CN112241913A - Ordering method and device - Google Patents
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Abstract
The application provides an ordering method and an ordering device, wherein through the method, ordering of take-out can be completed without ordering operation of an ordering user, so that taking-out ordering efficiency of the ordering user is improved, dish in a take-out order is considered to basic disease conditions of the ordering user, daily habits of the ordering user are considered, the take-out obtained by the ordering user cannot cause negative influence on self health, and the taste of the ordering user can be guaranteed to be met.
Description
Technical Field
The application relates to the technical field of computers, in particular to a method and a device for placing an order.
Background
With the great abundance of material life and the improvement of living standard of people, more and more foods can be selected by people, but for patients with basic diseases (such as hypertension, diabetes and the like), whether the food selected by the people has adverse effects on the condition of the people cannot be completely determined, and in the case, if the patients have difficulty in selecting at the time of taking out or do not know what to eat, a great deal of time is wasted for selecting.
Disclosure of Invention
In view of this, the present application provides an order placing method and apparatus, so as to improve the order placing efficiency of take-out.
In a first aspect, an embodiment of the present application provides a method for ordering, including:
responding to touch operation for random ordering, and acquiring basic disease information and current physiological index data of an ordering user, wherein the physiological index data comprises: body temperature data, respiratory rate data, heart rate data, blood pressure data, blood glucose data, blood lipid data, perspiration data, blood oxygen saturation data, and pulse data;
inputting the basic disease information and the physiological index data serving as input parameters into a food matching model to obtain candidate food materials and a cooking mode of each candidate food material;
determining candidate cooking seasonings according to the basic disease information, the physiological index data and the taste preference of the ordering user;
for each candidate food material, selecting candidate dishes capable of being made from dishes included in the health management platform by taking the candidate food material, the cooking mode of the candidate food material and the candidate cooking seasonings as matching conditions;
selecting a target dish from the candidate dishes according to the cooking materials used by the candidate dishes, wherein the cooking materials used by the target dish do not aggravate the basic diseases of the ordering user and can prevent the physiological indexes of the ordering user from continuously developing towards abnormal indexes;
inputting each target dish serving as an input parameter into a random screening model to obtain a target number of dishes to be ordered, wherein the target number is equal to the average value of daily ordering number of the ordering user;
taking the dish to be ordered as a query condition, and determining a takeout merchant for making the dish to be ordered;
determining a matching degree score of each take-out merchant and the ordering user according to the daily consumption level of the ordering user, the current time and the distribution path of each take-out merchant;
and according to the target number of dishes to be placed, placing orders from the takeaway merchants with the highest matching degree score, and sending the takeaway orders to the takeaway merchants with the highest matching degree score.
Optionally, the determining, according to the daily consumption level of the ordering user, the current time and the delivery path of each takeout merchant, the matching degree score between each takeout merchant and the ordering user includes:
determining estimated arrival time according to the distribution path;
calculating whether the sum of the current time and the estimated arrival time exceeds a preset time or not;
calculating a weight score of the takeaway merchant according to a first weight assigned to the daily consumption level and a second weight assigned to the delivery path, wherein the second weight is a first value when the sum of the current time and the estimated arrival time exceeds the preset time, and the second weight is a second value when the sum of the current time and the estimated arrival time does not exceed the preset time, and the first value is smaller than the second value;
and determining the matching degree score of each takeout merchant and the ordering user according to the weight score and the ordering times of the ordering user at each takeout merchant, wherein for each takeout merchant, if the ordering times of the ordering user at the takeout merchant is less than a preset threshold value, the sum of the weight score of the takeout merchant and a specified numerical value is calculated to serve as the matching degree score of the takeout merchant, and if the ordering times of the ordering user at the takeout merchant is greater than or equal to the preset threshold value, the difference between the weight score of the takeout merchant and the specified numerical value is calculated to serve as the matching degree score of the takeout merchant.
Optionally, after selecting the candidate dishes capable of being made from the dishes included in the health management platform, the method further comprises:
and displaying the candidate dishes on the terminal of the ordering user.
Optionally, after obtaining the target number of the to-be-ordered dishes, the method further includes:
and displaying the dishes to be ordered to the terminal of the ordering user.
In a second aspect, an embodiment of the present application provides an ordering apparatus, including:
the obtaining unit is used for responding to touch operation for random ordering and obtaining basic disease information and current physiological index data of an ordering user, wherein the physiological index data comprises: body temperature data, respiratory rate data, heart rate data, blood pressure data, blood glucose data, blood lipid data, perspiration data, blood oxygen saturation data, and pulse data;
the determining unit is used for inputting the basic disease information and the physiological index data serving as input parameters into a food matching model to obtain candidate food materials and cooking modes of the candidate food materials; and determining candidate cooking seasonings according to the basic disease information, the physiological index data and the taste preference of the ordering user; and selecting candidate dishes capable of being made from dishes included in the health management platform by taking the candidate food material, the cooking mode of the candidate food material and the candidate cooking seasoning as matching conditions for each candidate food material; the dish ordering system comprises a dish ordering user, a dish ordering system and a control system, wherein the dish ordering system comprises a plurality of candidate dishes, a plurality of cooking materials used by the dish ordering system are used for selecting a target dish from the candidate dishes according to the cooking materials used by the candidate dishes, the cooking materials used by the target dish do not aggravate basic diseases of the dish ordering user, and physiological indexes of the dish ordering user can not continue to develop towards abnormal indexes; the menu selection method comprises the steps of selecting a random screening model according to the number of dishes to be ordered, and inputting each target dish serving as an input parameter into the random screening model to obtain a target number of dishes to be ordered, wherein the target number is equal to the average value of daily ordering number of ordering users; and the system is used for determining a takeout merchant for making the dish to be ordered by taking the dish to be ordered as a query condition; the system comprises a meal ordering user, a matching degree score of each take-out merchant and the meal ordering user, wherein the daily consumption level of the meal ordering user, the current time and the distribution path of each take-out merchant are used for determining the matching degree score of each take-out merchant and the meal ordering user;
and the order placing unit is used for placing orders from the takeaway merchants with the highest matching degree score according to the target number of the dishes to be placed, and sending the takeaway orders to the takeaway merchants with the highest matching degree score.
Optionally, when the determining unit is configured to determine the matching degree score between each takeout merchant and the ordering user according to the daily consumption level of the ordering user, the current time, and the delivery path of each takeout merchant, the determining unit includes:
determining estimated arrival time according to the distribution path;
calculating whether the sum of the current time and the estimated arrival time exceeds a preset time or not;
calculating a weight score of the takeaway merchant according to a first weight assigned to the daily consumption level and a second weight assigned to the delivery path, wherein the second weight is a first value when the sum of the current time and the estimated arrival time exceeds the preset time, and the second weight is a second value when the sum of the current time and the estimated arrival time does not exceed the preset time, and the first value is smaller than the second value;
and determining the matching degree score of each takeout merchant and the ordering user according to the weight score and the ordering times of the ordering user at each takeout merchant, wherein for each takeout merchant, if the ordering times of the ordering user at the takeout merchant is less than a preset threshold value, the sum of the weight score of the takeout merchant and a specified numerical value is calculated to serve as the matching degree score of the takeout merchant, and if the ordering times of the ordering user at the takeout merchant is greater than or equal to the preset threshold value, the difference between the weight score of the takeout merchant and the specified numerical value is calculated to serve as the matching degree score of the takeout merchant.
Optionally, the apparatus further comprises:
and the first display unit is used for displaying the candidate dishes on the terminal of the ordering user after the candidate dishes capable of being made are selected from the dishes included in the health management platform.
Optionally, the apparatus further comprises:
and the second display unit is used for displaying the dishes to be ordered to the terminal of the ordering user after the target number of the dishes to be ordered are obtained.
The technical scheme provided by the embodiment of the application at least comprises the following beneficial effects:
in the application, basic disease information of an ordering user and current physiological indexes are combined to determine an order-placing dish, the order-placing dish is used as a query condition to determine a takeout merchant for making the order-placing dish, then according to daily consumption level, current time and distribution paths of the ordering user, matching degree scores of the takeout merchants and the ordering user are determined, a target number of the order-placing dishes to be placed are selected from the takeout merchants with the highest matching degree scores to perform order placing operation, so that a takeout order is sent to the takeout merchants with the highest matching degree scores, wherein the target number is equal to the average value of the daily ordering number of the ordering user, the order placing of the takeout order can be completed without the ordering user performing the ordering operation by the method, the takeout order placing efficiency of the ordering user is improved, and the dish in the takeout order not only considers the basic disease condition of the ordering user, daily habits of the ordering user are also considered, so that the takeaway obtained by the ordering user cannot cause negative influence on the health of the ordering user and can also be ensured to accord with the taste of the ordering user.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments are briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts;
fig. 1 is a schematic flow chart of a method for ordering documents according to an embodiment of the present disclosure;
fig. 2 is a schematic flow chart of another ordering method provided in the first embodiment of the present application;
fig. 3 is a schematic structural diagram of a ordering apparatus according to a second embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
The following embodiments can be applied to the aspect of health management of people, and can assist people in healthier life.
Example one
Fig. 1 is a schematic flow chart of a method for ordering documents according to an embodiment of the present application, as shown in fig. 1, the method includes the following steps:
Specifically, when a user ordering food uses a terminal to order food, if the user does not know what to eat, the user can click a control of a blind box order, the food ordering system can automatically take out the food for the user ordering food through the control, and in order to ensure the health of the user ordering food, basic disease information and current physiological index data of the user ordering food need to be acquired to serve as reference basis when the user ordering food.
And 102, inputting the basic disease information and the physiological index data serving as input parameters into a food matching model to obtain candidate food materials and a cooking mode of each candidate food material.
Specifically, different foods can be eaten by different basic disease and physiological index data, and the cooking modes of the foods are different, such as: for patients with hyperlipidemia, foods which can be eaten by the patients comprise potatoes but are not suitable for fried potatoes, so that the candidate food materials which can be eaten by the ordering user need to be determined by referring to the basic disease information and the physiological index data, and the candidate food materials do not have negative influence on the body health of the ordering user when the candidate food materials are used in any cooking mode.
And 103, determining candidate cooking seasonings according to the basic disease information, the physiological index data and the taste preference of the ordering user.
Taking a diabetic as an example, sugar can be used as a cooking seasoning, but sugar cannot be used as a cooking seasoning of the diabetic, otherwise adverse effects can be caused on the health of the ordering user, and especially under the condition that the blood sugar of the ordering user is high, the cooking seasoning selected in step 103 can not aggravate the condition of the ordering user, and can not lead the physiological index of the ordering user to develop towards an adverse direction, so that the health of the ordering user is facilitated, and the taste of the ordering user is also considered.
And 104, for each candidate food material, selecting the candidate food material, the cooking mode of the candidate food material and the candidate cooking seasoning as matching conditions, and selecting candidate dishes capable of being made from dishes included in the health management platform. Wherein the candidate food material is used as a main food material of the candidate dish.
And 105, selecting a target dish from the candidate dishes according to the cooking materials used by the candidate dishes, wherein the cooking materials used by the target dish do not aggravate the basic diseases of the ordering user, and the physiological indexes of the ordering user can not continue to develop towards abnormal indexes.
Specifically, one dish includes not only the main food material but also materials such as side dishes, and in the case that the main food material does not respond to the health of the ordering user, the side dishes cannot cause adverse effects on the health of the ordering user, so that a target dish needs to be selected from the candidate dishes according to the cooking materials used by the candidate dishes.
And step 106, inputting each target dish serving as an input parameter into a random screening model to obtain a target number of dishes to be ordered, wherein the target number is equal to the average value of the daily ordering number of the ordering user.
The number of dishes can be similar to the daily habits of the ordering user through the step 106, so that the food consumption and the daily habits of the ordering user can be met.
And step 107, determining a takeout merchant for making the dish to be ordered by taking the dish to be ordered as a query condition.
Specifically, in order to make the ordering mode relatively simple, it is necessary to determine a takeout merchant who can independently complete all the dishes to be ordered, so that all the dishes can be obtained after an order is made by one takeout merchant.
And 108, determining the matching degree score of each take-out merchant and the ordering user according to the daily consumption level of the ordering user, the current time and the distribution path of each take-out merchant.
Specifically, in daily takeout ordering, not only the price but also the time consumed by taking the takeout from the takeout merchant to the ordering user and the time taken by the ordering user to take the takeout are taken into consideration, and ordering needs to be performed by integrating the above conditions, so that the matching degree score between each takeout merchant and the ordering user needs to be determined, so as to determine the takeout merchant with higher matching degree with the ordering user through the matching degree score.
And step 109, placing orders from the takeaway merchants with the highest matching degree according to the target number of the dishes to be placed, and sending the takeaway orders to the takeaway merchants with the highest matching degree.
Specifically, by the method, ordering can be finished without ordering operation by the ordering user, so that the ordering efficiency of the ordering user can be improved, basic disease conditions of the ordering user are considered for dishes in the take-out order, and daily habits of the ordering user are considered, so that the taking-out obtained by the ordering user cannot cause negative influence on self health, and the taste of the ordering user can be ensured to be met.
In a possible implementation, fig. 2 is a schematic flow chart of another ordering method provided in the first embodiment of the present application, and as shown in fig. 2, when step 108 is executed, the following steps may be implemented:
Specifically, the weight score of the takeaway merchant may be calculated by the following formula:
the weight score of the take-out merchant = (daily consumption level consumption value-average consumption value of the take-out merchant) x first weight + estimated arrival time x second weight;
and 204, determining a matching degree score of each takeout merchant and the ordering user according to the weight score and the ordering times of the ordering user at each takeout merchant, wherein for each takeout merchant, if the ordering times of the ordering user at the takeout merchant is less than a preset threshold value, a sum of the weight score of the takeout merchant and a specified numerical value is calculated to use the sum as the matching degree score of the takeout merchant, and if the ordering times of the ordering user at the takeout merchant is greater than or equal to the preset threshold value, a difference between the weight score of the takeout merchant and the specified numerical value is calculated to use the difference as the matching degree score of the takeout merchant.
Specifically, the fact that the ordering times of the ordering user at a certain takeout merchant is smaller than a preset threshold value indicates that the ordering user does not order at the takeout merchant or the ordering times are few, the probability that the ordering user eats the takeout of the takeout merchant can be increased through the form of a sum value, so that the ordering user can try more flavors, the ordering times of the ordering user at a certain takeout merchant is larger than or the preset threshold value indicates that the ordering user often orders at the takeout merchant, the ordering user does not know what the ordering user has, the current interest of the ordering user in the takeout of the takeout merchant is relatively small, the probability that the ordering user eats the takeout of the takeout merchant can be reduced through the form of a difference value, and the ordering user can try dishes of other takeout merchants more probably.
In a possible embodiment, after the candidate dishes capable of being made are selected from the dishes included in the health management platform, the candidate dishes are displayed on the terminal of the ordering user, so that the ordering user can select from the candidate dishes, and the selection efficiency of the ordering user is improved.
In a feasible implementation scheme, after the target number of the dishes to be ordered are obtained, the dishes to be ordered are displayed on the terminal of the ordering user, so that the ordering user can select from the dishes to be ordered, and the selection efficiency of the ordering user is improved.
Example two
Fig. 3 is a schematic structural diagram of a sheet discharging apparatus according to a second embodiment of the present application, and as shown in fig. 3, the apparatus includes:
an obtaining unit 31, configured to obtain, in response to a touch operation for randomly ordering, basic disease information and current physiological index data of an ordering user, where the physiological index data includes: body temperature data, respiratory rate data, heart rate data, blood pressure data, blood glucose data, blood lipid data, perspiration data, blood oxygen saturation data, and pulse data;
the determining unit 32 is configured to input the basic disease information and the physiological index data as input parameters into a food matching model to obtain candidate food materials and a cooking manner of each candidate food material; and determining candidate cooking seasonings according to the basic disease information, the physiological index data and the taste preference of the ordering user; and selecting candidate dishes capable of being made from dishes included in the health management platform by taking the candidate food material, the cooking mode of the candidate food material and the candidate cooking seasoning as matching conditions for each candidate food material; the dish ordering system comprises a dish ordering user, a dish ordering system and a control system, wherein the dish ordering system comprises a plurality of candidate dishes, a plurality of cooking materials used by the dish ordering system are used for selecting a target dish from the candidate dishes according to the cooking materials used by the candidate dishes, the cooking materials used by the target dish do not aggravate basic diseases of the dish ordering user, and physiological indexes of the dish ordering user can not continue to develop towards abnormal indexes; the menu selection method comprises the steps of selecting a random screening model according to the number of dishes to be ordered, and inputting each target dish serving as an input parameter into the random screening model to obtain a target number of dishes to be ordered, wherein the target number is equal to the average value of daily ordering number of ordering users; and the system is used for determining a takeout merchant for making the dish to be ordered by taking the dish to be ordered as a query condition; the system comprises a meal ordering user, a matching degree score of each take-out merchant and the meal ordering user, wherein the daily consumption level of the meal ordering user, the current time and the distribution path of each take-out merchant are used for determining the matching degree score of each take-out merchant and the meal ordering user;
and an ordering unit 33, configured to perform an ordering operation from the takeaway merchants with the highest matching degree score according to the target number of the dishes to be ordered, and send the takeaway order to the takeaway merchants with the highest matching degree score.
In a possible embodiment, the determining unit 32 is configured to determine, according to the daily consumption level of the ordering user, the current time and the delivery path of each takeout merchant, a matching degree score between each takeout merchant and the ordering user, and includes:
determining estimated arrival time according to the distribution path;
calculating whether the sum of the current time and the estimated arrival time exceeds a preset time or not;
calculating a weight score of the takeaway merchant according to a first weight assigned to the daily consumption level and a second weight assigned to the delivery path, wherein the second weight is a first value when the sum of the current time and the estimated arrival time exceeds the preset time, and the second weight is a second value when the sum of the current time and the estimated arrival time does not exceed the preset time, and the first value is smaller than the second value;
and determining the matching degree score of each takeout merchant and the ordering user according to the weight score and the ordering times of the ordering user at each takeout merchant, wherein for each takeout merchant, if the ordering times of the ordering user at the takeout merchant is less than a preset threshold value, the sum of the weight score of the takeout merchant and a specified numerical value is calculated to serve as the matching degree score of the takeout merchant, and if the ordering times of the ordering user at the takeout merchant is greater than or equal to the preset threshold value, the difference between the weight score of the takeout merchant and the specified numerical value is calculated to serve as the matching degree score of the takeout merchant.
In one possible embodiment, the apparatus further comprises:
and the first display unit is used for displaying the candidate dishes on the terminal of the ordering user after the candidate dishes capable of being made are selected from the dishes included in the health management platform.
In one possible embodiment, the apparatus further comprises:
and the second display unit is used for displaying the dishes to be ordered to the terminal of the ordering user after the target number of the dishes to be ordered are obtained.
For the explanation of the second embodiment, reference may be made to the explanation of the first embodiment, and the detailed explanation will not be provided herein.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed 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 can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments provided in the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into 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 computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus once an item is defined in one figure, it need not be further defined and explained in subsequent figures, and moreover, the terms "first", "second", "third", etc. are used merely to distinguish one description from another and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the present disclosure, which should be construed in light of the above teachings. Are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (8)
1. A method of ordering, comprising:
responding to touch operation for random ordering, and acquiring basic disease information and current physiological index data of an ordering user, wherein the physiological index data comprises: body temperature data, respiratory rate data, heart rate data, blood pressure data, blood glucose data, blood lipid data, perspiration data, blood oxygen saturation data, and pulse data;
inputting the basic disease information and the physiological index data serving as input parameters into a food matching model to obtain candidate food materials and a cooking mode of each candidate food material;
determining candidate cooking seasonings according to the basic disease information, the physiological index data and the taste preference of the ordering user;
for each candidate food material, selecting candidate dishes capable of being made from dishes included in the health management platform by taking the candidate food material, the cooking mode of the candidate food material and the candidate cooking seasonings as matching conditions;
selecting a target dish from the candidate dishes according to the cooking materials used by the candidate dishes, wherein the cooking materials used by the target dish do not aggravate the basic diseases of the ordering user and can prevent the physiological indexes of the ordering user from continuously developing towards abnormal indexes;
inputting each target dish serving as an input parameter into a random screening model to obtain a target number of dishes to be ordered, wherein the target number is equal to the average value of daily ordering number of the ordering user;
taking the dish to be ordered as a query condition, and determining a takeout merchant for making the dish to be ordered;
determining a matching degree score of each take-out merchant and the ordering user according to the daily consumption level of the ordering user, the current time and the distribution path of each take-out merchant;
and according to the target number of dishes to be placed, placing orders from the takeaway merchants with the highest matching degree score, and sending the takeaway orders to the takeaway merchants with the highest matching degree score.
2. The method of claim 1, wherein determining a matching score for each take-out merchant with the ordering user based on the daily consumption level of the ordering user, the current time, and the delivery path of each take-out merchant comprises:
determining estimated arrival time according to the distribution path;
calculating whether the sum of the current time and the estimated arrival time exceeds a preset time or not;
calculating a weight score of the takeaway merchant according to a first weight assigned to the daily consumption level and a second weight assigned to the delivery path, wherein the second weight is a first value when the sum of the current time and the estimated arrival time exceeds the preset time, and the second weight is a second value when the sum of the current time and the estimated arrival time does not exceed the preset time, and the first value is smaller than the second value;
and determining the matching degree score of each takeout merchant and the ordering user according to the weight score and the ordering times of the ordering user at each takeout merchant, wherein for each takeout merchant, if the ordering times of the ordering user at the takeout merchant is less than a preset threshold value, the sum of the weight score of the takeout merchant and a specified numerical value is calculated to serve as the matching degree score of the takeout merchant, and if the ordering times of the ordering user at the takeout merchant is greater than or equal to the preset threshold value, the difference between the weight score of the takeout merchant and the specified numerical value is calculated to serve as the matching degree score of the takeout merchant.
3. The method of claim 1, wherein upon selecting a candidate dish that can be made from the dishes included in the health management platform, the method further comprises:
and displaying the candidate dishes on the terminal of the ordering user.
4. The method of claim 1, wherein after obtaining the target number of orders to be placed, the method further comprises:
and displaying the dishes to be ordered to the terminal of the ordering user.
5. An ordering apparatus, comprising:
the obtaining unit is used for responding to touch operation for random ordering and obtaining basic disease information and current physiological index data of an ordering user, wherein the physiological index data comprises: body temperature data, respiratory rate data, heart rate data, blood pressure data, blood glucose data, blood lipid data, perspiration data, blood oxygen saturation data, and pulse data;
the determining unit is used for inputting the basic disease information and the physiological index data serving as input parameters into a food matching model to obtain candidate food materials and cooking modes of the candidate food materials; and determining candidate cooking seasonings according to the basic disease information, the physiological index data and the taste preference of the ordering user; and selecting candidate dishes capable of being made from dishes included in the health management platform by taking the candidate food material, the cooking mode of the candidate food material and the candidate cooking seasoning as matching conditions for each candidate food material; the dish ordering system comprises a dish ordering user, a dish ordering system and a control system, wherein the dish ordering system comprises a plurality of candidate dishes, a plurality of cooking materials used by the dish ordering system are used for selecting a target dish from the candidate dishes according to the cooking materials used by the candidate dishes, the cooking materials used by the target dish do not aggravate basic diseases of the dish ordering user, and physiological indexes of the dish ordering user can not continue to develop towards abnormal indexes; the menu selection method comprises the steps of selecting a random screening model according to the number of dishes to be ordered, and inputting each target dish serving as an input parameter into the random screening model to obtain a target number of dishes to be ordered, wherein the target number is equal to the average value of daily ordering number of ordering users; and the system is used for determining a takeout merchant for making the dish to be ordered by taking the dish to be ordered as a query condition; the system comprises a meal ordering user, a matching degree score of each take-out merchant and the meal ordering user, wherein the daily consumption level of the meal ordering user, the current time and the distribution path of each take-out merchant are used for determining the matching degree score of each take-out merchant and the meal ordering user;
and the order placing unit is used for placing orders from the takeaway merchants with the highest matching degree score according to the target number of the dishes to be placed, and sending the takeaway orders to the takeaway merchants with the highest matching degree score.
6. The apparatus according to claim 5, wherein the determining unit is configured to determine the matching degree score between each takeout merchant and the ordering user according to the daily consumption level of the ordering user, the current time, and the delivery path of each takeout merchant, and includes:
determining estimated arrival time according to the distribution path;
calculating whether the sum of the current time and the estimated arrival time exceeds a preset time or not;
calculating a weight score of the takeaway merchant according to a first weight assigned to the daily consumption level and a second weight assigned to the delivery path, wherein the second weight is a first value when the sum of the current time and the estimated arrival time exceeds the preset time, and the second weight is a second value when the sum of the current time and the estimated arrival time does not exceed the preset time, and the first value is smaller than the second value;
and determining the matching degree score of each takeout merchant and the ordering user according to the weight score and the ordering times of the ordering user at each takeout merchant, wherein for each takeout merchant, if the ordering times of the ordering user at the takeout merchant is less than a preset threshold value, the sum of the weight score of the takeout merchant and a specified numerical value is calculated to serve as the matching degree score of the takeout merchant, and if the ordering times of the ordering user at the takeout merchant is greater than or equal to the preset threshold value, the difference between the weight score of the takeout merchant and the specified numerical value is calculated to serve as the matching degree score of the takeout merchant.
7. The apparatus of claim 5, wherein the apparatus further comprises:
and the first display unit is used for displaying the candidate dishes on the terminal of the ordering user after the candidate dishes capable of being made are selected from the dishes included in the health management platform.
8. The apparatus of claim 5, wherein the apparatus further comprises:
and the second display unit is used for displaying the dishes to be ordered to the terminal of the ordering user after the target number of the dishes to be ordered are obtained.
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|---|---|---|---|
| CN202011413744.8A CN112241913A (en) | 2020-12-07 | 2020-12-07 | Ordering method and device |
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| CN202011413744.8A CN112241913A (en) | 2020-12-07 | 2020-12-07 | Ordering method and device |
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| CN117195081A (en) * | 2023-11-07 | 2023-12-08 | 广东工业大学 | Food and beverage takeout package waste accounting method based on text mining |
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Application publication date: 20210119 |