KR101978066B1 - Method For Providing Dietary Recommendation Service For One-person Households - Google Patents

Abstract

A method for providing a diet recommendation service for a one-person household comprises: a step of receiving the desired number of meals N wherein N is a natural number and a desired food expense X wherein X is an integer from a one-person household user through a mobile terminal; and a step of calculating at least one of nutrients, calories, and the amount of foodstuff as a ratio of the desired food expense X to the desired number of meals N to meet the input desired food expense based on the desired number of meals N and the desired food expense X input through the mobile terminal and recommending, to the one-person household user, a diet within a range of the input desired food expense through the mobile terminal. By using a mobile application, it is possible to provide a customized diet that is optimized for the increasing number of one-person households by reducing the food cost burden that is particularly required for the one-person household, minimizing the waste of foodstuff, and enabling efficient management of food expenses.

Description

[0001] The present invention relates to a method for providing a recommendation service for a single-person household,

The present invention relates to a method of providing a menu recommendation service, and more particularly, to a method of providing a menu recommendation service for a single-person household.

As the number of single-person households increases, a customized menu recommendation service for single-person households is needed. In addition, food waste caused by residual food is recognized as a social problem. Recently, the need for food delivery service is growing in response to the proliferation of mobile online shopping based on O2O (Online To Offline) and the continuous rise of food and beverage products in mobile.

In order to solve the above-mentioned problems, a simple classification and search such as a hammock male and female, a country, a recipe, a theme, and a recommendation service based on simple basic information inputted by the user such as the frequency of cooking, CJ THE KITCHEN, a service that recommends a meal based on the recommendation, recommends a full-meal menu recommended for seasonal ingredients and seasonal dishes, emphasizes easy-to-cook dishes with a spoon weighing service, Food recommendations such as a meal of tea were introduced, and grocery delivery services such as Yantai Fresh, Cacao Gift, and Altar were offered.

However, existing user-customized meal recommendation service mainly focuses on information on simple food ingredients and cooking order. Therefore, even though food expenses are important factors for one-person households who want to reduce the cost of food expenses, they provide customized services considering such food expenses There is a problem that can not be done.

Korean Patent Laid-Open No. 10-2011-0050955 (Method of purchasing personalized goods and providing a recommendation service for a meal, Korean Institute of Oriental Medicine) Korean Patent Laid-Open Publication No. 10-2014-0070234 (apparatus and method for customized dietary and food purchasing service,

Recently, the number of single-person households is increasing, and as a result, people who eat rice alone are showing an increasing trend. Therefore, there is a problem of food expenses, nutrients, and calorie management of single-person households.

According to the statistics of the National Health and Nutrition Survey, the nutritional status of single-person households is inadequate or inadequate compared to that of two or more households.

In addition, despite the high proportion of food expenses in households, the ratio of food expenses to living expenses is high, the nutrition of one household is not well managed.

In addition, specialized services are needed for consumers who want to cook at home rather than eat out, thereby reducing the cost of food expenses.

Recently, in order to increase the efficiency of separating and discharging food waste, it has been shifted from the use of food-grade bag to the collection of dedicated containers. As a result, efforts to reduce food waste have been continuing. It is necessary to realize cost reduction and minimization of the amount of food waste by using in cooking.

Thus, there is a need for specialized services for single-singer consumers who want to reduce the cost of food for these single-person households and purchase the required amount of foodstuffs for cooking.

On the other hand, it can be seen that the O2O market growth and mobile shopping growth are shifting to the dominance of overall distribution industry. As consumers' consumption patterns spread through purchasing through applications, it is necessary to provide services that link market and store delivery systems Do.

On-line shopping transactions for e-commerce and groceries and agricultural products are steadily increasing, with mobile transactions increasing rapidly. In particular, it is necessary to provide a service for purchasing only necessary food materials through mobile for a household consumer who wants to reduce the cost of food expenses.

Accordingly, it is an object of the present invention to solve the above-mentioned problems, and it is an object of the present invention to provide a cooking method for a single-person household user, And provide a method of providing a recommendation service for a single person to provide a meal.

According to an aspect of the present invention for solving the above-mentioned problems, there is provided a method of controlling a mobile terminal, comprising: inputting a desired number of dishes N - where N is a natural number and a desired food ratio X - And the desired food ratio X based on the inputted number N of desired dishes and the desired food ratio X through the mobile terminal, And recommending at least one meal to the one user through the mobile terminal within a range of the inputted desired food ratio.

The amount of nutrition, calorie, and foodstuffs in the desired food ratio X ratio with respect to the desired number of dishes N, in accordance with the inputted desired food ratio X, based on the inputted number N of desired dishes and the inputted desired food ratio X through the mobile terminal Wherein the step of recommending at least one of the users to the one-user user through the mobile terminal of a diet within a range of the inputted desired food expenses comprises: The method comprising the steps of: inputting a score of 5 points; applying a MF (Matrix Factorization) algorithm to the diets to which the 1 point to 5 points are input; And calculating the food ratio per meal based on the desired number N of dishes.

The step of calculating the above-mentioned food-to-be-cooked food ratio includes the steps of:

는 각 끼니당 오차이며,

는 i 번째 식단의 식비를 의미하는 것을 포함할 수 있다.Where X is the desired food expense entered by a household user with 1, N is the number of desired dishes,

Is the error per meal,

Can be used to denote the food ratio of the i-th diet.

The nutrient, calorie, and the like in the desired food ratio X ratio to the input desired number of dishes N so as to match the inputted desired food ratio, based on the input desired food amount N and the inputted desired food ratio X through the mobile terminal Wherein the step of recommending the one-user user through the mobile terminal to calculate a meal amount within a range of the desired food ratio by calculating at least one of the amount of food ingredients, The method comprising: inputting a score of 1 to 5 points from a user who has a household user who is within the range of the input food cost; inputting 4 to 5 points by applying the MF algorithm to the diet that receives the 1 to 5 points; Performing a primary filtering of the received diets, and at least one of a food cost optimization algorithm, a calorie optimization algorithm, and a nutrient optimization algorithm (N-1) of the plurality of recommended dishes from the one-user household user to the one of the household users by applying the recommended filtering to the user with the preferred filtering through the mobile terminal (N-1) number of food items selected through the mobile terminal, wherein the remaining food items are selected from among (N-1) number of At least one of the meal cost optimization algorithm, the calorie optimization algorithm, and the nutrient optimization algorithm is applied to the remaining food ingredients, based on the material optimization algorithm based on the food ingredients available for purchase within the remaining meal expenses, And applying the remaining food items to the one-person household user to transmit the Nth diet to the mobile terminal And < / RTI >

At least one of the food cost optimization algorithm, the calorie optimization algorithm, and the nutrient optimization algorithm may calculate the price information of the ingredients using public data including the agricultural and horticultural retail price data.

The food price optimization algorithm uses price data of at least one of a traditional market, a large-sized mart, and a small-sized mart together with agricultural and slaughterhouse retail price data to generate a price error range or price error data, Or by providing the price error data to the one-person household user as reference data when ordering or purchasing food ingredients.

The food cost optimization algorithm may include calculating a predetermined food cost per meal including an error range based on the desired food ratio and the desired number of cuts in the preferred food group selected by the one-person household user.

Wherein the calorie optimization algorithm is a calculation of the calorie optimization algorithm based on the personal information received from the one household user, wherein the personal information includes the sex, birth year, body size, and / Calculating at least one of a body mass index (BMI) and a basal metabolic rate of a user of a household to calculate an average daily recommended calorie of the one-user household user; Calculating a difference between a recommended calorie amount per meal of the household user and a calorie amount of the recommended diet recommendation and sorting the differences in ascending order to recommend a diet through the mobile terminal can do.

The nutrient optimization algorithm may include calculating a NAR (Nutrition Adequacy Ratio) value that is a ratio of a specific nutrient intake amount to a recommended nutrient intake amount per day, calculating a Mean Adequacy Ratio (MAR) that is an average of the NAR values of each nutrient And a step of recommending the food order through the mobile terminal in the order of decreasing R value to the household user by arranging the order of | 1 - MAR | = R in a small order.

The material optimization algorithm may include recommending an N-th diet based on the ingredients available for purchase within the remaining meal cost range obtained by subtracting the meal ratio of (N-1) diets from the input desired meal ratio X. [

Wherein the material optimization algorithm comprises: sorting the ingredients of the (N-1) diets into a total sum of the ingredients of the ingredients; calculating the amount of the remaining ingredients after converting the amount of the necessary ingredients to integer values; Determining that the food is a foodstuff owned by the user of the one household when the remaining foodstuff is 0 or more; calculating a recommended foodstuff including the stored foodstuffs; And applying the nutrient optimization algorithm once more to provide a final Nth recommended diet.

The method of providing a meal recommendation service for a household includes the steps of delivering a foodstuff and receiving a desired delivery date and a desired time from a store where a delivery service is available based on the position of the one- And informing the user of the one household when the packaging of the foodstuffs requested by the one-user household user is completed at the store where the delivery service is not available.

The method of providing a meal recommendation service for a single-person household is characterized in that the marts around the residence of the single-person household within the range of the desired meals inputted from the single-user household user are classified into at least one of a large- And comparing the price information of the discount price with the price information of the low price mart.

When the price information is compared, the step of recommending a meal to the one-person household user based on the daily food expenses, the one-month food expenses, the one-month food expenses, the seasonal food expenses, and the food cost data for the age and sex of the other single- .

According to the method of providing a recommendation service for a single-person household according to the embodiments of the present invention, it is possible to reduce the burden of the food required for a single person by using a mobile application, Enabling a customized diet that is optimized for a growing number of single-person household users.

In addition, it is possible to cook as much as the amount of food that a single user wants, and the amount of material remaining after cooking can be minimized by a single user, and convenience of cooking can be improved have.

FIG. 1A is a flowchart illustrating a method of providing a recommendation service for a single-user household according to an exemplary embodiment of the present invention. Referring to FIG. 1A, The number of meals, and the N-th diet recommendation step.
FIG. 1B is a flowchart showing the steps from the recommendation step of the Nth number of desired dishes received from the household user, which is one of the methods of providing a meal recommendation service for a single-user household user, to receiving the dietary material.
FIG. 2 is a screen for receiving personal information from a single user in a mobile terminal according to a preferred embodiment of the present invention.
FIG. 3 is a screen for receiving a desired food purchase shop and a desired number of weddings from a household user in a mobile terminal according to a preferred embodiment of the present invention.
FIG. 4A is a screen for inputting a preferred food price and a preference score for a meal from a household user in a mobile terminal according to a preferred embodiment of the present invention.
FIG. 4B illustrates an MF (Matrix Factorization) algorithm that primarily performs a filtering process on the basis of a preference input from a household user in a mobile terminal according to a preferred embodiment of the present invention.
FIG. 5 is a screen for selecting a menu from a household user in a mobile terminal according to a preferred embodiment of the present invention.
FIG. 6 is a diagram illustrating a dietary recommendation and food ingredient calculation algorithm according to a preferred embodiment of the present invention.
7 is a food price optimization algorithm according to a preferred embodiment of the present invention.
Figure 8 is a calorie optimization algorithm in accordance with a preferred embodiment of the present invention.
9 is a nutrient optimization algorithm according to a preferred embodiment of the present invention.
10 is a material quantity optimization algorithm according to a preferred embodiment of the present invention.
FIG. 11 illustrates a screen for ordering food ingredients from a single-user household user according to a preferred embodiment of the present invention.
FIG. 12 is a list of my menu lists showing a list of recommended diets selected from a single-user household user according to a preferred embodiment of the present invention.
FIG. 13 is a screen for receiving an order and a delivery service from a single-user household user according to a preferred embodiment of the present invention.

FIG. 1A is a flowchart illustrating a method of providing a menu recommendation service for a single-user household user according to an exemplary embodiment of the present invention. Referring to FIG. 1A, The recommended number of dishes, and the N-th recommended dietary recommendation stage.

Referring to FIG. 1A, an embodiment of the present invention receives personal information of a single household user through a mobile terminal from a single household user (step 10). The process of receiving personal information of a single-user household user will be described later with reference to FIG.

Thereafter, at least one of a large-sized mart, a small-sized mart, and a traditional market is selected as a place where a single-user user wants to buy food (Step 20). The process of selecting a place such as a shop where a user of one person wants to purchase a food material will be described later with reference to Fig.

The desired food ratio X and the desired number of nights N are input from the one-person household user (step 30). Using the inputted desired food ratio X and the desired number of dishes N, the food cost optimization algorithm shown in FIG. 7 is applied to recommend a meal (step 40). The above-mentioned food cost optimization algorithm will be described later with reference to FIG.

Based on the inputted personal information, the calorie optimization algorithm of FIG. 8 is applied to calculate the recommended calorie consumption per person and the calorie difference of the recommended food group for the one-person household user, and arranges the foods in order of decreasing calorific value (Step 50).

Thereafter, the nutrient optimization algorithm of FIG. 9 is applied to evaluate the nutrient quality of the sorted diet in step 50, and a nutrient optimization algorithm is applied to a single-user household user (step 60). The nutrient optimization algorithm will be described below with reference to FIG. (N-1) of the food items selected from the users of the household 1 (N-1) is compared with N (N-1) Is recommended for a household user (step 80).

FIG. 1B is a flowchart illustrating a procedure from the recommendation step N to the delivery step of the desired number of dishes received from the household user, which is one of the methods of providing a recommendation service for a single-user household user according to an embodiment of the present invention.

Referring to FIG. 1B, step (step 80) of recommending an N-th diet including food materials based on the ingredients of the remaining diets excluding the (N-1) The last Nth diet is selected from the user (step 90).

The desired delivery time is input from the selected store to deliver the selected food items from the one-person household user (step 100). (Step 110). If the store is able to deliver the food, the food is received at the entered delivery time (step 130). If the store can not provide the delivery service (for example, , Some small and medium-sized marts), the user inputs a purchase order (120) after the order is placed.

FIG. 2 shows a screen for receiving personal information from a household user in the mobile terminal according to a preferred embodiment of the present invention.

Referring to FIG. 2, the personal information is inputted from the one-person household user on the information input screen 200. The personal information of the single-user household user includes a location information providing agreement 201, a birth year 202, a key 203, a weight 204, and an activity level 205. Based on the inputted personal information, the calculation results of the average daily required calories 211, the current weight 212, the healthy weight 213 and the obesity 214 of the single-user household user are displayed on the nutrition screen 210 . The personal information may include gender, birth year, body size, and / or activity level. Once the above calculations are completed, a personalized menu can be recommended for a single-user household.

FIG. 3 shows a screen for receiving a desired food purchase shop and a desired number of dishes from a single-user household user in a mobile terminal according to a preferred embodiment of the present invention.

Referring to FIG. 3, first, a user who wants to buy the foodstuff is input from a household user to calculate the value of the foodstuff. The desired store may be selected from at least one of a large mart button 310, a small mart button 320, and a traditional market button 330. If the on-line delivery service is not provided and the price information of the ingredients is not known, the price can be calculated using the ingredient price information of the public data. The public data may be public data provided by the agricultural, forestry, livestock and dairy department sites such as agricultural and fishery retail price data.

In the case of FIG. 3, it is assumed that the store is recommended based on the location of a single-user household and the 'open market' is selected from a single-user household user. The mobile terminal receives the desired period and the number of weddings N from the household user on the calendar screen 340 and informs the one-person household user of the input result about the desired period and the desired number of weddings N through a predetermined phrase. For example, if the user of one person clicks on the calendar screen 340 of FIG. 3 by the desired number of times N with the desired institution, the desired period and the number of the meal N selected by the user are calculated and output under the calendar screen 340 .

FIG. 4A is a screen for inputting a preferred food price and a preference score for a meal from a household user in a mobile terminal according to a preferred embodiment of the present invention.

Referring to FIG. 4A, the desired food ratio X for the desired number of nights N is input from the one-person household user to the desired food cost input box 410 in the desired food cost input screen. For example, assuming that a user who is one person in the input screen for inputting the food expenses has received a meal cost of 20,000 won for four meals considering the living cost of one month, an average food cost of 5,000 won per meal may be calculated. In order to recommend a preferred diet of a household user from one household user after the food expense input step, the user inputs a preference of 1 point to 5 points for the sample food on the food preference score input screen 420.

FIG. 4B illustrates an MF (Matrix Factorization) algorithm 430 for primarily filtering a menu based on a menu preference input from a household user in a mobile terminal according to a preferred embodiment of the present invention.

Referring to FIG. 4B, the MF algorithm 430 is a method of predicting unexpected values through factorization of a matrix. That is, the matrix V can be decomposed into a latent matrix of W and H, so that a null value can be predicted to reflect the preference of a potential user of a single user. In addition, the MF algorithm 430 has an advantage that prediction can be performed even without initial data. As the data of the selected food is gradually accumulated from one household user, the prediction of the favorite food of the household user can be increased. The MF algorithm 430 may be used to digitize the scores of the recommended diets inputted from the household user of one person so that the divergence can be primarily filtered based on the expectation that the preference is high on the basis of 4 points to 5 points.

FIG. 5 is a screen for selecting a menu from a household user in a mobile terminal according to a preferred embodiment of the present invention.

Referring to FIG. 5, there is shown a screen of a menu selected from a household user based on the desired food ratio X and the desired number of dishes N received from a single household user. Algorithms for implementing the present invention are divided into two algorithms in order to recommend N diets, which is a desired number of dishes desired by a household user. The first step is a process for selecting (N-1) recommended diets. The first step is to select one (N-1) The algorithm for optimizing the amount of the material of FIG. 10 is applied, the first filtering 640 is performed, and the Nth diet is recommended.

Referring to FIG. 5, the N-th meal is recommended to a household user who has one meal including the N-th meal after applying the material quantity optimization algorithm of FIG. For example, if the user selects 4 (N = 4) number of weddings for four days and inputs the desired food expenses of 20,000 won, the user can enjoy cooking with the preferred food group of the input user within the range of 20,000 won (N-1 = 3) is recommended first, and the other meal (N-th meal) is recommended to the one-person household user by newly loading the recommended diet by applying the material amount optimization algorithm of FIG. .

The user of one household can add, delete or modify the selected menus through the selection menu 510 and confirm the total amount of the selected recommended menu through the accumulated amount 520. When the selection of the menu is completed, information on the recommendation, nutrition, calorie, etc. of the menu can be checked.

FIG. 6 is a flowchart illustrating a method of calculating a food recommendation and a food ingredient according to a preferred embodiment of the present invention.

Referring to FIG. 6, the food recommendation and food ingredient calculation algorithm is roughly divided into two steps in order to recommend foods for the number N of desired dishes to a household user.

The first step is to input a preference of 1 to 5 points for the sample diet from the household user who is 1 for the (N-1) recommended dietary recommendation selection, and 1 After the difference filtering is performed 610, the food cost optimization algorithm 730 of FIG. 7, the calorie optimization algorithm 621 of FIG. 8, and the nutrient optimization algorithm of FIG. 9 are applied 910, (631) and selects (N-1) diets from among the plurality of customized diets from the one-person household user (632).

The second step is to first pass (640) through the quantity optimization algorithm 1000 of the material of Figure 10 based on the selected diets and to perform the first order filtering on the food cost optimization algorithm 730 of Figure 7, the calorie optimization algorithm of Figure 8, The nutrient optimization algorithm 910 of FIG. 9 is applied in the same manner as the first step (650), and the Nth diet is selected (662) through a recommendation step 661 of recommending the Nth diet to minimize the waste of the ingredients.

FIG. 7 is a flowchart illustrating a food price optimization algorithm according to a preferred embodiment of the present invention. Referring to FIG. 7, first, personal information is input from a single household user through a mobile terminal (step 710).

Then, the one-person household user receives the desired food ratio X and the desired number of dishes N through the mobile terminal (step 720). Using the input desired food ratio X and the desired number of dishes N, the range of the appropriate food ratio per meal is calculated using the following equation (1) (step 730).

는 각 끼니당 오차이며,

는 i번째 식단의 식비를 의미한다. 상기 수학식 1을 이용한 한 끼당 식비가 계산되면 도 8의 칼로리 최적화 알고리즘(910)을 적용한다.X is the desired meal cost input by the user of the household having one person, N is the number of desired dishes,

Is the error per meal,

Means the food ratio of the i-th diet. When the food ratio per one meal using the equation (1) is calculated, the calorie optimization algorithm 910 of FIG. 8 is applied.

In the embodiment of the present invention, the public data provided by the agriculture, forestry, and livestock food and beverage site such as the agricultural / fishery retail price data can be utilized when the food expenses of the single-user households are managed through the algorithm for optimizing the food expenses, nutrition and material amount. In particular, if there is no on-line delivery service and stores where price information is unknown, material price information of public data can be utilized.

Price data of traditional markets, large marts, and small and medium marts offered at the Korea Consumer Agency's true price site can be provided for users to use as reference data when ordering ingredients. The price data of traditional markets, large marts, and small and medium marts provided by the Korean Consumer Price Index site are used together with the retail price data of agricultural and marine products to generate price error range or price error data and provide users with price error range or price error data So that the user can be assisting in the purchase or purchase of the food.

8 is a flowchart illustrating a calorie optimization algorithm according to a preferred embodiment of the present invention. The calorie optimization algorithm includes a step of receiving personal information of a user through a mobile terminal from a household user (step 810), a step of calculating a BMI and a basic metabolic rate of a household user (step 820) (Step 830), calculating a recommended calorie value per meal and a recommended calorie calorie difference (step 840), calculating a difference between the recommended calorie value per meal and the recommended calorie value per meal And recommending the diets in order (step 850).

을 계산한다. NAR(Nutrition Adequacy Ratio)값은 1인 가구 사용자의 1일 특정 영양소 섭취량과 특정 영양소 권장 섭취량의 비율을 의미하며 n번째 영양소까지 각각의 비율을 구한다. 상기 n번째 영양소까지 NAR값의 평균 수치인 MAR(Mean Adequacy Ratio)값을 산출한다. 상기 MAR 값이 1에 가까울수록 상기 영양소의 질이 높은 것을 의미한다. 상기 추천된 개별 식단에서 상기 MAR값을 계산하여 상기 추천된 영양소의 품질을 평가하는 단계를 거친다. 이후, |1 ― MAR값|= R 이라 가정하여 상기 R 값이 작은 순서대로 정렬하여 식단을 1인 가구 사용자에게 추천하는 단계를 거친다. 1인 가구 사용자에게 추천하는 단계 이후 N 번째 식단 추천을 위한 재료 양 최적화 알고리즘을 거치게 된다.9 is a table for explaining a nutrient optimization algorithm according to a preferred embodiment of the present invention. The nutrient optimization algorithm is a step of converting the recommended nutrient intake provided by the Korean Nutrition Society into the recommended amount of the individual nutrient intake. First, Z means the dietary content of the second nutrient and calculates Z. Then, the ratio of the recommended number of dishes to the recommended recommended intake of the nth nutrient

. The NAR (Nutrition Adequacy Ratio) value is the ratio of specific nutrient intake per day to the recommended nutrient intake for a household with 1 person. And calculates the Mean Adequacy Ratio (MAR), which is an average value of the NAR values, up to the nth nutrient. The closer the MAR value is to 1, the higher the quality of the nutrient. And evaluating the recommended nutrient quality by calculating the MAR value at the recommended individual diet. Thereafter, it is assumed that the value of | 1 - MAR is | = R, and the R value is sorted in ascending order to recommend a meal to a household user. After the recommendation step to the one-person household user, it goes through the material quantity optimization algorithm for recommending the N-th diet.

10 is a table for explaining the material amount optimization algorithm according to a preferred embodiment of the present invention. In the N-th diet, the N-th diet is recommended based on the remaining ingredients of the diet (N-1 diets) excluding one from the input desired number of dishes N.

As shown in FIG. 10, after arranging the ingredients of the (N-1) diets, they are sorted into the total of the ingredients. After arranging the food materials of the (N-1) number of food items and arranging them into the total of the ingredients, the amount of the necessary ingredients is converted into an integer value, and the remaining amount of the ingredients is calculated. If it is more than 0, it is judged that the food is owned by the user of one person. After calculating the recommended diets containing the ingredients, the dietary optimizing algorithm of Fig. 7, the calorie optimization algorithm of Fig. 8, the nutrient optimization algorithm, and the last N-th recommended dietary recommendation are provided. When the material amount optimization algorithm of FIG. 9 is completed, the screen is switched to the delivery screen.

FIG. 11 illustrates a screen for ordering food ingredients from a single-user household user according to a preferred embodiment of the present invention. Food orders can be ordered immediately after selection from a single-person household user up to the Nth recommendation.

Referring to FIG. 11, a list of total ingredients of the recommended diets from the mobile terminal can be selected from a household user with one shown in the material information screen 1100. When the payment is completed in the shop desired to be delivered in FIG. 3, the order form is transmitted to the shop, and the delivery step proceeds.

FIG. 12 is a menu listing screen 1200 showing a list of recommended diets selected from a single-user household user according to a preferred embodiment of the present invention.

Referring to FIG. 12, when the satisfaction score 1210 is inputted from a household user for one of the selected diets, a function to be reflected in the recommendation of the next meal is included. In addition, the selected meal information can be confirmed for each desired period 1220, and the recipes 1230, nutrition information 1240, and material information 1250 of the selected food items during the desired period 1220 can be confirmed. For example, FIG. 12 shows a recommendation menu for a specific period selected from a household user and a menu list screen 1260 for the recommended menu.

FIG. 13 shows a screen 1300 for receiving an order and a delivery service from a single-user household user according to a preferred embodiment of the present invention. In the case of the ordering and delivery service, the food delivery service is realized by utilizing O2O, which is a technology for collecting consumers via online to induce commerce offline. The delivery service utilizes GPS and Geo-Fence, which are location-based service technologies, among the O2O technologies. The delivery service may be a large mart or a small mart in which a delivery system is built or a store in which food can be delivered in a traditional market and a store in which a delivery system is not built, If you place an order, the shop will confirm the order and prepare the ingredients. The one-person household user then receives the above-mentioned ingredients ordered from the store. In the case of the ordering and delivery service, the price information of the marts (for example, a large mart, a small mart, and a traditional market) around a residence of a single user is compared within the range of the desired food expenses inputted from the one- Quot; service " The ordering and delivery service also recommends one-person furniture user based on the data on the one-month, one-month food expenses (seasonal), age group, Services that you provide.

210: My Nutrition Screen 220: Daily Average Calories Required
230: current weight 240: healthy weight
250: Obesity 310: Large Mart Button
320: Small and Medium Mat Button 330: Traditional Market Button
340: Calendar screen 410: Enter the desired food bill
420: Entering a preference score score screen 510: Selection menu screen
520: Cumulative amount screen 1100: Material information screen
1200: My Diet List Screen 1210: Satisfaction Score
1220: Hope period 1230: Recipe
1240: Nutrition information 1250: Material information
1300: Screen for receiving order and shipping service

Claims (14)

N is a natural number - and a desired food ratio X - where X is an integer; And
At least one of nutrient, calorie, and the amount of foodstuffs at the desired food ratio X ratio with respect to the desired number of dishes N based on the input desired food ratio N and the desired food ratio X, And recommending to the one-user user through the mobile terminal a diet within a range of the input desired food ratio,
The amount of nutrition, calorie, and foodstuffs in the desired food ratio X ratio with respect to the desired number of dishes N, in accordance with the inputted desired food ratio X, based on the inputted number N of desired dishes and the inputted desired food ratio X through the mobile terminal And recommending at least one meal to the one user through the mobile terminal within a range of the input desired food ratio,
Receiving from the one-user household user a score of one to five points in a dietary range within the range of the input food expenses;
Applying a MF (Matrix Factorization) algorithm to the diets to which the 1 to 5 points are inputted; performing first filtering on the diets having 4 to 5 points; And
Further comprising the step of calculating a meal price per meal based on the desired food ratio X and the desired number of dishes N. The method of claim 1, delete The method according to claim 1,
The step of calculating the above-mentioned food-to-be-cooked food ratio includes the steps of:

Where X is the desired food expense entered by a household user with 1, N is the number of desired dishes,

Is the error per meal,

Wherein the meal recommendation service is a meal cost of the i-th diet. The method according to claim 1, further comprising: determining whether the desired food ratio X is greater than the desired food ratio N based on the input desired food amount N and the inputted desired food ratio X, Calculating at least one of nutrition, calories, and the amount of foodstuff to the one user and recommending the one meal within the input desired food ratio range through the mobile terminal
Receiving a score of one to five points from the one-person household user on the basis of the desired number of dishes N received from the one-person household user;
Performing a first-order filtering on the diets having 4 points to 5 points by applying the MF algorithm to the 1-point-to-5-point input;
Applying at least one of a food price optimization algorithm, a calorie optimization algorithm, and a nutrient optimization algorithm to the first filtered filtered menu to recommend the one-person household user through the mobile terminal, Selecting among (N-1) dietary terms among the plurality of dietary terms through the mobile terminal; And
(N-1) diets through the mobile terminal, wherein the remaining food is stored in the remaining food expenses range obtained by subtracting the food ratio of the (N-1) - applying at least one of the food price optimization algorithm, the calorie optimization algorithm, and the nutrient optimization algorithm to the remaining food items to apply an Nth diet to the remaining food ingredients, A step of recommending the one-user household user through the mobile terminal
Wherein the recommendation service is provided for a one-person household. 5. The method according to claim 4, wherein at least one of the food cost optimization algorithm, the calorie optimization algorithm and the nutrient optimization algorithm calculates price information of the ingredients using public data including agricultural / How to Provide Dietary Recommendation Services for Households. 5. The method of claim 4, wherein the food cost optimization algorithm utilizes price data of at least one of a traditional market, a large-sized mart, and a small-sized mart together with agricultural and slaughterhouse retail price data to generate price error range or price error data, And providing the price error range or the price error data to the user as reference data when ordering or purchasing a food ingredient to the one-person household user. 5. The method according to claim 4, wherein the food cost optimization algorithm includes calculating a predetermined meal cost per meal including an error range based on the desired food ratio and the desired number of cuts in the preferred food group selected by the one-
Wherein the recommendation service is provided for a one-person household. 5. The method of claim 4, wherein the calorie optimization algorithm comprises: receiving personal information input from the one household user, wherein the personal information includes a gender, birth year, body size, and / Calculating at least one of a body mass index (BMI) and a basic metabolic rate of the user of the one-person household based on the daily average recommended calorie of the one-user household user;
Converting the average daily recommended calories of the one-person household user into the recommended daily calories per person; And
Calculating divergence between recommended calorie consumption per meal and calorie recommendation of the one-person household user and recommending the diet through the mobile terminal by sorting the differences in ascending order;
Wherein the recommendation service is provided for a one-person household. [5] The method of claim 4, wherein the nutrient optimization algorithm comprises: calculating NAR (Nutrition Adequacy Ratio) value as a ratio of a specific nutrient intake amount to a recommended nutrient intake amount per day;
Calculating a Mean Adequacy Ratio (MAR) that is an average of the NAR values of each nutrient; And
1 - MAR | = R values in ascending order and recommending the food order to the one-user household user through the mobile terminal in order of decreasing R value
Wherein the recommendation service is provided for a one-person household. The method according to claim 4, characterized in that the material optimization algorithm recommends an N-th diet based on the ingredients available for purchase within the remaining meal cost range obtained by subtracting the food ratio of the (N-1) A method for providing a recommendation service for a single person having a meal. 11. The method of claim 10, wherein the material optimization algorithm comprises: sorting the ingredients of the (N-1) diets into a total sum of the ingredients;
Calculating an amount of the remaining foodstuff after converting the amount of the necessary foodstuff to an integer value and determining that the remaining foodstuff is a foodstuff owned by the one-user household user when the remaining foodstuff is 0 or more; And
A recommended calorie optimization algorithm, a calorie optimization algorithm, and a nutrient optimization algorithm, and then providing a final Nth recommended dietary supplement
Wherein the recommendation service is provided for a one-person household. [2] The method of claim 1, wherein the method further comprises a step of delivering a foodstuff item, wherein the method comprises the steps of: Receiving a desired time, informing the one-person household user of the completion of the packaging of the foodstuffs requested by the one-person household user at the store where the delivery service is not possible
Wherein the recommendation service is provided for a one-person household. The method according to claim 1, wherein the method for providing a meal recommendation service for the one-person household includes the steps of: And recommending a low cost mart by comparing price information of at least one of the traditional market and the traditional market. 14. The method according to claim 13, wherein when the price information is compared, the one-person household user is instructed by the user on the basis of the daily food expenses, the weekly food expenses, the monthly food expenses, the seasonal food expenses, And recommending the recommendation service for the one-person household.

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