Recommendation device

Abstract

This recommendation device comprises: an acquisition unit that acquires information pertaining to video content associated with a user; an identification unit that, on the basis of the information pertaining to the video content acquired by the acquisition unit, identifies a musical emotion configuration requested by the user; and a recommendation unit that recommends video content corresponding to the musical emotion configuration identified by the identification unit.

Description

[Technical Field]

[0001] One aspect of the present invention relates to a recommendation device. [Background Art]

[0002] Patent Document 1 and Patent Document 2 describe a recommendation system that recommends video content to a user in consideration of the user's tastes and preferences. [Prior Art Documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Unexamined Patent Application Publication No. 2008-117222 [Patent Document 2] Japanese Unexamined Patent Application Publication No. 2011-128981 [Summary of the Invention] [Problem to be Solved by the Invention]

[0004] In a general recommendation system for video distribution services and the like, for example, video content similar (in genre and the like) to video content that the user has viewed in the past is recommended. In this case, there is a risk that all of the recommended video content will be similar to each other.

[0005] One aspect of the present invention has been made in view of the above circumstances, and an object thereof is to broaden the range of recommended video content. [Means for Solving the Problem]

[0006] A recommendation device according to one aspect of the present invention includes: an acquisition unit that acquires information related to video content associated with a user; a specifying unit that specifies a music structure desired by the user based on the information related to the video content acquired by the acquisition unit; and a recommendation unit that recommends video content corresponding to the music structure specified by the specifying unit.

[0007] In a recommendation device according to one aspect of the present invention, the musical composition desired by the user is identified based on information related to video content associated with the user, and video content corresponding to that musical composition is recommended. In general recommendation systems in video distribution services, for example, video content similar to video content previously viewed by the user (similar in genre, etc.) is recommended. In this case, there is a risk that the recommended video content will all be similar to each other. The applicants hypothesized that even if video content has different genres and metadata, if the musical composition is similar, the user may be interested in it (it resonates with the user on a deeper level), and conceived of a video content recommendation system that focuses on musical composition. As described above, in a recommendation device according to one aspect of the present invention, the musical composition is identified from video content associated with the user, and video content corresponding to (for example, similar to) that musical composition is recommended. With such a configuration, it is possible to recommend video content that the user may be interested in from a new angle, namely musical composition, without relying on similarity in genre, etc., as in the conventional system. This will broaden the range of video content that can be recommended. [Effects of the Invention]

[0008] According to the present invention, the range of recommended video content can be broadened. [Brief explanation of the drawing]

[0009] [Figure 1] Figure 1 shows an image of video content recommendations by a recommendation device. [Figure 2] Figure 2 is a functional block diagram of the recommendation device included in the recommendation system. [Figure 3] Figure 3 illustrates the derivation of the music vector using a Mel spectrogram and a CNN. [Figure 4]Figure 4 illustrates the creation of a content map based on music vectors. [Figure 5] Figure 5 illustrates an example of how a user can acquire the emotions they desire. [Figure 6] Figure 6 illustrates another example of how users can acquire the emotions they desire. [Figure 7] Figure 7 shows an example of a UI. [Figure 8] Figure 8 shows another example of the UI. [Figure 9] Figure 9 shows yet another example of the UI. [Figure 10] Figure 10 shows yet another example of the UI. [Figure 11] Figure 11 is a flowchart of the recommendation process. [Figure 12] Figure 12 shows the hardware configuration of the recommendation device according to this embodiment. [Modes for carrying out the invention]

[0010] Embodiments of the present invention will be described in detail below with reference to the attached drawings. In the description of the drawings, the same or equivalent elements will be denoted by the same reference numerals, and redundant explanations will be omitted.

[0011] First, the recommendation of video content by the recommendation device according to this embodiment will be explained with reference to Figure 1. Figure 1 is a diagram showing an image of video content recommendation by the recommendation device.

[0012] As shown in Figure 1, let's assume that a user is currently watching a video content titled "TEL101". Furthermore, let's assume that the theme song for "TEL101" is "Honden" (Discharge), sung by "Taro Yoneyama". The recommendation device according to this embodiment, for example, identifies the musical emotional structure (details described later) of "Honden," the theme song of the video content "TEL101," and recommends video content corresponding to the identified musical emotional structure. Specifically, the recommendation device identifies music (e.g., songs) with the same or similar musical emotional structure as "Honden," and recommends video content in which the identified song is used as the theme song. Such recommendations are based on the hypothesis that "the atmosphere of a work (video content) can be grasped through its musical emotional structure."

[0013] The determination of what to recommend is made using, for example, the content map shown in the right-hand diagram of Figure 1 (details will be explained later). The content map maps each emotion to an emotion map, with Valance (emotional value) on the horizontal axis and Arousal (level of arousal) on the vertical axis, and associates each video content with it based on its musical composition. The emotion map includes emotions such as astonished, excited, happy, good, hopeful, peaceful, sleepy, bored, anxious, sad, disappointed, frustrated, annoyed, and afraid. Then, each video content (or the music associated with each video content) is mapped to the emotion map based on the musical emotion composition, which indicates the emotion of the music associated with each video content (for example, the theme song).

[0014] Currently, in the content map shown in the right diagram of FIG. 1, the aforementioned "Discharge" is mapped as music mapped near the music emotion composition "excited". Then, as music mapped near the same music emotion composition "excited", for example, the song "NewYork" by the singer "Nowgli‘s", the song "KNOCK OUT" by the singer "Taro Yoneyama", and the song "Door of Time" by the singer "BANDS" are mapped. In this case, the recommendation device recommends video content for which "NewYork", "KNOCK OUT", or "Door of Time", which are mapped near "excited" similarly to "Discharge", is the theme song. For example, the recommendation device may specify one song whose position in the content map (that is, music emotion composition) is closest to "Discharge", and recommend video content for which said song is the theme song. Assume now that in the content map, the song closest to "Discharge" is "KNOCK OUT". In this case, the recommendation device recommends the video content "Saw Man" for which "KNOCK OUT" is adopted as the theme song. Although an example in which recommendation is performed triggered by acquisition of information indicating video content viewed by a user has been described herein, recommendation may be performed triggered by acquisition of other information (details will be described later).

[0015] FIG. 2 is a functional block diagram of the recommendation device 10 included in the recommendation system 1. As shown in FIG. 2, the recommendation system 1 is configured to include the recommendation device 10 and a user terminal 20 held by a user. Although the recommendation system 1 includes a plurality of user terminals 20 associated with a plurality of users, for convenience of description, only one user terminal 20 will be described herein. The user terminal 20 only needs to be a terminal capable of wireless communication, and is, for example, a smartphone, a tablet terminal, a PC terminal, or the like.

[0016] The recommendation device 10 is a device that recommends video content that is highly likely to be desired by the user (matches the user's preferences) to a user (a user terminal 20). Specifically, the recommendation device 10 identifies a musical emotion composition desired by the user from video content associated with the user (for example, video content that the user has watched), and recommends video content corresponding to the musical emotion composition. The musical emotion composition is information indicating an emotion expressed by music (an emotion evoked by music), and is represented, for example, by a multi-viewpoint vector (music vector) including Valance (emotional valence) and Arousal (arousal level).

[0017] The recommendation device 10 includes an acquisition unit 11, an identification unit 12, a recommendation unit 13, a display unit 14, and a storage unit 15.

[0018] The storage unit 15 stores a content map in which each piece of video content is associated based on the musical emotion composition with an emotion map obtained by mapping each emotion. Creation of the content map will be described with reference to FIGS. 3 and 4. When creating the content map, first, for music related to each piece of video content (for example, a theme song), a music vector indicating the musical emotion composition is derived (FIG. 3). Then, based on the music vectors, a content map in which each piece of video content is mapped on the emotion map is created (FIG. 4).

[0019] FIG. 3 is a diagram explaining derivation of a music vector using a mel-spectrogram and a CNN (Convolutional Neural Network). As shown in FIG. 3, music related to each piece of video content is converted into a mel-spectrogram, for example. A mel-spectrogram is an acoustic feature quantity in which the vertical axis represents time, the horizontal axis represents frequency, and the value represents power. The portion converted into the mel-spectrogram may be a characteristic portion representative of the music.

[0020] These distinctive parts can be extracted, for example, by the following method. First, k-medoids clustering is performed on the song segments (divided parts). A d-dimensional acoustic feature vector is used to represent each segment. A medoid from each cluster is selected to be annotated as a representative segment. The number of clusters, k, is set in proportion to the number of segments in the track. To ensure the quality and diversity of the k-medoids results, the algorithm is repeated multiple times, and the result is selected based on the cumulative distance between the segment and its medoid. Finally, a representative segment with an average of m is obtained for each track. Then, the mel spectrogram image is input into a CNN to derive a music vector that shows the musical emotion composition of each piece of music. Here, the music vector is, for example, a vector showing the features of Valance and Arousal.

[0021] Figure 4 illustrates the creation of content maps based on music vectors. Let's assume that the music vector for "Discharge," the theme song of the video content "TEL101," is derived as [Valance:0.40, Arousal:0.10,…], and the music vector for "KNOCK OUT," the theme song of the video content "Saw Man," is derived as [Valance:0.42, Arousal:0.13,…]. For each video content with music vectors derived in this way, they are mapped to a pre-prepared emotion map based on the music vector. The emotion map has Valance on the horizontal axis and Arousal on the vertical axis, and maps emotions such as astonished, excited, happy, good, hopeful, peaceful, sleepy, bored, anxious, sad, disappointed, frustrated, annoyed, and afraid. Music vectors are also represented by Valance and Arousal features, making it possible to map them to the emotion map of the video content. By mapping each video content to the emotion map, a content map is created. The memory unit 15 stores the content map created in this way.

[0022] The acquisition unit 11 acquires information related to video content associated with the user (user terminal 20). As information related to video content associated with the user, the acquisition unit 11 acquires, for example, information indicating the video content that the user has viewed. For example, when the user has finished viewing, the acquisition unit 11 acquires information indicating the video content that the user has viewed from the user terminal 20.

[0023] The acquisition unit 11 may acquire information related to the video content associated with the user (user terminal 20), such as information indicating the emotions the user wants to get from the video content. Figure 5 is a diagram illustrating an example of acquiring the emotions the user wants to get. As shown in Figure 5, the relationship between each emotion (whether or not they are similar emotions) is defined in the emotion map. Therefore, the acquisition unit 11 may acquire information indicating the emotions the user wants to get, compared to the emotions the user got from the video content they watched. Specifically, for example, after watching the video content, a question such as "What kind of work would you like to watch next?" is sent to the user terminal 20, and the user selects an answer from answer candidates such as "A. Keep it the same," "B. More intense than before," or "C. Quieter than before," thereby acquiring information indicating the emotions the user wants to get, compared to the emotions the user got from the video content they watched.

[0024] In the example shown in Figure 5, for instance, if the emotional composition of the music in the video content the user watched was "excited," and the user answered "A. Keep it as is," then, as shown in the left diagram of Figure 5, it is obtained that the emotion the user wants to experience is "excited." If the user answered "B. More intense than before," then, as shown in the center diagram of Figure 5, it is obtained that the emotion the user wants to experience is even more intense than "excited." If the user answered "C. Quieter than before," then, as shown in the right diagram of Figure 5, it is obtained that the emotion the user wants to experience is quieter than "excited" (for example, peaceful).

[0025] Figure 6 illustrates another example of obtaining the emotions a user desires. The acquisition unit 11 may acquire information that indicates the emotions the user currently desires from the video content, without comparing it to the video content viewed as described above. In the example shown in Figure 6, a question such as "What kind of work do you want to watch now?" is sent to the user terminal 20, and the user selects an answer from a list of answer candidates such as "A. Exciting," "B. Happy," and "C. Quiet." Based on the emotion map, the user's emotions corresponding to their answers are identified (acquired).

[0026] Furthermore, the acquisition unit 11 may acquire information indicating the emotions the user wants to obtain from the video content based on a selection operation by the user who has viewed the emotion map displayed on the user terminal 20 (see Figure 8; details will be described later).

[0027] The identification unit 12 identifies the musical emotional composition desired by the user based on the information related to the video content acquired by the acquisition unit 11. As described above, the information related to the video content acquired by the acquisition unit 11 may be information indicating the video content that the user has watched, or it may be information indicating the emotions that the user wants to get from the video content.

[0028] The identification unit 12 identifies the musical emotional configuration desired by the user based on the information related to the video content acquired by the acquisition unit 11 and the content map. Now, let's assume that the acquisition unit 11 has acquired information indicating the video content that the user has watched. In this case, the identification unit 12 refers to the content map and identifies the musical emotional configuration (excited, etc.) of the video content that the user has watched as the musical emotional configuration desired by the user.

[0029] Furthermore, the acquisition unit 11 acquires information indicating the emotions the user wants to experience from the video content. In this case, the identification unit 12 refers to the content map and identifies the musical emotion configuration corresponding to the emotions the user wants to experience as the musical emotion configuration the user is seeking.

[0030] The recommendation unit 13 recommends video content that corresponds to the musical emotion structure identified by the identification unit 12. By referring to the content map, the recommendation unit 13 identifies video content with a musical emotion structure that matches or is similar to the musical emotion structure identified by the identification unit 12, and recommends the video content. Matching musical emotion structures means, for example, that the closest emotion in the emotion map matches (for example, they match in terms of excitement). Similar musical emotion structures mean, for example, that the closest emotion in the emotion map does not match, but they are close in terms of emotion in the emotion map (for example, they are close in terms of excitement and happiness).

[0031] For example, if there are multiple video contents with matching musical emotional compositions, the recommendation unit 13 may recommend the video content with the musical emotional composition that is closest to the musical emotional composition of the video content the user has previously watched.

[0032] The display unit 14 displays information on the user terminal 20. The display unit 14 displays video content recommended by the recommendation unit 13 on the user terminal 20. The display unit 14 also displays a UI (User Interface) on the user terminal 20 to enable the acquisition of information by the acquisition unit 11.

[0033] Figure 7 shows an example of the UI displayed on the user terminal 20 by the display unit 14. For example, suppose the screen shown in Figure 7(a) is the initial screen. From this state, a screen is displayed asking the user about their preferred atmosphere for video content, as shown in Figure 7(b). Now, in Figure 7(b), if the user answers Y (YES) to the question, "Do you like works with a calm atmosphere?", then a list of works (video content) with a calm atmosphere in their musical emotional composition is displayed, as shown in Figure 7(c).

[0034] Figure 8 shows another example of the UI. In the example shown in Figure 8(a), the emotion map is divided into four main areas, and an icon of an expression corresponding to each area is displayed, along with the question, "Which emotion do you want to see?". In this state, if, for example, the smiling icon in the upper right is clicked, as shown in Figure 8(b), the details of the musical emotion composition in the upper right area are displayed, and the expression icons for the detailed emotion composition (excited, etc.) are displayed. Then, as shown in Figure 8(c), if, for example, "excited" is clicked, a list of works (video content) whose musical emotion composition is "excited" is displayed. In this case, the video content may be suggested in order of increasing excitement. In this way, the display unit 14 may display the emotion map on the user terminal 20. The acquisition unit 11 may also acquire information indicating the emotion the user wants to obtain from the video content based on the selection operation from the user who has viewed the emotion map displayed on the user terminal 20.

[0035] Figure 9 shows another example of the UI. In the example shown in Figure 9(a), when displaying the emotion map, as described above, it is divided into four main areas, and an icon of the appropriate expression is shown for each area. In the example shown in Figure 9(b), the emotion map is displayed as is without dividing it into areas as described above. In either case, by displaying it with a message such as "Which emotion's artwork would you like to see?", the user can obtain the emotion they want.

[0036] Figure 10 shows another example of the UI. In the example shown in Figure 10(a), for example, information about the video content the user has watched is displayed, which includes information indicating multiple emotions related to the video content (e.g., icons for each emotion). When one emotion is selected from the information indicating multiple emotions, a list of video content for the selected emotion is displayed, as shown in Figure 10(b).

[0037] Next, we will explain the recommendation process with reference to Figure 11. Figure 11 is a flowchart of the recommendation process.

[0038] As shown in Figure 11, the recommendation device 10 first acquires information related to the video content associated with the user (step S1).

[0039] Next, based on the information related to the acquired video content, the musical emotional composition desired by the user is identified (Step S2).

[0040] Finally, video content with musical emotional structures that correspond to (the same or similar to) the identified musical emotional structure is recommended (step S3). This completes the recommendation process.

[0041] Next, the operation and effects of the recommendation device 10 according to this embodiment will be described.

[0042] The recommendation device 10 includes an acquisition unit 11 that acquires information related to video content associated with a user, an identification unit 12 that identifies the musical emotional composition desired by the user based on the information related to the video content acquired by the acquisition unit 11, and a recommendation unit 13 that recommends video content corresponding to the musical emotional composition identified by the identification unit.

[0043] In the recommendation device 10 according to this embodiment, the musical emotional structure desired by the user is identified based on information related to video content associated with the user, and video content corresponding to that musical emotional structure is recommended. In general recommendation systems in video distribution services, for example, video content similar to video content previously viewed by the user (similar in genre, etc.) is recommended. In this case, there is a risk that the recommended video content will all be similar to each other. The applicants hypothesized that even if video content differs in genre and metadata, if the musical emotional structure is similar, the user may be interested in it (it resonates with the user on a deeper level), and conceived of recommending video content that focuses on musical emotional structure. As described above, in the recommendation device 10 according to this embodiment, the musical emotional structure is identified from the video content associated with the user, and video content corresponding to (for example, similar to) that musical emotional structure is recommended. With such a configuration, it is possible to recommend video content that the user may be interested in from a new angle, namely musical emotional structure, without relying on similarity in genre, etc., as in the conventional approach. This will broaden the range of video content that can be recommended. Specifically, it will be possible to recommend long-tail titles that may resonate with users at a deeper level, and to recommend video content from different genres and with different metadata.

[0044] The recommendation device described above further includes a storage unit 15 that stores a content map that associates each video content with an emotion map that maps each emotion, based on the emotional structure of the music. The identification unit 12 identifies the emotional structure of the music desired by the user based on the information related to the video content acquired by the acquisition unit 11 and the content map. The recommendation unit 13 may refer to the content map to identify video content with an emotional structure that matches or is similar to the emotional structure identified by the identification unit 12, and recommend the video content. In this way, by using an emotion map that maps each emotion, the emotional structure of the music desired by the user can be easily identified, and video content that matches or is similar to that emotional structure can be easily recommended. In other words, with such a configuration, the range of video content that can be recommended can be easily broadened.

[0045] The acquisition unit 11 may acquire information relating to video content associated with the user, specifically information indicating the video content the user has watched. With this configuration, it is possible to identify the musical emotional composition the user is looking for from the video content the user has actually selected and watched, and to appropriately recommend video content that is likely to suit the user's preferences.

[0046] The acquisition unit 11 may acquire information relating to the video content associated with the user, including information indicating the emotions the user wants to derive from the video content. By acquiring information indicating what emotions the user wants to derive from the video content in this way, it becomes possible to appropriately recommend video content with a musical emotional composition that matches the user's emotions, that is, video content that is highly likely to suit the user's preferences.

[0047] The acquisition unit 11 may acquire information indicating the emotions the user wants to experience, compared to the emotions the user experienced from the video content they watched. By acquiring information indicating what emotions the user wants to experience, compared to the emotions the user experienced from the video content they watched, it is possible to accurately identify the emotions the user wants to experience based on the video content they watched, and to appropriately recommend video content with a musical emotional composition that matches the user's emotions, i.e., video content that is likely to match the user's preferences.

[0048] The recommendation device 10 further includes a display unit 14 that displays information on a user terminal 20 held by the user. The display unit 14 displays an emotion map on the user terminal 20, and the acquisition unit 11 may acquire information indicating the emotion the user wants to obtain from the video content based on a selection operation from the user who has viewed the emotion map displayed on the user terminal 20. In this way, by displaying an emotion map and acquiring information indicating the emotion the user wants to obtain, the emotion the user is seeking can be acquired easily and with high accuracy.

[0049] Next, the hardware configuration of the recommendation device 10 described above will be explained with reference to Figure 12. Physically, the recommendation device 10 may be configured as a computer device including a processor 1001, memory 1002, storage 1003, communication device 1004, input device 1005, output device 1006, bus 1007, etc.

[0050] In the following explanation, the term "device" can be replaced with "circuit," "device," "unit," etc. The hardware configuration of the recommendation device 10 may include one or more of the devices shown in the figure, or it may be configured to omit some of the devices.

[0051] Each function in the recommendation device 10 is realized by loading predetermined software (programs) onto hardware such as the processor 1001 and memory 1002, causing the processor 1001 to perform calculations and control communication by the communication device 1004, as well as the reading and / or writing of data in the memory 1002 and storage 1003.

[0052] The processor 1001 controls the entire computer, for example, by running the operating system. The processor 1001 may consist of a central processing unit (CPU) that includes interfaces with peripheral devices, control devices, arithmetic units, registers, etc. For example, control functions such as the acquisition unit 11 may be implemented by the processor 1001.

[0053] Furthermore, the processor 1001 reads programs (program code), software modules, and data from the storage 1003 and / or communication device 1004 into the memory 1002, and executes various processes accordingly. The program used is one that causes the computer to execute at least a part of the operations described in the above embodiment.

[0054] For example, control functions such as the acquisition unit 11 may be stored in memory 1002 and implemented by a control program running on processor 1001, and other functional blocks may be implemented similarly. Although the above-described processes have been explained as being executed by one processor 1001, they may be executed simultaneously or sequentially by two or more processors 1001. The processor 1001 may be implemented on one or more chips. The program may also be transmitted from a network via a telecommunications line.

[0055] Memory 1002 is a computer-readable recording medium and may consist of at least one of the following: ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), RAM (Random Access Memory), etc. Memory 1002 may also be called a register, cache, main memory, etc. Memory 1002 can store executable programs (program code), software modules, etc., for carrying out a wireless communication method according to one embodiment of the present invention.

[0056] The storage 1003 is a computer-readable recording medium and may consist of at least one of the following: an optical disc such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., a compact disc, a digital multipurpose disc, a Blu-ray® disc), a smart card, flash memory (e.g., a card, a stick, a key drive), a floppy® disk, a magnetic strip, etc. The storage 1003 may also be called an auxiliary storage device. The above-mentioned storage medium may be, for example, a database, server, or other suitable medium including memory 1002 and / or storage 1003.

[0057] The communication device 1004 is hardware (transceiver / receiver device) for communicating between computers via a wired and / or wireless network, and is also referred to as a network device, network controller, network card, communication module, etc.

[0058] The input device 1005 is an input device that accepts input from an external source (e.g., a keyboard, mouse, microphone, switch, button, sensor, etc.). The output device 1006 is an output device that outputs to an external source (e.g., a display, speaker, LED lamp, etc.). The input device 1005 and the output device 1006 may be configured as an integrated unit (e.g., a touch panel).

[0059] Furthermore, each device, such as the processor 1001 and the memory 1002, is connected by a bus 1007 for communicating information. The bus 1007 may consist of a single bus or different buses may be used for communication between devices.

[0060] Furthermore, the recommendation device 10 may be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), or an FPGA (Field Programmable Gate Array), and some or all of each functional block may be realized by such hardware. For example, the processor 1001 may be implemented using at least one of these pieces of hardware.

[0061] Although this embodiment has been described in detail above, it will be clear to those skilled in the art that this embodiment is not limited to the embodiments described herein. This embodiment can be implemented as a modified and altered form without departing from the spirit and scope of the invention as defined by the claims. Therefore, the description herein is for illustrative purposes only and is not intended to be restrictive in any way to this embodiment.

[0062] Each aspect / embodiment described herein may be applied to systems utilizing LTE (Long Term Evolution), LTE-A (LTE-Advanced), SUPER 3G, IMT-Advanced, 4G, 5G, FRA (Future Radio Access), W-CDMA®, GSM®, CDMA2000, UMB (Ultra Mobile Broad-band), IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802.20, UWB (Ultra-Wide Band), Bluetooth®, and other appropriate systems, and / or next-generation systems extended based thereon.

[0063] The processing procedures, sequences, flowcharts, etc., of each aspect / embodiment described herein may be reordered, provided they are consistent with each other. For example, the methods described herein present the elements of various steps in an exemplary order and are not limited to that specific order.

[0064] Input and output information may be stored in a specific location (e.g., memory) or managed in a management table. Input and output information may be overwritten, updated, or appended to. Output information may be deleted. Input information may be transmitted to other devices.

[0065] The determination may be made by a value represented by 1 bit (0 or 1), by a boolean value (true or false), or by a numerical comparison (for example, a comparison with a predetermined value).

[0066] Each aspect / embodiment described herein may be used individually, in combination, or switched between as needed during implementation. Furthermore, notification of predetermined information (e.g., notification that "X is") is not limited to explicit notification, but may also be implicit (e.g., by not providing such notification).

[0067] Software should be broadly interpreted to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, execution threads, procedures, functions, and so on, whether they are called software, firmware, middleware, microcode, hardware description languages, or by any other name.

[0068] Furthermore, software, instructions, etc., may be transmitted and received via a transmission medium. For example, if software is transmitted from a website, server, or other remote source using wired technologies such as coaxial cable, fiber optic cable, twisted pair, and digital subscriber lines (DSL) and / or wireless technologies such as infrared, radio, and microwave, these wired and / or wireless technologies are included in the definition of a transmission medium.

[0069] The information, signals, etc. described herein may be represented using any one of various different techniques. For example, the data, instructions, commands, information, signals, bits, symbols, chips, etc., which may be referred to throughout the above description, may be represented by voltage, current, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

[0070] In addition, terms used herein and / or terms necessary for understanding this specification may be replaced with terms having the same or similar meanings.

[0071] Furthermore, the information, parameters, etc., described herein may be expressed as absolute values, relative values ​​from a given value, or as corresponding other information.

[0072] Communication terminals may also be referred to by those skilled in the art as mobile communication terminals, subscriber stations, mobile units, subscriber units, wireless units, remote units, mobile devices, wireless devices, wireless communication devices, remote devices, mobile subscriber stations, access terminals, mobile terminals, wireless terminals, remote terminals, handsets, user agents, mobile clients, clients, or several other appropriate terms.

[0073] As used herein, the phrase "based on" does not mean "based solely on" unless otherwise specified. In other words, the phrase "based on" means both "based solely on" and "based at least on."

[0074] Where the designations “first,” “second,” etc., are used herein, no reference to those elements shall generally limit the quantity or order of those elements. These designations may be used herein as a convenient way to distinguish between two or more elements. Thus, references to the first and second elements shall not imply that only two elements may be employed therein, or that the first element must precede the second element in any way.

[0075] To the extent that “include,” “including,” and their variations are used herein or in the claims, these terms are intended to be inclusive, just as the term “comprising.” Furthermore, the term “or” as used herein or in the claims is not intended to be exclusive OR.

[0076] In this specification, unless it is clear from the context or technically that only one device exists, the term also includes multiple devices.

[0077] Throughout this disclosure, unless the context clearly indicates a singular number, the terms shall include plural ones. [Explanation of symbols]

[0078] 10... Recommendation device, 11... Acquisition unit, 12... Identification unit, 13... Recommendation unit, 14... Display unit, 15... Storage unit, 20... User terminal.

Claims

1. An acquisition unit that acquires information related to video content associated with a user, Based on the information relating to the video content acquired by the acquisition unit, the identification unit identifies the music composition desired by the user, A recommendation unit that recommends video content corresponding to the music composition identified by the specified unit, It includes a memory unit that stores a content map that associates each video content with an emotion map that maps each emotion, based on the musical composition, and The identifying unit refers to the content map and identifies the musical emotion configuration corresponding to the emotion the user wants to experience, which was acquired by the acquisition unit, as the musical configuration the user is seeking. The recommendation unit, by referring to the content map, identifies video content with a musical composition that matches or is similar to the musical composition identified by the identification unit, and recommends the video content. The acquisition unit acquires information relating to the video content associated with the user, including information indicating the emotions the user wants to derive from the video content. The acquisition unit is a recommendation device that acquires information indicating the emotions the user wants to experience, compared with the emotions the user experienced from the video content the user watched.

2. The recommendation device according to claim 1, wherein the acquisition unit acquires information indicating the video content viewed by the user as information relating to the video content associated with the user.

3. It further includes a display unit that displays information on the user's terminal, The display unit displays the emotion map on the user terminal. The recommendation device according to claim 1, wherein the acquisition unit acquires information indicating the emotion the user wants to obtain from the video content based on a selection operation by the user who has viewed the emotion map displayed on the user terminal.

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