CN111540438B - Resource allocation method and device, electronic equipment and storage medium - Google Patents

Resource allocation method and device, electronic equipment and storage medium Download PDF

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CN111540438B
CN111540438B CN202010322749.3A CN202010322749A CN111540438B CN 111540438 B CN111540438 B CN 111540438B CN 202010322749 A CN202010322749 A CN 202010322749A CN 111540438 B CN111540438 B CN 111540438B
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user
food
target
information
heat
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CN111540438A (en
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翁政翔
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Douyin Vision Co Ltd
Douyin Vision Beijing Co Ltd
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Beijing ByteDance Network Technology Co Ltd
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets

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Abstract

The disclosure provides a resource allocation method, a device, an electronic device and a storage medium, wherein the resource allocation method comprises the following steps: acquiring a target picture, identifying target food contained in the target picture, and determining heat information of the target food; acquiring heat data information corresponding to a user, wherein the heat data information is determined based on characteristic information of the user and/or target event data corresponding to the user; and allocating resources for the user based on the heat information of the target food and the heat data information corresponding to the user.

Description

Resource allocation method and device, electronic equipment and storage medium
Technical Field
The disclosure relates to the technical field of internet, and in particular relates to a resource allocation method, a device, electronic equipment and a storage medium.
Background
With the increase of living standard, more and more people begin to pay attention to healthy diet and healthy life, and pay attention to food caloric intake while paying attention to exercise, so healthy diet and reasonable fitness have become a part of daily life.
In order to develop good eating habits, users generally rely on the help of professionals such as nutritionists to know the heat of daily food, and the process is complicated and has high labor cost.
Disclosure of Invention
The embodiment of the disclosure at least provides a resource allocation scheme to reduce labor cost and automatically allocate resources for users.
In a first aspect, an embodiment of the present disclosure provides a resource allocation method, including:
acquiring a target picture, identifying target food contained in the target picture, and determining heat information of the target food;
acquiring heat data information corresponding to a user, wherein the heat data information is determined based on characteristic information of the user and/or target event data corresponding to the user;
and distributing resources for the user based on the heat information of the target food and the heat data information corresponding to the user.
In one possible embodiment, the capturing a target picture, identifying a target food product contained in the target picture, and determining heat information of the target food product includes:
identifying foods to be detected contained in the target picture to obtain at least one candidate food contained in the target picture and attribute information of each candidate food;
the caloric information of the target food is determined based on attribute information of each candidate food and a probability that the user selects each food at the current time period predicted by the characteristic information of the user.
In a possible implementation manner, the identifying the food to be detected included in the target picture to obtain at least one candidate food and attribute information of each candidate food included in the target picture includes:
identifying foods to be detected in the target picture to obtain at least one candidate food contained in the target picture, and food type and specification information of each candidate food;
the food type and specification information corresponding to each candidate food is used as attribute information of the candidate food.
In one possible embodiment, the determining the caloric information of the target food item based on the attribute information of each candidate food item and the probability of the user selecting each food item in the current time period predicted by the feature information of the user includes:
determining a target food contained in the target picture among the at least one candidate food based on a food type of each candidate food and a probability that the user selects each food at a current time period predicted by the feature information of the user;
based on the food type and specification information of the target food, caloric information of the target food is determined.
In one possible embodiment, the thermal data information corresponding to the user is determined in the following manner:
determining a heat recommendation range for the user in a current time period based on the characteristic information of the user and the target event data corresponding to the user;
and determining the caloric data information corresponding to the user based on the caloric recommendation range and the caloric target data set by the user and ingested at the time.
In one possible implementation manner, the allocating resources for the user based on the caloric information corresponding to the target food and the caloric data information corresponding to the user includes:
determining whether the caloric target data which is set by the user and is ingested at the time is matched with the caloric recommended range;
when the heat target data of the current ingestion set by the user is matched with the heat recommended range, determining difference information between heat information of target food contained in the target picture and the heat target data of the current ingestion set by the user;
allocating resources matched with the difference information to the user based on the difference information;
and when the heat target data which is set by the user and is ingested at the time is not matched with the heat recommended range, configuring preset resources for the user.
In a second aspect, an embodiment of the present disclosure provides a resource allocation apparatus, including:
the first acquisition module is used for acquiring a target picture, identifying target food contained in the target picture and determining heat information of the target food;
the second acquisition module is used for acquiring heat data information corresponding to a user, wherein the heat data information is determined based on the characteristic information of the user and/or the target event data corresponding to the user;
and the resource allocation module is used for allocating resources for the user based on the heat information of the target food and the heat data information corresponding to the user.
In one possible embodiment, the first obtaining module, when configured to obtain a target picture, identify a target food product contained in the target picture, and determine heat information of the target food product, includes:
identifying foods to be detected contained in the target picture to obtain at least one candidate food contained in the target picture and attribute information of each candidate food;
the caloric information of the target food is determined based on attribute information of each candidate food and a probability that the user selects each food at the current time period predicted by the characteristic information of the user.
In one possible implementation manner, the first obtaining module, when used for identifying the food to be detected included in the target picture, obtains at least one candidate food and attribute information of each candidate food included in the target picture, includes:
identifying foods to be detected in the target picture to obtain at least one candidate food contained in the target picture, and food type and specification information of each candidate food;
the food type and specification information corresponding to each candidate food is used as attribute information of the candidate food.
In one possible embodiment, the first obtaining module, when determining the caloric information of the target food item based on the attribute information of each candidate food item and the probability of the user selecting each food item in the current time period predicted by the feature information of the user, includes:
determining a target food contained in the target picture among the at least one candidate food based on a food type of each candidate food and a probability that the user selects each food at a current time period predicted by the feature information of the user;
Based on the food type and specification information of the target food, caloric information of the target food is determined.
In one possible implementation manner, the second acquisition module determines the thermal data information corresponding to the user in the following manner:
determining a heat recommendation range for the user in a current time period based on the characteristic information of the user and the target event data corresponding to the user;
and determining the caloric data information corresponding to the user based on the caloric recommendation range and the caloric target data set by the user and ingested at the time.
In one possible implementation manner, the resource allocation module, when configured to allocate resources for the user based on the caloric information corresponding to the target food and the caloric data information corresponding to the user, includes:
determining whether the caloric target data which is set by the user and is ingested at the time is matched with the caloric recommended range;
when the heat target data of the current ingestion set by the user is matched with the heat recommended range, determining difference information between heat information of target food contained in the target picture and the heat target data of the current ingestion set by the user;
Allocating resources matched with the difference information to the user based on the difference information;
and when the heat target data which is set by the user and is ingested at the time is not matched with the heat recommended range, configuring preset resources for the user.
In a third aspect, an embodiment of the present disclosure provides an electronic device, including: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory in communication over the bus when the electronic device is running, the machine-readable instructions when executed by the processor performing the steps of the resource allocation method according to the first aspect.
In a fourth aspect, embodiments of the present disclosure provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the resource allocation method according to the first aspect.
According to the resource allocation method provided by the embodiment of the disclosure, after the target picture is obtained, target food contained in the target picture can be identified, heat information of the target food is determined, then heat data information corresponding to a user is obtained, the heat data information can be determined based on characteristic information of the user and/or target event data corresponding to the user, for example, the characteristic information of the user can be information of weight, height and the like which are authorized to be disclosed by the user, the target event data corresponding to the user can comprise data representing events such as weight loss, fat reduction and muscle increase, and the like, so that after the heat information of the target food and the heat data information corresponding to the user are obtained, resources can be allocated to the user according to the heat information corresponding to the target food and the heat data information corresponding to the user, namely, the resource allocation scheme with low cost and automation for the user can be provided by the embodiment of the disclosure.
The foregoing objects, features and advantages of the disclosure will be more readily apparent from the following detailed description of the preferred embodiments taken in conjunction with the accompanying drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings required for the embodiments are briefly described below, which are incorporated in and constitute a part of the specification, these drawings showing embodiments consistent with the present disclosure and together with the description serve to illustrate the technical solutions of the present disclosure. It is to be understood that the following drawings illustrate only certain embodiments of the present disclosure and are therefore not to be considered limiting of its scope, for the person of ordinary skill in the art may admit to other equally relevant drawings without inventive effort.
FIG. 1 illustrates a flow chart of a resource allocation method provided by an embodiment of the present disclosure;
FIG. 2 illustrates a flow chart of a method of determining caloric information of a target food product provided by an embodiment of the present disclosure;
FIG. 3 illustrates a flow chart of a method for determining heat data information corresponding to a user provided by an embodiment of the present disclosure;
FIG. 4 illustrates a flow chart of a particular resource allocation method provided by embodiments of the present disclosure;
FIG. 5 is a schematic diagram of a resource allocation apparatus according to an embodiment of the disclosure;
fig. 6 shows a schematic diagram of an electronic device provided by an embodiment of the disclosure.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present disclosure more apparent, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is apparent that the described embodiments are only some embodiments of the present disclosure, but not all embodiments. The components of the embodiments of the present disclosure, which are generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present disclosure provided in the accompanying drawings is not intended to limit the scope of the disclosure, as claimed, but is merely representative of selected embodiments of the disclosure. All other embodiments, which can be made by those skilled in the art based on the embodiments of this disclosure without making any inventive effort, are intended to be within the scope of this disclosure.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures.
With the increasing level of living, people are gradually focusing on diet health, such as by relying on professionals such as nutritionists to help know the calories of food consumed daily, which is tedious and costly to human.
The term "and/or" is used herein to describe only one relationship, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist together, and B exists alone. In addition, the term "at least one" herein means any one of a plurality or any combination of at least two of a plurality, for example, including at least one of A, B, C, and may mean including any one or more elements selected from the group consisting of A, B and C.
Based on the above-mentioned research, the present disclosure provides a resource allocation method, after a target picture is obtained, a target food contained in the target picture may be identified, and heat information of the target food may be determined, and then heat data information corresponding to a user may be obtained, where the heat data information may be determined based on feature information of the user and/or target event data corresponding to the user, for example, the feature information of the user may be information such as weight, height, etc. that the user authorizes disclosure, and the target event data corresponding to the user may include data representing events such as weight loss, fat loss, muscle increase, etc., so after the heat information of the target food and the heat data information corresponding to the user are obtained, resources may be allocated to the user according to the heat information corresponding to the target food and the heat data information corresponding to the user, that is, the embodiment of the present disclosure may provide a scheme with low cost and automatization for the user to perform resource allocation.
For the sake of understanding the present embodiment, first, a detailed description will be given of a resource allocation method disclosed in an embodiment of the present disclosure, where an execution body of the resource allocation method provided in the embodiment of the present disclosure is generally a computer device with a certain computing capability, where the computer device includes, for example: the terminal device or server or other processing device, the terminal device may be a User Equipment (UE), a mobile device, etc. In some possible implementations, the resource allocation method may be implemented by way of a processor invoking computer readable instructions stored in a memory.
In addition, the feature information of the user, a large amount of data acquired based on big data statistics, portrait information of the user, and historical behavior data of the user according to the following embodiments of the present disclosure are all information or data authorized by the user.
Referring to fig. 1, a flowchart of a resource allocation method according to an embodiment of the present disclosure may be applied to a client, where the resource allocation method includes steps S101 to S103, where:
s101, acquiring a target picture, identifying target food contained in the target picture, and determining heat information of the target food.
The target picture can be obtained by photographing food to be eaten by a user at the client side, and before each eating, the user can photograph the food to be eaten by the client side to obtain the target picture; alternatively, the user may directly upload a target picture associated with the food to be consumed, for example, upload a pre-taken picture including the food to be consumed as the target picture to the client.
The Client (Client) or referred to as Client herein refers to a program corresponding to a server and providing a local service for a Client, and is generally installed on a common Client, and needs to cooperate with the server to operate, for example, some application program App.
After the target food contained in the target picture is identified, the thermal information of the target food may be further determined based on the identified target food, for example, the thermal information of the target food may be determined based on the food type and specification information of the target food, which will be described in detail later.
S102, acquiring heat data information corresponding to the user, wherein the heat data information is determined based on the characteristic information of the user and/or the target event data corresponding to the user.
Here, the acquiring of the thermal data information corresponding to the user may be that, after receiving the target picture, determining the thermal data information corresponding to the user based on the feature information of the user and/or the target event data corresponding to the user is started, or may be that the thermal data information determined in advance based on the feature information of the user and/or the target event data corresponding to the user is not limited herein, specifically when the thermal data information corresponding to the user is acquired.
The caloric data information may include a caloric recommendation range corresponding to the user determined by the client, that is, a caloric range that can be eaten by the user in a current time period is recommended to the user, for example, a caloric range that can be eaten by the user in the current time period determined based on the characteristic information of the user and/or the target event data corresponding to the user, and in addition, the caloric data range corresponding to the user may also include caloric target data set by the user and ingested by the user at the time.
Specifically, the characteristic information of the user can comprise user portrait information authorized by the user, historical behavior data authorized by the user and height and weight information authorized by the user, wherein the user portrait information can comprise characteristic information such as gender, age bracket, place and the like of the user, and the historical behavior data of the user can comprise historical diet records, heat target information set by the user and the like; the target event data corresponding to the user may include data set by the user and used for representing a target physical state of the user, for example, may include data representing a weight increasing state, a weight reducing state and a holding state, and may also include data representing a current physical state of the user, for example, data representing that the current physical state of the user is a pregnancy, a pregnancy preparation period or a lactation period, and the like.
In this way, based on the characteristic information of the user, such as the height, weight, age and sex of the user, the body quality index of the user can be determined, and then the heat recommendation range corresponding to the user in the current time period can be recommended to the user by combining the historical diet record of the user; or, the characteristic information of the user and the corresponding target event data of the user can be combined, for example, the target physical state set by the user is a weight increasing state, and the corresponding heat recommendation range of the user in the current time period can be recommended to the user together; or, the heat recommendation range corresponding to the user in the current time period can be recommended to the user only through the target event data corresponding to the user, such as that the target physical state set by the user is the weight increasing state and the current physical state of the user is the pregnancy period.
S103, distributing resources for the user based on the heat information of the target food and the heat data information corresponding to the user.
As can be seen from the foregoing, the heat data information corresponding to the user may include the heat recommended range corresponding to the user and/or the heat target data set by the user and taken this time, so after obtaining the heat information of the target food, resources may be allocated to the user based on the heat information of the target food and the heat data information corresponding to the user, for example, when determining that the heat information corresponding to the target food matches the heat data information corresponding to the user, a red packet, a coupon or other excitation resources for exciting the user, such as a fitness video, a fitness article, a fitness recipe, etc., which are used to keep healthy by the user, specifically how to allocate resources to the user based on the heat information of the target food and how to allocate resources to the user will be described in detail later.
According to the resource allocation method provided by S101-S103, after the target picture is obtained, the target food contained in the target picture can be identified, the heat information of the target food is determined, then the heat data information corresponding to the user is obtained, the heat data information can be determined based on the characteristic information of the user and/or the target event data corresponding to the user, for example, the characteristic information of the user can be information of weight, height and the like which are authorized to be disclosed by the user, the target event data corresponding to the user can comprise data representing events such as weight loss, fat loss, muscle increase and the like, and therefore after the heat information of the target food and the heat data information corresponding to the user are obtained, resources can be allocated for the user according to the heat information corresponding to the target food and the heat data information corresponding to the user, namely, the scheme with lower cost and automation for resource allocation for the user can be provided by the embodiment of the disclosure.
The above-described S101 to S103 will be described in detail with reference to specific embodiments.
For S101, when acquiring a target picture, identifying a target food contained in the target picture, and determining heat information of the target food, as shown in fig. 2, the following S201 to S202 are included:
S201, identifying foods to be detected contained in a target picture to obtain at least one candidate food contained in the target picture and attribute information of each candidate food;
s202, determining caloric information of the target food based on attribute information of each candidate food and probability of the user selecting each food in the current time period predicted by the feature information of the user.
At least one candidate food item contained in the target picture may be identified here by an image identification technique, such as based on a pre-trained neural network, identifying the food item to be detected contained in the target picture.
Specifically, for S201, when identifying the food to be detected included in the target picture, to obtain at least one candidate food and attribute information of each candidate food included in the target picture, the method may include:
(1) Identifying foods to be detected in the target picture to obtain at least one candidate food contained in the target picture, and food type and specification information of each candidate food;
(2) The food type and specification information corresponding to each candidate food is used as attribute information of the candidate food.
The attribute information of the candidate food may include the food type of the candidate food and the specification information of the candidate food, the specification information may include weight information, quantity information, volume information, or the like of the candidate food, specifically, based on the recognition of the target picture, the specification information of the candidate food may include various determination manners, for example, when the specification information of the candidate food is included in the target picture, the specification information of the candidate food may be obtained directly based on the picture recognition, and when the specification information of the candidate food is not included in the target picture, the user may be prompted to manually input the specification information of the candidate food.
In addition, with respect to the above S202, the probability that the user predicted from the characteristic information of the user selects each food item in the current time period here may be a probability that the user predicted in advance by the client terminal selects each food item in the current time period based on the user portrayal information authorized by the user and the historical behavior data.
The gender, age and location of the user contained in the portrait information of the user have certain influence on the diet preference of the user, such as staple food preference cooked rice eaten by the user in the southern area, and staple food preference cooked wheaten food eaten by the user in the northern area, namely the corresponding relation between the portrait information of the user and various food types can be determined through big data statistics.
In addition, the historical behavior data of the user can also reflect the eating habits of the user, for example, if the number of times of sweet foods in the historical eating records of the user is more, the user can be supposed to prefer sweet foods, if the user consumes a certain type of food in the same time period in a large probability, the probability of selecting the food in the current time period by the user is predicted to be higher, in addition, the historical behavior data can also comprise heat target data set by the user in the same time period in the history, and if the heat target data set by the user in the same time period in the history is lower, the probability of predicting that the type of the food of the candidate food in the target picture uploaded by the user is the low-heat food type is higher.
In summary, the feature information such as the sex, age, region, etc. of the user included in the user portrait information, and the feature information such as the historical diet record included in the historical behavior data of the user, and the heat target data set by the user in the same time period of the history may be used as the feature information for predicting the probability that the user selects each food corresponding to the current time period.
For example, the probability that the user selects each food item in the current time period can be predicted by a pre-trained neural network, wherein the user portrait information and the characteristic information contained in the historical behavior data of the user can be input into the pre-trained neural network, so that the probability that the user selects each food item type in the current time period is predicted.
Specifically, the neural network pre-trained herein may be trained for different time periods of each day, such as training for a neural network corresponding to a noon time period of each day (11:00-13:00), a large amount of sample data may be collected, where the sample data includes user portrait sample information of the users, historical behavior sample data corresponding to the historical noon time periods of the users (such as historical behavior sample data corresponding to the noon time period in the last year), and probabilities corresponding to each food sample type selected by the users based on the food sample types consumed by the large number of users on the day of training.
When training, user portrait sample information and historical behavior sample data of a user are used as network input features, probabilities corresponding to each food sample type selected by the user are used as network output features, the neural network is trained, and a trained neural network is obtained.
After obtaining at least one candidate food contained in the target food and the probability that the user selects each food in the current time period, the caloric information of the target food contained in the target picture can be further determined based on the probability, specifically, when determining caloric information of the target food based on attribute information of each candidate food and the probability that the user selects each food in the current time period predicted by the characteristic information of the user, the method may include:
(1) Determining a target food contained in the target picture among at least one candidate food based on the food type of each candidate food and the probability that the user selects each food at the current time period predicted by the characteristic information of the user;
(2) Based on the food type and specification information of the target food, caloric information of the target food is determined.
Specifically, the food type of the target food contained in the target picture can be determined firstly based on the food type of each candidate food and the probability of selecting each food by the user in the current time period, and then the heat information of the target food can be determined together according to the specification information of the target food.
For example, after identifying the target picture, the food types of the candidate foods contained in the target picture include a type a, a type B and a type C, and if the probability corresponding to the food of the type a is highest in the probability that the predicted user selects each food type in the current time period, the food type of the target food contained in the target picture is determined to be the type a.
Then after obtaining the food type of the target food, based on the food type and specification information of the target food, the heat information of the target food can be determined, for example, the determined food type of the target food is potato, and the specification information of the potato is 500g, and based on a pre-stored food heat meter, the heat information of the target food contained in the target picture can be determined.
In particular, if the food type of the target food cannot be determined based on the food type of the candidate food and the predicted probability that the user selects each food in the current time period, the user may also be prompted to manually input the food type of the target food contained in the target picture.
For the above S102, as shown in fig. 3, the heat data information corresponding to the user may be specifically determined as follows:
s301, determining a heat recommendation range for a user in a current time period based on characteristic information of the user and target event data corresponding to the user;
s302, determining heat data information corresponding to the user based on the heat recommended range and the heat target data set by the user and ingested at the time.
Here, the feature information of the user and the target event data corresponding to the user have been explained above, which is not described herein, specifically, how to determine the heat recommendation range for the user in the current time period based on the feature information of the user and the target event data corresponding to the user is mainly described herein, specifically:
taking the characteristic information of the user as an example, taking the user's sex, age, height and weight as the example, taking the target event data corresponding to the user as the data representing the target physical state of the user, for example, taking the target event data as the data representing the target physical state of the user as the weight reduction state, thus, firstly, the physical quality index of the user can be determined based on the sex, age, height and weight of the user, then the physical quality index of the user can be determined based on the physical quality index of the user, the standard physical quality index given by the national relevant nutrition health departments, and the food calories ingested by the user with a large number of standard physical indexes in the same time period corresponding to the current time period, then the initial caloric recommendation range for the user in the current time period is determined, then the weight reduction state set by the user is combined, the initial caloric recommendation range is adjusted, and the upper limit and the lower limit of the caloric recommendation range determined after adjustment are in accordance with health standards, for example, if the physical quality index is lower, but if the state of variation of the physical quality index expected by the user is weight reduction, then the lowest value of the caloric recommendation range is set as the lower limit, the initial caloric recommendation range is not damaged, the highest value can be set as the initial caloric recommendation range, if the maximum value is not the initial caloric value is the initial caloric recommendation range is higher than the maximum value.
In S302, the caloric target data set by the user and about to be ingested by the user before the meal is set, where the caloric target data may be set by the user according to the characteristic information of the user, such as according to the height and weight of the user; the caloric data information includes caloric recommendation range for the user and caloric target data set by the user in the current time period.
In addition, the heat target data set by the user and taken at this time may be manually input by the user before the meal, or may be determined by the client according to the heat target data input by the user in the same time period according to the history corresponding to the current time period, for example, the current time period is noon, and if the heat target data input by the user in the noon in the past week is a joule, the a joule may be used as the heat target data set by the user and taken at this time.
Next, resources may be allocated to the user based on the caloric information of the target food, the caloric recommendation range for the user in the current time period, and the caloric target data of the current ingestion set by the user, as shown in fig. 4, and specifically may include the following S401 to S404:
S401, determining whether the caloric target data which is set by a user and is ingested at the time is matched with a caloric recommended range;
s402, when the fact that the heat target data set by the user and taken at the time are matched with the heat recommended range is determined, determining difference information between heat information of target food contained in a target picture and the heat target data set by the user and taken at the time;
s403, distributing resources matched with the difference information to the user based on the difference information;
s404, when the fact that the caloric target data which are set by the user and are ingested at the time are not matched with the caloric recommendation range is determined, preset resources are configured for the user.
The matching of the heat target data of the current intake set by the user and the heat recommended range means that the heat target data of the current intake set by the user is located in the heat recommended range, then difference information between the heat information of the target food contained in the target picture and the heat target data of the current intake set by the user is further determined, and when the heat information of the target food is the heat data of the target food, the difference information can be represented by a difference value between the heat data of the target food and the heat target data of the current intake set by the user, and in order to make the difference information positive, the difference value can be taken as an absolute value.
After obtaining the difference information, the difference information may be classified, for example, a plurality of gears are preset, and excitation resources corresponding to each gear are different, where after obtaining the difference information, the gear to which the difference information belongs is determined, and then excitation resources are allocated to the user according to the gear, for example, red packet credit or coupon number corresponding to the gear is allocated to the user, where when the heat information in the embodiment of the disclosure is represented by calories, if a difference between calories of the target food and the calorie target data of the current intake set by the user is smaller than a first difference threshold, the difference information is determined to belong to the first gear, if the difference is greater than or equal to the first difference threshold and smaller than a second difference threshold, and if the difference is greater than or equal to a third difference threshold, the difference information is determined to belong to the third gear, where the first difference threshold is smaller than the second difference threshold, the second difference threshold is smaller than the third difference threshold, and the excitation resources of the first gear are greater than the excitation resources of the second gear, and the excitation resources of the second gear are greater than the excitation resources of the third gear.
Of course, when it is determined that the caloric target data set by the user and ingested this time do not match the caloric recommendation range, a preset incentive resource may be configured for the user.
If the heat target data of the current ingestion set by the user is not in the heat recommendation range, the resource configuration can be performed for the user according to the preset excitation resource, for example, the red package limit contained in the preset excitation resource is 0, that is, the red package is not issued to the user; or recommending videos or science popularization articles about healthy diet to the user, and helping the user establish habit of healthy diet.
In another embodiment, if the obtained caloric data information corresponding to the user only includes a caloric recommendation range, a preset incentive resource may be configured for the user according to the caloric information of the target food and the caloric recommendation range, for example, when it is determined that the caloric information of the target food is within the caloric recommendation range, a first preset resource may be allocated for the user, for example, a red pack, a coupon, etc., and if it is determined that the caloric information of the target food is not within the caloric recommendation range, a second preset resource may be allocated for the user, for example, a video or a science popularization article related to healthy diet is recommended for the user.
In addition, in order to continuously encourage the user to develop a habit of reasonable diet, the adhesiveness between the user and the client is increased, and the allocated incentive resources can be increased along with the increase of the number of times that the caloric target data is matched with the caloric recommendation range, for example, if the number of times that the caloric target data is continuously matched with the caloric recommendation range reaches a set number of times threshold value within a set period of time at the current moment, the incentive resources can be adjusted to be the incentive resources matched with the set number of times threshold value when the resources matched with the difference information are allocated to the user, for example, if the set number of times threshold value is N times, when the number of times that the caloric target data is continuously matched with the caloric recommendation range reaches N times, the number of incentive resources can be adjusted to be N times, and N is larger than 1, for example, the red packet quota is adjusted to be N times as original diet, and the user can be stimulated to develop a good and healthy habit.
In summary, the present disclosure provides a resource allocation method, after a target picture is obtained, a target food contained in the target picture may be identified, heat information of the target food may be determined, and then heat data information corresponding to a user may be obtained, where the heat data information may be determined based on feature information of the user and/or target event data corresponding to the user, for example, the feature information of the user may be information of weight, height, etc. that the user authorizes disclosure, and the target event data corresponding to the user may include data representing events such as weight loss, fat loss, muscle increase, etc., so after the heat information of the target food and the heat data information corresponding to the user are obtained, resources may be allocated to the user according to the heat information corresponding to the target food and the heat data information corresponding to the user, that is, the embodiment of the disclosure may provide a scheme for resource allocation for the user with lower cost and automatization.
In addition, the embodiment of the disclosure can guide the user to reasonably eat and help the user to develop the habit of healthy eating by configuring the incentive resource.
It will be appreciated by those skilled in the art that in the above-described method of the specific embodiments, the written order of steps is not meant to imply a strict order of execution but rather should be construed according to the function and possibly inherent logic of the steps.
Based on the same technical concept, the embodiments of the present disclosure further provide a resource allocation device corresponding to the resource allocation method, and since the principle of solving the problem by the device in the embodiments of the present disclosure is similar to that of the foregoing resource allocation method in the embodiments of the present disclosure, implementation of the device may refer to implementation of the method, and repeated descriptions are omitted.
Referring to fig. 5, a schematic diagram of a resource allocation apparatus 500 according to an embodiment of the disclosure is provided, where the resource allocation apparatus 500 includes: a first acquisition module 501, a second acquisition module 502, and a resource configuration module 503.
The first obtaining module 501 is configured to obtain a target picture, identify a target food contained in the target picture, and determine heat information of the target food;
the second obtaining module 502 is configured to obtain thermal data information corresponding to a user, where the thermal data information is determined based on feature information of the user and/or target event data corresponding to the user;
the resource allocation module 503 is configured to allocate resources for the user based on the thermal information of the target food and the thermal data information corresponding to the user.
In one possible implementation, the first obtaining module 501, when configured to obtain a target picture, identify a target food product included in the target picture, and determine heat information of the target food product, includes:
Identifying foods to be detected contained in the target picture to obtain at least one candidate food contained in the target picture and attribute information of each candidate food;
the caloric information of the target food is determined based on the attribute information of each candidate food and the probability of the user selecting each food at the current time period predicted by the feature information of the user.
In a possible implementation manner, when the first obtaining module 501 is configured to identify the food to be detected included in the target picture, obtain at least one candidate food and attribute information of each candidate food included in the target picture, the first obtaining module includes:
identifying foods to be detected in the target picture to obtain at least one candidate food contained in the target picture, and food type and specification information of each candidate food;
the food type and specification information corresponding to each candidate food is used as attribute information of the candidate food.
In one possible implementation, the first obtaining module 501 when determining the caloric information of the target food product based on the attribute information of each candidate food product and the probability of the user selecting each food product in the current time period predicted by the feature information of the user, includes:
Determining a target food contained in the target picture among at least one candidate food based on the food type of each candidate food and the probability that the user selects each food at the current time period predicted by the characteristic information of the user;
based on the food type and specification information of the target food, caloric information of the target food is determined.
In one possible implementation, the second acquisition module 502 determines the thermal data information corresponding to the user in the following manner:
determining a heat recommendation range for a user in a current time period based on the characteristic information of the user and target event data corresponding to the user;
and determining the caloric data information corresponding to the user based on the caloric recommendation range and the caloric target data set by the user and ingested at the time.
In one possible implementation, the resource configuration module 503, when configured to allocate resources for a user based on the caloric information corresponding to the target food and the caloric data information corresponding to the user, includes:
determining whether the caloric target data which is set by the user and is ingested at the time is matched with a caloric recommendation range;
when the heat target data of the current ingestion set by the user is matched with the heat recommended range, determining difference information between heat information of target food contained in the target picture and the heat target data of the current ingestion set by the user;
Based on the difference information, distributing resources matched with the difference information to the user;
and when the caloric target data which is set by the user and is ingested at the time is not matched with the caloric recommended range, configuring preset resources for the user based on the caloric information and the caloric recommended range of the target food.
The process flow of each module in the apparatus and the interaction flow between the modules may be described with reference to the related descriptions in the above method embodiments, which are not described in detail herein.
Corresponding to the resource allocation method in fig. 1, the embodiment of the present disclosure further provides an electronic device 600, as shown in fig. 6, which is a schematic structural diagram of the electronic device 600 provided in the embodiment of the present disclosure, including:
a processor 61, a memory 62, and a bus 63; memory 62 is used to store execution instructions, including memory 621 and external memory 622; the memory 621 is also referred to as an internal memory, and is used for temporarily storing operation data in the processor 61 and data exchanged with the external memory 622 such as a hard disk, the processor 61 exchanges data with the external memory 622 through the memory 621, and when the electronic device 600 is operated, the processor 61 and the memory 62 communicate with each other through the bus 63, so that the processor 61 executes the following instructions: acquiring a target picture, identifying target food contained in the target picture, and determining heat information of the target food; acquiring heat data information corresponding to a user, wherein the heat data information is determined based on characteristic information of the user and/or target event data corresponding to the user; and allocating resources for the user based on the heat information of the target food and the heat data information corresponding to the user.
The disclosed embodiments also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the resource allocation method described in the method embodiments described above. Wherein the storage medium may be a volatile or nonvolatile computer readable storage medium.
The computer program product of the resource allocation method provided in the embodiments of the present disclosure includes a computer readable storage medium storing a program code, where the program code includes instructions for executing the steps of the resource allocation method described in the above method embodiments, and specific reference may be made to the above method embodiments, which are not described herein.
The disclosed embodiments also provide a computer program which, when executed by a processor, implements any of the methods of the previous embodiments. The computer program product may be realized in particular by means of hardware, software or a combination thereof. In an alternative embodiment, the computer program product is embodied as a computer storage medium, and in another alternative embodiment, the computer program product is embodied as a software product, such as a software development kit (Software Development Kit, SDK), or the like.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described system and apparatus may refer to corresponding procedures in the foregoing method embodiments, which are not described herein again. In the several embodiments provided in the present disclosure, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, for example, the division of the units is merely a logical function division, and there may be other manners of division in actual implementation, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, device or unit indirect coupling or communication connection, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present disclosure may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer readable storage medium executable by a processor. Based on such understanding, the technical solution of the present disclosure may be embodied in essence or a part contributing to the prior art or a part of the technical solution, or in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in the embodiments of the present disclosure. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Finally, it should be noted that: the foregoing examples are merely specific embodiments of the present disclosure, and are not intended to limit the scope of the disclosure, but the present disclosure is not limited thereto, and those skilled in the art will appreciate that while the foregoing examples are described in detail, it is not limited to the disclosure: any person skilled in the art, within the technical scope of the disclosure of the present disclosure, may modify or easily conceive changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features thereof; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the disclosure, and are intended to be included within the scope of the present disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.

Claims (9)

1. A method for resource allocation, comprising:
acquiring a target picture, and identifying foods to be detected contained in the target picture to obtain at least one candidate food contained in the target picture and attribute information of each candidate food;
determining a target food item from the at least one candidate food item based on attribute information of each candidate food item and a probability that the user selects each food item at a current time period predicted by characteristic information of the user, and determining caloric information of the target food item;
acquiring heat data information corresponding to the user, wherein the heat data information is determined based on the characteristic information of the user and/or target event data corresponding to the user;
and distributing resources for the user based on the heat information of the target food and the heat data information corresponding to the user.
2. The method for configuring resources according to claim 1, wherein the identifying the food to be detected included in the target picture to obtain at least one candidate food and attribute information of each candidate food included in the target picture includes:
identifying foods to be detected in the target picture to obtain at least one candidate food contained in the target picture, and food type and specification information of each candidate food;
The food type and specification information corresponding to each candidate food is used as attribute information of the candidate food.
3. The resource allocation method according to claim 2, wherein said determining caloric information of the target food product comprises:
based on the food type and specification information of the target food, caloric information of the target food is determined.
4. The resource allocation method according to claim 1, wherein the user-corresponding thermal data information is determined in the following manner:
determining a heat recommendation range for the user in a current time period based on the characteristic information of the user and the target event data corresponding to the user;
and determining the caloric data information corresponding to the user based on the caloric recommendation range and the caloric target data set by the user and ingested at the time.
5. The method of claim 4, wherein the allocating resources to the user based on the caloric information corresponding to the target food and the caloric data information corresponding to the user comprises:
determining whether the caloric target data which is set by the user and is ingested at the time is matched with the caloric recommended range;
When the heat target data of the current ingestion set by the user is matched with the heat recommended range, determining difference information between heat information of target food contained in the target picture and the heat target data of the current ingestion set by the user;
allocating resources matched with the difference information to the user based on the difference information;
and when the heat target data which is set by the user and is ingested at the time is not matched with the heat recommended range, configuring preset resources for the user.
6. A resource allocation apparatus, comprising:
the first acquisition module is used for acquiring a target picture, identifying foods to be detected contained in the target picture, and obtaining at least one candidate food contained in the target picture and attribute information of each candidate food;
determining a target food item from the at least one candidate food item based on attribute information of each candidate food item and a probability that the user selects each food item at a current time period predicted by characteristic information of the user, and determining caloric information of the target food item;
the second acquisition module is used for acquiring heat data information corresponding to the user, wherein the heat data information is determined based on the characteristic information of the user and/or the target event data corresponding to the user;
And the resource allocation module is used for allocating resources for the user based on the heat information of the target food and the heat data information corresponding to the user.
7. The resource allocation apparatus according to claim 6, wherein the first obtaining module, when identifying the food to be detected included in the target picture, obtains at least one candidate food and attribute information of each candidate food included in the target picture, includes:
identifying foods to be detected in the target picture to obtain at least one candidate food contained in the target picture, and food type and specification information of each candidate food;
the food type and specification information corresponding to each candidate food is used as attribute information of the candidate food.
8. An electronic device, comprising: a processor, a memory and a bus, said memory storing machine readable instructions executable by said processor, said processor and said memory communicating over the bus when the electronic device is running, said machine readable instructions when executed by said processor performing the steps of the resource allocation method according to any of claims 1 to 5.
9. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, performs the steps of the resource allocation method according to any of claims 1 to 5.
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Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106663137A (en) * 2014-04-28 2017-05-10 耶达研究及发展有限公司 Method of predicting a response of a subject to food
CN107731278A (en) * 2017-09-04 2018-02-23 广东数相智能科技有限公司 A kind of food recognition methods, nutrient health analysis method, system and device
CN108292420A (en) * 2015-11-25 2018-07-17 三星电子株式会社 Subscriber terminal equipment and its control method
CN108630298A (en) * 2018-05-09 2018-10-09 南京邮电大学 Healthy diet management method and system, computer readable storage medium, terminal
CN108682451A (en) * 2018-04-28 2018-10-19 上海与德科技有限公司 Information-pushing method, device, equipment based on intelligent refrigerator and storage medium
CN109767825A (en) * 2019-01-31 2019-05-17 北京卡路里信息技术有限公司 Diet control method, apparatus, equipment and storage medium
CN110867239A (en) * 2019-11-07 2020-03-06 北京理工大学 Diet suggestion generation method and device, computer device and storage medium

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106663137A (en) * 2014-04-28 2017-05-10 耶达研究及发展有限公司 Method of predicting a response of a subject to food
CN108292420A (en) * 2015-11-25 2018-07-17 三星电子株式会社 Subscriber terminal equipment and its control method
CN107731278A (en) * 2017-09-04 2018-02-23 广东数相智能科技有限公司 A kind of food recognition methods, nutrient health analysis method, system and device
CN108682451A (en) * 2018-04-28 2018-10-19 上海与德科技有限公司 Information-pushing method, device, equipment based on intelligent refrigerator and storage medium
CN108630298A (en) * 2018-05-09 2018-10-09 南京邮电大学 Healthy diet management method and system, computer readable storage medium, terminal
CN109767825A (en) * 2019-01-31 2019-05-17 北京卡路里信息技术有限公司 Diet control method, apparatus, equipment and storage medium
CN110867239A (en) * 2019-11-07 2020-03-06 北京理工大学 Diet suggestion generation method and device, computer device and storage medium

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