Electronic device for providing summary content and operation method thereof

Abstract

Disclosed are an electronic device for providing summary content and an operation method thereof. The electronic device may comprise at least one processor including a processing circuit. The electronic device may comprise a memory including one or more storage media for storing instructions. The instructions, when executed individually or collectively by the at least one processor, may cause the electronic device to generate summary text from target content, to be shared with another user, through a summary function, determine an image corresponding to the summary text, and share the summary content, composed of the summary text and the image corresponding to the summary text, with the other user.

Description

Electronic device providing summary content and method of operation thereof

[0001] Embodiments of the present disclosure relate to an electronic device providing summary content and a method of operating the same.

[0002] Web developers can design HTML (Hypertext Markup Language) for webpages using the Open Graph standard and define metadata for specific items within the HTML. A user terminal that receives a URL (Uniform Resource Locator) for a webpage designed with HTML can access that URL, crawl the metadata defined for that webpage, and provide it to the user.

[0003] However, if the webpage corresponding to the URL received by the user terminal is not a webpage according to the Open Graph standard or is a content in a different form than a webpage, there is a problem in that the information corresponding to the URL cannot be previewed.

[0004] The above information may be provided as background art to aid in understanding the present disclosure. No claim or determination is made as to whether any of the above is applicable as prior art related to the present disclosure.

[0005] According to one embodiment, an electronic device may include at least one processor comprising a processing circuit. The electronic device may include a memory comprising one or more storage media storing instructions. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to generate a summary text from target content to be shared with another user through a summary function, determine an image corresponding to the summary text, and share the summary content comprised of the summary text and the image corresponding to the summary text with the other user.

[0006] According to one embodiment, an electronic device may include at least one processor comprising a processing circuit. The electronic device may include a memory comprising one or more storage media storing instructions. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to receive summary content including summary text for target content through a specific application, identify an image corresponding to the summary text within the summary content, and display the identified image on a display together with the summary text.

[0007] According to one embodiment, the operating method of an electronic device may generate a summary text from target content to be shared with other users through a summary function. The operating method of the electronic device may determine an image corresponding to the summary text. The operating method of the electronic device may share the summary content, in which the summary text and the image corresponding to the summary text are encoded together, with other users.

[0008] According to one embodiment, instructions recorded on a computer-readable recording medium, when executed by one or more processors, can cause an electronic device to perform operations of a method of operating.

[0009] FIG. 1 is a block diagram of an electronic device within a network environment according to one embodiment.

[0010] Figure 2 is a drawing for explaining the open graph standard to be utilized in the present invention.

[0011] FIG. 3 is a diagram for explaining an operation in which a transmitting electronic device according to one embodiment generates summary content through an image generated in response to summary text and shares the generated summary content with other users.

[0012] FIG. 4 is a diagram for explaining an operation of a transmitting electronic device according to one embodiment of the present invention to create summary content using metadata of an image included in a web page and share it with other users.

[0013] FIG. 5 is a diagram illustrating an example of a transmitting electronic device sharing a summarized web page according to one embodiment.

[0014] FIG. 6 is a diagram for explaining an operation of a receiving electronic device according to one embodiment of the present invention to display received summary content on the execution screen of a communication app.

[0015] FIG. 7 is a diagram for explaining an operation of a receiving electronic device according to one embodiment of the present invention to display a received URL on the execution screen of a communication app.

[0016] FIG. 8 is a diagram illustrating an operation of a receiving electronic device according to one embodiment of the present invention to display received text-based content on the execution screen of a communication app.

[0017] FIG. 9 is a diagram for explaining an operation of a transmitting electronic device sharing text content according to one embodiment.

[0018] FIG. 10 is a diagram for explaining an operation of a receiving electronic device according to one embodiment of the present invention to display shared text content on the execution screen of a communication app.

[0019] FIG. 11 is a diagram for explaining an operation in which a transmitting electronic device and a receiving electronic device share URL information according to one embodiment.

[0020] FIG. 12 is a diagram for explaining an operation in which an additional comment is created and displayed when URL information is shared between a transmitting electronic device and a receiving electronic device according to one embodiment.

[0021] FIG. 13 is a diagram for explaining an operation of recommending an additional comment when URL information is shared between a transmitting electronic device and a receiving electronic device according to one embodiment.

[0022] FIG. 14 is a diagram for explaining an operation in which a transmitting electronic device and a receiving electronic device share URL information according to one embodiment.

[0023] FIG. 15 is a diagram for explaining an operation of a receiving electronic device according to one embodiment of the present invention to generate and display an additional comment corresponding to URL information.

[0024] FIG. 16 is a diagram illustrating a method for sharing summary content with other users according to one embodiment.

[0025] Hereinafter, embodiments will be described in detail with reference to the attached drawings. In the description with reference to the attached drawings, identical components are assigned the same reference numerals regardless of the drawing numbers, and redundant descriptions thereof will be omitted.

[0026] FIG. 1 is a block diagram of an electronic device (101) within a network environment (100) according to various embodiments. Referring to FIG. 1, in the network environment (100), the electronic device (101) may communicate with an electronic device (102) via a first network (198) (e.g., a short-range wireless communication network), or may communicate with at least one of an electronic device (104) or a server (108) via a second network (199) (e.g., a long-range wireless communication network). According to one embodiment, the electronic device (101) may communicate with the electronic device (104) via the server (108). According to one embodiment, the electronic device (101) may include a processor (120), a memory (130), an input module (150), an audio output module (155), a display module (160), an audio module (170), a sensor module (176), an interface (177), a connection terminal (178), a haptic module (179), a camera module (180), a power management module (188), a battery (189), a communication module (190), a subscriber identification module (196), or an antenna module (197). In some embodiments, the electronic device (101) may omit at least one of these components (e.g., the connection terminal (178)), or may have one or more other components added. In some embodiments, some of these components (e.g., the sensor module (176), the camera module (180), or the antenna module (197)) may be integrated into one component (e.g., the display module (160)).

[0027] The processor (120) may, for example, execute software (e.g., a program (140)) to control at least one other component (e.g., a hardware or software component) of the electronic device (101) connected to the processor (120) and perform various data processing or operations. According to one embodiment, as at least a part of the data processing or operations, the processor (120) may store commands or data received from other components (e.g., a sensor module (176) or a communication module (190)) in a volatile memory (132), process the commands or data stored in the volatile memory (132), and store result data in a non-volatile memory (134). The processor (120) may also be implemented as a system on chip (SoC) or an integrated circuit (IC) that performs processing. The processor (120) may include one or more processors, and the operations of the electronic device (101) described in the present disclosure may be performed by a single processor or by a combination of multiple processors. When the operations of the electronic device (101) are performed by a combination of multiple processors, any one processor included in the combination of processors may perform some of the operations of the electronic device (101). For example, the processor (120) may correspond to multiple processors that collectively perform a plurality of operations by dividing them among the processors.

[0028] According to one embodiment, the processor (120) may be implemented as a circuit (e.g., a processing circuit) such as a system on chip (SoC) or an integrated circuit (IC). The processor (120) may include one or more processors. For example, the processor (120) may include a combination of one or more processors such as a CPU, a GPU, an MPU, an AP, and a CP.

[0029] According to one embodiment, the processor (120) may include a main processor (121) (e.g., a central processing unit or an application processor) or an auxiliary processor (123) (e.g., a graphics processing unit, a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor) that can operate independently or together with the main processor (121). For example, when the electronic device (101) includes the main processor (121) and the auxiliary processor (123), the auxiliary processor (123) may be configured to use less power than the main processor (121) or to be specialized for a given function. The auxiliary processor (123) may be implemented separately from the main processor (121) or as a part thereof.

[0030] The auxiliary processor (123) may control at least a portion of functions or states associated with at least one component (e.g., a display module (160), a sensor module (176), or a communication module (190)) of the electronic device (101), for example, on behalf of the main processor (121) while the main processor (121) is in an inactive (e.g., sleep) state, or together with the main processor (121) while the main processor (121) is in an active (e.g., application execution) state. In one embodiment, the auxiliary processor (123) (e.g., an image signal processor or a communication processor) may be implemented as a part of another functionally related component (e.g., a camera module (180) or a communication module (190)). In one embodiment, the auxiliary processor (123) (e.g., a neural network processing unit) may include a hardware structure specialized for processing artificial intelligence models. The artificial intelligence models may be generated through machine learning. This learning can be performed, for example, on the electronic device (101) itself where the artificial intelligence model is executed, or can be performed through a separate server (e.g., server (108)). The learning algorithm can include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but is not limited to the examples described above. The artificial intelligence model can include multiple artificial neural network layers.The artificial neural network may be one of a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), a deep Q-network, or a combination of two or more of the above, but is not limited to the examples described above. In addition to, or alternatively to, a hardware structure, an artificial intelligence model may include a software structure.

[0031] The memory (130) can store various data used by at least one component (e.g., the processor (120) or the sensor module (176)) of the electronic device (101). The data can include, for example, software (e.g., the program (140)) and input data or output data for commands related thereto. The memory (130) can include a volatile memory (132) or a non-volatile memory (134). The memory (130) can store at least one instruction executable by the processor (120). The memory (130) can include one or more memories, and instructions for controlling the processor (120) to perform operations of the electronic device (101) described in the present disclosure can be stored in one memory or can be divided and stored in multiple memories.

[0032] The program (140) may be stored as software in the memory (130) and may include, for example, an operating system (142), middleware (144), or an application (146).

[0033] The input module (150) can receive commands or data to be used in a component of the electronic device (101) (e.g., a processor (120)) from an external source (e.g., a user) of the electronic device (101). The input module (150) can include, for example, a microphone, a mouse, a keyboard, a key (e.g., a button), or a digital pen (e.g., a stylus pen).

[0034] The audio output module (155) can output audio signals to the outside of the electronic device (101). The audio output module (155) can include, for example, a speaker or a receiver. The speaker can be used for general purposes, such as multimedia playback or recording playback. The receiver can be used to receive incoming calls. In one embodiment, the receiver can be implemented separately from the speaker or as part of the speaker.

[0035] The display module (160) can visually provide information to an external device (e.g., a user) of the electronic device (101). The display module (160) may include, for example, a display, a holographic device, or a projector, and a control circuit for controlling the device. According to one embodiment, the display module (160) may include a touch sensor configured to detect a touch, or a pressure sensor configured to measure the intensity of a force generated by the touch. The display module (160) may be implemented with an illustrative foldable structure and / or a rollable structure. For example, the size of the display screen of the display module (160) may be reduced when folded, and may be expanded when unfolded.

[0036] The audio module (170) can convert sound into an electrical signal, or vice versa, convert an electrical signal into sound. According to one embodiment, the audio module (170) can acquire sound through the input module (150), output sound through the sound output module (155), or an external electronic device (e.g., electronic device (102)) (e.g., speaker or headphone) directly or wirelessly connected to the electronic device (101).

[0037] The sensor module (176) can detect the operating status (e.g., power or temperature) of the electronic device (101) or the external environmental status (e.g., user status) and generate an electrical signal or data value corresponding to the detected status. According to one embodiment, the sensor module (176) can include, for example, a gesture sensor, a gyro sensor, a barometric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biometric sensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0038] The interface (177) may support one or more designated protocols that may be used to directly or wirelessly connect the electronic device (101) with an external electronic device (e.g., the electronic device (102)). In one embodiment, the interface (177) may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0039] The connection terminal (178) may include a connector that allows the electronic device (101) to be physically connected to an external electronic device (e.g., electronic device (102)). According to one embodiment, the connection terminal (178) may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0040] A haptic module (179) can convert electrical signals into mechanical stimuli (e.g., vibration or movement) or electrical stimuli that a user can perceive through tactile or kinesthetic sensations. In one embodiment, the haptic module (179) can include, for example, a motor, a piezoelectric element, or an electrical stimulation device.

[0041] The camera module (180) can capture still images and videos. According to one embodiment, the camera module (180) may include one or more lenses, image sensors, image signal processors, or flashes.

[0042] The power management module (188) can manage power supplied to the electronic device (101). According to one embodiment, the power management module (188) can be implemented, for example, as at least a part of a power management integrated circuit (PMIC).

[0043] A battery (189) may power at least one component of the electronic device (101). In one embodiment, the battery (189) may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0044] The communication module (190) may support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between the electronic device (101) and an external electronic device (e.g., electronic device (102), electronic device (104), or server (108)), and the performance of communication through the established communication channel. The communication module (190) may operate independently from the processor (120) (e.g., application processor) and may include one or more communication processors that support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication module (190) may include a wireless communication module (192) (e.g., a Wi-Fi communication module, a cellular communication module, a short-range wireless communication module, or a global navigation satellite system (GNSS) communication module) or a wired communication module (194) (e.g., a local area network (LAN) communication module, or a power line communication module). Among these communication modules, the corresponding communication module can communicate with an external electronic device (104) via a first network (198) (e.g., a short-range communication network such as Bluetooth, wireless fidelity (WiFi) direct, or infrared data association (IrDA)) or a second network (199) (e.g., a long-range communication network such as a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network (e.g., a LAN or WAN)). These various types of communication modules can be integrated into a single component (e.g., a single chip) or implemented as multiple separate components (e.g., multiple chips). The wireless communication module (192) can verify or authenticate the electronic device (101) within a communication network such as the first network (198) or the second network (199) by using subscriber information (e.g., an international mobile subscriber identity (IMSI)) stored in the subscriber identification module (196).

[0045] The wireless communication module (192) can support 5G networks and next-generation communication technologies following the 4G network, such as NR access technology (new radio access technology). The NR access technology can support high-speed transmission of high-capacity data (eMBB (enhanced mobile broadband)), minimization of terminal power and connection of multiple terminals (mMTC (massive machine type communications)), or high reliability and low latency (URLLC (ultra-reliable and low-latency communications)). The wireless communication module (192) can support, for example, a high-frequency band (e.g., mmWave band) to achieve a high data transmission rate. The wireless communication module (192) can support various technologies for securing performance in a high-frequency band, such as beamforming, massive multiple-input and multiple-output (MIMO), full dimensional MIMO (FD-MIMO), array antenna, analog beam-forming, or large scale antenna. The wireless communication module (192) can support various requirements specified in the electronic device (101), an external electronic device (e.g., the electronic device (104)), or a network system (e.g., the second network (199)). According to one embodiment, the wireless communication module (192) can support a peak data rate (e.g., 20 Gbps or more) for eMBB realization, a loss coverage (e.g., 164 dB or less) for mMTC realization, or a U-plane latency (e.g., 0.5 ms or less for downlink (DL) and uplink (UL), or 1 ms or less for round trip) for URLLC realization.

[0046] The antenna module (197) can transmit or receive signals or power to or from an external device (e.g., an external electronic device). In one embodiment, the antenna module (197) may include an antenna including a radiator formed of a conductor or a conductive pattern formed on a substrate (e.g., a PCB). In one embodiment, the antenna module (197) may include a plurality of antennas (e.g., an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network, such as the first network (198) or the second network (199), may be selected from the plurality of antennas by, for example, the communication module (190). A signal or power may be transmitted or received between the communication module (190) and an external electronic device through the selected at least one antenna. In some embodiments, in addition to the radiator, another component (e.g., a radio frequency integrated circuit (RFIC)) may be additionally formed as a part of the antenna module (197).

[0047] According to various embodiments, the antenna module (197) may form a mmWave antenna module. According to one embodiment, the mmWave antenna module may include a printed circuit board, an RFIC disposed on or adjacent a first side (e.g., a bottom side) of the printed circuit board and capable of supporting a designated high frequency band (e.g., a mmWave band), and a plurality of antennas (e.g., an array antenna) disposed on or adjacent a second side (e.g., a top side or a side side) of the printed circuit board and capable of transmitting or receiving signals in the designated high frequency band.

[0048] At least some of the above components can be interconnected and exchange signals (e.g., commands or data) with each other via a communication method between peripheral devices (e.g., a bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)).

[0049] According to one embodiment, commands or data may be transmitted or received between the electronic device (101) and an external electronic device (104) via a server (108) connected to a second network (199). Each of the external electronic devices (102 or 104) may be the same or a different type of device as the electronic device (101). According to one embodiment, all or part of the operations executed in the electronic device (101) may be executed in one or more of the external electronic devices (102, 104, or 108). For example, when the electronic device (101) is to perform a certain function or service automatically or in response to a request from a user or another device, the electronic device (101) may, instead of or in addition to executing the function or service itself, request one or more external electronic devices to perform the function or at least a part of the service. One or more external electronic devices that receive the request may execute at least a portion of the requested function or service, or an additional function or service related to the request, and transmit the result of the execution to the electronic device (101). The electronic device (101) may process the result as is or additionally and provide it as at least a portion of a response to the request. For this purpose, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used, for example. The electronic device (101) may provide an ultra-low latency service by using distributed computing or mobile edge computing, for example. In another embodiment, the external electronic device (104) may include an Internet of Things (IoT) device. The server (108) may be an intelligent server utilizing machine learning and / or a neural network. According to one embodiment, the external electronic device (104) or the server (108) may be included in the second network (199).The electronic device (101) can be applied to intelligent services (e.g., smart home, smart city, smart car, or healthcare) based on 5G communication technology and IoT-related technology.

[0050] Electronic devices according to various embodiments disclosed in this disclosure may take various forms. Electronic devices may include, for example, portable communication devices (e.g., smartphones), computer devices, portable multimedia devices, portable medical devices, cameras, wearable devices, or home appliances. Electronic devices according to embodiments of this disclosure are not limited to the aforementioned devices.

[0051] The various embodiments of the present disclosure and the terminology used therein are not intended to limit the technical features described in the present disclosure to specific embodiments, but should be understood to include various modifications, equivalents, or substitutes of the embodiments. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of the items, unless the context clearly indicates otherwise. In the present disclosure, each of the phrases "A or B," "at least one of A and B," "at least one of A or B," "A, B, or C," "at least one of A, B, and C," and "at least one of A, B, or C" can include any one of the items listed together in the corresponding phrase among the phrases, or all possible combinations thereof. Terms such as "first," "second," or "first" or "second" may be used merely to distinguish one component from another, and do not limit the components in any other respect (e.g., importance or order). When a component (e.g., a first component) is referred to as "coupled" or "connected" to another component (e.g., a second component), with or without the terms "functionally" or "communicatively," it means that the component can be connected to the other component directly (e.g., wired), wirelessly, or through a third component.

[0052] The term "module" used in various embodiments of the present disclosure may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit. A module may be an integral component, or a minimum unit or part of such a component that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0053] Various embodiments of the present disclosure may be implemented as software (e.g., a program (140)) including one or more instructions stored in a storage medium (e.g., an internal memory (136) or an external memory (138)) readable by a machine (e.g., an electronic device (101) of FIG. 1). For example, a processor (e.g., a processor (120)) of a machine (e.g., an electronic device (101)) may call at least one command among the one or more instructions stored from the storage medium and execute it. This enables the machine to operate to perform at least one function according to the at least one called instruction. The one or more instructions may include code generated by a compiler or code executable by an interpreter. The machine-readable storage medium may be provided in the form of a non-transitory storage medium. Here, 'non-transitory' simply means that the storage medium is a tangible device and does not contain signals (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently or temporarily on the storage medium.

[0054] According to one embodiment, the method according to various embodiments disclosed in the present disclosure may be provided as included in a computer program product. The computer program product may be traded as a commodity between a seller and a buyer. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., compact disc read-only memory (CD-ROM)), or may be distributed online (e.g., downloaded or uploaded) via an application store (e.g., Play Store™) or directly between two user devices (e.g., smart phones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily generated in a machine-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0055] According to various embodiments, each component (e.g., a module or a program) of the above-described components may include one or more entities, and some of the entities may be separated and placed in other components. According to various embodiments, one or more components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (e.g., a module or a program) may be integrated into a single component. In such a case, the integrated component may perform one or more functions of each of the plurality of components identically or similarly to those performed by the corresponding component among the plurality of components prior to the integration. According to various embodiments, the operations performed by a module, program, or other component may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

[0056] According to one embodiment, the electronic device (101) may include at least one processor (120) including a processing circuit. The electronic device (101) may include a memory (130) including one or more storage media storing instructions. The instructions, when individually or collectively executed by the at least one processor (120), may cause the electronic device (101) to generate a summary text from target content to be shared with another user through a summary function, determine an image corresponding to the summary text, and share the summary content in which the summary text and the image corresponding to the summary text are encoded together with the other user.

[0057] According to one embodiment, the instructions, when individually or collectively executed by at least one processor (120), may cause the electronic device (101) to prompt a generative artificial intelligence (AI) model to generate an image corresponding to the summary text by inputting summary text as a prompt if no image exists in the target content.

[0058] According to one embodiment, the instructions, when individually or collectively executed by at least one processor (120), may cause the electronic device (101) to identify a correlation between captioning information and summary text for each of the plurality of images when there are multiple images in the target content, and to determine an image corresponding to the summary text by comparing the identified correlation with a preset criterion.

[0059] According to one embodiment, the instructions, when individually or collectively executed by at least one processor (120), may cause the electronic device (101) to determine an image having the highest correlation among the images identified as having a correlation greater than a preset criterion as the image corresponding to the summary text.

[0060] According to one embodiment, the instructions, when individually or collectively executed by at least one processor (120), may cause the electronic device (101) to generate an image corresponding to the summary text in response to inputting the image having the highest correlation among the images for which the correlation is less than the preset criterion and the summary text into the generative AI model, when the identified correlation for each of the plurality of images is less than the preset criterion.

[0061] According to one embodiment, the instructions, when individually or collectively executed by at least one processor (120), may cause the electronic device (101) to identify a length of a summary text generated from target content, and, if the length of the summary text is greater than or equal to a preset standard, crawl an image included in the target content or generate an image corresponding to the summary text.

[0062] According to one embodiment, the instructions, when individually or collectively executed by at least one processor (120), may cause the electronic device (101) to generate personalized summary text for another user based on past conversation history with the other user.

[0063] According to one embodiment, the summary text generated from the target content and the images determined in response to the summary text may have different lengths of the summary text or the number of the images depending on the sharing means or sharing target of the summary content.

[0064] According to one embodiment, the instructions, when individually or collectively executed by at least one processor (120), may cause the electronic device (101) to generate summary content by encoding summary text and an image corresponding to the summary text as metadata of an open graph, and to share the generated summary content with other users.

[0065] According to one embodiment, the electronic device (101) may include at least one processor (120) including a processing circuit. The electronic device (101) may include a memory (130) including one or more storage media for storing instructions. The instructions, when individually or collectively executed by the at least one processor (120), may cause the electronic device (101) to receive summary content including summary text for target content through a specific application, identify an image corresponding to the summary text within the summary content, and display the identified image on a display together with the summary text.

[0066] According to one embodiment, the instructions, when individually or collectively executed by at least one processor (120), may cause the electronic device (101) to input the summary text as a prompt to a generative AI model to generate an image corresponding to the summary text, if no image corresponding to the summary text exists within the summary content.

[0067] According to one embodiment, the instructions, when individually or collectively executed by at least one processor (120), may cause the electronic device (101) to generate an image corresponding to the summary text included in the summary content if the length of the summary text is greater than or equal to a preset standard.

[0068] According to one embodiment, the instructions, when individually or collectively executed by at least one processor (120), may cause the electronic device (101) to generate a summary text from the target content corresponding to the URL (uniform resource locator) information when the URL information for the target content is received through a specific application through a summary function.

[0069] According to one embodiment, the instructions, when individually or collectively executed by at least one processor (120), may cause the electronic device (101) to generate a personalized summary text for a user based on a past conversation history with another user to whom the summary content is transmitted.

[0070] Figure 2 is a drawing for explaining the open graph standard to be utilized in the present invention.

[0071] Web creators can define metadata for specific items on HTML using the Open Graph standard. For example, referring to Figure 2, metadata defined by a web creator using the Open Graph standard may include at least one of the following: a website title (og:title), a website type (og:type), a representative image (og:image), a website URL (og:url), and a website description (og:description). However, the types of metadata described above are merely examples and are not limited to the examples above.

[0072] Meanwhile, when a link (e.g., URL) to a specific webpage for which metadata is defined through the Open Graph standard is displayed on a communication app by one or more processors (e.g., processor (120) of FIG. 1) included in an electronic device (e.g., electronic device (101) of FIG. 1), the one or more processors may access the HTML of the specific webpage through a crawler to collect metadata defined through the Open Graph standard. The one or more processors may display the collected metadata together with the link to the specific webpage on the communication app, thereby providing a preview so that other metadata of the specific webpage can be recognized without accessing the specific webpage through the link displayed as in FIG. 2.

[0073] FIG. 3 is a diagram illustrating an operation of a transmitting electronic device according to one embodiment of the present invention to generate summary content using an image generated in response to summary text and share the generated summary content with other users. In one embodiment, at least one of the operations in FIG. 3 may be performed simultaneously or in parallel with other operations, and the order between the operations may be changed. In addition, at least one of the operations may be omitted, and other operations may be additionally performed. The operations illustrated in FIG. 3 may be performed by at least one component of a transmitting electronic device (e.g., the electronic device (101) of FIG. 1 ).

[0074] According to one embodiment, one or more processors included in the transmitting electronic device may, in operation (310), identify a webpage loaded via a browser. In this case, the identified webpage may be a webpage to be shared with other users.

[0075] In operation (320), one or more processors may obtain a summary text summarizing the content of the webpage in response to inputting the loaded webpage into an artificial intelligence model. For example, the artificial intelligence model that outputs the summary text from the loaded webpage may be a large language model (LLM) such as a generative pre-trained transformer (GPT) or bidirectional encoder representations from transformers (BERT). However, the type of such artificial intelligence model is only one example and is not limited to the above example. The artificial intelligence model that outputs the summary text may be implemented in an on-device form within the transmitting electronic device or implemented on an external server.

[0076] In operation (330), one or more processors may generate an image corresponding to the summary text in response to inputting the summary text for the acquired webpage as a prompt to a generative artificial intelligence (AI) model. At this time, the image corresponding to the summary text may be generated when an operation of transmitting the summary text to another user occurs on the transmitting electronic device, or when the summary text is acquired through the artificial intelligence model. Similarly, the generative AI model that generates the image corresponding to the summary text may be implemented in an on-device form within the transmitting electronic device, or may be implemented on an external server.

[0077] In operation (340), one or more processors may generate summary content by encoding the image generated in operation (330) in the metadata format of the Open Graph standard and packaging it together with the summary text obtained in operation (320). However, according to one embodiment, the one or more processors may not perform packaging of the image encoded in the metadata format of the Open Graph standard and the summary text, but may share with other users an image generated based on text, an image related to a webpage that performed the summary, a link to the image, or an image and a summary text received from a link to the image. In this case, operation (340) may be omitted.

[0078] In operation (350), one or more processors may share the generated summary content with other users via a communication app of the transmitting electronic device. For example, the communication app may include a short message service (SMS), an additional service of a mobile phone, or a chat app such as KakaoTalk or Telegram. However, the types of communication apps are merely examples and are not limited to the above examples.

[0079] Meanwhile, the summary content may vary in the degree of summary text and the form of the image depending on the user characteristics, such as age, gender, and areas of interest, of the other users who have shared the summary content. In one embodiment, an AI model that outputs the summary text may increase the length of the summary text for a more detailed explanation when the other users who have shared the summary content are younger. Alternatively, a generative AI model that generates an image corresponding to the summary text may select a learning database for generating an animated image rather than a photorealistic image to provide a higher level of familiarity when the other users who have shared the summary content are younger.

[0080] In one embodiment, an AI model that outputs a summary text may reduce the length of the summary text for a more concise explanation when other users' areas of interest are similar to the content in question. Alternatively, an AI model that generates an image corresponding to the summary text may select a learning database to generate realistic images for more realistic and professional information delivery when other users' areas of interest are similar to the content in question.

[0081] Additionally, the summary content may vary in terms of the degree of summary text and the number of images depending on the type of target application providing the summary content. In one embodiment, an AI model that outputs summary text may reduce the length of the summary text to provide more intuitive information when the target application is a short message service (SMS) or a chat app. Alternatively, a generative AI model that generates images corresponding to the summary text may reduce the number of generated images by generating images corresponding to the shortened summary text when the target application is a short message service (SMS) or a chat app.

[0082] In one embodiment, an AI model that outputs summary text may increase the length of the summary text to provide richer information when the target application is document scraping or printer output. Alternatively, a generative AI model that generates images corresponding to the summary text may increase the number of generated images by generating images corresponding to the longer summary text when the target application is document scraping or printer output.

[0083] Meanwhile, the example of FIG. 3 provides a configuration in which one or more processors obtain a summary text through an artificial intelligence model, generate an image corresponding to the summary text obtained through a generative AI model, and transmit it to another user. However, this is merely an example and is not limited to the above example. In other words, one or more processors may obtain a plain text before the summary, rather than the summary text, and generate an image corresponding to the plain text obtained through a generative AI model and transmit it to another user.

[0084] FIG. 4 is a diagram illustrating an operation of a transmitting electronic device according to one embodiment of the present invention to generate summary content using metadata of an image included in a webpage and share the summary content with other users. In one embodiment, at least one of the operations in FIG. 4 may be performed simultaneously or in parallel with other operations, and the order between the operations may be changed. In addition, at least one of the operations may be omitted, and other operations may be additionally performed. The operations illustrated in FIG. 4 may be performed by at least one component of a transmitting electronic device (e.g., the electronic device (101) of FIG. 1 ).

[0085] According to one embodiment, one or more processors included in the transmitting electronic device may, in operation (410), identify a webpage loaded via a browser. In this case, the identified webpage may be a webpage to be shared with other users.

[0086] In operation (420), one or more processors may obtain a summary text summarizing the content of the loaded webpage in response to inputting the loaded webpage into an artificial intelligence model. As mentioned above, the artificial intelligence model that outputs the summary text from the loaded webpage may be a large-scale language model such as GPT or BERT. However, the type of such large-scale language model is merely an example and is not limited to the above example. The artificial intelligence model that outputs the summary text may be implemented on-device within the transmitting electronic device or implemented on an external server.

[0087] In operation (430), one or more processors may identify metadata of an image defined by the Open Graph standard in a loaded webpage. At this time, one or more processors may download metadata of an image defined by the Open Graph standard from the loaded webpage or identify URI (uniform resource identifier) ​​information regarding the metadata of the image.

[0088] In operation (440), one or more processors may generate summary content by encoding metadata of the image identified in operation (430) into a metadata format of the Open Graph standard and packaging it together with the summary text obtained in operation (420). At this time, if metadata of an image is downloaded from a loaded webpage, the one or more processors may generate summary content by encoding metadata of the downloaded image into a metadata format of the Open Graph standard and packaging it together with the summary text. Conversely, if URI information for metadata of an image is identified from a loaded webpage, the one or more processors may generate summary content by encoding the identified URI information into a metadata format of the Open Graph standard and packaging it together with the summary text.

[0089] In operation (450), one or more processors can share the generated summary content with other users via a communication app. For example, the communication app may include a short message service (SMS), an additional service for mobile phones, or a chat app such as KakaoTalk or Telegram. However, the types of communication apps are merely examples and are not limited to the above examples.

[0090] FIG. 5 is a diagram illustrating an example of a transmitting electronic device summarizing and sharing a webpage according to one embodiment. In one embodiment, at least one of the operations illustrated in FIG. 5 may be performed simultaneously or in parallel with other operations, and the order of the operations may be changed. Furthermore, at least one of the operations may be omitted, and other operations may be additionally performed. The operations illustrated in FIG. 5 may be performed by at least one component of the transmitting electronic device (e.g., the electronic device (101) of FIG. 1 ).

[0091] According to one embodiment, one or more processors included in the transmitting electronic device may, in operation (510), obtain a summary text summarizing the contents of the webpage in response to inputting the webpage to be shared into the artificial intelligence model.

[0092] In operation (520), one or more processors can download metadata of an image defined by the Open Graph standard from a meta image address in the web page, or identify captioning information describing the metadata of the image by referring to the meta image address.

[0093] In operation (530), one or more processors may identify a correlation (score) between the summary text obtained in operation (510) and the captioning information identified in operation (520). At this time, one or more processors may compare the identified correlation with a preset criterion (k) to determine an image corresponding to the summary text.

[0094] More specifically, one or more processors may determine, in operation (540), that the metadata of the captioned image is a thumbnail image for encoding as a representative image of the summary content according to the Open Graph standard, if the identified correlation is greater than or equal to a preset criterion.

[0095] Alternatively, in operation (550), one or more processors may, in response to inputting the summary text obtained in operation (510) as a prompt to the generative AI model if the identified correlation is below a preset standard, generate an image corresponding to the summary text. The one or more processors may determine the image thus generated as a thumbnail image for encoding as a representative image of the summary content according to the Open Graph standard.

[0096] Meanwhile, if there are multiple images, including images defined by the Open Graph standard, on a web page to be shared, one or more processors can identify a correlation between caption information and summary text for each of the multiple images, and compare the identified correlation with a preset standard to determine an image corresponding to the summary text.

[0097] More specifically, one or more processors may determine an image with the highest correlation among images identified with correlations exceeding a preset standard as a thumbnail image for encoding as a representative image of the summary content. Alternatively, one or more processors may generate an image with a higher correlation to the summary text in response to inputting the image with the highest correlation and the summary text into a generative AI model, and determine the image thus generated as a thumbnail image for encoding as a representative image of the summary content.

[0098] Alternatively, if the identified correlation for each of a plurality of images is below a preset threshold, one or more processors may input the image with the highest correlation among the images identified with correlations below the preset threshold and the summary text into the generative AI model, thereby generating an image with a higher correlation to the summary text. The one or more processors may determine the image thus generated as a thumbnail image for encoding as a representative image of the summary content.

[0099] FIG. 6 is a diagram illustrating an operation of a receiving electronic device according to one embodiment of the present invention to display received summary content on the execution screen of a communication app. The operations illustrated in FIG. 6 may be performed by at least one component of the receiving electronic device (e.g., the electronic device (101) of FIG. 1 ).

[0100] According to one embodiment, a communication app (610) running on a receiving electronic device can receive summary content (620) transmitted from a transmitting electronic device. For example, the communication app (610) may include a short message service (SMS), which is an additional service of a mobile phone, or a chat app such as KakaoTalk or Telegram. However, the types of such communication apps are merely examples and are not limited to the above examples.

[0101] The communication app (610) can decode the received summary content (620) to identify whether additional data encoded by the Open Graph standard exists in addition to the summary text. More specifically, the communication app (610) can identify at least one of the following metadata defined by the Open Graph standard: a website title (og:title), a website type (og:type), a representative image (og:image), a website URL (og:url), and a website description (og:description). However, the types of such metadata are merely examples and are not limited to the above examples.

[0102] Let's assume that a representative image (og:image) corresponding to the summary text among the metadata defined by the Open Graph standard has been identified. If the identified representative image is an image existing on the original webpage, the communication app (610) can obtain the URI information of the image existing on the original webpage as additional data. Conversely, if the identified representative image is an image generated by the sending electronic device, the communication app (610) can obtain the image itself generated by the sending electronic device, not the Open Graph standard, as additional data.

[0103] The communication app (610) can display the summary text and additional data identified through decoding of the summary content (620) received in this manner adjacent to the execution screen (630) of the communication app (610). As in the example of FIG. 6, if the website title (og:title) and representative image (og:image) among the metadata of the Open Graph standard are identified as additional data, the communication app (610) can display the website title (og:title), summary text, and representative image adjacent to each other in that order. However, the method of displaying such data is merely an example and is not limited to the above example. For example, the communication app (610) can also display the website description (og:description) area of ​​the Open Graph standard by replacing it with summary text.

[0104] FIG. 7 is a diagram illustrating an operation of a receiving electronic device according to one embodiment of the present invention to display a received URL on the execution screen of a communication app. The operations illustrated in FIG. 7 may be performed by at least one component of the receiving electronic device (e.g., the electronic device (101) of FIG. 1 ).

[0105] In the previous embodiment, a method was provided for receiving summary content including summary text from a transmitting electronic device and displaying the received summary content through a communication app of a receiving electronic device. In contrast, if only URL information (720) is received from the transmitting electronic device without separate summary content, the communication app (710) of the receiving electronic device can crawl a specific webpage of a website (730) corresponding to the received URL information (720).

[0106] The communication app (710) can transmit data of a crawled specific webpage to an application programming interface (API) module (740) to summarize the specific webpage, and can receive a summary text for the specific webpage from the API module (740). At this time, the API module (740) is an artificial intelligence model that outputs a summary text from the webpage, and may be a large language model such as GPT or BERT. However, the type of such artificial intelligence model is only one example and is not limited to the above example. The artificial intelligence model that outputs the summary text in this way can be implemented in an on-device form within the receiving electronic device or implemented on an external server.

[0107] Meanwhile, the communication app (710) of the receiving electronic device can display the summarized text received through the API module (740) on the execution screen (750) adjacent to the metadata identified through decoding of the URL information (720). For example, the communication app (710) can display metadata such as a website title (og:title), website type (og:type), representative image (og:image), website URL (og:url), or website description (og:description) identified through decoding of the URL information (720) at the bottom of the summary text, as shown in FIG. 7. However, the method of displaying such data is merely an example and is not limited to the above example.

[0108] FIG. 8 is a diagram illustrating an operation of a receiving electronic device according to one embodiment of the present invention to display received text content on the execution screen of a communication app. The operations illustrated in FIG. 8 may be performed by at least one component of the receiving electronic device (e.g., the electronic device (101) of FIG. 1 ).

[0109] Referring to FIG. 8, when only text content (820) is received from the transmitting electronic device without separate summary content, the communication app (810) of the receiving electronic device can transmit the received text content (820) to the generative AI model (830) and generate a thumbnail image corresponding to the text content (820) from the generative AI model (830). The communication app (810) of the receiving electronic device can display the thumbnail image generated by the generative AI model (830) adjacent to the received text content (820) on the execution screen (840). For example, the communication app (810) can display the thumbnail image generated and received by the generative AI model (830) at the bottom of the text content (820) as shown in FIG. 8. However, the method of displaying such data is merely an example and is not limited to the above example.

[0110] Meanwhile, the example of FIG. 8 provides a configuration in which a communication app (810) of a receiving electronic device obtains a summary text from a transmitting electronic device and generates and displays an image corresponding to the summary text obtained through a generative AI model (830), but this is only one example and is not limited to the above example. That is, the communication app (810) of the receiving electronic device may obtain a general text before summary, not a summary text, from the transmitting electronic device and generate and display an image corresponding to the general text obtained through a generative AI model (830).

[0111] FIG. 9 is a diagram illustrating an operation of a transmitting electronic device sharing text content according to one embodiment. In one embodiment, at least one of the operations in FIG. 9 may be performed simultaneously or in parallel with other operations, and the order of the operations may be changed. Furthermore, at least one of the operations may be omitted, and other operations may be additionally performed. The operations illustrated in FIG. 9 may be performed by at least one component of a transmitting electronic device (e.g., the electronic device (101) of FIG. 1 ).

[0112] According to one embodiment, one or more processors included in the transmitting electronic device may, in operation (910), identify text content to be shared. The identified text content may be content that does not include a separate image.

[0113] In operation (920), one or more processors can identify whether the text content to be shared is longer than a preset length.

[0114] If the length of the text content is identified as content longer than a preset length, one or more processors may, in operation (930), obtain an image corresponding to the text content in response to inputting the text content to be shared as a prompt to the generative AI model.

[0115] In operation (940), one or more processors may package the acquired image and the text content corresponding to the acquired image, and in operation (950), the packaging result of the acquired image and the text content may be shared with other users.

[0116] Meanwhile, in operation (920), if one or more processors identify that the text content to be shared is less than a preset length, they can share only the text content with other users without a separate image acquisition process.

[0117] However, the example of FIG. 9 provides a configuration for acquiring an image through a generative AI model depending on the length of the text content to be shared. However, this is merely an example, and images can be acquired through a generative AI model regardless of the length of the text content. In this case, operation (920) may be omitted.

[0118] FIG. 10 is a diagram illustrating an operation of a receiving electronic device displaying shared text content on the execution screen of a communication app according to one embodiment. In one embodiment, at least one of the operations in FIG. 10 may be performed simultaneously or in parallel with other operations, and the order of the operations may be changed. In addition, at least one of the operations may be omitted, and other operations may be additionally performed. The operations illustrated in FIG. 10 may be performed by at least one component of the receiving electronic device (e.g., the electronic device (101) of FIG. 1 ).

[0119] According to one embodiment, one or more processors included in a receiving electronic device may, in operation (1010), receive shared text content transmitted from a transmitting electronic device. In this case, the received text content may be content that does not include a separate image.

[0120] In operation (1020), one or more processors may identify whether the received shared text content is longer than a preset length.

[0121] If the length of the shared text content is identified as being greater than a preset length, one or more processors may, in operation (1030), obtain an image corresponding to the shared text content in response to inputting the shared text content as a prompt to the generative AI model.

[0122] In operation (1040), one or more processors may display the image obtained in this manner and the shared text content corresponding to the obtained image adjacent to the execution screen of the communication app.

[0123] Meanwhile, in operation (1020), if one or more processors identify that the received shared text content is less than a preset length, they can display only the shared text content on the execution screen of the communication app without a separate image acquisition process.

[0124] However, the example of FIG. 10 provides a configuration for acquiring an image through a generative AI model based on the length of the received shared text content. However, this is merely an example, and images can be acquired through a generative AI model regardless of the length of the shared text content. In this case, operations (1020) and (1050) may be omitted.

[0125] FIG. 11 is a diagram illustrating an operation of sharing URL information between a transmitting electronic device and a receiving electronic device according to one embodiment. The operations illustrated in FIG. 11 may be performed by at least one component of a transmitting electronic device (e.g., electronic device (101) of FIG. 1) or a receiving electronic device (e.g., electronic device (101) of FIG. 1).

[0126] Referring to FIG. 11, one or more processors included in a transmitting electronic device can identify (1110) a webpage loaded via a browser. If URL information corresponding to the identified webpage is to be shared with other users, the transmitting electronic device can parse the URL information via a URL summary module (1120) to obtain a summary text. At this time, the URL summary module (1120) is an artificial intelligence model that outputs a summary text from a webpage, and may be a large-scale language model such as GPT or BERT. However, the types of such artificial intelligence models are only one example and are not limited to the above examples.

[0127] The URL summary module (1120) of the transmitting electronic device can generate a comment to be delivered to the other user in relation to the URL information based on the acquired summary text and the past conversation history (1130) with the other user. For example, as shown in FIG. 12, let's assume that the URL information that the transmitting electronic device wants to deliver to the other user is information related to a concert of a specific singer. In this case, if the URL summary module (1120) analyzes the past conversation history (1130) between the user using the transmitting electronic device and the other user using the receiving electronic device and identifies that the other user has requested information related to a concert of a specific singer, the URL summary module (1120) can additionally generate a comment to be delivered to the other user, such as "This is the concert information you said you needed." The transmitting electronic device can share this additionally generated comment with the receiving electronic device along with the URL information.

[0128] According to one embodiment, when URL information is identified in an input window as illustrated in FIG. 13, one or more processors included in a transmitting electronic device may parse the URL information through a URL summary module (1120) to obtain a summary text. At this time, the URL summary module (1120) of the transmitting electronic device may generate at least one comment to be delivered to another user in relation to the URL information based on the obtained summary text and past conversation history (1130) with another user, and display the generated comment on the execution screen of the communication app. When any one of the at least one comment displayed on the execution screen is selected, the transmitting electronic device may share the selected comment and URL information corresponding to the selected comment with the receiving electronic device.

[0129] Meanwhile, the receiving electronic device can receive URL information shared from the transmitting electronic device and comments shared with the URL information through the communication app (1140). At this time, the communication app (1140) of the receiving electronic device can display the received URL information and comments shared with the URL information adjacent to the execution screen.

[0130] FIG. 14 is a diagram illustrating an operation of sharing URL information between a transmitting electronic device and a receiving electronic device according to one embodiment. The operations illustrated in FIG. 14 may be performed by at least one component of a transmitting electronic device (e.g., electronic device (101) of FIG. 1) or a receiving electronic device (e.g., electronic device (101) of FIG. 1).

[0131] Referring to FIG. 14, one or more processors included in the transmitting electronic device can identify (1410) a webpage loaded via a browser. In this case, the identified webpage may be a webpage to be shared with other users.

[0132] One or more processors included in the receiving electronic device may receive URL information for a webpage shared from the transmitting electronic device via the communication app (1420). In this case, as shown in FIG. 15 , assume that the communication app (1420) receives only the URL information without a separate comment. In this case, the communication app (1420) can identify metadata defined by the Open Graph standard by crawling a specific webpage of a website corresponding to the URL information.

[0133] Meanwhile, the communication app (1420) can obtain a summary text for a specific webpage by inputting data obtained by crawling the specific webpage into the URL summary module (1430). At this time, the URL summary module (1430) can regenerate a summary text that is more personalized for the user based on the summary text for the specific webpage and the user's personal information (1440). For example, the user's personal information may include contextual information about the user, such as schedule information, past conversation history with the other party, health status, or location information. For example, let's assume that the summary text of a specific webpage summarized through the URL summary module (1430) is information related to a soccer game of a specific team. At this time, if the URL summary module (1430) searches for schedule information and identifies a schedule related to watching a soccer game of the specific team, the URL summary module (1430) can regenerate the summary text by additionally reflecting comments related to the schedule, such as "3 PM, Saturday, October 21, Seoul Stadium." In this case, the URL summary module (1430) may additionally inform the user that the comment has been automatically generated by displaying the reflected comment in a different format or color than the original message display method of the other party. The communication app (1420) may display the regenerated summary text and the received URL information adjacent to each other on the execution screen.

[0134] FIG. 16 is a diagram illustrating a method for sharing summary content with other users according to one embodiment. In one embodiment, at least one of the operations illustrated in FIG. 16 may be performed simultaneously or in parallel with other operations, and the order of the operations may be changed. Furthermore, at least one of the operations may be omitted, and other operations may be additionally performed. The operations illustrated in FIG. 16 may be performed by at least one component of an electronic device (e.g., the electronic device (101) of FIG. 1 ).

[0135] In operation (1610), the electronic device may generate a summary text from the target content to be shared with other users through a summary function. In operation (1620), the electronic device may determine an image corresponding to the summary text. In operation (1630), the electronic device may share the summary content, in which the summary text and the image corresponding to the summary text are encoded together, with other users.

[0136] In one embodiment, the action of determining an image may include inputting a summary text as a prompt to a generative AI (Artificial Intelligence) model to generate an image corresponding to the summary text if no image exists in the target content.

[0137] In one embodiment, the operation of determining an image may, when multiple images exist in the target content, identify a correlation between captioning information and summary text for each of the multiple images. The operation of determining the image may determine an image corresponding to the summary text by comparing the identified correlation with a preset standard.

[0138] In one embodiment, the operation of determining an image may identify the length of a summary text generated from the target content. If the length of the summary text is greater than a preset standard, the operation of determining the image may crawl the images contained in the target content or generate an image corresponding to the summary text.

[0139] In one embodiment, the act of generating a summary text may generate a personalized summary text for the other user based on a past conversation history with the other user.

[0140] The embodiments of the present invention disclosed in this specification and drawings are merely specific examples presented to easily explain the technical contents according to the embodiments of the present invention and to help understand the embodiments of the present invention, and are not intended to limit the scope of the embodiments of the present invention. Therefore, the scope of the embodiments of the present invention should be interpreted as including all changes or modified forms derived based on the technical idea of ​​the embodiments of the present invention in addition to the embodiments disclosed herein.

Claims

1. In an electronic device (101), At least one processor (120) comprising a processing circuit; and A memory (130) comprising one or more storage media storing instructions, The above instructions, when individually or collectively executed by the at least one processor (120), cause the electronic device (101) to: The summary feature allows you to create a summary text from the target content you want to share with other users. Determine the image corresponding to the above summary text, To share summary content consisting of the above summary text and an image corresponding to the above summary text with the above other users. Electronic device (101).

2. In paragraph 1, The above instructions, when individually or collectively executed by the at least one processor (120), cause the electronic device (101) to: If there is no image in the above target content, the summary text is input as a prompt to a generative AI (artificial intelligence) model to generate an image corresponding to the summary text. Electronic device (101).

3. In any one of paragraphs 1 and 2, The above instructions, when individually or collectively executed by the at least one processor (120), cause the electronic device (101) to: If there are multiple images in the above target content, identify the correlation between captioning information for each of the multiple images and the summary text, To determine an image corresponding to the summary text by comparing the identified correlation with a preset criterion. Electronic device (101).

4. In any one of paragraphs 1 to 3, The above instructions, when individually or collectively executed by the at least one processor (120), cause the electronic device (101) to: Determine the image with the highest correlation among the images identified with a correlation higher than the preset standard as the image corresponding to the summary text. Electronic device (101).

5. In any one of paragraphs 1 to 4, The above instructions, when individually or collectively executed by the at least one processor (120), cause the electronic device (101) to: If the identified correlation for each of the above multiple images is less than the preset criterion, an image having the highest correlation among the images identified with a correlation less than the preset criterion and the summary text is input to the generative AI model, thereby generating an image corresponding to the summary text. Electronic device (101).

6. In any one of paragraphs 1 to 5, The above instructions, when individually or collectively executed by the at least one processor (120), cause the electronic device (101) to: Identify the length of the summary text generated from the above target content, If the length of the above summary text is longer than a preset standard, crawling the image included in the target content or generating an image corresponding to the above summary text. Electronic device (101).

7. In any one of paragraphs 1 to 6, The above instructions, when individually or collectively executed by the at least one processor (120), cause the electronic device (101) to: Generate personalized summary text for said other user based on past conversation history with said other user; Electronic device (101).

8. In any one of paragraphs 1 to 7, A summary text generated from the above target content and an image determined in response to the summary text are as follows: The length of the summary text or the form of the image may vary depending on the sharing method or target of the summary content. Electronic device (101).

9. In any one of paragraphs 1 to 8, The above instructions, when individually or collectively executed by the at least one processor (120), cause the electronic device (101) to: The summary content is generated by encoding an image corresponding to the summary text as metadata of an open graph and packaging it together with the summary text. To share the above generated summary content with the above other users, Electronic device (101).

10. In the operating method of an electronic device (101), The action of generating a summary text from the target content that you want to share with other users, through the summary function; An action for determining an image corresponding to the above summary text; and An action to share summary content consisting of the above summary text and an image corresponding to the above summary text with the above other users. A method of operation comprising:

11. In paragraph 10, The action that determines the above image is, If there is no image in the above target content, an action to input the summary text as a prompt to a generative AI (Artificial Intelligence) model to generate an image corresponding to the summary text A method of operation comprising:

12. In any one of paragraphs 10 to 11, The action that determines the above image is, When there are multiple images in the above target content, an operation of identifying the correlation between captioning information for each of the multiple images and the summary text; and An operation of determining an image corresponding to the summary text by comparing the identified correlation with a preset criterion. A method of operation comprising:

13. In any one of paragraphs 10 to 12, The action that determines the above image is, An operation for identifying the length of a summary text generated from the above target content; and If the length of the above summary text is longer than a preset standard, an action of crawling an image included in the above target content or generating an image corresponding to the above summary text A method of operation comprising:

14. In any one of paragraphs 10 to 13, The action of generating the above summary text is: An action to generate a personalized summary text for said other user based on past conversation history with said other user. A method of operation comprising:

15. A computer-readable recording medium having recorded thereon instructions that, when executed by one or more processors (120), cause the one or more processors (120) to perform the method of any one of claims 10 to 14.

Images