EP-4738227-A1 - RECIPE RECOMMENDATION METHOD, RECIPE RECOMMENDATION APPARATUS, AND READABLE STORAGE MEDIUM

EP4738227A1EP 4738227 A1EP4738227 A1EP 4738227A1EP-4738227-A1

Abstract

The present application provides a recipe recommendation method, a recipe recommendation apparatus, and a readable storage medium. The recipe recommendation method comprises: acquiring preparation condition information for a cooking process; acquiring first demand information of a user; and generating a recommendation list on the basis of the preparation condition information and the first demand information, wherein the preparation condition information comprises at least one of cooking device type information, food ingredient type information and food ingredient remaining amount information which are used for the cooking process.

Inventors

QIAN, Zhida
SUN, Yuwen

Assignees

Guangdong Midea Kitchen Appliances Manufacturing Co., Ltd.

Dates

Publication Date: 20260506
Application Date: 20231106

Claims (12)

A recipe recommendation method, comprising: obtaining preparation condition information for a cooking process; obtaining first demand information of a user; and generating a recommendation list based on the preparation condition information and the first demand information, wherein the preparation condition information comprises at least one of cooking device type information, food ingredient type information, and food ingredient remaining amount information for the cooking process.
The recipe recommendation method according to claim 1, wherein, the recommendation list comprises a first recommendation list, and the generating the recommendation list based on the preparation condition information and the first demand information comprises: generating a recipe list based on the preparation condition information; determining first keywords based on the first demand information; and generating the first recommendation list based on the first keywords and the recipe list.
The recipe recommendation method according to claim 2, wherein, the generating the first recommendation list based on the first keywords and the recipe list comprises: determining second keywords conflicting with the preparation condition information among the first keywords; obtaining confirmation information input by the user in a case that the second keywords are obtained; generating the first recommendation list based on the first keywords and the recipe list in a case that the confirmation information is obtained; deleting the second keywords from the first keywords in a case that the confirmation information is not obtained; and generating the first recommendation list based on remaining first keywords and the recipe list.
The recipe recommendation method according to claim 2, wherein, the determining the first keywords based on the first demand information comprises: determining the first keywords corresponding to the first demand information from a preset keyword list based on the demand information.
The recipe recommendation method according to claim 2, wherein, the determining the first keywords based on the first demand information comprises: inputting the first demand information into a pre-trained deep learning algorithm to generate the first keywords corresponding to the first demand information.
The recipe recommendation method according to claim 2, wherein, the recommendation list further comprises a second recommendation list, and after the generating the first recommendation list based on the first keywords and the recipe list, the recipe recommendation method further comprises: obtaining second demand information of the user; determining third keywords based on the second demand information in a case that the second demand information input by the user is received; generating the second recommendation list based on the third keywords and the recipe list; and stopping obtaining the second demand information in a case that the user has determined a target recipe from the first recommendation list.
The recipe recommendation method according to any one of claims 1 to 6, wherein, the generating the recommendation list based on the preparation condition information and the first demand information, the recommendation method further comprises: obtaining historical cooking information of the user; determining a priority of recipes in the recommendation list based on the historical cooking information; and sorting the recipes in the recommendation list by the priority.
The recipe recommendation method according to claim 7, wherein, the determining the priority of the recipes in the recommendation list based on the historical cooking information comprises: constructing a historical cooking information matrix based on the historical cooking information; and inputting the historical cooking information matrix into a preset algorithm to generate the priority of the recipes in the recommendation list.
The recipe recommendation method according to any one of claims 1 to 6, wherein, the obtaining the first demand information of the user comprises: obtaining voice information input by the user; converting the voice information into text information; and determining the first demand information based on the text information.
A recipe recommendation apparatus, comprising: an obtaining unit configured to obtain preparation condition information for a cooking process; and obtain first demand information of a user; a generating unit configured to generate a recommendation list based on the preparation condition information and the first demand information; wherein the preparation condition information comprises at least one of cooking device type information, food ingredient type information, and food ingredient remaining amount information for the cooking process.
A recipe recommendation apparatus, comprising: a processor and a memory, wherein the memory stores a program or an instruction which runs in the processor, and when executed by the processor, the program or instruction implements steps of a recipe recommendation method according to any one of claims 1 to 9.
A computer-readable storage medium, wherein, a program or an instruction are stored in the computer-readable storage medium, and when executed by a processor, the program or instruction implement steps of a recipe recommendation method according to any one of claims 1 to 9.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to Chinese Patent Application No. 202310788360.1 filed with the China National Intellectual Property Administration on June 30, 2023 and entitled "RECIPE RECOMMENDATION METHOD, RECIPE RECOMMENDATION APPARATUS, AND READABLE STORAGE MEDIUM", the entire contents of which are herein incorporated by reference. FIELD The present application relates to the technical field of household electrical appliances, and specifically relates to a recipe recommendation method, a recipe recommendation apparatus, and a computer-readable storage medium. BACKGROUND In related technologies, during a recipe recommendation process, recipes can be recommended based on the demand information input by users. However, while the recommended recipes meet the users' needs, there is often a situation where users are unable to implement the selected recipes, which affects user experience. SUMMARY The present application aims to solve at least one of the technical problems existing in the prior art. Thus, a first aspect of the present application provides a recipe recommendation method. A second aspect of the present application provides a recipe recommendation apparatus. A third aspect of the present application provides a recipe recommendation apparatus. A fourth aspect of the present application provides a computer-readable storage medium. The first aspect of the present application provides a recipe recommendation method, comprising: obtaining preparation condition information for a cooking process; obtaining first demand information of a user; and generating a recommendation list on the basis of the preparation condition information and the first demand information, wherein the preparation condition information comprises at least one of cooking device type information, food ingredient type information and food ingredient remaining amount information which are for the cooking process. The recipe recommendation method provided by the present application can be used to recommend recipes corresponding to users' needs to meet their cooking requirements. Users can input their cooking needs through an intelligent device, and the intelligent device can then recommend a list of recipes based on the users' needs for them to select the desired ones from the list. First, the preparation condition information for the cooking process is obtained. Wherein, the preparation condition information can comprise cooking device type information used in the cooking process, for example, the cooking device types available in the user's kitchen, such as a rice cooker, an oven, a microwave oven, or an electric grill. Furthermore, the preparation condition information can further comprise food ingredient type information, that is, the different food ingredients that can be obtained by users, for example, different types of food ingredients in the refrigerator in the user's kitchen, such as chicken, pork, fish, or various types of vegetables. Furthermore, the preparation condition information can further comprise food ingredient remaining amount information, that is, the remaining amount of food ingredients that can be obtained by the user, for example, the remaining amount of chicken or various vegetables in the refrigerator in the user's kitchen. By obtaining the preparation condition information, during the recipe recommendation process, recipes in the recipe list can be selected based on the preparation condition information of the user. This ensures that the recipe chosen by the user can be implemented under the current preparation conditions and improves the accuracy of recipe recommendation. Wherein, the preparation condition information can be obtained in an intelligent ecological environment established by the user's household electrical appliances. The intelligent ecological environment refers to the intelligent ecological environment formed on the basis of the user's use of a series of intelligently connected devices, and all intelligent device information can be obtained from a unified control platform. Each intelligent device can transmit device information, device operation status information, and various other information in the user's home such as temperature, humidity, air quality, as well as the information of food ingredients contained in the refrigerator, shelf life, etc., to a control terminal through the local area network, thus facilitating the unified management of the user's home environment. Thus, before recommending recipes, the preparation condition information for the user's cooking process can be determined from the intelligent ecological environment. Furthermore, the first demand information of the user is obtained. The first demand information of the user refers to the user's requirements for the dishes to be prepared. It can comprise the type of dishes, such as cold dishes, fried foods, and roasted foods. It can further comprise the taste of the dishes, such a