Method and apparatus for providing personalized cooking service

Patent metadata

Field	Value
Publication number	US-2023134600-A1
Application number	US-202117434166-A
Country	US
Kind code	A1
Filing date	Jul 20, 2021
Priority date	Jul 22, 2020
Publication date	May 4, 2023
Grant date	—

Abstract

Provided are a server and a method for generating data for cooking food. The method may include: obtaining text indicating a food recipe; applying the text to each of a plurality of natural language understanding (NLU) models for analyzing the text; identifying a plurality of semantic elements included in the text based on at least one semantic element that is output from each of the plurality of NLU models; generating first machine readable recipe (MRR) data structured to include a plurality of cooking device control parameters, by using the plurality of semantic elements; obtaining log data of a user related to a device control action performed by the user to operate a cooking device; and generating second MRR data personalized to the user, by updating the plurality of cooking device control parameters, based on the log data.

First claim

1 . A method performed by a server for generating data for cooking food, the method comprising:
obtaining text indicating a food recipe; applying the text to each of a plurality of natural language understanding (NLU) models for analyzing the text; identifying a plurality of semantic elements included in the text based on at least one semantic element that is output from each of the plurality of NLU models; generating first machine readable recipe (MRR) data structured to include a plurality of cooking device control parameters, by using the plurality of semantic elements; obtaining log data of a user related to a device control action performed by the user to operate a cooking device; and generating second MRR data personalized to the user, by updating the plurality of cooking device control parameters, based on the log data.

2 . The method of claim 1 , wherein the generating of the second MRR data comprises:
providing, to the cooking device, control information for controlling the cooking device based on the first MRR data; obtaining compensation values for control operations of the cooking device corresponding to the control information; and generating the second MRR data by updating the plurality of cooking device control parameters based on an accumulated sum of the compensation values, wherein the compensation values are determined based on the log data of the user.

3 . The method of claim 2 , wherein the generating of the second MRR data comprises:
while the cooking device operates according to the control information for controlling the cooking device, receiving, from the cooking device, input data indicating the device control action of the user; obtaining evaluation data of the user on the food cooked by an operation of the cooking device; and allocating the received input data of the user and the evaluation data of the user to the compensation values.

4 . The method of claim 1 , further comprising:
generating a plurality of first recipe cards for cooking the food by using the first MRR data; and providing the plurality of first recipe cards to a client device.

5 . The method of claim 4 , further comprising:
generating a plurality of second recipe cards for cooking the food personalized to the user by using the second MRR data; and providing the plurality of second recipe cards to the client device.

6 . The method of claim 4 , further comprising determining cooking steps for cooking the food by using the plurality of semantic elements,
wherein the generating of the plurality of first recipe cards comprises determining a type of the plurality of first recipe cards, based on the first MRR data and the determined cooking steps, and wherein the type of the plurality of first recipe cards comprises at least one of a cooking device control type, a cooking item purchase type, or a cooking information provision type.

7 . The method of claim 1 , further comprising:
changing at least part of the first MRR data and the second MRR data, so that the food is cooked by another cooking device, based on identification information of the other cooking device.

8 . A server for generating data for cooking food, the server comprising:
a communication interface; a memory storing one or more instructions; and a processor configured to execute the one or more instructions stored in the memory to: obtain text indicating a food recipe, apply the text to each of a plurality of natural language understanding (NLU) models for analyzing the text, identify a plurality of semantic elements included in the text, based on at least one semantic element that is output from each of the plurality of NLU models, generate first machine readable recipe (MRR) data structured to include a plurality of cooking device control parameters, by using the plurality of semantic elements, obtain log data of a user related to device control action performed by the user to operate a cooking device, and generate second MRR data personalized to the user by updating the plurality of cooking device control parameters, based on the log data.

9 . The server of claim 8 , wherein the processor is further configured to execute the one or more instructions to:
provide, to the cooking device, control information for controlling the cooking device based on the first MRR data, obtain compensation values for control operations of the cooking device corresponding to the control information, and generate the second MRR data by updating the plurality of cooking device control parameters based on an accumulated sum of the compensation values, and wherein the compensation values are determined based on the log data of the user.

10 . The server of claim 9 , wherein the processor is further configured to execute the one or more instructions to:
while the cooking device operates according to the control information for controlling the cooking device, receive, from the cooking device, input data indicating the device control action of the user, obtain evaluation data of the user on the food cooked by an operation of the cooking device, and allocate the received input data of the user and the evaluation data of the user to the compensation values.

11 . The server of claim 8 , wherein the processor is further configured to execute the one or more instructions to:
generate a plurality of first recipe cards for cooking the food by using the first MRR data, and provide the plurality of first recipe cards to a client device.

12 . The server of claim 11 , wherein the processor is further configured to execute the one or more instructions to:
generate a plurality of second recipe cards for cooking the food personalized to the user by using the generated second MRR data, and provide the plurality of second recipe cards to the client device.

13 . The server of claim 11 , wherein the processor is further configured to execute the one or more instructions to:
determine cooking steps for cooking the food by using the plurality of semantic elements, and determine a type of the plurality of first recipe cards, based on the first MRR data and the cooking steps, and wherein the type of the plurality of first recipe cards comprises at least one of a cooking device control type, a cooking item purchase type, or a cooking information provision type.

14 . The server of claim 8 , wherein the processor is further configured to execute the one or more instructions to change at least part of the first MRR data and the second MRR data, so that the food is cooked by another cooking device, based on identification information of the other cooking device.

15 . A non-transitory computer-readable recording medium having recorded thereon a program for executing a method for generating data for cooking food, the method comprising:
obtaining text indicating a food recipe; applying the text to each of a plurality of natural language understanding (NLU) models for analyzing the text; identifying a plurality of semantic elements included in the text based on at least one semantic element that is output from each of the plurality of NLU models; generating first machine readable recipe (MRR) data structured to include a plurality of cooking device control parameters, by using the plurality of semantic elements; obtaining log data of a user related to a device control action performed by the user to operate a cooking device; and generating second MRR data personalized to the user, by updating the plurality of cooking device control parameters, based on the log data.

Assignees

• Samsung Electronics Co Ltd

Inventors

• Kim Keunseob
• Kim Kiljong
• Kim Hongyoon
• Yoon Jongsoo
• Choi Byunguk

Classifications

• G06N3/092

  Reinforcement learning · CPC title

• G06F40/279

  Recognition of textual entities · CPC title

• G06F40/205

  Parsing · CPC title

• G06F40/40

  Processing or translation of natural language (natural language analysis G06F40/20; semantic analysis G06F40/30) · CPC title

• G06F40/20 Primary

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