Recommendation system, recommendation system program

Abstract

To provide a recommendation system that enables users to easily understand the appeal of proposed content. [Solution] The recommendation system 100 comprises a user terminal 110 and a server 120, and when a predetermined operation requesting a recommendation is performed on the user terminal, a recommendation means on the user terminal or server uses pre-trained artificial intelligence means to generate a sentence about an activity theme based on pre-entered user attribute information, selects a destination and a means of transportation that matches the sentence about the activity theme from the server's database 121, generates course name text for the course name using the pre-trained artificial intelligence means based on the selected destination information and travel route information for the travel means, and displays the generated course name text CS, destination information DN, and travel route information RT on the user terminal 110.

Description

[Technical Field]

[0001] The present invention relates to a recommendation system that includes a user terminal and a server and recommends destinations to users, and a program for the system. [Background technology]

[0002] Conventionally, a recommendation system is known that takes into consideration the preferences of a user and makes suggestions suited to the user's current situation (for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-129411 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the conventional recommendation systems mentioned above were only able to provide fragmented location and activity suggestions, and therefore were unable to adequately convey the appeal of the suggestions.

[0005] Therefore, the present invention solves the problems of the prior art as described above, that is, the object of the present invention is to provide a recommendation system and a program therefor that allow users to easily understand the appeal of the proposed content. [Means for solving the problem]

[0006] The invention of claim 1 is a recommendation system that includes a user terminal and a server and recommends destinations to a user, and when a predetermined operation requesting a recommendation is performed on the user terminal, the recommendation means in the user terminal or server uses pre-trained artificial intelligence means to generate a sentence about an activity theme based on pre-entered user attribute information, selects a destination and a means of transportation that matches the sentence about the activity theme from the server's database, generates course name text about a course name based on the selected destination information and travel route information for the selected means of transportation using the pre-trained artificial intelligence means, and displays the generated course name text, destination information, and travel route information on the user terminal. This solves the above-mentioned problems.

[0007] The invention of claim 2 further solves the above-mentioned problem by being configured such that, in addition to the configuration of the recommendation system described in claim 1, when the recommendation means generates course name text data for the course name using the pre-trained artificial intelligence means, it generates a story text with an introduction, development, twist, and conclusion using the pre-trained artificial intelligence means based on the selected destination information and travel route information by the means of transportation, and displays the generated story text on the user terminal.

[0008] The invention of claim 3 further solves the above-mentioned problem by, in addition to the configuration of the recommendation system described in claim 2, having the recommendation means select multiple sets of destinations and means of transportation that are in line with the sentences of the activity theme from a database on a server, and generate course name text and story text with an introduction, development, twist, and conclusion for the course name using pre-trained artificial intelligence means based on the multiple sets of selected destination information and travel route information by the travel route, and display each generated course name text, generated story text, destination information, and travel route information on the user terminal.

[0009] The invention of claim 4 further solves the above-mentioned problem by, in addition to the configuration of the recommendation system described in claim 3, displaying an icon for the destination and the travel route on a map when the destination information and travel route information are displayed on a user terminal, and the content of the icon includes story content about the destination corresponding to the icon in the generated story text.

[0010] The invention of claim 5 further solves the above-mentioned problem by, in addition to the configuration of the recommendation system described in claim 4, having the user terminal display story content regarding the destination corresponding to the icon in the generated story text when the icon is selected.

[0011] The invention of claim 6 further solves the above-mentioned problem by being configured such that, in addition to the configuration of the recommendation system described in any one of claims 1 to 5, when an operation to change, delete, or cancel schedule information is performed on the user terminal, the recommendation means on the user terminal or server searches for available information in the user's schedule information, and if available information is detected, generates a sentence about the activity theme using pre-trained artificial intelligence means based on the length of the available time information.

[0012] The invention of claim 7 further solves the above-mentioned problem by being configured such that, in addition to the configuration of the recommendation system described in any one of claims 1 to 5, when an operation to launch an arbitrary application is performed on the user terminal, if the recommendation means in the user terminal or server detects a change in the operation to launch an arbitrary application that is greater than a predetermined early timing change amount relative to the daily log information on the user terminal, the recommendation means generates a sentence about the behavioral theme using a pre-trained artificial intelligence means based also on the change amount of the operation to launch the arbitrary application.

[0014] This claim 8The invention relates to a program for a recommendation system that recommends destinations to a user, and solves the above-mentioned problem by causing a recommendation means in the user terminal or server to execute the following steps when a predetermined operation requesting a recommendation is performed on the user terminal: an action theme generation step in which a sentence about an action theme is generated using pre-trained artificial intelligence means based on pre-entered user attribute information; a destination / means of transportation selection step in which a destination and means of transportation that are consistent with the sentence about the action theme are selected from a server database; a course name generation step in which a course name text about a course name is generated using pre-trained artificial intelligence means based on the selected destination information and travel route information by the travel means; and a recommendation display step in which the generated course name text, destination information, and travel route information are displayed on the user terminal. [Effects of the Invention]

[0015] The recommendation system of the present invention is equipped with a user terminal and a server, which not only enables the user terminal to communicate with the server, but also provides the following unique effects.

[0016] According to the recommendation system of the invention of claim 1, when destination information and travel route information are displayed as suggestions on a user terminal, the generated course name text based on this destination information and travel route information is displayed as a consistent theme title, so that the user can easily understand the appeal of the proposed content from the generated course name text, which is a consistent theme title. This makes it easier for users to take action based on the suggestions, and they can feel a sense of excitement from the moment they start taking action.

[0017] According to the recommendation system of the invention of claim 2, in addition to the effects achieved by the invention of claim 1, generated story text with a specific beginning, development, climax and conclusion that is based on not only the theme title of the generated course name text data but also destination information and travel route information by means of transportation is displayed on the user's terminal, allowing the user to understand the story of the proposed content from the generated story text and to gain a deeper understanding of the appeal of the proposed content.

[0018] According to the recommendation system of the invention of claim 3, in addition to the effect achieved by the invention of claim 2, multiple generated course name texts and generated story texts are displayed as suggestions on the user's terminal, allowing the user to compare and select the generated course name texts and generated story texts that interest them from the options. In other words, not only multiple destinations and travel routes but also multiple generated course name texts and generated story texts are displayed, so rather than simply comparing destinations, users can compare and select the excitement they get from the generated course name texts and generated story texts about destinations and means of transportation that are in line with the activity theme.

[0019] According to the recommendation system of the invention of claim 4, in addition to the effect of the invention of claim 3, the content of the icon indicates what part of the destination is related to the content of the generated story text, so that the user can easily visually understand the relationship between the content of the generated story text and the destination.

[0020] According to the recommendation system of the invention of claim 5, in addition to the effect achieved by the invention of claim 4, parts corresponding to the icons of the introduction, development, twist, and conclusion in the generated story text are displayed, so that the user can easily understand the story of the introduction, development, twist, and conclusion by switching between icon selections, and can gain a deeper understanding of the appeal of the proposed content by matching it with the order of the story.

[0021] According to the recommendation system of the invention of claim 6, in addition to the effects achieved by the invention of any one of claims 1 to 5, when a free time occurs in the user's schedule, an activity theme is generated based on the length of the free time information, and a destination and means of transportation are selected and displayed as a suggestion on the user's terminal along with the generated course name text, allowing the user to make effective use of the free time in their schedule.

[0022] According to the recommendation system of the invention of claim 7, in addition to the effects of the invention of any one of claims 1 to 5, if the user performs an operation to launch an arbitrary application at a timing earlier than the usual time by a predetermined time or more based on the user's daily log, it is determined that free time has occurred, and an action theme is generated based on the amount of change in the operation to launch the arbitrary application, and a destination and means of transportation are selected and displayed as a suggestion on the user's terminal along with the generated course name text, thereby allowing the user to make effective use of free time in their schedule.

[0024] This claim 8 According to the program of the recommendation system of the invention, similar to the effect achieved by the invention of claim 1, when destination information and travel route information are displayed as suggestions on a user terminal, the generated course name text based on this destination information and travel route information is displayed as a consistent theme title, so that the user can easily understand the appeal of the proposed content from the generated course name text, which is a consistent theme title. This makes it easier for users to take action based on the suggestions, and they can feel a sense of excitement from the moment they start taking action. [Brief explanation of the drawings]

[0025] [Figure 1] FIG. 1 is a diagram showing the concept of a recommendation system according to an embodiment of the present invention. [Figure 2] FIG. 1 is a chart showing an example of the operation of a recommendation system according to an embodiment of the present invention. [Figure 3] FIG. 1 is a diagram showing a My Page screen of a recommendation system according to an embodiment of the present invention. [Figure 4] FIG. 10 is a diagram showing a "Your Mood" screen of the recommendation system according to an embodiment of the present invention. [Figure 5] FIG. 1 is a diagram showing a search screen of a recommendation system according to an embodiment of the present invention. [Figure 6] FIG. 10 is a diagram showing an example of data for generating an action theme of a recommendation system according to an embodiment of the present invention. [Figure 7] 1A and 1B are diagrams showing an example of a template for an action theme of a recommendation system according to an embodiment of the present invention, and an example of information inserted into the template. [Figure 8] 1A and 1B are diagrams showing examples of recommendation displays of a recommendation system according to an embodiment of the present invention. [Figure 9] FIG. 1 is a diagram showing an example of a recommendation display of a recommendation system according to an embodiment of the present invention. [Figure 10] 1A and 1B are diagrams showing examples of input data of a recommendation system according to an embodiment of the present invention, examples of generated course name text, examples of generated story text with an introduction, development, twist, and conclusion, and examples of generation reason explanation text. [Figure 11] FIG. 10 is a diagram showing an example of a pop-up display when a change of more than a predetermined early timing change amount is detected in the operation of launching an arbitrary application in the log information of a user terminal of a recommendation system that is an embodiment of the present invention. [Figure 12] FIG. 10 is a diagram showing an example of a pop-up display when free time information is searched for in a user's schedule information on the schedule screen of a user terminal of a recommendation system according to an embodiment of the present invention, and free time information is detected. DETAILED DESCRIPTION OF THE INVENTION

[0026] The recommendation system of the present invention comprises a user terminal and a server, and when a predetermined operation requesting a recommendation is performed on the user terminal, the recommendation means on the user terminal or server uses pre-trained artificial intelligence means to generate a sentence about an action theme based on pre-input user attribute information, selects a destination or service and means of transportation that matches the sentence about the action theme from the server's database, generates course name text for the course name using pre-trained artificial intelligence means based on the selected destination information or service information and travel route information by the travel means, and displays the generated course name text, destination information or service information, and travel route information on the user terminal.The specific implementation of the system is not limited to any one, as long as the user can easily understand the appeal of the proposed content from the generated course name text, which is a consistent theme title. Furthermore, in the recommendation system of the present invention, when a predetermined operation requesting a recommendation is performed on a user terminal, the recommendation means on the user terminal or server uses pre-trained artificial intelligence means to generate a sentence about the activity theme based on the user's attribute information input in advance, selects a destination or service and a means of transportation that matches the activity theme sentence from the server's database, and displays the activity theme sentence, destination information or service information, and transportation route information on the user terminal, allowing the user to easily understand the appeal of the proposed content from the activity theme, which has a consistent theme title. Furthermore, the program of the recommendation system of the present invention, when a predetermined operation requesting a recommendation is performed on a user terminal, executes the following steps on the user terminal or server: an action theme generation step in which a recommendation means generates a sentence about an action theme using pre-trained artificial intelligence means based on pre-entered user attribute information; a destination / means of transportation selection step in which a destination or service and means of transportation that align with the sentence about the action theme are selected from the server's database; a course name generation step in which a course name text about a course name is generated using pre-trained artificial intelligence means based on the selected destination information or service information and travel route information by the travel means; and a recommendation display step in which the generated course name text, destination information or service information, and travel route information are displayed on the user terminal.The specific implementation of the program is not limited to this, as long as the user can easily understand the appeal of the proposed content from the generated course name text, which is a consistent theme title.

[0027] For example, the user terminal may be any device that has a display and an operating unit and can send and receive information, such as a notebook-type personal computer terminal, a smartphone terminal, a tablet terminal, a wristwatch-type terminal, or an eyeglass-type terminal, and can be freely connected to a server via a communication network including a wide area network such as the Internet, a local network, or a telephone line. Furthermore, the server may be a cloud server created in a cloud environment, and the number of physical servers that make up the server may be one or more. Furthermore, the pre-trained artificial intelligence means may be composed of a text generation means that generates text data, such as an interactive ChatGPT (Generative Pre-trained Transformer) (hereinafter referred to as ChatGPT), which is also called a large-scale language model, an image generation means that generates image data such as photographs, illustrations, and videos, or a voice generation means that generates voice data, and may be configured to be installed on one server or multiple servers on the cloud. [Example]

[0028] A recommendation system 100 according to an embodiment of the present invention will be described below with reference to FIGS. 1 is a diagram showing the concept of a recommendation system 100 according to an embodiment of the present invention, FIG. 2 is a chart showing an example of the operation of the recommendation system 100 according to an embodiment of the present invention, FIG. 3 is a diagram showing a My Page screen 112 of the recommendation system 100 according to an embodiment of the present invention, FIG. 4 is a diagram showing a Your Mood screen 113 of the recommendation system 100 according to an embodiment of the present invention, FIG. 5 is a diagram showing a search screen 114 of the recommendation system 100 according to an embodiment of the present invention, FIG. 6 is a diagram showing an example of data for generating a behavioral theme AT of the recommendation system 100 according to an embodiment of the present invention, FIG. 7(A) is a diagram showing an example of a template of a behavioral theme AT of the recommendation system 100 according to an embodiment of the present invention, and FIG. 7(B) is a diagram showing an example of information inserted into the template, and FIGS. Figure 9 is a diagram showing an example of a recommendation display of the recommendation system 100, which is an embodiment of the present invention; Figure 10 is a diagram showing an example of input data of the recommendation system 100, which is an embodiment of the present invention, an example of generated course name text CS, an example of generated story text SR with an introduction, development, twist, and conclusion, and an example of generation reason explanation text RE; Figure 11 is a diagram showing an example of a pop-up display PP when a change of more than a predetermined early timing change amount is detected in the operation of launching an arbitrary application in the log information on the user terminal 110 of the recommendation system 100, which is an embodiment of the present invention; and Figure 12 is a diagram showing an example of a pop-up display PP when availability information is searched for in the user's schedule information on the schedule screen 117 of the user terminal 110 of the recommendation system 100, which is an embodiment of the present invention, and availability information is detected.

[0029] As shown in FIG. 1, a recommendation system 100 according to an embodiment of the present invention includes a user terminal 110 and a server 120. The user terminal 110 is provided so as to be able to communicate freely with the server 120 . The server 120 includes a database 121 . The recommendation system 100 is configured to recommend destinations to users based on a database 121 that registers the latest information on products, services, locations, etc. input from a store terminal (not shown).

[0030] More specifically, first, the user logs in to the recommendation system 100 using the user terminal 110 . The user then inputs the user's attribute information US and preference information LK in advance. For example, on a user registration screen (not shown) of the recommendation system 100 displayed on the display unit 111 of the user terminal 110, the user inputs and registers the user's attribute information US in an input field.

[0031] In addition, the "Favorite Things" screen (not shown) of the recommendation system 100 displayed on the display unit 111 of the user terminal 110 has categories such as gourmet, cafes, outdoors, shopping, going out, entertainment, fashion, and indoors, and within each category, multiple photos of content related to that category are displayed. The user then selects one or more photos that show something they like. Each photo is tagged with information that indicates what is shown in the photo. When a photo is selected by the user, the tag information of the selected photo is added as preference information LK, which is information about the user's favorite things.

[0032] The user may also select icons, keywords, sounds, etc. in addition to photos. Icons, keywords, and sounds represent something. In the case of audio, a button is displayed so that when the button is operated, something is output as audio, and when the button is selected, tag information of the button content is added as preference information LK. In addition, the user may use the microphone on the user terminal 110 to input voice input about what they like, or may use the input keys to input text about what they like in sentences or words, and this information may be added as preference information LK.

[0033] Furthermore, a "Your Personality" screen (not shown) of the recommendation system 100 displayed on the display unit 111 of the user terminal 110 includes a plurality of simple questions. For example, questions include, "I like meeting new people and can enjoy conversations with people even when meeting them for the first time." As an example, the system is designed so that users can intuitively answer each question using a five-point scale, such as completely not applicable, hardly applicable, neither applicable nor unapplicable, somewhat applicable, or completely applicable. When the user inputs these answers, a recommendation means having artificial intelligence in the user terminal 110 or the server 120 analyzes the answer information and obtains user type tendency information TP.

[0034] It is assumed that an operation for requesting a recommendation is then performed as a predetermined operation. Here, operations to request a recommendation include launching the recommendation system 100 app on the user terminal 110, operating the "Leave it to AI" button 114a described below, or inputting the user's current situation information ST. Then, when an operation to request a recommendation is performed as a predetermined operation, the recommendation means in the user terminal 110 or the server 120 generates a sentence about the behavioral theme AT using a pre-trained artificial intelligence means based on at least the user's attribute information US that has been input in advance.

[0035] Furthermore, the recommendation means selects a destination and a means of transportation that are in line with the sentence of the activity theme AT from the database 121 of the server 120. Next, the recommendation means generates a course name text for the course name using the pre-trained artificial intelligence means based on the selected destination information DN and travel route information RT by the travel means. The recommendation means is configured to display the generated course name text CS, the destination information DN, and the travel route information RT on the display unit 111 of the user terminal 110.

[0036] As a result, when the destination information DN and travel route information RT are displayed as suggestions on the user terminal 110, the generated course name text CS based on this destination information DN and travel route information RT is displayed as a consistent theme title. As a result, users can easily understand the appeal of the proposed content from the generated course name text CS, which is a consistent theme title. Users are then more likely to be motivated to take action based on the suggestions. As a result, users can feel a sense of excitement from the moment they start taking action.

[0037] Next, the operation of the recommendation system 100 will be described in detail. As shown in FIG. 2, in step S1, as a step of determining whether or not a recommendation request operation has been performed as a predetermined operation, the user terminal 110 or the server 120 determines whether or not an operation requesting a recommendation has been performed as the predetermined operation described above. As mentioned above, operations to request recommendations as a predetermined operation include launching the recommendation system 100 app, operating the "Leave it to AI" button 114a described below, or inputting the user's current situation information ST.

[0038] Here, before performing the operation to request recommendations, the user registers by entering the user's attribute information US in the input field on the user registration screen (not shown) of the recommendation system 100 displayed on the display unit 111 of the user terminal 110. Furthermore, the user may select a photo on the "Favorite Things" screen described above, for example. Then, the user terminal 110 or the server 120 registers the user's preference information LK in the database 121 in the server 120.

[0039] Then, as shown in FIG. 3, once the user's preference information LK is registered, the user's preference information LK is displayed on a My Page screen 112 of the recommendation system 100 displayed on the display unit 111 of the user terminal 110. More specifically, the tag information of the photograph selected by the user is registered as the preference information LK, and the tag information is displayed in the "Favorite things and events" section.

[0040] In addition, the recommendation means may be configured to display the user type tendency information TP obtained based on the answer information provided on the aforementioned ``Your Personality'' screen (not shown) in the ``Your Personality'' section of the My Page screen 112. As an example, the user type tendency information TP has items such as openness, conscientiousness, extroversion, agreeableness, and neuroticism, and is configured to be displayed as a level value for each item. The user type tendency information TP is configured to be registered in the database 121 in the server 120, similar to the user preference information LK.

[0041] Then, as an example of the operation for requesting a recommendation as a predetermined operation, the user terminal 110 or the server 120 determines whether or not the user has performed an operation to input the current situation information ST of the user in the user terminal 110. For example, as shown in FIG. 4, the user's current situation information ST is freely inputtable on the "Your Mood" screen 113 of the recommendation system 100 displayed on the display unit 111 of the user terminal 110.

[0042] The "Your Mood" screen 113 has fields for inputting information about people you are with, free time information, appetite and material desire information, and activity and rest desire information. For example, in the section about information about people you are with, options such as alone, couple, friends, and family are set to indicate whether you are alone or who you are with. Furthermore, the item of free time information is provided so that the current amount of free time can be freely input. In addition, for the appetite and material desire information items, you can freely input which of the following is given more weight. Furthermore, for the active / rest desire information items, you can freely input which of the two you would like to prioritize. When an input operation is performed on these items, the user terminal 110 or the server 120 determines that the user's current situation information ST has been input.

[0043] Also, as shown in Figure 5, as an example of an operation to request recommendations as a specified operation, the user terminal 110 or the server 120 may determine whether or not the "Leave it to AI" button 114a displayed on the search screen 114 of the recommendation system 100 of the user terminal 110 has been operated. If it is determined that an operation for which a recommendation is requested has been performed, the process proceeds to step S2, and if it is determined that no operation has been performed yet, step S1 is repeated.

[0044] In step S2, as an action theme generation step, the recommendation means in the user terminal 110 or the server 120 generates sentences about the action theme AT using pre-trained artificial intelligence means based on at least the user attribute information US input in advance. Here, as shown in FIG. 6, the data used to generate the behavioral theme AT may include preference information LK about hobbies and preferences entered on the My Page screen 112 in FIG. 3, situation information ST entered on the Your Mood screen 113 in FIG. 4, comment information entered by the user in chat or the like on a social networking service (SNS), location information of the user terminal 110 from a Global Positioning System (GPS), log information about the operation and location of the user terminal 110, and information entered via the user terminal 110, such as vital information such as heart rate, blood pressure, and sleep status obtained from a watch-type terminal worn on the user's wrist, etc.

[0045] In addition, external environment information EF, which is external environment data such as coupon information for any spot, information on means of transportation, traffic congestion information, store congestion information, event information such as concerts, and weather information, may be used as data for generating behavioral themes AT. Furthermore, as data for generating the behavioral theme AT, training data using collaborative filtering technology or statistical analysis technology, such as spot matching trend data that accumulates previous recommendation information and user satisfaction information (feedback information), may be used.

[0046] We explain the generation of behavioral themes AT. Here, the behavioral theme AT refers to an expression of what kind of person is considering a destination and a means of transportation under what conditions. For example, as shown in Figure 7(A), weather information, transportation information, hobby and preference information LK, vital signs information, situation information ST that represents your mood, and user attribute information US may be inserted into a template, and a sentence about an action theme AT may be generated using a pre-trained artificial intelligence means.

[0047] More specifically, as shown in Figure 7(B), the recommendation means may insert weather information, transportation information, hobby and preference information LK, vital signs information, situation information ST (your mood), and user attribute information US into a template, and generate sentences about the behavioral theme AT using a pre-trained artificial intelligence means. As an example, by inserting each piece of information as shown in Figure 7(B) into the template shown in Figure 7(A), a sentence is generated for the behavioral theme AT, stating, "In the weather forecast, there is a 50% chance of rain, a person with the user attributes of a 'female office worker in her 30s' who is a type who 'likes emotional expressions' and tends to 'like castles' is considering a destination and mode of transportation when she feels like 'relaxing for about three hours' in an area where 'there is data on spots that can be enjoyed even on rainy days', and has the option of 'walking or train' for transportation."

[0048] Although the sentences about the behavioral theme AT are generated using the template, it goes without saying that the sentences about the behavioral theme AT may be generated without using the template. Here, the reason for using a template as an example is that by using a template, the format of the text about the behavioral theme AT is established. As a result, when selecting candidate destinations and modes of transportation in the next step, the accuracy of the generated sentences about the action theme AT can be improved when vectorized as an example, thereby improving the accuracy of selection and making suggestions that suit the user.

[0049] In step S3, as a destination and transportation means selection step, the recommendation means selects a destination and transportation means that are in line with the sentence of the activity theme AT from the database 121 of the server 120. In this case, the recommendation means uses an estimation model, which is a concept of technical idea, to estimate that the user will be satisfied by providing an output in response to the input, for example, having a relationship between output information such as destination information DN and transportation information corresponding to input information such as the user's attribute information US, situation information ST, and preference information LK, and selects a destination and transportation method that are in line with the text of the behavioral theme AT from the database 121 of the server 120. In order to improve the accuracy of the output when making this selection, as one example, the text about the generated behavioral theme AT may be vectorized (embedding process).

[0050] In step S4, as a course name generation step, the recommendation means generates a course name text for the course name using the pre-trained artificial intelligence means based on the selected destination information DN and travel route information RT by the travel means. For example, based on the destination information DN and the travel route information RT by means of transportation, a "Temple of the atmosphere of XX course," a "Sweets and walking course," a "Shopping course in the early morning sky," etc. are generated.

[0051] Although the order of generating the action theme AT, selecting the destination and transportation means, and generating the course name was carried out, this is not limited to this. After generating the activity theme AT, a course name may be generated based on the activity theme AT, and a destination and a means of transportation may be selected based on the course name. In addition, the action theme AT may be generated by including the course name, and the destination and the means of transportation may be selected based on this.

[0052] In step S5, as a recommendation display step, the recommendation means displays the generated course name text CS, the destination information DN, and the travel route information RT on the user terminal 110. More specifically, as shown in Figures 8(A) to 9, the recommendation means displays the generated course name text CS, such as "XX Temple Style Course," "Sweets and Walking Course," or "Morning Sky Shopping Course," as well as the destination information DN and travel route information RT on the recommendation display screen 115 of the display unit 111 of the user terminal 110.

[0053] As a result, as described above, when the destination information DN and travel route information RT are displayed as suggestions on the user terminal 110, the generated course name text CS based on this destination information DN and travel route information RT is displayed as a consistent theme title. As a result, users can easily understand the appeal of the proposed content from the generated course name text CS, which is a consistent theme title. Users are then more likely to be motivated to take action based on the suggestions. As a result, users can feel a sense of excitement from the moment they start taking action.

[0054] Furthermore, in this embodiment, when the recommendation means generates course name text data for the course name using a pre-trained artificial intelligence means, it generates a story text with an introduction, development, twist, and conclusion using the pre-trained artificial intelligence means based on the selected destination information DN and travel route information RT by the travel means, and is configured to display the generated story text SR on the recommendation display screen 115 of the display unit 111 of the user terminal 110.

[0055] More specifically, as shown in FIG. 10, the user's attribute information US includes information such as "resident of Fukuoka city, 42 years old, sales position, arrives at work at 10:00, arrives at Hakata Station at 7:30 in the morning, and usually goes straight to work." Furthermore, the situation information ST includes information such as "Mood this morning: A little tired. Yesterday I worked overtime until late at night for an internal meeting." Additionally, vital signs log information includes information such as "the number of steps taken recently has been low and there are concerns about his health."

[0056] Furthermore, the weather information includes information such as "sunny, temperature 22°C." Additionally, the current available time information is "Wednesday 8:00-10:00." Then, it is assumed that the recommendation means generates a generated course name text CS to the effect of "A morning course to relax with a short natural bath" using the pre-trained artificial intelligence means. In this case, as an example, the recommendation means uses a pre-trained artificial intelligence means to generate a generated story text SR that includes the following: "Introduction: Experience a little greenery at Sumiyoshi Shrine near Hakata Station," "Development: Suggest a bus that runs along the Naka River (to get a glimpse of nature) (means of transportation)," "Turnaround: Have a snack at a bakery with benches," and "Conclusion: Go to work via an empty terrace in the Canal City shopping complex." The generated story text SR is displayed, for example, in a detail display window WD of the recommendation display screen 115 shown in FIGS. 8(A) to 9. FIG.

[0057] As a result, the generated story text SR with a specific beginning, development, twist and conclusion, which is fitted with not only the theme title of the data of the generated course name text CS but also the destination information DN and the travel route information RT by means of transportation, is displayed on the user terminal 110. As a result, the user can understand the story of the proposal content from the generated story text SR and gain a deeper understanding of the appeal of the proposal content.

[0058] When the recommendation means generates the generated course name text CS, the pre-trained artificial intelligence means may be used to generate a reason explanation text in natural language. For example, as shown in Figure 10, the recommendation means uses a pre-trained artificial intelligence means to generate a generation reason explanation text RE that states, "Considering the fatigue from working overtime last night, travel is limited to a 10-minute walk. The route is designed to allow you to feel nature and tranquility, so that you can start your day in a positive way." Then, the recommendation means displays the creation reason explanation text RE on the recommendation display screen 115 of the display unit 111 of the user terminal 110. The creation reason explanation text RE is displayed, for example, in a detail display window WD of the recommendation display screen 115 shown in FIGS. 8(A) to 9. FIG.

[0059] As a result, when the destination information DN and the travel route information RT are displayed as a proposal on the user terminal 110, the generation reason explanation text RE based on the destination information DN and the travel route information RT is displayed. As a result, the user can easily understand the reason for the recommendation from the generation reason explanation text RE, which is the reason for the recommendation, and can trust, be convinced, and be satisfied. Users are then more likely to be motivated to take action based on the suggestions. As a result, user acceptance can be increased.

[0060] In this embodiment, the recommendation means selects a plurality of sets of destinations and means of transportation that are in line with the sentences in the activity theme AT from the database 121 of the server 120 . Furthermore, the recommendation means generates course name text for the course name and story text with an introduction, development, twist, and conclusion using the pre-trained artificial intelligence means based on the multiple sets of selected destination information DN and travel route information RT by travel means. As shown in Figures 8(A) to 9, the recommendation means may be configured to display each generated course name text CS, generated story text SR, destination information DN, and travel route information RT on a recommendation display screen 115 of the display unit 111 of the user terminal 110.

[0061] As a result, a plurality of generated course name texts CS and generated story texts SR are displayed on the user terminal 110 as suggestions. As a result, the user can compare and select the generated course name text CS and generated story text SR that interest them from the options. That is, not only a plurality of destinations and travel routes but also a plurality of generated course name texts CS and generated story texts SR are displayed. As a result, rather than simply comparing destinations, users can compare and select destinations and means of transportation that are in line with the action theme AT, based on the sense of excitement they get from the generated course name text CS and generated story text SR.

[0062] Furthermore, in this embodiment, as shown in Figures 8(A) to 9, when the destination information DN and travel route information RT are displayed on the recommendation display screen 115 of the display unit 111 of the user terminal 110, an icon IC for the destination and the travel route are displayed on the map. The content of the icon IC may be configured to include story content relating to the destination corresponding to the icon IC in the generated story text SR. Regarding the contents of the icon IC, the recommendation means may generate them using an image generation means that generates image data such as photographs, illustrations, and videos, which is an example of a pre-trained artificial intelligence means, or may be configured to display the icon IC based on image data on the Internet. This allows the contents of the icon IC to indicate what is relevant to the content of the generated story text SR at the destination. As a result, users can visually and easily understand the relationship between the content of the generated story text SR and the destination.

[0063] In this embodiment, when the icon IC is selected, the user terminal 110 may be configured to display on the recommendation display screen 115 the story content relating to the destination corresponding to the icon IC in the generated story text SR. As a result, a part corresponding to the introduction, development, turn, and conclusion icons IC in the generated story text SR is displayed. As a result, users can easily understand the story's beginning, development, twist, and conclusion by switching between icon IC selections, and can gain a deeper understanding of the appeal of the proposed content by matching it with the order of the story. It should be noted that the recommendation means may be configured to generate image data for the content of the generated story text SR using the image generation means, and display the image data on the recommendation display screen 115 or the detailed display window WD.

[0064] Furthermore, in this embodiment, as shown in FIG. 11, when an operation to start an arbitrary application is performed on the user terminal 110 as an example of a predetermined operation, the user terminal 110 starts the arbitrary application and displays the arbitrary application screen 116. At this time, in the user terminal 110 or the server 120, when the recommendation means detects a change of more than a predetermined early timing change amount in the operation of launching an arbitrary application as an example of a predetermined operation for daily log information in the user terminal 110, the recommendation means is configured to generate a sentence about the behavioral theme AT using the pre-trained artificial intelligence means based also on the change amount of the operation of launching the arbitrary application.

[0065] More specifically, when a change equal to or greater than a predetermined early timing change amount is detected in the launch operation of an arbitrary application as an example of a predetermined operation, the user terminal 110 displays a pop-up PP on the display unit 111, for example, saying, "Hello! It's an hour earlier than usual! Would you like to take an hour to change your mood?" When this pop-up display PP is operated, it is determined that this is the predetermined operation for requesting a recommendation in step S1 described above, and the recommendation means generates a sentence about the action theme AT. Subsequently, the user terminal 110 or the server 120 executes steps S2 to S5.

[0066] As a result, if an operation to start an arbitrary application is performed at a timing earlier than the normal time by a predetermined time or more based on the user's daily log, it is determined that free time has occurred, and an action theme AT is generated based on the amount of change in the operation to start the arbitrary application, and a destination and means of transportation are selected and displayed as a proposal on the user terminal 110 together with the generated course name text CS. As a result, users can make effective use of free time in their schedules.

[0067] In this embodiment, as shown in FIG. 12, it is assumed that an operation to arbitrarily change, delete, or cancel a schedule on the schedule screen 117 is performed as an example of a predetermined operation on the user terminal 110. At this time, in the user terminal 110 or the server 120, the recommendation means searches for free time information in the user's schedule information, and if free time information is detected, it is configured to generate a sentence about the behavioral theme AT using a pre-trained artificial intelligence means based on the length of the free time information.

[0068] More specifically, an example of a predetermined operation is an operation to arbitrarily change, delete, or cancel a schedule on the schedule screen 117, and the recommendation means searches for available information in the user's schedule information, and when available information is detected, the user terminal 110 displays a pop-up PP on the display unit 111, for example, saying, "Hello! You have about two hours free! Would you like to take a break for about 1.5 hours?" When this pop-up display PP is operated, it is determined that this is the predetermined operation for requesting a recommendation in step S1 described above, and the recommendation means generates a sentence about the action theme AT. Subsequently, the user terminal 110 or the server 120 executes steps S2 to S5.

[0069] As a result, when a free time occurs in the user's schedule, an action theme AT is generated based on the length of free time information, a destination and a means of transportation are selected, and are displayed as a proposal on the user terminal 110 together with the generated course name text CS. As a result, users can make effective use of free time in their schedules.

[0070] The recommendation system 100, an embodiment of the present invention obtained in this manner, comprises a user terminal 110 and a server 120. When a predetermined operation requesting a recommendation is performed on the user terminal 110, a recommendation means in the user terminal 110 or the server 120 uses pre-trained artificial intelligence means to generate a sentence about the action theme AT based on the user's attribute information US input in advance, selects a destination and means of transportation that are consistent with the sentence about the action theme AT from the database 121 of the server 120, generates course name text for the course name using pre-trained artificial intelligence means based on the selected destination information DN and travel route information RT using the selected means of transportation, and displays the generated course name text CS, destination information DN, and travel route information RT on the user terminal 110. This allows the user to easily understand the appeal of the proposed content from the generated course name text CS, which is a consistent theme title, and the user can feel a sense of excitement from the moment they start their action.

[0071] Furthermore, when the recommendation means generates course name text data for the course name using a pre-trained artificial intelligence means, it generates a story text with an introduction, development, twist, and conclusion using the pre-trained artificial intelligence means based on the selected destination information DN and travel route information RT by the travel means, and displays the generated story text SR on the user terminal 110, allowing the user to understand the story nature of the proposed content from the generated story text SR and gain a deeper understanding of the appeal of the proposed content.

[0072] In addition, the recommendation means selects multiple sets of destinations and means of transportation that are in line with the text of the action theme AT from the database 121 of the server 120, and generates course name text for the course name and story text with an introduction, development, twist, and conclusion using pre-trained artificial intelligence means based on the multiple sets of selected destination information DN and travel route information RT by the travel route, and displays each generated course name text CS, generated story text SR, destination information DN, and travel route information RT on the user terminal 110, allowing the user to compare and select the generated course name text CS and generated story text SR that interest them from the options, and not simply compare destinations, but compare and select the sense of excitement that can be obtained from the generated course name text CS and generated story text SR for destinations and means of transportation that are in line with the action theme AT.

[0073] Furthermore, when the destination information DN and travel route information RT are displayed on the user terminal 110, an icon IC for the destination and the travel route are displayed on a map, and the content of the icon IC includes the story content for the destination corresponding to the icon IC in the generated story text SR, allowing the user to visually and easily understand the relationship between the content of the generated story text SR and the destination.

[0074] Furthermore, when an icon IC is selected, the user terminal 110 displays the story content relating to the destination corresponding to the icon IC in the generated story text SR, allowing the user to easily understand the story's beginning, development, twist, and conclusion by switching the icon IC selection, and to understand more deeply the appeal of the proposed content by matching it with the order of the story.

[0075] Furthermore, when an operation to change, delete, or cancel schedule information is performed on the user terminal 110, the recommendation means on the user terminal 110 or the server 120 searches for available time information in the user's schedule information, and if available time information is detected, the recommendation means uses pre-trained artificial intelligence means to generate a sentence about the action theme AT based on the length of the available time information, thereby allowing the user to make effective use of available time in their schedule.

[0076] In addition, when an operation to launch an arbitrary application is performed on the user terminal 110, if the recommendation means on the user terminal 110 or the server 120 detects a change in the operation to launch an arbitrary application relative to the daily log information on the user terminal 110 that is greater than a predetermined early timing change amount, the recommendation means generates a sentence about the behavioral theme AT using a pre-trained artificial intelligence means based on the change amount of the operation to launch the arbitrary application, thereby allowing the user to make effective use of free time in their schedule.

[0077] Furthermore, the recommendation system 100, which is an embodiment of the present invention, comprises a user terminal 110 and a server 120, and when a predetermined operation requesting a recommendation is performed on the user terminal 110, the recommendation means in the user terminal 110 or the server 120 generates a sentence about the action theme AT using a pre-trained artificial intelligence means based on the user's attribute information US that has been input in advance, selects a destination and a means of transportation that matches the sentence about the action theme AT from the database 121 of the server 120, and displays the sentence about the action theme AT, the destination information DN, and the travel route information RT on the user terminal 110.This allows the user to easily understand the appeal of the proposed content from the consistent theme title of the action theme AT, and the user can feel excited from the moment they start the action.

[0078] Furthermore, the program of the recommendation system 100, which is an embodiment of the present invention, executes the following steps when a predetermined operation requesting a recommendation is performed on the user terminal 110: an action theme generation step S2 in which a recommendation means generates a sentence about an action theme AT using pre-trained artificial intelligence means based on the user's attribute information US input in advance on the user terminal 110; a destination / means of transportation selection step S3 in which a destination and means of transportation that are consistent with the sentence about the action theme AT are selected from the database 121 of the server 120; a course name generation step S4 in which a course name text about the course name is generated using pre-trained artificial intelligence means based on the selected destination information DN and travel route information RT using the travel route; and a recommendation display step S5 in which the generated course name text CS, destination information DN, and travel route information RT are displayed on the user terminal 110. By doing so, the user can easily understand the appeal of the proposed content from the generated course name text CS, which is a consistent theme title, and the user can feel a sense of excitement from the moment they start their action, which has enormous effects. [Explanation of symbols]

[0079] 100 ··· Recommendation System 110 User terminal 111... Display section 112 ··· My Page screen 113 ··· Your Mood Screen 114 ··· Search screen 114a··· "Leave it to AI" button 115 ··· Recommendation display screen 116 ··· Any app screen 117 ··· Schedule screen 120 Server 121 ··· Database PP ··· Pop-up display US ··· User demographic information ST: Situation information (situation information, physical condition information, mood information) LK...Preference information RT ··· Travel route information DN ··· Destination Information IC icon AT ··· Action Theme CS ··· Generate course name text SR ··· Generated story text TP User type trend information RE... Explanation of the reason for creation WD...Detailed View Window EF: External environmental information (external environmental data, weather information, traffic congestion information, traffic information)

Claims

1. A recommendation system that includes a user terminal and a server and recommends destinations to a user, A recommendation system characterized in that, when a predetermined operation requesting a recommendation is performed on the user terminal, a recommendation means on the user terminal or server uses pre-trained artificial intelligence means to generate a sentence about an activity theme based on pre-input user attribute information, selects a destination and means of transportation that match the sentence about the activity theme from the server's database, generates course name text for the course name using pre-trained artificial intelligence means based on the selected destination information and travel route information by the travel route, and displays the generated course name text, destination information, and travel route information on the user terminal.

2. The recommendation system described in claim 1 is characterized in that, when the recommendation means generates course name text data for a course name using the pre-trained artificial intelligence means, it generates a story text with an introduction, development, twist, and conclusion using the pre-trained artificial intelligence means based on the selected destination information and travel route information by the means of transportation, and displays the generated story text on the user terminal.

3. The recommendation system described in claim 2, characterized in that the recommendation means selects multiple sets of destinations and means of transportation that are in line with the sentences of the activity theme from the server's database, and uses pre-trained artificial intelligence means to generate course name text and story text with an introduction, development, twist, and conclusion for the course name based on the multiple sets of selected destination information and travel route information by the travel means, and displays each generated course name text, generated story text, destination information, and travel route information on the user terminal.

4. When the destination information and the travel route information are displayed on the user terminal, an icon for the destination and the travel route are displayed on a map; The recommendation system of claim 3 , wherein the content of the icon includes story content related to the destination corresponding to the icon in the generated story text.

5. The recommendation system of claim 4, characterized in that when the icon is selected, the user terminal displays story content regarding the destination corresponding to the icon in the generated story text.

6. A recommendation system as described in any one of claims 1 to 5, characterized in that when a change or deletion operation is performed on the user terminal for schedule information, a recommendation means on the user terminal or server searches for free time information in the user's schedule information, and if free time information is detected, generates a sentence about the activity theme using a pre-trained artificial intelligence means based also on the length of the free time information.

7. A recommendation system as described in any one of claims 1 to 5, characterized in that when an operation to launch an arbitrary application is performed on the user terminal, a recommendation means in the user terminal or server detects a change in the operation to launch an arbitrary application that is greater than a predetermined early timing change amount relative to the daily log information on the user terminal, and generates a sentence about the behavioral theme using a pre-trained artificial intelligence means based also on the change amount of the operation to launch the arbitrary application.

8. A program for a recommendation system that recommends destinations to users, an action theme generation step in which, when a predetermined operation for requesting a recommendation is performed on the user terminal, the recommendation means generates a sentence about an action theme using the pre-trained artificial intelligence means on the user terminal or the server based on the user's attribute information input in advance; a destination and transportation means selection step of selecting a destination and transportation means according to the sentence of the activity theme from a database of a server; a course name generation step of generating a course name text for the course name using the pre-trained artificial intelligence means based on the selected destination information and travel route information by the travel means; and a recommendation display step of displaying the generated course name text, destination information, and travel route information on the user terminal.

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