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EP-4742683-A1 - ELECTRONIC DEVICE AND OPERATION METHOD THEREOF

EP4742683A1EP 4742683 A1EP4742683 A1EP 4742683A1EP-4742683-A1

Abstract

The present disclosure relates to an artificial intelligence (AI) system and application thereof, which use a machine learning algorithm. An electronic device according to the present disclosure may include memory storing one or more instructions, and one or more processors configured to execute the one or more instructions stored in the memory, wherein the one or more processors are configured to transmit, to a server, request information that is obtained from at least one of situation information and metadata corresponding to content, the request information including input conversational text information, and receive, from the server, a recommendation result based on the request information.

Inventors

  • LEE, DAEHYUN
  • JEONG, Yoonyoung

Assignees

  • Samsung Electronics Co., Ltd.

Dates

Publication Date
20260513
Application Date
20240604

Claims (15)

  1. An electronic device (100) comprising: memory (120) storing one or more instructions; and one or more processors (110) configured to execute the one or more instructions stored in the memory, wherein the one or more processors are configured to transmit, to a server (200), request information that is obtained from at least one of situation information and metadata corresponding to content, the request information including input conversational text information, and receive, from the server, a recommendation result based on the request information.
  2. The electronic device of claim 1, wherein the one or more processors are configured to transmit the request information to the server when a control signal corresponding to execution of one function among a search function, a channel change function, and a function of return to main screen is received.
  3. The electronic device of claim 1 or 2, wherein the situation information comprises at least one of context information of content being currently output, user information, characteristic information, and circumstantial situation information.
  4. The electronic device of any one of claims 1 to 3, wherein the metadata corresponding to content comprises at least one of metadata corresponding to content being currently output, metadata corresponding to content outputtable by the electronic device, and schedule information.
  5. The electronic device of any one of claims 1 to 4, wherein the recommendation result received from the server comprises at least one of an executable operation, an outputtable channel, or information corresponding to content, the one or more processors are configured to control at least one of an audio signal and a video signal to be output, the audio signal and the video signal corresponding to the recommendation result received from the server, and the video signal comprises conversational text information.
  6. The electronic device of claim 5, wherein, when the recommendation result is output via a multi-view screen, the one or more processors are configured to: receive, from the server, next screen information to be output in a first area comprised in the multi-view screen, and control output of a screen based on a recommendation result corresponding to the next screen information received from the server, when a user input of selecting screen information currently output in the first area is received.
  7. A server (200) comprising: memory (220) storing one or more instructions; and one or more processors (210) configured to execute the one or more instructions stored in the memory, wherein the one or more processors are configured to, when request information including input conversational text information is received from an electronic device (100), transmit, to the electronic device, a recommendation result comprising a recommendation reason that corresponds to the request information and is obtained based on one or more neural networks.
  8. The server of claim 7, wherein the one or more processors are configured to obtain at least one of additional information and user information, and obtain the recommendation result from the one or more neural networks by inputting the request information along with at least one of the additional information and the user information to the one or more neural networks.
  9. The server of claim 8, wherein the additional information comprises at least one of metadata corresponding to content, popular content, curated content, content selected based on particular theme, and key performance index (KPI) information, and the user information comprises at least one of setting information, a user profile, a user's viewing history information, and channel change history information.
  10. The server of any one of claims 7 to 9, wherein the one or more processors are configured to obtain, as a recommendation reason, candidate information having high priority among a plurality of pieces of candidate information related to a recommendation reason, from the one or more neural networks.
  11. The server of any one of claims 7 to 10, wherein the one or more neural networks comprise a plurality of theme-specific neural networks, and the one or more processors are configured to obtain the recommendation result from at least one of the plurality of theme-specific neural networks by inputting, to the plurality of theme-specific neural networks, information corresponding to the plurality of theme-specific neural networks obtained based on the request information.
  12. The server of any one of claims 7 to 11, wherein the recommendation result further comprises information corresponding to an additional function executable by the electronic device.
  13. An operation method of an electronic device, the operation method comprising: transmitting, to a server, request information that is obtained from at least one of situation information and metadata corresponding to content, the request information including input conversational text information; and receiving, from the server, a recommendation result based on the request information.
  14. The operation method of claim 13, wherein the transmitting of the request information to the server comprises transmitting the request information to the server, when a control signal corresponding to execution of one function among a search function, a channel change function, and a function of return to main screen is received.
  15. The operation method of claim 13 or 14, further comprising outputting at least one of an audio signal and a video signal which correspond to the recommendation result, and wherein the video signal comprises conversational text information.

Description

Technical Field Disclosed various embodiments relate to an electronic device and an operation method thereof, and more particularly, to an electronic device having embedded therein an artificial intelligence technology, and an operation method using the electronic device. Background Art Hyper-scale artificial intelligence (Al) is an Al model trained on a large amount of data. The hyper-scale Al is capable of processing and analyzing a large amount of data, and exhibits high accuracy and performance. With the introduction of the hyper-scale Al, the performance of generative Al has significantly advanced. Unlike the existing Al system designed to recognize and predict a pattern, the generative Al is an Al algorithm that generates new data based on existing data. Disclosure of Invention Solution to Problem According to an embodiment, an electronic device may include memory storing one or more instructions, and one or more processors configured to execute the one or more instructions stored in the memory. In an embodiment, the one or more processors may be configured to transmit, to a server, request information that is obtained from at least one of situation information and metadata corresponding to content, the request information including input conversational text information. In an embodiment, the one or more processors may be configured to receive, from the server, a recommendation result based on the request information. Brief Description of Drawings FIG. 1 illustrates an electronic device that transmits request information to a server and receives a recommendation result from the server, according to an embodiment.FIG. 2 is a block diagram of an electronic device according to an embodiment.FIG. 3 illustrates a block diagram of a processor according to an embodiment.FIG. 4 is a block diagram of a situation information obtainer, according to an embodiment.FIG. 5 illustrates a case in which an electronic device outputs a video signal that is a recommendation result received from a server, according to an embodiment.FIG. 6 illustrates a case in which an electronic device outputs an audio signal as a recommendation result received from a server, according to an embodiment.FIG. 7 illustrates a case in which an electronic device outputs a video signal as a recommendation result received from a server, according to an embodiment.FIG. 8 illustrates a case in which an electronic device outputs a video signal that is a recommendation result received from a server, according to an embodiment.FIG. 9 is a block diagram of an electronic device according to an embodiment.FIG. 10 is a block diagram of a server according to an embodiment.FIG. 11 is a block diagram of a server according to an embodiment.FIG. 12 illustrates a case in which a server obtains both a recommendation result and a recommendation reason, according to an embodiment.FIG. 13 illustrates a case in which a server generates a recommendation result by using a consistent method, according to an embodiment.FIG. 14 illustrates a case in which a server generates a recommendation result by using a consistent method, according to an embodiment.FIG. 15 is a diagram illustrating a case in which a server obtains a recommendation result by using a plurality of theme-specific neural networks, according to an embodiment.FIG. 16 illustrates a recommendation result output by an electronic device, according to an embodiment.FIG. 17 is a flowchart of an operation method of an electronic device and a server, according to an embodiment.FIG. 18 is a flowchart of an operation method of an electronic device and a server, according to an embodiment. Mode for the Invention According to an embodiment, a server may include memory storing one or more instructions and one or more processors configured to execute the one or more instructions stored in the memory. In an embodiment, the one or more processors may be configured to, when request information including input conversational text information is received from an electronic device, transmit, to the electronic device, a recommendation result including a recommendation reason that corresponds to the request information and is obtained based on one or more neural networks. According to an embodiment, an operation method of an electronic device may include transmitting, to a server, request information that is obtained from at least one of situation information and metadata corresponding to content, the request information including input conversational text information. In an embodiment, the operation method of the electronic device may include receiving, from the server, a recommendation result based on the request information. According to an embodiment, an operation method of a server may include, when request information including input conversational text information is received from an electronic device, transmitting, to the electronic device, a recommendation result including a recommendation reason that corresponds to t