Recommended content proposal program, recommended content proposal device, recommended content proposal method, and storage medium

Abstract

To provide a recommended content proposal program capable of recommending content matching a user's preferences.SOLUTION: A recommended content proposal program includes a generation procedure and an output procedure. The generation procedure generates recommended content information indicative of recommended content for a user on the basis of emotion time-series information indicative of a time series of the user's emotions, content time-series information indicative of a time series of portions of content browsed by the user, and content information indicative of contents of the content. The output procedure outputs the recommended content information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a recommended content suggestion program, a recommended content suggestion device, a recommended content suggestion method, and a recording medium. [Background technology]

[0002] Patent document 1 discloses an e-book system comprising an online e-book server having a storage device for storing a plurality of digital books, a communication means for importing the digital books, an input means operated by the reader, an e-book portable terminal having a display device for the reader to read the digital books, a storage device for storing a large number of digital books, and a communication means for delivering digital books to the e-book portable terminal in response to the operation of the reader operating the e-book portable terminal, wherein after the reader downloads a book from the online e-book server to the e-book portable terminal, the e-book portable terminal automatically records the reader's reading status while reading and notifies the publisher of the reading status via the communication means. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2004-252869 Summary of the Invention [Problem to be solved by the invention]

[0004] According to the invention of Patent Document 1, it is possible to grasp the reading status of a reader. On the other hand, the invention of Patent Document 1 does not make it possible to recommend content that matches the preferences of a user.

[0005] Therefore, an object of the present disclosure is to provide a recommended content suggestion program, a recommended content suggestion device, a recommended content suggestion method, and a recording medium that are capable of recommending content that matches a user's preferences. [Means for solving the problem]

[0006] In order to achieve the above object, the recommended content suggestion program of the present disclosure includes: A generating procedure and an output procedure are included, The generation step generates recommended content information indicating content recommended to the user based on emotion time series information indicating a time series of the user's emotions, content time series information indicating a time series of browsing positions of content browsed by the user, and content information indicating the details of the content; the output step outputs the recommended content information. The present invention is a recommended content suggestion program for causing a computer to execute each of the above procedures.

[0007] The recommended content suggestion device of the present disclosure includes: a generating unit and an output unit, the generation unit generates recommended content information indicating content recommended to the user based on emotion time series information indicating a time series of the user's emotions, content time series information indicating a time series of browsing positions of content browsed by the user, and content information indicating details of the content; the output unit outputs the recommended content information. A recommended content suggestion device.

[0008] The recommended content suggestion method of the present disclosure includes: A generating step and an output step are included, the generating step generates recommended content information indicating content recommended to the user based on emotion time series information indicating a time series of the user's emotions, content time series information indicating a time series of browsing positions of content browsed by the user, and content information indicating the details of the content; The output step outputs the recommended content information. The method for proposing recommended content is implemented by a computer.

[0009] The recording medium of the present disclosure includes: A generating procedure and an output procedure are included, The generation step generates recommended content information indicating content recommended to the user based on emotion time series information indicating a time series of the user's emotions, content time series information indicating a time series of browsing positions of content browsed by the user, and content information indicating the details of the content; the output step outputs the recommended content information. A computer-readable recording medium stores a recommended content suggestion program for causing a computer to execute each of the above procedures. [Effects of the Invention]

[0010] According to the present disclosure, it is possible to recommend content that matches the preferences of a user. [Brief explanation of the drawings]

[0011] [Figure 1] FIG. 1 is a block diagram showing an example of the configuration of a recommended content suggestion device according to the present disclosure. [Figure 2] FIG. 2 is a block diagram showing an example of the hardware configuration of the recommended content suggestion device of the present disclosure. [Figure 3] FIG. 3 is a flowchart showing an example of a procedure performed by the recommended content suggestion program of the present disclosure. [Figure 4] FIG. 4 is a block diagram showing another example of the configuration of the recommended content suggestion device of the present disclosure. [Figure 5] FIG. 5 is a flowchart showing another example of the procedure of the recommended content suggestion program of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. The present disclosure is not limited to the following embodiments. In the following drawings, identical parts are designated by the same reference numerals. Furthermore, the descriptions of the embodiments can be used interchangeably unless otherwise specified, and the configurations of the embodiments can be combined unless otherwise specified. In the present disclosure, each drawing may apply to one or more embodiments.

[0013] [Embodiment 1] The recommended content suggestion program of the present disclosure is a program for causing a computer to execute a generation procedure and an output procedure. The recommended content suggestion program of the present disclosure can also be said to be a program for causing a computer to function as the generation procedure and the output procedure. Furthermore, the recommended content suggestion program of the present disclosure can also be said to be a program for causing a computer to execute, for example, each step of a recommended content suggestion method described below.

[0014] The generation procedure generates recommended content information indicating recommended content for the user based on emotion time series information indicating the time series of the user's emotions, content time series information indicating the time series of the viewed parts of the content viewed by the user, and content information indicating the content of the content, and the output procedure outputs the recommended content information.

[0015] In each of the steps, for example, "step" can be read as "processing." The recommended content suggestion program of the present disclosure may be recorded on, for example, a computer-readable recording medium. The recording medium is, for example, a non-transitory computer-readable storage medium. The recording medium is not particularly limited, and examples thereof include random access memory (RAM), read-only memory (ROM), hard disk (HD), flash memory (e.g., SSD (Solid State Drive), USB flash memory, SD / SDHC card, etc.), optical disk (e.g., CD-R / CD-RW, DVD-R / DVD-RW, BD-R / BD-RE, etc.), magneto-optical disk (MO), floppy disk (FD), etc. The recommended content suggestion program of the present disclosure (also referred to as, for example, a programming product or program product) may be distributed from an external computer. The "distribution" may be, for example, distribution via a communication network or via a device connected via a wire. The recommended content suggestion program of the present disclosure may be installed and executed on a device to which it is distributed, or may be executed without being installed. An information processing device capable of executing the recommended content suggestion program of the present disclosure can be referred to as, for example, a recommended content suggestion device of the present disclosure.

[0016] Next, an example of the configuration of a recommended content suggestion device according to the present disclosure will be described with reference to FIG. 1. FIG. 1 is a block diagram showing an example of the configuration of a recommended content suggestion device 10 according to the present disclosure (hereinafter also referred to as the present device 10). As shown in FIG. 1, the present device 10 includes a generation unit 11 and an output unit 12. Although not shown, the present device 10 may also include, for example, an input unit, an output unit, a display unit, and / or a storage unit. The generation unit 11 and the output unit 12 are capable of executing, for example, a generation procedure and an output procedure in the recommended content suggestion program according to the present disclosure.

[0017] The device 10 may be, for example, a single device including the above-described units, or a device in which the units can be connected via a communication network. The device 10 can also be connected to an external device (described later) via the communication network. The communication network is not particularly limited and any known network can be used, for example, a wired or wireless network. Examples of the communication network include the Internet, the World Wide Web (WWW), a telephone line, a Local Area Network (LAN), a Storage Area Network (SAN), a Delay Tolerant Networking (DTN), a Low Power Wide Area Network (LPWA), and a Local 5G (L5G). Examples of wireless communication include Wi-Fi (registered trademark), Bluetooth (registered trademark), Local 5G, and LPWA. Examples of the wireless communication include direct communication between devices (Ad Hoc communication), infrastructure communication, and indirect communication via an access point. The device 10 may be incorporated into a server as a system. Furthermore, the present device 10 may be, for example, a personal computer (PC, for example, desktop or notebook type) on which the program of the present disclosure is installed, a smartphone, a tablet terminal, etc. The present device 10 may be in the form of cloud computing or edge computing, for example, in which at least one of the above-mentioned units is located on a server and the other units are located on a terminal.

[0018] 2 shows a block diagram of the hardware configuration of the device 10. The device 10 includes, for example, a central processing unit (CPU, GPU, etc.) 101, a memory 102, a bus 103, a storage device 104, an input device 105, an output device 106, and a communication device 107. The components of the device 10 are connected to each other via the bus 103 and their respective interfaces (I / F).

[0019] The central processing unit 101 cooperates with other components via a controller (such as a system controller or an I / O controller) and controls the entire device 10. In the device 10, the central processing unit 101 executes, for example, the program of the present disclosure (a recommended content suggestion program) and other programs, and also reads and writes various information. Specifically, for example, the central processing unit 101 functions as a generation unit 11 and an output unit 12. The device 10 may include, as a computing device, other computing devices such as a CPU, a GPU (Graphics Processing Unit), an APU (Accelerated Processing Unit), or a combination of these.

[0020] The bus 103 can also be connected to, for example, external devices. Examples of the external devices include an external storage device (such as an external database), a printer, an external input device, an external display device, and an external imaging device. The device 10 can be connected to an external network (the communication line network) by, for example, a communication device 107 connected to the bus 103, and can also be connected to other devices via the external network.

[0021] The memory 102 may be, for example, a main memory (primary storage device). When the central processing unit 101 performs processing, the memory 102 reads various operating programs, such as the program of the present disclosure, stored in the storage device 104 (described later), and the central processing unit 101 receives data from the memory 102 and executes the programs. The main memory may be, for example, a RAM (random access memory). The memory 102 may also be, for example, a ROM (read only memory).

[0022] The storage device 104 is also referred to as an auxiliary storage device, for example, in contrast to the main memory (primary storage device). As described above, the storage device 104 stores an operating program including the program of the present disclosure. The storage device 104 may be, for example, a combination of a recording medium and a drive for reading and writing data from and to the recording medium. The recording medium is not particularly limited and may be, for example, an internal or external type, such as a hard disk (HD), CD-ROM, CD-R, CD-RW, MO, DVD, flash memory, or memory card. The storage device 104 may be, for example, a hard disk drive (HDD) or a solid-state drive (SSD) in which the recording medium and drive are integrated. When the device 10 includes the storage unit, the storage device 104 functions as the storage unit, for example. The storage unit can store, for example, emotion time-series information, content time-series information, content information, recommended content information, feature information, purpose information, evaluation information, history information, other person information, and biometric information, as described below.

[0023] In the present device 10, the memory 102 and the storage device 104 can also store various information such as log information, information acquired from an external database (not shown) or an external device, information generated by the present device 10, and information used when the present device 10 executes processing. In this case, the memory 102 and the storage device 104 may store, for example, the above-mentioned information on the user of the present device. Note that at least a portion of the information may be stored, for example, in an external server other than the memory 102 and the storage device 104, or may be stored in a distributed manner across multiple terminals using blockchain technology or the like.

[0024] The device 10 further includes, for example, an input device 105 and an output device 106. Examples of the input device 105 include pointing devices such as a touch panel, track pad, and mouse; a keyboard; imaging means such as a camera and scanner; card readers such as an IC card reader and a magnetic card reader; and audio input means such as a microphone. Examples of the output device 106 include display devices such as an LED display and a liquid crystal display; audio output devices such as a speaker; a printer; and the like. In the first embodiment, the input device 105 and the output device 106 are configured separately, but the input device 105 and the output device 106 may be configured as an integrated device, such as a touch panel display.

[0025] An example of processing by the recommended content suggestion program of the present disclosure will be described more specifically with reference to Fig. 3. Fig. 3 is a flowchart showing an example of each procedure of the recommended content suggestion program of the present disclosure.

[0026] The generation unit 11 generates recommended content information indicating recommended content for the user based on emotion time series information indicating the time series of the user's emotions, content time series information indicating the time series of the viewed parts of the content viewed by the user, and content information indicating the content of the content (S1, generation procedure).

[0027] The emotion time series information is not particularly limited, and may be, for example, information indicating a time series of a user's emotion. The emotion time series information may be, for example, information linking emotion information with time series information. The emotion information may be, for example, information indicating a user's emotion. The time series information may be, for example, information indicating a time series of acquired biometric information, which will be described later. The emotion information may be, for example, an estimation of the user's emotion based on the user's biometric information. The estimation of the emotion based on the biometric information may be performed, for example, by an emotion information generation model that generates emotion information of the user when the user's biometric information is input. The emotion information may be, for example, emotion score information that scores the user's emotion, or emotion coordinate information that indicates coordinates in a multidimensional orthogonal coordinate system based on an emotion model. When the user's biometric information is input, for example, the emotion information generation model may generate the emotion score information or the emotion coordinate information. The emotion information generation model may be, for example, a model using a multidimensional orthogonal coordinate system based on an emotion model. The emotion model may be, for example, a Russell Circumplex model, but is not limited to this description. The emotion information generation model may be, for example, a publicly known model, such as the emotion analysis engine included in "NEC Emotion Analysis Solution," but is not limited to this description. The generation unit 11 may, for example, acquire the user's biometric information by linking it with the time-series information, generate the emotion information indicating the user's emotion based on the biometric information, link the emotion information with the time-series information, and generate the emotion time-series information.

[0028] The emotion information generation model may be stored, for example, in the memory 102 or storage device 104 of the device of the present disclosure, or may be stored in the memory or storage device of a device other than the device of the present disclosure.

[0029] The Russell circumplex model, for example, proposes that all emotions are located as points in a two-dimensional Cartesian coordinate system consisting of an AROUSAL axis indicating "pleasant-unpleasant" and a VALENCE axis indicating "alertness-sleepiness." The two-dimensional Cartesian coordinate system based on the Russell circumplex model classifies, for example, the first quadrant into "HAPPY," the second quadrant into "ANGRY," the third quadrant into "SAD," and the fourth quadrant into "RELAXED" out of the four quadrants of the two-dimensional Cartesian coordinate system. Therefore, the model based on the Russell circumplex model can estimate the emotion based on, for example, the quadrant in which the point indicated by the emotion coordinate information is located. Furthermore, the two-dimensional Cartesian coordinate system based on the Russell circumplex model classifies the type of emotion using, for example, a vector with its starting point at the origin of the two-dimensional Cartesian coordinate system and its end point being the emotion coordinate information. Specifically, the two-dimensional Cartesian coordinate system based on the Russell circumplex model classifies types of emotions in the two-dimensional Cartesian coordinate system based on, for example, the angle between the vector and the coordinate axis and the length of the vector. Therefore, emotion estimation based on the Russell circumplex model can estimate the emotion based on, for example, the origin of the two-dimensional Cartesian coordinate system and the emotion coordinate information. In this case, emotions estimated based on the Russell circumplex model include, for example, emotions included in the "ANGRY" quadrant, such as "tense," "nervous," "stressed," and "upset," emotions included in the "SAD" quadrant, such as "sad," "depressed," and "bored," emotions included in the "RELAXED" quadrant, such as "calm," "relaxed," "serene," and "content," and emotions included in the "HAPPY" quadrant, such as "happy," "elated," "excited," and "alert."

[0030] The biological information is, for example, information about a living organism, and examples thereof include information about the eyeballs, information about voice, information about movement, information about facial expressions, and information about physiological indices. The biological information may be, for example, a feature (e.g., mean, standard deviation, coefficient of variation, root mean square, frequency component, etc.) calculated using a known method based on the above-mentioned information about the living organism. The physiological indices include, for example, brain waves, heart rate, pulse, blood pressure, electrocardiogram, electromyogram, sweating, body temperature, skin temperature, and combinations thereof. The information about the physiological indices may be, for example, the physiological indices themselves (e.g., values ​​of the physiological indices, ratios of the physiological indices, etc.) or feature calculated from the physiological indices using a known method. For example, if the physiological index is pulse rate, examples of the information about the physiological indices include PPI (pulse peak interval).

[0031] The medium for acquiring the biological information may be, for example, a medical device or a wearable terminal. The medical device is, for example, a device having a function for measuring the biological information. Examples of the medical device include an electroencephalograph, a heart rate monitor, a pulse rate monitor, a blood pressure monitor, an electrocardiograph, an electromyograph, a sweat meter (a skin potential meter), a thermometer, and a skin thermometer. The wearable terminal is, for example, a terminal having a function for measuring the biological information. Examples of the type of the wearable terminal include a wristband type, a watch type, a clip type, a ring type, an earphone type, an eyeglass type, a goggle type, a contact lens type, a patch type, and a clothing type.

[0032] The emotion time-series information may include, for example, other information. The other information includes, for example, acquisition medium identification information (e.g., an identification number) that can identify an acquisition medium of the biometric information, user identification information (e.g., a name, an ID, etc.) that can identify a user, terminal identification information (e.g., an identification number, etc.) that can identify a user's terminal, user attribute information (e.g., gender, affiliation, occupation, age, job title, etc.), status information of the emotion time-series information (e.g., information indicating whether the emotion time-series information is valid or invalid), status information of the emotion information (e.g., information indicating whether the emotion information is valid or invalid), and invalidation information (e.g., whether or not invalidation information (e.g., information described below) has been assigned).

[0033] The emotion time-series information may be acquired, for example, by the device of the present disclosure, or by a device other than the device of the present disclosure. The acquired emotion time-series information may be stored, for example, in the memory 102 or storage device 104 of the device of the present disclosure, or in the memory or storage device of a device other than the device of the present disclosure.

[0034] The content time series information is not particularly limited, and may be, for example, information indicating the time series of viewing locations of the content viewed by the user. The content time series information may be, for example, information linking content viewing location information with time series information. The content viewing location information may be, for example, information regarding the viewing locations of the content viewed by the user. The content viewing location information may be, for example, coordinate information, which will be described later, or information based on coordinate information, which will be described later. The time series information may be, for example, information indicating the time series in which the content viewing location information was acquired. The generation unit 11 may, for example, acquire the content viewing location information in association with the time series information, link the content viewing location information with the time series information, and generate the content time series information.

[0035] The generation unit 11 may generate information regarding a user's content viewing speed, for example, based on the content time series information at a certain time point and the content time series information at a certain time point after the certain time point. Specifically, the generation unit 11 first calculates the viewing time required for the user to view the content, for example, from the time series information at the certain time point and the time series information at a certain time point after the certain time point. Next, the generation unit 11 calculates the number of characters viewed by the user within the viewing time, for example, from the content viewing location information at the certain time point and the content viewing location information at a certain time point after the certain time point. Finally, the generation unit 11 can generate information regarding the user's content viewing speed by calculating the number of characters the user can view per unit time, for example, from the viewing time and the number of characters viewed. Therefore, according to the present disclosure, for example, when a user requests content that can be completely viewed within a specific time, recommended content can be recommended according to the user's content viewing speed.

[0036] The content is not particularly limited, and is information that can be recognized by human perception, such as a book or a video. The book includes, for example, those that are mainly composed of text (e.g., novels, poetry collections, tanka, haiku, etc.) and those that are mainly composed of text and pictures (e.g., manga, picture books, etc.). The video includes, for example, movies and television programs. For example, when the content is a book, the content may be a paper medium or an electronic medium.

[0037] The content viewing medium may be, for example, an XR (cross reality) device when the content is an electronic medium. Examples of the XR device include a VR (virtual reality) device, an MR (mixed reality) device, and an AR (augmented reality) device. The content viewing medium may be, for example, a medium having a function for measuring the biometric information. The content viewing medium may be, for example, an acquisition medium having an eye tracking function, which will be described later. The content viewing medium may be, for example, the device itself disclosed herein, or a device other than the device disclosed herein.

[0038] For example, if the content is an electronic medium, the content viewing medium may be a personal computer (e.g., desktop, notebook, all-in-one, etc.), a smartphone terminal, or a tablet terminal. The content viewing medium may be, for example, a medium equipped with a function for measuring the biometric information. The content viewing medium may be, for example, an acquisition medium equipped with an eye-tracking function, which will be described later. The content viewing medium may be, for example, the device itself of the present disclosure, or a device other than the device of the present disclosure.

[0039] The acquisition medium for the content viewing location information may be, for example, an acquisition medium with an eye tracking function (e.g., an eye tracker, etc.). The eye tracking function, for example, tracks gaze. The eye tracking function may, for example, be a function that tracks gaze based on pupil movement, but is not limited to this description. The acquisition medium with the eye tracking function may, for example, be a wearable type or a screen-based type. The acquisition medium with the eye tracking function may, for example, be a medium with a function that can measure the biometric information. The acquisition medium with the eye tracking function may, for example, be the content viewing medium. The acquisition medium for the content viewing location information may, for example, be the device itself of the present disclosure, or a device other than the device of the present disclosure.

[0040] The acquisition of the content viewing location information may be, for example, acquisition of coordinate information indicating the coordinates of the viewing location in the content, or acquisition of information based on the coordinate information. In the former case, the acquisition of the content viewing location information may be performed, for example, by identifying the viewing location of the content viewed by the user using an acquisition medium having the eye tracking function. In the latter case, the acquisition of the content viewing location information may be performed, for example, by identifying structural information of the content based on the coordinate information. For example, if the content is a book, the structural information may include the page number of the content, the paragraph number of the content, the line number of the content, the column number of the content, the position from the first line of the content, and the position from the first column of the content. The acquisition of the content viewing location information may be, for example, acquisition of the coordinate information linked to the time series information. The acquisition of the content viewing location information may be, for example, acquisition of information based on the coordinate information linked to the time series information. For example, the generation unit 11 may acquire the viewing location of the content viewed by the user as image data simultaneously with acquisition of the content viewing location information. In this case, the generation unit 11 may extract character information included in the image data by, for example, OCR (Optical Character Recognition) and add the character information to the content viewing location information. For example, if the content is a book, the unit of the content viewing location information may be a word, a phrase, a sentence, a paragraph, a paragraph, an entire page, or a combination thereof.

[0041] The content time series information may include, for example, other information, such as acquisition medium identification information (e.g., identification number, etc.) that can identify an acquisition medium from which the content viewing location information was acquired, content identification information (e.g., identification number, etc.) that can identify the content, user identification information (e.g., name, ID, etc.) that can identify a user, terminal identification information (e.g., identification number, etc.) that can identify a user's terminal, and user attribute information (e.g., gender, affiliation, occupation, age, job title, etc.).

[0042] The content time series information may be acquired by, for example, the device of the present disclosure, or may be acquired by a device other than the device of the present disclosure. The acquired content time series information may be stored in, for example, the memory 102 or the storage device 104 of the device of the present disclosure, or may be stored in the memory or storage device of a device other than the device of the present disclosure.

[0043] The content information is not particularly limited and may be, for example, information indicating the content of the content. Examples of the content information include content attribute information indicating the attributes of the content and feature information indicating the features of each part of the content. The content attribute information may include, for example, the title of the content, the genre of the content, the total number of pages of the content, the name of the author of the content, the release date of the content, word-of-mouth reviews of the content, award history of the content, whether the content has been adapted into media, and whether the content has been completed.

[0044] The feature information is, for example, information linking content feature information with content posting location information. The content feature information is, for example, information indicating the features of the content. The content feature information includes, for example, content emotion information, story information, character information, scene information, frequently occurring words in the content, and the required time for the content. The content emotion information is, for example, information indicating the emotion caused by viewing the content, and is estimated based on a known emotion model. An example of the emotion model is the Russell Circumplex model, but the present invention is not limited to this description. The content emotion information may be, for example, information corresponding to the emotion information, information corresponding to the emotion score information, or information corresponding to the emotion coordinate information. The story information is, for example, information indicating the development of the story of the content, and may be information indicating whether the development of the story of the content corresponds to an introduction, development, turn, and conclusion, whether it corresponds to a jo-ha-kyu structure, whether it corresponds to a three-act structure, or whether it corresponds to a beat sheet. The character information is, for example, information indicating a character appearing in the content, including the character's personality, the character's gender, the character's age, the character's height and weight, the character's occupation, and the character's role in the story. The scene information is, for example, information indicating a scene in the content, including a location and a time period. The content posting location information is, for example, information indicating a location in the content where the feature is posted. The content posting location information may be, for example, the coordinate information or information based on the coordinate information. For example, if the content is a book, the unit of the content posting location information may be a word, a phrase, a sentence, a paragraph, a passage, an entire page, or a combination thereof. According to the present disclosure, for example, the features of each location in content can be linked to a user's emotions, thereby making it possible to grasp the features of the user's preferred content for each location and recommend content that better suits the user's preferences.

[0045] The content information may be, for example, stored in the memory 102 or storage device 104 of the device of the present disclosure, or may be stored in a memory or storage device of a device other than the device of the present disclosure. The content information may be, for example, acquired from the memory 102 or storage device 104 of the device of the present disclosure, or may be acquired from the memory or storage device of a device other than the device of the present disclosure.

[0046] The recommended content information is not particularly limited, and may be, for example, information indicating recommended content for the user. The recommended content may, for example, refer to an explanation of the content.

[0047] The recommended content information may be stored, for example, in the memory 102 or storage device 104 of the device of the present disclosure, or in the memory or storage device of a device other than the device of the present disclosure.

[0048] Generation of the recommended content information based on the emotion time-series information, the content time-series information, and the content information is not particularly limited, and can be performed, for example, by a recommended content information generation model that generates the recommended content information when the emotion time-series information, the content time-series information, and the content information are input. The recommended content information generation model may be a model that generates the recommended content information when, in addition to the emotion time-series information, the content time-series information, and the content information, at least one of objective information, evaluation information, history information, and other people's information, which will be described later, is input.

[0049] The recommended content information generation model may be stored, for example, in the memory 102 or storage device 104 of the device of the present disclosure, or may be stored in the memory or storage device of a device other than the device of the present disclosure.

[0050] Furthermore, the generation unit 11 may generate the recommended content information by taking into account at least one of, for example, purpose information indicating the user's purpose for viewing the content, evaluation information indicating the user's evaluation of the content, history information indicating the viewing history of content viewed by the user, and other information regarding users other than the user (S1A, generation procedure).

[0051] The intent information is, for example, information indicating the user's intent for viewing the content. The intent information may be, for example, information regarding an emotion the user wants to achieve by viewing the content. In this case, the intent information may be, for example, information corresponding to the emotion information, the emotion score information, or the emotion coordinate information.

[0052] The evaluation information is, for example, information indicating the user's evaluation of the content. The evaluation information may be, for example, an evaluation of the content as a whole, or an evaluation of a portion of the content. The evaluation of the portion of the content may be based, for example, on the content viewing location information. The evaluation information may be, for example, an evaluation of the good points of the content, or an evaluation of the bad points of the content. The evaluation information may be, for example, information regarding a self-evaluation of emotions caused by viewing the content. In this case, the evaluation information may be, for example, information corresponding to the emotion information, information corresponding to the emotion score information, or information corresponding to the emotion coordinate information.

[0053] The history information is, for example, information indicating the browsing history of the content browsed by the user. The history information may include, for example, information regarding when the user browsed the content (e.g., date, season, the user's age at the time of browsing, etc.), information regarding what prompted the user to browse the content (e.g., spontaneous browsing, browsing due to a recommendation from another person, browsing based on rankings, browsing based on the author, browsing for the purpose of exploring new content, etc.), and information regarding the time required for the user to browse the content. The history information may include, for example, the purpose information regarding the content browsed by the user and the evaluation information regarding the content browsed by the user.

[0054] The other person information is, for example, information about users other than the user. The other person information includes, for example, the purpose information indicating the purpose of viewing the content by the other users other than the user, the evaluation information indicating the evaluations of the content by the other users other than the user, and the history information indicating the viewing history of content viewed by the other users other than the user. The other person information may include, for example, the emotion time series information of the other users other than the user and the content time series information of the other users other than the user. According to the present disclosure, for example, by inputting the other person information into the recommended content information generation model, information about users other than the user who have similar tastes to the user can be reflected in the recommended content information.

[0055] The generation of the recommended content information taking into account at least one of the purpose information, the evaluation information, the history information, and the information of others can be performed by the recommended content information generation model that generates the recommended content information when at least one of the purpose information, the evaluation information, the history information, and the information of others is input in addition to the emotion time series information, the content time series information, and the content information.

[0056] The objective information, the evaluation information, the history information, and the information of others may be stored, for example, in the memory 102 or storage device 104 of the device disclosed herein, or may be stored in the memory or storage device of a device other than the device disclosed herein.

[0057] Furthermore, for example, when the content is a book, the generation unit 11 may generate the recommended content information based on the emotion time-series information, unit time-series information, and unit feature information (S1B, generation step).

[0058] The content time series information includes, for example, the unit time series information. The unit time series information is, for example, information indicating the time series of at least one of viewed sentences, viewed phrases, and viewed words in a book viewed by the user. In the unit time series information, for example, the unit of the content viewing location information is at least one of sentences, phrases, and words. The content information includes, for example, the unit feature information. The unit feature information is, for example, information indicating at least one of characteristics of each sentence of the book, characteristics of each phrase of the book, and characteristics of each word of the book. In the unit feature information, for example, the unit of the content publication location information is at least one of sentences, phrases, and words. According to the present disclosure, for example, if the content is a book, it is possible to link the user's emotions to each sentence, phrase, or word in the book, thereby making it possible to understand the user's preferred content in more detail.

[0059] The output unit 12 outputs the recommended content information (S2, output step).

[0060] The recommended content suggestion method of the present disclosure (hereinafter also referred to as the method of the present disclosure) is a method implemented, for example, by replacing the "procedures" in the program of the present disclosure with "processes." Specifically, the method of the present disclosure includes a generating process and an outputting process. The generating process generates recommended content information indicating content recommended to the user based on emotion time-series information indicating the time series of the user's emotions, content time-series information indicating the time series of the browsing locations of the content browsed by the user, and content information indicating the content of the content. The outputting process outputs the recommended content information. The method of the present disclosure can be implemented, for example, using the device 10 of the present disclosure shown in FIG. 1 or FIG. 2. Note that the method of the present disclosure is not limited to a method using the device 10 of the present disclosure. For example, the description of the program and the device of the present disclosure can be used for the method of the present disclosure.

[0061] As described above, according to the recommended content suggestion program of the present disclosure, a generation step generates recommended content information indicating content recommended to the user based on emotion time-series information indicating the time series of the user's emotions, content time-series information indicating the time series of the viewing positions of the content viewed by the user, and content information indicating the content of the content, and an output step outputs the recommended content information. Therefore, according to the present disclosure, content that matches the user's preferences can be recommended. Furthermore, according to the present disclosure, for example, emotion time-series information can be collected for each viewing position of the content, making it possible to recommend to the user content that has a development that matches the user's preferences from the middle of the story onwards.

[0062] [Embodiment 2] Another example of the recommended content suggestion program of the present disclosure will be described.

[0063] FIG. 4 is a block diagram showing an example of the configuration of a recommended content proposal device 10A. As shown in FIG. 4, the recommended content proposal device 10A includes a correction unit 13 in addition to the configuration of the recommended content proposal device 10 of embodiment 1. The hardware configuration of the recommended content proposal device 10A is the same as that of the recommended content proposal device 10 of FIG. 2, except that the central processing unit 101 has the configuration of the recommended content proposal device 10A of FIG. 4 instead of the configuration of the recommended content proposal device 10 of FIG. 1. The processing of the correction unit 13 will be described below. The processing of the correction unit 13 can be inserted at any position in the flowchart of FIG. 3 described in embodiment 1, as appropriate. However, as shown in FIG. 5, the processing of the correction unit 13 is preferably inserted, for example, before S1.

[0064] The correction unit 13 determines whether the user is viewing the content based on, for example, the biometric information of the user, and if it is determined that the user is not viewing the content, invalidates the emotion time-series information for the period when the user is not viewing the content (S3, correction procedure).

[0065] In this embodiment, the biometric information is preferably, for example, the biometric information described above that can determine whether the user is viewing the content. Examples of such biometric information include, but are not limited to, information about the eyeballs, information about the voice, and information about movement.

[0066] An example of the medium for acquiring information about the eyeballs is a terminal equipped with the eye tracking function. An example of the medium for acquiring information about the voice is a terminal equipped with a voice recognition function. An example of the medium for acquiring information about movement is a terminal equipped with at least one of an acceleration sensor function and a gyro sensor function. An example of the medium for acquiring information about the biometric information may be, for example, the device disclosed herein or a device other than the device disclosed herein.

[0067] The biometric information may be acquired by, for example, the device of the present disclosure, or may be acquired by a device other than the device of the present disclosure. The acquired biometric information may be stored in, for example, the memory 102 or the storage device 104 of the device of the present disclosure, or may be stored in the memory or storage device of a device other than the device of the present disclosure.

[0068] The determination of whether the content is being viewed based on the biometric information can be performed, for example, if the biometric information is information about the eyeballs, based on focal coordinate information indicating the coordinates of the focus of the user's gaze. In this case, the determination of whether the content is being viewed based on the biometric information can be performed, for example, if the focal coordinate information deviates from the content, to determine that the user is not viewing the content. The determination of whether the content is being viewed based on the biometric information can be performed, for example, if the biometric information is information about voice, based on voice recognition of a predetermined voice (e.g., a human voice, a telephone ringtone, an intercom sound, etc.). The determination of whether the content is being viewed based on the biometric information can be performed, for example, if the biometric information is information about movement, based on detection of the user's movement, to determine that the user is not viewing the content.

[0069] The invalidation of the emotion time-series information may be, for example, the deletion of the emotion time-series information, the change of state information of the emotion time-series information from valid to invalid, or the addition of invalidation information to the emotion time-series information.Furthermore, the invalidation of the emotion time-series information may be, for example, the deletion of the emotion information, the change of state information of the emotion information from valid to invalid, or the addition of invalidation information to the emotion information.

[0070] Furthermore, the correction unit 13 may correct the emotion time-series information based on, for example, at least one of purpose information indicating the user's purpose for viewing the content and evaluation information indicating the user's evaluation of the content (S3A, correction procedure).

[0071] The purpose information and the evaluation information may be, for example, as described above.

[0072] Correction of the emotion time-series information based on the objective information can be performed, for example, by identifying content posting location information that includes the same content emotion information as the emotion information set as the objective information, and using the difference between the emotion time-series information of the user at the time of viewing the identified content posting location information and the emotion information set as the objective information as a correction value. Correction of the emotion time-series information based on the rating information can be performed, for example, by identifying content posting location information that includes the same content emotion information as the emotion information set as the rating information, and using the difference between the emotion time-series information of the user at the time of viewing the identified content posting location information and the emotion information set as the rating information as a correction value. Furthermore, correction of the emotion time-series information based on the rating information can be performed, for example, by using the difference between the emotion information set as the rating information and the content emotion information in the content viewing location information where the rating information was set as a correction value. The correction value may be, for example, the difference between the emotion score information or the difference between the emotion coordinate information. The correction value may be used, for example, to correct the emotion time-series information of the user when viewing content in the future, or may be used to correct the emotion time-series information of the user when viewing content in the past. The correction of the emotion time-series information based on the purpose information and the evaluation information can be performed, for example, by combining the correction of the emotion time-series information based on the purpose information and the correction of the emotion time-series information based on the evaluation information.

[0073] S1 and S2 are executed in the same manner as S1 and S2 in the first embodiment.

[0074] The recommended content suggestion method of the present disclosure (hereinafter also referred to as the method of the present disclosure) is a method implemented, for example, by replacing the "procedures" in the program of the present disclosure with "processes." Specifically, the method of the present disclosure includes a correction process in addition to a generation process and an output process. The correction process determines whether the user is viewing the content based on the user's biometric information, and if it is determined that the user is not viewing the content, invalidates the emotion time-series information for the period during which the user is not viewing the content. The method of the present disclosure can be implemented, for example, using the device 10A of the present disclosure shown in FIG. 4 or the hardware configuration of the recommended content suggestion device 10 of FIG. 2, in which the central processing unit 101 has the configuration of the recommended content suggestion device 10A of FIG. 4 instead of the configuration of the recommended content suggestion device 10 of FIG. 1. Note that the method of the present disclosure is not limited to a method using the device 10A of the present disclosure. For example, the description of the program and the device of the present disclosure can be used for the method of the present disclosure.

[0075] As described above, according to the recommended content suggestion program of the present disclosure, a correction procedure is performed to determine whether the user is viewing the content based on the user's biometric information, and if it is determined that the user is not viewing the content, the emotion time-series information for the period when the user was not viewing the content can be invalidated. Therefore, according to the present disclosure, content that matches the user's preferences can be recommended. Furthermore, according to the present disclosure, for example, emotion time-series information for the period when the user was not viewing the content can be invalidated, thereby enabling more accurate estimation of the user's emotions. Furthermore, according to the present disclosure, for example, a discrepancy between actually acquired emotion time-series information and the user's subjective emotions can be corrected, thereby enabling more accurate estimation of the user's emotions.

[0076] [Embodiment 3] An example of how the device of the present disclosure is used will be described below. In the following description, the content is a book, but the present disclosure is not limited to the following description.

[0077] For example, a user wears a wristband-type wearable terminal and a wearable MR device and browses a book, which is an electronic medium, on the display unit of the MR device. The wearable terminal is, for example, a terminal equipped with a function for measuring a pulse, which is biometric information. The MR device is, for example, a device equipped with an eye tracking function. The wearable terminal is, for example, capable of transmitting and receiving information to and from a device disclosed herein. The MR device is, for example, capable of transmitting and receiving information to and from a device disclosed herein. While browsing a book, the wearable terminal, for example, acquires the user's pulse by linking it with time-series information, and transmits the acquired set of the user's pulse and time-series information to the device disclosed herein. The device disclosed herein, for example, uses an emotion information generation model to generate emotion information from the acquired user's pulse. The device disclosed herein, for example, associates the emotion information with the time-series information, generates emotion time-series information, and stores the emotion time-series information in a database. Additionally, while the user is browsing a book, the MR device, for example, acquires content browsing location information indicating the browsing locations of the book browsed by the user by linking it with time-series information, and transmits the acquired set of content browsing location information and time-series information to the device disclosed herein. The device disclosed herein, for example, links the acquired content browsing location information with time-series information, generates content time-series information, and stores the content time-series information in a database. The device disclosed herein, for example, pre-stores content information indicating the contents of the book. The device disclosed herein, for example, uses a recommended content information generation model to generate recommended content information from the emotion time-series information, the content time-series information, and the content information. The device disclosed herein, for example, outputs the recommended content information to the MR device.

[0078] According to the present disclosure, content that matches the preferences of a user can be recommended.

[0079] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0080] <Additional Notes> Some or all of the above embodiments can be described as, but not limited to, the following supplementary notes. (Appendix 1) A generating procedure and an output procedure are included, The generation step generates recommended content information indicating content recommended to the user based on emotion time series information indicating a time series of the user's emotions, content time series information indicating a time series of browsing positions of content browsed by the user, and content information indicating the details of the content; the output step outputs the recommended content information. A recommended content suggestion program for causing a computer to execute each of the above steps. (Appendix 2) The content information is feature information indicating features of each part of the content. The recommended content suggestion program described in Appendix 1. (Appendix 3) the generating step generates the recommended content information by taking into consideration at least one of purpose information indicating the user's purpose for browsing the content, evaluation information indicating the user's evaluation of the content, history information indicating a browsing history of content browsed by the user, and other information regarding users other than the user; A recommended content suggestion program as described in Appendix 1 or 2. (Appendix 4) the content is a book, the content time series information is unit time series information indicating the time series of at least one of a read sentence, a read phrase, and a read word in a book read by the user, the content information is unit feature information indicating at least one of features of each sentence of the book, features of each phrase of the book, and features of each word of the book; the generating step generates the recommended content information based on the emotion time-series information, the unit time-series information, and the unit feature information. 10. A recommended content suggestion program according to any one of appendices 1 to 3. (Appendix 5) Further, a correction procedure is included, the correction step includes determining whether the user is viewing the content based on biometric information of the user; When it is determined that the user has not viewed the content, invalidating the emotion time-series information for a period during which the user has not viewed the content. 5. A recommended content suggestion program according to any one of appendices 1 to 4. (Appendix 6) The biological information is information about an eyeball. The recommended content suggestion program described in Appendix 5. (Appendix 7) the correction step corrects the emotion time-series information based on at least one of purpose information indicating the user's purpose for viewing the content and evaluation information indicating the user's evaluation of the content; A recommended content suggestion program as described in Appendix 5 or 6. (Appendix 8) a generating unit and an output unit, the generation unit generates recommended content information indicating content recommended to the user based on emotion time series information indicating a time series of the user's emotions, content time series information indicating a time series of browsing positions of content browsed by the user, and content information indicating details of the content; the output unit outputs the recommended content information. Recommended content suggestion device. (Appendix 9) The content information is feature information indicating features of each part of the content. 9. The recommended content suggestion device according to claim 8. (Appendix 10) the generation unit generates the recommended content information by taking into consideration at least one of purpose information indicating the user's purpose for browsing the content, evaluation information indicating the user's evaluation of the content, history information indicating a browsing history of content browsed by the user, and other information regarding users other than the user. 10. The recommended content suggestion device according to claim 8 or 9. (Appendix 11) the content is a book, the content time series information is unit time series information indicating the time series of at least one of a read sentence, a read phrase, and a read word in a book read by the user, the content information is unit feature information indicating at least one of features of each sentence of the book, features of each phrase of the book, and features of each word of the book; the generation unit generates the recommended content information based on the emotion time-series information, the unit time-series information, and the unit feature information. 11. A recommended content suggestion device according to any one of appendixes 8 to 10. (Appendix 12) Further, a correction unit is included, the correction unit determines whether the user is viewing the content based on biometric information of the user; When it is determined that the user has not viewed the content, invalidating the emotion time-series information for a period during which the user has not viewed the content. 12. A recommended content suggestion device according to any one of appendixes 8 to 11. (Appendix 13) The biological information is information about an eyeball. 13. The recommended content suggestion device according to claim 12. (Appendix 14) the correction unit corrects the emotion time-series information based on at least one of purpose information indicating the user's purpose for viewing the content and evaluation information indicating the user's evaluation of the content. 14. The recommended content suggestion device according to claim 12 or 13. (Appendix 15) A generating step and an output step are included, the generating step generates recommended content information indicating content recommended to the user based on emotion time series information indicating a time series of the user's emotions, content time series information indicating a time series of browsing positions of content browsed by the user, and content information indicating the details of the content; The output step outputs the recommended content information. The method for proposing recommended content, wherein each of the steps is executed by a computer. (Appendix 16) The content information is feature information indicating features of each part of the content. The method for suggesting recommended content as described in Appendix 15. (Appendix 17) the generating step generates the recommended content information by taking into consideration at least one of purpose information indicating the user's purpose for browsing the content, evaluation information indicating the user's evaluation of the content, history information indicating a browsing history of content browsed by the user, and other information regarding users other than the user; 17. The method of suggesting recommended content according to claim 15 or 16. (Appendix 18) the content is a book, the content time series information is unit time series information indicating the time series of at least one of a read sentence, a read phrase, and a read word in a book read by the user, the content information is unit feature information indicating at least one of features of each sentence of the book, features of each phrase of the book, and features of each word of the book; the generating step generates the recommended content information based on the emotion time-series information, the unit time-series information, and the unit feature information. 18. The recommended content suggestion method according to any one of appendixes 15 to 17. (Appendix 19) Further, a correction step is included, the correcting step includes determining whether the user is viewing the content based on biometric information of the user; When it is determined that the user has not viewed the content, invalidating the emotion time-series information for a period during which the user has not viewed the content. 19. The recommended content suggestion method according to any one of appendixes 15 to 18. (Appendix 20) The biological information is information about an eyeball. The method for suggesting recommended content as described in Appendix 19. (Appendix 21) the correction step corrects the emotion time-series information based on at least one of purpose information indicating the user's purpose for viewing the content and evaluation information indicating the user's evaluation of the content; 21. The method of suggesting recommended content according to claim 19 or 20. (Appendix 22) A generating procedure and an output procedure are included, The generation step generates recommended content information indicating content recommended to the user based on emotion time series information indicating a time series of the user's emotions, content time series information indicating a time series of browsing positions of content browsed by the user, and content information indicating the details of the content; the output step outputs the recommended content information. A computer-readable recording medium having recorded thereon a recommended content suggestion program for causing a computer to execute each of the above procedures. (Appendix 23) The content information is feature information indicating features of each part of the content. 23. The recording medium according to claim 22. (Appendix 24) the generating step generates the recommended content information by taking into consideration at least one of purpose information indicating the user's purpose for browsing the content, evaluation information indicating the user's evaluation of the content, history information indicating a browsing history of content browsed by the user, and other information regarding users other than the user; 24. A recording medium according to claim 22 or 23. (Appendix 25) the content is a book, the content time series information is unit time series information indicating the time series of at least one of a read sentence, a read phrase, and a read word in a book read by the user, the content information is unit feature information indicating at least one of features of each sentence of the book, features of each phrase of the book, and features of each word of the book; the generating step generates the recommended content information based on the emotion time-series information, the unit time-series information, and the unit feature information. 25. A recording medium according to any one of appendices 22 to 24. (Appendix 26) Further, a correction procedure is included, the correction step includes determining whether the user is viewing the content based on biometric information of the user; When it is determined that the user has not viewed the content, invalidating the emotion time-series information for a period during which the user has not viewed the content. 26. A recording medium according to any one of appendices 22 to 25. (Appendix 27) The biological information is information about an eyeball. 27. A recording medium as described in Appendix 26. (Appendix 28) the correction step corrects the emotion time-series information based on at least one of purpose information indicating the user's purpose for viewing the content and evaluation information indicating the user's evaluation of the content; 28. A recording medium according to claim 26 or 27. [Industrial Applicability]

[0081] According to the present disclosure, it is possible to recommend content that matches the preferences of a user. Therefore, the present disclosure can be widely and usefully applied in the field of publishing, etc. [Explanation of symbols]

[0082] 10, 10A Recommended content suggestion device 11 Generation part 12 Output section 13 Correction unit 101 Central Processing Unit 102 memory 103 Bus 104 Storage device 105 Input Device 106 Output Device 107 Communication Devices

Claims

1. A generating procedure and an output procedure are included, The generation step generates recommended content information indicating content recommended to the user based on emotion time series information indicating a time series of the user's emotions, content time series information indicating a time series of browsing positions of content browsed by the user, and content information indicating the details of the content; the output step outputs the recommended content information. A recommended content suggestion program for causing a computer to execute each of the above steps.

2. The content information is feature information indicating features of each part of the content. The recommended content suggestion program according to claim 1.

3. the generating step generates the recommended content information by taking into consideration at least one of purpose information indicating the user's purpose for browsing the content, evaluation information indicating the user's evaluation of the content, history information indicating a browsing history of content browsed by the user, and other information regarding users other than the user; The recommended content suggestion program according to claim 1.

4. the content is a book, the content time series information is unit time series information indicating the time series of at least one of a read sentence, a read phrase, and a read word in a book read by the user, the content information is unit feature information indicating at least one of features of each sentence of the book, features of each phrase of the book, and features of each word of the book; the generating step generates the recommended content information based on the emotion time-series information, the unit time-series information, and the unit feature information. The recommended content suggestion program according to claim 1.

5. Further, a correction procedure is included, the correction step includes determining whether the user is viewing the content based on biometric information of the user; When it is determined that the user has not viewed the content, invalidating the emotion time-series information for a period during which the user has not viewed the content. The recommended content suggestion program according to any one of claims 1 to 4.

6. The biological information is information about an eyeball.

6. The recommended content suggestion program according to claim 5.

7. the correction step corrects the emotion time-series information based on at least one of purpose information indicating the user's purpose for viewing the content and evaluation information indicating the user's evaluation of the content; 6. The recommended content suggestion program according to claim 5.

8. a generating unit and an output unit, the generation unit generates recommended content information indicating content recommended to the user based on emotion time series information indicating a time series of the user's emotions, content time series information indicating a time series of browsing positions of content browsed by the user, and content information indicating details of the content; the output unit outputs the recommended content information. Recommended content suggestion device.

9. A generating step and an output step are included, the generating step generates recommended content information indicating content recommended to the user based on emotion time series information indicating a time series of the user's emotions, content time series information indicating a time series of browsing positions of content browsed by the user, and content information indicating the details of the content; The output step outputs the recommended content information. The method for proposing recommended content, wherein each of the steps is executed by a computer.

10. A generating procedure and an output procedure are included, The generation step generates recommended content information indicating content recommended to the user based on emotion time series information indicating a time series of the user's emotions, content time series information indicating a time series of browsing positions of content browsed by the user, and content information indicating the details of the content; the output step outputs the recommended content information. A computer-readable recording medium having recorded thereon a recommended content suggestion program for causing a computer to execute each of the above procedures.

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