Menu recommendation method and device based on health management

Abstract

The invention relates to the technical field of data processing, and discloses a menu recommendation method and device based on health management, and the method comprises the steps: determining food material data of a to-be-cooked target food material, the food material data at least comprising a food material type; obtaining multi-dimensional health data of a user to which the target food material faces; determining a target cooking menu corresponding to the food material type according to the food material data and the multi-dimensional health data; and recommending the target cooking menu to the user through target equipment, wherein the target equipment comprises intelligent cooking equipment or mobile equipment. Therefore, the target cooking menu corresponding to the food material of the corresponding type can be quickly and accurately determined based on the food material data of the food material to be cooked and the multi-dimensional health data of the user, and then the menu is recommended to the user, so that the menu matched with the body health of the user can be selected subsequently, the menu recommendation efficiency can be improved, and the user experience is improved. Therefore, the finally recommended menu can meet the body health requirement of the user.

Description

Technical Field

[0001] The present invention relates to the technical field of food data management, and in particular to a recipe recommendation method and device based on health management. Background Art

[0002] With the rapid development of science and technology, people are increasingly demanding smart cooking devices, such as those that can recommend recipes. Existing smart cooking devices typically simply select all recipes corresponding to the ingredient type data uploaded by the user and recommend all of them to the user.

[0003] However, in practice, it has been found that some recipes recommended by cooking devices may not be conducive to the user's current health, requiring the user to manually perform a secondary screening, which is inefficient and not intelligent enough. Therefore, it is particularly important to propose a new recipe recommendation solution. Summary of the Invention

[0004] The present invention provides a recipe recommendation method and device based on health management, which can improve the efficiency of recipe recommendation so that the final recommended recipe can meet the user's physical health needs.

[0005] In order to solve the above technical problems, the first aspect of the present invention discloses a recipe recommendation method based on health management, the method comprising:

[0006] Determining ingredient data of a target ingredient to be cooked, wherein the ingredient data at least includes an ingredient type;

[0007] Acquiring multi-dimensional health data of users targeted by the target food;

[0008] Based on the ingredient data and the multi-dimensional health data, a target cooking recipe corresponding to the ingredient type is determined; and the target cooking recipe is recommended to the user via a target device, where the target device includes a smart cooking device and / or a mobile device.

[0009] As an optional embodiment, in the first aspect of the present invention, determining the target cooking recipe corresponding to the ingredient type based on the ingredient data and the multi-dimensional health data includes:

[0010] Determining nutritional information corresponding to the food type based on the food data;

[0011] Analyzing the nutritional needs information of the user based on the multi-dimensional health data, wherein the multi-dimensional health data includes dimensional data of multiple dimensions related to the user's physical health, each of the dimensional data including one of basic data of the user, health status of the user, and eating habits of the user;

[0012] determining the user's cooking requirement information based on the nutritional component information and the nutritional requirement information;

[0013] According to the cooking requirement information, all initial cooking recipes corresponding to the predetermined ingredient type are screened to obtain a target cooking recipe corresponding to the ingredient type.

[0014] As an optional embodiment, in the first aspect of the present invention, determining the user's cooking requirement information based on the nutritional component information and the nutritional requirement information includes:

[0015] Determining at least one initial cooking method that matches the food type; and analyzing the nutrient loss that each of the initial cooking methods may cause to the nutrient component information;

[0016] selecting at least one target cooking method that meets a preset nutritional matching condition from all the initial cooking methods according to the nutritional loss corresponding to each of the initial cooking methods, the nutritional component information, and the nutritional requirement information;

[0017] For each target cooking method, analyzing the user's sub-cooking requirement information for the target cooking method based on the ingredient data of the target ingredient and a preset parameter ratio corresponding to the target cooking method, where the parameter ratio includes a side dish ratio and / or a cooking auxiliary ingredient ratio;

[0018] The cooking requirement information includes any one of the target cooking methods and sub-cooking requirement information corresponding to the target cooking method.

[0019] As an optional embodiment, in the first aspect of the present invention, selecting at least one target cooking method that meets a preset nutritional matching condition from all the initial cooking methods based on the nutrient loss corresponding to each initial cooking method, the nutrient component information, and the nutritional requirement information includes:

[0020] Calculating target nutrient information for the food type under each initial cooking method according to the nutrient loss corresponding to each initial cooking method and the nutrient information;

[0021] Calculating a matching degree between the target nutrient component information and the nutrient requirement information according to the target nutrient component information corresponding to each of the initial cooking methods, and obtaining a nutrient matching degree corresponding to each of the initial cooking methods;

[0022] According to the nutritional matching degrees corresponding to all the initial cooking methods, at least one target cooking method whose corresponding nutritional matching degree meets a preset nutritional matching condition is selected from all the initial cooking methods.

[0023] As an optional embodiment, in the first aspect of the present invention, the multi-dimensional health data further includes a user's nutritional goals;

[0024] The step of recommending the target cooking recipe to the user through the target device includes:

[0025] When the number of the target cooking recipes is greater than one, all the target cooking recipes are sorted according to the user's nutritional goal based on a preset sorting algorithm to obtain a recipe recommendation sequence, wherein the recipe recommendation sequence includes at least all the target cooking recipes and a sequence number corresponding to each target cooking recipe;

[0026] Acquire the historical cooking recipe record selected by the user, and select, based on the ingredient type, a historical cooking recipe corresponding to the ingredient type from among all historical cooking recipes in multiple historical time periods included in the historical cooking recipe record;

[0027] marking identical recipes in the recipe recommendation sequence according to the historical cooking recipes, so that the recipe recommendation sequence also includes marking information of the historical cooking recipe selected by the user;

[0028] According to the recipe recommendation sequence, all the target cooking recipes are recommended to the user in sequence via the target device.

[0029] As an optional embodiment, in the first aspect of the present invention, the preset sorting algorithm is used to sort all the target cooking recipes according to the user's nutritional goals to obtain a recipe recommendation sequence, including:

[0030] analyzing, based on the user nutritional goals included in the multi-dimensional health data, a target relationship between each target cooking recipe and the user nutritional goals, wherein the target relationship includes a positive correlation or a negative correlation;

[0031] predicting, based on the target relationship, the time required for the user to reach the user's nutritional goal under the influence of each target cooking recipe, and obtaining an expected nutritional control time corresponding to each target cooking recipe;

[0032] Based on a preset sorting algorithm, a sorting operation is performed on all the target cooking recipes according to the expected nutritional control times corresponding to all the target cooking recipes to obtain a recipe recommendation sequence; wherein, the recipe recommendation sequence is obtained by sorting all the target cooking recipes in ascending order of the expected nutritional control times.

[0033] As an optional embodiment, in the first aspect of the present invention, the method further comprises:

[0034] In response to a recipe selection operation for the intelligent cooking device, determining a target cooking recipe corresponding to the recipe selection operation as a recipe to be cooked by the intelligent cooking device;

[0035] determining cooking control parameters corresponding to the intelligent cooking device according to the cooking details included in the recipe to be cooked;

[0036] Cooking the target ingredients according to the cooking control parameters corresponding to the intelligent cooking device, and monitoring the actual nutritional information of the cooked dish corresponding to the target ingredients during the cooking process;

[0037] The cooking control parameters are adjusted according to the actual nutritional information so that the actual nutritional information meets the nutritional requirements corresponding to the multi-dimensional health data.

[0038] A second aspect of the present invention discloses a recipe recommendation device based on health management, the device comprising:

[0039] a determination module, configured to determine ingredient data of a target ingredient to be cooked, wherein the ingredient data at least includes an ingredient type;

[0040] An acquisition module, configured to acquire multi-dimensional health data of the user for whom the target food is intended;

[0041] The determination module is further configured to determine a target cooking recipe corresponding to the ingredient type based on the ingredient data and the multi-dimensional health data;

[0042] The recommendation module is configured to recommend the target cooking recipe to the user via a target device, where the target device includes a smart cooking device and / or a mobile device.

[0043] As an optional embodiment, in the second aspect of the present invention, the determination module determines the target cooking recipe corresponding to the ingredient type based on the ingredient data and the multi-dimensional health data, specifically including:

[0044] Determining nutritional information corresponding to the food type based on the food data;

[0045] Analyzing the nutritional needs information of the user based on the multi-dimensional health data, wherein the multi-dimensional health data includes dimensional data of multiple dimensions related to the user's physical health, each of the dimensional data including one of basic data of the user, health status of the user, and eating habits of the user;

[0046] determining the user's cooking requirement information based on the nutritional component information and the nutritional requirement information;

[0047] According to the cooking requirement information, all initial cooking recipes corresponding to the predetermined ingredient type are screened to obtain a target cooking recipe corresponding to the ingredient type.

[0048] As an optional embodiment, in the second aspect of the present invention, the determination module determines the user's cooking requirement information according to the nutritional component information and the nutritional requirement information in a manner that specifically includes:

[0049] Determining at least one initial cooking method that matches the food type; and analyzing the nutrient loss that each of the initial cooking methods may cause to the nutrient component information;

[0050] selecting at least one target cooking method that meets a preset nutritional matching condition from all the initial cooking methods according to the nutritional loss corresponding to each of the initial cooking methods, the nutritional component information, and the nutritional requirement information;

[0051] For each target cooking method, analyzing the user's sub-cooking requirement information for the target cooking method based on the ingredient data of the target ingredient and a preset parameter ratio corresponding to the target cooking method, where the parameter ratio includes a side dish ratio and / or a cooking auxiliary ingredient ratio;

[0052] The cooking requirement information includes any one of the target cooking methods and sub-cooking requirement information corresponding to the target cooking method.

[0053] As an optional embodiment, in the second aspect of the present invention, the method in which the determination module selects at least one target cooking method that meets a preset nutritional matching condition from all the initial cooking methods based on the nutritional loss corresponding to each initial cooking method, the nutritional component information, and the nutritional requirement information specifically includes:

[0054] Calculating target nutrient information for the food type under each initial cooking method according to the nutrient loss corresponding to each initial cooking method and the nutrient information;

[0055] Calculating a matching degree between the target nutrient component information and the nutrient requirement information according to the target nutrient component information corresponding to each of the initial cooking methods, and obtaining a nutrient matching degree corresponding to each of the initial cooking methods;

[0056] According to the nutritional matching degrees corresponding to all the initial cooking methods, at least one target cooking method whose corresponding nutritional matching degree meets a preset nutritional matching condition is selected from all the initial cooking methods.

[0057] As an optional embodiment, in the second aspect of the present invention, the multi-dimensional health data further includes a user's nutritional goals;

[0058] The method in which the recommendation module recommends the target cooking recipe to the user through the target device specifically includes:

[0059] When the number of the target cooking recipes is greater than one, all the target cooking recipes are sorted according to the user's nutritional goal based on a preset sorting algorithm to obtain a recipe recommendation sequence, wherein the recipe recommendation sequence includes at least all the target cooking recipes and a sequence number corresponding to each target cooking recipe;

[0060] Acquire the historical cooking recipe record selected by the user, and select, based on the ingredient type, a historical cooking recipe corresponding to the ingredient type from among all historical cooking recipes in multiple historical time periods included in the historical cooking recipe record;

[0061] marking identical recipes in the recipe recommendation sequence according to the historical cooking recipes, so that the recipe recommendation sequence also includes marking information of the historical cooking recipe selected by the user;

[0062] According to the recipe recommendation sequence, all the target cooking recipes are recommended to the user in sequence via the target device.

[0063] As an optional embodiment, in the second aspect of the present invention, the recommendation module sorts all the target cooking recipes according to the user's nutritional goals based on a preset sorting algorithm, and the method of obtaining the recipe recommendation sequence specifically includes:

[0064] analyzing, based on the user nutritional goals included in the multi-dimensional health data, a target relationship between each target cooking recipe and the user nutritional goals, wherein the target relationship includes a positive correlation or a negative correlation;

[0065] predicting, based on the target relationship, the time required for the user to reach the user's nutritional goal under the influence of each target cooking recipe, and obtaining an expected nutritional control time corresponding to each target cooking recipe;

[0066] Based on a preset sorting algorithm, a sorting operation is performed on all the target cooking recipes according to the expected nutritional control times corresponding to all the target cooking recipes to obtain a recipe recommendation sequence; wherein, the recipe recommendation sequence is obtained by sorting all the target cooking recipes in ascending order of the expected nutritional control times.

[0067] As an optional embodiment, in the second aspect of the present invention, the determining module is further configured to, in response to a recipe selection operation on the intelligent cooking device, determine a target cooking recipe corresponding to the recipe selection operation as a recipe to be cooked by the intelligent cooking device; the determining module is further configured to determine cooking control parameters corresponding to the intelligent cooking device based on cooking details included in the recipe to be cooked;

[0068] And, the device further comprises:

[0069] a cooking module, configured to cook the target ingredients according to cooking control parameters corresponding to the intelligent cooking device;

[0070] A monitoring module, used to monitor the actual nutritional information of the cooked dish corresponding to the target ingredient during the cooking process;

[0071] An adjustment module is used to adjust the cooking control parameters according to the actual nutritional information so that the actual nutritional information meets the nutritional requirements corresponding to the multi-dimensional health data.

[0072] A third aspect of the present invention discloses another recipe recommendation device based on health management, the device comprising:

[0073] a memory storing executable program code;

[0074] a processor coupled to the memory;

[0075] The processor calls the executable program code stored in the memory to execute the recipe recommendation method based on health management disclosed in the first aspect of the present invention.

[0076] A fourth aspect of the present invention discloses a computer storage medium storing computer instructions. When the computer instructions are called, they are used to execute the recipe recommendation method based on health management disclosed in the first aspect of the present invention.

[0077] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0078] In an embodiment of the present invention, the ingredient data of the target ingredient to be cooked is determined, the ingredient data at least including the ingredient type; the multi-dimensional health data of the user for whom the target ingredient is intended is obtained; based on the ingredient data and the multi-dimensional health data, a target cooking recipe corresponding to the ingredient type is determined; and the target cooking recipe is recommended to the user through a target device, which includes a smart cooking device or a mobile device. It can be seen that the implementation of the present invention can determine the target cooking recipe corresponding to the ingredient type based on the ingredient data and the multi-dimensional health data, and then recommend the target cooking recipe to the user through the target device. It can quickly and accurately determine the target cooking recipe corresponding to the corresponding type of ingredient based on the ingredient data of the ingredient to be cooked and the multi-dimensional health data of the user, and then recommend the recipe to the user, so as to facilitate the subsequent selection of a recipe that matches the user's physical health, and can improve the efficiency of recipe recommendation so that the final recommended recipe can meet the user's physical health needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0080] Figure 1 This is a flow chart of a recipe recommendation method based on health management disclosed in an embodiment of the present invention;

[0081] Figure 2 This is a flow chart of another recipe recommendation method based on health management disclosed in an embodiment of the present invention;

[0082] Figure 3 This is a structural diagram of a recipe recommendation device based on health management disclosed in an embodiment of the present invention;

[0083] Figure 4 2 is a schematic structural diagram of another health management-based recipe recommendation device disclosed in an embodiment of the present invention;

[0084] Figure 5 This is a structural diagram of another recipe recommendation device based on health management disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0085] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0086] The terms "first," "second," and so on, in the description and claims of the present invention and the accompanying drawings are used to distinguish between different items, not to describe a specific order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or end comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed therein, or may optionally include other steps or elements inherent to such process, method, product, or end.

[0087] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0088] The present invention discloses a recipe recommendation method and device based on health management. The method can determine a target cooking recipe corresponding to an ingredient type based on ingredient data and multi-dimensional health data, and then recommend the target cooking recipe to the user via a target device. Based on the ingredient data of the ingredients to be cooked and the user's multi-dimensional health data, the method can quickly and accurately determine the target cooking recipe corresponding to the corresponding type of ingredient, and then recommend the recipe to the user, facilitating the subsequent selection of a recipe that matches the user's health. The method can improve the efficiency of recipe recommendation so that the ultimately recommended recipe can meet the user's health needs. Detailed descriptions are given below.

[0089] Example 1

[0090] See also Figure 1 , Figure 1 This is a flow chart of a recipe recommendation method based on health management disclosed in an embodiment of the present invention. Figure 1 The described recipe recommendation method based on health management can be applied to a recipe recommendation device based on health management, wherein the device may include a recommendation device or a recommendation server, wherein the recommendation server may include a cloud server or a local server, which is not limited in the embodiment of the present invention. Figure 1 As shown, the recipe recommendation method based on health management may include the following operations:

[0091] 101. Determine ingredient data of target ingredients to be cooked.

[0092] In the embodiment of the present invention, the ingredient data may optionally include at least the ingredient type (e.g., fruit, vegetable, meat, seafood, grain, etc.). Alternatively, the ingredient data may include the ingredient type and further include one or more combinations of ingredient weight, ingredient quantity, ingredient freshness (e.g., ingredient shelf life, ingredient freezing time, etc.), ingredient origin, and ingredient allergen information, which are not limited in the embodiment of the present invention.

[0093] In an embodiment of the present invention, specifically, a user inputs ingredient identification information (such as ingredient name, ingredient type, etc.) of a target ingredient to be cooked in a mobile device, and the mobile device analyzes the ingredient identification information to obtain ingredient data of the target ingredient; or, in response to an ingredient scanning operation for a smart cooking device, the smart cooking device scans the target ingredient to be cooked placed by the user to obtain the ingredient type of the target ingredient, and obtains the ingredient data of the target ingredient through interactive operations regarding the ingredient type between the smart cooking device and the mobile device.

[0094] 102. Obtain multi-dimensional health data of users targeted by the target ingredients.

[0095] In an embodiment of the present invention, the multi-dimensional health data may optionally include dimensional data on multiple dimensions of the user's physical health. Each dimensional data may include one of basic user data, user health status, and user eating habits, and may also include user nutritional goals, which is not limited in the embodiment of the present invention.

[0096] In the embodiment of the present invention, specifically, in response to a user data upload operation on a mobile device, health-related data uploaded by the user is received through the mobile device, and the health-related data is integrated to obtain multi-dimensional health data of the user.

[0097] In the embodiment of the present invention, there is no order between step 101 and step 102, that is, step 102 can occur before step 101, or after step 101, or simultaneously with step 101, which is not limited in the embodiment of the present invention.

[0098] 103. Based on the food data and multi-dimensional health data, determine the target cooking recipe corresponding to the food type.

[0099] In an embodiment of the present invention, optionally, based on the ingredient data and multi-dimensional health data, a matching target cooking recipe is screened from multiple initial cooking recipes contained in a backend database of the smart cooking device / mobile device to serve as the target cooking recipe corresponding to the ingredient type. Alternatively, based on the ingredient data, multi-dimensional health data, and pre-set basic cooking parameters of the smart cooking device, target cooking parameters based on preset health standards are generated, and based on the target cooking parameters, recipes capable of being cooked by the smart cooking device are generated as the target cooking recipe corresponding to the ingredient type. The basic cooking parameters include one or more combinations of cooking-related numerical ranges, such as at least one cooking method, a cooking time range within the corresponding cooking method, a cooking temperature range within the corresponding cooking method, and a cooking flame area range within the corresponding cooking method, which are not limited in the embodiment of the present invention.

[0100] 104. Recommend the target cooking recipe to the user via the target device.

[0101] In the embodiment of the present invention, optionally, the target device includes a smart cooking device and / or a mobile device (such as a mobile phone). Specifically, in response to a recipe recommendation operation for a target ingredient triggered by a user detected on the smart cooking device, the target cooking recipe is displayed on a display device corresponding to the smart cooking device, so that the target cooking recipe is recommended to the user through the smart cooking device; or, in response to a recipe recommendation operation for a target ingredient triggered by a user detected on a mobile device, the target cooking recipe is displayed on a recipe recommendation page of the mobile device, so that the target cooking recipe is recommended to the user through the mobile device; or, in response to a recipe recommendation operation for a target ingredient triggered by a user detected on the smart cooking device, a recipe recommendation instruction is sent to the mobile device through the smart cooking device to trigger the mobile device to display the target cooking recipe on the recipe recommendation page of the mobile device, so that the target cooking recipe is recommended to the user through the linkage control of the smart cooking device and the mobile device. By providing multiple recipe recommendation methods, the flexibility and diversity of recommending the target cooking recipe can be improved, and the situation where the user cannot quickly and accurately receive the corresponding recipe due to external factors such as a device failure or the device being too far away from the user can be reduced, which is conducive to improving the accuracy and timeliness of recipe recommendations.

[0102] It can be seen that implementation Figure 1The described recipe recommendation method based on health management can determine the ingredient data of the target ingredients to be cooked, such as the ingredient type, and obtain the multi-dimensional health data of the user for which the target ingredients are intended. Then, based on the ingredient data and the multi-dimensional health data, the target cooking recipe corresponding to the ingredient type is determined, and then the target cooking recipe is recommended to the user through the target device. It can quickly and accurately determine the target cooking recipe corresponding to the corresponding type of ingredients based on the ingredient data of the ingredients to be cooked and the user's multi-dimensional health data, and then recommend the recipe to the user, so as to facilitate the subsequent selection of recipes that match the user's physical health, and can improve the efficiency of recipe recommendation so that the final recommended recipe can meet the user's physical health needs.

[0103] In an optional embodiment, the step 104 of recommending the target cooking recipe to the user via the target device may include:

[0104] When the number of target cooking recipes is greater than 1, all target cooking recipes are sorted according to the user's nutritional goals based on a preset sorting algorithm to obtain a recipe recommendation sequence. The recipe recommendation sequence includes at least all target cooking recipes and the sequence number corresponding to each target cooking recipe;

[0105] Obtaining the historical cooking recipe record selected by the user, and selecting, based on the ingredient type, a historical cooking recipe corresponding to the ingredient type from the historical cooking recipes of multiple historical time periods contained in all the historical cooking recipe records;

[0106] Marking identical recipes in a recipe recommendation sequence based on historical cooking recipes, so that the recipe recommendation sequence also includes marking information of the historical cooking recipe selected by the user;

[0107] According to the recipe recommendation sequence, all target cooking recipes are recommended to the user in sequence through the target device.

[0108] In an embodiment of the present invention, the user's nutritional goal may optionally be a user-customized nutritional goal, such as weight loss, muscle gain, etc. The preset sorting algorithm may be an algorithm that sorts based on the length of time required for the user to achieve the user-customized nutritional goal through the corresponding target cooking recipe and recipes of the same type, which is not limited in the embodiment of the present invention.

[0109] For example, assuming that there are target cooking recipes A and target cooking recipes B, the time required for the user to reach the user-customized nutritional goal by using target cooking recipe A and other recipes of the same type as target cooking recipe A is a, and the time required for the user to reach the user-customized nutritional goal by using target cooking recipe B and other recipes of the same type as target cooking recipe B is b, and a<b, then the order of target cooking recipe A can be arranged before target cooking recipe B. In this way, by providing target cooking recipes that reach the user's nutritional goal faster, the personalized needs of the recipe recommendation sequence can be intelligently realized based on the user's nutritional goal, which helps the user achieve the nutritional goal and is conducive to improving the user's experience and satisfaction with the recipe recommendation function.

[0110] It can be seen that this optional embodiment can, when the number of target cooking recipes is greater than 1, sort all target cooking recipes based on a preset sorting algorithm and according to the user's nutritional goals to obtain a recipe recommendation sequence. The recipe recommendation sequence at least includes all target cooking recipes and the sequence number corresponding to each target cooking recipe. It can improve the accuracy and efficiency of the recipe recommendation sequence obtained by sorting based on the sorting algorithm and the user's nutritional goals, and obtain the historical cooking recipe record selected by the user, and select the historical cooking recipe corresponding to the ingredient type from the historical cooking recipes of multiple historical time periods contained in all historical cooking recipe records according to the ingredient type, and select the historical cooking recipe corresponding to the ingredient type according to the historical cooking recipe. The same recipes in the recipe recommendation sequence are marked so that the recipe recommendation sequence also includes the marking information of the historical cooking recipes selected by the user. The same recipes in the recipe recommendation sequence can be marked quickly and accurately based on the historical cooking recipes corresponding to the ingredient type, which is beneficial to improving the content richness of the recipe recommendation sequence. Then, according to the recipe recommendation sequence, all target cooking recipes are recommended to the user in sequence through the target device. The target cooking recipes can be accurately recommended to the user based on the recipe recommendation sequence, which is beneficial to improving the accuracy and reliability of recipe recommendation. In addition, the recipe recommendation sequence combined with the historical cooking recipes is beneficial to improving the intelligence of recipe recommendation.

[0111] In this optional embodiment, as an optional implementation, all target cooking recipes are sorted according to the user's nutritional goals based on a preset sorting algorithm to obtain a recipe recommendation sequence, which may include:

[0112] Analyze the target relationship between each target cooking recipe and the user's nutritional goals based on the user's nutritional goals contained in the multi-dimensional health data;

[0113] Based on the target relationship, the time required for the user to reach the user's nutritional goal under the influence of each target cooking recipe is predicted, and the expected nutritional control time corresponding to each target cooking recipe is obtained;

[0114] Based on a preset sorting algorithm, a sorting operation is performed on all target cooking recipes according to the expected nutritional control time corresponding to all target cooking recipes to obtain a recipe recommendation sequence; wherein, the recipe recommendation sequence is obtained by sorting all target cooking recipes in ascending order of the expected nutritional control time.

[0115] In this embodiment of the present invention, the target relationship includes a positive correlation or a negative correlation. For example, if a user's nutritional goal indicates that the user needs to lose weight, and a target cooking recipe is not conducive to weight loss (for example, the recipe involves deep-frying), then the target cooking recipe is determined to be negatively correlated with the user's nutritional goal. If a user's nutritional goal indicates that the user needs to gain muscle, and a target cooking recipe is conducive to muscle gain (for example, the recipe contains a high-protein side dish), then the target cooking recipe is determined to be positively correlated with the user's nutritional goal.

[0116] Specifically, based on the target relationship, the time required for the user to reach the user's nutritional goal under the influence of each target cooking recipe is predicted, and the expected nutritional control time corresponding to each target cooking recipe is obtained. Specifically, it may include: based on the target relationship, predicting the time required for the user to reach the user's nutritional goal by using each target cooking recipe and other recipes of the same type through a preset usage frequency, and obtaining the expected nutritional control time corresponding to each target cooking recipe; or, replacing the historical cooking recipes of the same type contained in the user's historical cooking recipe records with each target cooking recipe as the user's future cooking recipe record, and based on the target relationship, predicting the time required for the user to reach the user's nutritional goal by using the future cooking recipe record, and obtaining the expected nutritional control time corresponding to each target cooking recipe.

[0117] It can be seen that this optional implementation method can analyze the target relationship between each target cooking recipe and the user's nutritional goal, such as a positive correlation or a negative correlation, based on the user's nutritional goal contained in the multi-dimensional health data, and predict the time required for the user to reach the user's nutritional goal under the influence of each target cooking recipe based on the target relationship, and obtain the expected nutritional control time corresponding to each target cooking recipe. This can improve the analysis accuracy of the target relationship between each target cooking recipe and the user's nutritional goal, thereby improving the prediction accuracy and reliability of the expected nutritional control time corresponding to each target cooking recipe based on the target relationship. Then, based on the preset sorting algorithm, all target cooking recipes are sorted according to the expected nutritional control time corresponding to all target cooking recipes to obtain a recipe recommendation sequence. This can achieve accurate sorting of all target cooking recipes based on the preset sorting algorithm and the expected nutritional control time corresponding to all target cooking recipes, which is conducive to improving the accuracy and reliability of the recipe recommendation sequence obtained by sorting, and is conducive to subsequent recipe recommendations.

[0118] Example 2

[0119] See also Figure 2 , Figure 2 This is a flow chart of a recipe recommendation method based on health management disclosed in an embodiment of the present invention. Figure 2 The described recipe recommendation method based on health management can be applied to a recipe recommendation device based on health management, wherein the device may include a recommendation device or a recommendation server, wherein the recommendation server may include a cloud server or a local server, which is not limited in the embodiment of the present invention. Figure 2 As shown, the recipe recommendation method based on health management may include the following operations:

[0120] 201. Determine ingredient data of target ingredients to be cooked.

[0121] 202. Obtain multi-dimensional health data of users targeted by the target ingredients.

[0122] In the embodiment of the present invention, there is no order between step 201 and step 202, that is, step 202 can occur before step 201, or after step 201, or simultaneously with step 201, which is not limited in the embodiment of the present invention.

[0123] 203. Determine the nutritional information corresponding to the food type based on the food data.

[0124] In an embodiment of the present invention, optionally, the nutritional information corresponding to the food type may include one or more combinations of the protein content corresponding to the food type at the target weight, the fat content corresponding to the food type at the target weight, the carbohydrate content corresponding to the food type at the target weight, the vitamin content corresponding to the food type at the target weight, the mineral content corresponding to the food type at the target weight, and the water content corresponding to the food type at the target weight, etc., and the embodiment of the present invention is not limited thereto.

[0125] 204. Analyze users’ nutritional needs information based on multi-dimensional health data.

[0126] In an embodiment of the present invention, optionally, the multi-dimensional health data includes dimensional data of multiple dimensions about the user's physical health. Among them, each dimensional data may include one of the user's basic data (such as the user's age, gender, height, weight, etc.), the user's health status (such as whether the user is allergic to something, whether the user has been sick recently, etc.), and the user's eating habits (such as whether the user is accustomed to a vegetarian, low-carb, light diet, or a heavy oil and salt diet, etc.). Optionally, the user's nutritional requirement information may include one or more combinations of the user's protein intake requirement, the user's fat intake requirement, the user's carbohydrate intake requirement, the user's vitamin intake requirement, the user's mineral intake requirement, and the user's water intake requirement, which is not limited in the embodiment of the present invention.

[0127] In the embodiment of the present invention, there is no order between step 203 and step 204, that is, step 204 can occur before step 203, or after step 203, or simultaneously with step 203, which is not limited in the embodiment of the present invention.

[0128] 205. Determine the user's cooking requirement information based on the nutritional component information and the nutritional requirement information.

[0129] 206. Filter all initial cooking recipes corresponding to the predetermined ingredient type according to the cooking requirement information to obtain a target cooking recipe corresponding to the ingredient type.

[0130] 207. Recommend the target cooking recipe to the user via the target device.

[0131] In the embodiment of the present invention, for other descriptions of step 201, step 202 and step 207, please refer to the detailed description of step 101, step 102 and step 104 in embodiment 1, which will not be repeated in this embodiment of the present invention.

[0132] It can be seen that implementation Figure 2The described recipe recommendation method based on health management can determine the ingredient data of the target ingredients to be cooked, such as the ingredient type, and obtain the multi-dimensional health data of the user for which the target ingredients are intended. Then, based on the ingredient data and the multi-dimensional health data, the target cooking recipe corresponding to the ingredient type is determined, and then the target cooking recipe is recommended to the user through the target device. It can quickly and accurately determine the target cooking recipe corresponding to the corresponding type of ingredients based on the ingredient data of the ingredients to be cooked and the user's multi-dimensional health data, and then recommend the recipe to the user, so as to facilitate the subsequent selection of recipes that match the user's physical health, and can improve the efficiency of recipe recommendation so that the final recommended recipe can meet the user's physical health needs. In addition, it is also possible to determine the nutritional information corresponding to the ingredient type based on the ingredient data, and analyze the user's nutritional needs information based on multi-dimensional health data, which can improve the accuracy and efficiency of the determined nutritional information of the ingredients and the user's nutritional needs information, and then determine the user's cooking needs information based on the nutritional information and nutritional needs information, which can improve the accuracy of determining the user's cooking needs information based on the nutritional information and nutritional needs information, and then screen all initial cooking recipes corresponding to the predetermined ingredient type based on the cooking needs information to obtain the target cooking recipe corresponding to the ingredient type, which can improve the accuracy and reliability of the screened target cooking recipe corresponding to the ingredient type based on the accurately determined user's cooking needs.

[0133] In an optional embodiment, determining the user's cooking requirement information based on the nutritional component information and the nutritional requirement information in step 205 may include:

[0134] Determine at least one initial cooking method that matches the food type; and analyze the nutrient loss that each initial cooking method may cause to the nutritional information;

[0135] selecting at least one target cooking method that meets preset nutritional matching conditions from all initial cooking methods based on nutritional loss, nutritional composition information, and nutritional requirement information corresponding to each initial cooking method;

[0136] For each target cooking method, the user's sub-cooking requirement information for the target cooking method is analyzed based on the ingredient data of the target ingredients and the preset parameter ratio corresponding to the target cooking method. The parameter ratio includes the ratio of side dishes and / or cooking accessories.

[0137] The cooking requirement information includes any target cooking method and sub-cooking requirement information corresponding to the target cooking method.

[0138] In embodiments of the present invention, the nutrient loss caused by each initial cooking method can optionally be used to represent the amount of nutrient loss caused by each initial cooking method with respect to the content of each nutrient contained in the nutrient information, and / or the ratio of nutrient loss caused by each nutrient contained in the nutrient information. Alternatively, the ratio of side dishes (e.g., when the target ingredient is chicken, the side dish can be at least one of broccoli, carrots, mashed potatoes, peppers, and mushrooms) can be the ratio of the weight of the side dish to the weight of the target ingredient, and the ratio of cooking aids (e.g., seasonings such as oil, salt, and chili sauce) can be the ratio of the cooking aids to the weight of the target ingredient. Alternatively, the preset nutritional matching condition can be a condition where the difference between the total nutritional information and nutrient loss corresponding to the initial cooking method and the user's nutritional requirement information is less than a preset difference, or a condition where the degree of match between the nutritional information and nutrient loss corresponding to the initial cooking method and the user's nutritional requirement information reaches a preset matching degree. Optionally, the sub-cooking requirement information corresponding to each target cooking method may include the side dish type requirement corresponding to the target cooking method, parameters such as the weight or quantity required for the corresponding side dish type, the cooking auxiliary material type requirement corresponding to the target cooking method, and the dosage required for the corresponding cooking auxiliary material type (such as: half a spoonful of salt, 1 gram of salt, etc.), and one or more combinations thereof are not limited in this embodiment of the present invention.

[0139] It can be seen that this optional embodiment can determine at least one initial cooking method that matches the ingredient type; and analyze the nutrient loss that each initial cooking method can cause to the nutrient component information, and select at least one target cooking method that meets the preset nutrient matching conditions from all the initial cooking methods based on the nutrient loss, nutrient component information and nutrient requirement information corresponding to each initial cooking method. This can improve the accuracy of selecting the target cooking method, and can improve the efficiency of selecting the target cooking method based on the various nutrition-related information corresponding to all the initial cooking methods. Subsequently, for each target cooking method, based on the ingredient data of the target ingredient and the parameter ratio corresponding to the preset target cooking method, the user's sub-cooking requirement information for the target cooking method is analyzed, and any target cooking method and the sub-cooking requirement information corresponding to the target cooking method are determined as the user's cooking requirement information. This can improve the accuracy and reliability of the analysis of the cooking requirements corresponding to each target cooking method, thereby improving the accuracy and reliability of determining the user's cooking requirement information, which is beneficial to the subsequent screening of cooking recipes.

[0140] In this optional embodiment, as an optional implementation manner, selecting at least one target cooking method that meets preset nutritional matching conditions from all initial cooking methods based on the nutritional loss, nutritional component information, and nutritional requirement information corresponding to each initial cooking method may include:

[0141] Calculate target nutrient information for each food type under each initial cooking method based on the nutrient loss and nutrient information corresponding to each initial cooking method;

[0142] According to the target nutritional component information corresponding to each initial cooking method and the nutritional requirement information, a matching degree between the target nutritional component information and the nutritional requirement information is calculated to obtain a nutritional matching degree corresponding to each initial cooking method;

[0143] According to the nutritional matching degrees corresponding to all the initial cooking methods, at least one target cooking method whose corresponding nutritional matching degree meets a preset nutritional matching condition is selected from all the initial cooking methods.

[0144] In embodiments of the present invention, the nutritional compatibility can optionally be calculated by comparing the content of each nutrient in the target nutritional information with the required amount of the corresponding nutrient in the nutritional requirement information. For example, the difference between the content of each nutrient in each initial cooking method and the required amount of that nutrient is calculated and then compared with the required amount of that nutrient to obtain a nutrient ratio. The nutritional compatibility corresponding to each initial cooking method is then calculated based on the nutrient ratios and a preset weighting factor for each nutrient (the weighting factor can be based on the user's nutritional goals or calculated based on nutritional anomalies analyzed based on the user's historical dietary habits. Nutritional anomalies can indicate a nutrient deficiency or excess intake). Specifically, based on the nutritional compatibility corresponding to all initial cooking methods, at least one of the initial cooking methods with the highest nutritional compatibility or a nutritional compatibility greater than or equal to a preset compatibility factor is selected as the target cooking method that meets the preset nutritional compatibility criteria. The preset compatibility factor can be 75%, 80%, or any other pre-set value, and is not limited in this embodiment.

[0145] It can be seen that this optional implementation method can calculate the target nutritional component information for the food type under each initial cooking method based on the nutritional loss and nutritional component information corresponding to each initial cooking method, and can accurately calculate the accuracy and reliability of the nutritional component information of the corresponding type of food under the influence of each initial cooking method. Subsequently, based on the target nutritional component information and nutritional requirement information corresponding to each initial cooking method, the matching degree between the target nutritional component information and the nutritional requirement information is calculated to obtain the nutritional matching degree corresponding to each initial cooking method. Based on the nutritional matching degrees corresponding to all initial cooking methods, at least one target cooking method whose corresponding nutritional matching degree meets the preset nutritional matching conditions is selected from all initial cooking methods. Based on the target nutritional component information and user nutritional requirement information corresponding to each initial cooking method, the matching accuracy and efficiency between the target cooking method and the user's needs can be improved, which is conducive to improving the accuracy and reliability of the matched target cooking method, thereby facilitating subsequent cooking needs analysis.

[0146] In another optional embodiment, the method may further include:

[0147] In response to a recipe selection operation for the intelligent cooking device, determining a target cooking recipe corresponding to the recipe selection operation as a recipe to be cooked by the intelligent cooking device;

[0148] Determine cooking control parameters corresponding to the intelligent cooking device based on the cooking details included in the recipe to be cooked;

[0149] Cook the target ingredients according to the cooking control parameters corresponding to the smart cooking device, and monitor the actual nutritional information of the cooked dishes corresponding to the target ingredients during the cooking process;

[0150] According to the actual nutritional information, the cooking control parameters are adjusted so that the actual nutritional information meets the nutritional needs corresponding to the multi-dimensional health data.

[0151] In an embodiment of the present invention, the recipe selection operation may optionally be an operation in which a user clicks on any target cooking recipe displayed on a display device corresponding to the smart cooking device, or an operation in which a user clicks on any target cooking recipe displayed on a recipe display page of a mobile device linked to the smart cooking device. Optionally, the cooking control parameters may include one or more combinations of cooking mode control parameters, cooking time control parameters, cooking temperature control parameters, and cooking heat control parameters. Different cooking devices correspond to different cooking modes. For example, an oven may have a pizza mode, a cake mode, and a barbecue mode, and a microwave may have a hot milk mode, a defrost mode, a grill mode, and a keep-warm mode, etc., although this is not limited in the embodiment of the present invention.

[0152] Specifically, the smart cooking device determines the cooking control parameters corresponding to the smart cooking device according to the cooking details contained in the recipe to be cooked, and triggers the smart cooking device to perform the operation of cooking the target ingredients according to the cooking control parameters corresponding to the smart cooking device; or, the mobile device determines the cooking control parameters corresponding to the smart cooking device according to the cooking details contained in the recipe to be cooked, and sends the cooking control parameters to the smart cooking device to trigger the smart cooking device to perform the operation of cooking the target ingredients according to the cooking control parameters corresponding to the smart cooking device.

[0153] It can be seen that this optional embodiment can respond to the recipe selection operation for the smart cooking device, determine the target cooking recipe corresponding to the recipe selection operation as the recipe to be cooked by the smart cooking device, and determine the cooking control parameters corresponding to the smart cooking device based on the cooking details contained in the recipe to be cooked. It can improve the accuracy and efficiency of determining the cooking control parameters corresponding to the smart cooking device based on the recipe selection operation triggered by the user, and then cook the target ingredients according to the cooking control parameters corresponding to the smart cooking device, and monitor the actual nutritional component information of the cooked dishes corresponding to the target ingredients during the cooking process, and then adjust the cooking control parameters according to the actual nutritional component information so that the actual nutritional component information meets the nutritional requirements corresponding to the multi-dimensional health data. It can realize adaptive adjustment of the cooking control parameters by setting a cooking monitoring process, which helps to make the dishes finally cooked more in line with the nutritional requirements corresponding to the user's multi-dimensional health data.

[0154] Example 3

[0155] See also Figure 3 , Figure 3 This is a structural diagram of a recipe recommendation device based on health management disclosed in an embodiment of the present invention. Figure 3 The described recipe recommendation device based on health management may include a recommendation device or a recommendation server, wherein the recommendation server may include a cloud server or a local server, which is not limited in the embodiment of the present invention. Figure 3 As shown, the recipe recommendation device based on health management may include:

[0156] The determination module 301 is used to determine the ingredient data of the target ingredient to be cooked, where the ingredient data at least includes the ingredient type.

[0157] The acquisition module 302 is used to obtain multi-dimensional health data of the user for which the target food is intended.

[0158] The determination module 301 is also used to determine the target cooking recipe corresponding to the ingredient type based on the ingredient data and the multi-dimensional health data.

[0159] The recommendation module 303 is configured to recommend a target cooking recipe to a user via a target device, where the target device includes a smart cooking device and / or a mobile device.

[0160] It can be seen that implementation Figure 3 The described recipe recommendation device based on health management can determine the ingredient data of the target ingredients to be cooked, such as the ingredient type, and obtain the multi-dimensional health data of the user for which the target ingredients are intended. Then, based on the ingredient data and the multi-dimensional health data, it determines the target cooking recipe corresponding to the ingredient type, and then recommends the target cooking recipe to the user through the target device. It can quickly and accurately determine the target cooking recipe corresponding to the corresponding type of ingredients based on the ingredient data of the ingredients to be cooked and the user's multi-dimensional health data, and then recommend the recipe to the user, so as to facilitate the subsequent selection of recipes that match the user's physical health, and can improve the efficiency of recipe recommendation so that the final recommended recipe can meet the user's physical health needs.

[0161] In an optional embodiment, the determination module 301 determines the target cooking recipe corresponding to the ingredient type based on the ingredient data and the multi-dimensional health data, which may specifically include:

[0162] Determine the nutritional information corresponding to the food type based on the food data;

[0163] Analyze the user's nutritional needs based on multi-dimensional health data, where the multi-dimensional health data includes multiple dimensions of the user's health, each of which includes one of the user's basic data, the user's health status, and the user's eating habits;

[0164] Determine the user's cooking needs based on nutritional information and nutritional needs information;

[0165] According to the cooking requirement information, all initial cooking recipes corresponding to the predetermined ingredient type are screened to obtain a target cooking recipe corresponding to the ingredient type.

[0166] It can be seen that this optional embodiment can determine the nutritional component information corresponding to the ingredient type based on the ingredient data, and analyze the user's nutritional requirement information based on multi-dimensional health data, which can improve the accuracy and efficiency of the determined nutritional component information of the ingredient and the user's nutritional requirement information, and then determine the user's cooking requirement information based on the nutritional component information and the nutritional requirement information, which can improve the accuracy of determining the user's cooking requirement information based on the nutritional component information and the nutritional requirement information, and then screen all initial cooking recipes corresponding to the predetermined ingredient type based on the cooking requirement information to obtain the target cooking recipe corresponding to the ingredient type, which can improve the accuracy and reliability of the target cooking recipe corresponding to the ingredient type screened based on the accurately determined user cooking needs.

[0167] In this optional embodiment, as an optional implementation manner, the determination module 301 determines the user's cooking requirement information based on the nutritional component information and the nutritional requirement information, specifically by:

[0168] Determine at least one initial cooking method that matches the food type; and analyze the nutrient loss that each initial cooking method may cause to the nutritional information;

[0169] selecting at least one target cooking method that meets preset nutritional matching conditions from all initial cooking methods based on nutritional loss, nutritional composition information, and nutritional requirement information corresponding to each initial cooking method;

[0170] For each target cooking method, the user's sub-cooking requirement information for the target cooking method is analyzed based on the ingredient data of the target ingredients and the preset parameter ratio corresponding to the target cooking method. The parameter ratio includes the ratio of side dishes and / or cooking accessories.

[0171] The cooking requirement information includes any target cooking method and sub-cooking requirement information corresponding to the target cooking method.

[0172] It can be seen that this optional implementation method can determine at least one initial cooking method that matches the ingredient type; and analyze the nutrient loss that each initial cooking method can cause to the nutrient component information, and according to the nutrient loss, nutrient component information and nutrient requirement information corresponding to each initial cooking method, select at least one target cooking method that meets the preset nutrient matching conditions from all the initial cooking methods, which can improve the accuracy of selecting the target cooking method, and can improve the efficiency of selecting the target cooking method based on the various nutrition-related information corresponding to all the initial cooking methods. Subsequently, for each target cooking method, according to the ingredient data of the target ingredient and the parameter ratio corresponding to the preset target cooking method, analyze the user's sub-cooking requirement information for the target cooking method, and determine any target cooking method and the sub-cooking requirement information corresponding to the target cooking method as the user's cooking requirement information, which can improve the accuracy and reliability of the analysis of the cooking requirements corresponding to each target cooking method, thereby improving the accuracy and reliability of determining the user's cooking requirement information, and thus facilitating the subsequent screening of cooking recipes.

[0173] In this optional embodiment, the determination module 301 may select at least one target cooking method that meets the preset nutritional matching conditions from all initial cooking methods based on the nutritional loss, nutritional component information, and nutritional requirement information corresponding to each initial cooking method. Specifically, the method may include:

[0174] Calculate target nutrient information for each food type under each initial cooking method based on the nutrient loss and nutrient information corresponding to each initial cooking method;

[0175] According to the target nutritional component information corresponding to each initial cooking method and the nutritional requirement information, a matching degree between the target nutritional component information and the nutritional requirement information is calculated to obtain a nutritional matching degree corresponding to each initial cooking method;

[0176] According to the nutritional matching degrees corresponding to all the initial cooking methods, at least one target cooking method whose corresponding nutritional matching degree meets a preset nutritional matching condition is selected from all the initial cooking methods.

[0177] It can be seen that this optional implementation method can also calculate the target nutritional component information for the food type under each initial cooking method based on the nutritional loss and nutritional component information corresponding to each initial cooking method, and can accurately calculate the accuracy and reliability of the nutritional component information of the corresponding type of food under the influence of each initial cooking method. Subsequently, based on the target nutritional component information and nutritional requirement information corresponding to each initial cooking method, the matching degree between the target nutritional component information and the nutritional requirement information is calculated to obtain the nutritional matching degree corresponding to each initial cooking method. Based on the nutritional matching degrees corresponding to all initial cooking methods, at least one target cooking method whose corresponding nutritional matching degree meets the preset nutritional matching conditions is selected from all initial cooking methods. Based on the target nutritional component information and user nutritional requirement information corresponding to each initial cooking method, the matching accuracy and efficiency between the target cooking method and the user's needs can be improved, which is conducive to improving the accuracy and reliability of the matched target cooking method, thereby facilitating subsequent cooking needs analysis.

[0178] In another optional embodiment, the multi-dimensional health data also includes the user's nutritional goals. The method in which the recommendation module 303 recommends the target cooking recipe to the user via the target device may specifically include:

[0179] When the number of target cooking recipes is greater than 1, all target cooking recipes are sorted according to the user's nutritional goals based on a preset sorting algorithm to obtain a recipe recommendation sequence. The recipe recommendation sequence includes at least all target cooking recipes and the sequence number corresponding to each target cooking recipe;

[0180] Obtaining the historical cooking recipe record selected by the user, and selecting, based on the ingredient type, a historical cooking recipe corresponding to the ingredient type from the historical cooking recipes of multiple historical time periods contained in all the historical cooking recipe records;

[0181] Marking identical recipes in a recipe recommendation sequence based on historical cooking recipes, so that the recipe recommendation sequence also includes marking information of the historical cooking recipe selected by the user;

[0182] According to the recipe recommendation sequence, all target cooking recipes are recommended to the user in sequence through the target device.

[0183] It can be seen that this optional embodiment can, when the number of target cooking recipes is greater than 1, sort all target cooking recipes based on a preset sorting algorithm and according to the user's nutritional goals to obtain a recipe recommendation sequence. The recipe recommendation sequence at least includes all target cooking recipes and the sequence number corresponding to each target cooking recipe. It can improve the accuracy and efficiency of the recipe recommendation sequence obtained by sorting based on the sorting algorithm and the user's nutritional goals, and obtain the historical cooking recipe record selected by the user, and select the historical cooking recipe corresponding to the ingredient type from the historical cooking recipes of multiple historical time periods contained in all historical cooking recipe records according to the ingredient type, and select the historical cooking recipe corresponding to the ingredient type according to the historical cooking recipe. The same recipes in the recipe recommendation sequence are marked so that the recipe recommendation sequence also includes the marking information of the historical cooking recipes selected by the user. The same recipes in the recipe recommendation sequence can be marked quickly and accurately based on the historical cooking recipes corresponding to the ingredient type, which is beneficial to improving the content richness of the recipe recommendation sequence. Then, according to the recipe recommendation sequence, all target cooking recipes are recommended to the user in sequence through the target device. The target cooking recipes can be accurately recommended to the user based on the recipe recommendation sequence, which is beneficial to improving the accuracy and reliability of recipe recommendation. In addition, the recipe recommendation sequence combined with the historical cooking recipes is beneficial to improving the intelligence of recipe recommendation.

[0184] In this optional embodiment, as an optional implementation, the recommendation module 303 sorts all target cooking recipes based on the user's nutritional goals based on a preset sorting algorithm. The method of obtaining the recipe recommendation sequence may specifically include:

[0185] Analyze the target relationship between each target cooking recipe and the user's nutritional goals based on the user's nutritional goals contained in the multi-dimensional health data. The target relationship includes a positive correlation or a negative correlation.

[0186] Based on the target relationship, the time required for the user to reach the user's nutritional goal under the influence of each target cooking recipe is predicted, and the expected nutritional control time corresponding to each target cooking recipe is obtained;

[0187] Based on a preset sorting algorithm, a sorting operation is performed on all target cooking recipes according to the expected nutritional control time corresponding to all target cooking recipes to obtain a recipe recommendation sequence; wherein, the recipe recommendation sequence is obtained by sorting all target cooking recipes in ascending order of the expected nutritional control time.

[0188] It can be seen that this optional implementation method can analyze the target relationship between each target cooking recipe and the user's nutritional goal, such as a positive correlation or a negative correlation, based on the user's nutritional goal contained in the multi-dimensional health data, and predict the time required for the user to reach the user's nutritional goal under the influence of each target cooking recipe based on the target relationship, and obtain the expected nutritional control time corresponding to each target cooking recipe. This can improve the analysis accuracy of the target relationship between each target cooking recipe and the user's nutritional goal, thereby improving the prediction accuracy and reliability of the expected nutritional control time corresponding to each target cooking recipe based on the target relationship. Then, based on the preset sorting algorithm, all target cooking recipes are sorted according to the expected nutritional control time corresponding to all target cooking recipes to obtain a recipe recommendation sequence. This can achieve accurate sorting of all target cooking recipes based on the preset sorting algorithm and the expected nutritional control time corresponding to all target cooking recipes, which is conducive to improving the accuracy and reliability of the recipe recommendation sequence obtained by sorting, and is conducive to subsequent recipe recommendations.

[0189] In another optional embodiment, the determination module 301 is further configured to, in response to a recipe selection operation on the smart cooking device, determine the target cooking recipe corresponding to the recipe selection operation as the recipe to be cooked by the smart cooking device; the determination module 301 is further configured to determine the cooking control parameters corresponding to the smart cooking device based on the cooking details included in the recipe to be cooked. And, Figure 4 As shown, Figure 4 is a structural diagram of another device for recommending recipes based on health management disclosed in an embodiment of the present invention, wherein the device may further include:

[0190] The cooking module 304 is used to cook the target ingredients according to the cooking control parameters corresponding to the intelligent cooking device.

[0191] The monitoring module 305 is used to monitor the actual nutritional information of the cooking dish corresponding to the target ingredient during the cooking process.

[0192] The adjustment module 306 is used to adjust the cooking control parameters according to the actual nutritional information so that the actual nutritional information meets the nutritional requirements corresponding to the multi-dimensional health data.

[0193] It can be seen that this optional embodiment can respond to the recipe selection operation for the smart cooking device, determine the target cooking recipe corresponding to the recipe selection operation as the recipe to be cooked by the smart cooking device, and determine the cooking control parameters corresponding to the smart cooking device based on the cooking details contained in the recipe to be cooked. It can improve the accuracy and efficiency of determining the cooking control parameters corresponding to the smart cooking device based on the recipe selection operation triggered by the user, and then cook the target ingredients according to the cooking control parameters corresponding to the smart cooking device, and monitor the actual nutritional component information of the cooked dishes corresponding to the target ingredients during the cooking process, and then adjust the cooking control parameters according to the actual nutritional component information so that the actual nutritional component information meets the nutritional requirements corresponding to the multi-dimensional health data. It can realize adaptive adjustment of the cooking control parameters by setting a cooking monitoring process, which helps to make the dishes finally cooked more in line with the nutritional requirements corresponding to the user's multi-dimensional health data.

[0194] Example 4

[0195] See also Figure 5 , Figure 5 This is a structural diagram of another recipe recommendation device based on health management disclosed in an embodiment of the present invention. Figure 5 As shown, the recipe recommendation device based on health management may include:

[0196] A memory 401 storing executable program code;

[0197] a processor 402 coupled to the memory 401;

[0198] The processor 402 calls the executable program code stored in the memory 401 to execute the steps of the recipe recommendation method based on health management described in the first embodiment of the present invention or the second embodiment of the present invention.

[0199] Example 5

[0200] An embodiment of the present invention discloses a computer storage medium storing computer instructions. When the computer instructions are called, they are used to execute the steps of the recipe recommendation method based on health management described in Embodiment 1 or Embodiment 2 of the present invention.

[0201] Example 6

[0202] An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to enable a computer to execute the steps of the recipe recommendation method based on health management described in Example 1 or Example 2.

[0203] The device embodiments described above are merely illustrative, wherein the modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, i.e., they may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Those skilled in the art can understand and implement the present invention without inventive effort.

[0204] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus the necessary general hardware platform, or of course, by means of hardware. Based on this understanding, the above technical solution, in essence, or the portion that contributes to the prior art, can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, including a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0205] Finally, it should be noted that the recipe recommendation method and device based on health management disclosed in the embodiments of the present invention only disclose the preferred embodiments of the present invention, which are only used to illustrate the technical solutions of the present invention, rather than to limit them. Although the present invention has been described in detail with reference to the aforementioned embodiments, it should be understood by those skilled in the art that the technical solutions described in the aforementioned embodiments can still be modified, or some of the technical features therein can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A recipe recommendation method based on health management, characterized in that: The method comprises: Determining ingredient data of a target ingredient to be cooked, wherein the ingredient data at least includes an ingredient type; Acquiring multi-dimensional health data of users targeted by the target food; Based on the ingredient data and the multi-dimensional health data, a target cooking recipe corresponding to the ingredient type is determined; and the target cooking recipe is recommended to the user via a target device, where the target device includes a smart cooking device and / or a mobile device.

2. The recipe recommendation method based on health management according to claim 1, characterized in that: Determining a target cooking recipe corresponding to the ingredient type based on the ingredient data and the multi-dimensional health data includes: Determining nutritional information corresponding to the food type based on the food data; Analyzing the nutritional needs information of the user based on the multi-dimensional health data, wherein the multi-dimensional health data includes dimensional data of multiple dimensions related to the user's physical health, each of the dimensional data including one of basic data of the user, health status of the user, and eating habits of the user; determining the user's cooking requirement information based on the nutritional component information and the nutritional requirement information; According to the cooking requirement information, all initial cooking recipes corresponding to the predetermined ingredient type are screened to obtain a target cooking recipe corresponding to the ingredient type.

3. The recipe recommendation method based on health management according to claim 2, characterized in that: The determining the user's cooking requirement information based on the nutritional component information and the nutritional requirement information includes: Determining at least one initial cooking method that matches the food type; and analyzing the nutrient loss that each of the initial cooking methods may cause to the nutrient component information; selecting at least one target cooking method that meets a preset nutritional matching condition from all the initial cooking methods according to the nutritional loss corresponding to each of the initial cooking methods, the nutritional component information, and the nutritional requirement information; For each target cooking method, analyzing the user's sub-cooking requirement information for the target cooking method based on the ingredient data of the target ingredient and a preset parameter ratio corresponding to the target cooking method, where the parameter ratio includes a side dish ratio and / or a cooking auxiliary ingredient ratio; The cooking requirement information includes any one of the target cooking methods and sub-cooking requirement information corresponding to the target cooking method.

4. The recipe recommendation method based on health management according to claim 3, characterized in that: The selecting, based on the nutrient loss situation corresponding to each of the initial cooking methods, the nutrient component information, and the nutrient requirement information, at least one target cooking method that meets a preset nutrient matching condition from all the initial cooking methods includes: Calculating target nutrient information for the food type under each initial cooking method according to the nutrient loss corresponding to each initial cooking method and the nutrient information; Calculating a matching degree between the target nutrient component information and the nutrient requirement information according to the target nutrient component information corresponding to each of the initial cooking methods, and obtaining a nutrient matching degree corresponding to each of the initial cooking methods; According to the nutritional matching degrees corresponding to all the initial cooking methods, at least one target cooking method whose corresponding nutritional matching degree meets a preset nutritional matching condition is selected from all the initial cooking methods.

5. The recipe recommendation method based on health management according to any one of claims 1 to 4, characterized in that: The multi-dimensional health data also includes user nutrition goals; The step of recommending the target cooking recipe to the user through the target device includes: When the number of the target cooking recipes is greater than one, all the target cooking recipes are sorted according to the user's nutritional goal based on a preset sorting algorithm to obtain a recipe recommendation sequence, wherein the recipe recommendation sequence includes at least all the target cooking recipes and a sequence number corresponding to each target cooking recipe; Acquire the historical cooking recipe record selected by the user, and select, based on the ingredient type, a historical cooking recipe corresponding to the ingredient type from among all historical cooking recipes in multiple historical time periods included in the historical cooking recipe record; marking identical recipes in the recipe recommendation sequence according to the historical cooking recipes, so that the recipe recommendation sequence also includes marking information of the historical cooking recipe selected by the user; According to the recipe recommendation sequence, all the target cooking recipes are recommended to the user in sequence via the target device.

6. The recipe recommendation method based on health management according to claim 5, characterized in that: The preset sorting algorithm is used to sort all the target cooking recipes according to the user's nutritional goals to obtain a recipe recommendation sequence, including: analyzing, based on the user nutritional goals included in the multi-dimensional health data, a target relationship between each target cooking recipe and the user nutritional goals, wherein the target relationship includes a positive correlation or a negative correlation; predicting, based on the target relationship, the time required for the user to reach the user's nutritional goal under the influence of each target cooking recipe, and obtaining an expected nutritional control time corresponding to each target cooking recipe; Based on a preset sorting algorithm, a sorting operation is performed on all the target cooking recipes according to the expected nutritional control times corresponding to all the target cooking recipes to obtain a recipe recommendation sequence; wherein, the recipe recommendation sequence is obtained by sorting all the target cooking recipes in ascending order of the expected nutritional control times.

7. The recipe recommendation method based on health management according to any one of claims 1, 2, 3, 4 and 6, characterized in that: The method further comprises: In response to a recipe selection operation for the intelligent cooking device, determining a target cooking recipe corresponding to the recipe selection operation as a recipe to be cooked by the intelligent cooking device; determining cooking control parameters corresponding to the intelligent cooking device according to the cooking details included in the recipe to be cooked; Cooking the target ingredients according to the cooking control parameters corresponding to the intelligent cooking device, and monitoring the actual nutritional information of the cooked dish corresponding to the target ingredients during the cooking process; The cooking control parameters are adjusted according to the actual nutritional information so that the actual nutritional information meets the nutritional requirements corresponding to the multi-dimensional health data.

8. A recipe recommendation device based on health management, characterized in that: The device comprises: a determination module, configured to determine ingredient data of a target ingredient to be cooked, wherein the ingredient data at least includes an ingredient type; An acquisition module, configured to acquire multi-dimensional health data of the user for whom the target food is intended; The determination module is further configured to determine a target cooking recipe corresponding to the ingredient type based on the ingredient data and the multi-dimensional health data; The recommendation module is configured to recommend the target cooking recipe to the user via a target device, where the target device includes a smart cooking device and / or a mobile device.

9. A recipe recommendation device based on health management, characterized in that: The device comprises: a memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the recipe recommendation method based on health management as described in any one of claims 1-7.

10. A computer storage medium, characterized in that The computer storage medium stores computer instructions, which, when called, are used to execute the recipe recommendation method based on health management as described in any one of claims 1 to 7.

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