Storage medium, information processing method and information processing device

Abstract

A non-transitory computer-readable storage medium, an information processing method, and an information processing device. The storage medium stores a program executable by at least one processor of an information processing device, wherein the at least one processor is configured to obtain first state data indicating a state in which a first subject person uses a functional element realized by executing a target program, obtain estimation data for estimating information related to the functional element matching the first subject person based on the first state data obtained, according to a calculation model generated by machine learning based on at least one of second state data and the first state data previously saved, wherein the second state data indicates a state in which a second subject person different from the first subject person used the functional element in the past, and cause a prompting unit to prompt information related to the functional element based on the acquired estimation data.

Description

Technical Field

[0001] The present invention relates to a storage medium, an information processing method and an information processing device. Background Art

[0002] Japanese Patent Application Laid-Open No. 2011-238283 discloses a technique in which a plurality of process selection buttons and explanation buttons are displayed, a process to be executed is selected by pressing a process selection button, and an explanation of the process selection button is displayed together with the process selection button by pressing the explanation button. Summary of the invention

[0003] However, in the technology described in Japanese Patent Application Laid-Open No. 2011-238283, when the explanation button is pressed, an explanation screen showing explanations corresponding to all of the displayed multiple processing selection buttons is displayed superimposed on the processing selection screen. Therefore, sometimes unnecessary large amounts of explanation information are displayed to indicate the user's convenience, which is likely to be reduced.

[0004] A non-temporary computer-readable storage medium storing a program executable by at least one processor of an information processing device, the at least one processor being configured to obtain first state data indicating a state in which a first subject person used a functional element implemented by execution of an object program, and, based on the first state data obtained and a computational model generated by machine learning based on at least one of second state data and the first state data previously saved, obtain estimated data for estimating information related to the functional element matching the first subject person, wherein the second state data indicates a state in which a second subject person different from the first subject person used the functional element in the past, and, based on the estimated data obtained, cause a prompt unit to prompt information related to the functional element.

[0005] An information processing method for an information processing device, comprising: obtaining first state data representing a state in which a first subject used a functional element realized by executing an object program, and obtaining, based on the first state data obtained, in accordance with a computational model generated by machine learning based on second state data and at least one of the first state data saved in the past, estimated data for estimating information related to the functional element matching the first subject, wherein the second state data represents a state in which a second subject different from the first subject used the functional element in the past, and causing a prompt unit to prompt information related to the functional element based on the acquired estimated data.

[0006] An information processing device comprises at least one processor for executing a program stored in a storage unit, wherein the at least one processor is configured to obtain first state data indicating a state in which a first subject person used a functional element implemented by executing an object program, and obtain, based on the first state data obtained, estimated data for estimating information related to the functional element matching the first subject person according to a calculation model generated by machine learning based on second state data and at least one of the first state data saved in the past, wherein the second state data indicates a state in which a second subject person different from the first subject person used the functional element in the past, and based on the estimated data obtained, cause a prompt unit to prompt information related to the functional element. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 It is a diagram showing a configuration example of an information processing system.

[0008] Figure 2 This is a diagram showing an example of screen display.

[0009] Figure 3 This is a diagram showing a display example of a tutorial.

[0010] Figure 4 This is a diagram showing an example of a My Page screen.

[0011] Figure 5 This is a diagram showing an example of the structure of a database.

[0012] Figure 6 It is a diagram showing a configuration example of an assist control unit.

[0013] Figure 7 This is a diagram showing a structural example of a neural network model.

[0014] Figure 8 It is a diagram showing a configuration example of a learning processing unit.

[0015] Fig. 9 This is a diagram showing an example of a target score value.

[0016] Fig.10 This is a diagram showing a specific example of determining a tutorial to be presented.

[0017] Fig.11 This is a flowchart showing an example of information provision processing.

[0018] Fig.12 This is a diagram showing a situation where a plurality of display areas are set.

[0019] Fig.13 This is a diagram showing an example of determining the coordinate values ​​of the floating label. DETAILED DESCRIPTION

[0020] Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. It should be noted that the same reference numerals are used for the same or corresponding parts in the drawings.

[0021] Figure 1 The following is a structural example of an information processing system 1 according to an embodiment of the present invention. The information processing system 1 includes a server device 10 and a terminal device 20. The server device 10 and the terminal device 20 are electrically connected via a network 30. The network 30 may be any electrical communication network, such as the Internet, a wireless LAN (Local Area Network), a wired LAN, a mobile communication network, a short-range wireless communication network, or a combination of some or all of them. Figure 1 In the figure, only one terminal device 20 is shown, but the number of terminal devices 20 connectable to the server device 10 via the network 30 is not limited thereto, and a plurality of terminal devices 20 may be connected.

[0022] The information processing system 1 is a system that can provide information processing services using multiple types of functional elements including functional elements related to various calculations and functional elements related to drawing. For example, the information processing system 1 can display a calculated value based on a calculation result of a mathematical formula input by a user, or display a curve graph of a function based on a function calculation result, or draw and display a graph based on an angle or side length, or display a table of numbers or a curve graph based on a sequence calculation result based on a leading term and a recursive formula, or display a statistical curve graph or statistical value based on a statistical calculation result based on a numerical value, or display a table of profit amounts and principal and interest totals based on a financial calculation result based on an investment amount, an annual interest rate, and a number of days.

[0023] In the information processing system 1, data and calculation instructions input to the terminal device 20 are sent from the terminal device 20 to the server device 10. The server device 10 performs calculations based on the data and calculation instructions sent from the terminal device 20, and sends the calculation results to the terminal device 20. The terminal device 20 can use the calculation results sent from the server device 10 to display corresponding to them, such as displaying a graph, displaying a table of numbers, displaying numerical values ​​that become calculation results, etc. In this way, the information processing system 1 is configured to provide processing results of information corresponding to the data and calculation instructions input by the user using the terminal device 20.

[0024] The server device 10 is an information processing device also called a host computer, a mainframe, or a workstation, and includes a processing unit 11 , a storage unit 12 , and a communication unit 13 . These components are connected to each other via a system bus 19 .

[0025] The processing unit 11 is configured to include a processor such as a CPU (Central Processing Unit) to control various operations of the server device 10. The processor of the processing unit 11 is not limited to the CPU, and for example, an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), etc. may also be used. The storage unit 12 is configured using a ROM (Read Only Memory), a RAM (Random Access Memory), an HDD (Hard Disk Drive), a flash memory, or any other storage device to store various programs and data. The processing unit 11 reads the calculation program stored in the storage unit 12 and performs various calculations. The communication unit 13 is configured to include a NIC (Network Interface Card), etc., and accesses the network 30 to perform electrical communication with external devices.

[0026] The terminal device 20 may be any of an information processing device such as a personal computer, a portable terminal device such as a tablet computer, and a mobile communication device such as a smartphone, and includes a processing unit 21, a storage unit 22, an input unit 23, an output unit 24, and a communication unit 25. These components are connected to each other via a system bus 29.

[0027] The processing unit 21 is configured to include a processor such as a CPU, and controls various actions of the terminal device 20. The storage unit 22 is configured using an arbitrary storage device, and stores various programs and data. The processing unit 21 reads out the application program including the browser program stored in the storage unit 22, and performs communication with the server device 10 and input and output control. The program executed by the processing unit 21 can also be downloaded to the storage unit 22 from the network server via the network 30 and the communication unit 25. The input unit 23 includes an operation input device such as a keyboard and a touch panel, or a sound input device such as a microphone. Through the operation input using the keyboard and touch panel of the input unit 23, the detection signal is input to the processing unit 21 via the system bus 29. The output unit 24 includes a display output device such as a liquid crystal display, or a sound output device such as a speaker. The output control signal from the processing unit 21 is transmitted via the system bus 29, and various outputs based on the output unit 24 are performed. In this way, the output unit 24 of the terminal device 20 becomes a prompting unit that prompts the user with various information through display output and sound output. The communication unit 25 is configured to include at least one of a wired communication module such as a NIC or a wireless communication module, and accesses the network 30 to perform electrical communication with external devices.

[0028] The user of the terminal device 20 starts an application that is a browser program or an application that is different from the browser program by operating the input unit 23, and instructs access to the server device 10. The terminal device 20 issues a request to the server device 10 in accordance with the input acceptance of a mathematical expression, a numerical value, etc., and receives the result of the calculation performed by the server device 10 according to the program as a response from the server device 10. In this way, when a calculation request is sent from the terminal device 20, the server device 10 performs the calculation through the processing unit 11 according to the program, and sends the calculation result after the execution to the terminal device 20 as a response. Then, the terminal device 20 uses the received calculation result to draw a function curve graph, a statistical curve graph, display the calculation result, etc. through the application. In this way, in the information processing system 1, the functional elements of the information processing service that can draw a curve graph, display the calculation result, etc. are realized by the execution of the application in the terminal device 20 and the execution of the server-side program in the server device 10. The processing unit 11 of the server device 10 can execute multiple types of object programs according to multiple types of requests sent from the terminal device 20.

[0029] Figure 2 FIG. 2 shows an example of a screen display 26 of an application program executed by the terminal device 20. The terminal device 20, for example, a liquid crystal display of the output unit 24 can display outputs such as Figure 2 The screen display 26 is shown.

[0030] constitute Figure 2 The screen frame 26a of the screen display 26 shown is divided into an upper area 100a and a lower area 100b. The upper area 100a is an elongated area in which a new page creation icon 100c is displayed. The lower area 100b is an area on the lower side of the upper area 100a in the screen frame 26a, and is also called page 100. Various floating objects (Floating Object) are displayed on the page 100. The floating object is an object (display body) displayed on the screen, and is a display body that can change the display position in units of at least one or more objects according to user operations. Each object is called a floating label.

[0031] exist Figure 2 In the illustrated page 100, a graph sign 101, a mathematical expression sign 102, a slider sign 103, a mathematical expression table sign 104, a statistical table sign 105, and a statistical calculation sign 106 are displayed. In addition, in the page 100, multiple types of signs such as general calculation signs, geometric signs, sequence calculation signs, financial calculation signs, and text signs can be displayed. Check boxes 121 to 126 are displayed in the upper left part of each sign. For example, when a sign is selected, a check mark is displayed in the check box of the sign.

[0032] The graph sign 101 can display a function graph and a statistical graph. In the graph sign 101, a graph of a mathematical expression input to the first mathematical expression sign 104a, i.e., a first mathematical expression graph, a graph of a mathematical expression input to the second mathematical expression sign 104b, i.e., a second mathematical expression graph, a first statistical graph which is a scatter diagram made based on the numerical values ​​input to the statistical table sign 105, and a second statistical graph which is a quadratic regression graph made based on the numerical values ​​input to the statistical table sign 105 are overlapped and drawn.

[0033] The first tab 112 to the fourth tab 115 are displayed at the lower left of the graph float 101. The first tab 112 is associated with the first graph, the second tab 113 is associated with the second graph, the third tab 114 is associated with the first statistical graph, and the fourth tab 115 is associated with the second statistical graph. Coordinate value labels 171 to 173 are displayed on the graph float 101. Coordinate value label 171 displays the coordinates of point P1, coordinate value label 172 displays the coordinates of point P3, and coordinate value label 173 displays the coordinates of point P4.

[0034] The mathematical formula floating label 102 can display a function of a mathematical formula corresponding to an input operation in the input unit 23. In the mathematical formula floating label 102, a first mathematical formula floating label 102a and a second mathematical formula floating label 102b are displayed vertically connected. A page label 151 is displayed on the first mathematical formula floating label 102a, and a page label 152 is displayed on the second mathematical formula floating label 102b.

[0035] When the mathematical expression input to the mathematical expression float 102 includes a character coefficient, the slider float 103 can display the value of the character coefficient in a variable manner. In the slider float 103, a first slider float 105a including a first slider 118 and a second slider float 105b including a second slider 119 are displayed in a vertical connection. The first slider 118 changes the value of the character coefficient included in the mathematical expression displayed on the first mathematical expression float 102a in accordance with the input operation, and updates the display of the first curve graph according to the value of the character coefficient. The second slider 119 changes the value of the character coefficient included in the mathematical expression displayed on the second mathematical expression float 102b in accordance with the input operation, and updates the display of the second curve graph according to the value of the character coefficient.

[0036] The mathematical expression table float 104 can display the variable values ​​included in the mathematical expression input to the mathematical expression float 102 in the form of a table. The mathematical expression table float 104 displays the variable values ​​of the mathematical expression displayed on the first mathematical expression float 102a and the variable values ​​of the mathematical expression displayed on the second mathematical expression float 102b. Page labels 116 and 117 are displayed on the lower side of the mathematical expression table float 104. Page label 116 is associated with the variable values ​​of the mathematical expression displayed on the first mathematical expression float 102a, and page label 117 is associated with the variable values ​​of the mathematical expression displayed on the second mathematical expression float 102b.

[0037] In the first row of the number table displayed on the mathematical expression table float 104, mathematical expressions corresponding to the variable values ​​displayed in each column are displayed as item names of each column in cells 181 and 182. The mathematical expression displayed on the first mathematical expression float 102a is displayed in cell 181, and the mathematical expression displayed on the second mathematical expression float 102b is displayed in cell 182.

[0038] The statistical table sign 105 can display the numerical value input into the table 111 corresponding to the input operation in the input unit 23 in the form of a table. The statistical calculation sign 106 can display information related to statistical calculation. In the statistical calculation sign 106, a first statistical calculation sign 106a and a second statistical calculation sign 106b are displayed in a vertical connection. A page label 153 is displayed on the first statistical calculation sign 106a, and a page label 154 is displayed on the second statistical calculation sign 106b.

[0039] The first statistical calculation label 106a displays information related to the first statistical curve graph that is a scatter diagram drawn on the graph label 101. The display of the first statistical calculation label 106a includes a character string indicating the statistical calculation related to the scatter diagram or a character string indicating the value of the statistical calculation object. The second statistical calculation label 106b displays information related to the quadratic regression curve graph drawn on the graph label 101, that is, the second statistical curve graph. The display of the second statistical calculation label 106b includes a character string indicating the statistical calculation related to the quadratic regression curve graph or a character string indicating the quadratic regression formula, a character string indicating the value of the statistical calculation object, a character string indicating the frequency of each value, and a character string indicating the coefficient value of the quadratic regression formula.

[0040] In addition, the general calculation floating sign can display the calculation formula and calculation result corresponding to the input operation in the input unit 23. The geometric floating sign can display the shapes of triangles, circles, cones, etc. corresponding to the input operation in the input unit 23. The sequence calculation floating sign can display the first term, recursive formula and number table corresponding to the input operation in the input unit 23. In addition, the number table can also be displayed as a floating sign different from the sequence calculation floating sign. The text floating sign can display text input information corresponding to the input operation in the input unit 23.

[0041] exist Figure 2 The page 100 shown has connecting lines 141 to 143 and connecting lines 146 and 147. Connecting line 141 indicates that the graph sign 101 is associated with the mathematical formula sign 102, connecting line 142 indicates that the mathematical formula sign 102 is associated with the slider sign 103, and connecting line 143 indicates that the mathematical formula sign 102 is associated with the mathematical formula table sign 104. In addition, connecting line 146 indicates that the graph sign 101 is associated with the statistical table sign 105, and connecting line 147 indicates that the statistical table sign 105 is associated with the statistical calculation sign 106.

[0042] exist Figure 2 The page 100 shown has a menu icon bar 50. The menu icon bar 50 is configured to include a plurality of icons for accepting an input operation for displaying a new floating tag. The menu icon bar 50 is displayed at a specific position where the user's input operation is accepted in an area where no object is configured in the page 100. The menu icon bar 50 is displayed as a floating object like other floating tags.

[0043] The menu icon bar 50 includes a general calculation icon 51, a curve chart icon 52, a geometry icon 53, a statistical table icon 54, a series calculation icon 55, and a text icon 56. The general calculation icon 51 accepts an input operation to display a new general calculation tag, the curve chart icon 52 accepts an input operation to display a new curve chart tag, the geometry icon 53 accepts an input operation to display a new geometry tag, the statistical table icon 54 accepts an input operation to display a new statistical table tag, the series calculation icon 55 accepts an input operation to display a new series calculation tag, and the text icon 56 accepts an input operation to display a new text tag. In addition, the menu icon bar 50 may also include a financial calculation icon that accepts an input operation to display a new financial calculation tag.

[0044] exist Figure 2 An icon group is displayed in the graph float 101 shown. The icon group includes a mathematical expression icon and a statistical table icon. The mathematical expression icon of the icon group accepts an input operation for creating a new mathematical expression float associated with the graph float 101, and an input operation for moving the focus to an existing mathematical expression float associated with the graph float 101. The statistical table icon of the icon group accepts an input operation for creating a new statistical table float associated with the graph float 101, and an input operation for moving the focus to an existing statistical table float associated with the graph float 101.

[0045] The information processing system 1 has a plurality of types of functional elements that can present information obtained through various information processing to the user, such as a functional element that creates various floating signs from a blank page 100, a functional element that displays a calculation result of a calculation executed, a functional element that draws a function curve graph or a statistical curve graph on a curve graph floating sign 101, a functional element that displays the coordinate value of an arbitrary point on the drawn curve graph, a functional element that displays a calculation result based on a calculation using coordinate values, a functional element that draws a figure on a geometric floating sign, and a functional element that inputs and displays a numerical value on a mathematical expression floating sign or a statistical floating sign. Such a plurality of types of functional elements are implemented by the execution of an object program in the processing unit 11 of the server device 10.

[0046] In the screen display 26 of page 100, a tutorial can be displayed as a part of the information related to the functional elements provided to the user. The tutorial, for example, prompts the usage method corresponding to each floating tag as information according to the actual production steps and execution steps. The content of the tutorial can be prepared differently according to the type of floating tag, the user's utilization level, etc. The tutorial is prompted to assist the user in using the information processing service, and is auxiliary information indicating the usage method corresponding to multiple types of functional elements that the information processing service can provide. In page 100, the tutorial can be displayed in an area where no object is configured. Alternatively, even in an area where an object is configured, the tutorial can be displayed overlappingly. Multiple tutorials can also be displayed in an arranged manner or overlapped. In this way, in the information processing system 1, as information corresponding to each floating tag providing multiple types of functional elements, a tutorial that becomes auxiliary information can be prompted by display output in the screen display 26 of page 100.

[0047] Figure 3The display example of the tutorial 107 in the screen display 26 of the page 100 is shown. The tutorial 107 is presented as auxiliary information indicating the usage method corresponding to the slider sticker 103. In the screen display 26 of the page 100, the tutorial 107 is displayed in the area below the slider sticker 103 where no object is arranged. Not limited to the slider sticker 103, the tutorial 107 with different contents can be displayed corresponding to the graph sticker 101, the mathematical formula sticker 102, the mathematical formula table sticker 104, the statistical table sticker 105, and the statistical calculation sticker 106. In addition, the general calculation sticker, the geometric sticker, the sequence calculation sticker, the financial calculation sticker, the text sticker, etc. can correspond to all or part of the stickers that can be provided by display output in the information processing service, and the tutorial 107 with different contents can be presented by display output. It is also possible to display and output the tutorial 107 with different contents corresponding to each icon 51 to 56 of the menu icon bar 50. As described above, the tutorial 107 is auxiliary information indicating how to use multiple types of functional elements such as multiple types of floating tags, and is included in the information related to the functional elements.

[0048] Tutorial 107 may also start displaying based on an input operation corresponding to a user's start request. Alternatively, the display of tutorial 107 may start automatically through the initial setting of the information processing service. It is also possible to selectively switch between automatically starting the display of tutorial 107, manually starting the display of tutorial 107, not starting the display of tutorial 107, and the like according to the option setting based on the user's input operation. Tutorial 107 may also be deleted based on an input operation performed by the user according to its content. Alternatively, a display area for a delete button may be set in tutorial 107, and the tutorial may be deleted based on an input operation of the delete button by the user. It is also possible to prepare multiple tutorials 107, and when an input operation according to the content shown in the first tutorial is detected, the display of the first tutorial is deleted, and the display of the second tutorial showing new content is started.

[0049] In the information processing system 1, when a user uses an information processing service, the user's ID and password are sent from the terminal device 20 to the server device 10. The user's ID and password are pre-assigned by the information processing service and stored in the storage unit 22 of the terminal device 20 or input through the input operation of the input unit 23. The user authentication process is performed in the server device 10, and when the login is permitted, the My Page screen is displayed in the terminal device 20. For example, the output unit 24 of the terminal device 20 can display the My Page screen through a liquid crystal display or the like.

[0050] Figure 4An example of a My Page screen 320 displayed on the terminal device 20 is shown. The My Page screen 320 includes a thumbnail image group 321. The thumbnail image group 321 includes a plurality of thumbnail images 322. Each thumbnail image 322 represents a page 100 that the user has created. Each thumbnail image 322 may include a page title 323, a creator 324, an update date and time 325, and the like.

[0051] In the My Page screen 320, various input operations of the user can be accepted. Information indicating the input operation of the user is sent from the input unit 23 to the terminal device 20 via the processing unit 21 and the communication unit 25, and is transmitted to the server device 10 through the network 30. For example, in the case of creating a new page 100, the creation icon 327 is selected. In the case of editing an already created page 100, the thumbnail image 322 corresponding to the page 100 is selected. In the case of creating a new page 100, the processing unit 11 creates new page data in the server device 10. In the case of editing an already created page 100, the processing unit 11 updates the page data in the server device 10. In addition, in addition to the overview display area displaying the thumbnail image group 321 and the header area displaying the creation icon 327, the My Page screen 320 may also include a side menu area displaying menu items corresponding to the switching of various displays.

[0052] Figure 5 2 shows a configuration example of the database 200. The database 200 is provided in the storage of the storage unit 12 provided in the server device 10. The database 200 includes a page management table 210, a floating sign management table 220, a user management table 230, a course management table 240, and a course data table 250.

[0053] The page management table 210 stores information such as data ID, user ID, page ID, page disclosure setting, and public URL (Uniform Resource Locator) for each page 100 created by the user. Data representing information stored in the page management table 210 is also referred to as page management data. When a new page 100 is created, one row of page management data is newly added to the page management table 210. Data ID is inherent identification information assigned to each page management data. User ID is identification information of the user who created the page 100. Page ID is identification information assigned to each page 100. The page disclosure setting is information indicating whether the corresponding page 100 is to be disclosed or set to be private. The public URL is address information assigned to the corresponding page 100 when the page disclosure setting is set to "disclosure". In addition, the page management data may also include image data representing a thumbnail image of the page 100. The thumbnail image of the page 100 may be an image created by taking in the screen data of the page 100 as a captured image.

[0054] The floating sign management table 220 stores information such as the floating sign ID, page ID, floating sign type, and floating sign content according to each object that the user makes to become a floating sign. The data representing the information stored in the floating sign management table 220 is also called the floating sign management data. When a new floating sign is made, in the floating sign management table 220, a new floating sign management data of 1 row is added. The floating sign ID is the inherent identification information given to the floating sign management data corresponding to each floating sign. The page ID is the identification information of the page 100 showing each floating sign, and corresponds to the page ID contained in the page management data stored in the page management table 210. The floating sign type is information representing the type corresponding to each floating sign, such as a general calculation floating sign, a curve floating sign, a mathematical formula floating sign, a slider floating sign, a mathematical formula table floating sign, a geometric floating sign, a statistical table floating sign, a statistical calculation floating sign, a financial calculation floating sign, and a text floating sign. The floating sign content represents the content of the floating sign, which is information that can definitely represent a character string, a mathematical formula, an image, etc. Furthermore, the floating sticker content may include information related to display settings such as display position, display size, and display color for each floating sticker on page 100 .

[0055] The user management table 230 stores information such as user ID, user name, email address, user category, age, gender, location, and utilization level for each user who uses the information processing service provided by the information processing system 1. Data representing information stored in the user management table 230 is also called user management data. When a new user is registered, a new row of user management data is added to the user management table 230. The user ID is inherent identification information given to the user management data corresponding to each user. The user name is information indicating the name of the registered user. The email address is address information of the email used by the registered user. The user category, age, gender, and location are attribute information corresponding to each user. Among them, the user category is attribute information corresponding to the user's status and ability, such as a student or teacher, or an agency, department, or professional field. The location is location information that can be set corresponding to each user, such as the country name, region name, postal code, other residence code, house number, etc., indicating at least one of the user's residence, residence, current location, residence of the organization to which the user belongs, and residence. The utilization level may be characteristic information indicating the number of times each user utilizes the information processing service, time, difficulty of access, proficiency, etc. In addition, the user management data may include log information indicating the history of each user utilizing multiple types of functional elements in the information processing service.

[0056] Tutorial Management Table 240 Figure 3Each tutorial that can be provided in the screen display 26 of page 100, such as the tutorial 107 shown, stores information such as the tutorial ID, the type of the sign, the utilization level, and the detailed level. The data representing the information stored in the tutorial management table 240 is also called the tutorial management data. The tutorial management data is pre-made by an internal or external device of the information processing system 1, and is stored in the storage of the storage unit 22 as the tutorial management table 240. In addition, when new tutorial management data is made by the administrator of the information processing system 1, it can also be updated by appending to the tutorial management table 240. The tutorial ID is identification information given to each tutorial management data. The sign type is information indicating whether the type of the sign that becomes the object of displaying the tutorial is a general calculation sign, a graph sign, a mathematical expression sign, a slider sign, a mathematical expression table sign, a geometric sign, a statistical table sign, a statistical calculation sign, a financial calculation sign, or a text sign. The utilization level is information indicating the utilization level of the user who becomes the object of displaying the tutorial. The detailed level is information indicating the degree of detail in the content of the tutorial.

[0057] Information related to the specific content of the tutorial is stored in the tutorial data table 250. The tutorial data table 250 stores information such as the tutorial ID and data content for each tutorial. The tutorial ID corresponds to the ID managed in the tutorial management table 240. The data content indicates the content of the tutorial and is information that can specifically represent a character string, a mathematical expression, an image, etc.

[0058] Figure 6 The structure example of the auxiliary control unit 500A configured in the server device 10 is shown. The auxiliary control unit 500A reads out and executes the program pre-stored in the storage of the storage unit 12 through the processor of the processing unit 11, etc., and uses hardware resources to implement software-based information processing. When the auxiliary control unit 500A prompts a tutorial for the use of auxiliary information processing services to a user who becomes an auxiliary object, it is possible to infer and prompt a tutorial that matches the user. The user who becomes the auxiliary object is, for example, a user who performs an input operation to start the screen display 26 of page 100. As long as the user uses the information processing service, anyone can become an auxiliary object. In addition, hereinafter, the user in the scenario where the tutorial is prompted for assistance is sometimes also specifically referred to as the first object, and the user in other scenarios is also referred to as the second object different from the first object, and the distinction between the two is explained.

[0059] Figure 6The auxiliary control unit 500A shown includes a calculation data acquisition unit 510, a score calculation unit 520, and a prompt information determination unit 530. The processing unit 11 of the server device 10 reads and executes a program stored in a memory or the like of the storage unit 12, so that the calculation data acquisition unit 510 realizes a first acquisition function, the score calculation unit 520 realizes a second acquisition function, and the prompt information determination unit 530 realizes a prompt processing function. That is, the storage unit 12 of the server device 10 stores a program for causing the processing unit 11 of the server device 10 as a computer to realize the first acquisition function of the calculation data acquisition unit 510, the second acquisition function of the score calculation unit 520, and the prompt processing function of the prompt information determination unit 530.

[0060] The calculation data acquisition unit 510 acquires various data used in the calculation processing of the process of estimating information related to the functional element matched to the user, when the tutorial is presented through the display output of the output unit 24 of the terminal device 20, as calculation data. The user who becomes the object of estimation through the calculation processing using the calculation data is also the user who becomes the object of using the auxiliary information processing service through the presentation of the tutorial, and becomes the auxiliary object person as the first object person. The calculation data includes user data 510A and thumbnail data 510B. The user data 510A is data related to the user who is the first object person to be presented with the tutorial and assisted among the multiple users who use the information processing service provided by the information processing system 1. In the user management table 230, part or all of the user management data stored corresponding to the user who becomes the first object person can be included. For example, the user data 510A may use attribute data representing the attribute information of the user, such as the user category, gender, age, and location included in the user management data, or information combining part or all of them. In addition, the user data 510A may use characteristic data representing the characteristic information of the user, such as the utilization level included in the user management data. The thumbnail data 510B is image data (data represented by pixel values) representing the thumbnail image 322 selected by the user who becomes the first subject in the My Page screen 320. In addition, when a new page creation is selected in the screen display 26 of the page 100 or the My Page screen 320, the image data representing the new thumbnail image 322 can be obtained as the thumbnail data 510B. In the new thumbnail image 322, only the display area that becomes the background of the page 100 is represented, and the display area corresponding to the floating tag is not included. The thumbnail data 510B is equivalent to the first state data, which represents the state of the user who becomes the first subject using the floating tag corresponding to the functional element in the information processing service provided by the information processing system 1 by using the image data representing the thumbnail image 322 selected in the My Page screen 320. In this way, the calculation data acquisition unit 510 realizes the first acquisition function (first acquisition unit) of acquiring the first state data, which represents the state of the first subject using the functional element realized by the execution of the object program in the processing unit 11 of the server device 10, etc. Furthermore, the calculation data acquisition unit 510 realizes a first acquisition function of acquiring attribute data indicating a combination of part or all of the sex, age, and location of the first target person.

[0061] The score calculation unit 520 performs calculation processing according to the calculation model which is a learned model generated by machine learning based on the calculation data obtained by the calculation data acquisition unit 510. The calculation model is a learned model that has been machine-learned in a manner of inputting the user data 510A and the thumbnail data 510B contained in the calculation data and outputting the score data 520A for estimating the information related to the floating ticket matching the user, for example, a neural network model. The score calculation unit 520 obtains the calculation model from the calculation model storage unit 600 provided in the storage unit 12 of the server device 10, for example, and performs calculation processing according to the calculation model. The calculation model generated by machine learning is pre-stored in the calculation model storage unit 600, thereby storing the calculation model. In addition, the calculation model storage unit 600 is not limited to the storage unit 12 provided in the server device 10, and can also be provided in the storage unit of a computer different from the server device 10.

[0062] Figure 7 An example of the structure of a neural network model is shown. The neural network is constructed to include an input layer, an intermediate layer, and an output layer. The intermediate layer is also called a hidden layer. The input layer, the intermediate layer, and the output layer all contain multiple neurons. The intermediate layer can be only one layer, or multiple layers of more than two layers, and can be arbitrarily set based on specifications such as computing resources and estimation accuracy. The input layer includes neurons for inputting user data 510A and neurons for inputting thumbnail data 510B. The output layer includes multiple neurons for outputting score data 520A for estimating a tutorial that is information related to the lottery matching the user, corresponding to each type of lottery such as general calculation lottery, graph lottery, mathematical formula lottery, slider lottery, mathematical formula table lottery, geometric lottery, statistical table lottery, statistical calculation lottery, series calculation lottery, financial calculation lottery, and text lottery. The score calculation unit 520 executes according to Figure 7 The computational processing of the neural network model shown implements a second acquisition function, which acquires estimated data for estimating information related to functional elements matching the first object person based on the first state data in accordance with the computational model generated by machine learning.

[0063] The prompt information determination unit 530 determines a tutorial as information that is presented to the user by the terminal device 20 through the display output of the output unit 24 in the information processing service based on the score data 520A that is the calculation result of the score calculation unit 520. For example, in the score data 520A output from the score calculation unit 520, the type of floating lottery with a large score value is inferred to be the number of times the user makes floating lottery or uses floating lottery, and the user is accustomed to use it. In contrast, in the score data 520A output from the score calculation unit 520, the type of floating lottery with a small score value is inferred to be the number of times the user makes floating lottery or uses floating lottery, and the user is not accustomed to use it. Therefore, the tutorial presented corresponding to the type of floating lottery with a large score value is compared with the tutorial presented corresponding to the type of floating lottery with a small score value. The information presented to the user as a tutorial can be determined in a way that becomes a tutorial with simple content. The calculation model used in the calculation processing of the score calculation unit 520 is generated by machine learning so that the score data 520A indicating the score value adapted to the calculation data is obtained as the score data 520A having such a relationship based on the calculation data obtained by the calculation data acquisition unit 510. The score data 520A which is the calculation result of the score calculation unit 520 corresponds to the estimated data used to estimate the information related to the functional element matched to the user in the information processing service provided by the information processing system 1. The prompt information determination unit 530 determines the information related to the functional element such as the tutorial which is the auxiliary information to be presented to the user based on the score data 520A output from the score calculation unit 520.

[0064] The prompt information determination unit 530 generates prompt control data 530A used for controlling the prompt of the determined information. The prompt control data 530A may include, for example, data content obtained from the course data table 250 based on the information of the course ID stored in the course management table 240. In addition, the prompt control data 530A may also include display position information indicating the display position of the course in the screen display 26 of the page 100. The prompt control data 530A generated by the prompt information determination unit 530 is transmitted from the communication unit 13 to the terminal device 20 via the network 30. The processing unit 21 of the terminal device 20 updates the display output in the display output device of the output unit 24 based on the prompt control data 530A received from the server device 10, so that information related to the functional elements matching the user, such as the tutorial as auxiliary information, can be prompted. In this way, by supplying the prompt control data 530A generated by the prompt information determination unit 530 to the terminal device 20, a prompt processing function (prompt processing unit) is realized, which prompts information related to functional elements matched to the user in the information processing service through display output or the like in the output unit 24 of the terminal device 20. The information related to the functional elements may be auxiliary information indicating usage methods corresponding to multiple types of functional elements.

[0065] Figure 8 The structure example of the learning processing unit 500B is shown. The learning processing unit 500B can be configured in the server device 10 or in a computer different from the server device 10. For example, in the processing unit 11 of the server device 10, a processor or the like reads and executes a program pre-stored in the storage of the storage unit 12, thereby using hardware resources to implement software-based information processing, and the learning processing unit 500B is configured by a block or process different from the auxiliary control unit 500A. In addition, a processor such as an image processing processor different from the CPU of the processing unit 11 of the server device 10 and provided separately from the processor for configuring the auxiliary control unit 500A can also be used. The learning processing unit 500B includes a learning data acquisition unit 540 and a calculation model update unit 550. In the case where the learning processing unit 500B is configured in the processing unit 11 of the server device 10, the processing unit 11 can also read and execute a program stored in the storage of the storage unit 12, so that the learning data acquisition unit 540 implements the third acquisition function and the calculation model update unit 550 implements the update processing function. In this case, the storage unit 12 of the server device 10 stores a program for realizing the third acquisition function of the learning data acquisition unit 540 and the update processing function of the calculation model update unit 550 in the processing unit 11 of the server device 10 as a computer.

[0066] The learning data acquisition unit 540 acquires various data used to make the computational model perform machine learning as learning data. The learning data includes user data 540A, thumbnail data 540B, page data 540C, and floating tag data 540D. The user data 540A is data related to a user who becomes a first object person among multiple users of the information processing service provided by the information processing system 1, or a user who becomes a first object person and a user who becomes a second object person different from the first object person. In the user management table 230, a part or all of the user management data corresponding to the user who becomes the first object person or the second object person can be included. In addition, in the case where the user who becomes the first object person is a new user, sometimes there is no data related to the user. In this case, the data related to the user who becomes the second object person different from the first object person can be set as user data 540A. For example, the user data 540A uses at least attribute data like the user data 510A acquired by the computational data acquisition unit 510, and characteristic data can also be used in addition to attribute data. The attribute data of the user data 540A indicates a combination of part or all of the gender, age, and location of at least one of the user who becomes the first subject and the user who becomes the second subject. The thumbnail data 540B may be included in the page management data stored in the page management table 210 as image data representing the thumbnail image 322. The thumbnail data 540B included in the learning data may include at least one of the image data of the thumbnail image 322 corresponding to the page 100 made in the past by the second subject different from the first subject, and the image data of the thumbnail image 322 corresponding to the page 100 made in the past by the first subject. The thumbnail data 540B is equivalent to at least one of the second state data indicating the state of the functional element such as the floating tag used in the past by the second subject different from the first subject, and the first state data stored in the past. The page data 540C is data related to the page 100 that can be displayed and output in the information processing service provided by the information processing system 1, and the page management table 210 may include part or all of the page management data stored for each page 100. For example, the page data 540C, as data representing the page ID included in the page management data, may be data representing the page ID assigned to the page 100 corresponding to the thumbnail image 322 represented by the image data included in the thumbnail data 540B. The floating tag data 540D is data related to various floating tags that can be displayed in the page 100, and in the floating tag management table 220, a part or all of the floating tag management data stored for each object that becomes a floating tag may be included. For example, the floating tag data 540D, as data representing the floating tag ID and the page ID included in the floating tag management data, may be data representing the floating tag ID associated with the page ID shown in the page data 540C. In addition, the floating tag data 540D may also include data representing the floating tag type or the floating tag content.

[0067] The learning data acquisition unit 540 can also obtain the teacher data used in the generation or update of the computing model of machine learning based on the page data 540C and the floating tag data 540D. For example, the learning data acquisition unit 540 extracts the floating tag ID corresponding to the same page ID included in the floating tag data 540D corresponding to the page ID included in the page data 540C. Then, according to each floating tag type corresponding to the extracted floating tag ID, the number of floating tags corresponding to the corresponding floating tag type is divided by the total number of floating tags corresponding to the same page ID. The value obtained by dividing the number of floating tags corresponding to the corresponding floating tag type by the total number of floating tags made in the page 100 is used as the score value for the correct answer of the corresponding floating tag type. The learning data acquisition unit 540 obtains the score data representing the score value obtained for each floating tag type as the teacher data for the correct answer data. In this way, the learning data acquisition unit 540 acquires the first state data indicating the state of the first subject's past use of the functional element and the second state data indicating the state of the second subject's past use of the functional element, either in the case of acquiring the first state data or in the case of acquiring both the first state data and the second state data. In either case, the learning data acquisition unit 540 acquires the first state data together with the teacher data that is different from the first state data and the second state data. That is, the learning data acquisition unit 540 implements a third acquisition function, which acquires the first state data, or both the first state data and the second state data together with the teacher data that is different from the first state data and the second state data.

[0068] The calculation model updating unit 550 updates the calculation model by adjusting the parameters of the calculation model used in the calculation of the score calculation unit 520 so as to learn the relationship between the user data 540A and the thumbnail data 540B and the score data corresponding to the estimated data. Figure 7The neural network model shown is based on the teacher data obtained by the learning data acquisition unit 540 using the page data 540C and the floating signature data 540D in the learning data, and learns the relationship between the user data 540A and the thumbnail data 540B and the score data through the so-called teacher learning. As a method of teacher learning, for example, the error back propagation method (Back Propagation) can also be used. When the user data 540A and the thumbnail data 540B are input, the parameters of the operation model such as the weighting coefficient or the bias component are adjusted to obtain the score value shown in the teacher data. The operation model updated by the operation model updating unit 550 is stored in the operation model storage unit 600, and the score operation unit 520 can obtain it and keep it. In this way, the operation model updating unit 550 realizes the update processing function, which updates the operation model through machine learning based on the data obtained by the learning data acquisition unit 540 that realizes the third acquisition function. In addition, the calculation model updating unit 550 may also implement a generation processing function that generates a calculation model by machine learning based on at least one of the second state data stored in the past and the first state data stored in the past. Figure 7 The user data 510A and thumbnail data 510B of the input layer of the neural network model shown in the figure, and the score data 520A corresponding to the floating tag made by the user who is the first subject in the actual page 100 are outputted at the output layer, thereby realizing the second acquisition function of acquiring the estimated data. Therefore, the score calculation unit 520 realizes the second acquisition function (second acquisition unit), which acquires the estimated data for estimating the information related to the functional element matching the user who is the first subject according to the calculation model generated by machine learning based on at least one of the second state data representing the state of the second subject different from the first subject using the functional element in the past and the first state data saved in the past, based on the first state data acquired by the first acquisition function implemented by the calculation data acquisition unit 510. In addition, the calculation model is generated by machine learning based on the attribute data of the combination of part or all of the gender, age, and location of at least one of the first subject and the second subject. The second acquisition function of the score calculation unit 520 is to acquire the estimated data according to the calculation model based on the first state data and the attribute data of the first subject acquired by the first acquisition function implemented by the calculation data acquisition unit 510.

[0069] The calculation model updating unit 550 uses the learning data prepared in advance as training data, and adjusts the parameters of the calculation model through machine learning that becomes initial learning. After that, the calculation model updating unit 550 uses new learning data as training data, and adjusts the parameters of the calculation model through machine learning that becomes additional learning, based on the establishment of the additional learning condition that becomes the update condition set in advance or afterwards. As an example, it is also possible that the additional learning condition is established every time the number of pages 100 produced increases by a specific number such as 100, based on the number of page IDs stored by page management data in the page management table 210. As another example, it is also possible that the additional learning condition is established every time the number of registered users increases by a specific number such as 100, based on the number of user IDs stored by user management data in the user management table 230. As another example, it is also possible that the additional learning condition is established every time the number of items in the stored tutorial increases by a specific number such as 100, based on the number of tutorial IDs stored by tutorial management data in the tutorial management table 240. Alternatively, the additional learning condition may be satisfied each time a new item is added to the course. In this case, the learning data acquisition unit 540 implements a third acquisition function, which acquires at least one of the first state data and the second state data included in the thumbnail data 540B together with the teacher data different from the first state data and the second state data based on the establishment of the additional learning condition that becomes the update condition. The calculation model update unit 550 implements an update processing function, which updates the calculation model through machine learning based on the data acquired by the learning data acquisition unit 540.

[0070] Fig. 9Shown is an example of a score value of a target output according to the operation processing of the operation model when the floating ticket made in page 100 includes 1 general calculation floating ticket, graph floating ticket, financial calculation floating ticket, and text floating ticket respectively. As mentioned above, the score value of each floating ticket type calculated using page data 540C and floating ticket data 540D is the value obtained by dividing the number of floating tickets corresponding to the corresponding floating ticket type by the total number of floating tickets made in page 100. In this example, since there are 4 floating tickets in total, the score values ​​corresponding to each floating ticket included in page 100 are all 0.25. The score values ​​corresponding to each floating ticket not included in page 100 are all 0. Similarly, the floating ticket type with a large number of floating tickets made in page 100 is compared with the floating ticket type with a small number of floating tickets made in page 100, and the corresponding score value becomes larger. When the user uses the floating ticket that becomes a plurality of types of functional elements corresponding to the floating ticket type, the score data representing the score value represents the probability distribution of the use state corresponding to the floating ticket type. In this case, the score data representing the probability distribution of the use state can be said to be data representing the probability of use corresponding to the type of the floating ticket by the size of the score value for the floating ticket made or edited in the past by the user who becomes the first object person or the user who becomes the second object person. In addition, it is inferred that: the number of times the floating ticket of the type of floating ticket with a large probability shown in the score value is made or used many times, and the user is used accustomed to it and has high proficiency. On the other hand, the number of times the floating ticket of the type of floating ticket with a small probability shown in the score value is made or used few times, and the user has no habit of using it and has low proficiency. The score calculation unit 520 can also implement a second acquisition function, which obtains the score data representing the probability distribution of the use state corresponding to the functional element corresponding to the type of the floating ticket according to the calculation model generated by machine learning based on the first state data obtained by the first acquisition function implemented by the calculation data acquisition unit 510.

[0071] In addition, the score data represents the use ratio or usage rate of each floating tag corresponding to the floating tag type used as the floating tag that has been made or edited under the state of the floating tag that the user has used the functional elements of multiple types corresponding to the floating tag type. In this case, the score data representing the use ratio or usage rate can also be said to be the floating tag made or edited in the past by the user who becomes the first object or the user who becomes the second object, and the data representing the tendency of use corresponding to the floating tag type by the size of the score value. It is speculated that: the number of times or the number of times of use of the floating tag of the floating tag type with a large score value in the score data are many, and the user is used to and has a high proficiency. On the other hand, the number of times or the number of times of use of the floating tag of the floating tag type with a small score value in the score data are few, and the user is not used to and has a low proficiency. Therefore, the score data representing the use ratio can also be said to be the floating tag made or edited in the past by the user who becomes the first object or the user who becomes the second object, and the data representing the proficiency of the user corresponding to the floating tag type by the size of the score value. Moreover, it is inferred that: the number of times the floating sign of the floating sign type with a large score value in the score data is made or used is large, and the degree of user attention consciousness is high. On the other hand, the number of times the floating sign of the floating sign type with a small score value in the score data is made or used is small, and the degree of user attention consciousness is low. Therefore, the score data representing the use ratio can also be said to be based on the floating sign made or edited by the user who becomes the first object person or the user who becomes the second object person in the past, and the size of the score value is used to represent the evaluation data of the degree of user attention consciousness, that is, the intentionality according to the floating sign type. The score calculation unit 520 can also realize the second acquisition function, which obtains the score data representing the use ratio or usage rate corresponding to the functional element corresponding to the floating sign type, the score data representing the proficiency of the first object person corresponding to the functional element corresponding to the floating sign type, and the score data representing the evaluation of the intentionality of the first object person corresponding to the functional element corresponding to the floating sign type according to the calculation model generated by machine learning, based on the first state data obtained by the first acquisition function realized by the calculation data acquisition unit 510.

[0072] In this way, based on the user data 540A and thumbnail data 540B obtained by the learning data acquisition unit 540, the page data 540C and the floating index data 540D obtained by the learning data acquisition unit 540 can be used to calculate the score values ​​that become the target values ​​in the score data output as the calculation result of the calculation model. The calculation model update unit 550 uses the score data representing the score values ​​calculated based on the page data 540C and the floating index data 540D as the teacher data to adjust the parameters in the calculation model to learn the relationship with the user data 540A and the thumbnail data 540B. For example, in Figure 7In the neural network model shown, the calculation model can be updated by adjusting the weight coefficient or bias component using the error back propagation method (Back Propagation).

[0073] In this way, the calculation model for obtaining the score data 520A has been learned by machine learning, so the prompt information determination unit 530 can determine the auxiliary information such as the tutorial matched with the user who becomes the first subject according to the input of the user data 510A and the thumbnail data 510B as the information related to the floating sign as the functional element based on the score data 520A obtained by the score calculation unit 520. For example, when the user data 510A and the thumbnail data 510B are obtained as calculation data by the calculation data acquisition unit 510 corresponding to the user who becomes the first subject, the score data 520A obtained by the score calculation unit 520 can represent the common score value with the user who becomes the second subject and has the same user data as the user who becomes the first subject. The user data and thumbnail data corresponding to the user who becomes the second object are pre-included in the user data 540A and thumbnail data 540B obtained by the learning data acquisition unit 540. Based on the teacher data obtained from the page data 540C and the floating signature data 540D, the parameters of the operation model are adjusted by the operation model update unit 550 to obtain score data consistent with the correct answer data. In this case, the score data obtained corresponding to the user who becomes the second object can be applied to the user who becomes the first object. Therefore, the parameters of the operation model generated by machine learning based on the learning data obtained by the learning data acquisition unit 540 are adjusted to obtain score data 520A representing a score value adaptive to the operation data obtained by the operation data acquisition unit 510.

[0074] The tutorials storing data contents in the tutorial data table 250 can be divided into multiple levels of detail of information in advance by the detail levels stored in the tutorial management table 240. For example, the detail levels can also be set to 7 levels from the first level to the seventh level, with the first level being the simplest and the seventh level being the most detailed. More specifically, the first level tutorial only shows the items with floating labels, the second level tutorial shows a simple description of the function, the third level tutorial shows a simple example, the fourth level tutorial shows a detailed description of the function, the fifth level tutorial shows the first detailed example, the sixth level tutorial shows the second detailed example, and the seventh level tutorial shows the entire detailed description.

[0075] Fig.10A specific example of determining the tutorial to be presented by performing a calculation process of a calculation model using calculation data is shown. In this specific example, the score calculation unit 520 performs a calculation process according to the calculation model, thereby obtaining score data 520A with a score value of 0.25 for general calculation, a score value of 0.4 for graph, a score value of 0.15 for geometry, a score value of 0.03 for statistical table, a score value of 0.05 for sequence calculation, a score value of 0.1 for financial calculation, and a score value of 0.02 for text.

[0076] When the presentation information determination unit 530 obtains the score data 520A indicating such a score value, it ranks the floating lot from the larger score value to the smaller score value. Fig.10 In the specific example, the graph is ranked first, the general calculation is ranked second, the geometry is ranked third, the financial calculation is ranked fourth, the sequence calculation is ranked fifth, the statistical table is ranked sixth, and the text is ranked seventh. Next, the prompt information determination unit 530 determines the stage and combination for the tutorial, i.e., the prompt tutorial, prompted by the terminal device 20, according to the ranking of the floats. Fig.10 In the specific example, only the first-level items are determined corresponding to the first-level graph float, the second-level general calculation float is determined corresponding to the second-level simple function description, the third-level geometric float is determined corresponding to the second-level simple function description and the third-level simple example, the fourth-level financial calculation float is determined corresponding to the fourth-level detailed function description and the third-level simple example, the fifth-level sequence calculation float is determined corresponding to the fifth-level detailed function description and the first detailed example of the fifth level, the sixth-level statistical table float is determined corresponding to the fourth-level detailed function description, the first detailed example of the fifth level and the second detailed example of the sixth level, and the seventh-level text float is determined corresponding to the fourth-level detailed function description, the first detailed example of the fifth level, the second detailed example of the sixth level and the seventh-level overall detailed function description. When the tutorial determined by the prompt information determination unit 530 creates a new float in page 100, it can be prompted by displaying and outputting corresponding to the float type. In the case where a combination of multiple tutorials is determined corresponding to the float type, the prompt can be made by arranging and displaying these tutorials, or by overlapping and displaying these tutorials.

[0077] Thus, the prompt information determination unit 530 may make the details of the information presented to the user different through the display output of the output unit 24 of the terminal device 20 according to the multiple types of functional elements corresponding to the floating lottery type based on the score data 520A obtained as the calculation result according to the calculation model of the score calculation unit 520. In addition, the prompt information determination unit 530 may also make the information presented to the user through the display output of the output unit 24 of the terminal device 20 different through the score data 520A obtained as the calculation result according to the calculation model of the score calculation unit 520 according to the multiple types of functional elements corresponding to the floating lottery type. In other words, the prompt information determination unit 530 may also make the amount of information presented to the user who is the first subject different through the display output of the output unit 24 of the terminal device 20 according to the multiple types of functional elements corresponding to the floating lottery type.

[0078] Fig.11 1 is a flowchart showing an example of information provision processing executed when a user who becomes the first target person uses information processing service in the information processing system 1. Such information provision processing is performed by the processor of the processing unit 11 in the server device 10, which reads and executes a program pre-stored in the memory of the storage unit 12, and implements software-based information processing using hardware resources. The information provision processing starts when the processing unit 11 of the server device 10 permits login due to access from the terminal device 20, for example.

[0079] When the user's login is permitted, the processing unit 11 of the server device 10 reads the user management data stored in the user management table 230 of the database 200 (step S101). At this time, the processing unit 11 determines the user ID assigned to the first object person permitted to log in. Then, the user management data corresponding to the determined user ID is read from the storage unit 12. For example, the processing unit 11 of the server device 10 reads the user management data through the calculation data acquisition unit 510 in the auxiliary control unit 500A. The calculation data acquisition unit 510 reads the user management data corresponding to the determined user ID from the user management table 230 in the database 200 provided in the storage unit 12, and acquires the user data 510A. When the user's login is permitted, the my page screen 320 prepared for each user is provided through the display output in the display output device provided in the output unit 24 of the terminal device 20.

[0080] Next, the processing unit 11 of the server device 10 reads the calculation model prepared corresponding to the user (step S102). For example, the processing unit 11 of the server device 10 selects the calculation model corresponding to the user ID from the calculation models prepared by the calculation model storage unit 600 provided in the memory of the storage unit 12, and reads it into the working area such as RAM so that it can be used in the calculation processing of the score calculation unit 520.

[0081] Then, it is determined whether the creation of a new page is indicated (step S103). For example, in the My Page screen 320, the input operation of selecting the creation icon 327 is detected by the touch panel, mouse, etc. of the input unit 23 of the terminal device 20, and notified to the processing unit 21 of the terminal device 20. The processing unit 21 of the terminal device 20 transmits a request corresponding to the notification from the communication unit 25 to the server device 10 via the network 30. The request transmitted at this time is also called a new creation request. The processing unit 11 of the server device 10 can recognize that the creation of the page 100 is newly indicated by accepting the new creation request from the terminal device 20.

[0082] When the creation of a new page is instructed (step S103: Yes), the image data representing the new thumbnail image 322 is read (step S104). For example, the processing unit 11 of the server device 10 reads the image data representing the new thumbnail image 322 through the calculation data acquisition unit 510 in the auxiliary control unit 500A, and acquires the thumbnail data 510B. The thumbnail data 510B acquired at this time is supplied to the score calculation unit 520 together with the user data 510A.

[0083] When the creation of a new page is not instructed (step S103: No), it is determined whether the start of editing the page 100 whose thumbnail image 322 is displayed in the My Page screen 320 is instructed (step S105). For example, in the My Page screen 320, the input operation of selecting the thumbnail image 322 is detected by the touch panel, mouse, etc. provided in the input unit 23 of the terminal device 20, and notified to the processing unit 21 of the terminal device 20. The processing unit 21 of the terminal device 20 transmits a request corresponding to the notification from the communication unit 25 to the server device 10 via the network 30. The request transmitted at this time is also called an edit start request. The processing unit 11 of the server device 10 can recognize that the start of editing the page 100 corresponding to the thumbnail image 322 is instructed by accepting the edit start request from the terminal device 20.

[0084] When the start of editing of the page 100 is instructed (step S105: Yes), the image data representing the thumbnail image 322 corresponding to the page 100 for which the start of editing is instructed is read (step S106). For example, the processing unit 11 of the server device 10 reads the image data representing the thumbnail image 322 corresponding to the page 100 through the calculation data acquisition unit 510 in the auxiliary control unit 500A, and acquires the thumbnail data 510B. The thumbnail data 510B acquired at this time is supplied to the score calculation unit 520 together with the user data 510A. By reading the image data representing the thumbnail image 322 in step S104 or step S106, the first step is executed, and the first step acquires the first status data representing the status of the first subject using the functional element realized by the execution of the object program in the processing unit 11 of the server device 10 or the like.

[0085] After the image data representing the thumbnail image 322 is read in step S104 or step S106, the score calculation unit 520 performs calculation based on the user data 510A and the thumbnail data 510B according to the calculation model generated by machine learning, thereby obtaining the score data 520A for estimating the information related to the functional element matching the user (step S107). The score data 520A obtained at this time is temporarily stored in the storage unit 12 of the server device 10, for example, in the RAM, so that the score value shown in the score data 520A is stored (step S108). The score data 520A obtained by the calculation of the score calculation unit 520 is supplied to the prompt information determination unit 530. By obtaining the score data 520A in step S107, the second step is executed, which is based on the calculation model generated by machine learning based on at least one of the second state data representing the state of the second subject person who used the functional element in the past and the first state data stored in the past, and the first state data obtained in the first step. The first state data obtained in the first step is used to obtain the estimated data for estimating the information related to the functional element matching the user who is the first subject person.

[0086] After the prompt information determining unit 530 determines the information to be prompted to the user based on the score data 520A from the score calculation unit 520, it performs prompts such as display output of the tutorial in the terminal device 20 (step S109). For example, after a new page 100 is made, if a new floating sign is made according to the selection of an icon in the menu icon bar 50, the display content of the tutorial corresponding to the floating sign type is determined corresponding to the score value shown in the score data 520A. In addition, when the editing of the page 100 is started, if the floating sign is displayed in the screen display 26 of the page 100, the display content of the tutorial corresponding to the floating sign type of each floating sign displayed is determined corresponding to the score value shown in the score data 520A. The prompt information determining unit 530 generates prompt control data 530A for controlling the prompt of the determined tutorial. The processing unit 11 of the server device 10 transmits the prompt control data 530A from the communication unit 13 to the terminal device 20 via the network 30. The processing unit 21 of the terminal device 20 receives the prompt control data 530A from the server device 10 and presents the tutorial through the display output of the output unit 24. By presenting the tutorial in step S109, the third step is executed, which causes the presenting unit to present information related to the functional element matching the user as the first subject person based on the estimated data obtained in the second step.

[0087] After a new page 100 is created, or after editing of the page 100 corresponding to the thumbnail 322 is started, multiple types of functional elements corresponding to each floating tag are provided according to the operation input detected by the input unit 23 of the terminal device 20. When the screen display 26 of the page 100 is displayed and output, the input data or input instruction in the terminal device 20 is sent to the server device 10 via the network 30. The processing unit 11 of the server device 10 performs processing for providing multiple types of functional elements, such as output of calculation results, drawing of curves or graphs, and creation of numerical tables, based on the input data or input instructions received from the terminal device 20. The output data representing the processing results is sent from the server device 10 to the terminal device 20 via the network 30. The processing unit 21 of the terminal device 20 updates the display output in the display output device of the output unit 24 based on the output data received from the server device 10.

[0088] In this way, when the screen display 26 of the page 100 is displayed and output, it is determined whether the end of the editing based on closing the page 100 is indicated (step S110). For example, in the screen display 26 of the page 100, the input operation of selecting the menu item of returning to the my page screen 320 is detected by the touch panel, mouse, etc. provided in the input unit 23 of the terminal device 20, and notified to the processing unit 21 of the terminal device 20. The processing unit 21 of the terminal device 20 transmits a request corresponding to the notification from the communication unit 25 to the server device 10 via the network 30. The request transmitted at this time is also called an edit end request. The processing unit 11 of the server device 10 can recognize that the end of the editing of the page 100 is indicated by accepting the edit end request from the terminal device 20.

[0089] If the completion of the editing of the page 100 is not instructed (step S110: No), the process returns to step S109, and control based on the display output of the tutorial or other prompts is performed. On the other hand, if the completion of the editing of the page 100 is instructed (step S110: Yes), the processing unit 11 of the server device 10 creates image data representing the thumbnail image 322 corresponding to the page 100 after the editing is completed, and stores it in the storage unit 12 (step S111). For example, the processing unit 11 of the server device 10 updates the page management data of the page management table 210 in the database 200 to store the image data representing the new thumbnail image 322.

[0090] In this way, when the editing of the page 100 is completed, the display output in the display output device provided in the output unit 24 of the terminal device 20 returns to the display of the My Page screen 320. In addition, the processing unit 11 of the server device 10 deletes the score data 520A in response to the closing of the page 100, thereby clearing the storage of the score value (step S112). After that, when the instruction in the My Page screen 320 is accepted, it is determined whether the end condition is satisfied (step S113). In addition, when the start of the editing of the page 100 is not instructed in the My Page screen 320 (step S105: No), the processing is also entered into step S113 to determine whether the end condition is satisfied. In step S113, when the input operation of logging out in the My Page screen 320 is detected, when the input operation of transferring to another page is detected, when the input operation is not detected and the preset timeout time has passed, when a specific input operation is detected, or when the end determination time has passed without the input operation being detected, it is determined that the end condition is satisfied. If the termination condition is not satisfied (step S113: No), the process returns to step S103 to wait for a new page creation instruction, etc. On the other hand, when the termination condition is satisfied (step S113: Yes), the processing unit 11 of the server device 10 terminates the information provision process.

[0091] In the case of indicating the production of a new page, the tour function of explaining the use of the information processing service in stages can also be realized by combining the auxiliary information of multiple tutorials and displaying the prompt control data 530A output in sequence. For example, the tutorial prepared by dividing the detail of the information into multiple stages corresponding to the floating lottery type is constituted so that no matter which position the score value represented by the score data 520A is assigned to the floating lottery, the combination of multiple tutorials is determined corresponding to the floating lottery type. If the prompt information determination unit 530 obtains the score data 520A representing the score value, the tour function implemented when the new page is produced is determined based on the position assigned to the floating lottery. For example, when the production of the new page is initially indicated, the tour function corresponding to the floating lottery type with the largest score value is determined, and the prompt control data 530A for displaying and outputting multiple tutorials and prompting is generated in sequence. In addition, when the production of the new page is the indicated multiple times after the second time, it is determined to be the tour function corresponding to the floating lottery type with the smallest score value, and the prompt control data 530A for displaying and outputting multiple tutorials and prompting is generated in sequence. Alternatively, when the creation of a new page is the number of creations indicated after the second time, the tour function to be implemented from among the tour functions corresponding to the plurality of floating lottery types may be determined according to the number of times the new page is created, in a manner that changes from the floating lottery type with a large score value to the floating lottery type with a small score value as the number of times the new page is created increases, and the prompt control data 530A may be generated. The prompt control data 530A may be control data for automatically starting the tour function, or control data for prompting the user to start the tour function.

[0092] The prompt information determination unit 530 can determine the provision of various information based on the score value shown in the score data 520A obtained by the score calculation unit 520. For example, the icons corresponding to each floating sign arranged in the menu icon bar 50 can also be set to different display colors according to the score value shown in the score data 520A. The prompt information determination unit 530 determines the display color of the icons corresponding to these floating sign types when the score value shown in the score data 520A is used to assign the rank of each floating sign type. As an example of determining the display color of the icon, the display color of the icon can be determined so that the first floating sign type is red, the second floating sign type is orange, the third floating sign type is yellow, the fourth floating sign type is green, the fifth floating sign type is cyan, the sixth floating sign type is blue, and the seventh floating sign type is purple. In addition, the display color of the icon can be changed in the process of inferring the information related to the functional element matching the user, such as the user's click operation, the display color of the icon with more tapping operations can be changed in a manner corresponding to the rank with a high score value. The information display method is not limited to the display color of the icon. For example, the display size, display position, shape, pattern, gloss, brightness shown by the icon, or a combination of part or all of these, etc., can be made different to make the information display method different. In this way, the display information determination unit 530 can also make the icon indicating the start of the functional element of each floating sign different according to the multiple types of functional elements corresponding to the floating sign type based on the score data 520A obtained by the score calculation unit 520. The icon as information indicating the start of the functional element is included in the information related to the functional element.

[0093] As another example, in the screen display 26 of the page 100 presented by the output unit 24 of the terminal device 20, the presentation position of the display output tutorial may be set to a different position according to the score value shown in the score data 520A. In this case, the screen display 26 of the page 100 is divided into a plurality of display areas. Fig.127 display areas 190A~190G shown. However, the boundary lines of display areas 190A~190G are not actually displayed, which is a setting based on the prompt tutorial. The prompt information determination unit 530 determines the display area corresponding to these floating sign types when the score value shown in the score data 520A is used to set the rank of each floating sign type. As an example of determining the display area, the prompt position of the tutorial can be determined so that the first floating sign type is display area 190A, the second floating sign type is display area 190B, the third floating sign type is display area 190C, the fourth floating sign type is display area 190D, the fifth floating sign type is display area 190E, the sixth floating sign type is display area 190F, and the seventh floating sign type is display area 190G. In addition, the prompt position of the tutorial can be changed in the process of inferring information related to the functional elements matching the user, for example, the display area where the user makes a lot of floating signs can be changed in a way that corresponds to the rank with a high score value. In this way, the prompt processing function of the prompt information determination unit 530 can also be to determine different positions in the screen display 26 as positions for prompting information related to functional elements such as tutorials, based on the score data 520A equivalent to the estimated data obtained by the second acquisition function of the score calculation unit 520, according to multiple types of functional elements corresponding to the floating sign type.

[0094] As described above, in the information processing system 1 of the present embodiment, information processing using the processing unit 11 of the server device 10 is performed to realize Figure 6The structure of the auxiliary control unit 500A shown in FIG. 1 is a structure of the auxiliary control unit 500A. In the auxiliary control unit 500A, the first acquisition function implemented by the calculation data acquisition unit 510 is to acquire first state data such as thumbnail data 510B corresponding to the object to be floated, etc., and the thumbnail data 510B indicates the state of the user as the first object person using the functional element realized by the execution of the object program. The second acquisition function implemented by the score calculation unit 520 is to acquire the estimated data for estimating information related to the functional element matching the user who becomes the first object person, i.e., score data 520A, based on the first state data acquired by the first acquisition function of the calculation data acquisition unit 510 according to the calculation model generated by machine learning based on at least one of the second state data such as thumbnail data 540B indicating the state of the user who becomes the second object person different from the user who becomes the first object person using the functional element in the past and the thumbnail data 540B indicating the state of the user who becomes the first object person using the functional element in the past. The prompt processing function implemented by the prompt information determination unit 530 is to generate prompt control data 530A based on the score data 520A corresponding to the estimated data obtained by the second acquisition function of the score calculation unit 520, and to prompt information related to the functional element by displaying and outputting it on the output unit 24 of the terminal device 20. In this way, according to the calculation model generated by machine learning, based on the acquired estimated data, information related to the functional element matching the user who becomes the first object person is appropriately prompted, thereby improving the convenience of the user.

[0095] In addition, the calculation model is generated by machine learning based on user data 540A, which is attribute data representing a combination of part or all of the gender, age, and location of at least one of the user who becomes the first subject and the user who becomes the second subject. The first acquisition function implemented by the calculation data acquisition unit 510 is to further acquire user data 510A, which is attribute data of the user who becomes the first subject. The second acquisition function implemented by the score calculation unit 520 is to acquire score data 520A corresponding to the estimated data based on the first state data and user data 510A, which is attribute data of the user who becomes the first subject acquired by the first acquisition function of the calculation data acquisition unit 510, according to the calculation model. In this way, according to the calculation model generated by machine learning based on the attribute data of the user who becomes the first subject, etc., estimated data is acquired based on the attribute data of the user who becomes the first subject together with the first state data, so that information related to the functional elements matching the user who becomes the first subject can be more appropriately presented, which can improve the convenience of the user.

[0096] The prompt processing function implemented by the prompt information determination unit 530 is to prompt information with different details according to multiple types of functional elements corresponding to the floating lottery type through the display output of the output unit 24 of the terminal device 20, which serves as the prompt unit, based on the score data 520A corresponding to the estimated data. In this way, since the prompt unit prompts information with different details according to multiple types of functional elements, by further appropriately prompting information related to the functional elements with different details matching the user who becomes the first object person, the convenience of the user can be improved.

[0097] The prompt processing function implemented by the prompt information determination unit 530 is to prompt information of different quantities according to multiple types of functional elements corresponding to the floating lottery type through the display output of the output unit 24 of the terminal device 20, which serves as the prompt unit, based on the score data 520A corresponding to the estimated data. In this way, since the prompt unit prompts information of different quantities according to multiple types of functional elements, by further appropriately prompting information related to the functional elements of different quantities matching the user who becomes the first subject, the convenience of the user can be improved.

[0098] The information related to the functional element is auxiliary information of usage methods corresponding to multiple types of functional elements, such as tutorials corresponding to the floating tag types. Since such auxiliary information is presented to the presentation unit as information related to the functional element, the user's convenience can be improved by appropriately presenting auxiliary information matching the user who is the first object.

[0099] The thumbnail data 510B and the thumbnail data 540B, which are the first state data and the second state data, are image data representing the thumbnail image 322 corresponding to the screen display 26 of the page 100 using the functional element such as the floating tag. According to the calculation model generated by machine learning based on the first state data and the second state data of such image data, the prompting unit prompts information related to the functional element matching the first subject person based on the first state data, so that the user's convenience can be improved by appropriately prompting information related to the functional element matching the user who becomes the first subject person.

[0100] The prompt processing function implemented by the prompt information determination unit 530 is to prompt information related to the functional element, such as the icon in the menu icon bar 50, and information indicating the start corresponding to the functional element, through the display output of the output unit 24 of the terminal device 20, based on the score data 520A corresponding to the estimated data, in a prompting method different from the display color of the icon according to the multiple types of functional elements. In this way, the prompting unit is prompted in different prompting methods according to the multiple types of functional elements, so that the user's convenience can be improved by appropriately prompting information matching the user who is the first object so that the user can easily recognize the information related to the functional element.

[0101] The prompt processing function implemented by the prompt information determination unit 530 is to determine different positions in the prompt unit as positions for prompting information related to the functional elements based on the score data 520A corresponding to the estimated data, according to multiple types of functional elements such as the prompt position for displaying the output tutorial in the output unit 24 of the terminal device 20. In this way, information related to the functional elements is prompted at different positions in the prompt unit according to multiple types of functional elements, so that the user's convenience can be improved by appropriately prompting information matching the user who becomes the first object so that the user can easily recognize the information related to the functional elements.

[0102] The third acquisition function implemented by the learning data acquisition unit 540 is to acquire the thumbnail data 540B corresponding to at least one of the first state data and the second state data together with the page data 540C and the floating signature data 540D corresponding to the teacher data which are different from the first state data and the second state data. The update processing function implemented by the calculation model update unit 550 is to update the calculation model through machine learning based on the data acquired through the third acquisition function of the learning data acquisition unit 540. In this way, according to the calculation model updated by machine learning, based on the acquired estimated data, the information related to the functional element is prompted to the prompt unit, so that the user's convenience can be improved by appropriately prompting the information matching the user who becomes the first object.

[0103] In addition, the present invention is not limited to the above-mentioned embodiments, and various changes can be made. For example, the server device 10 may not have all the technical features shown in the above-mentioned embodiments, and may also have a part of the structure described in the above-mentioned embodiments so as to solve at least one problem in the prior art. In the above-mentioned embodiments, when a matter that becomes a subordinate concept is recorded, an invention using a superordinate concept of a matter of the same family or the same type of matter or an invention using a superordinate concept of a common property is included as the invention of the present application, and may also have a part of the structure and characteristics described in the above-mentioned embodiments so as to solve at least one problem in the prior art.

[0104] Figure 3 The tutorial 107 shown presents auxiliary information to the user by displaying and outputting description information using characters, numbers, symbols, etc. Instead of or in addition to such description information, the auxiliary information may be presented to the user by controlling the display output of image information using still images or moving images, the output of sound information, or any combination thereof.

[0105] exist Fig.11In the information providing process shown, in addition to step S111, image data representing the thumbnail image 322 may be created at any timing and stored in the storage unit 12. For example, in the screen display 26 of the page 100, image data representing the thumbnail image 322 may be created at the timing when a new floating label is created or when an existing floating label is edited. In addition, in the page management table 210, image data representing the thumbnail image 322 may be accumulated in correspondence with date and time information indicating the creation date and time, etc., at the timing when the image data representing the thumbnail image 322 is created. Thus, in the page management table 210, image data representing the thumbnail image 322 may be stored together with the date and time information as history information indicating the history of creation and editing of the floating label for each page 100. When the image data representing the thumbnail image 322 is stored in the page management table 210, the floating label management data stored in the floating label management table 220 may be updated. The learning data acquisition unit 540 may also acquire date and time information that is history information corresponding to one page 100 and image data representing the thumbnail image 322 as thumbnail data 540B included in the learning data. In addition, the learning data acquisition unit 540 may also acquire a part or all of the floating ticket management data that is history information corresponding to one page 100 as floating ticket data 540D included in the learning data. The calculation model update unit 550 may also update the calculation model by machine learning based on the thumbnail data 540B that is history information acquired by the learning data acquisition unit 540 and the floating ticket data 540D, when the user uses floating tickets of multiple types of functional elements corresponding to the floating ticket type, so as to obtain score data representing the probability distribution for predicting the possibility of selecting the functional element corresponding to the floating ticket type, such as the floating ticket to be created or edited next time. In this case, the score data indicating the probability distribution can be said to indicate the predicted next use possibility of the functional element corresponding to the type of the floating ticket by the size of the score value based on the past history of the user who is the first subject or the user who is the second subject making or editing the floating ticket. The score calculation unit 520 can also implement a second acquisition function of acquiring score data indicating the predicted use possibility based on the functional element based on the first state data acquired by the first acquisition function implemented by the calculation data acquisition unit 510 according to the calculation model generated by machine learning.

[0106] A coordinate operation unit may be provided in place of the score operation unit 520 or together with the score operation unit 520. The coordinate operation unit uses the operation data obtained by the operation data acquisition unit 510 to perform operation processing according to the operation model generated as a learned model through machine learning. The coordinate operation unit may obtain the operation model from the operation model storage unit 600 such as the storage unit 12 provided in the server device 10, and perform operation processing according to the operation model. The operation model used in the coordinate operation unit is a learned model generated through machine learning, so that the user data 510A and the thumbnail data 510B included in the operation data are input, and the coordinate data representing the coordinate values ​​of the display coordinates of the floating tag corresponding to each floating tag type is output, for example, Figure 7 The neural network model used in the coordinate operation unit outputs coordinate data representing the coordinate values ​​of the display coordinates of the tutorial in correspondence with the plurality of neurons included in the output layer and the respective floating label types. The coordinate data is data representing the coordinate values ​​of the display position of the floating label in the screen display 26 of the page 100, and can correspond to the coordinate values ​​in a one-to-one manner or specify the coordinate values ​​in each range of the coordinate data.

[0107] Fig.13 An example of determining the coordinate value of a floating tag by performing a calculation process of a calculation model by a coordinate calculation unit is shown. The prompt information determination unit 530 determines the coordinate value of the floating tag arranged on page 100 as information that the terminal device 20 prompts to the user through the display output of the output unit 24 in the information processing service based on the coordinate data that becomes the calculation result of the coordinate calculation unit. In addition, the coordinate value of the floating tag not arranged on page 100 can be determined as the origin. In this way, the coordinate data obtained by the coordinate calculation unit represents the coordinates of the following situation: for the first object person, that is, the user, who is the user of the floating tag that becomes the functional element in the information processing service provided by the information processing system 1, multiple types of functional elements corresponding to the floating tag type are provided through the display output of the output unit 24 of the terminal device 20.

[0108] The prompt information determination unit 530 generates prompt control data 530A in order to control the display position of each floating tag to be changed to the coordinates shown in the coordinate data. The prompt control data 530A can, for example, update the information such as the floating tag content stored in the floating tag management table 220, and include the display position information for changing the display position of the floating tag in the screen display 26 of the page 100. As in the above-mentioned embodiment, the prompt control data 530A generated by the prompt information determination unit 530 is transmitted to the terminal device 20, and the processing unit 21 of the terminal device 20 updates the display output in the display output device of the output unit 24. Thus, corresponding to multiple types of functional elements such as floating tags provided in the information processing service, the floating tags that realize each functional element at the position matching the user can be prompted as functional information. In this case, by supplying the prompt control data 530A generated by the prompt information determination unit 530 to the terminal device 20, information related to the functional elements matching the user can be prompted in the information processing service.

[0109] In this way, the information prompted using the prompt control data 530A generated by the prompt information determination unit 530 is not limited to a tutorial explaining the method of use, but may also be information for realizing the display position of a plurality of types of functional elements provided in the information processing service, such as a floating sign. That is, the floating sign, which is information using the functional element or information prompted as the functional element, is included in the information related to the functional element. The second acquisition function implemented by the coordinate operation unit is to obtain coordinate data representing the coordinates of information related to the functional element such as a floating sign corresponding to the plurality of types of functional elements based on the thumbnail data 510B equivalent to the first state data acquired by the first acquisition function of the calculation data acquisition unit 510 according to the calculation model. The prompt processing function implemented by the prompt information determination unit 530 is to change the position of the information related to the functional element such as the floating sign by display output in the output unit 24 of the terminal device 20 based on the coordinate data acquired by the second acquisition function of the coordinate operation unit. In this way, according to the calculation model, the position of the prompt function information is changed based on the acquired coordinate data, so that the convenience of the user can be improved by prompting the function information at an appropriate position matching the user who becomes the first object.

[0110] In addition, when prompting a user who is able to use multiple types of functional elements provided in an information processing service with various information related to the functional elements, such as questions that should be answered using each functional element, problems that should be solved using each functional element, and tasks that should be accomplished using each functional element, information determined by each structure of the auxiliary control unit 500A may be prompted.

[0111] The calculation data obtained by the calculation data acquisition unit 510 may also be, for example, detailed image data obtained by capturing the screen display 26 of the page 100, to replace the thumbnail data 510B. In addition, part or all of the information contained in the page management data stored in the page management table 210, part or all of the information contained in the floating label management data stored in the floating label management table 220, and data representing information related to the page 100 or each floating label may be included in the calculation data. For example, the calculation data acquisition unit 510 extracts the floating label ID from the floating label management data stored in the floating label management table 220. Then, the number of times used is counted according to each floating label type corresponding to the extracted floating label ID. The number of times used for each floating label type can be counted corresponding to each user, or can be counted corresponding to a plurality of users determined to have a commonality of part or all of the attribute data or characteristic data. The number of times each type of floating lottery ticket is used, which is counted in this way, can also be inputted into the score calculation unit 520 together with the user data 510A and the abbreviated data 510B, or in place of a part of the user data 510A and the abbreviated data 510B. Figure 7 In this case, the input layer of the neural network model used by the score calculation unit 520 to perform the calculation processing includes neurons to which data representing the number of times the functional element corresponding to the type of the floating sign is input. Therefore, the second acquisition function of the score calculation unit 520 can also be to obtain estimated data based on the data representing the number of times the functional element corresponding to the first acquisition function obtained by the calculation data acquisition unit 510 according to the calculation model. In addition, the calculation model can also be generated by machine learning based on the data representing the number of times the functional element is used.

[0112] The calculation model used by the score calculation unit 520 and the coordinate calculation unit is not limited to the calculation model using the neural network model, and can be constructed by applying any machine learning algorithm. For example, machine learning can be performed according to logistic regression, SVM (Support Vector Machine), decision tree, RFM (Random Forests Model), Q learning, DQN (Deep Q-Network), genetic programming, functional logic programming, self-organizing map, etc.

[0113] Such a calculation model may be prepared differently for each user who can use multiple types of functional elements provided by the information processing service, or a common calculation model may be prepared for multiple users. Alternatively, a different calculation model may be prepared for each group formed by grouping multiple users. In this case, multiple users may be grouped based on some or all of the attributes included in attribute information such as user category, age, gender, and location, or may be grouped based on the utilization level indicated by the characteristic information.

[0114] The information processing service provided by the information processing system 1 is not limited to services for performing calculations based on mathematical formulas, graphs or graphics. For example, multiple types of functional elements that users can use to learn subject content other than foreign languages ​​or programming languages ​​can also be provided. In addition, multiple types of functional elements that users can use to make, edit, and read various design drawings can also be provided. The design drawing can be any design drawing such as circuit design drawings, building design drawings, and other industrial product design drawings. Alternatively, multiple types of functional elements that users can use to make, edit, and read various articles can also be provided. Multiple types of functional elements that users can use to play games can also be provided. Multiple types of functional elements that users can use to shop online can also be provided. Multiple types of functional elements that users can use to conduct virtual tours can also be provided. In addition, in any information processing service that provides multiple types of functional elements that users can use to make, edit, and watch and listen to any image data or sound data, information related to the functional elements can be prompted.

[0115] The information processing service is not limited to the service provided by the information processing system 1 to which the server device 10 and the terminal device 20 can be connected via the network 30. For example, the same information processing service as the information processing system 1 can be provided by installing software in a personal computer. In this case, the processing of the server device 10 and the terminal device 20 in the above-mentioned embodiment can be executed in a personal computer, and information related to the functional elements that can be used in the information processing service can be displayed by display output in a display output device, etc.

[0116] The program executed by the server device 10 and the terminal device 20 can be stored in a computer-readable storage medium such as a floppy disk, a CD (Compact Disc)-ROM, a DVD (Digital Versatile Disc)-ROM, a memory card, etc. for application. Furthermore, the program can be superimposed on a carrier wave and applied via a communication medium such as the Internet. For example, the program can be posted and distributed on a bulletin board on a communication network, i.e., a BBS (Bulletin Board System), or the program can be stored in an FTP (File Transfer Protocol) server and downloaded. Moreover, the program can also be configured to be started and executed under the control of an OS (Operating System), thereby enabling the above-mentioned processing to be performed.

[0117] In addition, the specific details of the structure, control steps, display examples, etc. shown in the above-mentioned embodiments can be appropriately changed without departing from the scope of the present invention. Several embodiments of the present invention have been described, but the scope of the present invention is not limited to the above-mentioned embodiments, and includes the scope of the invention described in the claims and its equivalent scope.

Claims

1. A non-transitory computer-readable storage medium storing a program executable by at least one processor of an information processing device, in, the at least one processor, acquiring first status data indicating a status in which a first subject uses a functional element realized by execution of the target program, According to a calculation model generated by machine learning based on at least one of second state data and the first state data stored in the past, inferred data for inferring information related to the functional element matched to the first subject person is obtained based on the first state data obtained, the second state data indicating a state in which a second subject person different from the first subject person used the functional element in the past, Based on the acquired estimated data, causing a presentation unit to present information related to the functional element, The first status data and the second status data are image data representing thumbnail images of screen displays using the functional element.

2. The storage medium according to claim 1, in, The calculation model is generated by machine learning based on attribute data, wherein the attribute data represents a combination of part or all of the gender, age, and location of at least one of the first subject person and the second subject person, the at least one processor, further acquiring the attribute data of the first object person, The estimated data is acquired based on the first state data and the acquired attribute data of the first subject in accordance with the calculation model.

3. The storage medium according to claim 1 or 2, in, the at least one processor, Based on the estimated data, the presenting unit is caused to present information having different levels of detail according to the plurality of types of functional elements.

4. The storage medium according to claim 1 or 2, in, the at least one processor, Based on the estimated data, the presenting unit is caused to present different amounts of information corresponding to the plurality of types of functional elements.

5. The storage medium according to claim 1 or 2, in, The information related to the functional elements is auxiliary information indicating usage methods corresponding to a plurality of types of the functional elements.

6. The storage medium according to claim 1 or 2, in, the at least one processor, Based on the estimated data, the presenting unit presents information related to the functional element in a presentation method that differs according to the plurality of types of the functional elements.

7. The storage medium according to claim 1 or 2, in, the at least one processor, Based on the estimation data, a position in the presentation unit that is different according to a plurality of types of the functional elements is determined as a position for presenting information related to the functional element.

8. The storage medium according to claim 1 or 2, in, the at least one processor, According to the calculation model, based on the first state data obtained, coordinate data indicating coordinates of information related to the plurality of types of functional elements is obtained; Based on the acquired coordinate data, a position where information related to the functional element is presented on the display unit as the presenting unit is changed.

9. The storage medium according to claim 1 or 2, in, the at least one processor, acquiring at least one of the first state data and the second state data together with teacher data different from the first state data and the second state data, The calculation model is updated by machine learning based on at least one of the first state data and the second state data and the teaching data.

10. The storage medium according to claim 1 or 2, in, The functional elements include functional elements related to calculation and functional elements related to rendering that are realized by executing the learning program as the target program.

11. An information processing method of an information processing device, in, acquiring first status data indicating a status in which a first subject uses a functional element realized by execution of the target program, According to a calculation model generated by machine learning based on at least one of second state data and the first state data stored in the past, inferred data for inferring information related to the functional element matched to the first subject person is obtained based on the first state data obtained, the second state data indicating a state in which a second subject person different from the first subject person used the functional element in the past, Based on the acquired estimated data, causing a presentation unit to present information related to the functional element, The first status data and the second status data are image data of thumbnail images representing screen displays using the functional elements.

12. The information processing method according to claim 11, in, The calculation model is generated by machine learning based on attribute data, wherein the attribute data represents a combination of part or all of the gender, age, and location of at least one of the first subject person and the second subject person, The information processing method, further acquiring the attribute data of the first object person, The estimated data is acquired based on the first state data and the acquired attribute data of the first subject in accordance with the calculation model.

13. The information processing method according to claim 11 or 12, in, Based on the estimated data, the presenting unit is caused to present information having different levels of detail according to the plurality of types of functional elements.

14. The information processing method according to claim 11 or 12, in, Based on the estimated data, the presenting unit is caused to present different amounts of information corresponding to the plurality of types of functional elements.

15. The information processing method according to claim 11 or 12, in, The information related to the functional elements is auxiliary information indicating usage methods corresponding to a plurality of types of the functional elements.

16. The information processing method according to claim 11 or 12, in, Based on the estimated data, the presenting unit presents information related to the functional element in a presentation method that differs according to the plurality of types of the functional elements.

17. The information processing method according to claim 11 or 12, in, Based on the estimation data, a position in the presentation unit that is different according to a plurality of types of the functional elements is determined as a position for presenting information related to the functional element.

18. An information processing device comprising at least one processor for executing a program stored in a storage unit, in, the at least one processor, acquiring first status data indicating a status in which a first subject uses a functional element realized by execution of the target program, According to a calculation model generated by machine learning based on at least one of second state data and the first state data stored in the past, inferred data for inferring information related to the functional element matched to the first subject person is obtained based on the first state data obtained, the second state data indicating a state in which a second subject person different from the first subject person used the functional element in the past, Based on the acquired estimated data, causing a presentation unit to present information related to the functional element, The first status data and the second status data are image data representing thumbnail images of screen displays using the functional element.

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