CN116304309A - Recipe recommendation method and device, storage medium and electronic device - Google Patents
Recipe recommendation method and device, storage medium and electronic device Download PDFInfo
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Abstract
The application discloses a recipe recommendation method and device, a storage medium and an electronic device, and relates to the technical field of smart families, wherein the recipe recommendation method comprises the following steps: target food material information of food materials stored in a refrigerator, diet preference information of target objects and associated information are obtained, wherein the associated information of the target objects at least comprises: a state of health of the target subject; and determining a recommended recipe according to the target food material information, the diet preference information and the associated information of the target object, and pushing the recommended recipe to the target object. By adopting the technical scheme, the problem that the recipes recommended by the traditional method do not meet the diet requirements of users is solved.
Description
Technical Field
The application relates to the technical field of smart families, in particular to a recipe recommendation method and device, a storage medium and an electronic device.
Background
Along with the improvement of the living standard of people, people pay more attention to healthy diet, but most town workers are busy working every day, and do not have time to match recipes according to foods in the refrigerator, so that the foods in the refrigerator do not exert the maximum value.
In addition, refrigerator recipes in the market are generally recommended through a mobile phone APP, names of foods to be eaten are input at the APP end, and recipes are searched through the Internet. The recommended recipes are not combined with the really willing to eat, and the recommended recipes are mostly unsatisfactory.
Aiming at the problem that the recipes recommended by the traditional method do not meet the diet requirements of users in the related technology, no effective solution is proposed at present.
Accordingly, there is a need for improvements in the related art to overcome the drawbacks of the related art.
Disclosure of Invention
The embodiment of the invention provides a recipe recommendation method and device, a storage medium and an electronic device, which are used for at least solving the problem that a recipe recommended by a traditional method does not meet the diet requirement of a user.
According to an aspect of the embodiment of the present invention, there is provided a recipe recommendation method, including: target food material information of food materials stored in a refrigerator, diet preference information of target objects and associated information are obtained, wherein the associated information of the target objects at least comprises: a state of health of the target subject; and determining a recommended recipe according to the target food material information, the diet preference information and the associated information of the target object, and pushing the recommended recipe to the target object.
In an exemplary embodiment, determining a recommended recipe from the target food material information, the dietary preference information of the target object, and the association information includes: determining whether food material information of a first food material is included in the target food material information when a diet request of a target object is acquired and the diet request is used for indicating to eat the first food material; determining a recommended recipe related to the first food material according to the diet preference information and the related information of the target object when the food material information of the first food material is included in the target food material information; and under the condition that the target food material information does not have the food material information of the first food material, determining a second food material according to the target food material information, and determining a recommended recipe related to the second food material according to the diet preference information and the associated information of the target object.
In an exemplary embodiment, determining a second food material from the target food material information includes: determining a plurality of food materials stored in the refrigerator according to the target food material information, and determining a food material with highest similarity with the first food material in the plurality of food materials as a second food material; or determining a second food material from the plurality of food materials according to the diet preference information, wherein the diet preference information comprises the food material preferred by the target object; or determining a second food material from the plurality of food materials according to the association information.
In an exemplary embodiment, in a case where a target food material is the first food material or the second food material, determining a recommended recipe related to the target food material according to diet preference information and association information of the target object includes: determining a plurality of first reference recipes according to the target food material and the associated information; determining one or more recommended recipes from the plurality of first reference recipes according to the diet preference information; wherein the diet preference information further comprises: and the taste preferred by the target object and the menu preferred by the target object.
In an exemplary embodiment, determining a recommended recipe from the target food material information, the dietary preference information of the target object, and the association information includes: determining a plurality of second reference recipes according to the food materials recorded in the target food material information; determining a score for each of the plurality of second reference recipes based on the diet preference information and the association information; one or more recommended recipes having scores greater than a preset threshold value are determined from the plurality of second reference recipes.
In an exemplary embodiment, determining a recommended recipe from the target food material information, the dietary preference information of the target object, and the association information includes: acquiring an object set with an association relation with the target object, and acquiring diet preference information and association information of each object in the object set; and determining a recommended recipe according to the target food material information, the diet preference information and the associated information of the target objects, and the diet preference information and the associated information of each object in the object set.
In an exemplary embodiment, determining a recommended recipe from the target food material information, the dietary preference information of the target object, and the association information includes: obtaining a recipe recommendation model, wherein the recipe recommendation model is a model obtained through training of a plurality of groups of sample data; and inputting the target food material information, the diet preference information and the associated information of the target object into the recipe recommendation model to obtain the recommended recipes.
According to another aspect of the embodiment of the present invention, there is also provided a recipe recommendation apparatus including: the acquisition module is used for acquiring target food material information of food materials stored in the refrigerator, diet preference information of target objects and associated information, wherein the associated information of the target objects at least comprises: a state of health of the target subject; and the recommending module is used for determining a recommended recipe according to the target food material information, the diet preference information and the associated information of the target object and pushing the recommended recipe to the target object.
According to a further aspect of embodiments of the present invention, there is also provided a computer readable storage medium having a computer program stored therein, wherein the computer program is arranged to perform the above-described recipe recommendation method when run.
According to still another aspect of the embodiments of the present invention, there is further provided an electronic device including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the recipe recommendation method through the computer program.
According to the invention, target food material information of food materials stored in the refrigerator, diet preference information of target objects and associated information are obtained, wherein the associated information of the target objects at least comprises: a state of health of the target subject; and determining a recommended recipe according to the target food material information, the diet preference information and the associated information of the target object, and pushing the recommended recipe to the target object. According to the method and the device, when the recipes are recommended, the target food material information of the food materials stored in the refrigerator, the diet preference information of the target objects and the associated information are comprehensively considered, so that the recommended recipes can meet the diet requirements of users, the diet experience of the users is improved, and the problem that the recipes recommended by the traditional method in the related technology do not meet the diet requirements of the users is solved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in 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 a hardware environment of a recipe recommendation method according to an embodiment of the present application;
FIG. 2 is a flow chart of a recipe recommendation method according to an embodiment of the present invention;
FIG. 3 is a block diagram of a recipe recommendation system according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a recipe recommendation method according to an embodiment of the present invention;
fig. 5 is a block diagram of a recipe recommendation device according to an embodiment of the present invention.
Detailed Description
In order to make the present application solution better understood by those skilled in the art, the following description will be made in detail and with reference to the accompanying drawings in the embodiments of the present application, it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that embodiments of the present application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
According to one aspect of the embodiments of the present application, a recipe recommendation method is provided. The recipe recommendation method is widely applied to full-house intelligent digital control application scenes such as Smart Home (Smart Home), intelligent Home equipment ecology, intelligent Home (intelligent house) ecology and the like. Alternatively, in the present embodiment, the recipe recommendation method described above may be applied to a hardware environment constituted by the terminal device 102 and the server 104 as shown in fig. 1. As shown in fig. 1, the server 104 is connected to the terminal device 102 through a network, and may be used to provide services (such as application services and the like) for a terminal or a client installed on the terminal, a database may be set on the server or independent of the server, for providing data storage services for the server 104, and cloud computing and/or edge computing services may be configured on the server or independent of the server, for providing data computing services for the server 104.
The network may include, but is not limited to, at least one of: wired network, wireless network. The wired network may include, but is not limited to, at least one of: a wide area network, a metropolitan area network, a local area network, and the wireless network may include, but is not limited to, at least one of: WIFI (Wireless Fidelity ), bluetooth. The terminal device 102 may not be limited to a PC, a mobile phone, a tablet computer, an intelligent air conditioner, an intelligent smoke machine, an intelligent refrigerator, an intelligent oven, an intelligent cooking range, an intelligent washing machine, an intelligent water heater, an intelligent washing device, an intelligent dish washer, an intelligent projection device, an intelligent television, an intelligent clothes hanger, an intelligent curtain, an intelligent video, an intelligent socket, an intelligent sound box, an intelligent fresh air device, an intelligent kitchen and toilet device, an intelligent bathroom device, an intelligent sweeping robot, an intelligent window cleaning robot, an intelligent mopping robot, an intelligent air purifying device, an intelligent steam box, an intelligent microwave oven, an intelligent kitchen appliance, an intelligent purifier, an intelligent water dispenser, an intelligent door lock, and the like.
In order to solve the above-mentioned problems, a recipe recommendation method is provided in the present embodiment, including but not limited to being applied to the server 104, and fig. 2 is a flowchart of a recipe recommendation method according to an embodiment of the present invention, the flowchart including the following steps:
step S202, obtaining target food material information of food materials stored in a refrigerator, diet preference information of a target object, and association information, wherein the association information of the target object at least includes: a state of health of the target subject;
the target object is a user who uses the refrigerator. The health status of a target subject includes what kind of disease the target subject has, and so on.
As an optional example, the association information of the target object further includes: the target subject's diet plan over a preset period of time (e.g., the user's diet plan for the future week, including the foods to be consumed for the future week, the type of food, etc.).
In an exemplary embodiment, the above step S202 may be implemented by the following steps S11-S13:
step S11: acquiring food material information of storage food materials reported by the refrigerator each time, wherein the food material information of storage food materials is information detected by the refrigerator in the process of storing storage food materials to the refrigerator, and the food material information at least comprises: the name of the stored food material, the type of the food material, the freshness and the optimal use time; the target food material information comprises the food material information for storing food materials;
step S12: obtaining diet preference information reported by the target object through the mobile terminal and/or determining the diet preference information according to the historical diet record of the target object, wherein the diet preference information comprises the following components: preference for cuisine, preference for taste, preference for food material;
step S13: and acquiring the association information reported by the target object through the mobile terminal.
It should be noted that, the steps S11, S12, and S13 are executed in no sequence.
Step S204, determining a recommended recipe according to the target food material information, the diet preference information and the association information of the target object, and pushing the recommended recipe to the target object.
In an exemplary embodiment, pushing the recommended recipe to the target object may be achieved by at least one of:
mode one: pushing the recommended recipe to the refrigerator;
mode two: pushing the recommended recipes to the mobile terminal of the target object;
as an alternative example, mobile terminals include, but are not limited to: cell phones, tablet computers, etc.
Mode three: pushing the recommended recipes to the household equipment nearest to the target object;
as an alternative example, after receiving a recommended recipe, a refrigerator, or a mobile terminal, or a home device may present the recommended recipe to the target object by: text scrolling, voice broadcasting and video broadcasting.
As an alternative example, after determining the recommended recipe, if there is food material in the recommended recipe that is not present in the refrigerator, the absent food material is actively ordered for purchase after the authorization of the target object can be acquired.
In an exemplary embodiment, the determining the recommended recipe according to the target food material information, the dietary preference information of the target object, and the associated information may be implemented by the following steps S21-S23:
step S21: determining whether food material information of a first food material is included in the target food material information when a diet request of a target object is acquired and the diet request is used for indicating to eat the first food material;
as an alternative example, the presentation of the diet request includes, but is not limited to, speech. The target food material information has food material information of all food materials stored in the refrigerator. The food material information at least comprises: the name of the food material, the type of food material, freshness, optimal use time, etc.
Step S22: determining a recommended recipe related to the first food material according to the diet preference information and the related information of the target object when the food material information of the first food material is included in the target food material information;
step S23: and under the condition that the target food material information does not have the food material information of the first food material, determining a second food material according to the target food material information, and determining a recommended recipe related to the second food material according to the diet preference information and the associated information of the target object.
In an exemplary embodiment, determining the second food material according to the target food material information may be achieved by the following step S31, or step S32, or step S33:
step S31: determining a plurality of food materials stored in the refrigerator according to the target food material information, and determining a food material with highest similarity with the first food material in the plurality of food materials as a second food material;
as an alternative example, the similarity between two food materials may be comprehensively determined according to the kind of food materials, the eating manner of the food materials, the nutritional ingredients, and the like. For example, chicken and duck meat have a high degree of similarity. The mushrooms and the hypsizigus marmoreus have higher similarity.
Step S32: determining a second food material from the plurality of food materials according to the diet preference information, wherein the diet preference information comprises the food material preferred by the target object;
for example, the target object prefers to eat tomatoes, then determines whether tomatoes are present from a plurality of food materials, and if so, treats tomatoes as a second food material.
Step S33: and determining a second food material from the plurality of food materials according to the association information.
For example, a second food material that is beneficial to the physical health of the target object may be determined from a plurality of food materials. For example, if the association information indicates that the target object has diabetes, the high-fiber food, or the low-sugar vegetables, or the selenium-rich food may be determined as the second food from the plurality of food materials.
In an exemplary embodiment, in a case where the target food material is the first food material or the second food material, determining the recommended recipe related to the target food material according to the diet preference information and the association information of the target object may be achieved by the following steps S41 to S42:
step S41: determining a plurality of first reference recipes according to the target food material and the associated information;
as an alternative example, the first reference recipe includes a plurality of food materials (a main food material and an auxiliary food material), and the main food material in the first reference recipe is the target food material.
Step S42: determining one or more recommended recipes from the plurality of first reference recipes according to the diet preference information; wherein the diet preference information further comprises: and the taste preferred by the target object and the menu preferred by the target object.
That is, in the above steps S41 to S42, a plurality of first reference recipes that are beneficial to the physical health of the user may be determined based on the association information and the target food material, and then one or more recommended recipes may be determined from the plurality of first reference recipes based on the diet preference information of the target subject. By adopting the scheme, the recommended recipe can meet the diet requirement of the user while guaranteeing the diet health of the user.
In an exemplary embodiment, determining the recommended recipe according to the target food material information, the dietary preference information of the target object, and the associated information may further be implemented according to the following steps S51-S53:
step S51: determining a plurality of second reference recipes according to the food materials recorded in the target food material information;
that is, the plurality of second reference recipes may be determined according to existing combinations of food materials in the refrigerator.
Step S52: determining a score for each of the plurality of second reference recipes based on the diet preference information and the association information;
step S53: one or more recommended recipes having scores greater than a preset threshold value are determined from the plurality of second reference recipes.
In an exemplary embodiment, the determining the recommended recipe according to the target food material information, the diet preference information of the target object, and the associated information may further be implemented according to the following steps S61-S62:
step S61: acquiring an object set with an association relation with the target object, and acquiring diet preference information and association information of each object in the object set;
as an alternative example, the objects in the set of objects may be objects that live with, eat with, etc. the target object, e.g., the family of the target object, etc.
Step S62: and determining a recommended recipe according to the target food material information, the diet preference information and the associated information of the target objects, and the diet preference information and the associated information of each object in the object set.
In this embodiment, when recommending a recipe, the target diet preference information and the associated information of the target diet together with the target are also comprehensively considered, so that the determined recommended recipe can meet the diet requirement of the group.
In an exemplary embodiment, the determining the recommended recipe according to the target food material information, the diet preference information of the target object, and the associated information may be further implemented according to the following steps S71-S72:
step S71: obtaining a recipe recommendation model, wherein the recipe recommendation model is a model obtained through training of a plurality of groups of sample data;
as an alternative example, the recipe recommendation model is a deep learning model that includes, but is not limited to, being implemented by a convolutional neural network or a recurrent neural network.
As an alternative example, each set of sample data in the plurality of sets of sample data includes: sample food material information, sample diet preference information, sample association information, and sample recommended recipes.
Step S72: and inputting the target food material information, the diet preference information and the associated information of the target object into the recipe recommendation model to obtain the recommended recipes.
In this embodiment, the deep learning model can more intelligently and accurately recommend recipes for the target object.
As an alternative example, during the process of pushing the recommended recipes to the target object, the common recipes of other objects may also be pushed to the target object, so that the target object may select the diet manner of trying other objects.
As an alternative example, pushing the recommended recipe to the target object includes: pushing the recommended recipes to the target object according to dimensions, wherein the dimensions comprise: cuisine, taste, dietary health, and the like.
It will be apparent that the embodiments described above are merely some, but not all, embodiments of the invention. For better understanding of the above method, the following description will explain the above process with reference to the examples, but is not intended to limit the technical solution of the embodiments of the present invention, specifically:
in an alternative embodiment, the present application further provides a recipe recommendation system, and fig. 3 is a frame diagram of the recipe recommendation system according to an embodiment of the present invention, and as shown in fig. 3, the recipe recommendation system is composed of three subsystems, namely, a refrigerator terminal, a recommendation system, and a mobile phone terminal.
The refrigerator terminal comprises three modules, namely an image acquisition module, a recipe display module and a recipe management module, wherein the image acquisition module is used for acquiring food image data, food is aligned to a photoreceptor before being put into a refrigerator, and after a 'beep' sound is heard, the refrigerator terminal is used for indicating that the information of the type, the freshness, the optimal eating time and the like of the food is uploaded to a recommendation system. The recipe display module is used for displaying the recipes pushed by the recommendation system, and has three forms of text carousel, voice broadcast and video broadcast. The recipe management module is used for managing the recipes of the user, the recommended recipes can be added into the common recipes and then are recommended preferentially, and the weekly recipes can be formulated, so that the recipes can be managed conveniently.
The recommendation system comprises two modules of deep learning and recipe recommendation. The deep learning module performs deep learning on food and user preferences by mainly using a deep neural network, particularly a convolutional neural network or a recurrent neural network which is widely applied in NLP. The recipe recommendation module pushes the deep learning result to the user according to the preference of the user, and the method has three recommendation forms of keywords, cuisines and health-preserving recipes, so that different consumer groups are satisfied.
The mobile phone terminal comprises three modules, namely preference setting, user data and user recipes. The user can set his own preferences through preference settings, such as wanting to eat spicy, yue-cai, liver-protecting recipes, etc. The user data module is used for inputting basic information of a user, such as a physical examination report of the user in the last half year or a diet work and rest plan of the user in the last week, and the data are used for recipe recommendation after being uploaded to the recommendation system for deep learning. The user recipe module is used for associating user recipes and can customize different recipes for different people in the family.
As an alternative example, fig. 4 is a schematic diagram of a recipe recommendation method according to an embodiment of the present invention, as shown in fig. 4, specifically having the following steps: 1. food material images are acquired through the refrigerator terminal, and acquired data are uploaded to a recommendation system; 2. setting user preferences, wherein the user preferences comprise three dimensions of taste, cuisine and health preserving recipes, and the user preferences are used for deep learning after uploading a recommendation system; 3. associating user data, the user data comprising physical examination reports or diet work and rest plans; 4. deep neural networks, particularly convolutional neural networks or recurrent neural networks with wider application range in NLP (non-linear point) are used for deep learning of food, user preference and user data, and training is repeated; 5. intelligent recommendation is carried out according to the set user preference, keywords and user data; 6. the recipe display specifically comprises three modes of text scrolling, voice broadcasting and video, and supports repeated broadcasting; 7. the refrigerator terminal can send the pushing recipes to the mobile phone terminal at the same time after receiving the pushing recipes, so that multi-end recipe sharing is realized; 8. and the user associates the user recipes of the family at the mobile phone end to conduct diversified recipe recommendation.
According to the recipe recommendation method, recipes can be recommended to the user in a personalized mode according to user preferences and user data, body requirements can be timely supplemented, and the diet experience and physical and mental health of the user are greatly improved.
From the description of the above embodiments, it will be clear to a person skilled in the art that the method according to the above embodiments may be implemented by means of software plus the necessary general hardware platform, but of course also by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method of the various embodiments of the present invention.
In this embodiment, a recipe recommendation device is further provided, and the device is used to implement the foregoing embodiments and preferred embodiments, and is not described in detail. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the devices described in the following embodiments are preferably implemented in software, implementations in hardware, or a combination of software and hardware, are also possible and contemplated.
Fig. 5 is a block diagram showing a configuration of a recipe recommendation apparatus according to an embodiment of the present invention, the apparatus including:
an obtaining module 52, configured to obtain target food material information of a food material stored in a refrigerator, diet preference information of a target object, and association information, where the association information of the target object at least includes: a state of health of the target subject;
the recommendation module 54 is configured to determine a recommended recipe according to the target food material information, the diet preference information of the target object, and the association information, and push the recommended recipe to the target object.
Through the device, the target food material information of the food material stored in the refrigerator, the diet preference information of the target object and the associated information are obtained, wherein the associated information of the target object at least comprises: a state of health of the target subject; and determining a recommended recipe according to the target food material information, the diet preference information and the associated information of the target object, and pushing the recommended recipe to the target object. According to the method and the device, when the recipes are recommended, the target food material information of the food materials stored in the refrigerator, the diet preference information of the target objects and the associated information are comprehensively considered, so that the recommended recipes can meet the diet requirements of users, the diet experience of the users is improved, and the problem that the recipes recommended by the traditional method in the related technology do not meet the diet requirements of the users is solved.
In an exemplary embodiment, the recommendation module 54 includes a first determining unit configured to determine, when a diet request of a target object is acquired and the diet request is used to indicate eating a first food material, whether food material information of the first food material is included in the target food material information; determining a recommended recipe related to the first food material according to the diet preference information and the related information of the target object when the food material information of the first food material is included in the target food material information; and under the condition that the target food material information does not have the food material information of the first food material, determining a second food material according to the target food material information, and determining a recommended recipe related to the second food material according to the diet preference information and the associated information of the target object.
In an exemplary embodiment, the first determining unit is configured to determine the second food material according to the target food material information by: determining a plurality of food materials stored in the refrigerator according to the target food material information, and determining a food material with highest similarity with the first food material in the plurality of food materials as a second food material; or determining a second food material from the plurality of food materials according to the diet preference information, wherein the diet preference information comprises the food material preferred by the target object; or determining a second food material from the plurality of food materials according to the association information.
In an exemplary embodiment, the first determining unit is configured to determine, when the target food material is the first food material or the second food material, a recommended recipe related to the target food material according to the dietary preference information and the association information of the target object by: determining a plurality of first reference recipes according to the target food material and the associated information; determining one or more recommended recipes from the plurality of first reference recipes according to the diet preference information; wherein the diet preference information further comprises: and the taste preferred by the target object and the menu preferred by the target object.
In an exemplary embodiment, the recommendation module 54 includes a second determining unit configured to determine a plurality of second reference recipes according to the food materials recorded in the target food material information; determining a score for each of the plurality of second reference recipes based on the diet preference information and the association information; one or more recommended recipes having scores greater than a preset threshold value are determined from the plurality of second reference recipes.
In an exemplary embodiment, the recommendation module 54 includes a third determining unit, configured to obtain a set of objects having an association relationship with the target object, and obtain diet preference information and association information of each object in the set of objects; and determining a recommended recipe according to the target food material information, the diet preference information and the associated information of the target objects, and the diet preference information and the associated information of each object in the object set.
In an exemplary embodiment, the recommendation module 54 includes a fourth determining unit, configured to obtain a recipe recommendation model, where the recipe recommendation model is a model obtained by training multiple sets of sample data; and inputting the target food material information, the diet preference information and the associated information of the target object into the recipe recommendation model to obtain the recommended recipes.
Embodiments of the present invention also provide a computer readable storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the method embodiments described above when run.
Alternatively, in the present embodiment, the above-described storage medium may be configured to store a computer program for performing the steps of:
s1, acquiring target food material information of food materials stored in a refrigerator, diet preference information of a target object and associated information, wherein the associated information of the target object at least comprises: a state of health of the target subject;
s2, determining a recommended recipe according to the target food material information, the diet preference information and the association information of the target object, and pushing the recommended recipe to the target object.
In one exemplary embodiment, the computer readable storage medium may include, but is not limited to: a usb disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing a computer program.
Specific examples in this embodiment may refer to the examples described in the foregoing embodiments and the exemplary implementation, and this embodiment is not described herein.
An embodiment of the invention also provides an electronic device comprising a memory having stored therein a computer program and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.
Alternatively, in the present embodiment, the above-described processor may be configured to execute the following steps by a computer program:
s1, acquiring target food material information of food materials stored in a refrigerator, diet preference information of a target object and associated information, wherein the associated information of the target object at least comprises: a state of health of the target subject;
s2, determining a recommended recipe according to the target food material information, the diet preference information and the association information of the target object, and pushing the recommended recipe to the target object.
In an exemplary embodiment, the electronic apparatus may further include a transmission device connected to the processor, and an input/output device connected to the processor.
Specific examples in this embodiment may refer to the examples described in the foregoing embodiments and the exemplary implementation, and this embodiment is not described herein.
It will be appreciated by those skilled in the art that the modules or steps of the invention described above may be implemented in a general purpose computing device, they may be concentrated on a single computing device, or distributed across a network of computing devices, they may be implemented in program code executable by computing devices, so that they may be stored in a storage device for execution by computing devices, and in some cases, the steps shown or described may be performed in a different order than that shown or described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple modules or steps of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The foregoing is merely a preferred embodiment of the present application and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present application and are intended to be comprehended within the scope of the present application.
Claims (10)
1. A recipe recommendation method, comprising:
target food material information of food materials stored in a refrigerator, diet preference information of target objects and associated information are obtained, wherein the associated information of the target objects at least comprises: a state of health of the target subject; and determining a recommended recipe according to the target food material information, the diet preference information and the associated information of the target object, and pushing the recommended recipe to the target object.
2. The recipe recommendation method according to claim 1, wherein determining a recommended recipe from the target food material information, the diet preference information of the target object, and the association information, comprises:
determining whether food material information of a first food material is included in the target food material information when a diet request of a target object is acquired and the diet request is used for indicating to eat the first food material;
determining a recommended recipe related to the first food material according to the diet preference information and the related information of the target object when the food material information of the first food material is included in the target food material information;
and under the condition that the target food material information does not have the food material information of the first food material, determining a second food material according to the target food material information, and determining a recommended recipe related to the second food material according to the diet preference information and the associated information of the target object.
3. The recipe recommendation method according to claim 2, wherein determining a second food item from the target food item information comprises:
determining a plurality of food materials stored in the refrigerator according to the target food material information, and determining a food material with highest similarity with the first food material in the plurality of food materials as a second food material; or (b)
Determining a second food material from the plurality of food materials according to the diet preference information, wherein the diet preference information comprises the food material preferred by the target object; or (b)
And determining a second food material from the plurality of food materials according to the association information.
4. The recipe recommendation method according to claim 2, wherein, in a case where a target food material is the first food material or the second food material, determining a recommended recipe related to the target food material from diet preference information and association information of the target object, comprises:
determining a plurality of first reference recipes according to the target food material and the associated information;
determining one or more recommended recipes from the plurality of first reference recipes according to the diet preference information; wherein the diet preference information further comprises: and the taste preferred by the target object and the menu preferred by the target object.
5. The recipe recommendation method according to claim 1, wherein determining a recommended recipe from the target food material information, the diet preference information of the target object, and the association information, comprises:
determining a plurality of second reference recipes according to the food materials recorded in the target food material information;
determining a score for each of the plurality of second reference recipes based on the diet preference information and the association information;
one or more recommended recipes having scores greater than a preset threshold value are determined from the plurality of second reference recipes.
6. The recipe recommendation method according to claim 1, wherein determining a recommended recipe from the target food material information, the diet preference information of the target object, and the association information, comprises:
acquiring an object set with an association relation with the target object, and acquiring diet preference information and association information of each object in the object set;
and determining a recommended recipe according to the target food material information, the diet preference information and the associated information of the target objects, and the diet preference information and the associated information of each object in the object set.
7. The recipe recommendation method according to claim 1, wherein determining a recommended recipe from the target food material information, the diet preference information of the target object, and the association information, comprises:
obtaining a recipe recommendation model, wherein the recipe recommendation model is a model obtained through training of a plurality of groups of sample data;
and inputting the target food material information, the diet preference information and the associated information of the target object into the recipe recommendation model to obtain the recommended recipes.
8. A recipe recommendation device, comprising:
the acquisition module is used for acquiring target food material information of food materials stored in the refrigerator, diet preference information of target objects and associated information, wherein the associated information of the target objects at least comprises: a state of health of the target subject;
and the recommending module is used for determining a recommended recipe according to the target food material information, the diet preference information and the associated information of the target object and pushing the recommended recipe to the target object.
9. A computer-readable storage medium, characterized in that the computer-readable storage medium comprises a stored program, wherein the program when run performs the method of any one of claims 1 to 7.
10. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the method according to any of claims 1 to 7 by means of the computer program.
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| CN202310139253.6A CN116304309A (en) | 2023-02-07 | 2023-02-07 | Recipe recommendation method and device, storage medium and electronic device |
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| CN202310139253.6A CN116304309A (en) | 2023-02-07 | 2023-02-07 | Recipe recommendation method and device, storage medium and electronic device |
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