a method for generating and presenting alternative reservation options to the user if a reservation is unsuccessful.

[0065] An "automated access method" is a means of automatically accessing a web interface to check the availability of a reservation.

[0066] A "monitoring measure" is a means of continuously checking the reservation status when a reservation is on a waiting list, and automatically executing the procedure when a new reservation becomes available.

[0067] As an embodiment of this invention, a system is constructed in which a user, a terminal, and a server work together to automate reservation operations. First, the user uses a terminal to input their desired reservation conditions. These conditions include the destination, desired reservation date and time, and type of event. The terminal formats this information and sends it to the server.

[0068] The server utilizes database management systems and analysis software (e.g., MySQL® and Python libraries) to analyze the received data. This process selects the reservation candidate that best matches the user's preferences. The server also uses software (e.g., Selenium) to automatically access the web interface and check online for reservation availability at the specified date and time. To prepare for cancellations, the server has a monitoring function that periodically checks the reservation status and automatically initiates the reservation process when a reservation becomes available.

[0069] As a concrete example, consider a scenario where a user requests tickets to a certain event. The user enters their desired date, time, and seat through their device, and the server automatically accesses the booking site based on this information and attempts to make a reservation. If the reservation is successful, the server immediately notifies the device of the result, and the device displays this information to the user. If the reservation is unsuccessful, the server generates and presents alternatives to similar events and seats.

[0070] An example of a prompt message for the generating AI model might be, "Please select the highest-rated restaurants with available waitlists for the next week and begin the reservation process." This system would free users from complex reservation tasks, allowing them to secure their desired events and services more efficiently.

[0071] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0072] Step 1:

[0073] The user enters booking conditions via a terminal. These conditions include destination, desired booking date and time, and event type. This information is entered through the user interface on the terminal, where it is reviewed and formatted. As output, the terminal generates formatted booking condition data, ready to be sent to the server in the next step.

[0074] Step 2:

[0075] The terminal sends the entered reservation condition data to the server. Data communication is performed using the HTTP protocol. The input is the reservation condition data provided by the user, and the output is the terminal transferring that data to the server, making it ready for the server to receive the data.

[0076] Step 3:

[0077] The server analyzes the received data. Using databases and analysis software, it performs data matching and filtering based on reservation conditions. The input is the reservation condition data received in the previous step, and the output is a list of reservation candidates that meet the conditions. The server then prepares to use this result in the next step.

[0078] Step 4:

[0079] The server automatically accesses the web interface of the reservation site based on the analysis results. During this process, it attempts to execute online reservations using a tool like Selenium. The input is a list of reservation candidates, and the output is a check of whether the reservation is possible. In this step, if a reservation is possible, it is confirmed, and the process proceeds to the next step.

[0080] Step 5:

[0081] The server, if there is a waiting list, runs a timer and schedule management system to periodically check the reservation status. This allows it to automatically process reservations when they become available. The input is the existing reservation status, and the output generates a reservation notification when a new slot becomes available. This process uses a Python script with cron to repeatedly perform checks.

[0082] Step 6:

[0083] The server notifies the terminal of the final reservation success or failure. If the reservation is successful, a success message is sent, which the terminal displays to the user. The input is information regarding the success or failure of the reservation, and the output generates a message that is transmitted to the user. If the reservation cannot be made, the server generates an alternative and presents it to the user again.

[0084] (Application Example 1)

[0085] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0086] In recent years, there has been a growing demand for participation in security-related events and training sessions. However, these events are highly popular, making it difficult to secure reservations. Furthermore, manually searching for and booking events that match users' desired dates and conditions is time-consuming and cumbersome. Therefore, there is a need for a system that allows users to efficiently make reservations and ensure their participation.

[0087] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0088] In this invention, the server includes an information input means for a user to input desired reservation conditions, an analysis means for automatically analyzing multiple reservation targets based on the desired conditions received from the information input means, and a reservation execution means for managing reservations and executing automatic reservations. This makes it possible to process reservations for security-related events quickly and automatically.

[0089] "Information input means" refers to the interface used by users to enter reservation conditions.

[0090] The "analysis means" refers to a function that analyzes the received reservation conditions and automatically considers multiple reservation targets.

[0091] The "reservation execution means" is a function that automatically executes reservation processing based on the analyzed results.

[0092] A "notification method" is a function that determines whether a reservation was successful or unsuccessful and informs the user of the result.

[0093] A "means of presenting options" is a function that generates and provides alternative reservation options to the user if the reservation is unsuccessful.

[0094] A "security-related event" is a group gathering aimed at improving security knowledge and providing training.

[0095] "Specialized methods" refer to technologies or systems that have functions specifically tailored to a particular field or application.

[0096] To implement this invention, the system is configured as follows. This system is used by users to automate the booking of security-related events and training sessions. Users use a smartphone or other information terminal to input their desired booking conditions. This includes information such as the location, date and time, and type of event.

[0097] The device sends the user's entered conditions to the server via the internet. The server, using Python as its execution environment, scrapes web pages using the Scrapy library to analyze the data and search for events to reserve, identifying available events. The server then automatically reserves events that match the user's conditions. The success or failure of this reservation is notified to the device using Firebase Cloud Messaging. This allows the user to receive immediate notification if the reservation is successful.

[0098] As a concrete example, a user enters that they want to attend a security seminar to be held on the 15th of next month. Based on this request, the server gathers information about the relevant event and attempts to make a reservation automatically. If the reservation is successful, the user receives a notification that their reservation has been confirmed.

[0099] An example of a prompt to a generating AI model is as follows: "I would like to attend a seminar on security risk management scheduled to be held in Tokyo on the 15th of next month. Please retrieve the corresponding reservation information and complete the reservation."

[0100] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0101] Step 1:

[0102] The user enters the reservation details into their smartphone or information terminal. This information includes the location, date, and category of the event. This information forms the basis for subsequent processing.

[0103] Step 2:

[0104] The terminal sends the entered reservation conditions to the server. The server prepares to analyze the received data. The input data is filtered and formatted to a state suitable for analysis.

[0105] Step 3:

[0106] The server uses Python and the Scrapy library to scrape security-related events available on the web. The scraped event information is then used for conditional matching within the server.

[0107] Step 4:

[0108] The server compares the analyzed reservation conditions with the scraped event information to identify the event that best matches the user's criteria. It then applies a data matching algorithm to select the most suitable candidate.

[0109] Step 5:

[0110] The server attempts to make a reservation for the identified event. During this process, the reservation web form is automatically populated, and the reservation process proceeds. The status regarding the success or failure of the reservation is then checked.

[0111] Step 6:

[0112] If the reservation is successful, the server sends a notification to the device using Firebase Cloud Messaging. The notification includes a reservation confirmation message, which the user can check within the app. This allows the user to know the result in real time.

[0113] Step 7:

[0114] If a reservation is unsuccessful, the server generates an alternative and sends it to the terminal. The user is then presented with the next best option and can try making a reservation again. This process is repeated to provide the best possible reservation opportunity.

[0115] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0116] This invention relates to a reservation system that takes user emotions into consideration, thereby improving the user experience.

[0117] This system first uses an emotion engine to recognize the user's emotions when they enter reservation conditions on their terminal. The terminal senses emotions not only from the input data but also from voice and facial analysis using the camera and microphone, and transmits this information to the server in real time. The server receives this information and uses it as a basis for the analysis tools to evaluate reservation options.

[0118] The emotional data obtained by the emotion engine is compared with past emotional history to determine the priority of reservations. For example, if a user had a very satisfying experience at a certain event in the past, similar events will be suggested preferentially. Also, options that are judged to be unsatisfactory may be removed from the list.

[0119] In the reservation execution mechanism, if positive emotions are detected in the user, more desirable suggestions will be made to the user before the reservation is confirmed. Conversely, if negative emotions are detected, simpler and faster suggestions will be made.

[0120] The notification system adjusts the tone and content of messages according to the user's current emotional state. Specifically, if the user is stressed, a softer tone is used; if they are calm, the result is communicated concisely. Furthermore, if a reservation is unsuccessful, the system considers the user's emotions and proposes alternative options that reflect those emotions using a choice-presentation system.

[0121] As a concrete example, consider the process of a user attempting to book tickets for a popular music event. The system reads the user's emotions of anticipation and excitement from their facial expressions and tone of voice while they are on the booking screen, and then offers them special seats or additional related events instead of general admission seats for the event.

[0122] By using this emotion engine, we aim to provide a more personalized and empathetic service that goes beyond mere scheduling.

[0123] The following describes the processing flow.

[0124] Step 1:

[0125] The user accesses the reservation application on their device, logs in, and then enters the details of the event or restaurant they wish to reserve. During this process, the device uses its camera and microphone to collect the user's facial expressions and voice tone, and sends this information to the emotion engine.

[0126] Step 2:

[0127] The terminal analyzes the user's emotional data obtained through the emotion engine and sends reservation conditions, including this data, to the server. The emotional data includes states such as joy, anticipation, and anxiety, and influences the server's priority determination.

[0128] Step 3:

[0129] The server uses analytical tools to select the appropriate booking destination based on the received booking conditions and sentiment data. In conjunction with past booking history, it prioritizes picking out related events that evoked positive emotions in the user.

[0130] Step 4:

[0131] The server automatically attempts to make a reservation at the selected location. While determining whether the reservation will be successful, it immediately prepares the next option if it fails or if there is a waiting list.

[0132] Step 5:

[0133] To notify the user of the success or failure, the server prepares a message that takes the user's emotional state into account and sends the result to the terminal. If the user is calm, the notification will include specific details; if the user is stressed, it will convey simple and clear information.

[0134] Step 6:

[0135] The device displays the notification to the user, who then reviews the result. If necessary, the user can choose to accept an alternative that takes emotions into consideration or try again with further adjusted booking conditions.

[0136] Step 7:

[0137] If the user accepts new conditions or alternatives, the device sends that information to the server and repeats the process. The emotion engine accumulates past analysis results and evolves to suggest more accurate options for future reservations.

[0138] (Example 2)

[0139] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0140] Traditional systems struggle to provide personalized experiences when users make reservations or selections because they don't consider individual emotions or satisfaction levels. In particular, the quality of the user experience tends to decline when users are presented with options they previously found unsatisfactory, or when suggestions that meet their expectations are not offered.

[0141] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0142] In this invention, the server includes data analysis means for analyzing data, emotion recognition means for detecting user emotions, and evaluation means for performing evaluations that take emotion data into consideration. This enables the provision of optimized choices and alternatives based on user emotions, thereby improving the user experience to be more personalized.

[0143] "Data input means" refers to an interface or device for users to input their desired conditions.

[0144] "Data analysis means" refers to functions or devices that automatically analyze a target based on input conditions.

[0145] "Emotion recognition means" refers to technologies and devices used to detect a user's emotions.

[0146] "Evaluation method" refers to a mechanism or device that optimizes analysis results by taking emotional data into consideration.

[0147] "Processing execution means" refers to a function or device that automatically executes processing based on the results optimized by the evaluation means.

[0148] "Information notification means" refers to a function or device that determines whether a process was successful or not and transmits that information to the user.

[0149] An "option provision mechanism" refers to a system that generates alternative candidates and provides them to the user if the processing fails.

[0150] This invention begins with the user accessing a reservation system using a terminal and entering their desired reservation conditions. The terminal is equipped with a data input section, allowing the user to provide conditions via text or voice input. The terminal further includes an emotion recognition system that uses a camera and microphone to detect emotions. This emotion recognition system uses a generative AI model to analyze the user's facial expressions and voice characteristics in real time and extract emotion data.

[0151] Data collected through emotion recognition is transmitted from the terminal to the server. The server is equipped with a data analysis system that performs analysis based on the received emotion data and the conditions provided by the user. During this analysis, the emotion data is compared with past history and used as evaluation criteria to provide the user with the most suitable suggestions. The evaluation method sets priorities considering the user's emotional state and generates appropriate candidates.

[0152] The server further includes a reservation processing execution system that automatically makes reservations based on optimized options determined through analysis. The results of the processing are notified to the user via a terminal, and the information notification unit adjusts the tone and content according to the user's emotions. In addition, if the reservation is unsuccessful, there is an option provision system that offers alternatives that take the user's emotions into consideration.

[0153] A concrete example is when a user tries to book a music event. If the system determines that the user is very excited, it will prioritize suggesting special seats or related events rather than standard seats. This makes it possible to provide a personalized experience that meets the user's expectations.

[0154] Example of a prompt:

[0155] "What methods can be used to sense a user's excitement when booking a popular music event and generate suggestions for special seats and related events?"

[0156] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0157] Step 1:

[0158] The user accesses the reservation system using a terminal and enters their desired reservation conditions. Input formats include text and voice. For example, the user might enter, "I want to get tickets for next month's concert." At this point, the output is the user's specific request. The terminal then prepares to send this data to the data analysis system.

[0159] Step 2:

[0160] The device analyzes the user's emotions in real time using emotion recognition technology. It captures facial expressions with a camera and collects voice tone with a microphone. Input is the user's actions and speech, and output is emotion data obtained using a generative AI model. This emotion data is transmitted to a server in a quantified form.

[0161] Step 3:

[0162] The server receives conditional and sentiment data from the user using data analysis tools. The input consists of reservation conditions and sentiment data sent by the user from their terminal. The server compares this data with a database of past sentiment history and analyzes the relevance of the data using a generative AI model. The output is a prioritized list of reservation candidates based on the user's sentiment.

[0163] Step 4:

[0164] The server uses evaluation tools to optimize the analyzed list of candidates. The input is a prioritized list of reservation candidates. The server highly values ​​the user's positive emotions and lists special offers (such as premium seats) accordingly. The output is the reservation option best suited to the user.

[0165] Step 5:

[0166] The server executes the reservation process based on optimized reservation options. The input is the optimized options, and the output is the success or failure status of the reservation. If successful, reservation information is generated; if unsuccessful, alternative options are considered.

[0167] Step 6:

[0168] The terminal uses an information notification system to communicate the processing results from the server to the user. The input is the reservation success or failure status, and the output is a notification message to the user. The tone of the message is adjusted based on the user's emotional state. Specifically, if the user is stressed, the notification is in a soft tone, and if they are calm, it is concise.

[0169] Step 7:

[0170] If a reservation is unsuccessful, the server uses an option provision mechanism to generate and suggest alternative options to the user. The input is the user's emotional state and information about the failed reservation. The output is a list of alternatives, including new suggestions based on the emotional state. This makes it possible to provide a more satisfying experience for the user.

[0171] (Application Example 2)

[0172] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0173] Traditional reservation systems simply present reservation options based on user input, failing to provide a personalized experience that takes user emotions into account. This made it difficult to increase user satisfaction or present more appropriate options.

[0174] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0175] In this invention, the server includes emotion analysis means for analyzing the user's emotions, comparison means for comparing the emotion data with past emotion history, and priority determination means for determining the priority of reservation items considering the user's emotions. This makes it possible to provide a personalized reservation experience based on the user's emotions and improve user satisfaction.

[0176] "Data input means" refers to devices or mechanisms used by users to input their desired reservation conditions.

[0177] "Evaluation means" refers to a device or program for automatically evaluating multiple reservation targets based on reservation request conditions received from a data input means.

[0178] "Emotional analysis tools" refer to devices or programs used to analyze a user's emotions.

[0179] A "comparison means" is a device or mechanism that uses user emotion data obtained by emotion analysis means to compare it with past emotion history.

[0180] A "priority determination means" is a device or program for determining the priority of reservation items based on the matching results obtained by a comparison means.

[0181] "Processing execution means" refers to a device or program for automatically executing reserved processing.

[0182] An "information notification means" is a device or program that determines whether or not a reservation process was successful and notifies the user.

[0183] A "candidate suggestion means" is a device or program that, if the reservation process is unsuccessful, provides alternative reservation candidates while taking the user's feelings into consideration.

[0184] This invention provides a configuration for a reservation system that offers a personalized experience that takes into account the user's emotions. The system acquires reservation conditions via a data input device and narrows down reservation candidates using an evaluation means to evaluate them. At this time, the system analyzes the user's emotions in real time using an emotion analysis means and collects emotion data.

[0185] Emotion analysis is performed, for example, by analyzing the user's emotions from their facial expressions and voice using a camera and microphone. This emotion data is then compared with a database of past emotion history using a comparison mechanism, and the priority of reservation targets is determined by a priority determination mechanism that reflects the user's preferences and past satisfaction levels. The server then processes the data based on this priority and determines the most suitable reservation candidates for the user.

[0186] Furthermore, even if a reservation cannot be completed, a system for suggesting alternatives tailored to the user's current emotional state will present the option that will be most satisfying to the user. When notifying the user of the reservation processing results or alternative options using information notification methods, the tone of the message will also be carefully considered to reduce stress.

[0187] As a concrete example, suppose a user attempts to book a music concert by inputting voice and facial expressions via a device. In this case, the emotion analysis engine analyzes that the user is excited and suggests special seats as priority seating options. Furthermore, if the user seems to be in a mood to patiently wait even if it means being put on a waiting list, the system will take steps to help them relax.

[0188] Specific examples of prompt messages include: "Create specific suggestions on what kind of music a user should choose when they are feeling stressed," and "If a positive emotion is detected in the user, explain how to optimize the booking process to improve their satisfaction."

[0189] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0190] Step 1:

[0191] The terminal receives the user's reservation details through a data entry device. The user enters their desired reservation details on the screen, and these details are converted into data format. The information entered includes date, time, and location.

[0192] Step 2:

[0193] The device uses its camera and microphone to capture the user's facial expressions and voice data. This data is sent to an emotion analysis system, where an algorithm analyzes the user's emotions in real time. The output obtained here is data indicating the user's emotional state.

[0194] Step 3:

[0195] The server compares the emotion data received from the emotion analysis device with a database of past emotion history. Using a comparison device, it evaluates which past situations this emotion is similar to, and obtains data that reflects the user's preferences and past satisfaction patterns as output.

[0196] Step 4:

[0197] The server uses comparative data and a priority determination mechanism to determine the priority of reservation options. Priorities are assigned to the reservation candidates in order of user preference, and a final list of reservation candidates is created.

[0198] Step 5:

[0199] The server uses processing execution means to determine the highest-priority reservation candidates. If the reservation is successful, this information is notified to the user through information notification means. The output used in this process is reservation confirmation data.

[0200] Step 6:

[0201] If a reservation is not confirmed, the server uses a suggestion system to generate and present alternative options that take into account the user's current feelings. The generated alternatives are then sent back to the reservation process. Here, the user is presented with the best option.

[0202] Step 7:

[0203] The server uses prompts to generate additional suggestions for the user in the generated AI model. These prompts are used to present music, messages, and other content tailored to the user's state. The generated output is content designed to enhance the user experience.

[0204] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0205] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated 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.

[0206] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0207] [Second Embodiment]

[0208] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0209] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0210] 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).

[0211] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, 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 microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0212] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0213] Camera 42 is a small digital camera equipped with an optical system including 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, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0214] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0215] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0216] The specific processing program 56 is an example of a "program" relating 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 in accordance with the specific processing program 56 executed on the RAM 30.

[0217] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0218] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 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 60 executed on the RAM 48.

[0219] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0220] This system automates the process of booking events and joining waiting lists for restaurants. Users first input their desired booking criteria into the system via a terminal. These criteria include information such as the destination, desired date and time, and type of event.

[0221] Once information is entered into the terminal, the terminal sends that data to the server. The server analyzes this data and prepares the necessary steps to execute the reservation. In this process, the server automatically searches for available reservation options and selects the one that best suits the criteria.

[0222] The server accesses the reservation site at the specified date and time and automatically checks whether a reservation is available based on the conditions set by the user. Furthermore, in the case of a waiting list, the system is configured to repeatedly check at specific intervals until a reservation becomes available.

[0223] If the reservation is successful, the server notifies the terminal, and the terminal displays the result to the user. If the reservation is unsuccessful, the server generates other suitable options and presents them to the user via the terminal.

[0224] A concrete example is booking tickets for the Japan Series. When a user enters the game date, time, and desired seat into the system, the server attempts to access the tickets based on that information and determines whether the reservation will be successful. If the reservation is successful, the user is immediately notified of the result; if it is unsuccessful, the user is provided with information on similar games and seats. Similarly, in the case of restaurant reservations, if a user is on a waiting list, the server checks based on pre-registered conditions and processes the reservation as soon as a seat becomes available.

[0225] As described above, users can easily obtain their desired reservations and then efficiently take their next actions based on the results obtained.

[0226] The following describes the processing flow.

[0227] Step 1:

[0228] The user accesses the reservation system on their device and logs in with their account. After logging in, they fill in the detailed reservation conditions, such as the desired event or restaurant, date and time, location, and seating type, in the input form. The device then sends the entered information to the server.

[0229] Step 2:

[0230] The server analyzes the reservation conditions received from the terminal and stores them in a database. Based on the analysis results, it prepares to identify which reservation system to access and what API keys or authentication are required.

[0231] Step 3:

[0232] The server initiates access to the target booking site or service based on stored conditions, timed to coincide with the start date and time of the booking. If the booking site provides an API, it uses the API; otherwise, it collects information through web scraping.

[0233] Step 4:

[0234] The server automatically checks the availability of the accessed destination and determines whether it matches the user's criteria. If there is a possibility of a match, it attempts to make a reservation. It also automatically registers the user to a waiting list if necessary.

[0235] Step 5:

[0236] The server determines whether the reservation is successful and sends the result to the terminal. If the reservation is confirmed, it sends the result including details; if the reservation is unsuccessful, it provides a statement to that effect and offers alternative options.

[0237] Step 6:

[0238] The device receives the results from the server and notifies the user via push notifications, etc. Information is displayed on the user interface so that the user can review the results and take additional actions as needed.

[0239] Step 7:

[0240] The user reviews the booking results and chooses whether to attempt a new booking from the other options presented or to restart the process by entering additional preferences. Once this step is complete, the terminal can send the new information to the server and restart the processing flow.

[0241] (Example 1)

[0242] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0243] Manually making reservations for desired events and restaurants is time-consuming and laborious, and securing a reservation for popular items is extremely difficult. Furthermore, even for those on waiting lists, reconfirmation is necessary. There is a need to automate these tasks appropriately and efficiently.

[0244] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0245] In this invention, the server includes information input means, analysis means, reservation execution means, automatic access means, and monitoring means. This enables the automation of reservation processing based on conditions desired by the user, and allows for the rapid and efficient notification of successful reservations and the presentation of alternative candidates.

[0246] "Information input means" refers to an interface or device used by a user to input reservation conditions, and is a means of inputting necessary information through a user interface.

[0247] "Analysis means" refers to a means for automatically analyzing multiple reservation targets based on reservation conditions entered by the user and performing processing to select the optimal reservation target.

[0248] A "reservation execution means" is a means of performing a procedure to execute a reservation based on the analyzed results and confirming the reservation.

[0249] A "notification method" is a means of informing the user of the results of the reservation process, and plays the role of transmitting information of success or failure to the terminal.

[0250] A "means for presenting options" refers to a method for generating and presenting alternative reservation options to the user if a reservation is unsuccessful.

[0251] An "automated access method" is a means of automatically accessing a web interface to check the availability of a reservation.

[0252] A "monitoring measure" is a means of continuously checking the reservation status when a reservation is on a waiting list, and automatically executing the procedure when a new reservation becomes available.

[0253] As an embodiment of this invention, a system is constructed in which a user, a terminal, and a server work together to automate reservation operations. First, the user uses a terminal to input their desired reservation conditions. These conditions include the destination, desired reservation date and time, and type of event. The terminal formats this information and sends it to the server.

[0254] The server utilizes database management systems and analysis software (e.g., MySQL or Python libraries) to analyze the received data. This process selects the reservation candidate that best matches the user's preferences. The server also uses software (e.g., Selenium) to automatically access the web interface and check online for reservation availability at the specified date and time. To prepare for cancellations, the server has a monitoring function that periodically checks the reservation status and automatically initiates the reservation process when a reservation becomes available.

[0255] As a concrete example, consider a scenario where a user requests tickets to a certain event. The user enters their desired date, time, and seat through their device, and the server automatically accesses the booking site based on this information and attempts to make a reservation. If the reservation is successful, the server immediately notifies the device of the result, and the device displays this information to the user. If the reservation is unsuccessful, the server generates and presents alternatives to similar events and seats.

[0256] An example of a prompt message for the generating AI model might be, "Please select the highest-rated restaurants with available waitlists for the next week and begin the reservation process." This system would free users from complex reservation tasks, allowing them to secure their desired events and services more efficiently.

[0257] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0258] Step 1:

[0259] The user enters booking conditions via a terminal. These conditions include destination, desired booking date and time, and event type. This information is entered through the user interface on the terminal, where it is reviewed and formatted. As output, the terminal generates formatted booking condition data, ready to be sent to the server in the next step.

[0260] Step 2:

[0261] The terminal sends the entered reservation condition data to the server. Data communication is performed using the HTTP protocol. The input is the reservation condition data provided by the user, and the output is the terminal transferring that data to the server, making it ready for the server to receive the data.

[0262] Step 3:

[0263] The server analyzes the received data. Using databases and analysis software, it performs data matching and filtering based on reservation conditions. The input is the reservation condition data received in the previous step, and the output is a list of reservation candidates that meet the conditions. The server then prepares to use this result in the next step.

[0264] Step 4:

[0265] The server automatically accesses the web interface of the reservation site based on the analysis results. During this process, it attempts to execute online reservations using a tool like Selenium. The input is a list of reservation candidates, and the output is a check of whether the reservation is possible. In this step, if a reservation is possible, it is confirmed, and the process proceeds to the next step.

[0266] Step 5:

[0267] The server, if there is a waiting list, runs a timer and schedule management system to periodically check the reservation status. This allows it to automatically process reservations when they become available. The input is the existing reservation status, and the output generates a reservation notification when a new slot becomes available. This process uses a Python script with cron to repeatedly perform checks.

[0268] Step 6:

[0269] The server notifies the terminal of the final reservation success or failure. If the reservation is successful, a success message is sent, which the terminal displays to the user. The input is information regarding the success or failure of the reservation, and the output generates a message that is transmitted to the user. If the reservation cannot be made, the server generates an alternative and presents it to the user again.

[0270] (Application Example 1)

[0271] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0272] In recent years, there has been a growing demand for participation in security-related events and training sessions. However, these events are highly popular, making it difficult to secure reservations. Furthermore, manually searching for and booking events that match users' desired dates and conditions is time-consuming and cumbersome. Therefore, there is a need for a system that allows users to efficiently make reservations and ensure their participation.

[0273] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0274] In this invention, the server includes an information input means for a user to input desired reservation conditions, an analysis means for automatically analyzing multiple reservation targets based on the desired conditions received from the information input means, and a reservation execution means for managing reservations and executing automatic reservations. This makes it possible to process reservations for security-related events quickly and automatically.

[0275] "Information input means" refers to the interface used by users to enter reservation conditions.

[0276] The "analysis means" refers to a function that analyzes the received reservation conditions and automatically considers multiple reservation targets.

[0277] The "reservation execution means" is a function that automatically executes reservation processing based on the analyzed results.

[0278] A "notification method" is a function that determines whether a reservation was successful or unsuccessful and informs the user of the result.

[0279] A "means of presenting options" is a function that generates and provides alternative reservation options to the user if the reservation is unsuccessful.

[0280] "Security-related events" refer to a collective venue aimed at improving security knowledge and training.

[0281] "Specialized means" refers to technologies or systems with functions specialized for specific fields or applications.

[0282] To implement this invention, the system is configured as follows. This system is used for users to automate reservations for security-related events and training. Users use a smartphone or other information terminal to input desired reservation conditions. This includes information such as the location, date and time of the event, and the type of event.

[0283] The terminal sends the conditions input by the user to the server via the Internet. The server uses a library called Scrapy to scrape web pages and identify available events in order to analyze data and search for reservation targets using Python as the execution environment. The server further automatically executes the reservation for events that match the user's conditions. The result of judging the success or failure of this reservation is notified to the terminal using Firebase Cloud Messaging. Thus, the user can receive the notification immediately when the reservation is successful.

[0284] As a specific example, a user inputs that they want to participate in a "security seminar to be held on the 15th of next month". Based on this wish, the server collects information on related events and attempts to make a reservation automatically. If the reservation is successful, the user receives a notification that "the reservation has been confirmed".

[0285] Examples of prompt texts for the generative AI model are as follows. "I want to participate in a seminar on security risk management scheduled to be held in Tokyo on the 15th of next month. Please obtain reservation information that matches this and complete the reservation."

[0286] The flow of the specific process in Application Example 1 will be described using Figure 12.

[0287] Step 1:

[0288] The user inputs reservation conditions into a smartphone or an information terminal. The information to be input includes the location of the target event, the scheduled date, the category of the event, etc. This input information serves as the basis for subsequent processing.

[0289] Step 2:

[0290] The terminal sends the input reservation conditions to the server. The server prepares to analyze the received data. The input data is subjected to filtering and format conversion, and is formatted into a state suitable for analysis.

[0291] Step 3:

[0292] The server uses Python and the Scrapy library to scrape security-related events available on the web. As a result of the scraping, event information is obtained, which is used for matching processing based on conditions within the server.

[0293] Step 4:

[0294] The server compares the analyzed reservation conditions with the scraped event information to identify the event that best suits the user's conditions. A data matching algorithm is applied to select the optimal candidate.

[0295] Step 5:

[0296] The server attempts to make a reservation for the identified event. In this process, automatic input is performed on the reservation web form, and the reservation work is advanced. The status regarding the success or failure of the reservation is confirmed.

[0297] Step 6:

[0298] If the reservation is successful, the server sends a notification to the device using Firebase Cloud Messaging. The notification includes a reservation confirmation message, which the user can check within the app. This allows the user to know the result in real time.

[0299] Step 7:

[0300] If a reservation is unsuccessful, the server generates an alternative and sends it to the terminal. The user is then presented with the next best option and can try making a reservation again. This process is repeated to provide the best possible reservation opportunity.

[0301] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0302] This invention relates to a reservation system that takes user emotions into consideration, thereby improving the user experience.

[0303] This system first uses an emotion engine to recognize the user's emotions when they enter reservation conditions on their terminal. The terminal senses emotions not only from the input data but also from voice and facial analysis using the camera and microphone, and transmits this information to the server in real time. The server receives this information and uses it as a basis for the analysis tools to evaluate reservation options.

[0304] The emotional data obtained by the emotion engine is compared with past emotional history to determine the priority of reservations. For example, if a user had a very satisfying experience at a certain event in the past, similar events will be suggested preferentially. Also, options that are judged to be unsatisfactory may be removed from the list.

[0305] When positive emotions of the user are detected by the reservation execution means, more desirable proposals for the user are made until the reservation is finalized. Conversely, in the case of negative emotions, simpler and quicker proposals are made.

[0306] The notification means changes the tone and content of the message according to the current emotional state of the user. That is, when the user is feeling stressed, it uses a soft tone, and when the user is calm, it simply notifies the result. Furthermore, when the reservation fails, it takes into account the user's emotions and proposes an alternative that reflects them using the option presentation means.

[0307] As a specific example, consider the process of a user attempting to reserve a popular music event. The system reads emotions of anticipation and excitement from the user's facial expressions and voice tone when the user is on the reservation screen, and also provides guidance on special seats or additional related events instead of general seats for the event.

[0308] By using the emotion engine in this way, it aims to provide a user experience that goes beyond a mere scheduling task and is offered as a more personal and empathetic service.

[0309] The following explains the processing flow.

[0310] Step 1:

[0311] The user accesses the reservation application on the terminal, logs in, and then enters the detailed conditions of the event or restaurant to be reserved. The terminal utilizes the camera and microphone during this process to collect the user's facial expressions and voice tone, and transmits them to the emotion engine.

[0312] Step 2:

[0313] The terminal analyzes the user's emotion data obtained through the emotion engine and transmits the reservation conditions including that data to the server. The emotion data includes states such as joy, anticipation, and anxiety, which affect the determination of priorities on the server side.

[0314] Step 3:

[0315] The server uses analytical tools to select the appropriate booking destination based on the received booking conditions and sentiment data. In conjunction with past booking history, it prioritizes picking out related events that evoked positive emotions in the user.

[0316] Step 4:

[0317] The server automatically attempts to make a reservation at the selected location. While determining whether the reservation will be successful, it immediately prepares the next option if it fails or if there is a waiting list.

[0318] Step 5:

[0319] To notify the user of the success or failure, the server prepares a message that takes the user's emotional state into account and sends the result to the terminal. If the user is calm, the notification will include specific details; if the user is stressed, it will convey simple and clear information.

[0320] Step 6:

[0321] The device displays the notification to the user, who then reviews the result. If necessary, the user can choose to accept an alternative that takes emotions into consideration or try again with further adjusted booking conditions.

[0322] Step 7:

[0323] If the user accepts new conditions or alternatives, the device sends that information to the server and repeats the process. The emotion engine accumulates past analysis results and evolves to suggest more accurate options for future reservations.

[0324] (Example 2)

[0325] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0326] Traditional systems struggle to provide personalized experiences when users make reservations or selections because they don't consider individual emotions or satisfaction levels. In particular, the quality of the user experience tends to decline when users are presented with options they previously found unsatisfactory, or when suggestions that meet their expectations are not offered.

[0327] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0328] In this invention, the server includes data analysis means for analyzing data, emotion recognition means for detecting user emotions, and evaluation means for performing evaluations that take emotion data into consideration. This enables the provision of optimized choices and alternatives based on user emotions, thereby improving the user experience to be more personalized.

[0329] "Data input means" refers to an interface or device for users to input their desired conditions.

[0330] "Data analysis means" refers to functions or devices that automatically analyze a target based on input conditions.

[0331] "Emotion recognition means" refers to technologies and devices used to detect a user's emotions.

[0332] "Evaluation method" refers to a mechanism or device that optimizes analysis results by taking emotional data into consideration.

[0333] "Processing execution means" refers to a function or device that automatically executes processing based on the results optimized by the evaluation means.

[0334] "Information notification means" refers to a function or device that determines whether a process was successful or not and transmits that information to the user.

[0335] An "option provision mechanism" refers to a system that generates alternative candidates and provides them to the user if the processing fails.

[0336] This invention begins with the user accessing a reservation system using a terminal and entering their desired reservation conditions. The terminal is equipped with a data input section, allowing the user to provide conditions via text or voice input. The terminal further includes an emotion recognition system that uses a camera and microphone to detect emotions. This emotion recognition system uses a generative AI model to analyze the user's facial expressions and voice characteristics in real time and extract emotion data.

[0337] Data collected through emotion recognition is transmitted from the terminal to the server. The server is equipped with a data analysis system that performs analysis based on the received emotion data and the conditions provided by the user. During this analysis, the emotion data is compared with past history and used as evaluation criteria to provide the user with the most suitable suggestions. The evaluation method sets priorities considering the user's emotional state and generates appropriate candidates.

[0338] The server further includes a reservation processing execution system that automatically makes reservations based on optimized options determined through analysis. The results of the processing are notified to the user via a terminal, and the information notification unit adjusts the tone and content according to the user's emotions. In addition, if the reservation is unsuccessful, there is an option provision system that offers alternatives that take the user's emotions into consideration.

[0339] A concrete example is when a user tries to book a music event. If the system determines that the user is very excited, it will prioritize suggesting special seats or related events rather than standard seats. This makes it possible to provide a personalized experience that meets the user's expectations.

[0340] Example of a prompt:

[0341] "What methods can be used to sense a user's excitement when booking a popular music event and generate suggestions for special seats and related events?"

[0342] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0343] Step 1:

[0344] The user accesses the reservation system using a terminal and enters their desired reservation conditions. Input formats include text and voice. For example, the user might enter, "I want to get tickets for next month's concert." At this point, the output is the user's specific request. The terminal then prepares to send this data to the data analysis system.

[0345] Step 2:

[0346] The device analyzes the user's emotions in real time using emotion recognition technology. It captures facial expressions with a camera and collects voice tone with a microphone. Input is the user's actions and speech, and output is emotion data obtained using a generative AI model. This emotion data is transmitted to a server in a quantified form.

[0347] Step 3:

[0348] The server receives conditional and sentiment data from the user using data analysis tools. The input consists of reservation conditions and sentiment data sent by the user from their terminal. The server compares this data with a database of past sentiment history and analyzes the relevance of the data using a generative AI model. The output is a prioritized list of reservation candidates based on the user's sentiment.

[0349] Step 4:

[0350] The server uses evaluation tools to optimize the analyzed list of candidates. The input is a prioritized list of reservation candidates. The server highly values ​​the user's positive emotions and lists special offers (such as premium seats) accordingly. The output is the reservation option best suited to the user.

[0351] Step 5:

[0352] The server executes the reservation process based on optimized reservation options. The input is the optimized options, and the output is the success or failure status of the reservation. If successful, reservation information is generated; if unsuccessful, alternative options are considered.

[0353] Step 6:

[0354] The terminal uses an information notification system to communicate the processing results from the server to the user. The input is the reservation success or failure status, and the output is a notification message to the user. The tone of the message is adjusted based on the user's emotional state. Specifically, if the user is stressed, the notification is in a soft tone, and if they are calm, it is concise.

[0355] Step 7:

[0356] If a reservation is unsuccessful, the server uses an option provision mechanism to generate and suggest alternative options to the user. The input is the user's emotional state and information about the failed reservation. The output is a list of alternatives, including new suggestions based on the emotional state. This makes it possible to provide a more satisfying experience for the user.

[0357] (Application Example 2)

[0358] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0359] Traditional reservation systems simply present reservation options based on user input, failing to provide a personalized experience that takes user emotions into account. This made it difficult to increase user satisfaction or present more appropriate options.

[0360] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0361] In this invention, the server includes emotion analysis means for analyzing the user's emotions, comparison means for comparing the emotion data with past emotion history, and priority determination means for determining the priority of reservation items considering the user's emotions. This makes it possible to provide a personalized reservation experience based on the user's emotions and improve user satisfaction.

[0362] "Data input means" refers to devices or mechanisms used by users to input their desired reservation conditions.

[0363] "Evaluation means" refers to a device or program for automatically evaluating multiple reservation targets based on reservation request conditions received from a data input means.

[0364] "Emotional analysis tools" refer to devices or programs used to analyze a user's emotions.

[0365] A "comparison means" is a device or mechanism that uses user emotion data obtained by emotion analysis means to compare it with past emotion history.

[0366] A "priority determination means" is a device or program for determining the priority of reservation items based on the matching results obtained by a comparison means.

[0367] "Processing execution means" refers to a device or program for automatically executing reserved processing.

[0368] An "information notification means" is a device or program that determines whether or not a reservation process was successful and notifies the user.

[0369] A "candidate suggestion means" is a device or program that, if the reservation process is unsuccessful, provides alternative reservation candidates while taking the user's feelings into consideration.

[0370] This invention provides a configuration for a reservation system that offers a personalized experience that takes into account the user's emotions. The system acquires reservation conditions via a data input device and narrows down reservation candidates using an evaluation means to evaluate them. At this time, the system analyzes the user's emotions in real time using an emotion analysis means and collects emotion data.

[0371] Emotion analysis is performed, for example, by analyzing the user's emotions from their facial expressions and voice using a camera and microphone. This emotion data is then compared with a database of past emotion history using a comparison mechanism, and the priority of reservation targets is determined by a priority determination mechanism that reflects the user's preferences and past satisfaction levels. The server then processes the data based on this priority and determines the most suitable reservation candidates for the user.

[0372] Furthermore, even if a reservation cannot be completed, a system for suggesting alternatives tailored to the user's current emotional state will present the option that will be most satisfying to the user. When notifying the user of the reservation processing results or alternative options using information notification methods, the tone of the message will also be carefully considered to reduce stress.

[0373] As a concrete example, suppose a user attempts to book a music concert by inputting voice and facial expressions via a device. In this case, the emotion analysis engine analyzes that the user is excited and suggests special seats as priority seating options. Furthermore, if the user seems to be in a mood to patiently wait even if it means being put on a waiting list, the system will take steps to help them relax.

[0374] Specific examples of prompt messages include: "Create specific suggestions on what kind of music a user should choose when they are feeling stressed," and "If a positive emotion is detected in the user, explain how to optimize the booking process to improve their satisfaction."

[0375] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0376] Step 1:

[0377] The terminal receives the user's reservation details through a data entry device. The user enters their desired reservation details on the screen, and these details are converted into data format. The information entered includes date, time, and location.

[0378] Step 2:

[0379] The device uses its camera and microphone to capture the user's facial expressions and voice data. This data is sent to an emotion analysis system, where an algorithm analyzes the user's emotions in real time. The output obtained here is data indicating the user's emotional state.

[0380] Step 3:

[0381] The server compares the emotion data received from the emotion analysis device with a database of past emotion history. Using a comparison device, it evaluates which past situations this emotion is similar to, and obtains data that reflects the user's preferences and past satisfaction patterns as output.

[0382] Step 4:

[0383] The server uses comparative data and a priority determination mechanism to determine the priority of reservation options. Priorities are assigned to the reservation candidates in order of user preference, and a final list of reservation candidates is created.

[0384] Step 5:

[0385] The server uses processing execution means to determine the highest-priority reservation candidates. If the reservation is successful, this information is notified to the user through information notification means. The output used in this process is reservation confirmation data.

[0386] Step 6:

[0387] If a reservation is not confirmed, the server uses a suggestion system to generate and present alternative options that take into account the user's current feelings. The generated alternatives are then sent back to the reservation process. Here, the user is presented with the best option.

[0388] Step 7:

[0389] The server uses prompts to generate additional suggestions for the user in the generated AI model. These prompts are used to present music, messages, and other content tailored to the user's state. The generated output is content designed to enhance the user experience.

[0390] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0391] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated 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.

[0392] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0393] [Third Embodiment]

[0394] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0395] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0396] 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).

[0397] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. 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 microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0398] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0399] Camera 42 is a small digital camera equipped with an optical system including 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, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0400] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0401] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0402] The specific processing program 56 is an example of a "program" relating 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 in accordance with the specific processing program 56 executed on the RAM 30.

[0403] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0404] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 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 60 executed on the RAM 48.

[0405] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0406] This system automates the process of booking events and joining waiting lists for restaurants. Users first input their desired booking criteria into the system via a terminal. These criteria include information such as the destination, desired date and time, and type of event.

[0407] Once information is entered into the terminal, the terminal sends that data to the server. The server analyzes this data and prepares the necessary steps to execute the reservation. In this process, the server automatically searches for available reservation options and selects the one that best suits the criteria.

[0408] The server accesses the reservation site at the specified date and time and automatically checks whether a reservation is available based on the conditions set by the user. Furthermore, in the case of a waiting list, the system is configured to repeatedly check at specific intervals until a reservation becomes available.

[0409] If the reservation is successful, the server notifies the terminal, and the terminal displays the result to the user. If the reservation is unsuccessful, the server generates other suitable options and presents them to the user via the terminal.

[0410] A concrete example is booking tickets for the Japan Series. When a user enters the game date, time, and desired seat into the system, the server attempts to access the tickets based on that information and determines whether the reservation will be successful. If the reservation is successful, the user is immediately notified of the result; if it is unsuccessful, the user is provided with information on similar games and seats. Similarly, in the case of restaurant reservations, if a user is on a waiting list, the server checks based on pre-registered conditions and processes the reservation as soon as a seat becomes available.

[0411] As described above, users can easily obtain their desired reservations and then efficiently take their next actions based on the results obtained.

[0412] The following describes the processing flow.

[0413] Step 1:

[0414] The user accesses the reservation system on their device and logs in with their account. After logging in, they fill in the detailed reservation conditions, such as the desired event or restaurant, date and time, location, and seating type, in the input form. The device then sends the entered information to the server.

[0415] Step 2:

[0416] The server analyzes the reservation conditions received from the terminal and stores them in a database. Based on the analysis results, it prepares to identify which reservation system to access and what API keys or authentication are required.

[0417] Step 3:

[0418] The server initiates access to the target booking site or service based on stored conditions, timed to coincide with the start date and time of the booking. If the booking site provides an API, it uses the API; otherwise, it collects information through web scraping.

[0419] Step 4:

[0420] The server automatically checks the availability of the accessed destination and determines whether it matches the user's criteria. If there is a possibility of a match, it attempts to make a reservation. It also automatically registers the user to a waiting list if necessary.

[0421] Step 5:

[0422] The server determines whether the reservation is successful and sends the result to the terminal. If the reservation is confirmed, it sends the result including details; if the reservation is unsuccessful, it provides a statement to that effect and offers alternative options.

[0423] Step 6:

[0424] The device receives the results from the server and notifies the user via push notifications, etc. Information is displayed on the user interface so that the user can review the results and take additional actions as needed.

[0425] Step 7:

[0426] The user reviews the booking results and chooses whether to attempt a new booking from the other options presented or to restart the process by entering additional preferences. Once this step is complete, the terminal can send the new information to the server and restart the processing flow.

[0427] (Example 1)

[0428] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0429] Manually making reservations for desired events and restaurants is time-consuming and laborious, and securing a reservation for popular items is extremely difficult. Furthermore, even for those on waiting lists, reconfirmation is necessary. There is a need to automate these tasks appropriately and efficiently.

[0430] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0431] In this invention, the server includes information input means, analysis means, reservation execution means, automatic access means, and monitoring means. This enables the automation of reservation processing based on conditions desired by the user, and allows for the rapid and efficient notification of successful reservations and the presentation of alternative candidates.

[0432] "Information input means" refers to an interface or device used by a user to input reservation conditions, and is a means of inputting necessary information through a user interface.

[0433] "Analysis means" refers to a means for automatically analyzing multiple reservation targets based on reservation conditions entered by the user and performing processing to select the optimal reservation target.

[0434] A "reservation execution means" is a means of performing a procedure to execute a reservation based on the analyzed results and confirming the reservation.

[0435] A "notification method" is a means of informing the user of the results of the reservation process, and plays the role of transmitting information of success or failure to the terminal.

[0436] A "means for presenting options" refers to a method for generating and presenting alternative reservation options to the user if a reservation is unsuccessful.

[0437] An "automated access method" is a means of automatically accessing a web interface to check the availability of a reservation.

[0438] A "monitoring measure" is a means of continuously checking the reservation status when a reservation is on a waiting list, and automatically executing the procedure when a new reservation becomes available.

[0439] As an embodiment of this invention, a system is constructed in which a user, a terminal, and a server work together to automate reservation operations. First, the user uses a terminal to input their desired reservation conditions. These conditions include the destination, desired reservation date and time, and type of event. The terminal formats this information and sends it to the server.

[0440] The server utilizes database management systems and analysis software (e.g., MySQL or Python libraries) to analyze the received data. This process selects the reservation candidate that best matches the user's preferences. The server also uses software (e.g., Selenium) to automatically access the web interface and check online for reservation availability at the specified date and time. To prepare for cancellations, the server has a monitoring function that periodically checks the reservation status and automatically initiates the reservation process when a reservation becomes available.

[0441] As a concrete example, consider a scenario where a user requests tickets to a certain event. The user enters their desired date, time, and seat through their device, and the server automatically accesses the booking site based on this information and attempts to make a reservation. If the reservation is successful, the server immediately notifies the device of the result, and the device displays this information to the user. If the reservation is unsuccessful, the server generates and presents alternatives to similar events and seats.

[0442] An example of a prompt message for the generating AI model might be, "Please select the highest-rated restaurants with available waitlists for the next week and begin the reservation process." This system would free users from complex reservation tasks, allowing them to secure their desired events and services more efficiently.

[0443] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0444] Step 1:

[0445] The user enters booking conditions via a terminal. These conditions include destination, desired booking date and time, and event type. This information is entered through the user interface on the terminal, where it is reviewed and formatted. As output, the terminal generates formatted booking condition data, ready to be sent to the server in the next step.

[0446] Step 2:

[0447] The terminal sends the entered reservation condition data to the server. Data communication is performed using the HTTP protocol. The input is the reservation condition data provided by the user, and the output is the terminal transferring that data to the server, making it ready for the server to receive the data.

[0448] Step 3:

[0449] The server analyzes the received data. Using databases and analysis software, it performs data matching and filtering based on reservation conditions. The input is the reservation condition data received in the previous step, and the output is a list of reservation candidates that meet the conditions. The server then prepares to use this result in the next step.

[0450] Step 4:

[0451] The server automatically accesses the web interface of the reservation site based on the analysis results. During this process, it attempts to execute online reservations using a tool like Selenium. The input is a list of reservation candidates, and the output is a check of whether the reservation is possible. In this step, if a reservation is possible, it is confirmed, and the process proceeds to the next step.

[0452] Step 5:

[0453] The server, if there is a waiting list, runs a timer and schedule management system to periodically check the reservation status. This allows it to automatically process reservations when they become available. The input is the existing reservation status, and the output generates a reservation notification when a new slot becomes available. This process uses a Python script with cron to repeatedly perform checks.

[0454] Step 6:

[0455] The server notifies the terminal of the final reservation success or failure. If the reservation is successful, a success message is sent, which the terminal displays to the user. The input is information regarding the success or failure of the reservation, and the output generates a message that is transmitted to the user. If the reservation cannot be made, the server generates an alternative and presents it to the user again.

[0456] (Application Example 1)

[0457] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0458] In recent years, there has been a growing demand for participation in security-related events and training sessions. However, these events are highly popular, making it difficult to secure reservations. Furthermore, manually searching for and booking events that match users' desired dates and conditions is time-consuming and cumbersome. Therefore, there is a need for a system that allows users to efficiently make reservations and ensure their participation.

[0459] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0460] In this invention, the server includes an information input means for a user to input desired reservation conditions, an analysis means for automatically analyzing multiple reservation targets based on the desired conditions received from the information input means, and a reservation execution means for managing reservations and executing automatic reservations. This makes it possible to process reservations for security-related events quickly and automatically.

[0461] "Information input means" refers to the interface used by users to enter reservation conditions.

[0462] The "analysis means" refers to a function that analyzes the received reservation conditions and automatically considers multiple reservation targets.

[0463] The "reservation execution means" is a function that automatically executes reservation processing based on the analyzed results.

[0464] A "notification method" is a function that determines whether a reservation was successful or unsuccessful and informs the user of the result.

[0465] A "means of presenting options" is a function that generates and provides alternative reservation options to the user if the reservation is unsuccessful.

[0466] A "security-related event" is a group gathering aimed at improving security knowledge and providing training.

[0467] "Specialized methods" refer to technologies or systems that have functions specifically tailored to a particular field or application.

[0468] To implement this invention, the system is configured as follows. This system is used by users to automate the booking of security-related events and training sessions. Users use a smartphone or other information terminal to input their desired booking conditions. This includes information such as the location, date and time, and type of event.

[0469] The device sends the user's entered conditions to the server via the internet. The server, using Python as its execution environment, scrapes web pages using the Scrapy library to analyze the data and search for events to reserve, identifying available events. The server then automatically reserves events that match the user's conditions. The success or failure of this reservation is notified to the device using Firebase Cloud Messaging. This allows the user to receive immediate notification if the reservation is successful.

[0470] As a concrete example, a user enters that they want to attend a security seminar to be held on the 15th of next month. Based on this request, the server gathers information about the relevant event and attempts to make a reservation automatically. If the reservation is successful, the user receives a notification that their reservation has been confirmed.

[0471] An example of a prompt to a generating AI model is as follows: "I would like to attend a seminar on security risk management scheduled to be held in Tokyo on the 15th of next month. Please retrieve the corresponding reservation information and complete the reservation."

[0472] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0473] Step 1:

[0474] The user enters the reservation details into their smartphone or information terminal. This information includes the location, date, and category of the event. This information forms the basis for subsequent processing.

[0475] Step 2:

[0476] The terminal sends the entered reservation conditions to the server. The server prepares to analyze the received data. The input data is filtered and formatted to a state suitable for analysis.

[0477] Step 3:

[0478] The server uses Python and the Scrapy library to scrape security-related events available on the web. The scraped event information is then used for conditional matching within the server.

[0479] Step 4:

[0480] The server compares the analyzed reservation conditions with the scraped event information to identify the event that best matches the user's criteria. It then applies a data matching algorithm to select the most suitable candidate.

[0481] Step 5:

[0482] The server attempts to make a reservation for the identified event. During this process, the reservation web form is automatically populated, and the reservation process proceeds. The status regarding the success or failure of the reservation is then checked.

[0483] Step 6:

[0484] If the reservation is successful, the server sends a notification to the device using Firebase Cloud Messaging. The notification includes a reservation confirmation message, which the user can check within the app. This allows the user to know the result in real time.

[0485] Step 7:

[0486] If a reservation is unsuccessful, the server generates an alternative and sends it to the terminal. The user is then presented with the next best option and can try making a reservation again. This process is repeated to provide the best possible reservation opportunity.

[0487] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0488] This invention relates to a reservation system that takes user emotions into consideration, thereby improving the user experience.

[0489] This system first uses an emotion engine to recognize the user's emotions when they enter reservation conditions on their terminal. The terminal senses emotions not only from the input data but also from voice and facial analysis using the camera and microphone, and transmits this information to the server in real time. The server receives this information and uses it as a basis for the analysis tools to evaluate reservation options.

[0490] The emotional data obtained by the emotion engine is compared with past emotional history to determine the priority of reservations. For example, if a user had a very satisfying experience at a certain event in the past, similar events will be suggested preferentially. Also, options that are judged to be unsatisfactory may be removed from the list.

[0491] In the reservation execution mechanism, if positive emotions are detected in the user, more desirable suggestions will be made to the user before the reservation is confirmed. Conversely, if negative emotions are detected, simpler and faster suggestions will be made.

[0492] The notification system adjusts the tone and content of messages according to the user's current emotional state. Specifically, if the user is stressed, a softer tone is used; if they are calm, the result is communicated concisely. Furthermore, if a reservation is unsuccessful, the system considers the user's emotions and proposes alternative options that reflect those emotions using a choice-presentation system.

[0493] As a concrete example, consider the process of a user attempting to book tickets for a popular music event. The system reads the user's emotions of anticipation and excitement from their facial expressions and tone of voice while they are on the booking screen, and then offers them special seats or additional related events instead of general admission seats for the event.

[0494] By using this emotion engine, we aim to provide a more personalized and empathetic service that goes beyond mere scheduling.

[0495] The following describes the processing flow.

[0496] Step 1:

[0497] The user accesses the reservation application on their device, logs in, and then enters the details of the event or restaurant they wish to reserve. During this process, the device uses its camera and microphone to collect the user's facial expressions and voice tone, and sends this information to the emotion engine.

[0498] Step 2:

[0499] The terminal analyzes the user's emotional data obtained through the emotion engine and sends reservation conditions, including this data, to the server. The emotional data includes states such as joy, anticipation, and anxiety, and influences the server's priority determination.

[0500] Step 3:

[0501] The server uses analytical tools to select the appropriate booking destination based on the received booking conditions and sentiment data. In conjunction with past booking history, it prioritizes picking out related events that evoked positive emotions in the user.

[0502] Step 4:

[0503] The server automatically attempts to make a reservation at the selected location. While determining whether the reservation will be successful, it immediately prepares the next option if it fails or if there is a waiting list.

[0504] Step 5:

[0505] To notify the user of the success or failure, the server prepares a message that takes the user's emotional state into account and sends the result to the terminal. If the user is calm, the notification will include specific details; if the user is stressed, it will convey simple and clear information.

[0506] Step 6:

[0507] The device displays the notification to the user, who then reviews the result. If necessary, the user can choose to accept an alternative that takes emotions into consideration or try again with further adjusted booking conditions.

[0508] Step 7:

[0509] If the user accepts new conditions or alternatives, the device sends that information to the server and repeats the process. The emotion engine accumulates past analysis results and evolves to suggest more accurate options for future reservations.

[0510] (Example 2)

[0511] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0512] Traditional systems struggle to provide personalized experiences when users make reservations or selections because they don't consider individual emotions or satisfaction levels. In particular, the quality of the user experience tends to decline when users are presented with options they previously found unsatisfactory, or when suggestions that meet their expectations are not offered.

[0513] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0514] In this invention, the server includes data analysis means for analyzing data, emotion recognition means for detecting user emotions, and evaluation means for performing evaluations that take emotion data into consideration. This enables the provision of optimized choices and alternatives based on user emotions, thereby improving the user experience to be more personalized.

[0515] "Data input means" refers to an interface or device for users to input their desired conditions.

[0516] "Data analysis means" refers to functions or devices that automatically analyze a target based on input conditions.

[0517] "Emotion recognition means" refers to technologies and devices used to detect a user's emotions.

[0518] "Evaluation method" refers to a mechanism or device that optimizes analysis results by taking emotional data into consideration.

[0519] "Processing execution means" refers to a function or device that automatically executes processing based on the results optimized by the evaluation means.

[0520] "Information notification means" refers to a function or device that determines whether a process was successful or not and transmits that information to the user.

[0521] An "option provision mechanism" refers to a system that generates alternative candidates and provides them to the user if the processing fails.

[0522] This invention begins with the user accessing a reservation system using a terminal and entering their desired reservation conditions. The terminal is equipped with a data input section, allowing the user to provide conditions via text or voice input. The terminal further includes an emotion recognition system that uses a camera and microphone to detect emotions. This emotion recognition system uses a generative AI model to analyze the user's facial expressions and voice characteristics in real time and extract emotion data.

[0523] Data collected through emotion recognition is transmitted from the terminal to the server. The server is equipped with a data analysis system that performs analysis based on the received emotion data and the conditions provided by the user. During this analysis, the emotion data is compared with past history and used as evaluation criteria to provide the user with the most suitable suggestions. The evaluation method sets priorities considering the user's emotional state and generates appropriate candidates.

[0524] The server further includes a reservation processing execution system that automatically makes reservations based on optimized options determined through analysis. The results of the processing are notified to the user via a terminal, and the information notification unit adjusts the tone and content according to the user's emotions. In addition, if the reservation is unsuccessful, there is an option provision system that offers alternatives that take the user's emotions into consideration.

[0525] A concrete example is when a user tries to book a music event. If the system determines that the user is very excited, it will prioritize suggesting special seats or related events rather than standard seats. This makes it possible to provide a personalized experience that meets the user's expectations.

[0526] Example of a prompt:

[0527] "What methods can be used to sense a user's excitement when booking a popular music event and generate suggestions for special seats and related events?"

[0528] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0529] Step 1:

[0530] The user accesses the reservation system using a terminal and enters their desired reservation conditions. Input formats include text and voice. For example, the user might enter, "I want to get tickets for next month's concert." At this point, the output is the user's specific request. The terminal then prepares to send this data to the data analysis system.

[0531] Step 2:

[0532] The device analyzes the user's emotions in real time using emotion recognition technology. It captures facial expressions with a camera and collects voice tone with a microphone. Input is the user's actions and speech, and output is emotion data obtained using a generative AI model. This emotion data is transmitted to a server in a quantified form.

[0533] Step 3:

[0534] The server receives conditional and sentiment data from the user using data analysis tools. The input consists of reservation conditions and sentiment data sent by the user from their terminal. The server compares this data with a database of past sentiment history and analyzes the relevance of the data using a generative AI model. The output is a prioritized list of reservation candidates based on the user's sentiment.

[0535] Step 4:

[0536] The server uses evaluation tools to optimize the analyzed list of candidates. The input is a prioritized list of reservation candidates. The server highly values ​​the user's positive emotions and lists special offers (such as premium seats) accordingly. The output is the reservation option best suited to the user.

[0537] Step 5:

[0538] The server executes the reservation process based on optimized reservation options. The input is the optimized options, and the output is the success or failure status of the reservation. If successful, reservation information is generated; if unsuccessful, alternative options are considered.

[0539] Step 6:

[0540] The terminal uses an information notification system to communicate the processing results from the server to the user. The input is the reservation success or failure status, and the output is a notification message to the user. The tone of the message is adjusted based on the user's emotional state. Specifically, if the user is stressed, the notification is in a soft tone, and if they are calm, it is concise.

[0541] Step 7:

[0542] If a reservation is unsuccessful, the server uses an option provision mechanism to generate and suggest alternative options to the user. The input is the user's emotional state and information about the failed reservation. The output is a list of alternatives, including new suggestions based on the emotional state. This makes it possible to provide a more satisfying experience for the user.

[0543] (Application Example 2)

[0544] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0545] Traditional reservation systems simply present reservation options based on user input, failing to provide a personalized experience that takes user emotions into account. This made it difficult to increase user satisfaction or present more appropriate options.

[0546] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0547] In this invention, the server includes emotion analysis means for analyzing the user's emotions, comparison means for comparing the emotion data with past emotion history, and priority determination means for determining the priority of reservation items considering the user's emotions. This makes it possible to provide a personalized reservation experience based on the user's emotions and improve user satisfaction.

[0548] "Data input means" refers to devices or mechanisms used by users to input their desired reservation conditions.

[0549] "Evaluation means" refers to a device or program for automatically evaluating multiple reservation targets based on reservation request conditions received from a data input means.

[0550] "Emotional analysis tools" refer to devices or programs used to analyze a user's emotions.

[0551] A "comparison means" is a device or mechanism that uses user emotion data obtained by emotion analysis means to compare it with past emotion history.

[0552] A "priority determination means" is a device or program for determining the priority of reservation items based on the matching results obtained by a comparison means.

[0553] "Processing execution means" refers to a device or program for automatically executing reserved processing.

[0554] An "information notification means" is a device or program that determines whether or not a reservation process was successful and notifies the user.

[0555] A "candidate suggestion means" is a device or program that, if the reservation process is unsuccessful, provides alternative reservation candidates while taking the user's feelings into consideration.

[0556] This invention provides a configuration for a reservation system that offers a personalized experience that takes into account the user's emotions. The system acquires reservation conditions via a data input device and narrows down reservation candidates using an evaluation means to evaluate them. At this time, the system analyzes the user's emotions in real time using an emotion analysis means and collects emotion data.

[0557] Emotion analysis is performed, for example, by analyzing the user's emotions from their facial expressions and voice using a camera and microphone. This emotion data is then compared with a database of past emotion history using a comparison mechanism, and the priority of reservation targets is determined by a priority determination mechanism that reflects the user's preferences and past satisfaction levels. The server then processes the data based on this priority and determines the most suitable reservation candidates for the user.

[0558] Furthermore, even if a reservation cannot be completed, a system for suggesting alternatives tailored to the user's current emotional state will present the option that will be most satisfying to the user. When notifying the user of the reservation processing results or alternative options using information notification methods, the tone of the message will also be carefully considered to reduce stress.

[0559] As a concrete example, suppose a user attempts to book a music concert by inputting voice and facial expressions via a device. In this case, the emotion analysis engine analyzes that the user is excited and suggests special seats as priority seating options. Furthermore, if the user seems to be in a mood to patiently wait even if it means being put on a waiting list, the system will take steps to help them relax.

[0560] Specific examples of prompt messages include: "Create specific suggestions on what kind of music a user should choose when they are feeling stressed," and "If a positive emotion is detected in the user, explain how to optimize the booking process to improve their satisfaction."

[0561] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0562] Step 1:

[0563] The terminal receives the user's reservation details through a data entry device. The user enters their desired reservation details on the screen, and these details are converted into data format. The information entered includes date, time, and location.

[0564] Step 2:

[0565] The device uses its camera and microphone to capture the user's facial expressions and voice data. This data is sent to an emotion analysis system, where an algorithm analyzes the user's emotions in real time. The output obtained here is data indicating the user's emotional state.

[0566] Step 3:

[0567] The server compares the emotion data received from the emotion analysis device with a database of past emotion history. Using a comparison device, it evaluates which past situations this emotion is similar to, and obtains data that reflects the user's preferences and past satisfaction patterns as output.

[0568] Step 4:

[0569] The server uses comparative data and a priority determination mechanism to determine the priority of reservation options. Priorities are assigned to the reservation candidates in order of user preference, and a final list of reservation candidates is created.

[0570] Step 5:

[0571] The server uses processing execution means to determine the highest-priority reservation candidates. If the reservation is successful, this information is notified to the user through information notification means. The output used in this process is reservation confirmation data.

[0572] Step 6:

[0573] If a reservation is not confirmed, the server uses a suggestion system to generate and present alternative options that take into account the user's current feelings. The generated alternatives are then sent back to the reservation process. Here, the user is presented with the best option.

[0574] Step 7:

[0575] The server uses prompts to generate additional suggestions for the user in the generated AI model. These prompts are used to present music, messages, and other content tailored to the user's state. The generated output is content designed to enhance the user experience.

[0576] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0577] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated 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.

[0578] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0579] [Fourth Embodiment]

[0580] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0581] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0582] 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).

[0583] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. 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 microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0584] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0585] Camera 42 is a small digital camera equipped with an optical system including 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, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0586] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0587] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0588] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0589] The specific processing program 56 is an example of a "program" relating 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 in accordance with the specific processing program 56 executed on the RAM 30.

[0590] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0591] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 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 60 executed on the RAM 48.

[0592] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0593] This system automates the process of booking events and joining waiting lists for restaurants. Users first input their desired booking criteria into the system via a terminal. These criteria include information such as the destination, desired date and time, and type of event.

[0594] Once information is entered into the terminal, the terminal sends that data to the server. The server analyzes this data and prepares the necessary steps to execute the reservation. In this process, the server automatically searches for available reservation options and selects the one that best suits the criteria.

[0595] The server accesses the reservation site at the specified date and time and automatically checks whether a reservation is available based on the conditions set by the user. Furthermore, in the case of a waiting list, the system is configured to repeatedly check at specific intervals until a reservation becomes available.

[0596] If the reservation is successful, the server notifies the terminal, and the terminal displays the result to the user. If the reservation is unsuccessful, the server generates other suitable options and presents them to the user via the terminal.

[0597] A concrete example is booking tickets for the Japan Series. When a user enters the game date, time, and desired seat into the system, the server attempts to access the tickets based on that information and determines whether the reservation will be successful. If the reservation is successful, the user is immediately notified of the result; if it is unsuccessful, the user is provided with information on similar games and seats. Similarly, in the case of restaurant reservations, if a user is on a waiting list, the server checks based on pre-registered conditions and processes the reservation as soon as a seat becomes available.

[0598] As described above, users can easily obtain their desired reservations and then efficiently take their next actions based on the results obtained.

[0599] The following describes the processing flow.

[0600] Step 1:

[0601] The user accesses the reservation system on their device and logs in with their account. After logging in, they fill in the detailed reservation conditions, such as the desired event or restaurant, date and time, location, and seating type, in the input form. The device then sends the entered information to the server.

[0602] Step 2:

[0603] The server analyzes the reservation conditions received from the terminal and stores them in a database. Based on the analysis results, it prepares to identify which reservation system to access and what API keys or authentication are required.

[0604] Step 3:

[0605] The server initiates access to the target booking site or service based on stored conditions, timed to coincide with the start date and time of the booking. If the booking site provides an API, it uses the API; otherwise, it collects information through web scraping.

[0606] Step 4:

[0607] The server automatically checks the availability of the accessed destination and determines whether it matches the user's criteria. If there is a possibility of a match, it attempts to make a reservation. It also automatically registers the user to a waiting list if necessary.

[0608] Step 5:

[0609] The server determines whether the reservation is successful and sends the result to the terminal. If the reservation is confirmed, it sends the result including details; if the reservation is unsuccessful, it provides a statement to that effect and offers alternative options.

[0610] Step 6:

[0611] The device receives the results from the server and notifies the user via push notifications, etc. Information is displayed on the user interface so that the user can review the results and take additional actions as needed.

[0612] Step 7:

[0613] The user reviews the booking results and chooses whether to attempt a new booking from the other options presented or to restart the process by entering additional preferences. Once this step is complete, the terminal can send the new information to the server and restart the processing flow.

[0614] (Example 1)

[0615] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0616] Manually making reservations for desired events and restaurants is time-consuming and laborious, and securing a reservation for popular items is extremely difficult. Furthermore, even for those on waiting lists, reconfirmation is necessary. There is a need to automate these tasks appropriately and efficiently.

[0617] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0618] In this invention, the server includes information input means, analysis means, reservation execution means, automatic access means, and monitoring means. This enables the automation of reservation processing based on conditions desired by the user, and allows for the rapid and efficient notification of successful reservations and the presentation of alternative candidates.

[0619] "Information input means" refers to an interface or device used by a user to input reservation conditions, and is a means of inputting necessary information through a user interface.

[0620] "Analysis means" refers to a means for automatically analyzing multiple reservation targets based on reservation conditions entered by the user and performing processing to select the optimal reservation target.

[0621] A "reservation execution means" is a means of performing a procedure to execute a reservation based on the analyzed results and confirming the reservation.

[0622] A "notification method" is a means of informing the user of the results of the reservation process, and plays the role of transmitting information of success or failure to the terminal.

[0623] A "means for presenting options" refers to a method for generating and presenting alternative reservation options to the user if a reservation is unsuccessful.

[0624] An "automated access method" is a means of automatically accessing a web interface to check the availability of a reservation.

[0625] A "monitoring measure" is a means of continuously checking the reservation status when a reservation is on a waiting list, and automatically executing the procedure when a new reservation becomes available.

[0626] As an embodiment of this invention, a system is constructed in which a user, a terminal, and a server work together to automate reservation operations. First, the user uses a terminal to input their desired reservation conditions. These conditions include the destination, desired reservation date and time, and type of event. The terminal formats this information and sends it to the server.

[0627] The server utilizes database management systems and analysis software (e.g., MySQL or Python libraries) to analyze the received data. This process selects the reservation candidate that best matches the user's preferences. The server also uses software (e.g., Selenium) to automatically access the web interface and check online for reservation availability at the specified date and time. To prepare for cancellations, the server has a monitoring function that periodically checks the reservation status and automatically initiates the reservation process when a reservation becomes available.

[0628] As a concrete example, consider a scenario where a user requests tickets to a certain event. The user enters their desired date, time, and seat through their device, and the server automatically accesses the booking site based on this information and attempts to make a reservation. If the reservation is successful, the server immediately notifies the device of the result, and the device displays this information to the user. If the reservation is unsuccessful, the server generates and presents alternatives to similar events and seats.

[0629] An example of a prompt message for the generating AI model might be, "Please select the highest-rated restaurants with available waitlists for the next week and begin the reservation process." This system would free users from complex reservation tasks, allowing them to secure their desired events and services more efficiently.

[0630] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0631] Step 1:

[0632] The user enters booking conditions via a terminal. These conditions include destination, desired booking date and time, and event type. This information is entered through the user interface on the terminal, where it is reviewed and formatted. As output, the terminal generates formatted booking condition data, ready to be sent to the server in the next step.

[0633] Step 2:

[0634] The terminal sends the entered reservation condition data to the server. Data communication is performed using the HTTP protocol. The input is the reservation condition data provided by the user, and the output is the terminal transferring that data to the server, making it ready for the server to receive the data.

[0635] Step 3:

[0636] The server analyzes the received data. Using databases and analysis software, it performs data matching and filtering based on reservation conditions. The input is the reservation condition data received in the previous step, and the output is a list of reservation candidates that meet the conditions. The server then prepares to use this result in the next step.

[0637] Step 4:

[0638] The server automatically accesses the web interface of the reservation site based on the analysis results. During this process, it attempts to execute online reservations using a tool like Selenium. The input is a list of reservation candidates, and the output is a check of whether the reservation is possible. In this step, if a reservation is possible, it is confirmed, and the process proceeds to the next step.

[0639] Step 5:

[0640] The server, if there is a waiting list, runs a timer and schedule management system to periodically check the reservation status. This allows it to automatically process reservations when they become available. The input is the existing reservation status, and the output generates a reservation notification when a new slot becomes available. This process uses a Python script with cron to repeatedly perform checks.

[0641] Step 6:

[0642] The server notifies the terminal of the final reservation success or failure. If the reservation is successful, a success message is sent, which the terminal displays to the user. The input is information regarding the success or failure of the reservation, and the output generates a message that is transmitted to the user. If the reservation cannot be made, the server generates an alternative and presents it to the user again.

[0643] (Application Example 1)

[0644] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0645] In recent years, there has been a growing demand for participation in security-related events and training sessions. However, these events are highly popular, making it difficult to secure reservations. Furthermore, manually searching for and booking events that match users' desired dates and conditions is time-consuming and cumbersome. Therefore, there is a need for a system that allows users to efficiently make reservations and ensure their participation.

[0646] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0647] In this invention, the server includes an information input means for a user to input desired reservation conditions, an analysis means for automatically analyzing multiple reservation targets based on the desired conditions received from the information input means, and a reservation execution means for managing reservations and executing automatic reservations. This makes it possible to process reservations for security-related events quickly and automatically.

[0648] "Information input means" refers to the interface used by users to enter reservation conditions.

[0649] The "analysis means" refers to a function that analyzes the received reservation conditions and automatically considers multiple reservation targets.

[0650] The "reservation execution means" is a function that automatically executes reservation processing based on the analyzed results.

[0651] A "notification method" is a function that determines whether a reservation was successful or unsuccessful and informs the user of the result.

[0652] A "means of presenting options" is a function that generates and provides alternative reservation options to the user if the reservation is unsuccessful.

[0653] A "security-related event" is a group gathering aimed at improving security knowledge and providing training.

[0654] "Specialized methods" refer to technologies or systems that have functions specifically tailored to a particular field or application.

[0655] To implement this invention, the system is configured as follows. This system is used by users to automate the booking of security-related events and training sessions. Users use a smartphone or other information terminal to input their desired booking conditions. This includes information such as the location, date and time, and type of event.

[0656] The device sends the user's entered conditions to the server via the internet. The server, using Python as its execution environment, scrapes web pages using the Scrapy library to analyze the data and search for events to reserve, identifying available events. The server then automatically reserves events that match the user's conditions. The success or failure of this reservation is notified to the device using Firebase Cloud Messaging. This allows the user to receive immediate notification if the reservation is successful.

[0657] As a concrete example, a user enters that they want to attend a security seminar to be held on the 15th of next month. Based on this request, the server gathers information about the relevant event and attempts to make a reservation automatically. If the reservation is successful, the user receives a notification that their reservation has been confirmed.

[0658] An example of a prompt to a generating AI model is as follows: "I would like to attend a seminar on security risk management scheduled to be held in Tokyo on the 15th of next month. Please retrieve the corresponding reservation information and complete the reservation."

[0659] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0660] Step 1:

[0661] The user enters the reservation details into their smartphone or information terminal. This information includes the location, date, and category of the event. This information forms the basis for subsequent processing.

[0662] Step 2:

[0663] The terminal sends the entered reservation conditions to the server. The server prepares to analyze the received data. The input data is filtered and formatted to a state suitable for analysis.

[0664] Step 3:

[0665] The server uses Python and the Scrapy library to scrape security-related events available on the web. The scraped event information is then used for conditional matching within the server.

[0666] Step 4:

[0667] The server compares the analyzed reservation conditions with the scraped event information to identify the event that best matches the user's criteria. It then applies a data matching algorithm to select the most suitable candidate.

[0668] Step 5:

[0669] The server attempts to make a reservation for the identified event. During this process, the reservation web form is automatically populated, and the reservation process proceeds. The status regarding the success or failure of the reservation is then checked.

[0670] Step 6:

[0671] If the reservation is successful, the server sends a notification to the device using Firebase Cloud Messaging. The notification includes a reservation confirmation message, which the user can check within the app. This allows the user to know the result in real time.

[0672] Step 7:

[0673] If a reservation is unsuccessful, the server generates an alternative and sends it to the terminal. The user is then presented with the next best option and can try making a reservation again. This process is repeated to provide the best possible reservation opportunity.

[0674] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0675] This invention relates to a reservation system that takes user emotions into consideration, thereby improving the user experience.

[0676] This system first uses an emotion engine to recognize the user's emotions when they enter reservation conditions on their terminal. The terminal senses emotions not only from the input data but also from voice and facial analysis using the camera and microphone, and transmits this information to the server in real time. The server receives this information and uses it as a basis for the analysis tools to evaluate reservation options.

[0677] The emotional data obtained by the emotion engine is compared with past emotional history to determine the priority of reservations. For example, if a user had a very satisfying experience at a certain event in the past, similar events will be suggested preferentially. Also, options that are judged to be unsatisfactory may be removed from the list.

[0678] In the reservation execution mechanism, if positive emotions are detected in the user, more desirable suggestions will be made to the user before the reservation is confirmed. Conversely, if negative emotions are detected, simpler and faster suggestions will be made.

[0679] The notification system adjusts the tone and content of messages according to the user's current emotional state. Specifically, if the user is stressed, a softer tone is used; if they are calm, the result is communicated concisely. Furthermore, if a reservation is unsuccessful, the system considers the user's emotions and proposes alternative options that reflect those emotions using a choice-presentation system.

[0680] As a concrete example, consider the process of a user attempting to book tickets for a popular music event. The system reads the user's emotions of anticipation and excitement from their facial expressions and tone of voice while they are on the booking screen, and then offers them special seats or additional related events instead of general admission seats for the event.

[0681] By using this emotion engine, we aim to provide a more personalized and empathetic service that goes beyond mere scheduling.

[0682] The following describes the processing flow.

[0683] Step 1:

[0684] The user accesses the reservation application on their device, logs in, and then enters the details of the event or restaurant they wish to reserve. During this process, the device uses its camera and microphone to collect the user's facial expressions and voice tone, and sends this information to the emotion engine.

[0685] Step 2:

[0686] The terminal analyzes the user's emotional data obtained through the emotion engine and sends reservation conditions, including this data, to the server. The emotional data includes states such as joy, anticipation, and anxiety, and influences the server's priority determination.

[0687] Step 3:

[0688] The server uses analytical tools to select the appropriate booking destination based on the received booking conditions and sentiment data. In conjunction with past booking history, it prioritizes picking out related events that evoked positive emotions in the user.

[0689] Step 4:

[0690] The server automatically attempts to make a reservation at the selected location. While determining whether the reservation will be successful, it immediately prepares the next option if it fails or if there is a waiting list.

[0691] Step 5:

[0692] To notify the user of the success or failure, the server prepares a message that takes the user's emotional state into account and sends the result to the terminal. If the user is calm, the notification will include specific details; if the user is stressed, it will convey simple and clear information.

[0693] Step 6:

[0694] The device displays the notification to the user, who then reviews the result. If necessary, the user can choose to accept an alternative that takes emotions into consideration or try again with further adjusted booking conditions.

[0695] Step 7:

[0696] If the user accepts new conditions or alternatives, the device sends that information to the server and repeats the process. The emotion engine accumulates past analysis results and evolves to suggest more accurate options for future reservations.

[0697] (Example 2)

[0698] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0699] Traditional systems struggle to provide personalized experiences when users make reservations or selections because they don't consider individual emotions or satisfaction levels. In particular, the quality of the user experience tends to decline when users are presented with options they previously found unsatisfactory, or when suggestions that meet their expectations are not offered.

[0700] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0701] In this invention, the server includes data analysis means for analyzing data, emotion recognition means for detecting user emotions, and evaluation means for performing evaluations that take emotion data into consideration. This enables the provision of optimized choices and alternatives based on user emotions, thereby improving the user experience to be more personalized.

[0702] "Data input means" refers to an interface or device for users to input their desired conditions.

[0703] "Data analysis means" refers to functions or devices that automatically analyze a target based on input conditions.

[0704] "Emotion recognition means" refers to technologies and devices used to detect a user's emotions.

[0705] "Evaluation method" refers to a mechanism or device that optimizes analysis results by taking emotional data into consideration.

[0706] "Processing execution means" refers to a function or device that automatically executes processing based on the results optimized by the evaluation means.

[0707] "Information notification means" refers to a function or device that determines whether a process was successful or not and transmits that information to the user.

[0708] An "option provision mechanism" refers to a system that generates alternative candidates and provides them to the user if the processing fails.

[0709] This invention begins with the user accessing a reservation system using a terminal and entering their desired reservation conditions. The terminal is equipped with a data input section, allowing the user to provide conditions via text or voice input. The terminal further includes an emotion recognition system that uses a camera and microphone to detect emotions. This emotion recognition system uses a generative AI model to analyze the user's facial expressions and voice characteristics in real time and extract emotion data.

[0710] Data collected through emotion recognition is transmitted from the terminal to the server. The server is equipped with a data analysis system that performs analysis based on the received emotion data and the conditions provided by the user. During this analysis, the emotion data is compared with past history and used as evaluation criteria to provide the user with the most suitable suggestions. The evaluation method sets priorities considering the user's emotional state and generates appropriate candidates.

[0711] The server further includes a reservation processing execution system that automatically makes reservations based on optimized options determined through analysis. The results of the processing are notified to the user via a terminal, and the information notification unit adjusts the tone and content according to the user's emotions. In addition, if the reservation is unsuccessful, there is an option provision system that offers alternatives that take the user's emotions into consideration.

[0712] A concrete example is when a user tries to book a music event. If the system determines that the user is very excited, it will prioritize suggesting special seats or related events rather than standard seats. This makes it possible to provide a personalized experience that meets the user's expectations.

[0713] Example of a prompt:

[0714] "What methods can be used to sense a user's excitement when booking a popular music event and generate suggestions for special seats and related events?"

[0715] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0716] Step 1:

[0717] The user accesses the reservation system using a terminal and enters their desired reservation conditions. Input formats include text and voice. For example, the user might enter, "I want to get tickets for next month's concert." At this point, the output is the user's specific request. The terminal then prepares to send this data to the data analysis system.

[0718] Step 2:

[0719] The device analyzes the user's emotions in real time using emotion recognition technology. It captures facial expressions with a camera and collects voice tone with a microphone. Input is the user's actions and speech, and output is emotion data obtained using a generative AI model. This emotion data is transmitted to a server in a quantified form.

[0720] Step 3:

[0721] The server receives conditional and sentiment data from the user using data analysis tools. The input consists of reservation conditions and sentiment data sent by the user from their terminal. The server compares this data with a database of past sentiment history and analyzes the relevance of the data using a generative AI model. The output is a prioritized list of reservation candidates based on the user's sentiment.

[0722] Step 4:

[0723] The server uses evaluation tools to optimize the analyzed list of candidates. The input is a prioritized list of reservation candidates. The server highly values ​​the user's positive emotions and lists special offers (such as premium seats) accordingly. The output is the reservation option best suited to the user.

[0724] Step 5:

[0725] The server executes the reservation process based on optimized reservation options. The input is the optimized options, and the output is the success or failure status of the reservation. If successful, reservation information is generated; if unsuccessful, alternative options are considered.

[0726] Step 6:

[0727] The terminal uses an information notification system to communicate the processing results from the server to the user. The input is the reservation success or failure status, and the output is a notification message to the user. The tone of the message is adjusted based on the user's emotional state. Specifically, if the user is stressed, the notification is in a soft tone, and if they are calm, it is concise.

[0728] Step 7:

[0729] If a reservation is unsuccessful, the server uses an option provision mechanism to generate and suggest alternative options to the user. The input is the user's emotional state and information about the failed reservation. The output is a list of alternatives, including new suggestions based on the emotional state. This makes it possible to provide a more satisfying experience for the user.

[0730] (Application Example 2)

[0731] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0732] Traditional reservation systems simply present reservation options based on user input, failing to provide a personalized experience that takes user emotions into account. This made it difficult to increase user satisfaction or present more appropriate options.

[0733] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0734] In this invention, the server includes emotion analysis means for analyzing the user's emotions, comparison means for comparing the emotion data with past emotion history, and priority determination means for determining the priority of reservation items considering the user's emotions. This makes it possible to provide a personalized reservation experience based on the user's emotions and improve user satisfaction.

[0735] "Data input means" refers to devices or mechanisms used by users to input their desired reservation conditions.

[0736] "Evaluation means" refers to a device or program for automatically evaluating multiple reservation targets based on reservation request conditions received from a data input means.

[0737] "Emotional analysis tools" refer to devices or programs used to analyze a user's emotions.

[0738] A "comparison means" is a device or mechanism that uses user emotion data obtained by emotion analysis means to compare it with past emotion history.

[0739] A "priority determination means" is a device or program for determining the priority of reservation items based on the matching results obtained by a comparison means.

[0740] "Processing execution means" refers to a device or program for automatically executing reserved processing.

[0741] An "information notification means" is a device or program that determines whether or not a reservation process was successful and notifies the user.

[0742] A "candidate suggestion means" is a device or program that, if the reservation process is unsuccessful, provides alternative reservation candidates while taking the user's feelings into consideration.

[0743] This invention provides a configuration for a reservation system that offers a personalized experience that takes into account the user's emotions. The system acquires reservation conditions via a data input device and narrows down reservation candidates using an evaluation means to evaluate them. At this time, the system analyzes the user's emotions in real time using an emotion analysis means and collects emotion data.

[0744] Emotion analysis is performed, for example, by analyzing the user's emotions from their facial expressions and voice using a camera and microphone. This emotion data is then compared with a database of past emotion history using a comparison mechanism, and the priority of reservation targets is determined by a priority determination mechanism that reflects the user's preferences and past satisfaction levels. The server then processes the data based on this priority and determines the most suitable reservation candidates for the user.

[0745] Furthermore, even if a reservation cannot be completed, a system for suggesting alternatives tailored to the user's current emotional state will present the option that will be most satisfying to the user. When notifying the user of the reservation processing results or alternative options using information notification methods, the tone of the message will also be carefully considered to reduce stress.

[0746] As a concrete example, suppose a user attempts to book a music concert by inputting voice and facial expressions via a device. In this case, the emotion analysis engine analyzes that the user is excited and suggests special seats as priority seating options. Furthermore, if the user seems to be in a mood to patiently wait even if it means being put on a waiting list, the system will take steps to help them relax.

[0747] Specific examples of prompt messages include: "Create specific suggestions on what kind of music a user should choose when they are feeling stressed," and "If a positive emotion is detected in the user, explain how to optimize the booking process to improve their satisfaction."

[0748] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0749] Step 1:

[0750] The terminal receives the user's reservation details through a data entry device. The user enters their desired reservation details on the screen, and these details are converted into data format. The information entered includes date, time, and location.

[0751] Step 2:

[0752] The device uses its camera and microphone to capture the user's facial expressions and voice data. This data is sent to an emotion analysis system, where an algorithm analyzes the user's emotions in real time. The output obtained here is data indicating the user's emotional state.

[0753] Step 3:

[0754] The server compares the emotion data received from the emotion analysis device with a database of past emotion history. Using a comparison device, it evaluates which past situations this emotion is similar to, and obtains data that reflects the user's preferences and past satisfaction patterns as output.

[0755] Step 4:

[0756] The server uses comparative data and a priority determination mechanism to determine the priority of reservation options. Priorities are assigned to the reservation candidates in order of user preference, and a final list of reservation candidates is created.

[0757] Step 5:

[0758] The server uses processing execution means to determine the highest-priority reservation candidates. If the reservation is successful, this information is notified to the user through information notification means. The output used in this process is reservation confirmation data.

[0759] Step 6:

[0760] If a reservation is not confirmed, the server uses a suggestion system to generate and present alternative options that take into account the user's current feelings. The generated alternatives are then sent back to the reservation process. Here, the user is presented with the best option.

[0761] Step 7:

[0762] The server uses prompts to generate additional suggestions for the user in the generated AI model. These prompts are used to present music, messages, and other content tailored to the user's state. The generated output is content designed to enhance the user experience.

[0763] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0764] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated 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.

[0765] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0766] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0767] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0768] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0769] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0770] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0771] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0772] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0773] 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.

[0774] 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 of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0775] 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.

[0776] 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.

[0777] 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.

[0778] 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.

[0779] 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.

[0780] 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.

[0781] 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.

[0782] 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.

[0783] 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 to be incorporated by reference.

[0784] The following is further disclosed regarding the embodiments described above.

[0785] (Claim 1)

[0786] A means for users to input their desired reservation conditions,

[0787] An analysis means that automatically analyzes multiple reservation targets based on the desired conditions received from the information input means,

[0788] A reservation execution means that automatically executes the reservation process based on the results of the analysis performed by the aforementioned analysis means,

[0789] A notification method to determine whether the reservation process was successful or not and notify the user,

[0790] If the aforementioned reservation process is unsuccessful, a means for presenting options to the user to offer alternative reservation candidates,

[0791] A system that includes this.

[0792] (Claim 2)

[0793] The system according to claim 1, wherein the reservation execution means continuously monitors the availability of the reservation target in order to satisfy the reservation conditions, including the waiting list.

[0794] (Claim 3)

[0795] The system according to claim 1, wherein the option presentation means generates other candidates based on the user's desired conditions and presents them to the user.

[0796] "Example 1"

[0797] (Claim 1)

[0798] A means for users to input their desired reservation conditions,

[0799] An analysis means that automatically analyzes multiple reservation targets based on the desired conditions received from the information input means,

[0800] A reservation execution means that automatically executes the reservation process based on the results of the analysis performed by the aforementioned analysis means,

[0801] A notification method to determine whether the reservation process was successful or not and notify the user,

[0802] If the aforementioned reservation process is unsuccessful, a means for presenting options to the user to offer alternative reservation candidates,

[0803] An automated access mechanism for automatically checking the availability of a reservation on the web interface and executing the process,

[0804] In the case of being on the waiting list, a monitoring system is in place to periodically check this and initiate the process when a reservation becomes available.

[0805] A system that includes this.

[0806] (Claim 2)

[0807] The system according to claim 1, wherein the reservation execution means includes a conversion means that continuously monitors the availability of the reservation target in order to satisfy the reservation conditions, including the waiting list, and notifies the terminal of the reservation result.

[0808] (Claim 3)

[0809] The system according to claim 1, wherein the option presentation means generates other candidates based on the user's desired conditions and presents the new candidates using the prompt generation means.

[0810] "Application Example 1"

[0811] (Claim 1)

[0812] A means for users to input their desired reservation conditions,

[0813] An analysis means that automatically analyzes multiple reservation targets based on the desired conditions received from the information input means,

[0814] A reservation execution means that automatically executes the reservation process based on the results of the analysis performed by the aforementioned analysis means,

[0815] A notification method to determine whether the reservation process was successful or not and notify the user,

[0816] If the aforementioned reservation process is unsuccessful, a means for presenting options to the user to offer alternative reservation candidates,

[0817] A specialized tool for managing and automating the booking of security-related events and programs,

[0818] A system that includes this.

[0819] (Claim 2)

[0820] The system according to claim 1, wherein the reservation execution means continuously monitors the availability of the reservation target in order to satisfy the reservation conditions, including the waiting list.

[0821] (Claim 3)

[0822] The system according to claim 1, wherein the option presentation means generates other candidates based on the user's desired conditions and presents them to the user.

[0823] "Example 2 of combining an emotion engine"

[0824] (Claim 1)

[0825] A data entry method for users to input their desired conditions,

[0826] A data analysis means that automatically analyzes multiple targets based on conditions received from the data input means,

[0827] A means for detecting a user's emotions,

[0828] An evaluation means that takes into account the emotion data obtained by the emotion recognition means and optimizes the results analyzed by the data analysis means,

[0829] A processing execution means that automatically executes processing based on the results optimized by the evaluation means,

[0830] A means of notifying the user whether the process was successful or not,

[0831] If the above process is unsuccessful, an option provision means is provided to offer the user alternative candidates.

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, wherein the processing execution means continuously monitors the status of the target in order to satisfy the conditions.

[0835] (Claim 3)

[0836] The system according to claim 1, wherein the option providing means generates and presents other candidates based on the user's emotions to the user.

[0837] "Application example 2 when combining with an emotional engine"

[0838] (Claim 1)

[0839] A data entry method for users to input their desired reservation conditions,

[0840] An evaluation means that automatically evaluates multiple reservation targets based on the desired conditions received from the data input means,

[0841] A means of analyzing user emotions,

[0842] A comparison means for comparing the user's emotional data obtained by the aforementioned emotional analysis means with past emotional history,

[0843] Priority determination means for determining the priority of reservation targets based on the matching results by the comparison means,

[0844] A processing execution means that automatically executes the reservation process based on the priority determination means,

[0845] A means of notifying the user whether the reservation process was successful or not,

[0846] If the aforementioned reservation process is unsuccessful, a candidate presentation means for providing alternative reservation candidates that take into account the user's feelings,

[0847] A system that includes this.

[0848] (Claim 2)

[0849] The system according to claim 1, wherein the processing execution means automatically makes suggestions desirable to the user based on the user's real-time emotions before the reservation is confirmed.

[0850] (Claim 3)

[0851] The system according to claim 1, wherein the candidate suggestion means generates guidance to provide alternatives that take into account and reflect the user's feelings when a reservation is not made. [Explanation of Symbols]

[0852] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for users to input their desired reservation conditions, An analysis means that automatically analyzes multiple reservation targets based on the desired conditions received from the information input means, A reservation execution means that automatically executes the reservation process based on the results of the analysis performed by the aforementioned analysis means, A notification method to determine whether the reservation process was successful or not and notify the user, If the aforementioned reservation process is unsuccessful, a means for presenting options to the user to offer alternative reservation candidates, A specialized tool for managing and automating the booking of security-related events and programs, A system that includes this.

2. The system according to claim 1, wherein the reservation execution means continuously monitors the availability of the reservation target in order to satisfy the reservation conditions, including the waiting list.

3. The system according to claim 1, wherein the option presentation means generates other candidates based on the user's desired conditions and presents them to the user.

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