KR20210051349A - Electronic device and control method thereof - Google Patents

Abstract

The present invention relates to an electronic device, which includes a processor for recommending a service related to content based on a preference characteristic of a user related to the content, and adjusting the preference characteristic of the user for content based on history information of the service used by the user through a network. According to the present invention, it is possible to provide a recommendation service more optimized for the user preference.

Description

Electronic device and its control method {ELECTRONIC DEVICE AND CONTROL METHOD THEREOF}

The present invention relates to an electronic device and a control method thereof, and more particularly, to an electronic device that provides a recommended service optimized to a user, and a control method thereof.

With the recent development of TV technology, TV has come to provide a so-called recommendation service that recommends content that users prefer among numerous contents that can be provided by TV, not just displaying content images. Such a recommendation service can reduce the effort and time that a user spends on searching for content he or she prefers in the prior art, and thus user convenience and TV usability can be improved. For example, when a user prefers a baseball game, the TV recommends a baseball broadcast channel to the user or connects a baseball shopping site to purchase baseball-related products, thereby providing an optimized viewing environment for users who prefer baseball. I can.

An object of the present invention is to provide an electronic device and a control method thereof capable of providing a recommendation service more optimized for user preference by considering a history capable of improving the accuracy of user preference.

In addition, another object of the present invention is to provide an electronic device capable of providing a recommended service most suitable for a viewing environment of a plurality of users, and a control method thereof.

It is an object of the present invention to recommend a service for the content based on a user's preference characteristic for the content, and the user's preference characteristic for the content based on the history information of the service used by the user through the network. It can be achieved by an electronic device including a processor that adjusts.

The display further includes a display, and the processor may control the display to display an image of the service through the network, and obtain the history information through character recognition of the image of the service.

The history information may include information on content provided to the user through the service.

The history information may include history information using a service of a social network to which the user belongs.

The history information may include history information of the user using the service using an external device.

The history information may include information on the surrounding environment of the electronic device.

When it is identified that a plurality of users including the user is watching, the processor may determine preference characteristics of the plurality of users based on the user's history information.

The processor may determine a preference characteristic of the plurality of users based on a preference characteristic of a user whose viewing immersion is equal to or greater than a set value among the plurality of users.

The processor may identify a user group corresponding to the user characteristic of the user from among a plurality of user groups provided for each user characteristic, and adjust the preference characteristic of the identified user group based on the user's history information.

The processor may adjust a preference characteristic of a user group corresponding to the user based on the user's history information whose viewing immersion of each of the plurality of users included in the plurality of user groups is equal to or greater than a set value.

An object of the present invention is the steps of recommending a service related to the content based on a user's preference characteristic for the content; And adjusting the user's preference characteristics with respect to the content based on the history information of the service used by the user through the network.

Adjusting the user's preference characteristics may include displaying an image of the service through the network; And acquiring the history information through character recognition of the image of the service.

The history information may include information on content provided to the user through the service.

The history information may include history information using a service of a social network to which the user belongs.

The history information may include history information of the user using the service using an external device.

The history information may include information on the surrounding environment of the electronic device.

Adjusting the preference characteristics may include determining the preference characteristics of the plurality of users based on the user's history information when it is identified that a plurality of users including the user are watching.

The determining of the preference characteristics of the plurality of users may include determining the preference characteristics of the plurality of users based on the preference characteristics of a user whose viewing immersion is equal to or greater than a set value among the plurality of users.

The adjusting of the preference characteristics may include: identifying a user group corresponding to the user characteristic of the user from among a plurality of user groups provided for each user characteristic; And adjusting the preference characteristics of the identified user group based on the user's history information.

An object of the present invention as described above is a computer-readable code, in a recording medium in which a computer program including a code for performing a method for controlling an electronic device is stored, the method for controlling the electronic device Recommending a service related to the content based on preference characteristics; And adjusting the user's preference characteristics with respect to the content based on the history information of the service used by the user through the network. I can.

According to the present invention, it is possible to provide a recommendation service that is more optimized for user preference.

In addition, according to the present invention, it is possible to provide a recommendation service that best suits the viewing environment of a plurality of users.

1 illustrates an electronic device according to an embodiment of the present invention.
2 shows an example of a configuration of the electronic device of FIG. 1.
3 shows an example of a control method for the electronic device of FIG. 1.
4 shows an example of history information in relation to operation S32 of FIG. 3.
5 shows an example of acquiring service history information through a network in relation to operation S32 of FIG. 3.
6 shows another example of acquiring service history information through a network in relation to operation S32 of FIG. 3.
7 illustrates an example of a control method of an electronic device for determining preference characteristics for a plurality of users in relation to operation S31 of FIG. 3.
FIG. 8 shows an example of adjusting preference characteristics of a user group in relation to operation S72 of FIG. 7.
9 illustrates another example of a control method of an electronic device for determining preference characteristics for a plurality of users in relation to operation S31 of FIG. 3.
FIG. 10 shows an example of adjusting preference characteristics of a user group in relation to operation S92 of FIG. 9.
11 shows an example of identifying the degree of immersion in relation to operation S91 of FIG. 9.
12 shows another example of identifying the degree of immersion in relation to operation S92 of FIG. 9.
13 illustrates an example of identifying preferred characteristics of a user group based on user characteristics according to an embodiment of the present invention.
14 illustrates an example of adjusting a preference characteristic of a user group based on service history information with reference to FIG. 13.
15 shows an example of the configuration of the processor of FIG. 3.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the following description of the embodiments, matters described in the accompanying drawings are referred to, and the same reference numerals or reference numerals in each drawing indicate components that perform substantially the same operation. At least one of the plurality of configurations in the present specification refers to not only all of the plurality of configurations, but also one of each of the plurality of configurations excluding the rest, or a combination thereof.

1 shows an electronic device 1 according to an embodiment of the present invention. As shown in FIG. 1, the electronic device 1 may be implemented as a display device capable of displaying an image. For example, the electronic device 1 may include a TV, a computer, a smart phone, a tablet, a portable media player, a wearable device, a video wall, an electronic frame, and the like. In addition, the electronic device 1 may be implemented as various types of devices such as image processing devices such as a set-top box without a display, household appliances such as refrigerators and washing machines, and information processing devices such as a computer body. However, in the following description, for convenience of description, it is assumed that the electronic device 1 is implemented as a TV.

The electronic device 1 may perform a service recommendation function. The service recommendation function is a function of providing content that the user 2 prefers based on the user's 2 history information. For example, as illustrated in FIG. 1, when the user 2 prefers news, the electronic device 1 may provide a recommendation channel 13 indicating at least one news channel. However, FIG. 1 shows that the recommended channel 13 is displayed in the form of a user interface, but is not limited thereto. Therefore, the electronic device 1 provides various information on the recommended channel 13 such as voice. It can be provided in a way. However, in the following description, for convenience of description, it is assumed that a recommended service is provided through a UI.

The electronic device 1 may identify the user 2 in order to provide a recommended service to the user 2. The electronic device 1 may identify the user 2 based on information about the user 2 acquired through the information acquisition unit 27. The information acquisition unit 27 may include a camera capable of acquiring an image or a microphone receiving a voice signal. The electronic device 1 may identify the user 2 by acquiring an image of the front of the electronic device 1 through a camera and recognizing the user 2 included in the acquired image. Also, the electronic device 1 may identify the user 2 based on the voice signal received through the microphone. The electronic device 1 may identify, for example, the identity, age, and gender of the user 2 based on information acquired through a camera or a microphone.

The electronic device 1 may obtain history information. The history information may include content history information about content provided through an internal service of the electronic device 1. In the case of a TV, for example, the internal service may include a service provided through channels such as terrestrial, cable, and satellite waves. The electronic device 1 may acquire content type and genre, content usage time, content language, and the like as content history information. The content type may be classified into, for example, music, photos, and videos, and the content genre may be classified into sports, dramas, and movies. Also, the content history may include a menu history used in the electronic device 1 in relation to the content. A menu related to content may mean a menu used in connection with the type, genre, usage time, language, etc. of the content being executed in the electronic device 1.

The history information may include surrounding environment history information. The surrounding environment history information may include information on a peripheral device connected to the electronic device 1 in relation to the content. For example, when a portable game device is connected to the electronic device 1, the electronic device 1 may obtain a history of contents executed in response to the connection of the portable game device, and when the portable game device is disconnected, the connection of the portable game device Content history executed in response to release may be obtained. In addition, the history of the surrounding environment may include a history of weather, temperature, humidity, lighting, etc. in relation to the content. The electronic device 1 may further include a sensor unit 25 to collect a history of weather, temperature, humidity, lighting, and the like.

In particular, according to the present embodiment, the electronic device 1 may obtain history information on an external service used through a network. The electronic device 1 may obtain a history of external services used by the user 2 through various communication networks such as an Internet network and a local network. The external service history may include a history of external services used by the user 2 using the external device 5 as well as the electronic device 1. The external device 5 may be implemented as a smart phone, a tablet, a personal computer, an electronic frame, and a server. However, in the following description, for convenience of explanation, it is assumed that the external device 5 is implemented as a smartphone. The electronic device 1 may obtain history information of an external service used through the external device 5.

The electronic device 1 may access the integrated server to obtain a history of external services used through a network. In this case, the electronic device 1 acquires the integrated account information of the user 2 and accesses the integrated server based on the acquired integrated account information, so that the user 2 ), the history information of the used network service can be obtained. If the electronic device 1 accesses an individual server, the electronic device 1 may access using each account information corresponding to the individual server, and obtain history information used by the user 2 through the individual server. However, since the present invention is not limited thereto, the electronic device 1 may access the service server in various ways to obtain history information of a network service.

Meanwhile, the electronic device 1 can remotely control the external device 5 and obtain history information using a network service by remote control. Conversely, the electronic device 1 may operate according to the remote control of the external device 5, use a network service through remote control, and obtain history information about it.

The electronic device 1 may adjust the preference characteristics of the user 2 based on the history information of the network service. The network service may include a social network service (SNS), an OTT (Over the TOP), etc., but hereinafter, a process of adjusting preference characteristics when the user 2 uses a social network service is described. Explain in detail. The social network service is a service that provides a virtual space where users can establish a virtual relationship, such as a social relationship, and the user (2) participates in the virtual space to provide information to other users or receive information from other users. have. The electronic device 1 may acquire, for example, a history of contacting news about a sporting event, a history of chatting directly input from a chat room about a sporting event, and the like through a social network to which the user 2 belongs. The electronic device 1 may identify that the user 2 prefers the sport rather than the news based on the acquired history information, and may adjust the preference characteristic of the user 2 from the original news to the sport. In this case, the electronic device 1 may provide a recommendation service based on the adjusted preference characteristics. For example, the electronic device 1 may provide a recommendation channel 13 indicating at least one sports channel. However, since the network service is not limited to the social network service, the electronic device 1 uses the user ( You can adjust the preferred characteristics of 2).

As described above, according to the present embodiment, since the electronic device 1 can adjust the preference characteristics of the user 2 based on the history information of the network service, it is possible to provide a recommendation service optimized for user preference.

2 shows an example of a configuration of the electronic device of FIG. 1. As shown in FIG. 2, the electronic device 1 includes a communication unit 21, a signal input/output unit 22, a display 11, a user input unit 23, a storage unit 24, a sensor unit 25, and information. It may include an acquisition unit 27 and a processor 20.

Hereinafter, the configuration of the electronic device 1 will be described. In this embodiment, a case where the electronic device 1 is a display device such as a TV is described, but since the electronic device 1 can be implemented with various types of devices, this embodiment limits the configuration of the electronic device 1. It is not. It is possible that the electronic device 1 is not implemented as a display device, and in this case, the electronic device 1 may not include components for image display such as the display 11. For example, when the electronic device 1 is implemented as a set-top box, the electronic device 1 may output an image signal to an external TV through the signal input/output unit 22.

The communication unit 21 is a two-way communication circuit including at least one of components such as a communication module and a communication chip corresponding to various types of wired and wireless communication protocols. For example, the communication unit 21 is a wireless communication module that performs wireless communication with an AP (Access Point) according to a Wi-Fi method, a wireless communication module that performs one-to-one direct wireless communication such as Bluetooth, or wired to a router or gateway. It can be implemented with a connected LAN card. The communication unit 21 may connect to a server or an external device 5 through a network. The server may include at least one service server capable of providing various services to the electronic device 1 or the external device 5 through a network.

In addition, the communication unit 21 may communicate with a remote controller or a smart phone separated from the main body of the electronic device 1. For example, when a remote controller, a smart phone, or the like receives a voice from the user 2, the communication unit 21 may receive a voice signal from a remote controller, a smart phone, or the like. In this case, a remote controller application may be installed on a smart phone or the like. The communication unit 21 may receive a voice signal from a remote controller, a smart phone, or the like through a method such as Wi-Fi or Bluetooth.

In addition, the communication unit 21 may include a configuration for transmitting and receiving data through a method such as Wi-Fi, Bluetooth, and infrared rays, such as a remote controller and a smart phone. However, when the communication unit 21 communicates with at least one service server, the communication unit that communicates with at least one service server and the communication unit that communicates with a remote controller, a smart phone, etc. may be provided to be the same, or may be provided separately. have.

The signal input/output unit 22 may be connected to a peripheral device to transmit and receive data. As an example, the signal input/output unit 22 is wired in a 1:1 or 1:N (N is a natural number) method with a peripheral device such as a set-top box or an optical media player, thereby receiving data from a peripheral device or a peripheral device. Output data to For example, the signal input/output unit 22 may receive a terrestrial, cable, or satellite broadcast signal from a peripheral device such as a set-top box. In this case, the signal input/output unit 22 may further include a tuning unit for tuning a broadcast signal. The signal input/output unit 22 includes a connector or port according to a preset transmission standard, such as an HDMI port, a DisplayPort, a DVI port, a Thunderbolt, a USB port, and the like.

The display 11 includes a display panel capable of displaying an image on a screen. The display panel is provided with a light-receiving structure such as a liquid crystal type or a self-luminous structure such as an OLED or LED type. The display 11 may additionally include an additional component according to the structure of the display panel. For example, if the display panel is a liquid crystal type, the display 11 includes a liquid crystal display panel, a backlight unit that supplies light, and It includes a panel driving substrate for driving the liquid crystal of the liquid crystal display panel. However, the display 11 may be omitted when the electronic device 1 is implemented as a set-top box or the like.

The user input unit 23 includes various types of input interface related circuits provided to be manipulated by a user to perform a user's input. The user input unit 23 can be configured in various forms depending on the type of the electronic device 1, for example, a mechanical or electronic button unit of the electronic device 1, a touch pad, a touch screen installed on the display 11 Etc.

The storage unit 24 stores digitized data. The storage unit 24 is loaded with storage of non-volatile properties that can store data regardless of whether or not power is supplied, and data to be processed by the processor 20 is loaded, and if power is not supplied, the data is stored. Includes memory of volatile properties that cannot be done. Storage includes flash-memory, hard-disc drive (HDD), solid-state drive (SSD) read-only memory (ROM), etc., and buffers and random access memory (RAM) in memory Etc. Buffers can temporarily store processed data to mitigate differences in processing speed between components.

The sensor unit 25 may include at least one sensor for detecting the location of the user 2. For example, the sensor unit 25 includes the distance sensor 26, and the position of the user 2 with respect to the electronic device 1, for example, the distance from the electronic device 1, and the relative You can detect angle differences and the like. When detecting the relative angle of the user 2, the distance sensor 26 may further include an orientation sensor. The distance sensor 26 may measure the location of the user 2 based on, for example, a difference between a time when an infrared ray or the like is emitted and a time when the infrared ray is emitted and a time reflected by the user 2 or the like and returned.

In addition, the sensor unit 25 may further include a temperature sensor, a humidity sensor, a weather sensor, etc. that can measure temperature, humidity, weather, and the like. However, since the electronic device 1 is not limited to acquiring information on temperature, humidity, weather, etc. through the sensor unit 25, the temperature, humidity, weather, etc. from the server providing weather information through the communication unit 21 You can get information about it.

The information acquisition unit 27 may acquire information on the user 2. The information acquisition unit 27 may further include a camera 28 capable of acquiring an image of the front surface of the electronic device 1 or the like. The processor 20 may identify the user 2 based on the image acquired by the camera 28. If a plurality of users are included in the acquired image, each of the plurality of users may be identified. The processor 20 may use various identification algorithms to identify a user.

In addition, the information acquisition unit 27 may further include a microphone 29 capable of receiving a voice signal from the user 2. When the microphone 29 is provided with two or more microphones 29, the processor 20 is the location of the user 2 who uttered the voice based on the voice signal flowing into the two or more microphones 29, that is, the location of the sound source. Location can be identified. As an example, assuming that the voice signal from a microphone with a closer distance to the sound source arrives first, and the voice signal arrives late by the arrival delay time t from the other microphone, the distance between the sound sources is the distance between the microphones 29 of 2 or more. And the sound wave traveling distance to two or more microphones 29 may be measured, and the direction of the sound source may be measured based on the arrival delay time t.

The processor 20 may identify the user 2 based on the voice signal acquired through the microphone 29. For example, the identity, age, and gender of the user 2 may be identified based on the tone, intensity, and frequency of the voice.

The processor 20 may perform voice recognition processing on the voice signal introduced into the microphone 29. The processor 20 may select a voice recognition model for voice and perform voice recognition processing for voice based on the selected voice recognition model. Further, the processor 20 may acquire text data as a result of recognition by speech recognition processing and perform an operation according to the text data. However, when the voice recognition processing for the voice signal is performed by at least one voice recognition processing server, the processor 20 processes at least one voice recognition process through the communication unit 21 with the voice signal acquired through the microphone 29. The text data is transmitted to the server, and the text data, which is the recognition result of the voice signal, is received from at least one voice recognition processing server through the communication unit 21, and the text data received from the at least one voice recognition processing server is processed. Can perform the indicated operation.

The processor 20 includes one or more hardware processors implemented as a CPU, chipset, buffer, circuit, etc. mounted on a printed circuit board, and may be implemented as a system on chip (SOC) depending on a design method. When the electronic device 1 is implemented as a display device, the processor 20 includes modules corresponding to various processes such as a demultiplexer, a decoder, a scaler, an audio digital signal processor (DSP), and an amplifier. Here, some or all of these modules may be implemented as an SOC. For example, a module related to image processing, such as a demultiplexer, a decoder, and a scaler, may be implemented as an image processing SOC, and an audio DSP may be implemented as an SOC and a separate chipset.

The processor 20 may recommend a service related to the content based on the preference characteristic of the user 2 regarding the content. For example, when the user 2's preferred characteristic is news, a news channel may be provided as the recommendation channel 13.

In addition, the processor 20 may adjust the user 2's preference characteristics with respect to the content based on the history information of the service used by the user 2 through the network. For example, when the user 2 shows a history of interest in sports-related information through a network service, the processor 20 indicates that the user 2 prefers sports to news based on the history of the network service, The preference characteristics of the user 2 can be adjusted. In addition, the processor 20 may provide a recommendation service based on the adjusted preferred sport.

On the other hand, the processor 20 is based on at least some of data analysis, processing, and generation of result information for identification of preference characteristics, performance of service recommendation operations, acquisition of network service history information, and adjustment of preference characteristics. Alternatively, it may be performed using at least one of machine learning, a neural network, or a deep learning algorithm as an artificial intelligence algorithm.

For example, the processor 20 may perform functions of a learning unit and a recognition unit together. The learning unit may perform a function of generating a learned neural network network, and the recognition unit may perform a function of recognizing (or inferring, predicting, estimating, or determining) data using the learned neural network network. The learning unit can create or update a neural network network. The learning unit may acquire training data to create a neural network. For example, the learning unit may acquire the learning data from the storage unit 24 or may obtain it from the outside. The training data may be data used for training the neural network, and the neural network network may be trained by using the data obtained by performing the above-described operation as training data.

The learning unit may perform pre-processing on the acquired training data before training the neural network network using the training data, or may select data to be used for training from among a plurality of training data. For example, the learning unit may process the training data into a preset format, filter it, or add/remove noise to process the training data into a form suitable for learning. The learning unit may generate a neural network network configured to perform the above-described operation by using the preprocessed training data.

The learned neural network network may be composed of a plurality of neural network networks (or layers). Nodes of a plurality of neural network networks have weights, and the plurality of neural network networks may be connected to each other such that an output value of one neural network network is used as an input value of another neural network network. Examples of neural network networks include CNN (Convolutional Neural Network), DNN (Deep Neural Network), RNN (Recurrent Neural Network), RBM (Restricted Boltzmann Machine), DBN (Deep Belief Network), BRDNN (Bidirectional Recurrent Deep Neural Network), and It may include models such as Deep Q-Networks.

Meanwhile, the recognition unit may acquire target data to perform the above-described operation. The target data may be obtained from the storage unit 24 or may be obtained from the outside. The target data may be data to be recognized by the neural network. The recognition unit may perform pre-processing on the acquired target data or select data to be used for recognition from among a plurality of target data before applying the target data to the learned neural network network. For example, the recognition unit may process target data into a preset format, filter, or add/remove noise to process the target data into a form suitable for recognition. The recognition unit may obtain an output value output from the neural network network by applying the preprocessed target data to the neural network network. The recognition unit may acquire a probability value or a reliability value together with the output value.

3 shows an example of a control method for the electronic device of FIG. 1. Each operation of FIG. 3 may be executed by the processor 20 of the electronic device 1. As shown in FIG. 3, the processor 20 may recommend a service related to the content based on the user's preference characteristic for the content (S31).

In addition, the processor 20 may adjust the user's preference characteristics for the content based on the history information of the service used by the user through the network (S32).

As described above, according to the control method of the present embodiment, the processor 20 of the electronic device 1 can adjust the preference characteristics of the user 2 based on the history information of the network service, so that the recommended service more optimized for the user preference. Can provide.

4 shows an example of history information in relation to operation S32 of FIG. 3. The processor 20 may collect history information of the user 2 related to the content provided to the user 2, and generate a lookup table, for example, as shown in FIG. 4 based on the collected history information. The history information may be generated as a personalized model corresponding to the user 2, and may be stored in the storage unit 24 or in an external server. However, since the history information shown in FIG. 4 is for convenience of description, history information different from that of FIG. 4 may be provided in some cases.

As shown in FIG. 4, the history information may include a history factor for an external network service used by the user 2 through a network. As an example, the history information may include a history factor such as a type of content used through an external network service, a genre, a usage time, a device used, and a weather. However, since it is not limited thereto, the history information may include various history factors according to a design method.

The processor 20 may, for example, identify a preference characteristic of the user 2 based on the history information collected according to the history factor shown in FIG. 4 and provide a recommendation service based on the identified preference characteristic. As an example, the processor 20 may obtain history information in which the user 2 mainly views a baseball video as a network service through the electronic device 1 between 7 and 8 pm. The processor 20 identifies that the preferred characteristic when the user 2 uses the electronic device 1 between 7 and 8 pm is a baseball video, based on the history information of the network service, and the user 2 When the electronic device 1 is used between 7 and 8 pm, for example, at least one baseball channel may be displayed as the recommended channel 13.

The processor 20 may adjust the preference characteristic based on the history information of the network service. As an example, the processor 20 may obtain history information in which the user 2 mainly views a drama video as a network service through the electronic device 1 between 7 and 8 pm. In this case, the processor 20 may adjust a preference characteristic when the user 2 uses the electronic device 1 between 7 and 8 PM based on the history information of the network service from a baseball video to a drama video. .

As another example, the processor 20 may identify a user's preference characteristic based on history information using a network service through the external device 5 and provide a recommendation service based on the identified preference characteristic. For example, the processor 20 may obtain history information in which the user 2 mainly listens to classical music as a network service through the external device 5 between 7 and 8 am. The processor 20 identifies classical music as a preferred characteristic when the user 2 uses the external device 5 between 7 and 8 am, based on the history information of the network service through the external device 5 In addition, when the user 2 uses the electronic device 1 between 7 and 8 am, for example, at least one music broadcasting channel may be displayed as the recommended channel 13.

Meanwhile, the processor 20 may additionally consider a history factor related to the surrounding environment such as weather, temperature, and humidity, and may provide a recommended service to the user 2 based on this. As an example, the processor 20 may obtain history information of the user 2 mainly listening to classical music through a network service through the external device 5 between 7 and 8 am whenever the weather is cloudy. In this case, when the user 2 uses the electronic device 1 between 7 and 8 a.m. when the weather is cloudy, the processor 20 displays at least one music broadcasting channel as, for example, a recommended channel 13. Can give. However, since the surrounding environment history factor is not limited thereto, it may be provided in various ways according to a design method. For example, the surrounding environment history factor may further include connection of peripheral devices, disconnection of connection, various noises, and the like. That is, the processor 20 additionally collects environmental history factors such as connection, disconnection of peripheral devices, various noises, etc., and identifies the preference characteristics of the user 2 based on the collected environmental history factors, or Can be adjusted.

As described above, according to the present embodiment, the processor 20 may provide a recommendation service optimized for user preference based on the history of using network services through the electronic device 1 or the external device 5.

5 shows an example of acquiring service history information through a network in relation to operation S32 of FIG. 3. As shown in FIG. 4, the user 2 can use the service through the network. Hereinafter, an example of acquiring history information when the user 2 uses a network service through the external device 5 will be described.

The processor 20 may acquire history information of various external network services used by the user 2 with the external device 5. For example, the user 2 may run an application capable of participating in the baseball social network installed on the external device 5 and use various services provided by the baseball social network server through the executed application. The user 2 can use, for example, a baseball news service, a baseball chat room service, a baseball product shopping mall service, a baseball game ticket purchase service, and the like by participating in a baseball-related social network, for example. In this case, the processor 20 may acquire the history information of the baseball social network service by the corresponding application, and acquire the history information according to the behavior, gesture, gaze, movement, etc. of the user 2 while the application is running. have.

The processor 20 may identify the state of account information of the user 2 with respect to the network service server. For example, before acquiring the history information for each service, the processor 20 may perform crawling to identify the status of each account information, thereby determining whether or not it is a network service to obtain the history information. For example, when the account information of the baseball social network service is identified as being activated through croring, the processor 20 may obtain history information on the baseball network service, and when it is identified as being deactivated account information, the baseball History information on network services may not be acquired. However, since the present invention is not limited thereto, the processor 20 may obtain history information for each service regardless of whether the account information is active or inactive.

The processor 20 may acquire history information of a network service in real time. Real-time may include the case where the user 2 watches the content image 12 displayed on the display 11. That is, while displaying the content image 12, the processor 20 may perform a crossing operation as described above or may perform an operation of obtaining history information. In this case, the preference characteristics of the user 2 may be identified or the preference characteristics may be adjusted based on the history information acquired in real time. However, since it is not limited thereto, history information may be obtained in various ways according to a design method. For example, the history information may be acquired according to whether or not the network service is used, or the history information may be acquired at a predetermined period.

In addition, since the method of acquiring the history information through the network service is not limited to the case of using the network service through the external device 5, the processor 20 is used even when the external network service is used through the electronic device 1 You can obtain history information. For example, when the user 2 executes an application installed in the electronic device 1 and uses a movie-related OTT service, the processor 20 may provide a movie OTT service used by the user 2, for example, the latest movie news service, It is possible to obtain history information such as a movie chat room service and a movie ticket purchase service. In this case, the processor 20 may obtain the history information of the movie OTT service by the user 2 through interworking with the application executed in the electronic device 1, and the user 2 It is possible to acquire history information according to actions, gestures, gazes, and movements.

As described above, according to the present embodiment, the processor 20 can obtain the history information of the network service through the external device 5 or the electronic device 1 in a wide range and easily. Accuracy can be improved.

6 shows another example of acquiring service history information through a network in relation to operation S32 of FIG. 3. As shown in FIG. 6, the user 2 can use the network service through the external device 5. Hereinafter, an example of acquiring history information when the user 2 uses a network service through the external device 5 will be described.

As shown in FIG. 6, when the user 2 uses a network service, for example, a baseball social network service through the external device 5, the processor 20 provides the history information of the baseball social network service of the user 2 Can be obtained. As an example, the user 2 participates in a baseball social network, searches for baseball news described in the baseball news section 61, displays the preference for the searched baseball news in the preference section 62, and retrieves the baseball news. You can enter your own comments on the comments section 63.

In this case, the processor 20 may identify the contents of the baseball news in the baseball news section 61. For example, the processor 20 may acquire information on a subject word, a representative word, a search word, and the like to identify baseball news content. Alternatively, the processor 20 identifies the news content by capturing the title and full text of the baseball news displayed on the external device 5 and then identifying the identified character using Automatic Character Recognition (ACR) technology. can do. The processor 20 also identifies the preferences of the user 2 indicated in the preferences section 62 and the contents of the comments of the user 2 indicated in the comment section 63 using, for example, automatic character recognition technology. can do.

In addition, since the method of acquiring the history information through the network service is not limited to the case of using the network service through the external device 5, the processor 20 is used even when the external network service is used through the electronic device 1 You can obtain history information. For example, when the user 2 uses a movie-related OTT service through the electronic device 1, the processor 20 provides a movie OTT service used by the user 2, for example, for a movie searched by the user 2. It is possible to obtain information on news content, whether the user 2 prefers a movie, or comment content. In this case, the processor 20 may use automatic character recognition technology for the video of the movie OTT service displayed on the display 11.

As described above, according to the present embodiment, since the processor 20 can accurately acquire the history information of the network service by the user 2, it is possible to increase the accuracy of identification and adjustment of the preferred characteristic based on this.

7 illustrates an example of a control method of an electronic device for determining preference characteristics for a plurality of users in relation to operation S31 of FIG. 3. Each operation of FIG. 7 may be executed by the processor 20 of the electronic device 1.

As shown in FIG. 7, the processor 20 may identify whether a plurality of users including a user are watching (S71).

In addition, when it is identified that a plurality of users are watching, the processor 20 may determine preference characteristics of the plurality of users based on the user's history information (S72).

As described above, according to the control method of the present embodiment, the processor 20 may provide a recommendation service suitable for a viewing environment of a plurality of users.

FIG. 8 shows an example of adjusting preference characteristics of a user group in relation to operation S72 of FIG. 7. As illustrated in FIG. 8, the electronic device 1 may display a predetermined content image 12 on the display 11 in a viewing environment of a plurality of users 21, 22, and 23.

In this case, the electronic device 1 may consider the preference characteristics of all of the plurality of users 21, 22, and 23 in providing the recommended service. As an example, when all of the preference characteristics are identified as sports based on the history information of the plurality of users 21, 22, 23, the processor 20 Can be grouped, and a preferred characteristic of the group can be determined as a sport.

If the preference characteristics of the plurality of users 21, 22, 23 are different, for example, the preference characteristics of the first user 21 and the second user 22 are sports, while the remaining third users 23 When the preference characteristic of is news, the processor 20 may group a plurality of users 21, 22, and 23, and set the preference characteristic of the group to a multiplayer sport.

In addition, the processor 20 may identify whether a plurality of users 21, 22, and 23 are viewing the image 12. The processor 20 may identify whether or not a plurality of users 21, 22, and 23 are watching based on the sensor unit 25 or the information acquisition unit 27. As an example, the processor 20 may identify whether or not to watch the view based on whether it is within a predetermined distance through the distance sensor 26. As another example, the processor 20 may identify whether to watch or not according to whether the direction of the body or the direction of the gaze is toward the display 11 through the camera 28. However, since it is not limited thereto, it is possible to identify whether the user is watching or not in various ways.

In addition, the processor 20 may group the plurality of users 21, 22, and 23 and determine preferred characteristics of the group when all of the plurality of users 21, 22, and 23 watch the image 12. . As described above, the preference characteristics of the group may be determined based on the common preference characteristics of the plurality of users 21, 22, and 23, or may be determined based on the preference characteristics of a plurality of users.

In addition, the processor 20 identifies at least one user viewing the image 12 among the plurality of users 21, 22, and 23, and based on the identified at least one user's history information, the plurality of users 21 , 22, 23) group preference characteristics can be determined. As an example, when the first user 21 of the plurality of users 21, 22, and 23 is identified as watching the video 12, the processor 20 is based on the history information of the first user 21. Sport, which is the identified preferred characteristic, may be set as the group preferred characteristic.

As described above, according to the present embodiment, the processor 20 may determine the group preference characteristic based on the history information of any one user according to whether or not the plurality of users 21, 22, and 23 have viewed, so that a plurality of users It is possible to provide a recommended service that meets the viewing environment of (21, 22, 23).

9 illustrates another example of a control method of an electronic device for determining preference characteristics for a plurality of users in relation to operation S31 of FIG. 3. Each operation of FIG. 9 may be executed by the processor 20 of the electronic device 1.

As shown in FIG. 9, the processor 20 may identify the viewing immersion of each of the plurality of users (S91).

In addition, the processor 20 may determine the preference characteristics of the plurality of users based on the preference characteristics of the user whose viewing immersion degree identified among the plurality of users is equal to or greater than a set value (S92).

As described above, according to the control method of the present embodiment, the processor 20 may provide a recommendation service suitable for a viewing environment of a plurality of users.

FIG. 10 shows an example of adjusting preference characteristics of a user group in relation to operation S92 of FIG. 9. As illustrated in FIG. 10, the processor 20 may display a content image 12 in a viewing environment of a plurality of users 21, 22, and 23.

If all of the plurality of users (21, 22, 23) are watching the video (12) and the preference characteristics of the plurality of users (21, 22, 23) are all different, it is recommended based on the preference characteristics of a certain user. It can be a question of whether to provide a service. In consideration of this situation, the processor 20 identifies the viewing immersion level of each of the plurality of users, and the plurality of users 21, 22, and 23 The preference characteristics of the users 21, 22, and 23 may be determined.

Hereinafter, an example of determining the viewing immersion degree will be described with reference to FIGS. 11 and 12 together. First, referring to FIG. 11, the processor 20 may determine a viewing immersion according to a user's location, for example, a distance separated from the electronic device 1. As an example, the processor 20 provides a distance d1, d2, and a plurality of users 21, 22, and 23 in front of the electronic device 1 through the distance sensor 26 separated from the electronic device 1. d3) can be identified. However, since it is limited to the distance sensor 26 and the separation distance is not measured, the separation distance may be measured by various measurement methods.

Since it can be seen that a user located close to the electronic device 1 is more immersed in the image 12, the separation distance between the first user 21, the second user 22, and the third user 23 is 1m ( When measured as d1), 2m(d2) and 3m(d3), the processor 20 calculates the respective immersion, for example, 0.8. It can be set to 0.5 or 0.4. However, since the immersion degree set according to the separation distance is for convenience of description, it may be provided in various ways according to the design method.

In this case, the processor 20 sets the preference characteristic of the first user 21 having the highest degree of immersion among the immersion degree as a group preference characteristic for the plurality of users 21, 22, and 23, and the set group preference characteristic Accordingly, it is possible to provide a recommended service. For example, when the preference characteristic of the first user 21 is sports, the group preference characteristic is set as sports, and a recommendation service corresponding to the sports, for example, information on at least one sports channel, is used as the recommendation channel 13. Can provide.

Subsequently, referring to FIG. 12, the processor 20 may determine a viewing immersion according to a user's location, for example, a relative angle with respect to the electronic device 1. As an example, the processor 20 uses the orientation sensor to determine the angles a1 and a2 at which each of the plurality of users 21, 22, and 23 in front of the electronic device 1 is relative to the plane of the display 11 through the orientation sensor. , a3) can be identified. The smaller the relative angle from the plane of the electronic device 1 is, the more immersed the user is in the image 12, so the first user 21, the second user 22, and the third user 23 When the relative angles are measured at 30 degrees (a1), 45 degrees (a2) and 60 degrees (a3), the respective immersion degrees, for example, 0.8. It can be set to 0.5 or 0.4. However, since the immersion degree set according to the relative angle is for convenience of description, it may be provided in various ways according to the design method.

In this case, the processor 20 sets the preference characteristic of the first user 21 having the highest degree of immersion among the immersion degree as a group preference characteristic for the plurality of users 21, 22, and 23, and the set group preference characteristic Accordingly, it is possible to provide a recommended service. For example, when the preference characteristic of the first user 21 is sports, the group preference characteristic is set as sports, and a recommendation service corresponding to the sports, for example, information on at least one sports channel, is used as the recommendation channel 13. Can provide.

In identifying the viewing immersion, the processor 20 may consider a separation distance and a relative angle, respectively, but may consider it comprehensively. In addition, since it is not limited to a separation distance and a relative angle, viewing immersion can be identified in consideration of various factors. For example, the processor 20 may identify viewing immersion based on an action or voice related to the image 12. The processor 20 may identify a user's motion that imitates or imitates the motion displayed by the image 12 of the camera 28, and may set a high degree of immersion to the user of the motion. For example, the processor 20 may set the degree of immersion according to the similarity between the motion of the image 12 and the motion of the user. In addition, the processor 20 may set the degree of immersion based on the similarity between the voice output by the image 12 and the voice of the user received through the microphone 29.

Referring back to FIG. 10, the processor 20 sets the viewing immersion in consideration of the above-described various factors, and among them, a plurality of users 21 and 22 based on the preference characteristics of users whose viewing immersion is equal to or greater than a preset value. , 23) group preference characteristics can be determined. Here, the preset value may be determined in consideration of the number of users, etc., but hereinafter, it is assumed to be 0.6 for convenience of description.

As previously described with reference to FIGS. 11 and 12, if, if the viewing immersion of the first user 21 is greater than the preset value of 0.6, the viewing immersion of the remaining users 22 and 23 is a preset value of 0.6. Since it is smaller, the processor 20 identifies the first user 21 as an immersive user, and selects a preferred characteristic of the first user 21, for example, a sports group including a plurality of users 21, 22, and 23. It can be set as a preferred characteristic of. Accordingly, the processor 20 may provide a recommendation service based on a sport, which is a preferred characteristic of a group, in a viewing environment of a plurality of users 21, 22, and 23.

On the other hand, in the case of considering only the preference characteristics of the first user 21 having the highest viewing immersion, the processor 20 considers a case in which the preference characteristics of the remaining users 22 and 23 are excluded. For example, when the sum of the viewing immersion of the remaining users 22 and 23 is greater than the highest viewing immersion, the preference characteristics of the remaining users 22 and 23 may be set as the preference characteristics of the group. As shown in FIG. 10, the sum of the viewing immersion of the second user 22 and the third user 23 is 0.9, and the viewing immersion of the first user 21 is greater than 0.8, so that the first user ( Rather than setting the preference characteristic of 21) as the preference characteristic of the group, sports, which is the preference characteristic of the second user 22 and the third user 23, may be set as the preference characteristic of the group. However, since the method of setting the preference characteristics of the group based on the viewing immersion is not limited thereto, it may be provided in various ways according to the design method.

As described above, according to the present embodiment, the processor 20 measures the viewing immersion in consideration of various factors in the viewing environment of a plurality of users, and the plurality of users' preference characteristics identified based on the measured viewing immersion By providing a recommendation service for a group including users of, it is possible to provide a recommendation service suitable for a viewing environment of a plurality of users.

13 illustrates an example of identifying a preference characteristic of a user group based on a user characteristic according to an embodiment of the present invention. As illustrated in FIG. 13, the processor 20 may display a predetermined content image 12 in a viewing environment of a plurality of users 21, 22, and 23.

The processor 20 may provide information 131 about user preference characteristics corresponding to user characteristics. User characteristics may include, for example, the user's gender, age, name, place of residence, nationality, occupation, and the like. The processor 20 may identify user characteristics based on user information acquired through the camera 28 or the microphone 29. However, since it is not limited thereto, the processor 20 may identify user characteristics in various ways.

In other words, the user preference characteristic corresponding to the user characteristic is information on the preferred characteristic according to the user's gender, age, etc. For example, when the user preference characteristic corresponding to the user characteristic in their 20s/male is sports, in the 20s/ Men may mean primarily to prefer sports, and when the user preference characteristic corresponding to the user's 50s/male is news, it may mean that the 50s/males mainly prefer news. The information 131 on user preference characteristics corresponding to such user characteristics may be provided in the storage unit 25 or outside in the form of a lookup table.

The processor 20 may provide a recommendation service based on user preference characteristics identified based on user characteristics. Of course, even in the case of the viewing environment of a single first user 21, the processor 20 may determine a user characteristic of the first user 21, for example, a sport that is a preferred characteristic corresponding to a man in his twenties/male. As in the embodiment, even in a viewing environment of a plurality of users 21, 22, and 23, preference characteristics of a group may be set according to user characteristics of each user.

Referring to FIG. 13 in more detail, the processor 20 may identify the user characteristics of each of the plurality of users 21, 22, and 23 as 20s/male, 50s/male, 20s/female, It can be identified that the preferred characteristic corresponding to each user characteristic is sports, news, or drama. In this case, the processor 20 sets the preference characteristics of a plurality of users with common preference characteristics as the preference characteristics of the group as the preference characteristics of the group, or, as described above, the preference characteristics of the immersive user identified based on the viewing immersion. Can be set as the group's preferred characteristics. If the viewing immersion of the first user 21 is higher than the remaining users 22 and 23 or higher than a preset value, the processor 20 identifies the first user 21 as an immersive user, and One preference characteristic of the user 21 may be set as the preference characteristic of a group consisting of a plurality of users 21, 22, and 23.

As described above, according to the present embodiment, the processor 20 provides a recommendation service for a group including a plurality of users according to the preference characteristics of the group set based on the user characteristics of each user in the viewing environment of the plurality of users. , It is possible to provide a recommendation service suitable for the viewing environment of a plurality of users.

14 illustrates an example of adjusting a preference characteristic of a user group based on service history information with reference to FIG. 13. Previously, as described with reference to FIG. 13, it is assumed that the preferred characteristic of the first user 21 identified as an immersive user is set as the preferred characteristic of a group consisting of a plurality of users 21, 22, and 23.

In this case, the processor 20 may adjust the group preference characteristic based on the history information of the first user 21. That is, when the first user 21 uses the service through the network, the processor 20 acquires the network service history of the first user 21, and based on the acquired network service history, the first user 21 You can adjust your preferences. For example, when the first user 21 accesses a social network service and searches for news related to a drama, purchases an item worn by the protagonist in a drama, and performs a chat on the drama content, the processor 20 Based on the preference characteristics of the first user 21 may be adjusted from conventional sports to drama. In addition, the processor 20 may adjust the preference characteristics of the user group including the first user 21 from conventional sports to drama.

As described above, according to the present embodiment, the processor 20 adjusts the preference characteristics of the group based on the history information of the network service for the immersive user, thereby flexibly responding to the history information in the viewing environment of a plurality of users. Can provide the enemy recommendation service.

15 shows an example of the configuration of the processor of FIG. 3. As shown in FIG. 15, the processor 20 includes a user information acquisition unit 151, an immersive user identification unit 152, a user characteristic identification unit 153, a user group identification unit 154, and a service recommendation unit 156. ) Can be included. Hereinafter, the operation of each component under the viewing environment of a plurality of users 21, 22, and 23 will be described in detail. However, since the operation of each configuration is not limited to the viewing environment of the plurality of users 21, 22, and 23, a single user 2 may operate in a similar manner.

First, the user information acquisition unit 151 may acquire information on each of the plurality of users 21, 22, and 23. As an example, the user information acquisition unit 151 acquires images of the shapes of the plurality of users 21, 22, 23 in front of the electronic device 1 through the camera 28, and based on the acquired images. Thus, a plurality of users 21, 22, and 23 can be identified. As another example, the user information acquisition unit 151 may identify a plurality of users 21, 22, 23 based on spoken voice signals of a plurality of users 21, 22, and 23 received through the microphone 29. have. The user information acquisition unit 151 may identify a plurality of users 21, 22, and 23 based on, for example, the size, intensity, and frequency of the spoken voice signal.

In addition, the user information acquisition unit 151 may acquire not only information on the plurality of users 21, 22, and 23, but also surrounding environment information through the microphone 29. The user information acquisition unit 151 based on the sound introduced through the microphone 29, not only natural sounds such as wind, rain, thunder, etc., but also noises of children, sounds of falling or bumping objects, It is possible to identify the operation sound of home appliances such as vacuum cleaners.

Also, the user information acquisition unit 151 may acquire information on a connected or disconnected peripheral device. For example, identification information of a peripheral device connected to or disconnected from the electronic device 1, information on a port number connected to the peripheral device, and the like may be obtained.

The immersive user identification unit 152 may identify whether the identified plurality of users 21, 22, and 23 are immersed in the image 12. The immersion user identification unit 152 may identify whether the plurality of users 21, 22, and 23 are immersed based on information acquired through the distance sensor 26, the camera 28, and the microphone 29. The immersion user identification unit 152 may identify whether immersion is based on, for example, positions, actions, and voices of the plurality of users 21, 22, and 23. For example, the immersive user identification unit 152 identifies the locations of a plurality of users 21, 22, and 23 based on the voice signal received through the microphone 29, and immerses the user whose location is fixed for a predetermined time. Can be identified as a user.

The user characteristic identification unit 153 may identify user characteristics for the identified plurality of users 21, 22, and 23. User characteristics may include age, gender, and the like, as described in connection with FIG. 13. The user characteristic identification unit 153 may identify user characteristics based on information on a plurality of users 21, 22, and 23 acquired through the camera 28 and the microphone 29. The user characteristic identification unit 153 may, for example, identify whether the plurality of users 21, 22, and 23 are in their 20s/males or 50s/males.

The user group identification unit 154 may group at least one immersive user among the plurality of users 21, 22, and 23, or group at least one user with common user characteristics. However, since it is not limited thereto, the user group identification unit 154 may perform grouping in consideration of both immersive user availability and user characteristics, and may perform grouping in consideration of other characteristics.

The service recommendation unit 156 may provide a recommendation service based on preference characteristics of each grouped user group. Since each user group is composed of, for example, an immersive user or a user having a common user characteristic, the service recommendation unit 156 may provide a recommendation service corresponding to the user's preference characteristic included in the user group.

However, the processor 20 may exclude at least one of the above-described configurations, and may include at least one of the configurations as necessary. For example, the processor 20 may further include a history information analysis unit 155, a group management unit 157, and the like.

The history information analysis unit 155 may obtain history information on a service used by a plurality of users 21, 22, and 23 through a network. For example, the history information analysis unit 155 may obtain history information of a plurality of users 21, 22, and 23, for example, an immersive user activity through a social network service. The history information analysis unit 155 may provide the acquired history information to the user group identification unit 154, and the user group identification unit 154 includes, for example, the immersive user based on the history information of the immersive user. User group preferences can be adjusted When the preference characteristics of the user group are adjusted by the user group identification unit 154, the service recommendation unit 156 may provide a recommendation service based on the adjusted group preference characteristics.

Meanwhile, the group management unit 157 may identify a user grouped by the user group identification unit 154, for example, among immersive users included in the immersive user group, who have lost their qualifications to be included in the immersive user group. For example, when the preferred characteristic of the immersive user group is sports, when a certain immersive user accesses a social network service not related to sports while the sports image 12 is displayed, the group management unit 157 The immersive user can be excluded from the immersive user group. On the other hand, even if previously identified as a non-immersive user, the group management unit 157 may include the corresponding non-immersive user in the immersive user group based on the history information corresponding to the preference characteristic of the immersive user group.

Various embodiments disclosed in this document may be implemented as software including one or more instructions stored in a storage medium readable by a machine such as the electronic device 1. As an example, the processor 10 of the electronic device 1 may call at least one command among one or more commands stored from a storage medium and execute it. This makes it possible for a device, such as the electronic device 1, to be operated to perform at least one function in accordance with the called at least one command. The one or more instructions may include code generated by a compiler or code executable by an interpreter. A storage medium that can be read by a device may be provided in the form of a non-transitory storage medium. Here,'non-transient' only means that the storage medium is a tangible device and does not contain a signal (e.g., electromagnetic wave), and this term is used when data is semi-permanently stored in the storage medium and temporarily stored. It does not distinguish between cases.

For example, a method according to various embodiments disclosed in the present document may be included in a computer program product and provided. Computer program products can be traded between sellers and buyers as commodities. The computer program product is distributed in the form of a device-readable storage medium (e.g., CD-ROM), or through an application store (e.g., Play StoreTM) or between two user devices (e.g., smartphones). It can be distributed directly, online (eg, downloaded or uploaded). In the case of online distribution, at least some of the computer program products may be temporarily stored or temporarily generated in a storage medium that can be read by a device such as a server of a manufacturer, a server of an application store, or a memory of a relay server.

As described above, the present invention has been described in detail through preferred embodiments, but the present invention is not limited thereto and may be variously implemented within the scope of the claims.

1: electronics
2: user
5: external device

Claims (20)

In the electronic device,
Recommends a service related to the content based on the user's preference characteristic for the content,
Adjusting the user's preference characteristics with respect to the content based on the history information of the service used by the user through the network
Electronic device including a processor. The method of claim 1,
Further comprising a display,
The processor,
Controlling the display to display an image of the service through the network,
An electronic device that acquires the history information through character recognition of the image of the service. The method of claim 1,
The history information includes information on content provided to the user through the service. The method of claim 1,
The history information includes history information using a service of a social network to which the user belongs. The method of claim 1,
The history information is an electronic device including history information of the user using the service using an external device. The method of claim 1,
The history information includes information on the surrounding environment of the electronic device. The method of claim 1,
The processor, when it is identified that a plurality of users including the user is watching, determines preference characteristics of the plurality of users based on the user's history information. The method of claim 7,
The processor is an electronic device configured to determine preference characteristics of the plurality of users based on preference characteristics of users whose viewing immersion is equal to or greater than a set value among the plurality of users. The method of claim 1,
The processor,
Identifying a user group corresponding to the user characteristic of the user from among a plurality of user groups prepared for each user characteristic,
An electronic device that adjusts a preference characteristic of the identified user group based on the user's history information. The method of claim 9,
The processor is an electronic device configured to adjust a preference characteristic of a user group corresponding to the user based on user history information having a viewing immersion degree of each of a plurality of users included in the plurality of user groups equal to or greater than a set value. In the control method of an electronic device,
Recommending a service for the content based on a user's preference for the content; And
Adjusting the user's preference characteristics with respect to the content based on the history information of the service used by the user through the network
Control method of an electronic device comprising a. The method of claim 11,
Adjusting the user's preference characteristics,
Displaying an image of the service through the network; And
And acquiring the history information through character recognition of the service image. The method of claim 11,
The history information includes information on content provided to the user through the service. The method of claim 11,
The history information includes history information using a service of a social network to which the user belongs. The method of claim 11,
The history information includes history information of the user using the service using an external device. The method of claim 11,
The history information includes information on the surrounding environment of the electronic device. The method of claim 11,
The adjusting of the preference characteristics includes determining the preference characteristics of the plurality of users based on the user's history information when a plurality of users including the user are identified as being watched. Way. The method of claim 17,
The determining of the preference characteristics of the plurality of users may include determining the preference characteristics of the plurality of users based on the preference characteristics of a user whose viewing immersion is equal to or greater than a set value among the plurality of users. Way. The method of claim 11,
Adjusting the preferred characteristics,
Identifying a user group corresponding to the user characteristic of the user from among a plurality of user groups provided for each user characteristic; And
And adjusting a preference characteristic of the identified user group based on the user's history information. A computer-readable code, in a recording medium storing a computer program including a code for performing a method for controlling an electronic device, wherein the method for controlling the electronic device comprises:
Recommending a service for the content based on a user's preference for the content; And
Adjusting the user's preference characteristics with respect to the content based on the history information of the service used by the user through the network
A recording medium in which a computer-readable program is recorded, comprising: a.

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