Method of establishing personalized database based on activity information and user device using the method

Patent metadata

Field	Value
Publication number	US-2025284667-A1
Application number	US-202418952331-A
Country	US
Kind code	A1
Filing date	Nov 19, 2024
Priority date	Mar 7, 2024
Publication date	Sep 11, 2025
Grant date	—

Abstract

A method of establishing a personalized database based on activity information is provided. The method includes generating action information corresponding to a unit operation of a user, based on data obtained by a user device, determining the activity information corresponding to a sequence including a series of sequential pieces of action information, generating episode information based on a plurality of pieces of related activity information, and managing the generated episode information as a personalized knowledge graph, based on a pattern of the generated episode information.

First claim

What is claimed is:

1 . A method of establishing a personalized database based on activity information, the method comprising:
generating action information corresponding to a unit operation of a user, based on data obtained by a user device; determining the activity information corresponding to a sequence comprising a series of sequential pieces of action information; generating episode information based on a plurality of pieces of related activity information; and managing the generated episode information as a personalized knowledge graph, based on a pattern of the generated episode information.

2 . The method of claim 1 , wherein the generating of the episode information comprises generating the episode information by deriving a common attribute with respect to the plurality of pieces of related activity information as the pattern and determining a reliability value with respect to the pattern.

3 . The method of claim 1 , wherein the managing of the generated episode information comprises:
determining a pattern of which episode information of the personalized knowledge graph, pre-stored in personal semantic memory, corresponds to the pattern of the generated episode information; and based on a result of the determining, storing the personalized knowledge graph reflecting the generated episode information in the personal semantic memory.

4 . The method of claim 3 , wherein the determining of the pattern comprises determining the pattern of which episode information of the personalized knowledge graph corresponds to the pattern of the generated episode information and whether or not the pattern of the generated episode information is within a defined range according to a reliability value with respect to the pattern.

5 . The method of claim 3 , wherein the storing of the personalized knowledge graph reflecting the generated episode information in the personal semantic memory comprises:
when the pattern of the generated episode information corresponds to the pattern of any episode information of the personalized knowledge graph, updating the episode information of the corresponding pattern, pre-stored in the personal semantic memory, with the generated episode information; and when the pattern of the generated episode information does not correspond to the pattern of any episode information of the personalized knowledge graph, storing the generated episode information in the personal semantic memory by registering the generated episode information as new episode information of the personalized knowledge graph.

6 . The method of claim 1 , wherein the managing of the generated episode information as the personalized knowledge graph comprises managing routine information comprising at least one piece of episode information as the personalized knowledge graph, based on the pattern of each piece of episode information stored in the personal semantic memory.

7 . The method of claim 1 , wherein the managing of the generated episode information as the personalized knowledge graph comprises, when the pattern of the generated episode information does not correspond to a pattern of homogeneous episode information of the personalized knowledge graph, managing each of the generated episode information and the homogeneous episode information in the personal semantic memory by setting a valid period for each of the generated episode information and the homogeneous episode information.

8 . The method of claim 1 , wherein the managing of the generated episode information as the personalized knowledge graph comprises, when the generated episode information comprises a plurality of patterns comprising different probability distributions from each other, managing each of pieces of episode information respectively corresponding to the plurality of patterns, in the personal semantic memory.

9 . The method of claim 1 , wherein the managing of the generated episode information as the personalized knowledge graph comprises managing, in the personal semantic memory, a parameter value derived as a defined pattern of the episode information, as preference information with respect to the activity information of the user.

10 . One or more non-transitory computer-readable storage media storing computer-executable instructions that, when executed by one or more processors individually or collectively, cause an electronic device to perform operations, the operations comprising:
generating action information corresponding to a unit operation of a user, based on data obtained by a user device; determining activity information corresponding to a sequence comprising a series of sequential pieces of action information; generating episode information based on a plurality of pieces of related activity information; and managing the generated episode information as a personalized knowledge graph, based on a pattern of the generated episode information.

11 . A user device for establishing a personalized database based on activity information, the user device comprising:
memory storing one or more computer programs; and one or more processors communicatively coupled to the memory, wherein the one or more computer programs include computer-executable instructions that, when executed by the one or more processors individually or collectively, cause the user device to:
generate action information corresponding to a unit operation of a user, based on data obtained by the user device,
determine activity information corresponding to a sequence comprising a series of sequential pieces of action information,
generate episode information based on a plurality of pieces of related activity information, and
manage the generated episode information as a personalized knowledge graph, based on a pattern of the generated episode information.

12 . The user device of claim 11 , wherein the one or more computer programs further include computer-executable instructions that, when executed by the one or more processors individually or collectively cause the user device to generate the episode information by deriving a common attribute with respect to the plurality of pieces of related activity information as the pattern and determining a reliability value with respect to the pattern.

13 . The user device of claim 11 , wherein the one or more computer programs further include computer-executable instructions that, when executed by the one or more processors individually or collectively cause the user device to:
determine a pattern of which episode information of the personalized knowledge graph, pre-stored in personal semantic memory, corresponds to the pattern of the generated episode information; and based on a result of the determining, store the personalized knowledge graph reflecting the generated episode information in the personal semantic memory.

14 . The user device of claim 13 , wherein the one or more computer programs further include computer-executable instructions that, when executed by the one or more processors individually or collectively cause the user device to determine the pattern of which episode information of the personalized knowledge graph corresponds to the pattern of the generated episode information and whether or not the pattern of the generated episode information is within a defined range according to a reliability value with respect to the pattern.

15 . The user device of claim 13 , wherein the one or more computer programs further include computer-executable instructions that, when executed by the one or more processors individually or collectively cause the user device to,
when the pattern of the ge

Assignees

• Samsung Electronics Co Ltd

Inventors

• Jung Jinhe
• Kim Sungwon
• Kong Seunggyu
• Park Sangwoong
• Seo Sungmok
• Oh Changhyup
• Oh Hyungrai
• Lee Yunsu
• Han Myunghee

Classifications

• G06F16/211 Primary

  Schema design and management · CPC title