CN110362739A - A kind of recommending recipes method based on big data - Google Patents
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- 238000000034 method Methods 0.000 title claims abstract description 17
- 239000002994 raw material Substances 0.000 claims abstract description 80
- 239000000463 material Substances 0.000 claims abstract description 56
- 235000015097 nutrients Nutrition 0.000 claims abstract description 18
- 235000019640 taste Nutrition 0.000 claims abstract description 18
- 235000012054 meals Nutrition 0.000 claims abstract description 12
- 235000005686 eating Nutrition 0.000 claims description 11
- 235000013305 food Nutrition 0.000 claims description 8
- 241000251468 Actinopterygii Species 0.000 claims description 6
- 150000001720 carbohydrates Chemical class 0.000 claims description 6
- 235000013372 meat Nutrition 0.000 claims description 6
- 241001122767 Theaceae Species 0.000 claims description 3
- 239000002253 acid Substances 0.000 claims description 3
- 235000009508 confectionery Nutrition 0.000 claims description 3
- 102000004169 proteins and genes Human genes 0.000 claims description 3
- 108090000623 proteins and genes Proteins 0.000 claims description 3
- 238000005259 measurement Methods 0.000 claims description 2
- QCVGEOXPDFCNHA-UHFFFAOYSA-N 5,5-dimethyl-2,4-dioxo-1,3-oxazolidine-3-carboxamide Chemical compound CC1(C)OC(=O)N(C(N)=O)C1=O QCVGEOXPDFCNHA-UHFFFAOYSA-N 0.000 claims 1
- 102000002322 Egg Proteins Human genes 0.000 claims 1
- 108010000912 Egg Proteins Proteins 0.000 claims 1
- 235000014103 egg white Nutrition 0.000 claims 1
- 210000000969 egg white Anatomy 0.000 claims 1
- 230000003252 repetitive effect Effects 0.000 description 8
- 238000007405 data analysis Methods 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 3
- 235000005911 diet Nutrition 0.000 description 3
- 235000016709 nutrition Nutrition 0.000 description 3
- 230000000378 dietary effect Effects 0.000 description 2
- 238000001228 spectrum Methods 0.000 description 2
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- 238000004364 calculation method Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000037213 diet Effects 0.000 description 1
- 235000006694 eating habits Nutrition 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 230000005802 health problem Effects 0.000 description 1
- 239000004615 ingredient Substances 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 230000035764 nutrition Effects 0.000 description 1
- 230000001932 seasonal effect Effects 0.000 description 1
- 235000014347 soups Nutrition 0.000 description 1
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- 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 present invention relates to Catering Management fields, are specifically related to a kind of recommending recipes method based on big data.The information of the every meal of collecting sample diner, constitute big data, raw material information library, dish essential information library and diner's information bank are established according to the information of the every meal of sample diner, raw material information library includes at least 3 kinds of essential informations, respectively material name, cost of material and material nutrient component；Dish essential information library includes at least 4 kinds of information, dosage, dish classification and the dish taste of menu name corresponding to the dish for respectively raw material in raw material information library being used to cook out, every kind of raw material included by the dish；Diner's information bank includes at least 4 kinds of information, number of respectively having dinner, expense, everyone labor intensity, season.It can recommend recipe out in Best-ever Recipes library according to the time of the number of dining personnel, expense, labor intensity and dining, meet the needs of diner.Existing receipe data can be efficiently used, accurately recipe is recommended out.
Description
Technical field
The present invention relates to Catering Management fields, are specifically related to a kind of recommending recipes method based on big data.
Background technique
The continuous improvement of living standard, people increasingly pay close attention to dietetic nutrition health problem, and individual wants to understand the body of oneself
Whether body situation lacks certain nutrient, and whether the eating habit for understanding oneself is healthy, formulates individual nutritional diet.It is tied from the age
Structure, labor intensity, physical fitness etc. are many-sided to be considered, scientific recipe is recommended.
It then can not be the nutrient health of various demand in the case of Various Complex if receipe data is difficult to efficiently use analysis
Recipe, which generates to provide, accurately suggests.It is last the result is that a large amount of original recipe data under retaining, but fail to efficiently use.
The method of existing recommending recipes, it is difficult to efficiently use existing receipe data, accurately recipe cannot be recommended out.
Summary of the invention
In order to solve the above technical problems, the present invention provides a kind of recommending recipes method based on big data, it can be effective
Using existing receipe data, recommend out accurately recipe.
To achieve the above object, the invention adopts the following technical scheme:
A kind of recommending recipes method based on big data, includes the following steps:
S1, the information of the every meal of collecting sample diner constitute big data, are established according to the information of the every meal of sample diner former
Expect information bank, dish essential information library and diner's information bank, raw material information library includes at least 3 kinds of essential informations, respectively former
Expect title, cost of material and material nutrient component；Dish essential information library includes at least 4 kinds of information, is respectively believed using raw material
Dosage, the dish class of menu name corresponding to the dish that raw material in breath library cooks out, every kind of raw material included by the dish
Other and dish taste；Diner's information bank includes at least 4 kinds of information, number of respectively having dinner, expense, everyone labor intensity, season
Section；
S2 establishes recipe template library, and the information in raw material information library, dish essential information library and diner's information bank is inserted
To the corresponding position of recipe template library, the recipe template library inserted after information is recipe library, and recipe library includes raw material information
Library, dish essential information library and diner's information bank；
Respective mark is arranged to every kind of information in recipe library in S3, and the recipe library after setting mark is Best-ever Recipes
Library, Best-ever Recipes library include the use in the raw material information library of setting mark, the dish essential information library of setting mark and setting mark
Meal person's information bank, i.e. Best-ever Recipes library include material name mark, cost of material mark, material nutrient component mark, dish name
Claim dosage mark, dish classification logotype, dish the taste mark, number of having dinner mark of every kind of raw material included by mark, the dish
Know, expense mark, everyone labor intensity mark, season mark；It is identified to needing the information for the personnel of eating to be arranged, the mark and food
The message identification composed in diner's information bank in selected library is corresponding, by the information input for needing the personnel of eating of setting mark
To Best-ever Recipes library；
S4, everyone labor intensity in the information for needing the personnel of eating identified according to setting identifies and number mark of having dinner
Know, calculate total labor intensity mark, heat is calculated according to total labor intensity mark；Material nutrient component mark includes at least
Albumen qualitative character p, fat mark f, carbohydrate identify c, and the quality m of protein mark p is calculated according to calorimeterp, fat
Identify the quality m of ff, carbohydrate mark c quality mc；The objective function for establishing recipe, according to every kind of raw material of unit mass
Quality, the quality of f, the quality of c of p contained by name identification establishes constraint condition, and target letter can be made by calculating under constraint condition
The smallest material name mark of number, and then generate recommending recipes.
Further, specific step is as follows by step S4:
Total labor intensity identifies=has dinner everyone labor intensity mark of number mark *
The total labor intensity mark/a of J=, a is constant, and J is heat
mp=J/d1,mf=J/d2,mc=J/d3,d1、d2、d3It is constant
Constraint condition are as follows:
N is the sum of material name mark,Name is identified for i-th of material nameiQuality,For i-th of original
Material unit mass contains the quality of p,Contain the quality of f for i-th of feed material quality,For i-th of feed material quality
Quality containing c, each i-th of feed material quality WithIt is constant；
Objective functionqiFor the price of i-th of material name mark, wants to buy and buy all material names
When the corresponding raw material of mark needs expense min to obtain minimum valueValue；It is zero, then does not include raw material in recipe
Name identification is nameiRaw material be otherwise identified as name comprising material name in recipeiRaw material；
Minimum value is obtained according to objective function, obtains the menu name mark of recommendation.
Further, before generating Best-ever Recipes library, recipe library is adjusted, 3 kinds of adjustment modes are included at least, respectively to food
Library is composed to increase dish, delete the dish and replacement dish in recipe library.
Further, dish taste includes at least inclined sweet tea type, meta-acid type, partially peppery type, partially bitter type.
Further, raw material information library further includes measurement unit.
Beneficial effects of the present invention are as follows:
(1) can be recommended in Best-ever Recipes library according to the time of the number of dining personnel, expense, labor intensity and dining
Recipe out meets the needs of diner.Existing receipe data can be efficiently used, accurately recipe is recommended out.
(2) method of recommending recipes of the invention is identified by setting, can be improved the accuracy of recommending recipes, more preferably
Meet the needs of dining personnel.
(3) present invention in raw material storage, dish library during formulation, fully consider the individual characteies such as timeliness, spatiality because
Element, so that the raw material and dish in raw material storage, dish library are more in line in terms of economy, taste preference
User's actual need guarantees the accuracy in recipe source.
Detailed description of the invention
Fig. 1 is the principle of the present invention figure；
Fig. 2 is the schematic diagram with appraisal procedure of the invention.
Specific embodiment
With reference to embodiments and Figure of description, the technical solution in the present invention is clearly and completely described.Base
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts it is all its
His embodiment, shall fall within the protection scope of the present invention.
Embodiment 1
The method of recommending recipes, includes the following steps:
S1, the information of the every meal of collecting sample diner establish raw material information library, dish according to the information of the every meal of sample diner
Meat and fish dishes essential information library and diner's information bank, as shown in Figure 1, raw material information library includes at least 3 kinds of essential informations, respectively raw material
Title, cost of material and material nutrient component；Dish essential information library includes at least 4 kinds of information, respectively menu name, raw material
Dosage, dish classification and dish taste；Diner's information bank include at least 4 kinds of information, number of respectively having dinner, expense, everyone
Labor intensity, season；Establish recipe template library.
In the present embodiment, dish library includes raw material information library and dish essential information library, establishes raw material information library, and input is former
When material, user can input raw material according to actual needs, need to safeguard the information such as nutritional ingredient and the procurement price of raw material, Ke Yijie
It closes local characteristic raw material and season raw material establishes raw material information library, it is contemplated that economy, characteristic raw material and seasonal cost of material
It is lower, while can also meet the constitution of locals.Meanwhile real-time servicing can be carried out to raw material information library according to the actual situation.
In the present embodiment, as shown in Fig. 2, raw material information library can also include at least material name, cost of material, raw material battalion
It forms point；Dish essential information library can also include at least dish classification belonging to raw material dosage, raw material, dish belonging to raw material
Taste, dish skill and technique；Diner's information bank can also include at least the meal time, number of having dinner, expense, labor intensity, season,
Dish repetitive rate, raw material repetitive rate, wherein dish repetitive rate be setting time in dish cannot duplicate number, raw material repetitive rate
It cannot duplicate number for raw material in setting time.
S2 generates dish library by raw material information library and dish essential information library, and dish library includes several dish.
The information of the information in dish library and diner's information bank is filled into the corresponding position of recipe template library by S3, raw
At recipe library.
S4 adjusts recipe library, and user carries out recipe adjustment in combination with actual conditions after recipe generates, including newly-increased dish,
Delete the operations such as dish, replacement dish.
Respective mark is arranged in every kind of information of S5, recipe library, generates Best-ever Recipes library, Best-ever Recipes library, that is, rule base.
The recipe for being added to different identification is added into Best-ever Recipes library, the data basis as subsequent dietary analysis.
In the present embodiment, Best-ever Recipes library include material name mark, cost of material mark, material nutrient component mark,
The dosage mark of every kind of raw material included by menu name mark, the dish, is had dinner at dish classification logotype, dish taste mark
Number mark, expense mark, everyone labor intensity mark, season mark.
In the present embodiment, the step of create-rule library may be: the recipe library after setting mark is believed according to diner
Meal time, number of having dinner, expense, labor intensity, season, dish repetitive rate, raw material repetitive rate in breath library, in recipe library
Recipe divided, generate Best-ever Recipes library.
S6 uses data analysis algorithm to Best-ever Recipes library, calculates in dish essential information library and diner's information bank
The corresponding weight identified of every kind of information.
Using the data in data analysis algorithm statistics Best-ever Recipes library, i.e. each menu name in calculating Best-ever Recipes library
The number put is identified, according to the number arrangement menu name mark put, the arrangement serial number that each menu name is identified is made
For the weight of each menu name mark；The number that every kind of dish taste mark is selected is calculated to identify with all dish tastes by point
The ratio of number, the weight which identifies as every kind of dish taste；It calculates and uses under everyone every kind labor intensity mark
The quantity of dish classification logotype, the quantity identify the weight of lower dish classification logotype as everyone every kind labor intensity.
Using the magnanimity recipe information in Best-ever Recipes library as data warehouse, had using data analysis algorithm parsing, extraction
The receipe data of value, obtaining the habit, hobby of user, taste etc. under different application scene influences the user personality that recipe generates
Information.
Data analysis algorithm is mainly to the every dinner cost proportional region of the receipe data analytical calculation of magnanimity；Dish is analyzed to use
Frequency finds the most frequently used dish sequence；Analyze the dish taste preference of user, different taste proportion；Analyze different labor
Dish classification ratio under intensity；Setting condition weight etc..
Mark corresponding to the information for needing the personnel of eating is input to the Best-ever Recipes library after calculating weight by S7,
Using data analysis algorithm, recommending recipes are generated.
The corresponding mark of number in the information for needing the personnel of eating and/or the corresponding mark of expense and/or labour is strong
It spends corresponding mark and/or season corresponding mark is input to the Best-ever Recipes library after calculating weight.It is analyzed using data
Algorithm calculates the Best-ever Recipes library after weight and recommends recipe corresponding with each mark out, the recommendation food as generated
Spectrum.
In the present embodiment, be according to setting mark the information for needing the personnel of eating in everyone labor intensity mark and
Number of having dinner mark, calculates total labor intensity mark, calculates heat according to total labor intensity mark；Material nutrient component mark
Know and include at least albumen qualitative character p, fat mark f, carbohydrate mark c, the matter of protein mark p is calculated according to calorimeter
Measure mp, fat mark f quality mf, carbohydrate mark c quality mc；The objective function for establishing recipe, according to unit mass
Quality, the quality of f, the quality of c that every kind of material name identifies contained p establish constraint condition, calculate energy under constraint condition
Make the smallest material name mark of objective function, and then generates recommending recipes.
Specific step is as follows:
Total labor intensity identifies=has dinner everyone labor intensity mark of number mark *
J=total labor intensity mark/a, a are constant, and J is heat, a=12 in the present embodiment.
mp=J/d1,mf=J/d2,mc=J/d3,d1、d2、d3It is constant, the present embodiment d1=0.2, d2=0.3, d3=
0.5.Constraint condition are as follows:
N is the sum of material name mark,Name is identified for i-th of material nameiQuality,For i-th of original
Material unit mass contains the quality of p,Contain the quality of f for i-th of feed material quality,For i-th of feed material quality
Quality containing c, each i-th of feed material quality WithIt is constant；
Objective functionqiFor the price of i-th of material name mark, wants to buy and buy all material names
When the corresponding raw material of mark needs expense min to obtain minimum valueValue；It is zero, then does not include raw material in recipe
Name identification is nameiRaw material be otherwise identified as name comprising material name in recipeiRaw material；Raw material name is obtained later
Claim, according in recipe library, the raw material that each dish contains, Best-ever Recipes library can recommend out some dish come out, diner's root
According to expense, season, dish repetitive rate, raw material repetitive rate, the dish for meeting oneself is selected from these dish.
Embodiment 2
On the basis of embodiment 1, the recommending recipes of generation are assessed, the food recommended according to assessment result adjustment
Spectrum.
As shown in Fig. 2, the recommending recipes to generation are assessed, imposes a condition, protect if the recommending recipes generated meet
The recommending recipes are stayed, and the recommending recipes are recommended and need the personnel of eating；Otherwise, rule base generates recommending recipes again, directly
Recommending recipes to generation meet setting condition.The information inputted in step S7 can also be readjusted, until the recommendation generated
Recipe, which meets, to impose a condition.It is the mark of everyone labor intensity of adjustment input, pole severe labor intensity, severe in the present embodiment
Labor intensity, moderate labor intensity, slight labor intensity mark be respectively 23,22,21,20, such as everyone labour inputted
Intensity is identified as 23, in constraint condition, is inputted by the expense that the recommending recipes that objective function acquires generate greater than diner
Expense, then can by reduce labor intensity, i.e., selection labor intensity identify it is small.
In the present embodiment, the setting condition that the recommending recipes of generation meet include expense meet expense setting condition and/or
Raw material dosage meets the setting condition of raw material dosage and/or nutrient meets the setting condition of nutrient；The setting condition of expense is
Expense that the recommending recipes of generation generate and need the personnel of eating to rule base input expense difference absolute value with need to use
Meal personnel input the ratio of expense less than the first setting value to rule base；The setting condition of raw material dosage is everyone average dosage
With the absolute value of the difference of dosage standard value and the ratio of dosage standard value less than the second setting value, dosage standard value is constant；Battalion
The setting condition for supporting element is the nutrient of raw material included by the recommending recipes of generation and the absolute value of the difference of nutrient standard value
It is less than third setting value with the ratio of nutrient standard value, nutrient standard value is constant.
In the present embodiment, the first setting value, the second setting value, third setting value are 5%.
In the present embodiment, user can also assess from the subjective recipe to generation, use from dish collocation, raw material
Amount, board expenses using asks, science, trophism, the economy of nutrition-allocated proportion etc. analysis recipe, can part dish to recipe
Meat and fish dishes is edited, while can check the recipe purchasing of raw materials amount, and user is facilitated to purchase raw material.
Embodiment 3
On the basis of embodiment 1,2, the spring in season, the summer, the autumn, the winter mark be respectively 10,11,12,13；Dish classification
Staple food, big meat or fish, half meat or fish, small meat or fish, Quan Su, congee, soup, fruit mark be respectively 1,2,3,4,5,6,7,8；The mark of raw material dosage
The as weight of raw material；The mark of cost of material is the expense of Unit Weight raw material；The inclined sweet tea type of dish taste, meta-acid type, partially
Peppery type, the mark of partially bitter type are respectively 30,31,32,33.
Claims (5)
1. a kind of recommending recipes method based on big data, which comprises the steps of:
S1, the information of the every meal of collecting sample diner constitute big data, establish raw material letter according to the information of the every meal of sample diner
Library, dish essential information library and diner's information bank are ceased, raw material information library includes at least 3 kinds of essential informations, respectively raw material name
Title, cost of material and material nutrient component；Dish essential information library includes at least 4 kinds of information, respectively uses raw material information library
In the dish that cooks out of raw material corresponding to menu name, the dosage of every kind of raw material included by the dish, dish classification and
Dish taste；Diner's information bank includes at least 4 kinds of information, number of respectively having dinner, expense, everyone labor intensity, season；
S2 establishes recipe template library, and the information in raw material information library, dish essential information library and diner's information bank is filled into food
The corresponding position of template library is composed, the recipe template library after filling information is recipe library, and recipe library includes raw material information library, dish
Meat and fish dishes essential information library and diner's information bank；
Respective mark is arranged to every kind of information in recipe library in S3, and the recipe library after setting mark is Best-ever Recipes library, food
Compose diner's letter in the raw material information library that selected library includes setting mark, the dish essential information library of setting mark and setting mark
Cease library, i.e., Best-ever Recipes library include material name mark, cost of material mark, material nutrient component mark, menu name mark,
Dosage mark, dish classification logotype, dish taste mark, number of the having dinner mark, expense of every kind of raw material included by the dish
Mark, everyone labor intensity mark, season mark；Mark, the mark and Best-ever Recipes are arranged to the information for needing the personnel of eating
The message identification in diner's information bank in library is corresponding, needs the information input for the personnel of eating to recipe setting mark
Selected library；
S4, identify and have dinner according to everyone labor intensity in the information for needing the personnel of eating of setting mark number mark,
Total labor intensity mark is calculated, heat is calculated according to total labor intensity mark；Material nutrient component mark includes at least egg
White matter identifies p, fat mark f, carbohydrate and identifies c, and the quality m of protein mark p is calculated according to calorimeterp, fat mark
Know the quality m of ff, carbohydrate mark c quality mc；The objective function for establishing recipe, according to every kind of raw material name of unit mass
The quality, the quality of f, the quality of c that identify contained p is claimed to establish constraint condition, objective function can be made by calculating under constraint condition
The smallest material name mark, and then generate recommending recipes.
2. recommending recipes method as described in claim 1, which is characterized in that specific step is as follows by step S4:
Total labor intensity identifies=has dinner everyone labor intensity mark of number mark *
The total labor intensity mark/a of J=, a is constant, and J is heat
mp=J/d1,mf=J/d2,mc=J/d3,d1、d2、d3It is constant
Constraint condition are as follows:
N is the sum of material name mark,Name is identified for i-th of material nameiQuality,For i-th of raw material list
Position quality contains the quality of p,Contain the quality of f for i-th of feed material quality,Contain for i-th of feed material quality
The quality of c, each i-th of feed material quality WithIt is constant；
Objective functionqiFor the price of i-th of material name mark, wants to buy and buy all material name marks
When corresponding raw material needs expense min to obtain minimum valueValue；It is zero, then does not include raw material name in recipe
Title is identified as nameiRaw material be otherwise identified as name comprising material name in recipeiRaw material；
Minimum value is obtained according to objective function, obtains the menu name mark of recommendation.
3. recommending recipes method as claimed in claim 1 or 2, which is characterized in that before generating Best-ever Recipes library, adjustment food
Library is composed, 3 kinds of adjustment modes are included at least, respectively increases dish to recipe library, delete the dish and replacement dish in recipe library.
4. recommending recipes method as described in claim 1, which is characterized in that dish taste include at least inclined sweet tea type, meta-acid type,
Partially peppery type, partially bitter type.
5. recommending recipes method as described in claim 1, which is characterized in that raw material information library further includes measurement unit.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113096770A (en) * | 2021-04-20 | 2021-07-09 | 中国人民解放军陆军勤务学院 | Standard recipe generation method, generation system, processing terminal and storage medium |
| CN115147247A (en) * | 2022-09-06 | 2022-10-04 | 深圳鸿博智成科技有限公司 | Intelligent canteen-based recipe recommendation system and method |
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