Electronic device and control method therefor

Patent metadata

Field	Value
Publication number	US-2025232136-A1
Application number	US-202519057402-A
Country	US
Kind code	A1
Filing date	Feb 19, 2025
Priority date	Sep 19, 2022
Publication date	Jul 17, 2025
Grant date	—

Abstract

An electronic device includes at least one sensor, memory storing instructions, and at least one processor, where the instructions, when executed by the at least one processor, cause the electronic device obtain a plurality of data related to a daily life of a user based on a sensing value obtained from the at least one sensor, based on a similarity of the plurality of data, determine an event related to the user and corresponding to at least one data of the plurality of data, based on the plurality of data, determine a plurality of keywords related to the event related to the user, and based on the plurality of keywords, generate at least one sentence corresponding to the event related to the user.

First claim

What is claimed is:

1 . An electronic device, comprising:
at least one sensor; memory storing instructions; and at least one processor, wherein the instructions, when executed by the at least one processor, cause the electronic device to:
obtain a plurality of data related to a daily life of a user based on a sensing value obtained from the at least one sensor;
based on a similarity of the plurality of data, determine an event related to the user and corresponding to at least one data of the plurality of data;
based on the plurality of data, determine a plurality of keywords related to the event related to the user; and
based on the plurality of keywords, generate at least one sentence corresponding to the event related to the user.

2 . The electronic device of claim 1 , wherein the instructions, when executed by the at least one processor, further cause the electronic device to determine the similarity of the plurality of data based on an artificial intelligence (AI) model,
wherein the AI model comprises at least one of a machine learning algorithm, a neural network algorithm, a gene algorithm, a deep learning algorithm, and a classification algorithm.

3 . The electronic device of claim 1 , wherein the plurality of data comprises a plurality of position data, and
wherein the instructions, when executed by the at least one processor, cause the electronic device to determine the event related to the user by:
determining first position data among the plurality of position data; and
determining the similarity of the plurality of data based on a distance value between the first position data and second position data that is obtained after the first position data.

4 . The electronic device of claim 1 , wherein the plurality of data comprises a plurality of movement data, and
wherein the instructions, when executed by the at least one processor, further cause the electronic device to determine the event related to the user by determining the similarity of the plurality of data based on a period in which the plurality of movement data is sustained.

5 . The electronic device of claim 1 , wherein the plurality of data related to the daily life of the user comprises at least one of location data, movement data, weather data, temperature data, date data, day data, time data, and photo data, and
wherein the plurality of keywords comprise at least one of a location keyword corresponding to the location data, a movement keyword corresponding to the movement data, a weather keyword corresponding to the weather data, a temperature keyword corresponding to the temperature data, a date keyword corresponding to the date data, a day keyword corresponding to the day data, a time keyword corresponding to the time data, and a photo keyword corresponding to the photo data.

6 . The electronic device of claim 1 , wherein the instructions, when executed by the at least one processor, further cause the electronic device to:
receive a user input corresponding to at least one of the plurality of keywords; change at least one of the plurality of keywords based on the user input; and based on the at least one of the plurality of keywords that are changed, generate the at least one sentence corresponding to the event related to the user.

7 . The electronic device of claim 1 , wherein the instructions, when executed by at the least one processor, further cause the electronic device to:
receive a user input corresponding to the at least one sentence; and change the at least one sentence based on the user input.

8 . The electronic device of claim 7 , wherein the instructions, when executed by the at least one processor, further cause the electronic device to change the at least one sentence by:
based on the user input being received, analyzing a component of the at least one sentence corresponding to the user input; and changing the at least one sentence corresponding to the event related to the user based on the analyzed component and the plurality of keywords.

9 . The electronic device of claim 1 , further comprising:
a display, wherein the instructions, when executed by the at least one processor, further cause the electronic device to display, on the display, at least one of the plurality of data, the plurality of keywords, or the at least one sentence corresponding to the event related to the user.

10 . The electronic device of claim 1 , wherein the instructions, when executed by the at least one processor, further cause the electronic device to:
determine a number of keywords that are the same among the plurality of keywords; and obtain a keyword statistic based on the determined number of keywords.

11 . A method of controlling an electronic device, comprising:
obtaining a plurality of data related to a daily life of a user based on a sensing value obtained from at least one sensor; based on a similarity of the plurality of data, determining an event related to the user and corresponding to at least one data of the plurality of data; based on the plurality of data, determining a plurality of keywords related to the event related to the user; and based on the plurality of keywords, generating at least one sentence corresponding to the event related to the user.

12 . The method of claim 11 , wherein the method further comprises determining the similarity of the plurality of data based on an artificial intelligence (AI) model,
wherein the AI model comprises at least one of a machine learning algorithm, a neural network algorithm, a gene algorithm, a deep learning algorithm, and a classification algorithm.

13 . The method of claim 11 , wherein the plurality of data comprises a plurality of position data, and
wherein the determining the event related to the user comprises:
determining first position data among the plurality of position data;
determining the similarity of the plurality of data based on a distance value between the first position data and second position data that is obtained after the first position data.

14 . The method of claim 11 , wherein the plurality of data comprises a plurality of movement data, and
wherein the determining the event related to the user comprises determining the similarity of the plurality of data based on a period in which the plurality of movement data is sustained.

15 . The method of claim 11 , wherein the plurality of data related to the daily life of the user comprises at least one of location data, movement data, weather data, temperature data, date data, day data, time data, or photo data, and
wherein the plurality of keywords comprises at least one of a location keyword corresponding to the location data, a movement keyword corresponding to the movement data, a weather keyword corresponding to the weather data, a temperature keyword corresponding to the temperature data, a date keyword corresponding to the date data, a day keyword corresponding to the day data, a time keyword corresponding to the time data, and a photo keyword corresponding to the photo data.

16 . The method of claim 11 , further comprising:
receiving a user input corresponding to at least one of the plurality of keywords; changing at least one of the plurality of keywords based on the user input; and based on the at least one of the plurality of keywords that are changed. generating the at least one sentence corresponding to the event related to the user.

17 . The method of claim 11 , further comprising:
receiving a user input corresponding to the at least one sentence; and changing the at least

Assignees

• Samsung Electronics Co Ltd

Inventors

• Yun Eunzu
• Kim Junhee
• Shin Wooheun
• Choi Minchang
• Han Seohui

Classifications

• G06F40/279

  Recognition of textual entities · CPC title

• G06F40/20

  Natural language analysis (semantic analysis of natural language G06F40/30) · CPC title

• G06F40/30

  Semantic analysis · CPC title

• G06F40/56 Primary

  Natural language generation · CPC title

• G06N3/045

  Combinations of networks · CPC title