CN117453756A

CN117453756A - Menu generation method, device, equipment and storage medium

Info

Publication number: CN117453756A
Application number: CN202311504452.9A
Authority: CN
Inventors: 任富佳; 胡杨; 黄闻霞; 王楠楠
Original assignee: Hangzhou Robam Appliances Co Ltd
Current assignee: Hangzhou Robam Appliances Co Ltd
Priority date: 2023-11-13
Filing date: 2023-11-13
Publication date: 2024-01-26

Abstract

The application discloses a menu generation method, device, equipment and storage medium, wherein the method comprises the following steps: acquiring menu demand information and taste demand information of a user; the menu demand information comprises information of at least one current food material; judging whether a menu associated with each current food material exists in a menu database at the same time based on the information of the current food material; when the recipes associated with each piece of current food material information do not exist at the same time, acquiring historical recipe data of all current food materials, and determining target recipe parameters of the current recipes based on the historical recipe data; and adjusting the current menu according to the target menu parameters of the current menu and the taste requirement information to obtain a first target menu. According to the scheme, the target menu which accords with the cooking taste of the user can be obtained, personalized menu recommendation of the user is realized, and user experience is improved to a great extent.

Description

Menu generation method, device, equipment and storage medium

Technical Field

The invention relates to the technical field of intelligent cooking, in particular to a menu generation method, a menu generation device, menu generation equipment and a storage medium.

Background

With the rapid development of intelligent technology, artificial intelligent technology has been increasingly applied to various fields such as intelligent manufacturing, smart home, smart finance, smart medical and so on, and at the same time, more and more intelligent products have been applied to daily life of people such as intelligent menu in kitchen field. In order to meet the requirements of users and enable the users to obtain better user experience, how to generate intelligent menus is particularly important.

Currently, in the related art, a menu list is formed by acquiring diet habit information of a user and making a corresponding menu to store in a menu database, so that the related menu is recommended to the user through the menu list. However, in the scheme, the types of food materials used by the user in the actual cooking process may be very limited, and a menu corresponding to the existing food materials of the user may not exist in the menu list, so that the user experience is poor.

Disclosure of Invention

Based on the foregoing, it is necessary to provide a method, an apparatus, a device and a storage medium for generating a menu, which can obtain a target menu according with the cooking taste of a user, and realize personalized menu recommendation of the user, thereby improving user experience to a great extent.

In a first aspect, an embodiment of the present application provides a method for generating a menu, including:

acquiring menu demand information and taste demand information of a user; the menu demand information comprises information of at least one current food material;

judging whether a menu associated with each current food material exists in a menu database at the same time based on the information of the current food material;

when the recipes associated with each piece of current food material information do not exist at the same time, acquiring historical recipe data of all current food materials, and determining target recipe parameters of the current recipes based on the historical recipe data;

and adjusting the current menu according to the target menu parameters and the taste requirement information of the current menu to obtain a first target menu.

In one embodiment, determining the target recipe parameters of the current recipe based on the historical recipe data includes:

acquiring all cooking modes and morphological parameters of food materials of the group to which each current food material belongs from the historical menu data of the current food material;

and determining target menu parameters of the current menu based on all cooking modes and the morphological parameters.

In one embodiment, determining target recipe parameters for a current recipe based on historical recipe data includes:

Determining the same key cooking modes in each current food material based on all the cooking modes of the current food material;

determining each form parameter corresponding to the key cooking mode in each current food material, and generating target cooking parameters according to the form parameters and the key cooking modes;

determining standard seasoning parameters with the use frequency of each current food material being greater than a preset threshold value in the history menu data based on the history menu data of each current food material;

determining a target seasoning parameter of the current menu and a target taste parameter of the current menu according to the standard seasoning parameters; the target condiment parameters include target condiment weight, target condiment addition order, and target condiment addition time.

In one embodiment, the information of the at least one current food material includes a weight of the at least one current food material, and determining the target condiment parameter of the current recipe and the target taste parameter of the current recipe based on the standard condiment parameter includes:

determining a target condiment weight for each current food material in the current recipe based on the weight of the current food material and the condiment weight in the standard condiment parameter;

acquiring the priority of selecting condiments in the historical menu data of the group to which the current food material belongs;

Determining a seasoning addition order of the current recipe based on the target seasoning weight and the priority of seasoning selection;

obtaining a target seasoning adding time of the current menu based on the historical menu data and the target cooking parameters;

and determining the target taste parameter of the current menu according to the weight of the target seasoning and the weight of the current food materials.

In one embodiment, obtaining a target seasoning addition time for a current recipe based on historical recipe data and target cooking parameters includes:

determining a cooking curve of each current food material in the cooking process from the history menu-based data; the integral area of the cooking curve is used for representing the heat absorbed by the current food material in the cooking process;

taking the current food material with the largest integral area in each cooking curve as a main food material, so as to preferentially add the main food material in the current menu;

when the remaining integral area of the cooking curve of the main food material is the same as the integral area of the cooking curve of the other food materials, the other food materials are added.

In one embodiment, according to a target recipe parameter and taste requirement information of a current recipe, the current recipe is adjusted to obtain a first target recipe, including:

Determining a difference value corresponding to a target taste parameter in the target menu parameters and a taste parameter corresponding to the taste requirement information;

determining a seasoning to be adjusted and the weight to be adjusted corresponding to the seasoning to be adjusted from the target seasoning based on the difference value;

and updating the condiments to be adjusted and the weight to be adjusted in the current menu to obtain a first target menu.

In one embodiment, obtaining taste requirement information of a user includes:

responding to input operation of a user, and acquiring taste requirement information of the user; or,

acquiring menu browsing data of a user in preset time;

based on menu browsing data, acquiring each browsing time of a user on different taste menus and the browsing quantity corresponding to each browsing time;

and obtaining taste requirement information of the user according to the browsing quantity, the browsing time and the preset scores corresponding to the browsing times.

In one embodiment, the recipe demand information further includes nutrient demand information of the user, and after acquiring the recipe demand information and the taste demand information of the user, the method further includes:

determining a recombined menu corresponding to the current food material from a menu database based on the menu demand information;

Adjusting the condiment parameters and the cooking parameters in the recombined menu based on the menu demand information to obtain an intermediate menu;

determining a nutrition recipe meeting nutrition requirements corresponding to the nutrition requirement information from the intermediate recipe;

and adjusting the nutrition menu according to the taste requirement information to obtain a second target menu.

In one embodiment, determining a restructured recipe corresponding to the current food material from a recipe database based on the recipe demand information includes:

judging whether the current food material is the existing food material in the menu database based on the information of the current food material;

if yes, determining the group in which the current food material is located and other food materials associated with the current food material in the group;

acquiring a menu of other food materials in a menu database, and updating the other food materials in the menu to current food materials to obtain a recombined menu corresponding to the current food materials.

In one embodiment, after determining whether the current food material is an existing food material in the recipe database, the method further includes:

if the current food material is not the current food material in the menu database, searching whether the current food material exists in the alias database;

when the current food material exists, searching the name of the current food material in a menu database;

And when the searching is successful, determining a recombined menu corresponding to the current food material from a menu database based on the name.

In a second aspect, an embodiment of the present application provides a menu generating apparatus, including:

the acquisition module is used for acquiring menu demand information and taste demand information of a user; the menu demand information comprises information of at least one current food material;

the judging module is used for judging whether a menu associated with each current food material exists in the menu database at the same time or not based on the information of the current food material;

the determining module is used for acquiring historical menu data of all current food materials when the menus associated with each piece of current food material information do not exist at the same time, and determining target menu parameters of the current menu based on the historical menu data;

and the adjusting module is used for adjusting the current menu according to the target menu parameters of the current menu and the taste requirement information to obtain a first target menu.

In a third aspect, an embodiment of the present application provides a computer device, including a memory and a processor, where the memory stores a computer program, and the processor implements the steps of the recipe generation method provided in any embodiment of the present application when the computer program is executed.

In a fourth aspect, embodiments of the present application provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the recipe generation method provided by any embodiment of the present application.

According to the menu generation method, device and equipment and storage medium, the menu demand information and the taste demand information of the user are obtained, the menu demand information comprises at least one piece of information of current food materials, whether a menu associated with each current food material exists in a menu database at the same time is judged based on the current food material information, when the menus associated with each piece of current food material information do not exist at the same time, historical menu data of all current food materials are obtained, target menu parameters of the current menu are determined based on the historical menu data, and the current menu is adjusted according to the target menu parameters and the taste demand information of the current menu, so that a first target menu is obtained. Compared with the prior art, the technical scheme fully considers the current food materials of the user, when the recipes associated with each piece of current food material information are not available at the same time, the target recipe parameters of the current recipes can be accurately and comprehensively determined according to the acquired historical recipe data of the current food materials under the condition that the types of the instant food materials are limited and the associated recipes cannot be acquired, and then the target recipes meeting the cooking tastes of the user can be flexibly adjusted according to the target recipe parameters and the taste requirement information of the current recipes, so that the personalized recipe recommendation of the user is realized, and the user experience is greatly improved.

Drawings

Other features, objects and advantages of the present application will become more apparent upon reading of the detailed description of non-limiting embodiments, made with reference to the following drawings, in which:

fig. 1 is a schematic structural diagram of a menu generating system according to an embodiment of the present application;

fig. 2 is a schematic flow chart of a recipe generation method according to an embodiment of the present application;

FIG. 3 is a flow chart of a method for determining target seasoning parameters and target taste parameters for a current recipe according to an embodiment of the present application;

fig. 4 is a schematic flow chart of a recipe generation method according to an embodiment of the present application;

fig. 5 is a schematic flow chart of generating a menu according to an embodiment of the present application;

FIG. 6 is a schematic flow chart of a method for generating a spareribs corn soup recipe according to an embodiment of the present application;

fig. 7 is a schematic flow chart of outputting a recommended menu according to the taste of a user according to an embodiment of the present application;

fig. 8 is a schematic flow chart of searching for food material names in a menu database and an alias database according to an embodiment of the present application;

fig. 9 is a schematic structural diagram of a menu generating device according to an embodiment of the present application;

fig. 10 is a schematic structural diagram of a computer device according to an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application. It should be noted that, for convenience of description, only the portions related to the invention are shown in the drawings.

It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

It can be understood that with the continuous development and progress of science and technology, intelligent products have been advanced into the life of users, such as intelligent recipes, which help and coact users to perform operation cooking according to the content recorded in the intelligent recipes by recording information such as food materials, auxiliary materials, working parameters required by cooking appliances and the like corresponding to each recipe in advance, so as to obtain dishes meeting the requirements of users. Currently, in the related art, a menu list is formed by acquiring diet habit information of a user and making a corresponding menu to store in a menu database, so that the related menu is recommended to the user through the menu list. However, in the actual cooking process, the user of the scheme has very limited types of food materials used at present, and a menu corresponding to the existing food materials of the user may not exist in the menu list, so that the user experience is poor.

Based on the defects, compared with the prior art, the technical scheme fully considers the current food materials of the user, and under the conditions that the types of instant food materials are limited and the associated menu cannot be acquired when the recipes associated with each piece of current food material information are different, the target menu parameters of the current menu can be accurately and comprehensively determined according to the acquired historical menu data of the current food materials, and then the target menu parameters and the taste requirement information of the current menu are used for flexibly adjusting the current menu to obtain the target menu meeting the cooking taste of the user, so that the personalized menu recommendation of the user is realized, and the user experience is greatly improved.

Fig. 1 is an implementation environment architecture diagram of a recipe generation method according to an embodiment of the present application. As shown in fig. 1, the implementation environment architecture includes: a terminal 100 and a server 200.

The process of generating the menu may be performed at the terminal 100 or the server 200 in the smart kitchen field. For example, the terminal 100 obtains the menu demand information and the taste demand information of the user, and a target menu may be generated locally at the terminal 100 according to the menu demand information and the taste demand information of the user; the recipe demand information and the taste demand information of the user may also be sent to the server 200, so that the server 200 obtains the recipe demand information and the taste demand information of the user, so as to generate a target recipe according to the recipe demand information and the taste demand information of the user, and then send the target recipe to the terminal 100, so as to implement the generation processing of the target recipe.

The terminal 100 may be a terminal device in various AI application scenarios. For example, the terminal 100 may be an intelligent home device such as an intelligent television, an intelligent television set-top box, or the terminal 100 may be a mobile portable terminal such as a smart phone, a tablet computer, and an electronic book reader, or the terminal 100 may be an intelligent wearable device such as an intelligent glasses, an intelligent watch, and the embodiment is not limited in this way.

Among them, the terminal 100 may have installed therein an AI application based on machine learning.

The server 200 may be a server device that provides a background service for the AI application installed in the terminal 100 described above. The server 200 may be a server, a server cluster or a distributed system formed by a plurality of servers, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (content delivery network, CDN), basic cloud computing services such as big data and artificial intelligent platforms, and the like.

A communication connection is established between the terminal 100 and the server 200 through a wired or wireless network. Alternatively, the wireless network or wired network described above uses standard communication techniques and/or protocols. The network is typically the Internet, but may be any network including, but not limited to, a local area network (Local Area Network, LAN), metropolitan area network (Metropolitan Area Network, MAN), wide area network (Wide Area Network, WAN), a mobile, wired or wireless network, a private network, or any combination of virtual private networks.

For easy understanding and explanation, the method, apparatus, device and storage medium for generating a menu according to the embodiments of the present application are described in detail below with reference to fig. 2 to 10.

Fig. 2 is a flow chart of a recipe generation method according to an embodiment of the present application, where the method is applied to a terminal, as shown in fig. 2, and the method includes:

s101, acquiring menu demand information and taste demand information of a user; the recipe demand information includes information of at least one current food material.

The menu demand information of the user refers to information of a menu which is required to be formulated by the user according to the current food materials. The taste demand information refers to information of taste required by the user. For example, when the current food materials are green peppers and eggs, the recipe demand information can be green peppers fried eggs, and the taste demand information can be slightly spicy, medium spicy or heavy spicy, etc. The recipe demand information may include information of at least one current food material, and the information of the current food material may include a weight of the current food material, a group of the current food material, and an identifier of the current food material, where the identifier of the current food material is used to uniquely represent identity information of the current food material.

In this embodiment, as an implementation manner, the above-mentioned menu requirement information and taste requirement information of the user may be obtained simultaneously, that is, when the menu requirement information and taste requirement information of the user are obtained, the data acquisition device may be called to obtain the menu requirement information and taste requirement information of the user, the menu requirement information and taste requirement information of the user may be obtained through cloud, the menu requirement information and taste requirement information of the user may be obtained through a database or a blockchain, or the menu requirement information and taste requirement information of the user may be obtained through external device import.

As another implementation manner, the recipe demand information and the taste demand information of the user may be obtained in batches, for example, the recipe demand information of the user is obtained first, the recipe demand information of the user is obtained by responding to a first input operation of the user, and the taste demand information of the user is obtained by responding to a second input operation of the user.

In the embodiment, by acquiring the menu demand information of the user and the taste demand information of the user, good data guiding information can be provided for the subsequent generation of the target menu, so that the corresponding menu is generated more pertinently according to the menu demand information and the taste demand information, the accuracy of determining the menu is improved, and the diversity demands of the user are met.

S102, judging whether a menu associated with each current food material exists in a menu database at the same time based on the information of the current food material.

S103, when the recipes associated with each piece of current food material information do not exist at the same time, acquiring historical recipe data of all current food materials, and determining target recipe parameters of the current recipes based on the historical recipe data.

It should be noted that a recipe database may be established in advance, and the recipe database includes a food material classification library, and classifies food materials, for example, according to food material characteristics, mainly related to food material maturity and cooking method similarity, and may be classified into melons and fruits, rhizomes, stems and leaves, mushrooms, pork, beef and mutton, poultry, meat products, freshwater fish, salted fish, shells, shrimps, crabs, algae, five cereals, dried fruits, beans, bean products, and the like.

Wherein, the classification of the food materials can be different in consideration of different cooking modes, for example, the cooking modes are divided into 8 types of cooking, stewing, soup stewing, stir-frying, cold dishes, baking and roasting; under each type of food material, the division is again made according to the cooking mode, and each food material name can only appear once in one cooking mode.

The menu associated with each current food material may be a menu corresponding to the group in which the current food material is located, or may be a menu corresponding to other food materials similar to the current food material in the group in which the current food material is located.

After the menu demand information of the user is obtained, whether a menu associated with each current food material exists in the menu database at the same time can be judged, for example, the current food materials comprise two food materials, namely an a food material and a b food material, whether the menu associated with the a food material exists or not can be searched from the menu database, whether the menu associated with the b food material exists or not is searched from the menu database in parallel, and when the menu associated with each current food material information does not exist at the same time, the history menu data of the current food material is obtained.

It can be understood that the above-mentioned history menu data refers to the menu data which is pre-established and associated with the current food material, and may be stored in a menu database, where the history menu data in the menu database may be recorded according to a standard template, where the standard template includes a cooking technique, a standby step, and a cooking parameter, and each food material corresponds to a standby step and a cooking step, and the standby step and the cooking step of the same food material may be extracted and grouped together to form a menu database.

Optionally, in determining the target recipe parameters of the current recipe based on the history recipe data, all cooking modes and form parameters of the food materials of the group to which each current food material belongs may be obtained from the history recipe data of the current food material, and then the target recipe parameters of the current recipe are determined based on all the cooking modes and form parameters.

The above-mentioned all cooking manners refer to cooking manners of the food materials of the current food material group in the history menu data, for example, when the current food material is an egg, the current food material group is an egg, and all the cooking manners corresponding to the food materials of the egg may include soup cooking, stir-frying, steaming, and the like. The morphological parameters are used for representing morphological information corresponding to the food materials under different cooking modes, and can be strip-shaped, block-shaped, liquid-shaped and the like. The shape parameter may be one shape parameter for each cooking mode, or one shape parameter for a plurality of cooking modes.

Specifically, the group of the current food material can be determined, then the food material of the group of the current food material is searched, all cooking modes and form parameters of the food material are obtained from the history menu data of the current food material, and all cooking modes and form parameters are analyzed and combined to obtain the target menu parameters of the current menu. Wherein the target recipe parameters may include a target cooking parameter, a target seasoning parameter, and a target taste parameter.

The target cooking parameters of the current menu refer to the corresponding cooking parameters of the current menu in the cooking process, and may include cooking temperature, cooking time and the like; the target seasoning parameters refer to seasoning parameters added to the current food materials in the cooking process of the current recipe, and the target seasoning parameters can comprise the adding sequence of the seasoning and the weight of the seasoning; the target taste parameters of the current recipe may refer to the taste scores of the current recipe, which may include, for example, 100%, 50%, and 20% peppery, and may also be 100%, 50%, and 20% sweet.

According to the embodiment, by acquiring the historical menu data of all the current food materials and determining the target menu parameters of the current menu based on the historical menu data, the relevant parameters of the current menu can be determined in a finer granularity, and the accuracy of determining the current menu is improved.

S104, according to the target menu parameters and the taste requirement information of the current menu, the current menu is adjusted to obtain a first target menu.

The first target menu refers to a menu which is cooked by using the current food materials and meets the taste requirement of the user, namely, a menu which is personalized and customized for the user according to the current food materials. The target taste parameter may include a main taste value of the current recipe or a taste value corresponding to a taste having the largest proportion.

Specifically, after the target taste parameter and the taste requirement information of the current recipe are obtained, a difference value corresponding to the taste parameter corresponding to the taste requirement information of the target taste parameter can be determined, the to-be-adjusted seasoning and the to-be-adjusted weight corresponding to the to-be-adjusted seasoning are determined from the target seasoning based on the difference value, and then the to-be-adjusted seasoning and the to-be-adjusted weight are updated in the current recipe, so that the first target recipe is obtained.

As an implementation manner, when the difference value between the target taste parameter and the taste parameter corresponding to the taste requirement information is a positive value, that is, the taste value is greater than the taste value corresponding to the taste requirement information, the taste value representing the current recipe is heavier and does not meet the taste requirement of the user, the current recipe needs to be adjusted, and the to-be-adjusted seasoning and the to-be-adjusted weight corresponding to the to-be-adjusted seasoning can be determined from the target seasoning, for example, the current weight of the to-be-adjusted seasoning is reduced, so that the first target recipe is obtained.

As another implementation manner, when the difference value between the target taste parameter and the taste parameter corresponding to the taste requirement information is negative, that is, the taste value is smaller than the taste value corresponding to the taste requirement information, the taste value representing the current recipe is lighter and does not meet the taste requirement of the user, the current recipe needs to be adjusted, the to-be-adjusted seasoning and the to-be-adjusted weight corresponding to the to-be-adjusted seasoning can be determined from the target seasoning, for example, the current weight of the to-be-adjusted seasoning is increased, so as to obtain the first target recipe.

Illustratively, the condiments added to the current food material may include table salt, white vinegar, aged vinegar, aromatic vinegar, etc., each of which also represents a different taste value, such as table salt: 100% salty; white sugar: 100% sweetness; mature vinegar: 100% acidity; aromatic vinegar: 98% acidity +2% sweetness. When the target taste parameter is, for example, acidity, and when the difference between the target taste parameter and the taste value corresponding to the taste requirement information is positive, that is, the acidity of the target taste parameter is greater than the acidity corresponding to the taste requirement information of the user, the condiments in the current recipe need to be adjusted, for example, when the target condiments in the current recipe are mature vinegar, the weight of the mature vinegar needs to be adjusted, and the first target recipe which meets the taste of the user is obtained by reducing the weight of the mature vinegar.

According to the menu generation method, the menu demand information and the taste demand information of the user are obtained, the menu demand information comprises information of at least one current food material, whether a menu associated with each current food material exists in a menu database at the same time is judged based on the current food material information, when the menus associated with each current food material information do not exist at the same time, historical menu data of all current food materials are obtained, target menu parameters of the current menu are determined based on the historical menu data, and the current menu is adjusted according to the target menu parameters and the taste demand information of the current menu, so that a first target menu is obtained. Compared with the prior art, the technical scheme fully considers the current food materials of the user, when the recipes associated with each piece of current food material information are not available at the same time, the target recipe parameters of the current recipes can be accurately and comprehensively determined according to the acquired historical recipe data of the current food materials under the condition that the types of the instant food materials are limited and the associated recipes cannot be acquired, and then the target recipes meeting the cooking tastes of the user can be flexibly adjusted according to the target recipe parameters and the taste requirement information of the current recipes, so that the personalized recipe recommendation of the user is realized, and the user experience is greatly improved.

In one embodiment, the present application further provides a specific implementation manner of determining the target recipe parameters of the current recipe based on all the cooking modes and the morphological parameters, referring to fig. 3, the method includes:

s201, determining the same key cooking modes in each current food material based on all the cooking modes.

S202, determining each form parameter corresponding to the key cooking mode in each current food material, and generating target cooking parameters according to the form parameters and the key cooking modes.

S203, determining standard seasoning parameters with the use frequency of each current food material being greater than a preset threshold value in the history menu data based on the history menu data of each current food material.

It should be noted that, the above-mentioned key cooking modes refer to the same cooking mode among all the cooking modes of the respective current food materials. For example, the current food materials are a food material and b food material respectively, the cooking modes in the historical menu data of the a food material comprise cooking, stewing and soup stewing, and the cooking modes in the historical menu data of the b food material comprise soup stewing, stir-frying and frying, so that the same cooking mode in all the cooking modes of the current food material is soup stewing, and the key cooking mode is soup stewing.

The target cooking parameter refers to a parameter in the current recipe, which needs to cook the current food material, and may include, for example, a cooking time, a cooking temperature, a shape of the current food material during cooking, a cooking mode, and the like. The morphological parameters refer to the morphological conditions of the current food material corresponding to the key cooking mode, and may include the shape and size of the current food material, for example, the morphological parameters of the a food material include bars, blocks, and the like. The standard condiments parameters refer to condiments with the use frequency higher than a preset threshold in the historical menu data, and can comprise the weight of the condiments and the addition sequence of the condiments, and the preset threshold is set in a self-defined mode according to actual requirements. The target seasoning parameter is a seasoning parameter in the current recipe that needs to be added to the current food material.

Specifically, taking the current food material as an example of the a food material and the b food material respectively, after the respective history menu data of the a food material and the b food material are obtained, all cooking modes of each current food material can be obtained from the history menu data of the a food material and the b food material, for example, the cooking modes in the history menu data of the a food material comprise cooking, stewing and soup stewing, and the cooking modes in the history menu data of the b food material comprise soup stewing, stir-frying and frying, and then the same key cooking modes in each current food material, such as soup stewing mode, are determined; and determining each morphological parameter corresponding to the key cooking mode in each current food material, wherein the morphological parameter corresponding to the food material a is in a block shape, and the morphological parameter corresponding to the food material b is also in a block shape when soup is cooked, and generating target cooking parameters according to the morphological parameters and the key cooking mode, wherein the target cooking parameters comprise cooking time, cooking temperature, cooking mode, morphology and the like of the food material a and the food material b in the cooking process. Among the automatically generated cooking parameters, a cooking parameter of a currently difficult-to-get-cooked food among the food materials may be selected as the target cooking parameter.

After the historical recipe data of each current food material is obtained, the historical condiment parameters can be obtained from each historical recipe data, the condiment parameters can comprise condiment adding quality and condiment adding sequence, the use frequency of the historical condiment parameters in each historical recipe data is determined, the historical condiment parameters with the use frequency being greater than a preset threshold value are used as standard condiment parameters, for example, the preset threshold value is 5, and the historical condiment parameters with the use frequency being greater than 5 are used as standard condiment parameters of the current recipe.

S204, determining a target seasoning parameter of the current menu and a target taste parameter of the current menu according to the standard seasoning parameters; the target condiment parameters include target condiment weight, target condiment addition order, and target condiment addition time.

The target seasoning weight refers to the weight of the seasoning added to the current food materials in the current menu; the target seasoning adding sequence refers to the sequence of the seasoning added to the current food materials in the current menu; the target seasoning addition time refers to the time of adding seasoning to the current food material in the current recipe.

Specifically, in the process of determining the target seasoning parameters of the current recipe and the target taste parameters of the current recipe, the target seasoning weight of each current food material in the current recipe can be determined firstly based on the weight of the current food material and the weight of the seasoning in the standard seasoning parameters, then the priority of selecting the seasoning in the historical recipe data is obtained, the seasoning adding sequence of the current recipe is determined based on the target seasoning weight and the priority of selecting the seasoning, the target seasoning adding time of the current recipe is obtained based on the historical recipe data and the target cooking parameters, and then the target taste parameters of the current recipe are determined according to the target seasoning weight and the weight of the current food material.

It should be noted that, the weight of the current food material and the weight of the food material in the history menu data may be obtained, and then the weight of the seasoning may be determined from the standard seasoning parameters, and for each current food material, according to the weight of the current food material: target condiment weight = food material weight: the weight of the seasoning, the weight of the target seasoning is calculated by the weight of the current food material, the weight of the food material and the weight of the seasoning.

Each current food material has a priority order, and the condiments can be selected according to the weight and the priority of the food material, namely the adding order of the condiments of the current menu is to add the condiments corresponding to the food materials with higher priority first, then add the condiments corresponding to the food materials with lower priority, and finally add the condiments corresponding to the food materials with minimum priority. For example, the priority for the current food ingredient selection may be: the method comprises the steps of selecting seasonings according to the sequence, namely meat, egg and milk, aquatic products, fruits and vegetables and grains, so as to determine the adding sequence of the seasonings.

Illustratively, for example, the current food material includes an a food material and a B food material, and the seasoning used by the a food material at high frequency is determined from the historical menu data: 1, 2 and 3, and B is used for high frequency use: the condiments 1 and 4 can be converted in equal ratio according to the weight of the condiments and the weight of the food materials, for example, if the weight ratio of the condiments 1 to the weight of the food materials in the historical menu data is 100:1, the weight of the condiments 1 is calculated according to the weight of the current food materials input by a user, so that the target weight of the condiments 1 to be added to the food materials A in the current menu is obtained, and similarly, the same mode as the determination of the weight of the condiments in the food materials A can be adopted to the food materials B, so that the target weight of the condiments to be added to the food materials B in the current menu is obtained.

After determining the order of addition of condiments for the current recipe, a target time of addition of condiments for the current recipe may be obtained based on the historical recipe data and the target cooking parameters, the target time of addition of condiments being used to characterize the time of addition of different condiments to the current food material during cooking. And scoring calculation is carried out on the salty degree, the sweetness degree, the hot degree, the bitter degree and the acidity degree of the condiments in the current menu according to the weight of the target condiments and the weight of the current food materials, so that the target taste parameters of the current menu are determined. For example, the ratio of the weight of the target seasoning to the weight of the current food material can be determined, and then the target taste parameter of the current recipe can be obtained by calculating according to the ratio and the preset seasoning weight.

According to the method and the device, related parameters can be intelligently adjusted based on the weight of the current food materials and the weight of the condiments in the standard condiments, so that the target condiments of each current food material in the current menu, the condiment adding sequence of the current menu and the target condiment adding time are determined more accurately, the current menu is closer to the actual requirements of a user, and the target taste parameters of the current menu can be determined accurately according to the target condiment weights and the weight of the current food materials, so that the current menu can be adjusted according to the tastes of the user.

In another embodiment of the present application, there is also provided a specific implementation of obtaining a target seasoning addition time of a current recipe based on historical recipe data and target cooking parameters, the method comprising:

determining a cooking curve of each current food material in the cooking process based on the historical menu data; the integral area of the cooking curve is used for representing the heat absorbed by the current food material in the cooking process; taking the current food material with the largest integral area in each cooking curve as a main food material, so as to preferentially add the main food material in the current menu; when the remaining integral area of the cooking curve of the main food material is the same as the integral area of the cooking curve of the other food materials, the other food materials are added.

In the above-mentioned history menu data, each history menu may include a cooking parameter and a cooking curve, where the cooking curve is a curve drawn in advance according to a change of the cooking parameter with time, and the cooking parameter may be, for example, a cooking temperature or a cooking power, and the integration area S, S may be calculated by integration ₀ Total food weight, S will be summarized ₀ Calculating the average value to obtain an average value area S ₁ The above S can be expressed by the following formula:

wherein x is time, y is temperature/power, z is integral area, S ₁ Is the mean area.

Specifically, the integral area refers to S of summary of each historical menu data ₀ Calculating the average value to obtain an average value area S ₁ In the process of acquiring the history menu data, the cooking curve of each current food material in the cooking process can be determined from the history menu data, and then the cooking curve is determined from each cooking curveThe current food material with the largest integral area is determined, the current food material with the largest integral area in each cooking curve is used as a main food material, the main food material is preferentially added in the current menu, and then other food materials are added when the residual integral area of the cooking curve of the main food material after the main food material starts to cook is the integral area of the cooking curve of the other food materials.

According to the embodiment, the adding time of each food material is determined according to the integral area, so that the quality of dishes corresponding to the menu can be accurately mastered, and the dishes cooked by a user are better.

In another embodiment of the present application, there is further provided a specific implementation manner of obtaining taste information of the user, where the method includes:

and responding to the input operation of the user, and acquiring the taste requirement information of the user. Or,

acquiring menu browsing data of a user in preset time, acquiring each browsing time of different taste menus and the browsing quantity corresponding to each browsing time based on the menu browsing data, and acquiring taste requirement information of the user according to the browsing quantity, the browsing time and preset scores corresponding to each browsing time.

As one implementation, a plurality of button controls may be included on a display interface of a computer device, such as a "next page" control, a "previous page" control, an "enter demand" control, a "return" control, and so forth, when a user is browsing a recipe web page. The user may click on the "input demand" control to input taste demand information on the interface, such that the computer device receives and responds to the user's input operation to obtain the user's taste demand information.

As another implementation manner, menu browsing data can be collected, and according to the menu browsing data, each browsing time and browsing quantity of a user on different taste menus can be obtained, wherein the browsing time can comprise, for example, 10s or less, 10 s-30 s or more, the preset score corresponding to each browsing time is respectively 10s or less a score, 10 s-30 s b score, 30s or more c score, and an automatic cooking instruction d score is issued. After each browsing time and browsing quantity are obtained, weighting and summing are carried out based on the preset score and browsing quantity corresponding to each browsing time, so that taste requirement information of a user is obtained, and the taste requirement information can be expressed by the following formula:

The taste value corresponding to the taste requirement information of the user=less than 10s browsing quantity x a score+10-30 s browsing quantity x b score+more than 30s browsing quantity x c score+issuing automatic cooking instruction quantity x d score;

for example, the taste value corresponding to the taste requirement information of the user=0 minutes for less than 10 s+10 to 30s browsing number, 10 minutes for more than 30s browsing number, 20 minutes for more than 30 s+50 minutes for issuing the automatic cooking instruction number.

It should be noted that, the above-mentioned user browsing for 10-30 s illustrates that the user browses the menu content, is interested in the menu but may encounter some reason or difficulty to do so; the user browses for more than 30 seconds to explain that the user carefully looks at the menu content and is interested in the menu; the user issues an automatic cooking instruction to indicate that the user has done the dish, which is of great interest to the menu.

For example, please refer to the following table, all the historical recipe data may be checked for taste tags, respectively including: (heavy oil, medium oil, small oil) (heavy salt, medium salt, small salt) (heavy acid, medium acid, slight acid) (heavy peppery, medium peppery, slight peppery) (extra sweet, medium sweet, slight sweet), which is a statistical map of the number of recipes that users commonly browse for one month, for example, the total number of browsing recipes is 111.

As can be seen from the above table, the favorite taste of the user is heavy and spicy, so that the heavy and spicy menu is recommended preferentially, and if no specific menu exists, other menus can be adjusted according to the favorite taste requirement information of the user.

It will be appreciated that after determining the taste requirement information of the user, the to-be-adjusted seasoning and the weight to be adjusted corresponding to the to-be-adjusted seasoning may be determined according to the target taste parameter, for example, the adjusted seasoning weight may be determined by the following formula:

adjusted seasoning weight = Φ × adjusted previous seasoning weight (weight of current food material/weight of raw food material) (0.5 +.ltoreq.Φ +.1), wherein the previous seasoning weight was the seasoning weight in the standard seasoning parameters and the weight of raw food material was the weight of food material in the current recipe data.

According to the method and the device, the taste requirement information of the user is determined according to the browsing data, so that the user can be automatically helped to adjust the seasoning ratio when recommending the menu, and the target menu meeting the taste requirement of the user is obtained.

In another embodiment of the present application, there is further provided a specific implementation manner of generating a recipe according to recipe demand information and taste demand information, and fig. 4 is a schematic flow chart of a method for generating a recipe, as shown in fig. 4, and the method includes:

S301, determining a recombined menu corresponding to the current food materials from a menu database based on menu demand information.

S302, adjusting the condiment parameters and the cooking parameters in the recombined menu based on the menu demand information to obtain the intermediate menu.

S303, determining a nutrition recipe meeting the nutrition requirements corresponding to the nutrition requirement information from the middle recipe.

S304, adjusting the nutrition menu according to the taste requirement information to obtain a second target menu.

It should be noted that the reorganized menu is used for representing the historical menu obtained after the menu database is adjusted according to the current food materials. The middle menu is obtained by adjusting the condiment parameters and the cooking parameters in the recombined menu. The nutrient menu is a menu which adjusts the middle menu and meets the nutrient requirements corresponding to the nutrient requirement information. The nutritional requirement information is used to characterize the nutritional composition information of the recipe desired by the user, and may include vitamins, proteins, etc., for example.

Specifically, after the menu demand information is obtained, a recombined menu corresponding to the current food materials can be determined from a menu database based on the menu demand information, for example, when the current food materials are a plurality of, an associated menu corresponding to the current food materials is determined for each current food material, then a menu with the same cooking mode in the associated menu is determined, so that the recombined menu is obtained, and then condiment parameters and cooking parameters in the recombined menu are adjusted based on the menu demand information, so that an intermediate menu is obtained. And acquiring nutrition demand information, determining a nutrition recipe meeting nutrition requirements corresponding to the nutrition demand information from the intermediate recipe, and adjusting the nutrition recipe according to the taste demand information to obtain a second target recipe.

In the process of determining the recombined menu, whether the current food material is the existing food material in the menu database can be judged based on the information of the current food material; if yes, determining the group where the current food material is located and other food materials associated with the current food material in the group based on the current food material identification; acquiring a menu of other food materials in a menu database, and updating the other food materials in the menu to current food materials to obtain a recombined menu corresponding to the current food materials.

Referring to fig. 5, a user may input recipe demand information and nutrition demand information on an interface, where the recipe demand information includes a current food material name and a weight of a current food material, and determine whether the input food material is an existing food material in a database, if yes, find a group corresponding to the food material according to the food material name input by the user, then find a recipe corresponding to other food materials in the group of the food material from the recipe database, and substitute the current food material name input by the user into the recipes of the other food materials in the group to obtain a recombined recipe, where all food materials in the group can be replaced with each other, then replace all original food material names in the recipe with the current food material, and modify a seasoning ratio according to the weight of the food material input by the user, and modify a cooking parameter according to the weight of the input food material, so as to obtain an intermediate recipe. Returning a taste inquiry request to the user so as to inquire whether the user adjusts recipe condiments according to the personal taste records, if so, acquiring historical browsing data of the user on the historical recipes, wherein each recipe corresponds to different tastes, and outputting a result according to the historical browsing data; if not, directly outputting the result, and recommending the menu meeting the nutrition requirement preferentially according to the nutrition requirement information input by the user.

After judging whether the input food is the existing food in the database, if not, searching whether the current food exists in the alias library, if so, searching the corresponding group of the food according to the name of the food input by the user, and then searching the menu of other food in the group of the food from the menu database to replace the other food to obtain the recombined menu.

In addition, in the computer equipment, data embedding can be carried out, food materials which do not generate a menu or combinations with high searching frequency of users are uploaded into a menu database, the menu is built into a menu self-learning system through data accumulation and a model, a menu which does not exist in the menu database is generated, and menu developers regularly select the menu from a menu pool to develop, shoot and enter the menu database.

It can be understood that the food materials can be classified according to the cooking mode, for example, the cooking mode is classified into 8 types of cooking, stewing, soup stewing, stir-frying, cold dishes, baking and roasting; under each type of food material, the division is again made according to the cooking mode, and each food material name can only appear once in one cooking mode.

Referring to the following table, the following table is a part of data of pork food material groups, the cooking mode is a cooking mode of a menu in a database, and the menu can be divided into 8 types of cooking, stewing, soup stewing, stir-frying, cold mixing, baking and roasting; the classification method can be adjusted according to specific conditions; the main food materials are pork, and the main food materials can be continuously classified into small food materials under the corresponding cooking modes, and the principle of food material classification is the similarity of maturity and cooking methods; under each cooking regime, the food material name can only appear 1 time.

Referring to fig. 6, a user may input recipe demand information including a current food material name, for example, including "pig bone" and "corn", and when the current food material is an existing food material in a recipe database, find whether a recipe including "pig bone" and "corn" exists in the recipe database, and if so, acquire a recipe including pig bone and corn and recommend the recipe to the user;

if the menu database does not contain the menus comprising the pig bones and the corn, searching which food materials and the pig bones can be replaced by each other and which food materials and the corn can be replaced by each other, searching the menu with intersection instead of the menu in different cooking modes, and searching the related menu between the cooking modes: the radish pork rib soup (the radish and the pork rib in the food materials can be replaced by corn and pig bone) can be replaced, so that the pork rib appearing in the menu is uniformly modified into the pig bone and the radish is uniformly modified into the corn; therefore, the menu name is changed into 'corn pig bone soup', the menu food material list is changed, the rest is unchanged, and the menu is generated.

The specific process can be that the pig bone and the corn are searched through the background, the group where the pig bone and the corn are located is determined based on the pig bone and the corn, for example, for the pig bone, the group can be determined to be soup-boiling bone, other food materials related to the current food materials, such as the pig bone, the pork rib and the like, are determined, the food materials, such as the pig bone, the pork rib and the like, in the group are found, the menu of the other food materials in the menu database is obtained, namely, the soup-boiling group is prepared, the menu of all the food materials in the group is prepared, and the other food materials in the menu are updated to the current food materials. For corn, the group can be determined to be steamed-rhizome, stewed-rhizome, soup-rhizome, stir-fried-rhizome and fried-rhizome, then corn, white radish, carrot and the like are found in the group, a menu of all food materials in the group is prepared in the soup-rhizome, and the radish pork rib soup with the intersection menu is prepared, then the fixed food materials in the menu are replaced with the current food materials, and the recombined menu corresponding to the current food materials of pig bones and corn is obtained as corn pig bone soup.

After obtaining the recombined menu, the recombined menu may include a plurality of nutritional requirement information which may include, for example, protein and vitamin a according to the nutritional requirement input by the user, and the recombined menu is matched according to the nutritional requirement input by the user, so that the nutritional menu meeting the nutritional requirement is recommended preferentially according to the nutritional requirement input by the user.

Further, after the nutrient menu is obtained, cooking parameters and seasoning proportions can be adjusted according to taste requirement information input by a user.

As an implementation manner, the nutrition menu can be adjusted according to the taste requirement information input by the user, the condiments and the food material maturity in the nutrition menu are modified, and the second target menu meeting the taste requirement and the nutrition requirement of the user is recommended preferentially according to the taste requirement information input by the user. As another implementation manner, recipe browsing data of the user may be obtained, where taste tags (heavy oil, medium oil, and small oil) (heavy salt, medium salt, and small salt) (heavy acid, medium acid, and small acid) (heavy hot, medium hot, and small hot) are respectively corresponding to the recipe browsing data, and then the user browsing time and the number of recipes corresponding to the browsing time are obtained according to the recipe browsing data, so as to obtain taste requirement information of the user.

For example, referring to fig. 7, when taste requirement information input by a user is: when favorite to calculate and soft food, the recipe database can be searched for whether the recipe of the sour food with soft taste exists, and when the recipe of the food with soft taste does not exist, the recipe database can be searched for whether the recipe of the soft taste exists, the recipe using sour seasoning is screened, and the gram weight of the sour seasoning is adjusted and improved to be n times of that of the original seasoning, so that the recommended recipe is output. Meanwhile, whether the menu with acid exists in the menu database can be searched first, the menu using cooking, stewing and stewing Shang Jifa can be screened, and then the cooking time of the menu can be adjusted and prolonged to be m times of the original time, so that the recommended menu can be output. Wherein n >0, m >0.

According to the embodiment, the diversified requirements of a user are met by intelligently adjusting recipe seasoning parameters and cooking parameters, personalized recipes can be provided for the user, recipes which are not in a recipe database can be flexibly generated according to current food materials of the user, for example, two food materials of goose and potato in the current hand of the user want to be cooked, but the recipe database does not have the recipes, the intelligent recipes can be used, the recipe database has duck meat and radish recipes, duck meat and goose meat in a food material recombination library can be mutually exchanged, and the goose meat and radish can be mutually exchanged, so that a goose meat and chicken block cooking recipe can be generated for the user; if the user wants to recommend the high-protein and low-sodium menu, all the menus in the menu database are subjected to nutrition labeling, and the high-protein and low-sodium menu meeting the user requirement can be matched for recommendation to the user; and searching in a menu database when the user wants to eat the food which is sour and soft, and changing the sour menu into soft food by adjusting the cooking time if the user does not search, or adding the menu with soft taste to achieve the taste effect of sour by improving sour seasoning; and the taste preference of the user can be calculated through a model according to the menu browsing data of the user, and the user is automatically helped to adjust the seasoning ratio when recommending the menu, so that the menu meeting the user requirement is obtained.

In another embodiment of the present application, if the current food material is not an existing food material in the recipe database, a specific implementation manner of generating a recipe is further provided, and the method includes:

if the current food material is not the current food material in the menu database, searching whether the current food material exists in the alias database; when the current food material exists, searching the name of the current food material in a menu database; when the search is successful, a recombined recipe corresponding to the current food material is determined from a recipe database based on the name.

Specifically, referring to fig. 8, a user inputs a current food material on an interface, searches a menu database for whether the current food material exists, and when the search is successful, searches a corresponding reorganized menu in the menu database. When the search fails, whether the current food material exists in the alias library can be searched, and when the search is successful, a judging message is sent to a user, so that the user can judge whether the food material in the alias library is the current food material or not, further confirm searching of the name of the current food material in the menu database, and when the success is confirmed, search the corresponding recombined menu in the menu database.

When the current food is not found in the alias database, namely the search fails, prompting the user to input the food name again, searching in the menu database further, if the search succeeds, associating the initially input food with the food in the menu database into the alias database, and when the administrator passes the examination, entering the alias database, or entering different homophones into the error correction database. If the search fails, it may continue searching from the alias library for the presence of the current food material. After the initially input food materials are associated with the food materials in the menu database and incorporated into the alias database, a judgment message can be sent to the user, so that the user judges whether the food materials in the alias database are current food materials or not, further confirms searching for the names of the current food materials in the menu database, and when the success is determined, the corresponding recombined menu is searched in the menu database.

According to the menu generation method, the user can input any food materials in the menu database according to the user input, personalized recommendation is achieved, cooking parameters and seasoning parameters can be adjusted according to nutrition requirements and taste requirements of the user, so that diversity requirements of the user are intelligently met, a menu meeting the user requirements is generated, and the use experience of the user is improved.

It should be noted that although the operations of the method of the present invention are depicted in the drawings in a particular order, this does not require or imply that the operations must be performed in that particular order or that all of the illustrated operations be performed in order to achieve desirable results. Rather, the steps depicted in the flowcharts may change the order of execution. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step to perform, and/or one step decomposed into multiple steps to perform.

On the other hand, fig. 8 is a schematic structural diagram of a menu generating device according to an embodiment of the present application. The apparatus may be an apparatus within a computer device, as shown in fig. 8, the apparatus 600 comprising:

an obtaining module 610, configured to obtain recipe demand information and taste demand information of a user; the menu demand information comprises information of at least one current food material;

A judging module 620, configured to judge whether a recipe associated with each current food material exists in the recipe database at the same time based on the information of the current food material;

a determining module 630, configured to obtain historical recipe data of all current food materials when there is no recipe associated with each current food material information, and determine a target recipe parameter of the current recipe based on the historical recipe data;

the adjusting module 640 is configured to adjust the current recipe according to the target recipe parameter and the taste requirement information of the current recipe, so as to obtain a first target recipe.

Optionally, the determining module 630 is specifically configured to:

acquiring all cooking modes and morphological parameters of food materials of the group to which each current food material belongs from historical menu data of the current food materials;

based on all cooking modes and morphological parameters, determining target menu parameters of the current menu.

Optionally, the determining module 630 is specifically configured to:

determining the same key cooking modes in each current food material based on all cooking modes of the current food material;

Optionally, the determining module 630 is further configured to:

determining the condiment adding sequence of the current menu based on the weight of the target condiments and the priority of condiment selection;

obtaining target seasoning adding time of the current menu based on the historical menu data and the target cooking parameters;

Optionally, the determining module 630 is further configured to:

Optionally, the adjusting module 640 is specifically configured to:

determining a difference value corresponding to a taste parameter corresponding to the taste demand information in the target recipe parameters;

Optionally, the acquiring module 610 is specifically configured to:

acquiring menu browsing data of a user in preset time;

Optionally, the device is specifically configured to:

Optionally, the device is further configured to:

when the search is successful, a recombined recipe corresponding to the current food material is determined from a recipe database based on the name.

For specific limitations of the menu-based generating device, reference may be made to the above limitation of the terminal data recovery method, and no further description is given here. The above-described respective modules in the menu generating apparatus may be implemented in whole or in part by software, hardware, and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In another aspect, a computer device provided in an embodiment of the present application includes a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements a recipe generation method as described above when the program is executed by the processor.

Referring now to fig. 10, fig. 10 is a schematic structural diagram of a computer system of a computer device according to an embodiment of the present application.

As shown in fig. 10, the computer system 300 includes a Central Processing Unit (CPU) 301 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 302 or a program loaded from a storage section 303 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the system 300 are also stored. The CPU 301, ROM 302, and RAM 303 are connected to each other through a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.

The following components are connected to the I/O interface 305: an input section 306 including a keyboard, a mouse, and the like; an output portion 307 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage section 308 including a hard disk or the like; and a communication section 309 including a network interface card such as a LAN card, a modem, or the like. The communication section 309 performs communication processing via a network such as the internet. The drive 310 is also connected to the I/O interface 305 as needed. A removable medium 311 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed on the drive 310 as needed, so that a computer program read therefrom is installed into the storage section 308 as needed.

In particular, according to embodiments of the present application, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a machine-readable medium, the computer program comprising program code for performing the method shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network through the communication portion 303, and/or installed from the removable medium 311. The above-described functions defined in the system of the present application are performed when the computer program is executed by a Central Processing Unit (CPU) 301.

It should be noted that the computer readable medium shown in the present application may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present application, however, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units or modules described in the embodiments of the present application may be implemented by software, or may be implemented by hardware. The described units or modules may also be provided in a processor, for example, as: a processor, comprising: the device comprises an acquisition module, a judgment module, a determination module and an adjustment module. Wherein the names of the units or modules do not in some cases constitute a limitation of the units or modules themselves, for example, the acquisition module may also be described as "for acquiring recipe demand information and taste demand information of the user; the recipe demand information includes information of at least one current food material.

As another aspect, the present application also provides a computer-readable storage medium that may be included in the electronic device described in the above embodiments; or may be present alone without being incorporated into the electronic device. The computer-readable storage medium stores one or more programs that, when used by one or more processors, perform the recipe generation method described in the present application:

and adjusting the current menu according to the target menu parameters of the current menu and the taste requirement information to obtain a first target menu.

In summary, according to the method, the device, the equipment and the storage medium for generating the menu provided by the embodiment of the application, by acquiring the menu demand information and the taste demand information of the user, the menu demand information comprises at least one piece of information of the current food materials, judging whether a menu associated with each current food material exists in the menu database at the same time based on the current food material information, acquiring the history menu data of all the current food materials when the menu associated with each piece of information of the current food material does not exist at the same time, determining the target menu parameters of the current menu based on the history menu data, and adjusting the current menu according to the target menu parameters and the taste demand information of the current menu to obtain the first target menu. Compared with the prior art, the technical scheme fully considers the current food materials of the user, when the recipes associated with each piece of current food material information are not available at the same time, the target recipe parameters of the current recipes can be accurately and comprehensively determined according to the acquired historical recipe data of the current food materials under the condition that the types of the instant food materials are limited and the associated recipes cannot be acquired, and then the target recipes meeting the cooking tastes of the user can be flexibly adjusted according to the target recipe parameters and the taste requirement information of the current recipes, so that the personalized recipe recommendation of the user is realized, and the user experience is greatly improved.

The foregoing description is only of the preferred embodiments of the present application and is presented as a description of the principles of the technology being utilized. It will be appreciated by persons skilled in the art that the scope of the invention referred to in this application is not limited to the specific combinations of features described above, but it is intended to cover other embodiments in which any combination of features described above or equivalents thereof is possible without departing from the spirit of the invention. Such as the above-described features and technical features having similar functions (but not limited to) disclosed in the present application are replaced with each other.

Claims

1. A recipe generation method, the method comprising:

2. The method of claim 1, wherein determining target recipe parameters for a current recipe based on the historical recipe data comprises:

3. The method of claim 2, wherein the target recipe parameters include a target cooking parameter, a target seasoning parameter, and a target taste parameter; determining a target recipe parameter of the current recipe based on the all cooking modes and the morphological parameters, including:

determining the same key cooking modes in each current food material based on all the cooking modes;

determining each morphological parameter corresponding to the key cooking mode in each current food material, and generating target cooking parameters according to the morphological parameters and the key cooking modes;

determining a target seasoning parameter of the current recipe and a target taste parameter of the current recipe according to the standard seasoning parameter; the target condiment parameters include a target condiment weight, a target condiment addition order, and a target condiment addition time.

4. A method according to claim 3, wherein the information of the at least one current food item comprises a weight of the at least one current food item, and determining the target condiment parameter of the current recipe and the target taste parameter of the current recipe based on the standard condiment parameter comprises:

5. The method of claim 4, wherein deriving a target seasoning addition time for the current recipe based on the historical recipe data and the target cooking parameter comprises:

determining a cooking curve of each current food material in a cooking process from the historical menu data; the integral area of the cooking curve is used for representing the heat absorbed by the current food material in the cooking process;

and adding the other food materials when the residual integral area of the cooking curve of the main food material is the same as the integral area of the cooking curve of the other food materials.

6. The method of claim 1, wherein adjusting the current recipe based on the target recipe parameters of the current recipe and the taste requirement information to obtain a first target recipe comprises:

7. The method of claim 1, wherein obtaining taste requirement information of the user comprises:

acquiring menu browsing data of the user in preset time;

based on the menu browsing data, acquiring each browsing time of the user on different taste menus and the browsing quantity corresponding to each browsing time;

8. The method according to any one of claims 1-7, wherein the recipe demand information further comprises nutrient demand information of the user, and after obtaining the recipe demand information and taste demand information of the user, the method further comprises:

determining a recombined recipe corresponding to the current food material from the recipe database based on the recipe demand information;

determining a nutrition recipe meeting the nutrition requirements corresponding to the nutrition requirement information from the middle recipe;

9. The method of claim 8, wherein determining a restructured recipe corresponding to the current food material from the recipe database based on the recipe demand information comprises:

if yes, determining a group in which the current food material is located and other food materials associated with the current food material in the group;

acquiring a menu of the other food materials in the menu database, and updating the other food materials in the menu to the current food materials to obtain a recombined menu corresponding to the current food materials.

10. The method of claim 9, wherein after determining whether the current food material is an existing food material in the recipe database, the method further comprises:

If the current food material is not the existing food material in the menu database, searching whether the current food material exists in an alias library;

when the current food material exists, searching the name of the current food material in the menu database;

and when the searching is successful, determining a recombined menu corresponding to the current food material from the menu database based on the name.

11. A menu generating apparatus, comprising:

12. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the recipe generation method of any one of claims 1-10 when the program is executed by the processor.

13. A computer readable storage medium having stored thereon a computer program for implementing the recipe generation method of any of claims 1-10 when executed by a processor.