CN116089719A - Menu recommendation method, device, equipment and medium - Google Patents
Menu recommendation method, device, equipment and medium Download PDFInfo
- Publication number
- CN116089719A CN116089719A CN202310079760.5A CN202310079760A CN116089719A CN 116089719 A CN116089719 A CN 116089719A CN 202310079760 A CN202310079760 A CN 202310079760A CN 116089719 A CN116089719 A CN 116089719A
- Authority
- CN
- China
- Prior art keywords
- menu
- recommended
- intelligent
- initial
- search request
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 59
- 235000013305 food Nutrition 0.000 claims abstract description 93
- 239000000463 material Substances 0.000 claims abstract description 90
- 238000010411 cooking Methods 0.000 claims abstract description 81
- 238000013507 mapping Methods 0.000 claims description 11
- 238000004590 computer program Methods 0.000 claims description 5
- 238000012216 screening Methods 0.000 claims description 5
- 238000012163 sequencing technique Methods 0.000 claims description 3
- 235000013372 meat Nutrition 0.000 description 33
- 244000061456 Solanum tuberosum Species 0.000 description 15
- 235000002595 Solanum tuberosum Nutrition 0.000 description 15
- 241000251468 Actinopterygii Species 0.000 description 12
- 235000019688 fish Nutrition 0.000 description 12
- 230000008569 process Effects 0.000 description 12
- 238000010586 diagram Methods 0.000 description 10
- 235000013311 vegetables Nutrition 0.000 description 7
- 235000014102 seafood Nutrition 0.000 description 6
- 235000015277 pork Nutrition 0.000 description 5
- 235000010149 Brassica rapa subsp chinensis Nutrition 0.000 description 4
- 235000000536 Brassica rapa subsp pekinensis Nutrition 0.000 description 4
- 241000499436 Brassica rapa subsp. pekinensis Species 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 241000143060 Americamysis bahia Species 0.000 description 2
- 230000008014 freezing Effects 0.000 description 2
- 238000007710 freezing Methods 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000010257 thawing Methods 0.000 description 2
- 241000238557 Decapoda Species 0.000 description 1
- 241000287828 Gallus gallus Species 0.000 description 1
- 235000007688 Lycopersicon esculentum Nutrition 0.000 description 1
- 240000003768 Solanum lycopersicum Species 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 235000015278 beef Nutrition 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 235000013601 eggs Nutrition 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 238000003058 natural language processing Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 235000012015 potatoes Nutrition 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Economics (AREA)
- General Physics & Mathematics (AREA)
- Strategic Management (AREA)
- Physics & Mathematics (AREA)
- Entrepreneurship & Innovation (AREA)
- Data Mining & Analysis (AREA)
- Educational Administration (AREA)
- Development Economics (AREA)
- Game Theory and Decision Science (AREA)
- General Engineering & Computer Science (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Cold Air Circulating Systems And Constructional Details In Refrigerators (AREA)
Abstract
The invention relates to a menu recommendation method, a device, equipment and a medium, which comprise the following steps: acquiring a menu search request, a prefabricated menu set corresponding to cooking intelligent equipment and food material information corresponding to an intelligent refrigerator, wherein the menu search request comprises at least one menu recommendation keyword, and the menu search request is used for requesting to acquire a target menu set corresponding to the menu recommendation keyword; generating a first initial recommended menu set according to the menu search request and a preset menu set corresponding to the cooking intelligent equipment; and determining a target recommended menu set based on food material information corresponding to the intelligent refrigerator aiming at the first initial recommended menu set. By adopting the method, the prefabricated menu set corresponding to the intelligent cooking equipment and the food material information corresponding to the intelligent refrigerator can be combined, so that the menu meeting the user can be provided more intelligently and reasonably.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a recipe recommendation method, apparatus, device, and medium.
Background
At present, with the rapid development of the internet of things of artificial intelligence, intelligent devices such as electric ovens and intelligent refrigerators for cooking intelligent devices can recommend one or more menus to a user after receiving a menu search request input by the user.
In the prior art, when intelligent devices such as an electric oven, an intelligent refrigerator and the like of cooking intelligent devices receive a menu search request input by a user, each intelligent device determines one or more menus recommended to the user only according to the menu related information stored by the intelligent device, and aiming at the menu search request, the relevance among the intelligent devices is not considered, namely, the menu related information stored by the intelligent devices cannot be combined, so that the menu which accords with the user is intelligently and reasonably recommended to the user.
Disclosure of Invention
In order to solve the technical problems or at least partially solve the technical problems, the invention provides a menu recommendation method, a device, equipment and a medium, wherein when a menu search request is received, a server can obtain a first initial recommended menu set meeting the requirements of a user according to a received prefabricated menu set corresponding to intelligent cooking equipment, and further determine a final target recommended menu set for the first initial recommended menu set by combining food material information corresponding to an intelligent refrigerator to the user.
In order to achieve the above object, the technical solution provided by the embodiments of the present invention is as follows:
in a first aspect, a recipe recommendation method is provided, including: acquiring a menu search request, a prefabricated menu set corresponding to cooking intelligent equipment and food material information corresponding to an intelligent refrigerator, wherein the menu search request comprises at least one menu recommendation keyword, and the menu search request is used for requesting to acquire a target menu set corresponding to the menu recommendation keyword;
generating a first initial recommended menu set according to the menu search request and the preset menu set corresponding to the cooking intelligent equipment;
and determining a target recommended menu set based on the food material information corresponding to the intelligent refrigerator aiming at the first initial recommended menu set.
As an optional implementation manner of the embodiment of the present invention, the generating a first initial recommended menu set according to the menu search request and the preset menu set corresponding to the cooking intelligent device includes:
determining at least one menu recommended keyword according to the menu search request;
and generating the first initial recommended menu set according to at least one menu recommended keyword and the prefabricated menu set, wherein the prefabricated menu set comprises a plurality of prefabricated menus.
As an optional implementation manner of the embodiment of the present invention, the generating the first initial recommended menu set according to at least one menu recommended keyword and the preset menu set includes:
sequentially matching each menu recommended keyword with a plurality of prefabricated menus;
when the menu recommendation keywords exist in the prefabricated menu, determining that the prefabricated menu with the menu recommendation keywords exists as a recommendation menu in the first initial recommendation menu set.
As an optional implementation manner of the embodiment of the present invention, the generating the first initial recommended menu set according to at least one menu recommended keyword and the preset menu set includes:
generating the first initial recommended menu set according to the menu recommended keywords, the prefabricated menus and a preset mapping relation;
the preset mapping relation is determined according to the menu recommended keywords and the preset menu.
As an optional implementation manner of the embodiment of the present invention, the food material information further includes: each food material is in the storage position of the intelligent refrigerator;
The determining, for the first initial recommended menu set, a target recommended menu set based on the food material information corresponding to the intelligent refrigerator includes:
determining all food materials stored in the intelligent refrigerator currently according to the food material information;
screening a plurality of first initial recommended menus included in the first initial recommended menu set according to all food materials stored in the intelligent refrigerator at present, and determining a second initial recommended menu set;
and determining a target recommended menu set according to the storage position of each food material in the intelligent refrigerator aiming at the second initial recommended menu set.
As an optional implementation manner of the embodiment of the present invention, for the second initial recommended menu set, determining the target recommended menu set according to the storage position of each food material in the intelligent refrigerator includes:
determining cooking information corresponding to each second initial recommended menu according to the storage positions aiming at a plurality of second initial recommended menus included in the second initial recommended menu set;
and sequencing the second initial recommended menus according to the cooking information corresponding to each second initial recommended menu, and determining a target recommended menu set.
As an optional implementation manner of the embodiment of the present invention, each target recommended menu included in the target recommended menu set further corresponds to a storage position of each food material in the intelligent refrigerator.
In a second aspect, a menu recommendation device is provided, including:
the intelligent cooking system comprises an acquisition module, a cooking intelligent device and an intelligent refrigerator, wherein the acquisition module is used for acquiring a menu search request, a prefabricated menu set corresponding to the intelligent cooking device and food material information corresponding to the intelligent refrigerator, the menu search request comprises at least one menu recommendation keyword, and the menu search request is used for requesting to acquire a target menu set corresponding to the menu recommendation keyword;
the first initial recommended menu set generation module is used for generating a first initial recommended menu set according to the menu search request and the preset menu set corresponding to the cooking intelligent equipment;
the target recommended menu set determining module is used for determining a target recommended menu set based on the food material information corresponding to the intelligent refrigerator aiming at the first initial recommended menu set.
In a third aspect, the present invention provides an electronic device, comprising: one or more processors;
storage means for storing one or more programs,
The one or more programs, when executed by the one or more processors, cause the one or more processors to implement the virtual human interaction method as shown in the first aspect.
In a fourth aspect, the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the virtual human interaction generating method as shown in the first aspect.
According to the menu recommendation method, device, equipment and medium provided by the embodiment of the invention, a menu search request, a prefabricated menu set corresponding to cooking intelligent equipment and food material information corresponding to an intelligent refrigerator are obtained, wherein the menu search request comprises at least one menu recommendation keyword, and the menu search request is used for requesting to obtain a target menu set corresponding to the menu recommendation keyword; generating a first initial recommended menu set according to the menu search request and a preset menu set corresponding to the cooking intelligent equipment; and determining a target recommended menu set based on food material information corresponding to the intelligent refrigerator aiming at the first initial recommended menu set. In the above process, when receiving the menu search request, the server can obtain a first initial recommended menu set meeting the user requirement according to the received prefabricated menu set corresponding to the cooking intelligent equipment, further, the server determines a final target recommended menu set for the user according to the food material information corresponding to the intelligent refrigerator, and in this way, the prefabricated menu set corresponding to the cooking intelligent equipment and the food material information corresponding to the intelligent refrigerator are combined, so that the menu meeting the user is provided more intelligently and reasonably.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.
In order to more clearly illustrate the embodiments of the present disclosure or the solutions in the prior art, the drawings that are required for the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
Fig. 1 is a schematic diagram of an application scenario between an intelligent device and a control device provided in an embodiment of the present disclosure;
FIG. 2 is a software configuration schematic diagram of an electronic device according to one or more embodiments of the present disclosure;
fig. 3A is a schematic flow chart of a recipe recommendation method according to an embodiment of the disclosure;
fig. 3B is an application scenario schematic diagram of a recipe recommendation method provided in an embodiment of the present disclosure;
fig. 3C is a flowchart illustrating another recipe recommendation method according to an embodiment of the present disclosure;
FIG. 3D is a schematic diagram of an interface for displaying a set of target recommended recipes provided by an embodiment of the disclosure;
Fig. 4 is a flowchart illustrating another recipe recommendation method according to an embodiment of the present disclosure;
fig. 5A is a flowchart illustrating another recipe recommendation method according to an embodiment of the present disclosure;
fig. 5B is a flowchart illustrating another recipe recommendation method according to an embodiment of the present disclosure;
FIG. 6 is a schematic diagram of yet another interface for displaying a set of target recommended recipes provided by an embodiment of the present disclosure;
fig. 7 is a schematic structural diagram of a menu recommendation device according to an embodiment of the present disclosure;
fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure.
Detailed Description
In order that the above objects, features and advantages of the invention will be more clearly understood, a further description of the invention will be made. It should be noted that, without conflict, the embodiments of the present invention and features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced otherwise than as described herein; it will be apparent that the embodiments in the specification are only some, but not all, embodiments of the invention.
The terms "first," second, "" third and the like in the description and in the claims and in the above-described figures are used for distinguishing between similar or similar objects or entities and not necessarily for limiting a particular order or sequence, unless otherwise indicated. It is to be understood that the terms so used are interchangeable under appropriate circumstances.
The terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a product or apparatus that comprises a list of elements is not necessarily limited to all elements explicitly listed, but may include other elements not expressly listed or inherent to such product or apparatus.
Fig. 1 is a schematic view of an application scenario between an intelligent device and a control device provided by an embodiment of the present disclosure, as shown in fig. 1, the intelligent device 200 may be, for example, an electric oven 201 of a cooking intelligent device or an intelligent refrigerator 202, and in fig. 1, when the intelligent device 200 such as the electric oven 201 of the cooking intelligent device or the intelligent refrigerator 202 receives a menu search request input by a user, according to the menu search request, each intelligent device 200 determines one or more menus recommended to the user only according to the menu related information stored by the user, for example, for the cooking intelligent device such as the electric oven 201, when receiving the menu search request input by the user, for example, "i want to make a fragrant and roast chicken wings", the electric oven 201 matches among a plurality of prefabricated menus contained in the prefabricated menu set through a keyword "fragrant and informs the user of whether the menu is present, when the menu is present, but only according to the conventional manner of searching the menu in the electric oven 201, determines whether the preset menu has a preset menu name, i.e., can not make a reasonable query with respect to the preset menu, and can not make a user 'if the user can' reasonably know about the information about the fact.
In summary, with the prior art, aiming at a menu search request input by a user, each intelligent device only recommends a recipe to the user according to the information related to the menu stored by each intelligent device, and the relevance among a plurality of intelligent devices is not considered, namely, the menu related information corresponding to the intelligent devices cannot be combined, so that the menu is intelligently and reasonably recommended to the user.
In order to solve the above-mentioned problems, an embodiment of the present disclosure provides a recipe recommendation method, by obtaining a recipe search request, a preset recipe set corresponding to a cooking intelligent device, and food material information corresponding to an intelligent refrigerator, where the recipe search request includes at least one recipe recommendation keyword, and the recipe search request is used for requesting to obtain a target recipe set corresponding to the recipe recommendation keyword; generating a first initial recommended menu set according to the menu search request and a preset menu set corresponding to the cooking intelligent equipment; and determining a target recommended menu set based on food material information corresponding to the intelligent refrigerator aiming at the first initial recommended menu set. In the above process, when receiving the menu search request, the server can obtain a first initial recommended menu set meeting the user requirement according to the received prefabricated menu set corresponding to the cooking intelligent equipment, further, the server determines a final target recommended menu set for the user according to the food material information corresponding to the intelligent refrigerator, and in this way, the prefabricated menu set corresponding to the cooking intelligent equipment and the food material information corresponding to the intelligent refrigerator are combined, so that the menu meeting the user is provided more intelligently and reasonably.
The menu recommendation method provided by the embodiment of the disclosure can be realized based on the electronic equipment or a functional module or a functional entity in the electronic equipment.
The electronic device may be a smart tv, a personal computer (personal computer, PC), a server, a mobile phone, a tablet computer, a notebook computer, a mainframe computer, etc., which is not particularly limited in the embodiments of the present disclosure.
By way of example, fig. 2 is a schematic software configuration diagram of an electronic device according to one or more embodiments of the present disclosure, and as shown in fig. 2, the system is divided into four layers, namely, an application layer (application layer), an application framework layer (Application Framework layer), an Android run layer and a system library layer (system runtime layer), and a kernel layer, from top to bottom.
In some embodiments, at least one application program is running in the application program layer, and these application programs may be a Window (Window) program of an operating system, a system setting program, a clock program, or the like; or may be an application developed by a third party developer. In particular implementations, the application packages in the application layer are not limited to the above examples.
The framework layer provides an application programming interface (application programming interface, API) and programming framework for the application. The application framework layer includes a number of predefined functions. The application framework layer corresponds to a processing center that decides to let the applications in the application layer act. Through the API interface, the application program can access the resources in the system and acquire the services of the system in the execution.
In some embodiments, the system runtime layer provides support for the upper layer, the framework layer, and when the framework layer is in use, the android operating system runs the C/C++ libraries contained in the system runtime layer to implement the functions to be implemented by the framework layer.
In some embodiments, the kernel layer is a layer between hardware and software. The kernel layer contains at least one of the following drivers: audio drive, display drive, bluetooth drive, camera drive, WIFI drive, USB drive, HDMI drive, sensor drive (e.g., fingerprint sensor, temperature sensor, pressure sensor, etc.), and power supply drive, etc.
The menu recommendation method provided by the embodiment of the application can be realized based on the electronic equipment.
For more detailed description of the present solution, the following description will be given by way of example with reference to fig. 3A, and it will be understood that the steps involved in fig. 3A may include more steps or fewer steps when actually implemented, and the order between these steps may also be different, so as to enable implementation of the recipe recommendation method provided in the embodiments of the present application.
Fig. 3A is a flowchart illustrating a recipe recommendation method according to an embodiment of the present disclosure. The method of the embodiment is applied to a server, and the method of the embodiment is executed by a menu recommendation device applied to intelligent equipment, and the device can be realized in a hardware/software mode. As shown in fig. 3A, the recipe recommendation method specifically includes the following steps:
s31, acquiring a menu search request, a prefabricated menu set corresponding to the intelligent cooking equipment and food material information corresponding to the intelligent refrigerator.
The menu search request comprises at least one menu recommendation keyword, and is used for requesting to acquire a target menu set corresponding to the menu recommendation keyword. For example, the recipe search request may be "i want to eat meat", and the recipe recommended keyword is "meat", but not limited thereto, the disclosure is not particularly limited, and those skilled in the art may set according to actual situations.
The preset menu set refers to a set including a plurality of preset menus stored in advance by the intelligent cooking device, and the preset menu set may be set by each manufacturer when the intelligent cooking device leaves the factory, or may be set by user definition, and each preset menu included by the preset menu set corresponds to a set of cooking process, for example, the cooking process includes cooking time, temperature, etc., but the present disclosure is not limited thereto, and a person skilled in the art may set according to actual conditions.
The above-mentioned food material information refers to each food material stored in the current intelligent refrigerator, and may also be a storage position for each food material, etc., but is not limited thereto, and the present disclosure is not particularly limited thereto, and those skilled in the art may set according to actual situations.
Specifically, the server receives a prefabricated menu set sent by the intelligent cooking device, food material information sent by the intelligent refrigerator and a menu search request comprising one or more menu recommendation keywords, so that the menu search request is utilized to obtain a target recommended menu set corresponding to the search menu recommendation keywords.
As shown in fig. 3B, the electric oven 201 and the intelligent refrigerator 202 can receive a recipe search request such as "i want to eat meat" input by a user through a built-in voice module, the recipe search request is "i want to eat meat" through the electric oven 201, and a preset recipe set of the electric oven 201 is transmitted to the server 300, and the intelligent refrigerator 202 transmits the currently stored food information to the server 300, so that the server 300 obtains the recipe search request "i want to eat meat", the preset recipe set of the electric oven 201, and the currently stored food information of the intelligent refrigerator 202, but the disclosure is not limited thereto, and the disclosure is not particularly limited thereto, and a person skilled in the art may set according to actual situations.
Optionally, the server may also actively send a request for obtaining food material information to the intelligent refrigerator when receiving the menu search request, so as to obtain the food material information of the intelligent refrigerator, which is not limited thereto, and the present disclosure is not particularly limited thereto, and a person skilled in the art may set the present disclosure according to actual situations.
The cooking intelligent device and the intelligent refrigerator are respectively in communication connection with the server, and the server can acquire the menu search request by sending the menu search request and a preset menu set corresponding to the cooking intelligent device to the server after receiving the menu search request of the user.
The menu search request input by the user can be received through a voice module arranged in the cooking intelligent device and the intelligent refrigerator, and when the search request input by the user through voice is received, each intelligent device can convert the voice input by the user into text according to the voice recognition technology, and the voice recognition technology is referred to the prior art and is not repeated here.
Optionally, the manner in which the intelligent device, such as the intelligent cooking device and the intelligent refrigerator, obtains the menu search request may also be by controlling the intelligent device, such as the terminal device of the intelligent cooking device and the intelligent refrigerator, but is not limited thereto, and the disclosure is not particularly limited thereto, and those skilled in the art may set the manner according to the actual situation.
S32, generating a first initial recommended menu set according to the menu search request and a preset menu set corresponding to the intelligent cooking equipment.
Specifically, the server generates a first initial recommended menu set required by a user according to the received menu search request, wherein the first initial recommended menu set comprises at least one menu recommended keyword and a prefabricated menu set corresponding to the intelligent cooking device.
Optionally, fig. 3C is a schematic flow chart of another recipe recommendation method according to an embodiment of the present disclosure, and fig. 3C is a further expansion and optimization based on the embodiment shown in fig. 3A. Further, a description of one possible implementation of S32, as shown in fig. 3C:
s321, determining at least one menu recommended keyword according to the menu search request.
Specifically, after receiving the menu search request, the server determines one or more menu recommendation keywords according to the received menu search request.
For example, with the above embodiment, for obtaining the menu recommended keywords of the menu search request "i want to eat meat", the grammar, syntax and semantic analysis of the menu search request "i want to eat meat" may be implemented through a natural language processing technology, so as to extract the menu recommended keywords corresponding to the menu search request, such as "meat", but not limited thereto, the disclosure is not particularly limited, and those skilled in the art may set according to practical situations.
S322, generating a first initial recommended menu set according to at least one menu recommended keyword and the preset menu set.
Wherein the prefabricated recipe set includes a plurality of prefabricated recipes, for example, the prefabricated recipe set includes, for example, "XX dish 1, XX meat 2, XX dish 3, XX meat 4, XXX dish 5, X meat 6, XXXX dish 7, XXXXX dish 8, XXXXX dish 9.
Specifically, after determining one or more corresponding menu recommendation keywords according to a menu search request, the server generates a first initial recommended menu set required by a user according to the one or more menu recommendation keywords and a preset menu set corresponding to the cooking intelligent device.
For example, in the above embodiment, for obtaining the recipe search request "i want to eat meat", the recipe recommendation keyword "meat" corresponding to the recipe search request is determined, and the prefabricated recipe set includes "XX dish 1, XX meat 2, XX dish 3, XX meat 4, XXX dish 5, X meat 6, XXXX dish 7, XXXX dish 8, XXXX dish 9.
In this way, in the technical scheme provided by the embodiment of the disclosure, in the above process, the first initial recommended menu set meeting the user requirement can be accurately obtained through one or more menu recommended keywords corresponding to the menu search request and the prefabricated menu set.
S33, determining a target recommended menu set based on food material information corresponding to the intelligent refrigerator according to the first initial recommended menu set.
The target recommended menu set is a recommended menu set which is displayed to a user through a display interface of a smart device such as an electric oven 201 of a cooking smart device or a smart refrigerator 202 and meets the requirements of the user. For example, referring to fig. 3D, the target recommended menu set 203 may be displayed on the display interface 2011 of the electric oven 201, or may be a recommended menu set meeting the user requirement, which is played by the voice broadcasting system of the electric oven 201, but not limited thereto, the disclosure is not particularly limited, and those skilled in the art may set according to practical situations.
Specifically, the server determines a target recommended menu set which is finally recommended to the user according to the received food material information corresponding to the intelligent refrigerator aiming at the first initial recommended menu set generated according to the menu search request.
In this way, in the recipe recommendation method provided in the embodiment of the present disclosure, by acquiring a recipe search request, a prefabricated recipe set corresponding to a cooking intelligent device, and food information corresponding to an intelligent refrigerator, the recipe search request includes at least one recipe recommendation keyword, and the recipe search request is used for requesting to acquire a target recipe set corresponding to the recipe recommendation keyword; generating a first initial recommended menu set according to the menu search request and a preset menu set corresponding to the cooking intelligent equipment; and determining a target recommended menu set based on food material information corresponding to the intelligent refrigerator aiming at the first initial recommended menu set. In the above process, when receiving the menu search request, the server can obtain a first initial recommended menu set meeting the user requirement according to the received prefabricated menu set corresponding to the cooking intelligent equipment, further, the server determines a final target recommended menu set for the user according to the food material information corresponding to the intelligent refrigerator, and in this way, the prefabricated menu set corresponding to the cooking intelligent equipment and the food material information corresponding to the intelligent refrigerator are combined, so that the menu meeting the user is provided more intelligently and reasonably.
Fig. 4 is a flowchart of still another recipe recommendation method according to an embodiment of the present disclosure, and fig. 4 is a description of one possible implementation of S322, which is further extended and optimized based on the embodiment shown in fig. 3C, as shown in fig. 4:
s3221, matching each menu recommended keyword with a plurality of prefabricated menus in sequence.
S3222, when the menu recommendation keywords exist in the prefabricated menu, determining the prefabricated menu with the menu recommendation keywords as the recommendation menu in the first initial recommendation menu set.
Specifically, the server sequentially matches each menu recommendation keyword extracted according to the menu search request with a plurality of prefabricated menus included in the prefabricated menu set corresponding to the intelligent cooking device, and when the menu recommendation keywords exist in the prefabricated menus, the prefabricated menus with the menu recommendation keywords are considered to be recommendation menus in the first initial recommendation menu set, so that the first initial recommendation menu set is obtained.
For example, for a recipe search request such as "i want to eat roast meat", the recipe recommendation keywords of the recipe search request "i want to eat roast meat" are determined to be "roast" and "meat", the recipe recommendation keywords "roast" and "meat" are sequentially matched with each of the prefabricated recipes included in the prefabricated recipe set, and if either one of the recipe recommendation keywords "roast" and "meat" exists or both of the prefabricated recipes exist, the prefabricated recipe in which the recipe recommendation keyword exists is considered to be the recommended recipe in the first initial recommended recipe set, but not limited thereto, the disclosure is not particularly limited, and those skilled in the art may set according to actual circumstances.
Optionally, in some embodiments of the present disclosure, when there are multiple menu recommendation keywords, the first menu recommendation keyword may be first matched with each of the prefabricated menus included in the prefabricated menu set, to determine multiple prefabricated menus including the first menu recommendation keyword, and further, screening, using other menu recommendation keywords, the multiple prefabricated menus including the first menu recommendation keyword currently until the last menu recommendation keyword, to determine the first initial recommended menu set.
In this way, in the menu recommendation method provided in the embodiment of the present disclosure, in the above process, by matching each menu recommendation keyword with each prefabricated menu included in the prefabricated menu set, a first initial recommended menu set can be obtained accurately from a plurality of prefabricated menus included in the prefabricated menu set.
Further, when the first initial recommended recipe set is determined according to the one or more recipe recommendation keywords and the preset recipe set, since there is no match between the recipe recommendation keywords and the preset recipes in the preset recipe set, for example, there is no match between the recipe recommendation keywords "seafood" corresponding to the recipe search request "i want to eat seafood" and the preset recipes in the preset recipe set, such as "boiled shrimps", but there is no match between the recipe recommendation keywords "i want to eat seafood" and the preset recipes in the preset recipe set, for "shrimps" belonging to seafood, based on this, in order to accurately determine the first initial recommended recipe set according to the one or more recipe recommendation keywords included in the recipe search request and the preset recipe set, there is no incomplete condition when there is a subsequent determination of the target recommended recipe set according to the first initial recommended recipe set, as shown in fig. 4, a description of another possible implementation of S322:
S3223, generating a first initial recommended menu set according to the menu recommended keywords, the prefabricated menus and the preset mapping relation.
The preset mapping relationship is determined according to the menu recommended keywords and the prefabricated menu, and exemplary, following the above embodiment, the preset mapping relationship is established for the menu recommended keywords "seafood" corresponding to the menu search request "i want to eat seafood" and the prefabricated menu "boiled shrimp", but not limited thereto, the disclosure is not particularly limited, and a person skilled in the art can set according to actual situations.
Specifically, the server determines a first initial recommended menu set according to each menu recommended keyword extracted from the menu search request, each prefabricated menu included in the prefabricated menu set, and a preset mapping relation determined according to the menu recommended keywords and the prefabricated menus.
In this way, in the above-mentioned process, the first initial recommended menu set is determined according to each menu recommended keyword, each prefabricated menu, and the preset mapping relation determined according to the menu recommended keywords and the prefabricated menu, so that the situation that the target recommended menu set is incomplete when the target recommended menu set is determined according to the first initial recommended menu set is avoided.
Fig. 5A is a flowchart of another recipe recommendation method according to an embodiment of the present disclosure, where fig. 5A is a flowchart of another recipe recommendation method according to an embodiment of fig. 4, and the food material information corresponding to the intelligent refrigerator may include food materials stored in the intelligent refrigerator currently, or may be a storage position of each food material in the intelligent refrigerator, based on this, further, a description of one possible implementation manner of S33 is shown in fig. 5A:
s331, determining all food materials stored in the current intelligent refrigerator according to the food material information.
S332, screening according to all food materials stored in the current intelligent refrigerator aiming at a plurality of first initial recommended menus included in the first initial recommended menu set, and determining a second initial recommended menu set.
Specifically, the server determines all food materials stored in the current intelligent refrigerator according to the food material information corresponding to the intelligent refrigerator, and after determining all the food materials stored in the current intelligent refrigerator, screens a plurality of first initial recommended menus included in the first initial recommended menu set according to all the food materials stored in the current intelligent refrigerator, so as to determine a second initial recommended menu set.
For example, for all food materials stored in the current intelligent refrigerator including "eggs, fish, pork, tomatoes, potatoes and pickled vegetables", and for the first initial recommended recipes set including the plurality of first initial recommended recipes including "potato stewed meat, quick-fried beef, spicy fried meat and pickled vegetable fish", the plurality of first initial recommended recipes are screened according to all food materials stored in the current intelligent refrigerator, and it is determined that the second initial recommended recipes set including "potato stewed meat and pickled vegetable fish", but not limited thereto, the disclosure is not particularly limited, and the person skilled in the art can set according to practical conditions.
S333, determining a target recommended menu set according to the storage position of each food material in the intelligent refrigerator aiming at the second initial recommended menu set.
Specifically, the server determines a target recommended menu set which is finally recommended to the user according to the storage position of each food material in the intelligent refrigerator aiming at the second initial recommended menu set.
Optionally, fig. 5B is a flowchart of another recipe recommendation method provided by the embodiment of the present disclosure, and fig. 5B is a description of one possible implementation of S333, which is further extended and optimized based on the embodiment shown in fig. 5A, as shown in fig. 5B:
s3331, determining cooking information corresponding to each second initial recommended menu according to the storage positions aiming at a plurality of second initial recommended menus included in the second initial recommended menu set.
The cooking information is determined at the storage position of the intelligent refrigerator according to each food material required by each second initial recommended menu included in the second initial recommended menu set, and the cooking information can be, for example, thawing time, but is not limited to this, the disclosure is not particularly limited, and a person skilled in the art can set according to practical situations.
For example, the storage position of each food material in the intelligent refrigerator may be a refrigerating chamber or a freezing chamber, and since the storage positions of each food material in the intelligent refrigerator are different, the cooking information of each second initial recommended recipe determined according to each food material is also different, and for the "potato stewed meat and pickled vegetable fish" included in the second initial recommended recipe set, the corresponding food material including potato, pork, pickled vegetable and fish is determined, the potato and pickled vegetable are determined to be stored in the refrigerating chamber of the intelligent refrigerator, and the pork and fish are stored in the freezing chamber of the intelligent refrigerator, based on the cooking information such as thawing time of the pork and the fish is obtained, so that the cooking time of each of the "potato stewed meat and pickled vegetable fish" included in the second initial recommended recipe set is determined to be completed.
Specifically, the server sets a plurality of second initial recommended menus included in the second initial recommended menu, and determines cooking information corresponding to each second initial recommended menu according to storage positions of each food material required by each second initial recommended menu in the intelligent refrigerator.
S3332, sorting the second initial recommended menus according to the cooking information corresponding to the second initial recommended menus, and determining a target recommended menu set.
Specifically, after determining the cooking information corresponding to each second initial recommended menu, the server performs sorting processing on a plurality of second initial recommended menus included in the second initial recommended menu set, and determines a target recommended menu set.
For the "potato stewed meat and pickled Chinese cabbage fish" included in the second initial recommended menu set, the cooking duration of the second initial recommended menu "potato stewed meat" can be determined to be T1 according to the storage position of the food material corresponding to each second initial recommended menu in the intelligent refrigerator, the cooking duration of the second initial recommended menu "pickled Chinese cabbage fish" is determined to be T2, the cooking duration T2 is less than the cooking duration T1, and based on the cooking duration T2, the "potato stewed meat and pickled Chinese cabbage fish" are ordered according to the cooking duration, so that the target recommended menu set is the "pickled Chinese cabbage fish and potato stewed meat", but the disclosure is not limited thereto, and the disclosure can be set according to practical situations by those skilled in the art.
In this way, in the menu recommendation method provided in the embodiment of the present disclosure, in the above process, by acquiring the cooking information corresponding to each second initial recommended menu, the plurality of second initial recommended menus are ranked according to the cooking information corresponding to each second initial recommended menu, so that a menu conforming to the user is provided more intelligently and reasonably.
Optionally, on the basis of the foregoing embodiments, in some embodiments of the present disclosure, each food material corresponding to each target recommended recipe included in the target recommended recipe set is stored in a storage location of the intelligent refrigerator.
Specifically, when determining each target recommended menu in the target recommended menu set, the server simultaneously acquires the storage position of each food material corresponding to each target recommended menu in the intelligent refrigerator, so that a user can acquire the storage position of each food material corresponding to each target recommended menu in the intelligent refrigerator while acquiring the target recommended menu set, and the user can quickly remove the food material from the intelligent refrigerator.
For example, referring to fig. 6, when the user selects the target recommended recipe 2 "potato stewed meat" from among the target recommended recipe sets, the target recommended recipe 2 "potato stewed meat" is displayed on the display window 204 as corresponding to the food material: the potato is stored in the second compartment of the refrigerator and the pork is stored in the first compartment of the refrigerator, and optionally, the target recommended menu 2 "potato stewed meat" may be displayed in the display window 204, which is not limited thereto, and the present disclosure is not particularly limited, and those skilled in the art may set according to practical situations.
In this way, the menu recommendation method provided by the embodiment of the disclosure can enable a user to quickly obtain food materials from the intelligent refrigerator in the process.
Fig. 7 is a schematic structural diagram of a menu recommendation device according to an embodiment of the present disclosure. The device can realize the menu recommendation method according to any embodiment of the disclosure. The device specifically comprises the following steps: the acquisition module 31, the first initial recommended recipe set generation module 32 and the target recommended recipe set determination module 33.
The obtaining module 31 is configured to obtain a recipe search request, a prefabricated recipe set corresponding to the cooking intelligent device, and food material information corresponding to the intelligent refrigerator, where the recipe search request includes at least one recipe recommendation keyword, and the recipe search request is configured to request to obtain a target recipe set corresponding to the recipe recommendation keyword;
a first initial recommended menu set generating module 32, configured to generate a first initial recommended menu set according to the menu search request and the preset menu set corresponding to the cooking intelligent device;
the target recommended menu set determining module 33 is configured to determine, for the first initial recommended menu set, a target recommended menu set based on the food material information corresponding to the intelligent refrigerator.
As an optional implementation manner of the embodiment of the present disclosure, the first initial recommended menu set generating module 32 is specifically configured to determine at least one menu recommended keyword according to the menu search request;
and generating the first initial recommended menu set according to at least one menu recommended keyword and the prefabricated menu set, wherein the prefabricated menu set comprises a plurality of prefabricated menus.
As an optional implementation manner of the embodiment of the present disclosure, the first initial recommended menu set generating module 32 is specifically further configured to match each of the menu recommended keywords with a plurality of the prefabricated menus in sequence;
when the menu recommendation keywords exist in the prefabricated menu, determining that the prefabricated menu with the menu recommendation keywords exists as a recommendation menu in the first initial recommendation menu set.
As an optional implementation manner of the embodiment of the present disclosure, the first initial recommended menu set generating module 32 is specifically further configured to generate the first initial recommended menu set according to each of the menu recommended keywords, each of the prefabricated menus, and a preset mapping relationship;
the preset mapping relation is determined according to the menu recommended keywords and the preset menu.
As an optional implementation manner of the embodiment of the present disclosure, the food material information further includes: each food material is in the storage position of the intelligent refrigerator;
the target recommended menu set determining module 33 is specifically configured to determine, according to the food material information, all food materials stored in the intelligent refrigerator currently;
screening a plurality of first initial recommended menus included in the first initial recommended menu set according to all food materials stored in the intelligent refrigerator at present, and determining a second initial recommended menu set;
and determining a target recommended menu set according to the storage position of each food material in the intelligent refrigerator aiming at the second initial recommended menu set.
As an optional implementation manner of the embodiment of the present disclosure, the target recommended menu set determining module 33 is specifically further configured to determine, for a plurality of second initial recommended menus included in the second initial recommended menu set, cooking information corresponding to each of the second initial recommended menus according to the storage location;
and sequencing the second initial recommended menus according to the cooking information corresponding to each second initial recommended menu, and determining a target recommended menu set.
As an optional implementation manner of the embodiment of the present disclosure, each target recommended menu included in the target recommended menu set further corresponds to a storage position of each food material in the intelligent refrigerator.
In this way, the obtaining module is configured to obtain a recipe search request, a prefabricated recipe set corresponding to the cooking intelligent device, and food material information corresponding to the intelligent refrigerator, where the recipe search request includes at least one recipe recommendation keyword, and the recipe search request is configured to request to obtain a target recipe set corresponding to the recipe recommendation keyword; the first initial recommended menu set generation module is used for generating a first initial recommended menu set according to the menu search request and the preset menu set corresponding to the intelligent cooking equipment; the target recommended menu set determining module is used for determining a target recommended menu set based on the food material information corresponding to the intelligent refrigerator aiming at the first initial recommended menu set. In the above process, when receiving the menu search request, the server can obtain a first initial recommended menu set meeting the user requirement according to the received prefabricated menu set corresponding to the cooking intelligent equipment, further, the server determines a final target recommended menu set for the user according to the food material information corresponding to the intelligent refrigerator, and in this way, the prefabricated menu set corresponding to the cooking intelligent equipment and the food material information corresponding to the intelligent refrigerator are combined, so that the menu meeting the user is provided more intelligently and reasonably.
Fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure. As shown in fig. 8, the electronic device includes a processor 1010 and a storage 1020; the number of processors 1010 in the electronic device may be one or more, one processor 1010 being illustrated in fig. 8; the processor 1010 and the memory device 1020 in the electronic device may be connected by a bus or otherwise, for example in fig. 8.
The storage device 1020 is used as a computer readable storage medium for storing a software program, a computer executable program, and modules, such as program instructions/modules corresponding to the recipe recommendation method in the embodiments of the present disclosure. The processor 1010 executes various functional applications of the electronic device and data processing by running software programs, instructions and modules stored in the storage 1020, i.e., implements the recipe recommendation method provided by the embodiments of the present disclosure.
The storage 1020 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, at least one application program required for a function; the storage data area may store data created according to the use of the terminal, etc. Further, the memory device 1020 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk memory device, flash memory device, or other non-volatile solid state memory device. In some examples, storage 1020 may further include memory located remotely from processor 1010, which may be connected to the electronic device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The electronic device provided by the embodiment can be used for executing the menu recommendation method provided by any embodiment, and has corresponding functions and beneficial effects.
The embodiments of the present disclosure provide a computer readable storage medium, on which a computer program is stored, where the computer program when executed by a processor implements each process executed by the recipe recommendation method described above, and the same technical effects can be achieved, and for avoiding repetition, a detailed description is omitted herein.
The computer readable storage medium may be a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, an optical disk, or the like.
The foregoing description, for purposes of explanation, has been presented in conjunction with specific embodiments. However, the above discussion in some examples is not intended to be exhaustive or to limit the embodiments to the precise forms disclosed above. Many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles and the practical application, to thereby enable others skilled in the art to best utilize the embodiments and various embodiments with various modifications as are suited to the particular use contemplated.
Claims (10)
1. A recipe recommendation method, which is applied to a server, comprising:
acquiring a menu search request, a prefabricated menu set corresponding to cooking intelligent equipment and food material information corresponding to an intelligent refrigerator, wherein the menu search request comprises at least one menu recommendation keyword, and the menu search request is used for requesting to acquire a target menu set corresponding to the menu recommendation keyword;
generating a first initial recommended menu set according to the menu search request and the preset menu set corresponding to the cooking intelligent equipment;
and determining a target recommended menu set based on the food material information corresponding to the intelligent refrigerator aiming at the first initial recommended menu set.
2. The method of claim 1, wherein the generating a first initial recommended set of recipes from the recipe search request and the pre-prepared set of recipes corresponding to the cooking intelligent device comprises:
determining at least one menu recommended keyword according to the menu search request;
and generating the first initial recommended menu set according to at least one menu recommended keyword and the prefabricated menu set, wherein the prefabricated menu set comprises a plurality of prefabricated menus.
3. The method of claim 2, wherein the generating the first initial recommended set of recipes from at least one of the recipe recommendation keywords and the pre-prepared set of recipes comprises:
sequentially matching each menu recommended keyword with a plurality of prefabricated menus;
when the menu recommendation keywords exist in the prefabricated menu, determining that the prefabricated menu with the menu recommendation keywords exists as a recommendation menu in the first initial recommendation menu set.
4. The method of claim 2, wherein the generating the first initial recommended set of recipes from at least one of the recipe recommendation keywords and the pre-prepared set of recipes comprises:
generating the first initial recommended menu set according to the menu recommended keywords, the prefabricated menus and a preset mapping relation;
the preset mapping relation is determined according to the menu recommended keywords and the preset menu.
5. The method of claim 1, wherein the food material information further comprises: each food material is in the storage position of the intelligent refrigerator;
The determining, for the first initial recommended menu set, a target recommended menu set based on the food material information corresponding to the intelligent refrigerator includes:
determining all food materials stored in the intelligent refrigerator currently according to the food material information;
screening a plurality of first initial recommended menus included in the first initial recommended menu set according to all food materials stored in the intelligent refrigerator at present, and determining a second initial recommended menu set;
and determining a target recommended menu set according to the storage position of each food material in the intelligent refrigerator aiming at the second initial recommended menu set.
6. The method of claim 5, wherein for a second initial recommended set of recipes, determining a target recommended set of recipes based on a storage location of each food material in the intelligent refrigerator, comprises:
determining cooking information corresponding to each second initial recommended menu according to the storage positions aiming at a plurality of second initial recommended menus included in the second initial recommended menu set;
and sequencing the second initial recommended menus according to the cooking information corresponding to each second initial recommended menu, and determining a target recommended menu set.
7. The method of claim 1, wherein each of the target recommended recipes of the target recommended recipe set further comprises a storage location of each food material in the intelligent refrigerator.
8. A menu recommendation device, comprising:
the intelligent cooking system comprises an acquisition module, a cooking intelligent device and an intelligent refrigerator, wherein the acquisition module is used for acquiring a menu search request, a prefabricated menu set corresponding to the intelligent cooking device and food material information corresponding to the intelligent refrigerator, the menu search request comprises at least one menu recommendation keyword, and the menu search request is used for requesting to acquire a target menu set corresponding to the menu recommendation keyword;
the first initial recommended menu set generation module is used for generating a first initial recommended menu set according to the menu search request and the preset menu set corresponding to the cooking intelligent equipment;
the target recommended menu set determining module is used for determining a target recommended menu set based on the food material information corresponding to the intelligent refrigerator aiming at the first initial recommended menu set.
9. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs,
When executed by the one or more processors, causes the one or more processors to implement the steps of the method of any of claims 1 to 7.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310079760.5A CN116089719A (en) | 2023-01-18 | 2023-01-18 | Menu recommendation method, device, equipment and medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310079760.5A CN116089719A (en) | 2023-01-18 | 2023-01-18 | Menu recommendation method, device, equipment and medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116089719A true CN116089719A (en) | 2023-05-09 |
Family
ID=86202238
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310079760.5A Pending CN116089719A (en) | 2023-01-18 | 2023-01-18 | Menu recommendation method, device, equipment and medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116089719A (en) |
-
2023
- 2023-01-18 CN CN202310079760.5A patent/CN116089719A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20190021144A1 (en) | Method for voice control on microwave oven, and microwave oven | |
| US20200036804A1 (en) | Cooking Device-Based Recipe Pushing Method and Apparatus | |
| US20210043108A1 (en) | Recipe conversion system | |
| CN104461501A (en) | Cloud intelligent cooking method, cloud intelligent cooking device and cloud server | |
| US20150289544A1 (en) | Sous vide cooking | |
| CN108255084B (en) | Cooking control method based on central control equipment and kitchen housekeeper robot | |
| CN105700680B (en) | A kind of control method and wearable device of smart machine | |
| CN110706131A (en) | Method and device for creating electronic menu, electronic equipment and storage medium | |
| CN112782996B (en) | Equipment linkage method and device, storage medium and electronic device | |
| WO2020027633A2 (en) | Cooking recipe service providing method for creating and sharing recipe | |
| CN112383455A (en) | Data generation method and execution method and equipment | |
| CN109300346A (en) | Smart kitchen systems and teaching method | |
| CN111811182B (en) | Refrigerator and recipe recommendation method | |
| CN113158018A (en) | Recipe recommendation method, refrigerator and computer-readable storage medium | |
| CN111061891A (en) | Image recognition menu development method, terminal and readable storage medium | |
| CN109672925B (en) | Live broadcast label loading method and device and computer equipment | |
| CN110989377A (en) | Method and device for managing multimedia data in smart home operating system | |
| CN114741588A (en) | Target electronic menu recommendation method and device, cooking equipment and terminal equipment | |
| CN116089719A (en) | Menu recommendation method, device, equipment and medium | |
| CN111444435A (en) | Dish searching method and device, intelligent cooking equipment and storage medium | |
| CN106951541B (en) | Cooking information recommending and acquiring method and device | |
| CN111125463A (en) | Time interval setting method and device, storage medium and electronic device | |
| WO2022041992A1 (en) | Refrigerator, display device, server, recommendation method, and message reminding method | |
| CN114893946B (en) | Food storage device and intelligent cooking method | |
| CN114756751A (en) | Recommendation word determination method and device, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |