Method and device for recommending dishes based on multi-dimensional user data

Abstract

The invention relates to the technical field of dish recommendation, and discloses a dish recommendation method and device based on multi-dimensional user data, and the method comprises the steps: determining the body index data of a user according to the attribute information and weight information of the user, and estimating the required nutritional value of the user; screening out all dish combinations meeting the nutritional value demand conditions of the user from a dish database according to the demand nutritional value; and inputting the dish types and the dish weights of all the dish combinations, the body health condition of the user, the historical nutrition intake data and the taste and food material preference data into a dish recommendation big language model for analysis to obtain a three-meal target dish combination conforming to the body and preference of the user. Therefore, the comprehensiveness, rationality and layer-by-layer progression of the three-meal target dish combination determination mode can be improved, the accuracy, reliability, determination efficiency and determination convenience of the three-meal target dish combination are improved, and the accuracy, efficiency and convenience of dish recommendation are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of dish recommendation, and in particular to a method and device for dish recommendation based on multi-dimensional user data. BACKGROUND

[0002] With the development of social economy and the improvement of public health awareness, the concept of balanced diet has been deeply rooted in people's minds and has become an important guideline for the public to pursue a healthy life. Effective dish matching is a key way to ensure balanced diet, therefore, personalized dish recommendation service has become a major service demand.

[0003] Currently, most dish recommendation methods rely on a single data source. In the catering industry, dish recommendation is mainly based on user historical ordering records, and in the home cooking scene, dish recommendation is only based on user past cooking records. Users still need to adjust dishes subjectively according to their current situation. The current method mainly relies on the subjective choice of users in the past, and there is a significant deficiency in ensuring balanced diet. The accuracy and reliability of dish recommendation are low. Therefore, it is particularly important to provide a dish recommendation method that can improve the accuracy and reliability of dish recommendation. SUMMARY

[0004] The present application provides a method and device for dish recommendation based on multi-dimensional user data, which can improve the accuracy and reliability of dish recommendation.

[0005] To solve the above technical problems, the present application discloses a method for dish recommendation based on multi-dimensional user data, which comprises:

[0006] According to the image data of the user collected by the image acquisition device, the attribute information of the user is analyzed, and the weight information of the user is obtained;

[0007] According to the attribute information and the weight information, the body index data of the user is determined;

[0008] According to the body index data, the required nutritional value of the user is estimated, and according to the required nutritional value, all dish combinations that meet the nutritional value requirement of the user are selected from the pre-determined dish database;

[0009] The dish types and dish weights of all the dish combinations, the determined body health condition of the user, the historical nutritional intake data and the taste material preference data are input into the trained and converged dish recommendation large language model for analysis, and the target dish combination of three meals that meets the user's body and preference is obtained.

[0010] As an optional implementation, in the first aspect of the present application, the dish category and dish weight of all the dish combinations, the determined physical health condition of the user, historical nutrition intake data and taste food material preference data are input into a trained dish recommendation large language model for analysis to obtain a target three-meal dish combination that meets the user's physical condition and preferences, including:

[0011] According to the dish category and dish weight of all the dish combinations and the determined health condition of the user, a first recommended three-meal dish combination corresponding to the user is determined;

[0012] According to the dish category and dish weight of all the dish combinations and the determined historical nutrition intake data of the user, a second recommended three-meal dish combination corresponding to the user is determined;

[0013] According to the dish category and dish weight of all the dish combinations and the determined taste food material preference data of the user, a third recommended three-meal dish combination corresponding to the user is determined;

[0014] According to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination, a target three-meal dish combination that meets the user's physical condition and preferences is determined.

[0015] As an optional implementation, in the first aspect of the present application, the determination of the target three-meal dish combination that meets the user's physical condition and preferences according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination includes:

[0016] determining whether the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination meet a preset exclusive efficacy supply condition;

[0017] When it is determined that the exclusive efficacy supply condition is met, according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination, a corresponding three-meal dish combination comprehensive adjustment operation is performed based on the user's reasonable intake level to obtain a target three-meal dish combination that meets the user's physical condition and preferences;

[0018] When it is judged that the exclusive efficacy supply condition is not met, a first recommended three-meal dish combination and a second recommended three-meal dish combination that meet a preset nutritional efficacy similarity condition and a third recommended three-meal dish combination that does not meet the preset nutritional efficacy similarity condition are screened out according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination; a corresponding dish optimization comprehensive operation is performed on all the first recommended three-meal dish combinations and a corresponding dish merging integration operation is performed on all the second recommended three-meal dish combinations, so as to obtain a three-meal target dish combination that meets the user's body and preferences.

[0019] As an optional implementation, in the first aspect of the present application, the three-meal target dish combination that meets the user's body and preferences is obtained by performing a corresponding three-meal dish combination comprehensive adjustment operation on the basis of the user's reasonable intake level according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination, including:

[0020] It is judged whether the user meets a preset abnormal intake condition according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination;

[0021] When it is judged that the user does not meet the abnormal intake condition, a corresponding direct integration operation is performed on the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination, so as to obtain a three-meal target dish combination that meets the user's body and preferences;

[0022] When it is judged that the user meets the abnormal intake condition, a dish combination priority scheme corresponding to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination is determined; a corresponding screening comprehensive operation is performed on the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination according to the dish combination priority scheme, so as to obtain a three-meal target dish combination that meets the user's body and preferences.

[0023] As an optional implementation, in the first aspect of the present application, it is judged whether the user meets a preset abnormal intake condition according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination, including:

[0024] A comprehensive intake component corresponding to the user is determined according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination;

[0025] It is judged whether the user meets a preset excessive intake condition according to the comprehensive intake component;

[0026] determining that the user meets the preset abnormal intake condition when it is judged that the user meets the excessive intake condition;

[0027] determining the comprehensive absorption nutrition corresponding to the user according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination when it is judged that the user does not meet the excessive intake condition;

[0028] judging whether the user meets a preset excessive absorption condition according to the comprehensive absorption nutrition;

[0029] determining that the user meets the preset abnormal intake condition when it is judged that the user meets the excessive absorption condition;

[0030] determining that the user does not meet the preset abnormal intake condition when it is judged that the user does not meet the excessive absorption condition.

[0031] As an optional implementation form, in the first aspect of the present application, the judging whether the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination meet the preset exclusive efficacy supply condition comprises:

[0032] determining a first supply parameter that can be achieved by the first recommended three-meal dish combination, a second supply parameter that can be achieved by the second recommended three-meal dish combination and a third supply parameter that can be achieved by the third recommended three-meal dish combination;

[0033] judging whether there is sub-parameter information meeting the preset similar condition among the first supply parameter, the second supply parameter and the third supply parameter;

[0034] determining that the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination meet the preset exclusive efficacy supply condition when the judgment result is yes;

[0035] determining that the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination do not meet the preset exclusive efficacy supply condition when the judgment result is no;

[0036] wherein the first supply parameter, the second supply parameter and the third supply parameter all comprise nutrition type and content information and / or function type and effect information.

[0037] As an optional implementation form, in the first aspect of the present application, the judging whether the user meets the preset excessive intake condition according to the comprehensive intake component comprises:

[0038] determining whether the comprehensive intake component is greater than or equal to a preset comprehensive intake component threshold value;

[0039] when it is determined that the comprehensive intake component is greater than or equal to the comprehensive intake component threshold value, determining that the user meets a preset excessive intake condition;

[0040] when it is determined that the comprehensive intake component is less than the comprehensive intake component threshold value, determining that the user does not meet the preset excessive intake condition;

[0041] and, the determining whether the user meets a preset nutrient absorption excess condition according to the comprehensive absorption nutrient, comprises:

[0042] determining whether the comprehensive absorption nutrient is greater than or equal to a preset comprehensive absorption nutrient threshold value;

[0043] when it is determined that the comprehensive absorption nutrient is greater than or equal to the comprehensive absorption nutrient threshold value, determining that the user meets a preset nutrient absorption excess condition;

[0044] when it is determined that the comprehensive absorption nutrient is less than the comprehensive absorption nutrient threshold value, determining that the user does not meet the preset nutrient absorption excess condition.

[0045] The second aspect of the present application discloses a device for dish recommendation based on multi-dimensional user data, comprising:

[0046] an information determination module, configured to analyze attribute information of a user according to image data of the user collected by an image collection device, and obtain body weight information of the user; and determine body index data of the user according to the attribute information and the body weight information;

[0047] a first dish combination determination module, configured to estimate required nutrient value to be taken by the user according to the body index data, and select all dish combinations meeting nutrient value requirement conditions of the user from a pre-determined dish database according to the required nutrient value;

[0048] a second dish combination determination module, configured to input dish categories and dish weights of all the dish combinations, determined body health conditions of the user, historical nutrient intake data and taste material preference data into a trained and converged dish recommendation large language model for analysis, and obtain three-meal target dish combinations meeting the body and preferences of the user.

[0049] As an optional implementation, in the second aspect of the present application, the second dish combination determination module inputs the dish categories and dish weights of all the dish combinations, the determined physical health condition of the user, historical nutrition intake data and taste food material preference data into the trained dish recommendation large language model for analysis to obtain a target three-meal dish combination that meets the user's physical condition and preferences in the following manner:

[0050] determining a first recommended three-meal dish combination corresponding to the user according to the dish categories and dish weights of all the dish combinations and the determined health condition of the user;

[0051] determining a second recommended three-meal dish combination corresponding to the user according to the dish categories and dish weights of all the dish combinations and the determined historical nutrition intake data of the user;

[0052] determining a third recommended three-meal dish combination corresponding to the user according to the dish categories and dish weights of all the dish combinations and the determined taste food material preference data of the user;

[0053] determining a target three-meal dish combination that meets the user's physical condition and preferences according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination.

[0054] As an optional implementation, in the second aspect of the present application, the second dish combination determination module determines a target three-meal dish combination that meets the user's physical condition and preferences according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination in the following manner:

[0055] determining whether the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination meet a preset exclusive efficacy supply condition;

[0056] when it is determined that the exclusive efficacy supply condition is met, performing corresponding three-meal dish combination comprehensive adjustment operations based on user reasonable intake level according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination to obtain a target three-meal dish combination that meets the user's physical condition and preferences;

[0057] When it is judged that the exclusive efficacy supply condition is not satisfied, a first recommended three-meal dish combination satisfying a preset nutrition efficacy similarity condition and a second recommended three-meal dish combination not satisfying the preset nutrition efficacy similarity condition are screened out according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination; a corresponding dish optimization comprehensive operation is performed on all the first recommended three-meal dish combinations and a corresponding dish combination integration operation is performed on all the second recommended three-meal dish combinations, so as to obtain a three-meal target dish combination conforming to the user's body and preference.

[0058] As an optional implementation, in the second aspect of the present application, the second dish combination determination module, based on the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination, performs a corresponding three-meal dish combination comprehensive adjustment operation on a user reasonable intake level to obtain a three-meal target dish combination conforming to the user's body and preference, and the specific implementation includes:

[0059] According to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination, it is judged whether the user satisfies a preset abnormal intake condition;

[0060] When it is judged that the user does not satisfy the abnormal intake condition, a corresponding direct integration operation is performed on the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination to obtain a three-meal target dish combination conforming to the user's body and preference;

[0061] When it is judged that the user satisfies the abnormal intake condition, a dish combination priority scheme corresponding to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination is determined; according to the dish combination priority scheme, a corresponding screening comprehensive operation is performed on the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination to obtain a three-meal target dish combination conforming to the user's body and preference.

[0062] As an optional implementation, in the second aspect of the present application, the second dish combination determination module, according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination, judges whether the user satisfies a preset abnormal intake condition, and the specific implementation includes:

[0063] According to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination, a comprehensive intake component corresponding to the user is determined;

[0064] Determining whether the user meets a preset excessive intake condition based on the comprehensive intake amount;

[0065] When it is determined that the user meets the excessive intake condition, determining that the user meets a preset abnormal intake condition;

[0066] When it is determined that the user does not meet the excessive intake condition, determining the comprehensive nutritional absorption corresponding to the user based on the first recommended three-meal dish combination, the second recommended three-meal dish combination, and the third recommended three-meal dish combination;

[0067] According to the comprehensive nutrition absorption, determining whether the user meets a preset excess nutrition absorption condition;

[0068] When it is determined that the user meets the excess nutrient absorption condition, determining that the user meets a preset abnormal intake condition;

[0069] When it is determined that the user does not meet the excess nutrient absorption condition, it is determined that the user does not meet the preset abnormal intake condition.

[0070] As an optional embodiment, in the second aspect of the present invention, the second dish combination determination module determines whether the first recommended three-meal dish combination, the second recommended three-meal dish combination, and the third recommended three-meal dish combination meet the preset exclusive efficacy supply conditions in a manner specifically including:

[0071] Determining a first achievable supply parameter based on the first recommended three-meal dish combination, determining a second achievable supply parameter based on the second recommended three-meal dish combination, and determining a third achievable supply parameter based on the third recommended three-meal dish combination;

[0072] Determining whether there is sub-parameter information that meets a preset similarity condition among the first supply parameter, the second supply parameter, and the third supply parameter;

[0073] When the judgment result is yes, it is determined that the first recommended three-meal dish combination, the second recommended three-meal dish combination, and the third recommended three-meal dish combination meet the preset exclusive efficacy supply conditions;

[0074] When the judgment result is no, it is determined that the first recommended three-meal dish combination, the second recommended three-meal dish combination, and the third recommended three-meal dish combination do not meet the preset exclusive efficacy supply conditions;

[0075] The first supply parameter, the second supply parameter and the third supply parameter all include nutritional type and content information and / or functional type and effect information.

[0076] As an optional implementation, in the second aspect of the present application, the manner in which the second dish combination determination module determines whether the user satisfies the preset excessive intake condition according to the comprehensive intake component specifically includes:

[0077] determining whether the comprehensive intake component is greater than or equal to a preset comprehensive intake component threshold value;

[0078] when it is determined that the comprehensive intake component is greater than or equal to the comprehensive intake component threshold value, determining that the user satisfies the preset excessive intake condition;

[0079] when it is determined that the comprehensive intake component is less than the comprehensive intake component threshold value, determining that the user does not satisfy the preset excessive intake condition;

[0080] and the manner in which the second dish combination determination module determines whether the user satisfies the preset excessive nutrient absorption condition according to the comprehensive absorption nutrient specifically includes:

[0081] determining whether the comprehensive absorption nutrient is greater than or equal to a preset comprehensive absorption nutrient threshold value;

[0082] when it is determined that the comprehensive absorption nutrient is greater than or equal to the comprehensive absorption nutrient threshold value, determining that the user satisfies the preset excessive nutrient absorption condition;

[0083] when it is determined that the comprehensive absorption nutrient is less than the comprehensive absorption nutrient threshold value, determining that the user does not satisfy the preset excessive nutrient absorption condition.

[0084] The third aspect of the present application discloses another device for dish recommendation based on multi-dimensional user data, and the device comprises:

[0085] a memory in which executable program codes are stored;

[0086] a processor coupled with the memory;

[0087] the processor invokes the executable program codes stored in the memory to execute the method for dish recommendation based on multi-dimensional user data disclosed in the first aspect of the present application.

[0088] The fourth aspect of the present application discloses a computer storage medium, and the computer storage medium stores computer instructions which, when invoked, are used to execute the method for dish recommendation based on multi-dimensional user data disclosed in the first aspect of the present application.

[0089] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0090] In the embodiment of the present application, according to the image data of the user collected by the image acquisition device, the attribute information of the user is analyzed, and the weight information of the user is obtained; according to the attribute information and the weight information, the body index data of the user is determined; according to the body index data, the required nutritional value required by the user is estimated, and according to the required nutritional value, all dish combinations meeting the nutritional value requirement of the user are screened out from the dish database determined in advance; the dish types and dish weights of all the dish combinations, the determined body health condition of the user, the historical nutritional intake data and the taste food material preference data are input into the trained and converged dish recommendation large language model for analysis, and the target dish combination of three meals meeting the body and preference of the user is obtained. It can be seen that the present application can perform a first-level dish combination recommendation operation based on the attribute information and the weight information of the user, further perform a second-level dish combination recommendation operation based on the dish types and dish weights of the first-level dish combination, the body health condition of the user, the historical nutritional intake data and the taste food material preference data, and obtain the target dish combination of three meals meeting the body and preference of the user, which is beneficial to improve the comprehensiveness, rationality and layer-by-layer progression of the target dish combination determination method of three meals, and further beneficial to improve the accuracy and reliability of the determined target dish combination of three meals, and beneficial to improve the determination efficiency and convenience of the target dish combination of three meals, thereby beneficial to improve the accuracy, efficiency and convenience of dish recommendation. BRIEF DESCRIPTION OF DRAWINGS

[0091] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0092] Figure 1 is a flow diagram of a device for dish recommendation based on multi-dimensional user data disclosed by the embodiment of the present application;

[0093] Figure 2 is a flow diagram of another device for dish recommendation based on multi-dimensional user data disclosed by the embodiment of the present application;

[0094] Figure 3 is a structural diagram of a device for dish recommendation based on multi-dimensional user data disclosed by the embodiment of the present application;

[0095] Figure 4 is a structural diagram of another device for dish recommendation based on multi-dimensional user data disclosed by the embodiment of the present application. DETAILED DESCRIPTION

[0096] In the following, the technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0097] The terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish different objects, rather than to describe a particular order. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, device, product, or the like including a series of steps or units is not limited to the listed steps or units, but can optionally further include steps or units not listed or can optionally further include other steps or units inherent to the process, method, product, or the like.

[0098] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearance of this phrase in various places in the specification does not necessarily all refer to the same embodiment, nor is it necessarily mutually exclusive of other embodiments. It is explicitly and implicitly understood that the embodiments described herein can be combined with other embodiments.

[0099] The application discloses a method and device for dish recommendation based on multi-dimensional user data, which can perform first-level dish combination recommendation operation based on attribute information and weight information of a user, further perform second-level dish combination recommendation operation based on dish categories and dish weights of the first-level dish combination, physical health conditions of the user, historical nutrition intake data and taste and food material preference data, so as to obtain a three-meal target dish combination meeting the physical conditions and preferences of the user, which is beneficial to improving the comprehensiveness, rationality and layer-by-layer progression of the three-meal target dish combination determination method, and further beneficial to improving the accuracy and reliability of the determined three-meal target dish combination, and beneficial to improving the determination efficiency and convenience of the three-meal target dish combination, so as to be beneficial to improving the accuracy, efficiency and convenience of dish recommendation. The following will be described in detail.

[0100] Embodiment one

[0101] Please refer to Figure 1 , Figure 1 is a flowchart of a method for dish recommendation based on multi-dimensional user data according to an embodiment of the present application. In the method, Figure 1The described method can be applied to a device for dish recommendation based on multi-dimensional user data, wherein the device can include a server, and the server can include a local server or a cloud server, and embodiments of the present application are not limited. Figure 1 As shown in the figure, the method for dish recommendation based on multi-dimensional user data includes the following operations:

[0102] 101. Analyze the attribute information of the user according to the image data of the user collected by the image collection device, and obtain the weight information of the user.

[0103] Optionally, the attribute information of the user can include one or more of the user's age, gender, height, and other attribute information, and embodiments of the present application are not limited.

[0104] Optionally, the weight information of the user is determined by a weighing scale or other weight collection device, and embodiments of the present application are not limited.

[0105] Optionally, the attribute information of the user is analyzed according to the image data of the user collected by the image collection device, for example, user information is managed through face recognition, and the attribute information of the user is obtained through image recognition, and embodiments of the present application are not limited.

[0106] 102. Determine the body index data of the user according to the attribute information and the weight information.

[0107] Optionally, the body index data can include one or more of BMI data, body fat rate, and other information that can reflect the body index of the user, and embodiments of the present application are not limited.

[0108] 103. Estimate the required nutritional value of the user according to the body index data, and select all dish combinations that meet the nutritional value requirement of the user from the pre-determined dish database according to the required nutritional value.

[0109] Optionally, the required nutritional value can include but is not limited to the required nutritional type and the specific required nutritional degree; further, for example, protein, vitamin, mineral, fat, carbohydrate, dietary fiber, water, and bioactive ingredients, and embodiments of the present application are not limited.

[0110] Optionally, the dish combination can include one or more dishes, the cooking method of each dish, and the like, and embodiments of the present application are not limited.

[0111] 104. Input the dish types and dish weights of all dish combinations, the determined health condition of the user, the historical nutritional intake data, and the taste and food material preference data into the trained and converged dish recommendation large language model for analysis, and obtain the target dish combination of three meals that meets the user's body and preferences.

[0112] Optionally, the historical nutrition intake data of the user can be queried by the user identity, and the embodiments of the present application are not limited.

[0113] Optionally, the historical nutrition intake data can include, but is not limited to, historical nutrition intake dish variety, historical nutrition intake dish nutritional value, and the embodiments of the present application are not limited.

[0114] It can be seen that the method for dish recommendation based on multi-dimensional user data described in the embodiments of the present application can perform first-level dish combination recommendation operation based on the attribute information and weight information of the user, and further perform second-level dish combination recommendation operation based on the dish variety and dish weight of the first-level dish combination, the physical health condition of the user, the historical nutrition intake data and the taste and food material preference data, to obtain the target dish combination of three meals that meets the body and preferences of the user, which is beneficial to improve the comprehensiveness, rationality and layer-by-layer progression of the target dish combination determination method of three meals, and further beneficial to improve the accuracy and reliability of the determined target dish combination of three meals, and beneficial to improve the determination efficiency and determination convenience of the target dish combination of three meals, thereby beneficial to improve the accuracy, efficiency and convenience of dish recommendation.

[0115] Embodiment two

[0116] Please refer to Figure 2 , Figure 2 is another flowchart of the method for dish recommendation based on multi-dimensional user data disclosed in the embodiments of the present application. Wherein, Figure 2 The method described can be applied to the device for dish recommendation based on multi-dimensional user data, wherein the device can include a server, wherein the server includes a local server or a cloud server, and the embodiments of the present application are not limited. As Figure 2 shown, the method for dish recommendation based on multi-dimensional user data includes the following operations:

[0117] 201, according to the image data of the user collected by the image collection device, analyze the attribute information of the user, and obtain the weight information of the user.

[0118] 202, according to the attribute information and weight information, determine the physical index data of the user.

[0119] 203, according to the physical index data, estimate the required nutrition value required to be taken by the user, and according to the required nutrition value, filter all dish combinations that meet the nutrition value requirement conditions of the user from the dish database determined in advance.

[0120] 204, according to the dish variety and dish weight of all dish combinations, the determined identity health condition of the user, determine the first recommended dish combination of three meals corresponding to the user.

[0121] Further optionally, the determining the first recommended three-meal dish combination corresponding to the user according to the determined identity health condition of the user, the dish category and the dish weight of all dish combinations can include:

[0122] determining a health problem existing in the user according to the determined identity health condition of the user, determining a corresponding food therapy cure scheme according to the health problem, and determining the first recommended three-meal dish combination corresponding to the user according to the food therapy cure scheme, the dish category and the dish weight of all dish combinations.

[0123] 205. determining the second recommended three-meal dish combination corresponding to the user according to the determined historical nutrition intake data of the user, the dish category and the dish weight of all dish combinations.

[0124] Further optionally, the determining the second recommended three-meal dish combination corresponding to the user according to the determined historical nutrition intake data of the user, the dish category and the dish weight of all dish combinations can include:

[0125] predicting possible nutritional content deficiency of the user in the current period according to the determined historical nutrition intake data of the user, and determining the second recommended three-meal dish combination corresponding to the user according to the possible nutritional content deficiency, the dish category and the dish weight of all dish combinations.

[0126] 206. determining the third recommended three-meal dish combination corresponding to the user according to the determined taste and material preference data of the user, the dish category and the dish weight of all dish combinations.

[0127] Further optionally, the determining the third recommended three-meal dish combination corresponding to the user according to the determined taste and material preference data of the user, the dish category and the dish weight of all dish combinations can include:

[0128] determining the taste and flavor information corresponding to each dish combination based on different dish weight units according to the dish category and the dish weight of all dish combinations, and determining the third recommended three-meal dish combination corresponding to the user according to the taste and flavor information, the dish category and the dish weight of all dish combinations, and the determined taste and material preference data of the user.

[0129] 207. determining the three-meal target dish combination meeting the body and preference of the user according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination.

[0130] In the embodiment of the application, for other descriptions of steps 201-207, please refer to the other detailed descriptions of steps 101-104 in embodiment one, and the embodiment of the application will not be repeated here.

[0131] It can be seen that the embodiment of the present application can perform first-level dish combination recommendation operation based on the attribute information and weight information of the user, further perform second-level dish combination recommendation operation based on the dish category and dish weight of the first-level dish combination, the physical health condition of the user, the historical nutrition intake data and the taste food material preference data, obtain the target dish combination of three meals that meets the body and preference of the user, and is beneficial to improve the comprehensiveness, rationality and layer-by-layer progression of the determination method of the target dish combination of three meals, and further beneficial to improve the accuracy and reliability of the determined target dish combination of three meals, and beneficial to improve the determination efficiency and determination convenience of the target dish combination of three meals, thereby beneficial to improve the accuracy, efficiency and convenience of dish recommendation; and can also match the corresponding recommended dish combination determination method of three meals according to the health condition of the user, the historical nutrition intake data and the taste food material preference data, and further determine the target dish combination of three meals that meets the body and preference of the user according to the first recommended dish combination of three meals, the second recommended dish combination of three meals and the third recommended dish combination of three meals, and beneficial to improve the pertinence, diversity and flexibility of the recommended dish combination determination method of three meals, and further beneficial to improve the comprehensiveness, accuracy and reliability of the determined recommended dish combination of three meals, thereby beneficial to improve the accuracy and reliability of the determined target dish combination of three meals.

[0132] In an optional embodiment, the determination of the target dish combination of three meals that meets the body and preference of the user according to the first recommended dish combination of three meals, the second recommended dish combination of three meals and the third recommended dish combination of three meals can include:

[0133] determining whether the first recommended dish combination of three meals, the second recommended dish combination of three meals and the third recommended dish combination of three meals meet the preset exclusive efficacy supply condition;

[0134] when it is determined that the first recommended dish combination of three meals, the second recommended dish combination of three meals and the third recommended dish combination of three meals meet the exclusive efficacy supply condition, performing corresponding comprehensive adjustment operation of the dish combination of three meals based on the reasonable intake level of the user according to the first recommended dish combination of three meals, the second recommended dish combination of three meals and the third recommended dish combination of three meals, and obtaining the target dish combination of three meals that meets the body and preference of the user;

[0135] When it is judged that the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination do not satisfy the exclusive efficacy supply condition, according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination, a first recommended three-meal dish satisfying a preset nutritional efficacy similarity condition and a second recommended three-meal dish not satisfying the preset nutritional efficacy similarity condition are screened out; a corresponding dish optimization comprehensive operation is performed on all the first recommended three-meal dishes and a corresponding dish combination and integration operation is performed on all the second recommended three-meal dishes, so as to obtain a three-meal target dish combination meeting the user's body and preference.

[0136] Optionally, the judgment of whether the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination satisfy the preset exclusive efficacy supply condition is exemplified as follows: whether the nutritional type / nutritional supply value / specific dish type / specific dish combination / specific dish amount / specific dish taste / specific dish cooking method and the like realized between the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination are consistent, if not, the preset exclusive efficacy supply condition is satisfied, if yes, the preset exclusive efficacy supply condition is not satisfied; further, it is exemplified as follows: the first recommended three-meal dish combination is fish and vegetable heart, the second recommended three-meal dish combination is pork and vegetable heart, if both are for protein supply and the corresponding protein supply conditions are the same (i.e., the exclusive efficacy supply condition is satisfied), then the minimum intake requirement and the maximum acceptable intake amount of the user are further combined to perform partial intake (corresponding to three-meal dish combination comprehensive adjustment operation); if both are for intake of multiple types of dishes (i.e., the exclusive efficacy supply condition is not satisfied), then different nutritional efficacy dishes are all taken or similar nutritional efficacy dishes are selectively taken, which is not limited by the embodiments of the present application.

[0137] Optionally, the corresponding dish optimization comprehensive operation performed on all the first recommended three-meal dishes is exemplified as follows: the dish combination with similar nutritional efficacy only needs to be selectively taken, which is not limited by the embodiments of the present application.

[0138] Optionally, the corresponding dish combination and integration operation performed on all the second recommended three-meal dishes is exemplified as follows: the dish combination with different nutritional efficacies can be all taken, which is not limited by the embodiments of the present application.

[0139] It can be seen that the optional embodiment can match the corresponding way of determining the three-meal target dish combination based on the recommended three-meal dish combination for meeting the exclusive function supply condition and not meeting the exclusive function supply condition respectively, which is beneficial to improve the comprehensiveness and rationality of the way of determining the three-meal target dish combination based on the recommended three-meal dish combination, and is beneficial to improve the pertinence, diversity and flexibility of the way of determining the three-meal target dish combination based on the recommended three-meal dish combination, and thus is beneficial to improve the accuracy and reliability of the determined three-meal target dish combination.

[0140] In another optional embodiment, the above-mentioned operation of performing corresponding three-meal dish combination comprehensive adjustment based on the user reasonable intake level according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination to obtain the three-meal target dish combination meeting the user's body and preferences can include:

[0141] According to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination, it is judged whether the user meets the preset abnormal intake condition;

[0142] When it is judged that the user does not meet the abnormal intake condition, corresponding direct integration operation is performed on the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination to obtain the three-meal target dish combination meeting the user's body and preferences;

[0143] When it is judged that the user meets the abnormal intake condition, the dish combination priority scheme corresponding to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination is determined; according to the dish combination priority scheme, corresponding screening comprehensive operation is performed on the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination to obtain the three-meal target dish combination meeting the user's body and preferences.

[0144] Optionally, the above-mentioned judging whether the user meets the preset abnormal intake condition is exemplified as follows: when the user's total intake of the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination appears overeating / nutrition overload, etc., it is determined that the preset abnormal intake condition is met, and further, the dish combination with greater demand is screened out according to the dish demand priority (i.e. screening comprehensive operation); when the user's total intake of the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination belongs to the normal meal intake of the user, etc., it is determined that the preset abnormal intake condition is not met, and further, the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination are all taken as the three-meal target dish combination of the user (i.e. direct integration), which is not limited by the embodiment of the present application.

[0145] Optionally, the meal combination priority scheme can be determined according to a degree of demand of the user for nutrition provided by each meal combination, can be determined according to a matching degree of different meal combinations and a current dining scene, or can be determined according to other factors that can reflect a demand of the user for different meal combinations, and the embodiments of the present application are not limited in this regard.

[0146] It can be seen that the optional embodiment can match corresponding three-meal meal combination comprehensive adjustment modes according to the satisfaction of the abnormal intake condition and the non-satisfaction of the abnormal intake condition, which is beneficial to improving the comprehensiveness and rationality of the three-meal meal combination comprehensive adjustment mode, is beneficial to improving the pertinence, diversity and flexibility of the three-meal meal combination comprehensive adjustment mode, and is further beneficial to improving the execution accuracy and execution reliability of the three-meal meal combination comprehensive adjustment operation, thereby being beneficial to improving the accuracy and reliability of the determined three-meal target meal combination.

[0147] In yet another optional embodiment, the above determining whether the user satisfies the preset abnormal intake condition according to the first recommended three-meal meal combination, the second recommended three-meal meal combination and the third recommended three-meal meal combination can include:

[0148] determining a comprehensive intake component corresponding to the user according to the first recommended three-meal meal combination, the second recommended three-meal meal combination and the third recommended three-meal meal combination;

[0149] determining whether the user satisfies a preset excessive intake condition according to the comprehensive intake component;

[0150] when it is determined that the user satisfies the excessive intake condition, determining that the user satisfies the preset abnormal intake condition;

[0151] when it is determined that the user does not satisfy the excessive intake condition, determining a comprehensive absorption nutrition corresponding to the user according to the first recommended three-meal meal combination, the second recommended three-meal meal combination and the third recommended three-meal meal combination;

[0152] determining whether the user satisfies a preset nutrition absorption excess condition according to the comprehensive absorption nutrition;

[0153] when it is determined that the user satisfies the nutrition absorption excess condition, determining that the user satisfies the preset abnormal intake condition;

[0154] when it is determined that the user does not satisfy the nutrition absorption excess condition, determining that the user does not satisfy the preset abnormal intake condition.

[0155] Optionally, the above judging whether the user meets the preset excessive intake condition may be exemplified as follows: in combination with the historical average intake component of the user or the predicted regular intake component of the user at the current stage (such as the current time, the current amount of exercise, etc.), it is judged whether the comprehensive intake component of the user will be overfull or exceed the regular intake component, if yes, it is determined that the user meets the preset abnormal intake condition, and if no, it is determined that the user does not meet the preset abnormal intake condition, which is not limited by the embodiments of the present application.

[0156] Optionally, the above judging whether the user meets the preset excessive intake condition may be exemplified as follows: in combination with the historical average intake component of the user or the predicted regular intake component of the user at the current stage (such as the current time, the current amount of exercise, etc.), it is judged whether the comprehensive intake component of the user will be overfull or exceed the regular intake component, if yes, it is determined that the user meets the preset abnormal intake condition, and if no, it is determined that the user does not meet the preset abnormal intake condition, which is not limited by the embodiments of the present application.

[0157] It can be seen that the optional embodiment can further determine the abnormal intake condition satisfaction result by the determined excessive intake condition satisfaction result and the nutrient absorption excess condition satisfaction result, which is beneficial to improve the comprehensiveness, rationality and layer-by-layer progression of the abnormal intake condition satisfaction result determination manner, and further beneficial to improve the accuracy and reliability of the determined abnormal intake condition satisfaction result, thereby beneficial to improve the execution accuracy, timeliness and reliability of the three-meal dish combination comprehensive adjustment operation triggered based on the abnormal intake condition satisfaction result.

[0158] In yet another optional embodiment, the above judging whether the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination meet the preset exclusive efficacy supply condition may include:

[0159] determining the first supply parameter that can be achieved by the first recommended three-meal dish combination, determining the second supply parameter that can be achieved by the second recommended three-meal dish combination, and determining the third supply parameter that can be achieved by the third recommended three-meal dish combination;

[0160] judging whether there is sub-parameter information meeting the preset similar condition in the first supply parameter, the second supply parameter and the third supply parameter;

[0161] when the judgment result is yes, it is determined that the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination meet the preset exclusive efficacy supply condition;

[0162] when the judgment result is no, it is determined that the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination do not meet the preset exclusive efficacy supply condition;

[0163] The first supply parameter, the second supply parameter and the third supply parameter each include nutrient type and content information and / or function type and effect information.

[0164] It can be seen that the optional embodiment can determine the exclusive efficacy supply condition satisfaction result according to the presence of similar sub-parameter information in the first supply parameter corresponding to the first recommended three-meal dish combination, the second supply parameter corresponding to the second recommended three-meal dish combination, and the third supply parameter corresponding to the third recommended three-meal dish combination, which is beneficial to improve the comprehensiveness and rationality of the exclusive efficacy supply condition satisfaction result determination method, and further beneficial to improve the accuracy and reliability of the determined exclusive efficacy supply condition satisfaction result, thereby beneficial to improve the execution accuracy, timeliness and reliability of the three-meal target dish combination determination operation triggered based on the exclusive efficacy supply condition satisfaction result.

[0165] In yet another optional embodiment, the above determining whether the user satisfies the preset excessive intake condition according to the comprehensive intake component can include:

[0166] determining whether the comprehensive intake component is greater than or equal to a preset comprehensive intake component threshold value;

[0167] when it is determined that the comprehensive intake component is greater than or equal to the comprehensive intake component threshold value, determining that the user satisfies the preset excessive intake condition;

[0168] when it is determined that the comprehensive intake component is less than the comprehensive intake component threshold value, determining that the user does not satisfy the preset excessive intake condition.

[0169] It can be seen that the optional embodiment can determine the excessive intake condition satisfaction result according to the size comparison of the comprehensive intake component and the corresponding threshold value, which is beneficial to improve the comprehensiveness and rationality of the excessive intake condition satisfaction result determination method, and further beneficial to improve the accuracy and reliability of the determined excessive intake condition satisfaction result.

[0170] In yet another optional embodiment, the above determining whether the user satisfies the preset excessive intake condition according to the comprehensive intake component can include:

[0171] determining whether the comprehensive intake component is greater than or equal to a preset comprehensive intake component threshold value;

[0172] when it is determined that the comprehensive intake component is greater than or equal to the comprehensive intake component threshold value, determining that the user satisfies the preset excessive intake condition;

[0173] when it is determined that the comprehensive intake component is less than the comprehensive intake component threshold value, determining that the user does not satisfy the preset excessive intake condition.

[0174] It can be seen that the optional embodiment can determine the nutrient absorption excess condition satisfaction result according to the comprehensive absorption of nutrients and the size comparison of the corresponding threshold, which is beneficial to improve the comprehensiveness and rationality of the nutrient absorption excess condition satisfaction result determination method, and further improve the accuracy and reliability of the determined nutrient absorption excess condition satisfaction result.

[0175] Embodiment three

[0176] Please refer to Figure 3 , Figure 3 is a structure schematic diagram of a device for dish recommendation based on multi-dimensional user data disclosed by the embodiment of the application. Wherein, Figure 3 The device described can include a server, wherein the server includes a local server or a cloud server, and the embodiment of the application does not limit. As Figure 3 shown, the device for dish recommendation based on multi-dimensional user data can include:

[0177] The information determination module 301 is configured to analyze the attribute information of the user according to the image data of the user collected by the image acquisition device, and obtain the body weight information of the user; and determine the body index data of the user according to the attribute information and the body weight information.

[0178] The first dish combination determination module 302 is configured to estimate the required nutrient value required to be ingested by the user according to the body index data, and select all dish combinations satisfying the nutrient value requirement of the user from the pre-determined dish database according to the required nutrient value.

[0179] The second dish combination determination module 303 is configured to input the dish types and dish weights of all dish combinations, the determined body health condition of the user, the historical nutrient intake data and the taste and material preference data into the trained and converged dish recommendation large language model for analysis, and obtain the target dish combination of three meals that meets the body and preference of the user.

[0180] It can be seen that the embodiment Figure 3 The device for dish recommendation based on multi-dimensional user data described can perform a first-level dish combination recommendation operation based on the attribute information and the body weight information of the user, and further perform a second-level dish combination recommendation operation based on the dish types and dish weights of the first-level dish combination, the body health condition of the user, the historical nutrient intake data and the taste and material preference data, to obtain the target dish combination of three meals that meets the body and preference of the user, which is beneficial to improve the comprehensiveness, rationality and layer-by-layer progression of the target dish combination of three meals determination method, and further improve the accuracy and reliability of the determined target dish combination of three meals, improve the determination efficiency and convenience of the target dish combination of three meals, and thus improve the accuracy, efficiency and convenience of dish recommendation.

[0181] In an optional embodiment, the second dish combination determination module 303 inputs the dish categories and dish weights of all dish combinations, the determined physical health condition of the user, the historical nutrition intake data and the taste food material preference data of the user into the trained convergent dish recommendation large language model for analysis to obtain a target three-meal dish combination that meets the user's physical condition and preferences. The specific way includes:

[0182] According to the dish categories and dish weights of all dish combinations and the determined physical health condition of the user, a first recommended three-meal dish combination corresponding to the user is determined;

[0183] According to the dish categories and dish weights of all dish combinations and the determined historical nutrition intake data of the user, a second recommended three-meal dish combination corresponding to the user is determined;

[0184] According to the dish categories and dish weights of all dish combinations and the determined taste food material preference data of the user, a third recommended three-meal dish combination corresponding to the user is determined;

[0185] According to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination, a target three-meal dish combination that meets the user's physical condition and preferences is determined.

[0186] It can be seen that the implementation Figure 3 The described device can also match the corresponding recommended three-meal dish combination determination method according to the physical health condition, historical nutrition intake data and taste food material preference data of the user, and then determine a target three-meal dish combination that meets the user's physical condition and preferences according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination. This is beneficial to improve the pertinence, diversity and flexibility of the recommended three-meal dish combination determination method, and thus beneficial to improve the comprehensiveness, accuracy and reliability of the determined recommended three-meal dish combination, thereby beneficial to improve the accuracy and reliability of the determined target three-meal dish combination.

[0187] In another optional embodiment, the second dish combination determination module 303 determines a target three-meal dish combination that meets the user's physical condition and preferences according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination. The specific way includes:

[0188] determining whether the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination meet the preset exclusive efficacy supply condition;

[0189] When it is judged that the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination satisfy the exclusive efficacy supply condition, a corresponding three-meal dish combination comprehensive adjustment operation is performed based on the user reasonable intake level according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination, and a three-meal target dish combination conforming to the user body and preference is obtained;

[0190] When it is judged that the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination do not satisfy the exclusive efficacy supply condition, a first recommended three-meal dish satisfying a preset nutritional efficacy similarity condition and a second recommended three-meal dish not satisfying the preset nutritional efficacy similarity condition are screened out according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination; a corresponding dish optimization comprehensive operation is performed on all the first recommended three-meal dishes and a corresponding dish merging and integration operation is performed on all the second recommended three-meal dishes, and a three-meal target dish combination conforming to the user body and preference is obtained.

[0191] It can be seen that the embodiment Figure 3 The described device can also match a corresponding way of determining a three-meal target dish combination based on a recommended three-meal dish combination for the exclusive efficacy supply condition and the non-exclusive efficacy supply condition respectively, which is beneficial to improve the comprehensiveness and rationality of the way of determining a three-meal target dish combination based on a recommended three-meal dish combination, and is beneficial to improve the pertinence, diversity and flexibility of the way of determining a three-meal target dish combination based on a recommended three-meal dish combination, and thus is beneficial to improve the accuracy and reliability of the determined three-meal target dish combination.

[0192] In yet another optional embodiment, the second dish combination determination module 303 performs a corresponding three-meal dish combination comprehensive adjustment operation based on the user reasonable intake level according to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination, and the way of obtaining a three-meal target dish combination conforming to the user body and preference specifically includes:

[0193] According to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination, it is judged whether the user satisfies a preset abnormal intake condition;

[0194] When it is judged that the user does not satisfy the abnormal intake condition, a corresponding direct integration operation is performed on the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination, and a three-meal target dish combination conforming to the user body and preference is obtained;

[0195] When it is judged that the user meets the abnormal intake condition, a meal combination priority scheme corresponding to the first recommended three-meal meal combination, the second recommended three-meal meal combination and the third recommended three-meal meal combination is determined; and according to the meal combination priority scheme, corresponding screening and comprehensive operations are performed on the first recommended three-meal meal combination, the second recommended three-meal meal combination and the third recommended three-meal meal combination, so as to obtain a three-meal target meal combination meeting the user's body and preferences.

[0196] It can be seen that, in the implementation Figure 3 The described device can also match corresponding three-meal meal combination comprehensive adjustment modes for users meeting the abnormal intake condition and users not meeting the abnormal intake condition, respectively, which is beneficial to improving the comprehensiveness and rationality of the three-meal meal combination comprehensive adjustment mode, and is beneficial to improving the pertinence, diversity and flexibility of the three-meal meal combination comprehensive adjustment mode, and thus is beneficial to improving the execution accuracy and execution reliability of the three-meal meal combination comprehensive adjustment operation, thereby being beneficial to improving the accuracy and reliability of the determined three-meal target meal combination.

[0197] In yet another optional embodiment, the second meal combination determination module 303 determines whether the user meets the preset abnormal intake condition according to the first recommended three-meal meal combination, the second recommended three-meal meal combination and the third recommended three-meal meal combination in the following manner:

[0198] According to the first recommended three-meal meal combination, the second recommended three-meal meal combination and the third recommended three-meal meal combination, a comprehensive intake component corresponding to the user is determined;

[0199] According to the comprehensive intake component, it is judged whether the user meets a preset excessive intake condition;

[0200] When it is judged that the user meets the excessive intake condition, it is determined that the user meets the preset abnormal intake condition;

[0201] When it is judged that the user does not meet the excessive intake condition, according to the first recommended three-meal meal combination, the second recommended three-meal meal combination and the third recommended three-meal meal combination, a comprehensive absorption nutrient corresponding to the user is determined;

[0202] According to the comprehensive absorption nutrient, it is judged whether the user meets a preset nutrient absorption excess condition;

[0203] When it is judged that the user meets the nutrient absorption excess condition, it is determined that the user meets the preset abnormal intake condition;

[0204] When it is judged that the user does not meet the nutrient absorption excess condition, it is determined that the user does not meet the preset abnormal intake condition.

[0205] It can be seen that, in the implementation Figure 3The described device can also further determine the abnormal intake condition satisfaction results through the determined excessive intake condition satisfaction results and excess nutrient absorption condition satisfaction results, which is conducive to improving the comprehensiveness, rationality and progressiveness of the abnormal intake condition satisfaction determination method, and thus is conducive to improving the accuracy and reliability of the determined abnormal intake condition satisfaction results, thereby helping to improve the accuracy, timeliness and reliability of the execution of the comprehensive adjustment operation of the three meals dish combination triggered by the abnormal intake condition satisfaction results.

[0206] In another optional embodiment, the second dish combination determination module 303 determines whether the first recommended three-meal dish combination, the second recommended three-meal dish combination, and the third recommended three-meal dish combination meet the preset exclusive efficacy supply conditions in the following manner:

[0207] Determining a first achievable supply parameter based on the first recommended three-meal dish combination, determining a second achievable supply parameter based on the second recommended three-meal dish combination, and determining a third achievable supply parameter based on the third recommended three-meal dish combination;

[0208] Determine whether there is sub-parameter information that meets a preset similarity condition in the first supply parameter, the second supply parameter, and the third supply parameter;

[0209] When the judgment result is yes, it is determined that the first recommended three-meal dish combination, the second recommended three-meal dish combination, and the third recommended three-meal dish combination meet the preset exclusive efficacy supply conditions;

[0210] When the judgment result is no, it is determined that the first recommended three-meal dish combination, the second recommended three-meal dish combination, and the third recommended three-meal dish combination do not meet the preset exclusive efficacy supply conditions;

[0211] The first supply parameter, the second supply parameter and the third supply parameter all include nutrient type and content information and / or function type and effect information.

[0212] It can be seen that implementation Figure 3 The described device can also determine the exclusive efficacy supply condition satisfaction result based on the existence of similar sub-parameter information in the first supply parameter corresponding to the first recommended three-meal dish combination, the second supply parameter corresponding to the second recommended three-meal dish combination, and the third supply parameter corresponding to the third recommended three-meal dish combination, which is conducive to improving the comprehensiveness and rationality of the method for determining the exclusive efficacy supply condition satisfaction result, and thus is conducive to improving the accuracy and reliability of the determined exclusive efficacy supply condition satisfaction result, thereby helping to improve the execution accuracy, timeliness and reliability of the three-meal target dish combination determination operation triggered by the exclusive efficacy supply condition satisfaction result.

[0213] In still another optional embodiment, the second dish combination determining module 303 determines whether the user satisfies the preset excessive intake condition according to the comprehensive intake component in the following manner:

[0214] determining whether the comprehensive intake component is greater than or equal to a preset comprehensive intake component threshold value;

[0215] when it is determined that the comprehensive intake component is greater than or equal to the comprehensive intake component threshold value, determining that the user satisfies the preset excessive intake condition;

[0216] when it is determined that the comprehensive intake component is less than the comprehensive intake component threshold value, determining that the user does not satisfy the preset excessive intake condition.

[0217] It can be seen that the apparatus described in the embodiment Figure 3 The apparatus described can also determine the excessive intake condition satisfaction result according to the size comparison between the comprehensive intake component and the corresponding threshold value, which is conducive to improving the comprehensiveness and rationality of the excessive intake condition satisfaction result determination manner, and further conducive to improving the accuracy and reliability of the determined excessive intake condition satisfaction result.

[0218] In still another optional embodiment, the second dish combination determining module 303 determines whether the user satisfies the preset excessive intake condition according to the comprehensive intake component in the following manner:

[0219] determining whether the comprehensive intake component is greater than or equal to a preset comprehensive intake component threshold value;

[0220] when it is determined that the comprehensive intake component is greater than or equal to the comprehensive intake component threshold value, determining that the user satisfies the preset excessive intake condition;

[0221] when it is determined that the comprehensive intake component is less than the comprehensive intake component threshold value, determining that the user does not satisfy the preset excessive intake condition.

[0222] It can be seen that the apparatus described in the embodiment Figure 4 The apparatus described can also determine the excessive intake condition satisfaction result according to the size comparison between the comprehensive intake component and the corresponding threshold value, which is conducive to improving the comprehensiveness and rationality of the excessive intake condition satisfaction result determination manner, and further conducive to improving the accuracy and reliability of the determined excessive intake condition satisfaction result.

[0223] Embodiment Four

[0224] Please refer to Figure 4 , Figure 4 is another structure schematic diagram of the apparatus for dish recommendation based on multi-dimensional user data disclosed in the embodiment of the application. In the apparatus, Figure 4 The apparatus described can include a server, wherein the server includes a local server or a cloud server, and the embodiment of the application does not make any limitation. For example,​ As shown in the figure, the apparatus can include:

[0225] a memory 401 storing executable program code;

[0226] a processor 402 coupled with the memory 401;

[0227] Further, an input interface 403 and an output interface 404 coupled with the processor 402 can also be included;

[0228] The processor 402 invokes the executable program code stored in the memory 401 to execute the steps in the method for dish recommendation based on multi-dimensional user data described in Embodiment One or Embodiment Two.

[0229] Embodiment Five

[0230] The embodiments of the present application disclose a computer storage medium storing a computer program for electronic data exchange, wherein the computer program causes a computer to execute the steps in the method for dish recommendation based on multi-dimensional user data described in Embodiment One or Embodiment Two.

[0231] Embodiment Six

[0232] The embodiments of the present application disclose a computer program product comprising a non-transitory computer readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute the steps in the method for dish recommendation based on multi-dimensional user data described in Embodiment One or Embodiment Two.

[0233] The apparatus embodiments described above are only schematic, wherein the modules illustrated as separate components can or can not be physically separate, and the components illustrated as modules can or can not be physical modules, i.e., can be located in one place, or can be distributed on multiple network modules. Part or all of the modules can be selected according to actual needs to achieve the purpose of the present embodiment scheme. Those skilled in the art can understand and implement without creative labor.

[0234] Those skilled in the art can clearly understand the implementation of the various embodiments by means of software and necessary general hardware platforms through the above specific description of the embodiments, and of course, the embodiments can also be implemented by hardware. Based on such understanding, the above technical solutions, essentially or in other words, the part of the prior art that makes a contribution, can be embodied in the form of a software product. The computer software product can be stored in a computer readable storage medium, and the storage medium includes 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 electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disk storage, a magnetic disk storage, a magnetic tape storage, or any other computer readable medium that can be used to carry or store data.

[0235] Finally, it should be noted that: the method and device for dish recommendation based on multi-dimensional user data disclosed by the embodiments of the present application are only the preferred embodiments of the present application, and are used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: the technical solutions recorded in the foregoing embodiments can still be modified, or some technical features can be replaced by equivalents; and these modifications or replacements do not make the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for dish recommendation based on multi-dimensional user data, characterized in that: The method comprises: Analyzing attribute information of the user based on image data of the user captured by the image capture device, and obtaining weight information of the user; Determining the user's physical indicator data based on the attribute information and the weight information; estimating the required nutritional value of the user's intake based on the physical indicator data, and screening all dish combinations that meet the user's nutritional value requirements from a predetermined dish database based on the required nutritional value; The types and weights of all the dish combinations, the determined physical health condition of the user, historical nutritional intake data and taste and ingredient preference data are input into the trained and converged dish recommendation language model for analysis to obtain the target dish combinations for three meals a day that are in line with the user's physical condition and preferences.

2. The method for dish recommendation based on multi-dimensional user data according to claim 1, characterized in that: The types and weights of all the dish combinations, the determined health status of the user, historical nutritional intake data, and taste and ingredient preference data are input into the trained and converged dish recommendation language model for analysis to obtain target meal combinations that meet the user's health and preferences, including: Determining a first recommended three-meal dish combination corresponding to the user based on the dish types and dish weights of all the dish combinations and the determined identity and health status of the user; Determining a second recommended three-meal dish combination corresponding to the user based on the dish types and dish weights of all the dish combinations and the determined historical nutritional intake data of the user; Determining a third recommended three-meal dish combination corresponding to the user based on the dish types and dish weights of all the dish combinations and the determined taste and ingredient preference data of the user; Based on the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination, a three-meal target dish combination that suits the user's physical condition and preferences is determined.

3. The method for recommending dishes based on multi-dimensional user data according to claim 2, characterized in that: The determining, based on the first recommended three-meal dish combination, the second recommended three-meal dish combination, and the third recommended three-meal dish combination, of a target three-meal dish combination that meets the user's physical condition and preferences includes: Determining whether the first recommended three-meal dish combination, the second recommended three-meal dish combination, and the third recommended three-meal dish combination meet preset exclusive efficacy supply conditions; When it is determined that the exclusive efficacy supply condition is met, a corresponding three-meal dish combination comprehensive adjustment operation is performed based on the first recommended three-meal dish combination, the second recommended three-meal dish combination, and the third recommended three-meal dish combination, based on the user's reasonable intake level, to obtain a three-meal target dish combination that meets the user's physical condition and preferences; When it is determined that the exclusive efficacy supply conditions are not met, the first recommended three meals dishes that meet the preset nutritional efficacy similarity conditions and the second recommended three meals dishes that do not meet the preset nutritional efficacy similarity conditions are screened out based on the first recommended three meals dishes combination, the second recommended three meals dishes combination and the third recommended three meals dishes combination; the corresponding dish selection and comprehensive operation is performed on all the first recommended three meals dishes and the corresponding dish merging and integration operation is performed on all the second recommended three meals dishes to obtain the three meals target dish combination that meets the user's physical condition and preferences.

4. The method for dish recommendation based on multi-dimensional user data according to claim 3, characterized in that: The step of performing corresponding comprehensive adjustment operations on the three-meal dish combinations based on the first recommended three-meal dish combination, the second recommended three-meal dish combination, and the third recommended three-meal dish combination based on the user's reasonable intake level to obtain a target three-meal dish combination that meets the user's physical condition and preferences includes: determining whether the user meets a preset abnormal intake condition based on the first recommended three-meal dish combination, the second recommended three-meal dish combination, and the third recommended three-meal dish combination; When it is determined that the user does not meet the abnormal intake condition, performing corresponding direct integration operations on the first recommended three-meal dish combination, the second recommended three-meal dish combination, and the third recommended three-meal dish combination to obtain a three-meal target dish combination that meets the user's physical condition and preferences; When it is determined that the user meets the abnormal intake condition, the dish combination priority scheme corresponding to the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination is determined; according to the dish combination priority scheme, corresponding screening and comprehensive operations are performed on the first recommended three-meal dish combination, the second recommended three-meal dish combination and the third recommended three-meal dish combination to obtain the three-meal target dish combination that meets the user's physical condition and preferences.

5. The method for dish recommendation based on multi-dimensional user data according to claim 4, characterized in that: The determining, based on the first recommended three-meal dish combination, the second recommended three-meal dish combination, and the third recommended three-meal dish combination, whether the user meets a preset abnormal intake condition includes: determining a corresponding comprehensive intake amount for the user based on the first recommended three-meal dish combination, the second recommended three-meal dish combination, and the third recommended three-meal dish combination; Determining whether the user meets a preset excessive intake condition based on the comprehensive intake amount; When it is determined that the user meets the excessive intake condition, determining that the user meets a preset abnormal intake condition; When it is determined that the user does not meet the excessive intake condition, determining the comprehensive nutritional absorption corresponding to the user based on the first recommended three-meal dish combination, the second recommended three-meal dish combination, and the third recommended three-meal dish combination; According to the comprehensive nutrition absorption, determining whether the user meets a preset excess nutrition absorption condition; When it is determined that the user meets the excess nutrient absorption condition, determining that the user meets a preset abnormal intake condition; When it is determined that the user does not meet the excess nutrient absorption condition, it is determined that the user does not meet the preset abnormal intake condition.

6. The method for dish recommendation based on multi-dimensional user data according to claim 3, characterized in that: The determining whether the first recommended three-meal dish combination, the second recommended three-meal dish combination, and the third recommended three-meal dish combination meet preset exclusive efficacy supply conditions includes: Determining a first achievable supply parameter based on the first recommended three-meal dish combination, determining a second achievable supply parameter based on the second recommended three-meal dish combination, and determining a third achievable supply parameter based on the third recommended three-meal dish combination; Determining whether there is sub-parameter information that meets a preset similarity condition among the first supply parameter, the second supply parameter, and the third supply parameter; When the judgment result is yes, it is determined that the first recommended three-meal dish combination, the second recommended three-meal dish combination, and the third recommended three-meal dish combination meet the preset exclusive efficacy supply conditions; When the judgment result is no, it is determined that the first recommended three-meal dish combination, the second recommended three-meal dish combination, and the third recommended three-meal dish combination do not meet the preset exclusive efficacy supply conditions; The first supply parameter, the second supply parameter and the third supply parameter all include nutritional type and content information and / or functional type and effect information.

7. The method for dish recommendation based on multi-dimensional user data according to claim 5, characterized in that: The determining, based on the comprehensive intake amount, whether the user meets a preset excessive intake condition includes: Determining whether the comprehensive intake amount is greater than or equal to a preset comprehensive intake amount threshold; When it is determined that the comprehensive intake amount is greater than or equal to the comprehensive intake amount threshold, determining that the user meets a preset excessive intake condition; When it is determined that the comprehensive intake amount is less than the comprehensive intake amount threshold, determining that the user does not meet the preset excessive intake condition; Furthermore, judging whether the user meets a preset excess nutrition absorption condition based on the comprehensive nutrition absorption includes: Determining whether the comprehensive absorption nutrition is greater than or equal to a preset comprehensive absorption nutrition threshold; When it is determined that the comprehensive absorbed nutrition is greater than or equal to the comprehensive absorbed nutrition threshold, determining that the user meets a preset excess nutrition absorption condition; When it is determined that the comprehensive absorbed nutrition is less than the comprehensive absorbed nutrition threshold, it is determined that the user does not meet the preset excess nutrition absorption condition.

8. A device for recommending dishes based on multi-dimensional user data, characterized in that: The device comprises: an information determination module, configured to analyze attribute information of the user based on image data of the user captured by the image capture device, and obtain weight information of the user; and determine physical index data of the user based on the attribute information and the weight information; a first dish combination determination module, configured to estimate the required nutritional value of the user's intake based on the physical indicator data, and screen all dish combinations that meet the user's nutritional value requirements from a predetermined dish database based on the required nutritional value; The second dish combination determination module is used to input the types and weights of all the dish combinations, the determined physical health status of the user, the historical nutritional intake data and the taste and ingredient preference data into the trained and converged dish recommendation large language model for analysis, so as to obtain the target dish combinations for three meals a day that are in line with the user's physical condition and preferences.

9. A device for recommending dishes based on multi-dimensional user data, 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 method for recommending dishes based on multi-dimensional user data 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 method for recommending dishes based on multi-dimensional user data as described in any one of claims 1 to 7.

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