CN113808706A - Recipe recommendation method and device, electronic equipment and storage medium - Google Patents
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Abstract
The invention discloses a recipe recommendation method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining basic information input by a user and monitoring information of related products; and recommending recipes according to the basic information and the monitoring information. By adopting the scheme provided by the invention, the recipe can be pertinently recommended to the user according to the user condition, the user experience is improved, and the healthy diet of the user is realized.
Description
Technical Field
The invention relates to the technical field of intelligent recommendation, in particular to a recipe recommendation method and device, electronic equipment and a storage medium.
Background
At present, with the development of society, the living requirements of people are higher and higher. Among them, diet is an important aspect of people's daily life. The health of eating and the smoothness of eating are the important requirements of the users for diet at present. Some current recommendation systems and applications recommend recipes for users, but the recommended recipes are not different and targeted for different user groups. That is, the current recommendation system and application cannot make recipe recommendation specifically for the user's situation.
Disclosure of Invention
In order to solve the technical problem that a recommended recipe is not targeted based on user information, embodiments of the present invention provide a recipe recommendation method, apparatus, electronic device, and storage medium.
The technical scheme of the embodiment of the invention is realized as follows:
the embodiment of the invention provides a recipe recommendation method, which comprises the following steps:
acquiring basic information input by a user and monitoring information of a related product;
and recommending recipes according to the basic information and the monitoring information.
In the foregoing solution, the recommending recipes according to the basic information and the monitoring information includes:
determining an initial recipe set according to the basic information;
optimizing the initial recipe set according to the monitoring information to determine an optimized recipe set;
and recommending the optimized recipe set to a user.
In the foregoing solution, the basic information includes a food material contraindicated by a user, and the determining an initial recipe set according to the basic information includes:
acquiring a first recipe set containing taboo food materials in a preset recipe and a second recipe set not containing the taboo food materials in the preset recipe, and determining the second recipe set as an initial recipe set;
alternatively, the first and second electrodes may be,
determining a second food material equivalent to the taboo food material, replacing the taboo food material in the preset recipe with the second food material, and determining the replaced recipe as an initial recipe set.
In the foregoing solution, the basic information includes user status information, and the determining an initial recipe set according to the basic information includes:
acquiring a third recipe set corresponding to the user state information in a preset recipe;
determining the third recipe set as an initial recipe set.
In the foregoing solution, the monitoring information includes sleep data, and the optimizing the initial recipe set according to the monitoring information and determining the optimized recipe set includes:
determining a fourth recipe set of the initial recipe set that is conducive to user sleep and a fifth recipe set of the initial recipe set that is detrimental to user sleep;
determining the sleep state of the user according to the monitoring information;
and adjusting the recommendation coefficient of the fourth recipe set and the recommendation coefficient of the fifth recipe set according to the sleep state.
In the foregoing solution, the optimizing the initial recipe set according to the monitoring information, and determining an optimized recipe set includes:
determining the number of times of adoption of each recipe in the initial recipe set;
and adjusting the recommendation coefficient of the corresponding recipe according to the adoption times.
In the above scheme, after recommending recipes according to the basic information and the monitoring information, the method further includes:
and recommending the cooking teaching materials of the recipe and the purchasing ways of the food materials in the recipe for the user.
The embodiment of the invention also provides a recipe recommendation device, which comprises the following components:
the acquisition module is used for acquiring basic information input by a user and monitoring information of related products;
and the recommending module is used for recommending recipes according to the basic information and the monitoring information.
An embodiment of the present invention further provides an electronic device, including: a processor and a memory for storing a computer program capable of running on the processor; wherein the content of the first and second substances,
the processor is adapted to perform the steps of any of the methods described above when running the computer program.
The embodiment of the invention also provides a storage medium, wherein a computer program is stored in the storage medium, and when the computer program is executed by a processor, the steps of any one of the methods are realized.
The recipe recommendation method, the apparatus, the electronic device and the storage medium provided by the embodiment of the invention obtain basic information input by a user and monitoring information of related products; and recommending recipes according to the basic information and the monitoring information. By adopting the scheme provided by the invention, the recipe can be pertinently recommended to the user according to the user condition, the user experience is improved, and the healthy diet of the user is realized.
Drawings
FIG. 1 is a flowchart illustrating a recipe recommendation method according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a recipe recommendation apparatus according to an embodiment of the present invention;
fig. 3 is an internal structural diagram of a computer device according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
An embodiment of the present invention provides a recipe recommendation method, as shown in fig. 1, the method includes:
step 101: acquiring basic information input by a user and monitoring information of a related product;
step 102: and recommending recipes according to the basic information and the monitoring information.
Specifically, the system may preset a plurality of basic information options for the user to select, so as to obtain the basic information of the user. Further, the basic information may include height, weight, gender, age, family membership, preferences, allergens, and current status. The preference may be a specific food material that the user likes or dislikes. The current state can be a fat-reducing period, a lactation period, a body recovery period, a muscle-increasing period and the like.
In practical applications, the related products may include a sleep detector, a microwave oven, a refrigerator, an oven, and the like. Namely, the associated products may include home appliances, wearable devices, detection devices, and the like. Accordingly, the monitoring information may include sleep data, microwave oven heating food information, refrigerator holding food information, and the like.
Further, in an embodiment, the recommending recipes according to the basic information and the monitoring information includes:
determining an initial recipe set according to the basic information;
optimizing the initial recipe set according to the monitoring information to determine an optimized recipe set;
and recommending the optimized recipe set to a user.
In practical application, the basic information of the user can be acquired to determine an initial recipe set, and then the recommended recipes are further optimized by collecting the use data of the user in the use process of the user, so that recipes which meet the requirements of the user are recommended to the user.
Specifically, in an embodiment, the basic information includes a food material contraindicated by a user, and the determining the initial recipe set according to the basic information includes:
acquiring a first recipe set containing taboo food materials in a preset recipe and a second recipe set not containing the taboo food materials in the preset recipe, and determining the second recipe set as an initial recipe set;
alternatively, the first and second electrodes may be,
determining a second food material equivalent to the taboo food material, replacing the taboo food material in the preset recipe with the second food material, and determining the replaced recipe as an initial recipe set.
In practical application, the contraindicated food materials of the user can be determined from the preference of the user and/or the allergen input by the user. For example, the user dislikes the caraway, and the caraway may be set as a taboo food material. For another example, the user may be allergic to peanuts, and the peanuts may be set as contraindicated food materials.
Specifically, the recipes preset by the system may include names and usage amounts of food materials required by each recipe. According to the food material names contained in each recipe, a first recipe set containing the contraindicated food materials and a second recipe set not containing the contraindicated food materials are determined, and the second recipe set not containing the contraindicated food materials is used as an initial recipe set.
In addition, to improve user experience, a second food material equivalent to the contraindicated food material may be determined. For example, when the contraindicated food material is a caraway, celery may be used as the second food material equivalent to the caraway. And replacing the caraway in each recipe in the preset recipe with celery, and taking the replaced recipe as an initial recipe set.
In addition, when determining the initial set of recipes, the determination may also be made in conjunction with user status information.
Specifically, in an embodiment, the basic information includes user status information, and the determining an initial recipe set according to the basic information includes:
acquiring a third recipe set corresponding to the user state information in a preset recipe;
determining the third recipe set as an initial recipe set.
Here, the system may preset a correspondence relationship between the user status information and a plurality of recipes that are preset. For example, when the user status information is a fat-reduction period, a recipe consisting of low-calorie food materials may be set to correspond to the fat-reduction period. When the user state information is in the body recovery period, a tonic recipe such as chicken soup can be set to correspond to the body recovery period. In actual application, the recipe corresponding to the user state information can be determined as an initial recipe set according to the user state information.
Furthermore, in order to improve the intellectualization level of recipe recommendation, other product data can be combined for further recommendation.
Specifically, in an embodiment, the monitoring information includes sleep data, and the optimizing the initial recipe set according to the monitoring information and determining the optimized recipe set includes:
determining a fourth recipe set of the initial recipe set that is conducive to user sleep and a fifth recipe set of the initial recipe set that is detrimental to user sleep;
determining the sleep state of the user according to the monitoring information;
and adjusting the recommendation coefficient of the fourth recipe set and the recommendation coefficient of the fifth recipe set according to the sleep state.
In practice, the system can preset whether the recipe is helpful for the user to sleep or harmful to the user to sleep. For example, when caffeine is included in the recipe, the recipe may be set to be detrimental to the user's sleep at that time. For example, when milk is included in the recipe, the recipe may be set to help the user sleep.
Specifically, the sleep state of the user may be determined from the monitoring information. For example, according to the data detected by the sleep detector, it is detected that the sleep duration of the user in the last week is short, and the sleep state of the user can be determined to be poor. For another example, according to data detected by the sleep detector, it is monitored that the number of times of turning over and kicking the user in the yesterday sleep time period is large, and it can be judged that the sleep state of the user is poor.
When the sleep state of the user is poor, the sleep state of the user can be improved by increasing the recommendation coefficient of the recipe which is helpful for the user to sleep. In addition, the sleep state of the user can be improved by reducing the recommendation coefficient of the recipe harmful to the sleep of the user.
Further, the monitoring data may also include information about heating of food by microwave oven and information about keeping of food by refrigerator. The number of times the user takes the recommended recipes can be counted by the information. And further optimizing a recipe recommendation mode according to the times of the recipe taking.
Specifically, in an embodiment, the optimizing the initial recipe set according to the monitoring information, and determining an optimized recipe set includes:
determining the number of times of adoption of each recipe in the initial recipe set;
and adjusting the recommendation coefficient of the corresponding recipe according to the adoption times.
Specifically, the ranking may be performed according to the number of acquisitions of each recipe. The recommendation coefficient of the recipes with more adoption times is improved, and the recommendation coefficient of the recipes with less adoption times is reduced. In addition, a corresponding relation between the number of times of adoption and the recommendation coefficient may be preset, when the number of times of adoption changes, the recommendation coefficient corresponding to the number of times of adoption latest is determined according to the set corresponding relation, and the recommendation coefficient of the recipe is determined according to the latest determined recommendation coefficient.
In addition, in order to further improve the user experience, after the recipe is recommended to the user, the cooking teaching materials of the recipe and the purchasing ways of the food materials in the recipe can be further recommended to the user.
Specifically, the cooking teaching material can be in a graphic version or a video. The purchase route of the food material may be to purchase a web link.
The recipe recommendation method provided by the embodiment of the invention obtains basic information input by a user and monitoring information of related products; and recommending recipes according to the basic information and the monitoring information. By adopting the scheme provided by the invention, the recipe can be pertinently recommended to the user according to the user condition, the user experience is improved, and the healthy diet of the user is realized.
The present invention will be described in further detail with reference to the following application examples.
The embodiment provides a food material replacement scheme according to diet taboos of users. In the scheme, intelligent and accurate user healthy diet maintenance is realized through intelligent recipe data analysis.
Specifically, the intelligent menu can record the long-term eating habits and preferences of the user, and match the more scientific and healthy menu for the user. Such as: the user does not eat caraway, and the intelligent menu can avoid recommending any caraway matching to the user; for another example, when the user sets a period of weight loss, the smart recipe may recommend low-calorie food materials for the user, for example: purple sweet potato, chicken breast, beef and the like. I.e. replacing high calorie food with low calorie food material. In addition, the intelligent menu can push the corresponding menu to the user according to the recommendation of the food materials every day. Meanwhile, the shopping mall is matched to select and purchase fresh food materials in time, and the intelligent menu cooking video is pushed to teach the user to make food.
That is, the embodiment requires the user to perform the predefining, selecting, and setting, and then perform the dynamic adjustment according to the actual situation after collecting the work and rest, preference, and stage target set data of the user. I.e. a simple overview of the recommendation process may be: the user acquires the basic information of the user through intelligent recipe scene setting, and recommends recipes for the user through continuously accumulating user data so as to meet various dietary requirements of the user, such as food taboos, fat reduction stages, infant complementary food and the like. Rules such as data collection, intelligent menu pushing and the like are established based on the dietary requirements of users and families, and through continuous optimization decision of the intelligent menu, the intelligent menu does not need to be set in advance by the users, and taboo replacement of food materials and daily menus are automatically pushed.
Specifically, the recipe recommendation process may include the following:
content 1: and collecting intelligent menu data.
Various food material categories and corresponding cooking modes are collected, such as: vegetables: water spinach, shanghai green, etc., meat: chicken, beef, pork, etc., seasoning: light soy, oil, chicken essence, etc., low calorie food: chicken breast, cabbage, etc. to make graph and text menu and video menu for user.
Content 2: data recommendation and user information characteristic judgment.
The method comprises the steps of distinguishing and processing data and information input by a user, extracting user identity characteristics and user food preference, taboo food materials and special period requirements in the data, analyzing the data, finally recommending related required food materials for the user on the basis of the extracted user identity characteristics and the user food material preference, recommending alternative taboo food materials, and reporting results to a server through a data interface.
Content 3: the intelligent menu continuously carries out data accumulation and information updating.
The recipe has huge food material data volume, needs a background to continuously collect relevant information and update the information in time, and further needs to continuously make videos and image-text recipes so as to meet the requirements of users.
Content 4: the background classifies the user data.
Automatically matching related data in an intelligent menu according to the locally reported user identity and information, wherein the intelligent menu mainly comprises rules based on the age of the user, such as the old, children, adults and the like; rules aiming at the food material preference, taboo and special period of the user are included, such as fat-reducing period, gestational period, teenagers and the like; various recipe food material recommendation scheme rules and the like of the system are also included.
Content 5: and (4) intelligent recommendation.
The user identity data reported locally is collected and processed, periodic intelligent recommendation is carried out to meet the requirements of different users, meanwhile, various image-text menus, video menus and purchasing malls are established by the system, and different recommendations are set every day according to the selection of the users.
Content 6: and the user finishes the operation, and the system background exits.
Related food materials are not recommended repeatedly in the near term (within seven days), and the diversity of user selection is met.
According to the embodiment, various food materials and seasonings are equivalently replaced or avoided on the menu selected by the user through long-term user health information filing and data tracking collection of the intelligent home system, if the cola is normally matched with white granulated sugar, and the zero-degree cola replaces the white granulated sugar with aspartame, so that the food materials contraindicated by the user are avoided, a targeted recipe is provided for the user, and the user experience is improved. In addition, according to the method, the intelligent recipe is enabled to collect user habits and taboos according to the predefined, selected and set scenes, and corresponding replaceable food materials, purchasing ways and cooking modes can be intelligently recommended for the user; simultaneously with wisdom shopping mall, wisdom sleep linkage according to user's work and rest and data detection, recommends healthy diet scheme more intelligently, ensures that the user is healthy.
In order to implement the method according to the embodiment of the present invention, an embodiment of the present invention further provides a recipe recommendation device, as shown in fig. 2, a recipe recommendation device 200 includes: an acquisition module 201 and a recommendation module 202; wherein the content of the first and second substances,
an obtaining module 201, configured to obtain basic information input by a user and monitoring information of a related product;
and the recommending module 202 is used for recommending recipes according to the basic information and the monitoring information.
In an embodiment, the recommending module 202 is specifically configured to:
determining an initial recipe set according to the basic information;
optimizing the initial recipe set according to the monitoring information to determine an optimized recipe set;
and recommending the optimized recipe set to a user.
In an embodiment, the recommending module 202 is specifically configured to:
acquiring a first recipe set containing taboo food materials in a preset recipe and a second recipe set not containing the taboo food materials in the preset recipe, and determining the second recipe set as an initial recipe set;
alternatively, the first and second electrodes may be,
determining a second food material equivalent to the taboo food material, replacing the taboo food material in the preset recipe with the second food material, and determining the replaced recipe as an initial recipe set.
In an embodiment, the recommending module 202 is specifically configured to:
acquiring a third recipe set corresponding to the user state information in a preset recipe;
determining the third recipe set as an initial recipe set.
In an embodiment, the recommending module 202 is specifically configured to:
determining a fourth recipe set of the initial recipe set that is conducive to user sleep and a fifth recipe set of the initial recipe set that is detrimental to user sleep;
determining the sleep state of the user according to the monitoring information;
and adjusting the recommendation coefficient of the fourth recipe set and the recommendation coefficient of the fifth recipe set according to the sleep state.
In an embodiment, the recommending module 202 is specifically configured to:
determining the number of times of adoption of each recipe in the initial recipe set;
and adjusting the recommendation coefficient of the corresponding recipe according to the adoption times.
In an embodiment, the recommending module 202 is specifically configured to:
and recommending the cooking teaching materials of the recipe and the purchasing ways of the food materials in the recipe for the user.
In practical applications, the obtaining module 201 and the recommending module 202 may be implemented by a processor in the recipe recommending apparatus.
It should be noted that: the above-mentioned apparatus provided in the above-mentioned embodiment is only exemplified by the division of the above-mentioned program modules when executing, and in practical application, the above-mentioned processing may be distributed to be completed by different program modules according to needs, that is, the internal structure of the terminal is divided into different program modules to complete all or part of the above-mentioned processing. In addition, the apparatus provided by the above embodiment and the method embodiment belong to the same concept, and the specific implementation process thereof is described in the method embodiment and is not described herein again.
Based on the hardware implementation of the program module, in order to implement the method according to the embodiment of the present invention, an electronic device (computer device) is also provided in the embodiment of the present invention. Specifically, in one embodiment, the computer device may be a terminal, and its internal structure diagram may be as shown in fig. 3. The computer apparatus includes a processor a01, a network interface a02, a display screen a04, an input device a05, and a memory (not shown in the figure) connected through a system bus. Wherein processor a01 of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises an internal memory a03 and a non-volatile storage medium a 06. The nonvolatile storage medium a06 stores an operating system B01 and a computer program B02. The internal memory a03 provides an environment for the operation of the operating system B01 and the computer program B02 in the nonvolatile storage medium a 06. The network interface a02 of the computer device is used for communication with an external terminal through a network connection. The computer program is executed by the processor a01 to implement the method of any of the above embodiments. The display screen a04 of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device a05 of the computer device may be a touch layer covered on the display screen, a button, a trackball or a touch pad arranged on a casing of the computer device, or an external keyboard, a touch pad or a mouse.
Those skilled in the art will appreciate that the architecture shown in fig. 3 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
The device provided by the embodiment of the present invention includes a processor, a memory, and a program stored in the memory and capable of running on the processor, and when the processor executes the program, the method according to any one of the embodiments described above is implemented.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include transitory computer readable media (transmyedia) such as modulated data signals and carrier waves.
It will be appreciated that the memory of embodiments of the invention may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. Among them, the nonvolatile Memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a magnetic random access Memory (FRAM), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical disk, or a Compact Disc Read-Only Memory (CD-ROM); the magnetic surface storage may be disk storage or tape storage. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), Enhanced Synchronous Dynamic Random Access Memory (Enhanced DRAM), Synchronous Dynamic Random Access Memory (SLDRAM), Direct Memory (DRmb Access), and Random Access Memory (DRAM). The described memory for embodiments of the present invention is intended to comprise, without being limited to, these and any other suitable types of memory.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A recipe recommendation method, characterized in that the method comprises:
acquiring basic information input by a user and monitoring information of a related product;
and recommending recipes according to the basic information and the monitoring information.
2. The method of claim 1, wherein the recommending recipes according to the base information and the monitoring information comprises:
determining an initial recipe set according to the basic information;
optimizing the initial recipe set according to the monitoring information to determine an optimized recipe set;
and recommending the optimized recipe set to a user.
3. The method of claim 2, wherein the base information comprises a user contraindicated food material, and wherein determining the initial set of recipes from the base information comprises:
acquiring a first recipe set containing taboo food materials in a preset recipe and a second recipe set not containing the taboo food materials in the preset recipe, and determining the second recipe set as an initial recipe set;
alternatively, the first and second electrodes may be,
determining a second food material equivalent to the taboo food material, replacing the taboo food material in the preset recipe with the second food material, and determining the replaced recipe as an initial recipe set.
4. The method of claim 2, wherein the base information comprises user status information, and wherein determining an initial set of recipes from the base information comprises:
acquiring a third recipe set corresponding to the user state information in a preset recipe;
determining the third recipe set as an initial recipe set.
5. The method of claim 2, wherein the monitoring information includes sleep data, wherein the optimizing the initial recipe set based on the monitoring information, and wherein determining an optimized recipe set comprises:
determining a fourth recipe set of the initial recipe set that is conducive to user sleep and a fifth recipe set of the initial recipe set that is detrimental to user sleep;
determining the sleep state of the user according to the monitoring information;
and adjusting the recommendation coefficient of the fourth recipe set and the recommendation coefficient of the fifth recipe set according to the sleep state.
6. The method of claim 2, wherein the optimizing the initial recipe set based on the monitoring information, and wherein determining an optimized recipe set comprises:
determining the number of times of adoption of each recipe in the initial recipe set;
and adjusting the recommendation coefficient of the corresponding recipe according to the adoption times.
7. The method of claim 1, wherein after recommending recipes based on the base information and the monitoring information, the method further comprises:
and recommending the cooking teaching materials of the recipe and the purchasing ways of the food materials in the recipe for the user.
8. A recipe recommendation apparatus characterized in that the recipe recommendation apparatus comprises:
the acquisition module is used for acquiring basic information input by a user and monitoring information of related products;
and the recommending module is used for recommending recipes according to the basic information and the monitoring information.
9. An electronic device, comprising: a processor and a memory for storing a computer program capable of running on the processor; wherein the content of the first and second substances,
the processor is adapted to perform the steps of the method of any one of claims 1 to 7 when running the computer program.
10. A storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, performs the steps of the method of any one of claims 1 to 7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114329198A (en) * | 2021-12-27 | 2022-04-12 | 海信集团控股股份有限公司 | Method and device for recommending health information based on user sleep |
| CN115291782A (en) * | 2022-07-01 | 2022-11-04 | 宁波拓邦智能控制有限公司 | Method, system, computer readable medium and electronic device for automatically generating menu |
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| CN112182355A (en) * | 2019-07-02 | 2021-01-05 | 青岛海尔智能技术研发有限公司 | Recipe recommendation method and device and intelligent terminal |
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Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112182355A (en) * | 2019-07-02 | 2021-01-05 | 青岛海尔智能技术研发有限公司 | Recipe recommendation method and device and intelligent terminal |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114329198A (en) * | 2021-12-27 | 2022-04-12 | 海信集团控股股份有限公司 | Method and device for recommending health information based on user sleep |
| CN115291782A (en) * | 2022-07-01 | 2022-11-04 | 宁波拓邦智能控制有限公司 | Method, system, computer readable medium and electronic device for automatically generating menu |
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