CN110287306B - Recipe recommendation method and equipment - Google Patents
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- CN110287306B CN110287306B CN201910562158.0A CN201910562158A CN110287306B CN 110287306 B CN110287306 B CN 110287306B CN 201910562158 A CN201910562158 A CN 201910562158A CN 110287306 B CN110287306 B CN 110287306B
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Abstract
The application provides a recipe recommendation method and device which are used for flexibly recommending recipes for users. The recipe recommendation method comprises the following steps: acquiring food material information; generating a recipe according to the food material information and the food material knowledge graph; the food material knowledge graph comprises at least two nodes and a relation between every two nodes in the at least two nodes, and each node in the at least two nodes represents a food material; and recommending the recipe to the user.
Description
Technical Field
The present application relates to the field of electronic technologies, and in particular, to a recipe recommendation method and apparatus.
Background
At present, many intelligent devices such as a range hood, a refrigerator or a mobile terminal (a smart phone, a tablet computer and the like) have a recipe recommendation function, and great convenience is brought to life of people.
And when the existing intelligent equipment recommends a recipe, the intelligent equipment can recommend the recipe to the user only when the obtained food material information meets the food material requirements of the recipe. For example, the food materials required for the recipe corresponding to tomato scrambled eggs are: tomato 4, egg 3, shallot are a plurality of, and when the edible material that the smart machine acquireed is egg 2, tomato 1, just can't recommend the recipe to the user. However, in the actual operation process, the tomato fried eggs can be made under the condition that 2 eggs and 1 tomato exist, or other dishes can be made by using 2 eggs and 1 tomato.
Therefore, the recipe recommendation mode in the prior art is mechanical and lacks flexibility.
Disclosure of Invention
The embodiment of the application provides a recipe recommendation method and device, which are used for providing a flexible recipe recommendation mode and improving user experience.
In a first aspect, the present application provides a recipe recommendation method, including:
acquiring food material information;
generating a recipe according to the food material information and the food material knowledge graph; the food material knowledge graph comprises at least two nodes and a relation between every two nodes in the at least two nodes, and each node in the at least two nodes represents a food material;
and recommending the recipe to the user.
In the embodiment of the application, the food material knowledge graph comprises the corresponding relation among food materials, so that diversified collocation modes among the food materials are guaranteed, a recipe can be flexibly recommended to a user, the food material knowledge graph is not limited to the existing recipe any more, and the experience degree of the user can be improved.
In one possible design, the relationship between each two nodes includes one or more of the following relationships:
the ratio between the food materials represented by each two nodes is determined; or
The recommendation index of collocation between the food materials represented by each two nodes; or
And the cooking modes, the cooking tools, the cooking duration and the cooking duration of the food materials represented by every two nodes.
The relationship between every two nodes is only an example, and other relationships, such as a nutrition index between the food materials characterized by every two nodes, a gram index between the food materials characterized by every two nodes, and the like, may also be included.
In one possible design, generating a recipe according to the food material information and the food material knowledge graph includes:
acquiring identity information of a user;
determining a food material knowledge graph corresponding to the identity information;
and generating a recipe according to the food material information and the food material knowledge graph corresponding to the identity information.
In this embodiment of the application, the identity information of the user may be acquired by an image acquisition unit disposed on an electronic device connected to the server. The identity information of the user may be an identity card (ID) of the user, fingerprint information of the user, or palm print information of the user, or other information capable of characterizing the identity of the user.
In the embodiment of the application, the recipe is generated according to the food material knowledge graph corresponding to the identity information, the recipe can be recommended to the user more accurately, and the experience degree of the user is improved.
In one possible design, the method further includes:
when new food material information is obtained, the new food material information is added to the food material knowledge graph to obtain an updated food material knowledge graph.
In the embodiment of the application, the food material knowledge graph is updated according to the newly acquired food material information, so that a better recipe is recommended for the user. In a specific implementation process, the food material knowledge graph can be updated according to a preset time interval.
In one possible design, generating a recipe according to the food material information and the food material knowledge graph includes:
acquiring batching information;
and generating a recipe according to the food material information, the ingredient information and the food material knowledge graph.
In the embodiment of the application, the existing ingredient information of the user can be obtained, and the recipe is generated according to the ingredient information, the food material information and the food material knowledge graph. So as to avoid the ingredients in the recipe recommended to the user, and the user does not buy the recipe or add the recipe, which brings inconvenience to the user.
In a second aspect, an embodiment of the present application further provides a server, including:
an acquisition unit for acquiring food material information;
the generating unit is used for generating a recipe according to the food material information and the food material knowledge graph; the food material knowledge graph comprises at least two nodes and a relation between every two nodes in the at least two nodes, and each node in the at least two nodes represents a food material;
and the recommending unit is used for recommending the recipe to the user.
In one possible design, the relationship between each two nodes includes one or more of the following relationships:
the ratio between the food materials represented by each two nodes is determined; or
The recommendation index of collocation between the food materials represented by each node; or
And the cooking modes, the cooking tools, the cooking duration and the cooking duration of the food materials represented by every two nodes.
In one possible design, when the generating unit generates the recipe according to the food material information and the food material knowledge graph, the generating unit is specifically configured to:
acquiring identity information of a user;
determining a food material knowledge graph corresponding to the identity information;
and generating a recipe according to the food material information and the food material knowledge graph corresponding to the identity information.
In one possible design, the server further includes:
the adding unit is used for adding the new food material information to the food material knowledge graph when new food material information is obtained so as to obtain an updated food material knowledge graph.
In one possible design, when the generating unit generates the recipe according to the food material information and the food material knowledge graph, the generating unit is specifically configured to:
acquiring batching information;
and generating a recipe according to the food material information, the ingredient information and the food material knowledge graph.
In a third aspect, an embodiment of the present application further provides a server, including: a memory to store instructions; at least one processor configured to read instructions from the memory to implement the method as performed by the server in the first aspect or any one of the possible designs of the first aspect.
In a fourth aspect, there is provided a computer storage medium storing computer software instructions for an electronic device as described in the second aspect or a server as described in the third aspect, and containing a program designed for the server to perform any one of the possible designs of the first aspect or the first aspect.
Drawings
Fig. 1 is a schematic diagram of an application scenario provided in an embodiment of the present application;
fig. 2 is a schematic flowchart of a recipe recommendation method provided in the present application;
fig. 3 is a schematic view of a food material knowledge graph provided in the present application;
fig. 4 is a schematic structural diagram of a server provided in the present application;
fig. 5 is a schematic structural diagram of another server provided in the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
Hereinafter, some terms in the embodiments of the present application are explained to facilitate understanding by those skilled in the art.
(1) The intelligent device can be a household intelligent device, such as a refrigerator and a range hood; may be a portable device such as, by way of example, a mobile phone, a tablet computer, a notebook computer, etc.
(2) The knowledge graph is a data structure based on a graph and consists of nodes (points) and edges (edges). In the knowledge-graph, each node represents an "entity" existing in the real world, and each edge is a "relationship" between entities.
(3) The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship, unless otherwise specified. Also, in the description of the embodiments of the present application, the terms "first," "second," and the like are used for descriptive purposes only and are not intended to indicate or imply relative importance nor order to indicate or imply order.
Referring to fig. 1, an application scenario provided by the present application includes a smart device 101 (a refrigerator, a range hood, a mobile terminal) and a server 102. The intelligent equipment collects food material information and uploads the food material information to the cloud server, and the cloud server generates a recipe according to the food material information.
The technical solutions provided by the embodiments of the present application are described below with reference to the accompanying drawings. In the following description, the technical solution provided by the present application is applied to the application scenario shown in fig. 1 as an example.
Referring to fig. 2, a recipe recommendation method according to an embodiment of the present application is described as follows:
s201: acquiring food material information;
in the embodiment of the application, the server receives the food material information uploaded by the intelligent device. Wherein, the smart device may receive a trigger instruction from the user, for example, "can do tomato stir-frying? And when the voice command of ' or ' what dish I can do ', food material information is collected.
When the smart device is a refrigerator, the refrigerator may collect food material information in the refrigerator through an image collecting unit, such as a camera, where the food material information includes the number and the kind of the existing food materials in the refrigerator, such as three tomatoes, two eggs, and the like. In a specific implementation process, the refrigerator can also measure the weight of food materials in the refrigerator through a built-in weight sensor, and then the collected food material information is uploaded to a server.
When the intelligent device is a range hood, an induction cooker or a mobile terminal, the range hood, the induction cooker or the mobile terminal can collect food material information placed on a cooking bench through an image collecting unit, the food material information comprises the number and the type of the existing food materials on the cooking bench, and then the food material information is uploaded to a server.
Certainly, in the embodiment of the application, the intelligent device may also receive the food material information input by the user, and then upload the food material information to the server. The input mode of the user includes, but is not limited to, handwriting input or voice input.
S202: generating a recipe according to the food material information and the food material knowledge graph; the food material knowledge graph comprises at least two nodes and a relation between every two nodes of the at least two nodes, and each node of the at least two nodes represents a food material.
Referring to fig. 3, a food material knowledge graph provided by the present application includes at least two nodes and a relationship between every two nodes of the at least two nodes. Wherein each of the at least two nodes represents a food material, such as eggs, fish, peppers, cucumbers, tomatoes, etc. as shown in fig. 3. The connecting line between every two nodes in at least two nodes is used for representing that the two nodes can be combined. For example, a line between an egg and a tomato is used to characterize that the egg and tomato can be paired together.
The relationship between each two of the at least two nodes includes one or more of the following combinations:
the ratio between the food materials represented by each two nodes is determined; or
The recommendation index of collocation between the food materials represented by each two nodes; or
And the cooking modes, the cooking tools, the cooking duration and the cooking duration of the food materials represented by every two nodes.
The relationship between every two nodes in the embodiment of the present application includes, but is not limited to:
and (3) recommending indexes of collocation between the food materials represented by every two nodes, for example, the recommending indexes of collocation between the food materials are five stars, five stars represent strong recommendation, four stars represent comparative recommendation, three stars represent general recommendation, two stars represent no recommendation and the like. Taking the food material knowledge graph shown in fig. 3 as an example, the recommendation index of matching between eggs and tomatoes is four stars.
The ratio between the food materials represented by each two nodes, for example, the ratio between the consumption of the food materials, taking the food material knowledge graph illustrated in fig. 3 as an example, is 1:3, that is, one egg is matched with 3 tomatoes.
Cooking modes of food materials represented by every two nodes, such as quick-frying, soup boiling, pan-frying, steaming and the like; cooking tools such as iron pans, saucepans, stockpots, and the like; cooking time periods, such as 20 minutes, 30 minutes, 1 hour, and the like; the cooking duration is, for example, big fire, slow fire, small fire or big fire to small fire. Continuing with the food material knowledge graph shown in fig. 3 as an example, the cooking mode of eggs and tomatoes is stir-frying, the cooking tool is an iron pan, the cooking time is 20 minutes, and the cooking duration is from big fire to small fire.
In the specific implementation process, different cooking modes between the food materials represented by every two nodes can be classified to correspond to different cooking tools, and different cooking durations and different cooking duration are corresponded to. Continuing to take the food material knowledge graph shown in fig. 3 as an example, when the cooking mode of eggs and tomatoes is frying, the corresponding cooking tool is an iron pan, the cooking time is 20 minutes, and the cooking duration is from big fire to small fire; when the cooking mode between the eggs and the tomatoes is soup cooking, the corresponding cooking tool is a soup pot, the cooking time is 30 minutes, and the cooking duration is small fire.
In addition to the above examples, the relationship between the food materials represented by each two nodes may also include the gram index, the nutritional value of the matching, and the like.
Therefore, when the food material information acquired by the server is eggs and tomatoes, the recipe can be generated according to the food material knowledge graph, for example, one egg and 3 tomatoes are suitable for being fried by an iron pan, the duration is changed from big fire to small fire, and the nutritive value is high.
In the embodiment of the present application, the specific implementation process of step S202 includes the following steps:
acquiring identity information of a user;
determining a food material knowledge graph corresponding to the identity information;
and generating a recipe according to the food material information and the food material knowledge graph corresponding to the identity information.
In the embodiment of the present application, the identity information of the user may be an ID number of the user, fingerprint information of the user, palm print information of the user, or other information that can be used to characterize the identity of the user.
In the embodiment of the present application, the manner of determining the food material knowledge graph corresponding to the identity information includes, but is not limited to, the following two manners:
the first method is as follows:
a plurality of food material knowledge maps are established on the server, and different food material knowledge maps correspond to different users. After the identity information of the user is obtained, the food material knowledge graph corresponding to the user can be determined according to the corresponding relation between the food material knowledge graph and the user.
Mode two
The method comprises the steps that a food material knowledge graph is established on a server, after identity information of a user is obtained, relevant information of the user, such as diet preference, taboo, physical health condition and the like of the user, is also required to be obtained, and then dynamic adjustment is carried out on the food material knowledge graph established on the server according to the obtained relevant information of the user, for example, the user A is recommended to be a current recipe, and the user A tastes sweet, likes carrot, beef, does not eat potatoes, does not eat dishes and the like.
In the embodiment of the application, the diet preference and the taboo of the user can be preset in the intelligent device and then uploaded to the server by the intelligent device, or the diet preference and the taboo of the user can be determined by the server according to the obtained food material information and/or the times of the user adopting the recommended recipe. For example, if the food material information frequently acquired by the server is beef, carrot and vermicelli, it indicates that the user may prefer beef and carrot. Or the server recommends the recipes with the spicy taste to the user for ten times, and the recipes are rejected by the user, which indicates that the user does not like to eat spicy food, and the taste is relatively light or sweet.
After the diet preference and the taboo of the user are obtained, the food material knowledge graph is adjusted according to the diet preference and the taboo of the user, so that the adjusted food material knowledge graph can better meet the requirements of the user, the recipe can be more accurately recommended to the user, and the user is prevented from recommending the recipe which is disliked by the user. For example, taking the food material knowledge graph shown in fig. 3 as an example, if the taste of the user a is slightly light or sweet, the node of pepper is deleted from the food material knowledge graph shown in fig. 3, so as to avoid that all recommended recipes contain pepper, or a small amount of pepper is remarked in the food material knowledge graph and sugar is added.
In the second mode, after the food material knowledge graph is adjusted, the server may store the adjusted food material knowledge graph, or may restore the food material knowledge graph to the original food material knowledge graph after the food material knowledge graph is recommended based on the adjusted food material knowledge graph.
In the embodiment of the application, in order to recommend a novel recipe to a user, in a specific implementation process, the food material knowledge graph needs to be updated periodically, for example, the food material knowledge graph is updated every half month, one month or two months according to a preset time interval. Or when new food material information is obtained, the food material knowledge graph can be updated. Specifically, new food material information is added to the food material knowledge graph to obtain an updated food material knowledge graph. The following description is made with reference to specific examples.
If the original food material knowledge graph does not include the bitter gourds, when the server receives the bitter gourds and the food material information, the bitter gourds are added into the food material knowledge graph, the association relation between the bitter gourds and other nodes is established, for example, the bitter gourds and the eggs are established, the recommendation index of matching between the bitter gourds and the eggs, the proportion between the bitter gourds and the eggs, the cooking modes between the bitter gourds and the eggs, cooking tools, cooking duration or cooking duration and the like are increased. In order to generate a more detailed recipe for the user.
In the process of generating the recipe, the server inevitably needs ingredients, such as salt, pepper, edible oil, oil consumption, soy sauce, vinegar and the like. And when the server adds the ingredients, the ingredients are often added according to actual needs and are recommended to the user after the recipe is generated. When a user receives a recipe recommended by a server, the user often finds that some ingredients in the recommended recipe do not exist, under the circumstance, if the user wants to ensure the taste of making dishes, the user needs to buy the ingredients at present, unnecessary trouble is brought to the user, and if the ingredients are not put, the taste of making the dishes is affected, and bad experience is brought to the user. To avoid this, the server may receive the ingredient information sent by the smart device and match it according to the existing ingredient information.
For example, the food material information obtained by the server is eggs and tomatoes, the recipe recommended to the user is tomato scrambled eggs, the required ingredients are shallots, white granulated sugar and salt, the ingredients actually obtained by the server include shallots, sugar cubes, salt and the like, and white granulated sugar is not used.
In the embodiment of the application, for more accurate recipe recommendation for the user, the server can also acquire the number of current dinning people, and the consumption of food materials used in the recipe is determined according to the number of dinning people, so that waste is avoided. For example, when the server does not obtain the number of people having a meal, the recommended recipe tomato scrambled eggs need 1 egg and three tomatoes, and when the number of people having a meal is obtained by one person and the number of people possibly does not need the large number, the food material ratio is adjusted to 1 egg and 1 tomato; and when the number of people for dining is four, the food material ratio is adjusted to 2 eggs and 4 tomatoes.
The server may also obtain information about the user's state of life, including but not limited to the user's health status, whether the user is losing weight or not. For example, if the user has diabetes, taking the recipe recommended to the user as tomato scrambled eggs as an example, when the tomato scrambled eggs are made, ingredient sugar needs to be added, and the amount of the added sugar is originally 10 g, but considering that the user has diabetes, the amount of the added sugar is reduced by half, even no sugar is added.
The server can also acquire the current weather conditions, for example, the current temperature is low and is relatively cold, and at this time, the server can recommend some recipes capable of warming the stomach for the user according to the food material information. For example, when the food material information acquired by the server is eggs and tomatoes, tomato scrambled eggs are not recommended to the user, and tomato egg soup is recommended to the user, so that the user can warm the body after eating the tomato egg soup.
S203: and recommending the recipe to the user.
After the server generates the recipe, the recipe is sent to the intelligent terminal, and the recipe is displayed to the user by the intelligent terminal, for example, the recipe is displayed through a display panel of the intelligent device, or the recipe is broadcasted to the user through a voice broadcast unit of the intelligent device.
When the intelligent equipment reports the recipe through the voice broadcasting unit, the recipe recommended can be played circularly for convenience of a user to make dishes according to the recipe, the situation that the user forgets a certain making step suddenly and needs to look over again is avoided, and when the recipe is looked over again, the dishes in the pot are burnt, and the like, so that poor experience is brought to the user.
In the embodiment of the application, the server can also record the times of the user adopting the recommended recipes, and the diet preference and taboo of the user are adjusted in real time according to the times of the recommended recipes, so that the food material knowledge graph can be updated in real time.
Referring to fig. 4, based on the same inventive concept, an embodiment of the present application provides a server 400, including:
an obtaining unit 401, configured to obtain food material information;
a generating unit 402, configured to generate a recipe according to the food material information and the food material knowledge graph; the food material knowledge graph comprises at least one node and a relation between every two nodes in the at least one node, and each node in the at least one node represents a food material;
a recommending unit 403, configured to recommend the recipe to the user.
In one possible design, the relationship between each two nodes includes one or more of the following relationships:
the ratio between the food materials represented by each two nodes is determined; or
The recommendation index of collocation between the food materials represented by each node; or
And the cooking modes, the cooking tools, the cooking duration and the cooking duration of the food materials represented by every two nodes.
In one possible design, when the generating unit generates the recipe according to the food material information and the food material knowledge graph, the generating unit is specifically configured to:
acquiring identity information of a user;
determining a food material knowledge graph corresponding to the identity information;
and generating a recipe according to the food material information and the food material knowledge graph corresponding to the identity information.
In one possible design, the electronic device further includes:
the adding unit is used for adding the new food material information to the food material knowledge graph when new food material information is obtained so as to obtain an updated food material knowledge graph.
In one possible design, when the generating unit generates the recipe according to the food material information and the food material knowledge graph, the generating unit is specifically configured to:
acquiring batching information;
and generating a recipe according to the food material information, the ingredient information and the food material knowledge graph.
Referring to fig. 5, an embodiment of the present application further provides a server 500, including:
a memory 501 for storing instructions; at least one processor 502 adapted to read instructions from the memory to implement the method as performed by the electronic device of the first aspect or any one of the possible designs of the first aspect.
In the embodiment of the present application, the processor 502 may be a Central Processing Unit (CPU), an application-specific integrated circuit (ASIC), one or more integrated circuits for controlling program execution, a baseband chip, or the like. The number of memories may be one or more, and the memories may be read-only memories (ROMs), Random Access Memories (RAMs), or disk memories, etc.
Embodiments of the present application also provide a computer storage medium, which may include a memory, where the memory may store a program, and the program includes all the steps executed by the server described in the method embodiment shown in fig. 2 when executed.
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 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. It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (10)
1. A recipe recommendation method comprising:
acquiring food material information;
generating a recipe according to the food material information and the food material knowledge graph; the food material knowledge graph comprises at least two nodes and a relation between every two nodes in the at least two nodes, and each node in the at least two nodes represents a food material;
recommending the recipe to a user;
wherein the relationship between each two nodes comprises one or more of the following relationships:
the ratio between the food materials represented by each two nodes is determined; or
The recommendation index of collocation between the food materials represented by each two nodes; or
And the cooking modes, the cooking tools, the cooking duration and the cooking duration of the food materials represented by every two nodes.
2. The method of claim 1, wherein generating a recipe from the food material information and food material knowledge graph comprises:
acquiring identity information of a user;
determining a food material knowledge graph corresponding to the identity information;
and generating a recipe according to the food material information and the food material knowledge graph corresponding to the identity information.
3. The method of claim 1, further comprising:
when new food material information is obtained, the new food material information is added to the food material knowledge graph to obtain an updated food material knowledge graph.
4. The method of claim 1, wherein generating a recipe from the food material information and food material knowledge graph comprises:
acquiring batching information;
and generating a recipe according to the food material information, the ingredient information and the food material knowledge graph.
5. A server, comprising:
an acquisition unit for acquiring food material information;
the generating unit is used for generating a recipe according to the food material information and the food material knowledge graph; the food material knowledge graph comprises at least two nodes and a relation between every two nodes of the at least two nodes, each node of the at least two nodes represents a food material, and the relation between every two nodes comprises one or more combinations of the following relations: the ratio between the food materials represented by each two nodes is determined; or the recommendation index of collocation between the food materials represented by each two nodes; or the cooking mode, the cooking tool, the cooking duration and the cooking duration of the food material represented by each two nodes;
and the recommending unit is used for recommending the recipe to the user.
6. The server according to claim 5, wherein when the generating unit generates the recipe according to the food material information and the food material knowledge graph, the generating unit is specifically configured to:
acquiring identity information of a user;
determining a food material knowledge graph corresponding to the identity information;
and generating a recipe according to the food material information and the food material knowledge graph corresponding to the identity information.
7. The server according to claim 5, further comprising:
the adding unit is used for adding the new food material information to the food material knowledge graph when new food material information is obtained so as to obtain an updated food material knowledge graph.
8. The server according to claim 5, wherein when the generating unit generates the recipe according to the food material information and the food material knowledge graph, the generating unit is specifically configured to:
acquiring batching information;
and generating a recipe according to the food material information, the ingredient information and the food material knowledge graph.
9. A server, comprising:
a memory to store instructions;
at least one processor configured to read instructions stored in the memory and implement the method of any of claims 1-4.
10. A computer storage medium having stored therein instructions that, when executed on a computer, cause the computer to perform the method of any one of claims 1-4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910562158.0A CN110287306B (en) | 2019-06-26 | 2019-06-26 | Recipe recommendation method and equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910562158.0A CN110287306B (en) | 2019-06-26 | 2019-06-26 | Recipe recommendation method and equipment |
Publications (2)
| Publication Number | Publication Date |
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| CN110287306A CN110287306A (en) | 2019-09-27 |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110837552B (en) * | 2019-09-30 | 2022-12-09 | 口口相传(北京)网络技术有限公司 | Diet information recommendation method and device |
| CN111506735A (en) * | 2020-04-07 | 2020-08-07 | 珠海格力电器股份有限公司 | Dish recommendation method, storage medium, electronic device and refrigerator |
| CN111811182B (en) * | 2020-07-14 | 2022-01-28 | 青岛聚好联科技有限公司 | Refrigerator and recipe recommendation method |
| CN113486186A (en) * | 2020-08-27 | 2021-10-08 | 青岛海信电子产业控股股份有限公司 | Healthy diet knowledge map construction and food material recommendation method |
| CN113283364A (en) * | 2021-06-04 | 2021-08-20 | 青岛海尔科技有限公司 | Recipe determination method and apparatus, storage medium, and electronic apparatus |
| CN116417115B (en) * | 2023-06-07 | 2023-12-01 | 北京四海汇智科技有限公司 | Personalized nutrition scheme recommendation method and system for gestational diabetes patients |
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