Recommendation System

Abstract

The present invention makes a recommendation pertaining to music to be used to a user in a suitable manner.　A recommendation system 10 determines recommendation information for recommending music to be used to a user, and comprises: an acquisition unit 11 which acquires information indicating a remaining time in which the music is used; and a determination unit 12 which determines recommendation information on the basis of the information acquired by the acquisition unit 11.

Description

Technical Field

[0001] The present invention relates to a recommendation system for recommendations regarding music.

Background Art

[0002] Conventionally, it has been proposed to recommend music to be listened to inside a vehicle such as a private car. For example, Patent Document 1 shows recommending music according to the current position, vehicle speed, and current time of the vehicle.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] With the ongoing situation of difficulty in visiting karaoke shops during the COVID-19 pandemic and the spread of karaoke applications and devices, the number of facilities for individual karaoke in private cars has increased, and the usage scenarios of karaoke have diversified. When performing karaoke during movement in a private car, it is conceivable to recommend music to the user by the method shown in Patent Document 1. However, when recommending music in the above situations, etc., it is required to recommend more appropriate music.

[0005] One embodiment of the present invention has been made in view of the above, and an object thereof is to provide a recommendation system capable of appropriately recommending music to be used by a user.

Means for Solving the Problems

[0006] In order to achieve the above object, a recommendation system according to an embodiment of the present invention is a recommendation system that determines recommendation information for recommending to a user regarding the music to be used, including an acquisition unit that acquires information indicating the remaining time during which the music is to be used, and a determination unit that determines the recommendation information based on the information acquired by the acquisition unit. The acquisition unit acquires information indicating the location where the music is to be used. , using a pre-stored model that inputs the information obtained by the acquisition unit and outputs the information of the recommended music A determination unit that determines the recommendation information, and the acquisition unit acquires information indicating the location where the music is to be used.

[0007] In the recommendation system according to an embodiment of the present invention, information indicating the remaining time during which the music is to be used is used to determine the recommendation information. Therefore, according to the recommendation system according to an embodiment of the present invention, it is possible to appropriately recommend to the user regarding the music to be used according to the remaining time.

Advantages of the Invention

[0008] According to an embodiment of the present invention, it is possible to appropriately recommend to the user regarding the music to be used according to the remaining time.

Brief Description of the Drawings

[0009]

Figure 1

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Embodiments for Carrying Out the Invention

[0010] Hereinafter, embodiments of the recommendation system according to the present invention will be described in detail with reference to the drawings. In the description of the drawings, the same reference numerals are assigned to the same elements, and duplicate descriptions are omitted.

[0011] Fig. 1 shows a recommendation system 10 according to the present embodiment. The recommendation system 10 is a system (device) that determines recommendation information for making recommendations (recommendations) to a user regarding the music to be used. For example, the recommendation system 10 determines recommendation information for recommending the music used by the user. The recommendation system 10 makes a recommendation by presenting the determined recommendation information to the user. That is, the recommendation system 10 presents recommended music to the user. Note that the recommendation system 10 only needs to determine recommendation information for making recommendations regarding music, and does not necessarily have to determine recommendation information for recommending the music itself. For example, the recommendation system 10 may determine recommendation information for recommending the singer singing the music. In this case, the user can use the music sung by the recommended singer.

[0012] For example, the recommendation system 10 determines recommendation information for making recommendations regarding the music that the user sings at karaoke as the use of music by the user. In addition, the recommendation system 10 may determine recommendation information for making recommendations regarding the music used by the user for purposes other than karaoke. For example, the recommendation system 10 may determine recommendation information for making recommendations regarding the music that the user listens to.

[0013] In this embodiment, the user to be recommended may include a group of a plurality of users who perform karaoke simultaneously, for example, a group of users who sing in turn. In the following description, even when simply referred to as a "user", it shall also include a group of a plurality of users.

[0014] In this embodiment, the recommendation system 10 is configured to determine recommendation information for recommending a song that the user sings during karaoke. Specifically, the recommendation system 10 determines recommendation information for recommending a song that the user sings during karaoke performed inside a vehicle such as a private car while the vehicle is in motion.

[0015] The recommendation system 10 is constituted by a computer such as a PC (Personal Computer) having a communication function or a server device. The recommendation system 10 may be constituted by a plurality of computers, that is, a computer system. The recommendation system 10 can transmit and receive information to and from the user terminal (personal terminal) 20 via a network such as a mobile communication network.

[0016] The user terminal 20 is a terminal used by the user. The user terminal 20 is, for example, a smartphone or a tablet terminal carried by the user (that is, a brought-in terminal brought into the vehicle), and is used for making recommendations to the user. The user terminal 20 may be the same as a conventional user terminal. As described above, the user terminal 20 is a front-end system for the recommendation system 10 that transmits and receives information to and from the recommendation system 10.

[0017] The vehicle used by the user is provided with an in-vehicle terminal 30. The in-vehicle terminal 30 has a function of car navigation (hereinafter referred to as car navigation). The function of car navigation is used for determining the recommendation information of the recommendation system 10 as described later. Specifically, what functions are used will be described later. In addition, the in-vehicle terminal 30 is equipped with a device for performing karaoke. For example, the in-vehicle terminal 30 is equipped with a speaker and a microphone. In addition, the in-vehicle terminal 30 has functions for performing karaoke such as accepting a user's music designation and playing the music. The in-vehicle terminal 30 may be the same as a conventional in-vehicle terminal. Note that the device having the function of car navigation and the device for performing karaoke may be separate and independent devices (terminals).

[0018] The user terminal 20 and the in-vehicle terminal 30 can transmit and receive information to and from each other via short-range wireless communication or wired communication or the like. The information transmitted and received is information related to recommendations. Note that some or all of the functions of the user terminal 20 may be provided in the in-vehicle terminal 30. When all the functions of the user terminal 20 are provided in the in-vehicle terminal 30, there is no need to use the user terminal 20. Conversely, some or all of the functions of the in-vehicle terminal 30 may be provided in the user terminal 20. When all the functions of the in-vehicle terminal 30 are provided in the user terminal 20, there is no need to use the in-vehicle terminal 30.

[0019] Subsequently, the functions of the recommendation system 10 according to the present embodiment will be described. As shown in FIG. 1, the recommendation system 10 includes an acquisition unit 11 and a determination unit 12.

[0020] The acquisition unit 11 is a functional unit that acquires information indicating the remaining time during which a piece of music is used. The acquisition unit 11 may acquire information indicating the location where the music is used. As the information indicating the location where the music is used, the acquisition unit 11 may acquire an image corresponding to the location. As the information indicating the location where the music is used, the acquisition unit 11 may acquire information indicating a POI (Point Of Interest) corresponding to the location. The acquisition unit 11 may acquire information indicating the destination of the user who uses the music. The acquisition unit 11 may acquire information indicating the usage history of the user's music.

[0021] The information acquired by the acquisition unit 11 is information used for determining recommendation information in the recommendation system 10. The acquisition unit 11 acquires each piece of information as follows. Specifically, the car navigation of the in-vehicle terminal 30 has the following functions. The car navigation performs positioning of the vehicle on which the in-vehicle terminal 30 is mounted. Further, the car navigation receives an input of a destination from the user and calculates a route from the position of the vehicle obtained by positioning to the destination. Further, the car navigation calculates the required time from the current time when moving to the destination through the calculated route. The car navigation presents the calculated route and the required time to the user.

[0022] The user terminal 20 acquires the following information obtained by the function of the car navigation from the in-vehicle terminal 30. Specifically, the user terminal 20 acquires information indicating the position of the vehicle obtained by positioning as information indicating the location where the music is used. The information indicating the position of the vehicle is, for example, information indicating the latitude and longitude of the current location. Further, the user terminal 20 acquires information indicating the destination as information indicating the destination of the user who uses the music. The information indicating the destination is the name of the destination (for example, the name of a facility) or information indicating the latitude and longitude of the destination. Further, the user terminal 20 acquires information indicating the required time to the destination as information indicating the remaining time during which the music is used. The information indicating the required time to the destination is information in time units or minute units. Note that as long as it is information indicating the remaining time, it may be information other than the above.

[0023] The user terminal 20 acquires the following information related to the function of performing karaoke on the in-vehicle terminal 30 from the in-vehicle terminal 30. Specifically, the user terminal 20 may acquire information indicating the singing history of the user as information indicating the usage history of the user's music. An example of the information indicating the singing history of the user is shown in FIG. 2. The information is such that the singing time and the music ID are associated with each other. The singing time is information indicating the time when the music was used (sung) (for example, year / month / day / hour / minute as shown in FIG. 2). The music ID is the music ID of the music that was used (sung). The music ID is information (identifier) for specifying each preset music.

[0024] The user terminal 20 transmits the above information acquired from the in-vehicle terminal 30 to the recommendation system 10. Note that the user terminal 20 may acquire information used for determining recommendation information in the recommendation system 10 by means of the user's input operation or the like instead of from the in-vehicle terminal 30. The acquisition unit 11 receives and acquires the information transmitted from the user terminal 20.

[0025] The acquisition unit 11 may further generate and acquire information used for determining recommendation information from the information received from the user terminal 20. For example, the acquisition unit 11 may acquire an image corresponding to the location from the information indicating the location of the above vehicle as information indicating the location where the music is used. Specifically, the acquisition unit 11 stores in advance data of a map image, and acquires an image of a map within a preset range centered on the location of the vehicle as an image corresponding to the location.

[0026] Also, for example, the acquisition unit 11 may acquire information indicating a POI corresponding to the location (for example, a building or a sports facility that is a landmark) from the information indicating the location of the above vehicle as information indicating the location where the music is used. Specifically, the acquisition unit 11 stores in advance information indicating the location (for example, latitude and longitude) of the POI, determines the POI closest to the location of the vehicle based on the information, and acquires the information indicating the POI as information indicating a POI corresponding to the location.

[0027] Also, for example, the acquisition unit 11 may acquire information indicating a mesh including the position (e.g., mesh ID) from the information indicating the position of the vehicle as information indicating the location where the music is used. A mesh is a division of an area into rectangles. Specifically, the acquisition unit 11 stores in advance the correspondence between the mesh and the position, and based on the correspondence, acquires information indicating the mesh including the position from the information indicating the position of the vehicle.

[0028] Also, for example, the acquisition unit 11 may acquire information indicating the genre of the destination (e.g., genre ID) from the information indicating the destination as information indicating the destination of the user who uses the music. The genre of the destination is, for example, a resort, a theme park, or a restaurant. For example, the above genre ID is information (identifier) for specifying each preset genre. Specifically, the acquisition unit 11 stores in advance the correspondence between the information indicating the destination and the genre ID. An example of the information indicating the correspondence is shown in FIG. 3. The acquisition unit 11 acquires the genre ID related to the destination from the information indicating the destination (e.g., facility name) based on the correspondence.

[0029] The acquisition of information by the user terminal 20 and the transmission to the recommendation system 10 are performed, for example, triggered by a predetermined operation by the user terminal 20. The predetermined operation is an operation indicating that the user wants to receive a reminder of the music being sung. In that case, the acquisition unit 11 acquires information when the user wants to receive a reminder of the music being sung. However, the timing of the acquisition of information by the acquisition unit 11, that is, the timing of the acquisition of information by the user terminal 20 and the transmission to the recommendation system 10 is not necessarily limited to the above and may be any timing. Also, the acquisition unit 11 may be acquired with information used for determining the recommendation information by other methods than the above. The acquisition unit 11 outputs the acquired information to the determination unit 12.

[0030] The determination unit 12 is a functional unit that determines recommendation information based on the information acquired by the acquisition unit 11. The determination unit 12 may exclude candidates for the recommendation information based on the information indicating the usage history of the user's music, and then determine the recommendation information. The determination unit 12 determines the recommendation information as follows.

[0031] The determination unit 12 determines recommendation information for recommending the music that the user is singing in karaoke at that time based on the information acquired by the acquisition unit 11. For example, the determination unit 12 inputs the information acquired by the acquisition unit 11 and determines the recommendation information using a model that outputs information indicating the music to be recommended. The determination unit 12 stores the model in advance.

[0032] FIG. 4 and FIG. 5 schematically show the model (algorithm). As shown in FIG. 4, the model is a model that inputs each of the information of the music ID, the current location information, the destination information, and the remaining time information to the destination. Further, as shown in FIG. 5, the model is a model that outputs information of the music to be recommended to the user. The model includes, for example, a neural network generated by machine learning. The neural network may be a multi-layer one, that is, one generated by performing deep learning.

[0033] The determination unit 12 inputs each information from the acquisition unit 11. The determination unit 12 inputs the input information into the model, acquires the information output from the model, and determines the recommendation information. As shown in FIG. 4, the music ID input to the model is the music ID included in the user's singing history. The music IDs are input to the model in order from the oldest singing time. The current location information input to the model is information indicating the position of the vehicle (for example, information indicating the latitude and longitude described above). The destination information input to the model is the genre ID. The remaining time information to the destination input to the model is information indicating the required time to the destination.

[0034] As shown in Fig. 5, the information of the music recommended to the user output from the model is, for example, for each piece of music, that is, a numerical value (a vector in the dimension of the number of music pieces) indicating the degree of recommendation for each music ID. For example, the larger the numerical value, the higher the degree of recommendation. Also, the numerical value for each music ID output from the combined layer (the numerical value in the upper table in Fig. 5) may be converted, for example, so that all the values are added up to 1 and expressed as a probability (the numerical value in the lower table in Fig. 5). This numerical value can also be regarded as the probability that the user selects the music.

[0035] In the operation using the model, the determination unit 12 may perform the characterization (feature quantization) of each piece of information input to the model, that is, the projection into the feature space. As shown in Fig. 4, the characterization of the information is performed for each piece of information. The characterization is performed within the model and can be performed in the same manner as in the prior art. Taking the music ID as an example, the characterization will be described. First, the determination unit 12 inputs the music ID and converts it into an N-dimensional vector V1 associated with the music ID in advance (N is set in advance). Subsequently, the determination unit 12 converts the N-dimensional vector V1 into a feature quantity C1, which is a preset number of numerical values (that is, a vector in the preset number of dimensions). Each numerical value of the feature quantity C1 corresponds to the numerical value of a neuron in the neural network. The conversion from the vector V1 to the feature quantity C1 is performed based on the numerical values (weights) set for the connection between the numerical values in the same manner as in the normal operation in the neural network. The vector V1 associated with the music ID and the weights for converting the vector V1 into the feature quantity C1 are generated by machine learning. Note that the vector V1 at the start point of machine learning is composed of random numerical values. For other information, the characterization is performed in the same manner as above and is used as the feature quantity.

[0036] Note that the characterization does not necessarily have to be performed. For example, information that is originally numerical (for example, the current location information indicating latitude and longitude and the information indicating the remaining time to the destination) may be used in the model without being characterized. Also, other information may be converted into a form used in the model by means other than characterization.

[0037] The determination unit 12 inputs the feature amount C1 of the music ID into an RNN (Recurrent Neural Network) included in the model. Also, the determination unit 12 inputs the feature amount C2 (feature extraction layer of the previous time) after processing in the RNN obtained by an operation on the music ID one before in the user's singing history into the RNN. The determination unit 12 adds these feature amounts C1 and C2 to generate a feature amount C3. The feature amount C3 generated here is input into the RNN as the above-mentioned feature amount C2 during the operation on the next music ID in the user's singing history. When the input music ID is the first music ID in the user's singing history, since the operation on the music ID one before has not been performed, a preset and stored feature amount (for example, a feature amount with all element values set to 0) is used as the feature amount C2. By using the RNN in this way, it is possible to output information on music recommended to the user, taking into account all of the user's singing history including the order.

[0038] The determination unit 12 generates information on the combined layer from the information input to the model and characterized. The information on the combined layer is a simple horizontal combination (placing each information side by side) of each information. Regarding the information of the music ID, as the information on the combined layer, the feature amount C3 generated by the RNN after all the music IDs in the user's singing history are input is used.

[0039] As shown in FIG. 5, the determination unit 12 calculates the information output from the information on the combined layer, that is, the information on the music recommended to the user. This calculation is performed based on numerical values (weights) set for the connection between numerical values in the same way as normal operations in a neural network. The said weights are generated by machine learning.

[0040] Note that, as shown in FIG. 6, as the current location information input to the model, instead of the information indicating latitude and longitude as described above, it may also be an image of a map corresponding to the current location acquired by the acquisition unit 11, information indicating a POI corresponding to the current location, and a mesh ID of a mesh including the current location. Note that, as the current location information input to the model, it is not necessary to use all of the above, and any of them may not be included.

[0041] Each piece of information shown in FIG. 6 is characterized in the same manner as the method described above and used as a feature amount. Also, when using a plurality of pieces of information, their feature amounts may be added together. The added feature amount is used as the feature amount of the current location information shown in FIG. 4.

[0042] In addition, as the information related to the user's singing history input to the model, instead of or in addition to the music ID of the music sung by the user, other information related to the music sung by the user may be used. For example, meta information of the singer singing the music, specifically, any information such as the singer's ID, the singer's age, the singer's gender, whether the singer is a group, and the number of released songs by the singer may be used. Alternatively, meta information of the music itself, specifically, any information such as the lyricist, the composer, whether the music is a live performance, whether the music is used in a drama, and whether the music is Western music may be used. For example, in the internal data server in the recommendation system 10, these pieces of information may be stored in association with the music (for example, the music ID), and acquired as the information input to the model based on the music.

[0043] The generation of the above model by machine learning can be performed, for example, using each piece of past information as learning data (teacher data). In that case, regarding the information of the music to be recommended to the user corresponding to the output, for the music ID number of the music actually sung next to the singing history of the user corresponding to the input, the value is set to 1, and for the music ID numbers of other music, the values are set to 0. Machine learning optimizes the music to be recommended based on each piece of information so that the music to be recommended changes according to the input of the singing history. Note that the generation of the model may be performed by the recommendation system 10 or by a system (device) other than the recommendation system 10.

[0044] The above model, which is a learned model used in the recommendation system 10, is assumed to be used as a program module that is part of artificial intelligence software. The model is used, for example, in a computer equipped with a CPU (Central Processing Unit) and memory, and the CPU of the computer operates according to instructions from the model stored in the memory. For example, the CPU of the computer operates to input information to the model according to the instructions, perform calculations according to the model, and output results from the model. Specifically, the CPU of the computer operates to input information to the input layer of the neural network according to the instructions, perform calculations based on the learned weight coefficients, etc. in the neural network, and output results from the output layer of the neural network.

[0045] The determination unit 12 determines the music to be recommended to the user based on the calculated information of the music to be recommended to the user. For example, the determination unit 12 determines the music with the numerical values of each music indicated by the information of the music to be recommended to the user up to the top N as the music to be recommended to the user. N here is a numerical value set and stored in advance.

[0046] Also, when determining the music to recommend to the user, the determination unit 12 may exclude candidates for recommendation information based on the information indicating the user's music usage history. For example, the determination unit 12 identifies the singer who sings the music included in the user's singing history. The determination unit 12 excludes the music sung by singers other than the said singer (candidates for recommendation information) from the music to be recommended to the user. For example, as shown in the lower table in FIG. 5, the music of singers with no history is masked (excluded). For example, the determination unit 12 stores in advance the correspondence between music and singers and performs the above exclusion process. Note that the music usage history used for excluding music does not necessarily have to be the singing history, and may be the history of music used in music-based applications other than karaoke (for example, music listened to by the user). By filtering music based on the history in this way, it is possible to recommend only the music that the user can surely sing.

[0047] The determination unit 12 outputs the information of the determined music as recommendation information. For example, the determination unit 12 transmits the recommendation information to the user terminal 20 for display. Note that the determination of the music to recommend to the user does not necessarily have to be performed as described above, and may be performed based on the calculated result. Also, the output of the information may be performed by a method other than the above. Also, the determination of the recommendation information may be performed by means other than the model generated by machine learning. The above are the functions of the recommendation system 10 according to the present embodiment.

[0048] Subsequently, with reference to the flowchart of FIG. 7, the process executed by the recommendation system 10 according to the present embodiment (the operation method performed by the recommendation system 10) will be described. In this process, the acquisition unit 11 acquires the information used to determine the music to recommend to the user (S01). The acquired information includes the information indicating the remaining time during which the music is used. Also, it may include the other above-described information. The acquisition of the information is performed, for example, by receiving the information transmitted from the user terminal 20.

[0049] Subsequently, the determination unit 12 uses a pre-stored model to calculate information on music to be recommended to the user from the information acquired by the acquisition unit 11. The said information is, for example, the probability that the user selects a piece of music. Based on the calculated information, the music to be recommended to the user is determined by the determination unit 12 (S02). Subsequently, the determined music is recommended by the determination unit 12 (S03). The recommendation is made, for example, by transmitting the information of the determined music to the user terminal 20 as recommendation information. At the user terminal 20, the recommendation information is received and output such as display is performed. The user can determine the music to sing by referring to the said information. The above is the process executed by the recommendation system 10 according to the present embodiment.

[0050] In the present embodiment, information indicating the remaining time that the music is used is used for determining the recommendation information. For example, the information indicating the required time to the destination as described above is used. Therefore, according to the present embodiment, it is possible to appropriately recommend music to be used by the user according to the remaining time.

[0051] Also, as in the present embodiment, information indicating the place where the music is used, for example, the information indicating the current location of the vehicle as described above, may be used for the recommendation. According to this configuration, it becomes possible to recommend music according to the place. For example, it becomes possible to recommend music considering the current location of the vehicle such as being on the coastline or on the highway. Specifically, when driving along the coastline, it is possible to recommend songs related to summer or the sea.

[0052] Also, as the information indicating the place where the music is used, an image corresponding to the place (for example, an image of a map) may be used for the recommendation. Alternatively, as the information indicating the place where the music is used, the information indicating the POI corresponding to the place may be used for the recommendation. According to this configuration, it becomes possible to make a recommendation considering the terrain of the place where the user is located or the nearby landmarks.

[0053] Also, information indicating the destination of the user who uses the music may be used for the recommendation. According to this configuration, it becomes possible to recommend music according to the user's destination. For example, when the destination is the sea or a snow-capped mountain, etc., it becomes possible to recommend music corresponding to it. Or, when the destination is a baseball stadium, it becomes possible to recommend music related to baseball or sports. In this way, by using the above information for the recommendation, it becomes possible to recommend music according to the surrounding background and scene. However, the information indicating the location where the music is used and the information indicating the destination of the user who uses the music may not be used for the recommendation.

[0054] Also, information indicating the usage history of the user's music may be used for the recommendation. According to this configuration, it becomes possible to recommend music considering the user's music preferences and singing tendencies. Further, candidates for the recommendation information may be excluded based on the information indicating the usage history of the user's music, and the recommendation information may be determined. According to this configuration, a more appropriate recommendation can be made. For example, as described above, only the music that the user can surely sing can be recommended. However, the information indicating the usage history of the user's music may not be used for the recommendation. Also, as long as an effective recommendation can be made to the user regarding the music to be used, information other than the above-mentioned information may be used for the recommendation.

[0055] In the above-described embodiment, the recommendation related to the music during karaoke in the vehicle has been described as an example, but it is not necessarily premised on the recommendation in the vehicle. As long as the remaining time when the music is used is known and a recommendation related to the music is made. For example, it may be applied to the case of making a recommendation related to the music when the end time is determined in a karaoke store.

[0056] Note that the block diagrams used in the description of the above embodiments show blocks of functional units. These functional blocks (components) are realized by any combination of at least one of hardware and software. Also, the method of realizing each functional block is not particularly limited. That is, each functional block may be realized using one physically or logically combined device, or two or more physically or logically separated devices may be directly or indirectly (e.g., using wired, wireless, etc.) connected and realized using these multiple devices. The functional block may be realized by combining software with the above one device or the above multiple devices.

[0057] Functions include, but are not limited to, judgment, decision, determination, calculation, computation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, solution, selection, selection, establishment, comparison, assumption, expectation, regarded as, notification (broadcasting), notification (notifying), communication (communicating), forwarding, configuration (configuring), reconfiguration (reconfiguring), allocation (allocating, mapping), assignment (assigning), etc. For example, a functional block (component) that functions to transmit is called a transmitting unit or a transmitter. In any case, as described above, the realization method is not particularly limited.

[0058] For example, the recommendation system 10 in an embodiment of the present disclosure may function as a computer that performs the information processing of the present disclosure. FIG. 8 is a diagram showing an example of the hardware configuration of the recommendation system 10 according to an embodiment of the present disclosure. The above-described recommendation system 10 may physically be configured as a computer device including a processor 1001, a memory 1002, a storage 1003, a communication device 1004, an input device 1005, an output device 1006, a bus 1007, and the like. Also, the hardware configurations of the user terminal 20 and the in-vehicle terminal 30 may also be those described here.

[0059] In the following description, the term "device" can be read as a circuit, a device, a unit, etc. The hardware configuration of the recommendation system 10 may be configured to include one or more of each device shown in the figure, or may be configured without including some devices.

[0060] Each function in the recommendation system 10 is realized by causing a processor 1001 to perform operations and control communication by a communication device 1004, or by controlling at least one of reading and writing data in a memory 1002 and a storage 1003, by loading a predetermined software (program) onto hardware such as the processor 1001 and the memory 1002.

[0061] The processor 1001 controls the entire computer by operating an operating system, for example. The processor 1001 may be constituted by a central processing unit (CPU: Central Processing Unit) including an interface with peripheral devices, a control device, an arithmetic device, a register, and the like. For example, each function in the above-described recommendation system 10 may be realized by the processor 1001.

[0062] Also, the processor 1001 reads a program (program code), a software module, data, etc. from at least one of the storage 1003 and the communication device 1004 into the memory 1002, and executes various processes according to these. As the program, a program that causes a computer to execute at least a part of the operations described in the above-described embodiments is used. For example, each function in the recommendation system 10 may be realized by a control program stored in the memory 1002 and operating in the processor 1001. Although it has been described that the above-described various processes are executed by one processor 1001, they may be executed simultaneously or sequentially by two or more processors 1001. The processor 1001 may be mounted by one or more chips. Note that the program may be transmitted from a network via a telecommunication line.

[0063] The memory 1002 is a computer-readable recording medium and may be constituted by at least one of, for example, ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), RAM (Random Access Memory), etc. The memory 1002 may be referred to as a register, a cache, a main memory (main storage device), etc. The memory 1002 can store a program (program code), a software module, etc. that are executable for implementing information processing according to an embodiment of the present disclosure.

[0064] The storage 1003 is a computer-readable recording medium and may be constituted by at least one of, for example, 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 versatile disc, a Blu-ray (registered trademark) disc), a smart card, a flash memory (e.g., a card, a stick, a key drive), a floppy (registered trademark) disk, a magnetic strip, etc. The storage 1003 may be referred to as an auxiliary storage device. The storage medium included in the recommendation system 10 may be, for example, a database including at least one of the memory 1002 and the storage 1003, a server, or other appropriate media.

[0065] The communication device 1004 is hardware (a transmission / reception device) for performing communication between computers via at least one of a wired network and a wireless network, and is also referred to as, for example, a network device, a network controller, a network card, a communication module, etc.

[0066] The input device 1005 is an input device that receives external input (for example, a keyboard, a mouse, a microphone, a switch, a button, a sensor, etc.). The output device 1006 is an output device that performs output to the outside (for example, a display, a speaker, an LED lamp, etc.). Note that the input device 1005 and the output device 1006 may have an integrated configuration (for example, a touch panel).

[0067] Also, each device such as the processor 1001 and the memory 1002 is connected by a bus 1007 for communicating information. The bus 1007 may be configured using a single bus, or may be configured using different buses for each device.

[0068] Also, the recommendation system 10 may be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), a field programmable gate array (FPGA), etc., and some or all of the functional blocks may be realized by the hardware. For example, the processor 1001 may be implemented using at least one of these hardware.

[0069] The processing procedures, sequences, flowcharts, etc. of each aspect / embodiment described in the present disclosure may be reordered as long as there is no contradiction. For example, regarding the method described in the present disclosure, the elements of various steps are presented using an exemplary order and are not limited to the specific order presented.

[0070] The input / output information, etc. may be stored in a specific location (for example, a memory), or may be managed using a management table. The input / output information, etc. may be overwritten, updated, or appended. The output information, etc. may be deleted. The input information, etc. may be transmitted to other devices.

[0071] The determination may be made based on a value represented by 1 bit (either 0 or 1), a Boolean value (true or false), or a numerical comparison (e.g., comparison with a predetermined value).

[0072] Each aspect / embodiment described in the present disclosure may be used alone, in combination, or switched and used during execution. Also, the notification of predetermined information (e.g., the notification of "being X") is not limited to being explicitly performed, and may be performed implicitly (e.g., without performing the notification of the predetermined information).

[0073] As described in detail above regarding the present disclosure, it is obvious to those skilled in the art that the present disclosure is not limited to the embodiments described in the present disclosure. The present disclosure can be implemented as modified and changed aspects without departing from the spirit and scope of the present disclosure defined by the claims. Therefore, the description of the present disclosure is for illustrative purposes and has no restrictive meaning for the present disclosure.

[0074] 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, etc., whether called software, firmware, middleware, microcode, a hardware description language, or by another name.

[0075] Also, software, instructions, information, etc. may be transmitted and received via a transmission medium. For example, when software is transmitted from a website, server, or other remote source using at least one of wired technologies (such as coaxial cable, optical fiber cable, twisted pair, Digital Subscriber Line (DSL), etc.) and wireless technologies (such as infrared, microwave, etc.), at least one of these wired and wireless technologies is included within the definition of the transmission medium.

[0076] The terms "system" and "network" used in the present disclosure are used interchangeably.

[0077] Also, the information, parameters, etc. described in the present disclosure may be represented using absolute values, relative values from a predetermined value, or corresponding other information.

[0078] The terms "determining" and "deciding" as used in this disclosure may encompass a wide variety of operations. "Determining" and "deciding" may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up (e.g., searching in a table, database, or another data structure), ascertaining, and considering something as having been "determined" or "decided". Also, "determining" and "deciding" may include considering something as having been "determined" or "decided" after receiving (e.g., receiving information), transmitting (e.g., transmitting information), inputting, outputting, accessing (e.g., accessing data in memory), etc. Further, "determining" and "deciding" may include considering something as having been "determined" or "decided" after resolving, selecting, choosing, establishing, comparing, etc. That is, "determining" and "deciding" may include considering that some operation has been "determined" or "decided". Also, "determining (deciding)" may be read as "assuming", "expecting", "considering", etc.

[0079] The terms "connected" or "coupled", or any variations thereof, mean any direct or indirect connection or coupling between two or more elements, and can include the presence of one or more intermediate elements between two elements that are "connected" or "coupled" to each other. The coupling or connection between elements can be physical, logical, or a combination thereof. For example, "connected" may be read as "accessed". As used in this disclosure, two elements can be considered to be "connected" or "coupled" to each other using at least one of one or more wires, cables, and printed electrical connections, and also, by way of some non-limiting and non-exhaustive examples, electromagnetic energy having wavelengths in the radio frequency region, microwave region, and optical (both visible and invisible) regions.

[0080] As used in this disclosure, the recitation "based on" does not mean "based only on" unless otherwise specified. In other words, the recitation "based on" means both "based only on" and "based at least on".

[0081] Any reference to an element using designations such as "first", "second", etc. used in this disclosure does not generally limit the quantity or order of those elements. These designations can be used in this disclosure as a convenient way to distinguish between two or more elements. Thus, a reference to a first and a second element does not mean that only two elements can be employed, or that the first element must precede the second element in any form.

[0082] In this disclosure, when the terms "include", "including", and variations thereof are used, these terms are intended to be inclusive in the same manner as the term "comprising". Further, the term "or" used in this disclosure is not intended to be exclusive.

[0083] In the present disclosure, for example, when articles are added by translation, such as a, an, and the in English, the present disclosure may include that the nouns following these articles are in the plural form.

[0084] In the present disclosure, the term "A and B are different" may mean that "A and B are different from each other". Note that the term may also mean that "A and B are different from C respectively". Terms such as "separate", "coupled", etc. may also be interpreted in the same way as "different".

Description of Reference Numerals

[0085] 10… Recommendation system, 11… Acquisition unit, 12… Determination unit, 20… User terminal, 30… In-vehicle terminal, 1001… Processor, 1002… Memory, 1003… Storage, 1004… Communication device, 1005… Input device, 1006… Output device, 1007… Bus.

Claims

1. A recommendation system that determines recommendation information for recommending to a user regarding a piece of music to be used, an acquisition unit that acquires information indicating the remaining time during which the music is to be used, a determination unit that determines the recommendation information by using a model stored in advance that inputs the information acquired by the acquisition unit and outputs information on the music to be recommended based on the information acquired by the acquisition unit, comprising: the acquisition unit is a recommendation system that acquires information indicating the location where the music is to be used.

2. The recommendation system according to claim 1, wherein the acquisition unit acquires an image corresponding to the location as information indicating the location where the music is to be used.

3. The recommendation system according to claim 1 or 2, wherein the acquisition unit acquires information indicating a POI corresponding to the location as information indicating the location where the music is to be used.

4. The recommendation system according to any one of claims 1 to 3, wherein the acquisition unit acquires information indicating the destination of the user who uses the music.

5. The recommendation system according to any one of claims 1 to 4, wherein the acquisition unit acquires information indicating the usage history of the user's music.

6. The recommendation system according to claim 5, wherein the determination unit determines the recommendation information by excluding candidates for the recommendation information based on the information indicating the usage history of the user's music.

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