CN112287211A

CN112287211A - Food material collocation scheme generation method and device, computer equipment and storage medium

Info

Publication number: CN112287211A
Application number: CN202010993500.5A
Authority: CN
Inventors: 赵天翼; 毛端中; 林嘉烨; 王聪; 邓贤杰
Original assignee: Individual
Current assignee: Individual
Priority date: 2020-09-21
Filing date: 2020-09-21
Publication date: 2021-01-29

Abstract

The application relates to the technical field of computers, in particular to a method and a device for generating a food material collocation scheme, computer equipment and a storage medium. The method comprises the following steps: acquiring user portrait data of a target user; determining daily dietary energy demand and recommended nutrient intake of a target user according to the user portrait data; determining an edible alternative food material according to the user portrait data, wherein the edible alternative food material is a plurality of food materials confirmed by the target user; and generating a food material collocation scheme according to the daily dietary energy requirement, the recommended nutrient intake and the edible alternative food materials. The embodiment of the invention can provide a food material proportioning scheme with higher precision.

Description

Food material collocation scheme generation method and device, computer equipment and storage medium

Technical Field

The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for generating a food material matching scheme, a computer device, and a storage medium.

Background

The current diet therapy mainly adopts the food exchange portion method. The food exchange portion method was first proposed by the American society for disease. The method has simple calculation and convenient use, and can be applied to the diet management of the hypertensive and also can be applied to the diet management of other chronic diseases needing energy control. Since the same kind of food in the meal exchange portion only requires similar energy, protein, fat and carbohydrate supply, but has no specific requirements for other nutrients such as vitamins, minerals and the like, the recipe selected by a patient or a dietician according to the meal exchange portion method may cause problems such as difficulty in quantifying the level of each nutrient.

Therefore, the accuracy of the recipe prepared by the food exchange portion method is not high, and there are problems that it is difficult to determine whether the goal of the nutritional design is achieved, it is difficult to determine whether there is a nutritional defect or deficiency, and it is difficult to determine what proportion of the recipe with nutritional defect is in the selectable recipe.

Disclosure of Invention

Aiming at the defects of the prior art, the invention provides a method and a device for generating a food material matching scheme, computer equipment and a storage medium.

The invention provides a food material collocation scheme generation method according to a first aspect, and in one embodiment, the method comprises the following steps:

acquiring user portrait data of a target user;

determining daily dietary energy demand and recommended nutrient intake of a target user according to the user portrait data;

determining an edible alternative food material according to the user portrait data, wherein the edible alternative food material is a plurality of food materials confirmed by the target user;

and generating a food material collocation scheme according to the daily dietary energy requirement, the recommended nutrient intake and the edible alternative food materials.

In one embodiment, the user profile data includes user body basic information, food exclusion data, user illness information, and user energy expenditure data; the food exclusion data includes at least one food material that is not available for consumption by the target user;

the edible alternative food materials confirmed by the target user include a plurality of food materials.

In one embodiment, the step of determining a daily dietary energy requirement and a recommended nutrient intake for the target user based on the user profile data comprises:

determining daily meal energy requirement of a target user according to the body basic information of the user and the energy consumption data of the user;

and determining the recommended nutrient intake according to the body basic information and the disease information of the user.

Preferably, in one embodiment, the step of determining the recommended intake of nutrients based on the user body basic information and the user disease information includes:

inquiring a nutrient database according to the basic information of the body of the user to obtain the recommended intake of the initial nutrients;

inquiring a disease knowledge database according to the disease information of the user, and determining nutrient intake adjustment information based on the inquiry result;

and updating the initial nutrient recommended intake according to the nutrient intake adjustment information to obtain the nutrient recommended intake.

Preferably, in one embodiment, the initial recommended nutrient intake includes a plurality of nutrients and recommended intakes for each nutrient; a step of updating the initial nutrient recommended intake according to the nutrient intake adjustment information to obtain a nutrient recommended intake, including:

determining nutrients to be updated and intake adjustment information corresponding to the nutrients in a plurality of nutrients included in the initial nutrient recommended intake according to the nutrient intake adjustment information, wherein the plurality of nutrients include at least one nutrient to be updated, and the nutrients to be updated are nutrients required to be updated in the corresponding recommended intake;

and updating the recommended intakes corresponding to the various nutrients to be updated according to the intake adjustment information corresponding to the various nutrients to be updated to obtain the recommended intakes of the nutrients.

In one embodiment, the step of determining an edible alternative food material from the user representation data comprises:

establishing a food material exclusion database according to food exclusion data and user disease information included in the user portrait data, wherein the food material exclusion database includes at least one inedible food material;

extracting food materials to be confirmed from a preset target food material selection database according to all inedible food materials stored in a food material exclusion database, wherein the food materials to be confirmed comprise a plurality of food materials except any inedible food material in the target food material selection database;

displaying the food materials to be confirmed to a target user;

receiving alternative food material confirmation information from a target user, and determining the food materials related to the alternative food material confirmation information in the food materials to be confirmed as edible alternative food materials.

Preferably, in an embodiment, the step of extracting the food material to be confirmed from the preset target food material selection database according to all inedible food materials stored in the food material exclusion database further includes:

and determining a target food material provider associated with the target user, and taking a preset food material selection database corresponding to the target food material provider as a target food material selection database.

Preferably, in one embodiment, the step of generating the food material matching scheme according to the daily dietary energy requirement, the recommended nutrient intake and the edible alternative food material further comprises the following steps:

and sending the food material collocation scheme to a target food material provider so that staff of the target food material provider prepares the food materials corresponding to the food material collocation scheme.

In one embodiment, the step of building a food material exclusion database based on food exclusion data and user illness information included in the user profile data includes:

determining a first inedible food material corresponding to the food exclusion data;

determining a second inedible food material corresponding to the user disease information;

a food material exclusion database is established based on the first inedible food material and the second inedible food material.

In one embodiment, the step of determining an edible alternative food material from the user representation data may be preceded by:

the method comprises the steps of obtaining food material supply information provided by any food material provider, wherein the food material supply information comprises a plurality of food materials which can be provided by the food material provider within a preset time interval;

and establishing a food material selection database corresponding to any food material provider according to the food material supply information.

Preferably, the step of establishing the food material selection database corresponding to any food material provider according to the food material supply information further includes the following steps.

And updating the food material selection database corresponding to any food material provider according to the food material updating information every time the food material updating information belonging to any food material provider is received.

In one embodiment, the step of generating a food material matching program from the daily dietary energy requirement, the recommended nutrient intake, and the edible alternative food material comprises:

establishing a first model according to daily dietary energy requirement, recommended nutrient intake and edible alternative food materials;

and solving the first model, and generating a food material collocation scheme according to a result obtained by solving the first model.

The present invention provides a food material collocation scheme generation apparatus according to a second aspect, and in one embodiment, the apparatus includes:

the user portrait acquisition module is used for acquiring user portrait data of a target user;

the first determination module is used for determining daily dietary energy demand and nutrient recommended intake of a target user according to the user portrait data;

the second determination module is used for determining edible alternative food materials according to the user portrait data, wherein the edible alternative food materials are food materials confirmed by the target user;

and the food material matching scheme generating module is used for generating a food material matching scheme according to the daily dietary energy requirement, the recommended nutrient intake and the edible alternative food materials.

The present invention provides according to a third aspect a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of an embodiment of any of the methods described above when executing the computer program.

The present invention provides according to a fourth aspect a computer-readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the embodiments of the method of any one of the above.

In the embodiment of the invention, different nutrients are more finely quantized, computer science and nutriology are combined, the nutrition requirement of a user is comprehensively calculated, and the requirement of the type and the quantity of the food materials per day is formulated, so that the problem that the traditional food exchange portioning method needs manual calculation can be solved.

Drawings

Fig. 1 is a schematic flow chart of a method for generating a food material matching scheme according to an embodiment;

FIG. 2 is a flowchart illustrating an implementation of step S120 in one embodiment;

FIG. 3 is a flowchart illustrating the steps of determining an edible alternative food material according to one embodiment

Fig. 4 is a block diagram illustrating an exemplary embodiment of a food material matching scheme generating apparatus;

FIG. 5 is a diagram illustrating an internal structure of a computer device according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

The invention provides a food material collocation scheme generation method, which can be realized by a server (or a server cluster) independently, or a system consisting of the server and an intelligent terminal (such as a smart phone, a notebook computer, a tablet computer and/or wearable equipment). The method is described below by way of example as applied to the above-described server (hereinafter referred to as an execution server), and in one embodiment, as shown in fig. 1, the method includes the steps of:

s110: user representation data of a target user is obtained.

In this embodiment, the target user refers to a user for whom a food material collocation scheme is to be generated. The user profile data includes user body basic information, food exclusion data, user illness information, and user energy expenditure data. The user body basic information includes at least one of sex, age, height and weight of the user, further, if the sex of the user is female, the user body basic information may further include physiological condition information (e.g., whether pregnant, whether lactating, etc.), the physiological condition information includes pregnancy status information for characterizing that the user is lactating or pregnant or non-pregnant, and further, if the user is pregnant, the physiological condition information includes pregnancy period information (e.g., number of days of pregnancy and/or pregnancy stage, etc.). The food exclusion data includes at least one food material that cannot be provided to the target user for consumption, and the food materials that cannot be provided to the target user for consumption include food materials that the target user does not want to eat (e.g., tomatoes that the target user does not like to eat, etc.) and food materials that the target user cannot eat (e.g., shrimps that the target user has allergies to eat, crabs that the target user needs to fast or be prohibited from suffering from a disease, etc.). The user disease information comprises health state information for characterizing the user as healthy or sick; further, if the health status of the user is "sick", disease type information (e.g., nutritional deficiency disease) and disease description information (e.g., protein-malnutrition) are also included in the user disease information. The user energy consumption data can be obtained by calculating the total daily energy consumption (TEE), namely the user energy consumption data, of the target user through the all-day motion condition data of the target user recorded by the mobile phone, the motion bracelet or other wearable devices of the target user, and the execution server updates the user portrait data corresponding to the target user at intervals (for example, every day).

S120: and determining the daily dietary energy requirement and the recommended nutrient intake of the target user according to the user profile data.

In the embodiment, after the execution server obtains the user profile data of the target user, the daily dietary energy demand and the nutrient recommended intake of the target user are respectively calculated based on the user profile data.

In one embodiment, as shown in FIG. 2, the step of determining a daily dietary energy requirement and a recommended nutrient intake for a target user based on user profile data comprises:

s121: and determining the daily meal energy requirement of the target user according to the user body basic information and the user energy consumption data which are included in the user portrait data.

S122: and determining the recommended nutrient intake according to the user body basic information and the user disease information which are included in the user portrait data.

In this embodiment, when calculating the daily dietary energy requirement of the target user, the Basic Energy Expenditure (BEE) may be calculated according to the Harris-Benedict formula (i.e., formula 1-1 and formula 1-2) according to the height, weight and age of the target user, and then the physical activity level of the target user may be calculated in combination with the user energy expenditure data of S110, i.e., the Total Energy Expenditure (TEE). And querying a preset nutrient database according to the Physical Activity Level (PAL) and the gender and the age of the target user to obtain the daily dietary energy requirement of the target user.

BEE (Man) ═ 66.47730+13.7516W +5.0033S-6.7550A (formula 1-1)

BEE (female) ═ 655.0955+9.5634W +1.8496S-4.6756A (formula 1-2)

Wherein W, S and A represent the weight, height and age of a user (e.g., a target user), and wherein W is in kilograms, S is in centimeters and A is in years. The unit of Basal Energy Expenditure (BEE) is kilocalories (Kcal).

When the daily meal energy requirement of the target user is calculated, the execution server firstly queries the nutrient database according to the body basic information of the user to obtain the initial recommended nutrient intake (including various nutrients and recommended intakes corresponding to various nutrients), then queries the disease knowledge database according to the disease information of the user, and determining nutrient intake adjustment information based on the query result, finally updating the initial nutrient recommended intake according to the nutrient intake adjustment information to obtain a nutrient recommended intake, and adjusting the initial nutrient recommended intake based on the query result of the disease knowledge database, so that a more accurate nutrition assessment result can be obtained, for example, a hypertensive patient needs to take less fat, and if the target user suffers from hypertension, the recommended intake corresponding to the nutrient related to fat in the initial nutrient recommended intake needs to be adjusted.

Wherein, the nutrient database and the disease knowledge database are established in advance. Specifically, when the nutrient database is constructed, the dietary nutrient intake standards can be screened out based on professional nutrition guidelines published by each institution such as the chinese nutrition society, the european intestinal and parenteral nutrition society, the american nutrition society and the like, and are respectively: macronutrients, fat-soluble vitamins, water-soluble vitamins, macroelements and trace elements. And (4) performing tabulation treatment, and sorting corresponding nutrients into corresponding database files according to indexes such as different sexes, ages, body activity levels and the like. The disease knowledge database is used for performing medical grade nutrition assessment on patients, when the disease knowledge database is constructed, diet guidance which needs to be noticed by chronic patients can be searched in professional nutrition guidelines published by the Chinese society for nutrition, the American society for nutrition and the European Association for enteral and parenteral nutrition, and nutritional papers which evidence first to second evidences of medicine are screened on a Sinomed database (Chinese biomedical literature service system), a Pubmad database (a database which provides the paper search and abstract in the aspect of biomedicine and is searched freely) and an Embase (excelpt medical database) database, and the opinions of related clinicians are integrated and the contents are unified and integrated to establish the disease knowledge database.

More specifically, in one embodiment, the step of updating the initial nutrient recommended intake according to the nutrient intake adjustment information to obtain a nutrient recommended intake includes:

Wherein, the nutrient to be updated refers to the nutrient which needs to be updated corresponding to the recommended intake in the plurality of nutrients included in the recommended intake of the initial nutrient.

Specifically, the nutrient intake adjustment information is used to determine which one or ones of the plurality of nutrients included in the initial nutrient recommended intake are the nutrients to be updated, and intake adjustment information corresponding to the respective nutrients to be updated. The intake adjustment information corresponding to the nutrient to be updated may be the recommended intake after the update of the nutrient to be updated, for example, the initial nutrient recommended intake includes 2g of nutrient a-recommended intake, 4 g of nutrient B-recommended intake, 6 g of nutrient C-recommended intake, the nutrient intake adjustment information includes nutrient A-intake adjustment information 1g and nutrient B-intake adjustment information 2g, then, the nutrients to be updated are determined to be nutrient A and nutrient B, the recommended intake of the adjusted nutrient A is 1g, the recommended intake of the adjusted nutrient B is 2g, and the adjusted recommended intake of the nutrient A, the nutrient B and the nutrient C is 1g, 2g and 6 g, which are the recommended intake of the nutrient.

S130: determining an edible alternative food material based on the user representation data. The edible alternative food materials are food materials confirmed by the target user, and the edible alternative food materials confirmed by the target user comprise a plurality of food materials.

In this embodiment, the process of determining the edible alternative food material according to the user portrait data by the execution server is shown in fig. 3, and includes:

s131: and establishing a food material exclusion database according to food exclusion data and user disease information included in the user portrait data.

S132: and extracting the food materials to be confirmed from a preset target food material selection database according to all inedible food materials stored in the food material exclusion database.

S133: and displaying the food materials to be confirmed to the target user.

S134: receiving alternative food material confirmation information from a target user, and determining the food materials related to the alternative food material confirmation information in the food materials to be confirmed as edible alternative food materials.

The target food material exclusion database comprises at least one inedible food material, the execution server determines a first inedible food material corresponding to food exclusion data in the user portrait data and a second inedible food material corresponding to user disease information in the user portrait data after obtaining user portrait data of a target user, and then establishes the food material exclusion database according to the first inedible food material and the second inedible food material, specifically, the execution server establishes the target food material exclusion database (which can be realized by a data table) according to all food materials corresponding to the food exclusion data in the user portrait data and all food materials which are needed to be fast (or forbidden) for diseases of the target user and obtained by querying the disease knowledge database according to the user disease information.

The preset target food material selection database includes all food materials that can be provided by a food material supplier, and content information of various nutrients corresponding to the various food materials (for example, the content of fat-soluble vitamins is 1mg, the content of water-soluble vitamins is 2mg, the content of macroelements is 3mg, and the content of trace elements is 4 mg). The food materials to be identified include all food materials (typically multiple food materials) in the target food material selection database except any (or all) inedible food materials.

S140: and generating a food material collocation scheme according to the daily dietary energy requirement, the recommended nutrient intake and the edible alternative food materials.

In this embodiment, after the execution server determines the edible alternative food material, the food material matching scheme is generated according to the daily dietary energy requirement, the recommended nutrient intake and the edible alternative food material.

Compared with the prior art, according to the embodiment, different nutrients are more finely quantized, computer science and nutriology are fused, the nutrition requirement of a user is comprehensively calculated, the requirement of the type and the quantity of the food materials per day is worked out, the problem that the traditional food exchange portioning method needs to be manually calculated can be solved, specifically, when the food material collocation scheme is calculated, a server used for generating the food material collocation scheme firstly obtains user portrait data of the target user, then the daily dietary energy requirement and the nutrient recommended intake of the target user are determined according to the user portrait data, edible alternative food materials are determined according to the user portrait data, and finally the food material collocation scheme with higher precision can be generated according to the daily dietary energy requirement, the nutrient recommended intake and the edible alternative food materials.

In one embodiment, the food product supplier is a supplier capable of providing food products to the target user, such as a canteen, a vegetable market, a supermarket, or the like. It should be noted that in different application scenarios, the types and the number of the food material suppliers may be different, for example, in one scenario, the food material supplier only refers to a canteen, and in another scenario, the food material supplier may be a canteen or a vegetable market or a supermarket.

Specifically, some prior arts can automatically perform nutrition assessment for a patient according to physical information of the patient (such as height, weight, age, illness information, and the like) (here, accuracy of a nutrition assessment result is not considered for the moment) and provide a diet suggestion for the patient, however, even if the patient knows about the diet suggestion and knows which food materials and weights corresponding to various food materials, in a practical scenario, food material suppliers capable of providing food materials, such as a canteen, may provide different food material types, for example, a diet suggestion for a certain meal time or a certain day of a certain user needs to eat lotus seeds, lotus roots and Chinese cabbages, whereas canteen a provides only lotus roots and Chinese cabbages related thereto, and canteen B provides only lotus seeds and Chinese cabbages related thereto, which does not easily satisfy the diet suggestion for the user, and if the diet suggestion is not executed, it is not beneficial to manage the disease of the patient, and it can be understood that it is most convenient for the user to purchase or eat all food materials satisfying the diet recommendation from one food material supplier, which in turn is also beneficial to manage the disease of the patient. Therefore, in this embodiment, when a target user needs to purchase a food material for cooking by himself or a dish cooked based on the relevant food material, a request for purchasing the food material or the dish can be sent to an execution server (the execution server may refer to a terminal or a server of a certain food material supplier in this embodiment, or a server of a platform where a plurality of food material suppliers reside) through a user terminal (e.g. a mobile phone, a computer, etc.), if the execution server refers to a server of a certain food material supplier, the execution server determines a food material to be confirmed based on user image data of the target user and a target food material selection database (including all food materials that the current food material supplier can provide) and sends the food material to the user terminal of the target user, and the target user can select a food material that the target user wants to purchase or eat from the food materials to be confirmed through the user terminal, the execution server generates a food material collocation plan (including a plurality of food materials suggested to be consumed by the target user and recommended intakes corresponding to the various food materials) based on the edible alternative food materials, since all food materials displayed to the target user by the execution server through the user terminal are provided by the execution server, all food materials included in the food material matching scheme generated based on the edible alternative food materials that the target user confirms to purchase are available to the target user by the present food material supplier, therefore, the target user can purchase the food materials (dishes are provided when the food material supplier is a dish market or a supermarket or a store selling the food materials) or the dishes (dishes are provided when the food material supplier is a canteen) which accord with the diet suggestion from the food material supplier, and the control of the diseases of the target user is facilitated in the aspect of diet.

In another embodiment, if the execution server is a server accessing a platform hosting a plurality of food material suppliers, the execution server performs the step of extracting the food material to be confirmed from the preset target food material selection database according to all inedible food materials stored in the food material exclusion database, and further comprises: and determining a target food material provider associated with the target user, and taking a preset food material selection database corresponding to the target food material provider as a target food material selection database.

Specifically, since there are a plurality of food providers in the embodiment, and the food materials that can be provided by each food provider may be different, the food material to be confirmed to be displayed to the target user needs to be determined based on the food material selection database corresponding to the target food provider, so as to ensure that the target user can obtain the food material or the dish that can satisfy the diet recommendation of the target user from one food provider.

Further, in one embodiment, the step of generating the food material matching scheme according to the daily dietary energy requirement, the recommended nutrient intake and the edible alternative food material is followed by the steps of: and sending the food material collocation scheme to a target food material provider so that a worker of the target food material provider prepares the food material corresponding to the food material collocation scheme, or sending the food material collocation scheme to the target food material provider so that the worker of the target food material provider prepares a dish based on the food material corresponding to the food material collocation scheme.

acquiring food material supply information of any food material provider;

In this embodiment, if the execution server is a server that resides in a platform with a plurality of food material suppliers, the execution server will establish a corresponding food material selection database for each food material supplier residing in the platform. Specifically, after obtaining the food material supply information of any food material provider, the execution server establishes a food material selection database corresponding to the any food material provider according to the food material supply information. The food supply information includes all food materials that can be provided by the food material provider within a preset time interval (for example, within one day). Further, the food material supply information of the food material provider may be sent by the food material provider to the execution server through a terminal of the food material provider, or may be uploaded to the execution server by a staff of the platform after the staff collects the food material supply information of the food material provider.

Further, in an embodiment, the step of establishing the food material selection database corresponding to any food material provider according to the food material supply information further includes the following steps.

In this embodiment, after the execution server establishes the food material selection database for each food material provider, the food materials included in the database need to be maintained, and specifically, each time the food material update information belonging to any food material provider is received, the food material selection database corresponding to any food material provider may be updated according to the food material update information.

In this embodiment, assuming that the edible alternative food material comprises m (m is a positive integer greater than 0) alternative food materials, the recommended nutrient intake comprises n (n is a positive integer greater than 0) nutrients. The execution server firstly inquires the nutrient component information corresponding to each alternative food material from the food material database, and then establishes a first model based on the information. The food material database is a pre-constructed database, in which names (or codes) of a plurality of (for example, thousands) food materials and corresponding nutritional ingredients are introduced.

Specifically, let x_mRepresenting the components corresponding to the mth alternative food materials respectively; let A_ijRepresents the content of j-th group nutrient in the i-th alternative food material, wherein i is 1,2,3, …, m, j is 1,2,3, …, n; let y_nIndicating the recommended intake for the nth nutrient.

To minimize the relative error of each nutrient from the recommended intake, the optimization objective is then:

at the same time, it is desirable that the relative error of each nutrient does not exceed a preset threshold d (e.g., 15%), 0. ltoreq. d.ltoreq.1, for which constraint conditions are added: 1-D is less than or equal to D_j≤1+d。

And finally, changing the multi-objective optimization problem into a single objective, obtaining a final optimization problem (shown in the following formula IV) by adopting simple addition, and then solving the single objective optimization problem to obtain the food material collocation scheme, wherein the single objective optimization problem can be solved by using a genetic algorithm to improve the solving speed.

Based on the same inventive concept, the invention also provides a food material collocation scheme generation device. In one embodiment, as shown in fig. 4, the food material collocation scheme generation apparatus includes the following modules:

a user representation acquisition module 110 for acquiring user representation data of a target user;

a first determination module 120 for determining a daily dietary energy requirement and a recommended nutrient intake of a target user based on the user profile data;

a second determining module 130, configured to determine an edible alternative food material according to the user portrait data, where the edible alternative food material is a food material confirmed by the target user;

and a food material matching scheme generating module 140, configured to generate a food material matching scheme according to the daily dietary energy requirement, the recommended nutrient intake, and the edible alternative food materials.

In one embodiment, the user profile data includes user body basic information, food exclusion data, user illness information, and user energy expenditure data; the food exclusion data includes at least one food material that is not available for consumption by the target user; the edible alternative food materials confirmed by the target user include a plurality of food materials.

In one embodiment, the first determining module includes:

the meal demand determining submodule is used for determining the daily meal energy demand of the target user according to the body basic information of the user and the energy consumption data of the user;

and the nutrient intake determining submodule is used for determining the recommended nutrient intake according to the user body basic information and the user disease information.

Further, in one embodiment, a nutrient intake determination submodule, comprising:

the initial recommended intake determining unit is used for inquiring the nutrient database according to the basic information of the body of the user to obtain the initial recommended intake of the nutrients;

the adjustment information determining submodule is used for inquiring the disease knowledge database according to the disease information of the user and determining the adjustment information of the nutrient intake based on the inquiry result;

a nutrient intake determination unit for updating the initial nutrient recommended intake according to the nutrient intake adjustment information to obtain a nutrient recommended intake;

further, in one embodiment, the initial recommended nutrient intake includes a plurality of nutrients and recommended intakes for each nutrient. A nutrient intake determination unit comprising:

the first subunit is used for determining a nutrient to be updated and intake adjustment information corresponding to the nutrient to be updated in a plurality of nutrients included in the initial nutrient recommended intake according to the nutrient intake adjustment information, wherein the plurality of nutrients include at least one nutrient to be updated, and the nutrient to be updated is a nutrient which needs to be updated in the corresponding recommended intake;

and the second subunit is used for updating the recommended intake amount corresponding to each nutrient to be updated according to the intake amount adjustment information corresponding to each nutrient to be updated, so as to obtain the recommended intake amount of the nutrient.

In one embodiment, the second determining module includes:

the elimination database establishing sub-module is used for establishing a food material elimination database according to food elimination data and user disease information included in the user portrait data, and the food material elimination database includes at least one inedible food material;

the food material to be confirmed determining submodule is used for extracting food materials to be confirmed from a preset target food material selecting database according to all inedible food materials stored in a food material excluding database, wherein the food materials to be confirmed comprise a plurality of food materials except any inedible food material in the target food material selecting database;

the display submodule is used for displaying the food materials to be confirmed to the target user;

and the alternative food material determining submodule is used for receiving the alternative food material confirmation information from the target user and determining the food material which is associated with the alternative food material confirmation information in the food materials to be confirmed as the edible alternative food material.

In one embodiment, the second determining module further comprises a selection database determining module.

The selection database determining module is used for determining a target food material provider associated with a target user before all inedible food materials stored in the food material exclusion database are extracted from a preset target food material selection database to be confirmed, and taking the preset food material selection database corresponding to the target food material provider as the target food material selection database.

Further, in an embodiment, the food material collocation scheme generating device further includes:

the food material collocation scheme sending module is used for sending the food material collocation scheme to a target food material provider after the food material collocation scheme is generated according to the daily dietary energy requirement, the nutrient recommended intake and the edible alternative food materials, so that staff of the target food material provider can prepare the food materials corresponding to the food material collocation scheme.

Further, in another embodiment, the exclude database building sub-module comprises:

a first food material determining unit for determining a first inedible food material corresponding to the food exclusion data;

the second food material determining unit is used for determining a second inedible food material corresponding to the user disease information;

and the excluding database establishing unit is used for establishing a food material excluding database according to the first inedible food material and the second inedible food material.

Further, in yet another embodiment, the food material matching scheme generating apparatus further comprises a selection database establishing module. The system comprises a selection database establishing module, a selection database establishing module and a selection database establishing module, wherein the selection database establishing module is used for acquiring food material supply information provided by any food material provider before determining edible alternative food materials according to user portrait data, and the food material supply information comprises a plurality of food materials which can be provided by the food material provider within a preset time interval; and establishing a food material selection database corresponding to any food material provider according to the food material supply information.

Further, in an embodiment, the food material collocation scheme generation apparatus further includes a selection database update module. The selection database updating module is used for updating the food material selection database corresponding to any food material provider according to the food material update information when the food material update information belonging to any food material provider is received after the food material selection database corresponding to any food material provider is established according to the food material supply information.

In one embodiment, the food material collocation scheme generation module includes:

the model building module is used for building a first model according to daily dietary energy demand, nutrient recommended intake and edible alternative food materials;

and the food material collocation scheme generation submodule is used for solving the first model and generating a food material collocation scheme according to a result obtained by solving the first model.

For specific limitations of the food material collocation scheme generation apparatus, reference may be made to the above limitations of the food material collocation scheme generation method, which are not described herein again. All or part of the modules in the food material collocation scheme generation device can be realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.

In one embodiment, a computer device is provided, the internal structure of which may be as shown in FIG. 5. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing data such as user portrait data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a food material matching scheme generation method.

Those skilled in the art will appreciate that the architecture shown in fig. 5 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:

acquiring user portrait data of a target user; determining daily dietary energy demand and recommended nutrient intake of a target user according to the user portrait data; determining an edible alternative food material according to the user portrait data, wherein the edible alternative food material is a plurality of food materials confirmed by the target user; and generating a food material collocation scheme according to the daily dietary energy requirement, the recommended nutrient intake and the edible alternative food materials.

In one embodiment, the processor executes a computer program to perform the following steps in determining a daily dietary energy requirement and a recommended nutrient intake for a target user based on user profile data:

determining daily meal energy requirement of a target user according to the body basic information of the user and the energy consumption data of the user; and determining the recommended nutrient intake according to the body basic information and the disease information of the user.

In one embodiment, the processor executes the computer program to determine recommended nutrient intake based on the user body basic information and the user disease information, and further performs the steps of:

inquiring a nutrient database according to the basic information of the body of the user to obtain the recommended intake of the initial nutrients; inquiring a disease knowledge database according to the disease information of the user, and determining nutrient intake adjustment information based on the inquiry result; and updating the initial nutrient recommended intake according to the nutrient intake adjustment information to obtain the nutrient recommended intake.

In one embodiment, the processor executes the computer program to perform the following steps when updating the initial nutrient recommended intake based on the nutrient intake adjustment information to obtain the nutrient recommended intake:

determining nutrients to be updated and intake adjustment information corresponding to the nutrients in a plurality of nutrients included in the initial nutrient recommended intake according to the nutrient intake adjustment information, wherein the plurality of nutrients include at least one nutrient to be updated, and the nutrients to be updated are nutrients required to be updated in the corresponding recommended intake; and updating the recommended intakes corresponding to the various nutrients to be updated according to the intake adjustment information corresponding to the various nutrients to be updated to obtain the recommended intakes of the nutrients.

In one embodiment, the processor executes the computer program to perform the following steps when determining the edible alternative food material from the user representation data:

establishing a food material exclusion database according to food exclusion data and user disease information included in the user portrait data, wherein the food material exclusion database includes at least one inedible food material; extracting food materials to be confirmed from a preset target food material selection database according to all inedible food materials stored in a food material exclusion database, wherein the food materials to be confirmed comprise a plurality of food materials except any inedible food material in the target food material selection database; displaying the food materials to be confirmed to a target user; receiving alternative food material confirmation information from a target user, and determining the food materials related to the alternative food material confirmation information in the food materials to be confirmed as edible alternative food materials.

In one embodiment, before the processor executes the computer program to extract the food material to be confirmed from the preset target food material selection database according to all inedible food materials stored in the food material exclusion database, the following steps are further implemented:

In one embodiment, the processor executes the computer program, and after the step of generating the food material collocation plan according to the daily dietary energy requirement, the recommended nutrient intake and the edible alternative food material is realized, the following steps are further realized:

In one embodiment, the processor executes the computer program to realize the following steps when establishing the food material exclusion database according to the food exclusion data and the user disease information included in the user image data:

determining a first inedible food material corresponding to the food exclusion data; determining a second inedible food material corresponding to the user disease information; a food material exclusion database is established based on the first inedible food material and the second inedible food material.

In one embodiment, the processor executes the computer program to perform the following steps prior to the step of determining an edible alternative food material from the user representation data:

the method comprises the steps of obtaining food material supply information provided by any food material provider, wherein the food material supply information comprises a plurality of food materials which can be provided by the food material provider within a preset time interval; and establishing a food material selection database corresponding to any food material provider according to the food material supply information.

In one embodiment, the processor executes the computer program to perform the following steps after the step of establishing the food material selection database corresponding to any food material provider according to the food material supply information:

In one embodiment, the processor executes the computer program to perform the following steps when generating the food material collocation plan according to the daily meal energy requirement, the recommended nutrient intake and the edible alternative food material:

establishing a first model according to daily dietary energy requirement, recommended nutrient intake and edible alternative food materials; and solving the first model, and generating a food material collocation scheme according to a result obtained by solving the first model.

In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:

In one embodiment, the computer program when executed by the processor, when determining the daily dietary energy requirement and the recommended nutrient intake for the target user based on the user profile data, further performs the steps of:

In one embodiment, the computer program when executed by the processor, when determining the recommended intake of nutrients based on the user's physical basic information and the user's disease information, further performs the steps of:

In one embodiment, the computer program when executed by the processor to update the initial nutrient recommended intake based on the nutrient intake adjustment information to obtain a nutrient recommended intake further implements the steps of:

In one embodiment, the computer program when executed by the processor, when determining an edible alternative food material from the user representation data, further implements the steps of:

In one embodiment, the computer program when executed by the processor further implements the following steps before extracting the food material to be confirmed from the preset target food material selection database according to all inedible food materials stored in the food material exclusion database:

In one embodiment, the computer program when executed by the processor further implements the following steps after the step of generating the food material collocation plan based on the daily dietary energy requirement, the recommended nutrient intake, and the edible alternative food material:

In one embodiment, the computer program, when executed by the processor, when building a food material exclusion database based on food exclusion data and user disease information included in the user image data, further implements the steps of:

In one embodiment, the computer program when executed by the processor further performs the steps of, prior to the step of determining an edible alternative food material from the user representation data:

In one embodiment, the computer program when executed by the processor further performs the following steps after the step of establishing a food material selection database corresponding to the any food material provider according to the food material supply information:

In one embodiment, the computer program when executed by the processor further implements the following steps in generating a food material collocation plan based on the daily dietary energy requirement, the recommended nutrient intake, and the edible alternative food material:

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims

1. A method for generating a food material collocation scheme is characterized by comprising the following steps:

acquiring user portrait data of a target user;

determining daily dietary energy requirements and recommended nutrient intake of the target user according to the user profile data;

determining an edible alternative food material according to the user portrait data, wherein the edible alternative food material is the food material confirmed by the target user;

2. The food material collocation scheme generation method of claim 1,

the user representation data comprises user body basic information, food exclusion data, user disease information and user energy consumption data; the food exclusion data comprises at least one food material that is not available to the target user for consumption;

the target user identified edible alternative food materials comprise a plurality of food materials.

3. The food material collocation scheme generation method of claim 2,

the step of determining the daily dietary energy requirement and recommended nutrient intake of the target user based on the user profile data comprises:

determining daily dietary energy requirements of the target user according to the user body basic information and the user energy consumption data;

determining recommended nutrient intake according to the user body basic information and the user disease information;

preferably, the step of determining the recommended intake of nutrients according to the user body basic information and the user disease information comprises:

inquiring a nutrient database according to the basic information of the user body to obtain the recommended intake of the initial nutrients;

inquiring a disease knowledge database according to the user disease information, and determining nutrient intake adjustment information based on the inquiry result;

updating the initial nutrient recommended intake according to the nutrient intake adjustment information to obtain a nutrient recommended intake;

preferably, the initial recommended nutrient intake includes a plurality of nutrients and recommended intakes corresponding to the various nutrients; the step of updating the initial nutrient recommended intake according to the nutrient intake adjustment information to obtain a nutrient recommended intake includes:

determining a nutrient to be updated and intake adjustment information corresponding to the nutrient to be updated in a plurality of nutrients included in the initial nutrient recommended intake according to the nutrient intake adjustment information, wherein the plurality of nutrients include at least one nutrient to be updated, and the nutrient to be updated is a nutrient which needs to be updated in the corresponding recommended intake;

4. The food material collocation scheme generation method of claim 2,

the step of determining an edible alternative foodstuff material from the user representation data comprises:

establishing a food material exclusion database according to the food exclusion data and the user disease information included in the user portrait data, wherein the food material exclusion database includes at least one inedible food material;

extracting food materials to be confirmed from a preset target food material selection database according to all inedible food materials stored in the food material exclusion database, wherein the food materials to be confirmed comprise a plurality of food materials in the target food material selection database except any inedible food material;

displaying the food materials to be confirmed to the target user;

receiving alternative food material confirmation information from the target user, and determining the food material associated with the alternative food material confirmation information in the food materials included in the food materials to be confirmed as the edible alternative food material;

preferably, the step of extracting the food material to be confirmed from the preset target food material selection database according to all inedible food materials stored in the food material exclusion database further includes:

determining a target food material provider associated with the target user, and taking a preset food material selection database corresponding to the target food material provider as a target food material selection database;

preferably, the step of generating a food material collocation scheme according to the daily dietary energy requirement, the recommended nutrient intake and the edible alternative food material is followed by further comprising

And sending the food material matching scheme to the target food material provider so that staff of the target food material provider can prepare the food materials corresponding to the food material matching scheme.

5. The food material collocation scheme generation method of claim 4,

the step of establishing a food material exclusion database according to the food exclusion data and the user disease information included in the user portrait data includes:

and establishing a food material exclusion database according to the first inedible food material and the second inedible food material.

6. The food material collocation scheme generation method of claim 4,

the step of determining an edible alternative food material from the user representation data may also include:

establishing a food material selection database corresponding to any food material provider according to the food material supply information;

preferably, the step of establishing a food material selection database corresponding to any food material provider according to the food material supply information further includes the following steps.

7. The food material collocation scheme generation method of claim 2,

the step of generating a food material collocation plan according to the daily dietary energy requirement, the recommended nutrient intake and the edible alternative food materials comprises:

establishing a first model according to the daily dietary energy requirement, the recommended nutrient intake and the edible alternative food materials;

8. An apparatus for generating a food material matching scheme, comprising:

a first determination module for determining a daily dietary energy requirement and a recommended nutrient intake of the target user based on the user profile data;

a second determining module, configured to determine an edible alternative food material according to the user representation data, where the edible alternative food material is a food material confirmed by the target user;

and the food material matching scheme generating module is used for generating a food material matching scheme according to the daily dietary energy requirement, the nutrient recommended intake and the edible alternative food materials.

9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 7 are implemented when the computer program is executed by the processor.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.