CN113470784A - Recipe recommendation method and recipe recommendation system - Google Patents
Recipe recommendation method and recipe recommendation system Download PDFInfo
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
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Abstract
The invention provides a recipe recommendation method and a recipe recommendation system. The recipe recommendation method comprises the following steps: receiving data of eating habits, exercise conditions or health conditions input by a user; analyzing nutrition required by the user according to the data of the eating habits, the exercise conditions or the health conditions input by the user; searching corresponding food materials from a food material nutrition knowledge base module according to nutrition required by a user; and outputting the recipe information corresponding to the corresponding food material. In the recipe recommendation method, the nutrition required by the user is analyzed through data of dietary habits, exercise conditions or health conditions input by the user; and according to the nutrition required by the user, searching the corresponding food materials from the food material nutrition knowledge base module and recommending the recipes corresponding to the food materials to the user, thereby realizing the accuracy and effectiveness of recipe recommendation.
Description
Technical Field
The invention relates to the technical field of food processing, in particular to a recipe recommendation method and a recipe recommendation system.
Background
In modern society, people do not have time to select a diet suitable for the current physical condition due to busy work, thereby causing one or more nutrient deficiencies and one or more nutrient overabundance in the body. Malnutrition or overnutrition can easily cause further deterioration of the physical condition, which leads to various diseases.
Disclosure of Invention
The invention mainly aims to provide a recipe recommendation method and a recipe recommendation system, and aims to solve the problem of malnutrition or overnutrition caused by unreasonable dietary conditions of people in modern society.
In order to achieve the above object, an embodiment of the present invention provides a recipe recommendation method, including the following steps:
receiving data of eating habits, exercise conditions or health conditions input by a user;
analyzing nutrition required by the user according to the data of the eating habits, the exercise conditions or the health conditions input by the user;
searching corresponding food materials from a food material nutrition knowledge base module according to nutrition required by a user;
and outputting the recipe information corresponding to the corresponding food material.
In one embodiment, the input data of the user further includes:
one or more of basic information of the user, personal physical conditions of the user, or sleeping conditions.
In one embodiment, the recipe recommendation method further includes the following steps:
receiving information input by an expert;
and according to the information input by the experts, adding the relation between the new food materials and the nutrition in the food material nutrition knowledge base module.
In one embodiment, the recipe recommendation method further includes the following steps:
receiving food information input by a user;
searching the source, the processing process or the circulation process information of the food according to the food information input by the user; and
and outputting the food source, processing process or circulation process information to a user.
In one embodiment, the food information input by the user comprises a food sales number or an RFID bar code on a food package.
In one embodiment, the source, process or circulation process information of the food comprises:
in the food planting process, one or more of planting time, fertilizing times and deinsectization pesticide spraying information;
during the food processing, one or more of the processing plant site, the processing plant environment, the additive use condition and the disinfection and sterilization information;
and in the food circulation process, one or more of logistics information, warehousing information and sales information.
In one embodiment, the recipe recommendation method further includes the following steps:
collecting information of each node in a food planting process, a food processing process or a food circulation process;
and uploading the collected information of each node to the blockchain node.
Another embodiment of the present invention further provides a recipe recommendation system, including:
the data input module is used for receiving data of eating habits, exercise conditions or health conditions input by a user;
the food material nutrition knowledge base module is used for storing food material information and nutrition information related to the food material information; and
and the data analysis module is used for analyzing the nutrition required by the user according to the dietary habits, the exercise conditions or the health conditions of the user, matching the nutrition required by the user with the food material nutrition knowledge base module and outputting the recipe corresponding to the user.
In one embodiment, the recipe recommendation system further includes:
the searching module is used for searching the source, the processing process or the circulation process information of the food according to the food information input by the user; and outputting the searched food source, processing process or circulation process information to the user.
In one embodiment, the source, process or circulation process information of the food comprises:
in the food planting process, one or more of planting time, fertilizing times and deinsectization pesticide spraying information;
during the food processing, one or more of the processing plant site, the processing plant environment, the additive use condition and the disinfection and sterilization information;
and in the food circulation process, one or more of logistics information, warehousing information and sales information.
In the recipe recommendation method and the recipe recommendation system provided by the embodiment of the invention, the nutrition required by the user is analyzed through the data of the dietary habits, the exercise conditions or the health conditions input by the user; and according to the nutrition required by the user, searching the corresponding food materials from the food material nutrition knowledge base module and recommending the recipes corresponding to the food materials to the user, thereby realizing the accuracy and effectiveness of recipe recommendation.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
Fig. 1 is a flowchart illustrating a recipe recommendation method according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart illustrating the process of receiving expert input information in the food recommendation method of FIG. 1;
FIG. 3 is a schematic flow chart of the food source tracing in the food recommendation method in FIG. 1;
FIG. 4 is a schematic flow chart of the method for recommending food in FIG. 3 for preventing data tampering;
FIG. 5 is a block diagram of a recipe recommendation system according to another embodiment of the present invention;
FIG. 6 is a schematic block diagram of the food tracing database in FIG. 5 during food tracing;
fig. 7 is a schematic physical architecture diagram of an electronic device according to still another embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that if directional indications (such as up, down, left, right, front, and back … …) are involved in the embodiment of the present invention, the directional indications are only used to explain the relative positional relationship between the components, the movement situation, and the like in a specific posture, and if the specific posture is changed, the directional indications are changed accordingly.
In addition, if there is a description of "first", "second", etc. in an embodiment of the present invention, the description of "first", "second", etc. is for descriptive purposes only and is not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, if the meaning of "and/or" and/or "appears throughout, the meaning includes three parallel schemes, for example," A and/or B "includes scheme A, or scheme B, or a scheme satisfying both schemes A and B. In addition, technical solutions between various embodiments may be combined with each other, but must be realized by a person skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present invention.
Referring to fig. 1, an embodiment of the invention provides a recipe recommendation method. The recipe recommendation method comprises the following steps:
step 101: and receiving data of eating habits, exercise conditions or health conditions input by a user.
Step 102: analyzing nutrition required by the user according to the data of the eating habits, the exercise conditions or the health conditions input by the user;
step 103: searching corresponding food materials from a food material nutrition knowledge base module according to nutrition required by a user;
step 104: and outputting the recipe information corresponding to the corresponding food material.
In the recipe recommendation method provided by the embodiment of the invention, the nutrition required by the user is analyzed through the data of the dietary habits, the exercise conditions or the health conditions input by the user; and according to the nutrition required by the user, searching the corresponding food materials from the food material nutrition knowledge base module and recommending the recipes corresponding to the food materials to the user, thereby realizing the accuracy and effectiveness of recipe recommendation.
The eating habit information of the user may include: staple preference information, meat preference information, and vegetarian preference information. Alternatively, in step 101, the eating habit information of the user may include: lucai, Chuan, Yue, Jiangsu, Min, Zhejiang, Xiang and Hui cuisine.
Wherein the staple food preference information may include: rice, wheaten food, bread, etc.
The meat preference information may include: pork, beef, mutton, chicken, duck meat, fish, shrimp, etc.
The vegetable preference information may include: leaf vegetables, root vegetables, melon and fruit vegetables, and mushroom vegetables.
Wherein, the corresponding various cuisine can comprise various tastes, such as: salty taste, spicy taste, fresh flavor, light taste, spicy taste, fresh spicy taste and the like.
The eating habit information of the user may include a food prohibited by the user.
The motion information may include: type of movement, time of movement, frequency of movement, etc. For example, the motion types may be: running, cycling, fitness, skipping ropes, basketball, football, swimming, etc.; the movement time may be: 10 minutes, 30 minutes, 1 hour, 2 hours, etc.; the motion frequency may be: once a day, twice a day, once every two days, twice a week, once a week, etc. It is understood that the corresponding exercise information may be input by the user himself or imported from the user's exercise device, such as a sports bracelet or the like.
The health information may include: the user's past medical history, current abnormal physiological status, etc.
Specifically, according to the data of the dietary habits, the exercise condition or the health condition input by the user, the process of analyzing the nutrition required by the user may be as follows. For example, when the user has a lot of exercise, meat and protein are needed to be supplemented, and at this time, a corresponding menu is recommended to the user according to the user's taste, staple preference, or cuisine preference. For another example, the health information of the user may be considered when recommending the corresponding recipe, e.g., if the user has a history of diabetes, the corresponding recipe does not contain high sugar or food with a high glycemic index. For another example, when the user gets angry, some relatively light cuisine can be selected from the corresponding menu, but the user does not contain spicy and pungent food.
In one embodiment, the input data of the user further includes: one or more of basic information of the user, personal physical conditions of the user, or sleeping conditions. The basic information of the user includes but is not limited to: the nickname, sex, height, weight, age and the like of the user.
Referring to fig. 2, in an embodiment, the recipe recommendation method further includes the following steps:
receiving information input by an expert;
and according to the information input by the experts, adding the relation between the new food materials and the nutrition in the food material nutrition knowledge base module.
It is to be understood that, in some cases, relationship information between some food and nutrition issued or input by some experts such as doctors or professors, etc. may be collected and corresponding relationship information between food and nutrition may be input into the food material nutrition knowledge base. Thereby the relation between the newly added food materials and the nutrition is added in the food material nutrition knowledge base module. According to the needs, some common diseases and food therapy recipes of food can be related according to the suggestions of some experts and input into the food nutrition knowledge base.
Referring to fig. 3, in one embodiment, the recipe recommendation method further includes a food source tracing step, so that the user can eat more confident food. Specifically, the food tracing process comprises the following steps:
receiving food information input by a user;
searching the source, the processing process or the circulation process information of the food according to the food information input by the user; and
and outputting the food source, processing process or circulation process information to a user.
In one embodiment, the food information input by the user comprises a food sales number or an RFID bar code on a food package.
In one embodiment, the source, process or circulation process information of the food comprises:
in the food planting process, one or more of planting time, fertilizing times and deinsectization pesticide spraying information;
during the food processing, one or more of the processing plant site, the processing plant environment, the additive use condition and the disinfection and sterilization information;
and in the food circulation process, one or more of logistics information, warehousing information and sales information.
In the specific implementation process, the data collection module can be adopted to record the information of each node in the planting process, the processing process and the selling process of the food so as to form a corresponding database. For example, information including planting time, fertilization times, pesticide spraying and the like is started from the planting period; the factory environment of the processing link, the information of the use, sterilization and the like of the additive are recorded and stored, the RFID technology is utilized to label the additive, and the information is scanned and stored in a computer through a scanning gun. As another example, logistics information, warehousing information, and sales information are uploaded directly to a computer.
Referring to fig. 4, in one embodiment, in order to prevent the collected data from being tampered with, the recipe recommendation method further includes the following steps:
collecting information of each node in a food planting process, a food processing process or a food circulation process;
and uploading the collected information of each node to the blockchain node.
For example, the blockchain includes many nodes, such as a plant feeding node, a production node, a storage node, a logistics node, and a sales node. The nodes are restricted and supervised mutually in the block chain, all information is synchronously stored in all nodes according to a common mechanism, and the chain cannot be modified. Taking the production node as an example, when the production information is written in the factory, the system judges the compliance of the input information according to the embedded rule, and if the input information is invalid, the input information cannot be written. The production information is simultaneously transmitted into a common database and block link points, the nodes are responsible for converting the production information into 16-bit string data summary information by utilizing an encryption algorithm and uploading the 16-bit string data summary information to a block link network, whether the data are falsified or not can be accurately judged through an encryption technology, and a unique hash value generated after the data are successfully written into the blocks is stored into other nodes of the database to carry out the same operation.
Referring to fig. 5, another embodiment of the invention further provides a recipe recommendation system 100. The recipe recommendation system 100 includes a data input module 110, a food material nutrition knowledge base module 120, and a data analysis module 130.
The data input module 110 is used for receiving the data of eating habits, exercise conditions or health conditions input by the user. The data of the eating habits, the exercise conditions or the health conditions of the user may be as described in the above embodiments, and are not described herein again.
The food material nutrition knowledge base module 120 is used for storing food material information and nutrition information associated with the food material information.
The data analysis module 130 is configured to analyze nutrition required by the user according to the dietary habits, exercise conditions, or health conditions of the user, match the nutrition required by the user with the food material nutrition knowledge base module 120, and output a recipe corresponding to the user.
In the recipe recommendation system provided in this embodiment, data of eating habits, exercise conditions, or health conditions of the user is collected through the data input module 110, nutrition required by the user is analyzed through the data analysis module 130, and according to the nutrition required by the user, a corresponding food material is searched from the food material nutrition knowledge base module 120 and a recipe corresponding to the food material is recommended to the user, so that accuracy and effectiveness of recipe recommendation are achieved.
As required, the food material nutrition knowledge module 120 is a cloud-based data center or database. The food material nutrition knowledge module 120 stores food material information, and can perform nutrition classification on the input food material. For example, the food material nutrition knowledge module 120 can process, sort, classify, etc. the nutrition data of the food material.
According to the requirement, the data analysis module 130 can analyze and process the data input by the user to obtain the nutritional data required by the user. Then, the data analysis module 130 analyzes and learns the stored data based on big data analysis to obtain a nutrition analysis model. At this time, the nutrition required by the user is analyzed according to the data of the eating habits, the physical conditions, the work and rest habits and the like of the user, which are acquired by the data input module 110, and the nutrition analysis model corresponding to the food material nutrition knowledge base module 120 is matched, so that the recipe corresponding to the user is output.
Specifically, the data input module 110 includes a user client 111, an expert client 112, and a backend management terminal 113.
Among other things, user client 111 may include a user input module 1111. The user can input his or her registration/login information, personal basic information, personal physical conditions, work and rest habits, eating habits, exercise situations, sleep situations, etc. through the user input module 1111. If necessary, the user may also perform online questioning based on the user client 111, for example, to inquire the physical health condition, inquire about food materials corresponding to the health condition, and the like. There are experts such as doctors or professors that can answer these questions. According to the requirement, the user can also input some feedback and help information in the user input module 1111, and the corresponding feedback and help information will be sent only to the background management terminal 113 of the system, so as to process the corresponding feedback and help information.
Wherein the expert client 112 is adapted for an expert to register/log in. The expert client 112 may include the title, job information, etc. of the expert. The expert may answer questions or share experiences at the expert client 112. It will be appreciated that to encourage the expert to share in their experience, a corresponding credit system, reward system or rating system may be set to encourage the expert to be willing to answer the question. If necessary, the expert may also input some feedback and help information at the expert client 112, and the corresponding feedback and help information may be sent to the backend management terminal 113 of the system only, so as to process the corresponding feedback and help information.
In one embodiment, the user client 111 further comprises a lookup module 1112.
The searching module 1112 is configured to search the source, processing procedure, or circulation procedure information of the food according to the food information input by the user. In addition, the searching module 1112 outputs the searched food source, processing procedure or circulation procedure information to the user.
Specifically, the food information input by the user comprises a food sale number or RFID bar code or two-dimensional code information on a food package. It is to be appreciated that a user can input food information into the lookup module 1112 by capturing RFID barcode or two-dimensional code information on the food package via a mobile device.
In one embodiment, the source, process or circulation process information of the food comprises:
in the food planting process, one or more of planting time, fertilizing times and deinsectization pesticide spraying information;
during the food processing, one or more of the processing plant site, the processing plant environment, the additive use condition and the disinfection and sterilization information;
and in the food circulation process, one or more of logistics information, warehousing information and sales information.
And storing the food source, processing process or circulation process information in a database according to needs, and storing the food source, processing process or circulation process information in a block chain mode to prevent data tampering.
The user may also view his or her health information and recipe recommendation information in the lookup module 1112, as desired.
In one embodiment, the searching module 1112 searches the food source, processing procedure, or circulation procedure information from the food source database.
Referring collectively to fig. 6, the recipe trace source database 200 includes a data collection module 210 and a blockchain module 220.
The data collection module 210 can record information of each node in the planting process, the processing process and the selling process of the food to form a corresponding database. For example, information including planting time, fertilization times, pesticide spraying and the like is started from the planting period; the factory environment of the processing link, the information of the use, sterilization and the like of the additive are recorded and stored, the RFID technology is utilized to label the additive, and the information is scanned and stored in a computer through a scanning gun. As another example, logistics information, warehousing information, and sales information are uploaded directly to a computer.
The blockchain module 220 may store information of each node in a food planting process, a food processing process, or a food circulation process to prevent data tampering.
For example, the blockchain includes many nodes, such as a plant feeding node, a production node, a storage node, a logistics node, and a sales node. The nodes are restricted and supervised mutually in the block chain, all information is synchronously stored in all nodes according to a common mechanism, and the chain cannot be modified. Taking the production node as an example, when the production information is written in the factory, the system judges the compliance of the input information according to the embedded rule, and if the input information is invalid, the input information cannot be written. The production information is simultaneously transmitted into a common database and block link points, the nodes are responsible for converting the production information into 16-bit string data summary information by utilizing an encryption algorithm and uploading the 16-bit string data summary information to a block link network, whether the data are falsified or not can be accurately judged through an encryption technology, and a unique hash value generated after the data are successfully written into the blocks is stored into other nodes of the database to carry out the same operation.
Referring to fig. 7, an embodiment of the present invention further provides an entity architecture diagram of an electronic device applying the recipe recommendation method according to any of the above embodiments. The electronic device 300 may include: a processor 310, a communication interface 320, a memory 330, and a communication bus 340. The processor 310, the communication interface 320, and the memory 330 are configured to communicate with each other via a communication bus 340. The processor 310 may call logic instructions in the memory 330 to perform the following method:
step 101: and receiving data of eating habits, exercise conditions or health conditions input by a user.
Step 102: analyzing nutrition required by the user according to the data of the eating habits, the exercise conditions or the health conditions input by the user;
step 103: searching corresponding food materials from a food material nutrition knowledge base module according to nutrition required by a user;
step 104: and outputting the recipe information corresponding to the corresponding food material.
In addition, the logic instructions in the memory 330 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, where the computer program is implemented to perform the recipe recommendation method provided in the foregoing embodiments when executed by a processor, for example:
step 101: and receiving data of eating habits, exercise conditions or health conditions input by a user.
Step 102: analyzing nutrition required by the user according to the data of the eating habits, the exercise conditions or the health conditions input by the user;
step 103: searching corresponding food materials from a food material nutrition knowledge base module according to nutrition required by a user;
step 104: and outputting the recipe information corresponding to the corresponding food material.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all modifications and equivalents of the present invention, which are made by the contents of the present specification and the accompanying drawings, or directly/indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A recipe recommendation method, comprising the steps of:
receiving data of eating habits, exercise conditions or health conditions input by a user;
analyzing nutrition required by the user according to the data of the eating habits, the exercise conditions or the health conditions input by the user;
searching corresponding food materials from a food material nutrition knowledge base module according to nutrition required by a user;
and outputting the recipe information corresponding to the corresponding food material.
2. The recipe recommendation method as claimed in claim 1, wherein the user's input data further comprises:
one or more of basic information of the user, personal physical conditions of the user, or sleeping conditions.
3. The recipe recommendation method as claimed in claim 1, further comprising the steps of:
receiving information input by an expert;
and according to the information input by the experts, adding the relation between the new food materials and the nutrition in the food material nutrition knowledge base module.
4. The recipe recommendation method as claimed in claim 1, further comprising the steps of:
receiving food information input by a user;
searching the source, the processing process or the circulation process information of the food according to the food information input by the user; and
and outputting the food source, processing process or circulation process information to a user.
5. The recipe recommendation method of claim 4 wherein the user entered food information comprises a food sales number or an RFID barcode on a food package.
6. The recipe recommendation method of claim 1, wherein the food source, processing procedure or circulation procedure information comprises:
in the food planting process, one or more of planting time, fertilizing times and deinsectization pesticide spraying information;
during the food processing, one or more of the processing plant site, the processing plant environment, the additive use condition and the disinfection and sterilization information;
and in the food circulation process, one or more of logistics information, warehousing information and sales information.
7. The recipe recommendation method as claimed in claim 6, further comprising the steps of:
collecting information of each node in a food planting process, a food processing process or a food circulation process;
and uploading the collected information of each node to the blockchain node.
8. A recipe recommendation system, comprising:
the data input module is used for receiving data of eating habits, exercise conditions or health conditions input by a user;
the food material nutrition knowledge base module is used for storing food material information and nutrition information related to the food material information; and
and the data analysis module is used for analyzing the nutrition required by the user according to the dietary habits, the exercise conditions or the health conditions of the user, matching the nutrition required by the user with the food material nutrition knowledge base module and outputting the recipe corresponding to the user.
9. The recipe recommendation system as set forth in claim 8, further comprising:
the searching module is used for searching the source, the processing process or the circulation process information of the food according to the food information input by the user; and outputting the searched food source, processing process or circulation process information to the user.
10. The recipe recommendation system according to claim 9, wherein the food source, processing or circulation information comprises:
in the food planting process, one or more of planting time, fertilizing times and deinsectization pesticide spraying information;
during the food processing, one or more of the processing plant site, the processing plant environment, the additive use condition and the disinfection and sterilization information;
and in the food circulation process, one or more of logistics information, warehousing information and sales information.
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