CN112070583A - Chocolate formula generation system based on user taste - Google Patents
Chocolate formula generation system based on user taste Download PDFInfo
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Abstract
The invention discloses a chocolate formula generating system based on user taste, which comprises a collecting unit, a database, a matching analysis unit, a taste selecting unit, a formula generating unit and intelligent equipment, wherein the collecting unit is used for collecting chocolate; the acquisition unit is used for acquiring chocolate browsing related information in the user account record, automatically acquiring browsing information and transmitting the browsing information to the matching analysis unit; according to the invention, through the arrangement of the taste selection unit and the formula generation unit, data analysis is carried out on the collected related data, chocolate selection is carried out according to the result of the data analysis, and formula calculation is carried out on the selected chocolate, so that a new formula is obtained, the accuracy of data analysis is improved, the persuasion force of data is increased, the time consumed by analysis is saved, and the working efficiency is improved.
Description
Technical Field
The invention relates to the technical field of food formulas, in particular to a chocolate formula generation system based on user taste.
Background
Food refers to various finished products and raw materials for people to eat or drink and the products which are both food and traditional Chinese medicinal materials according to the tradition, but does not include the products aiming at treatment, and the definition of the food is as follows: the substances for human consumption or drinking include processed food, semi-finished product and unprocessed food, do not include tobacco or substances used only as medicines, chocolate is one of the food, chocolate, the original product of Central and south America, the main raw material of which is cocoa beans produced in a narrow and long zone with the equator of less than 18 degrees north-south latitude, and is often called 'hot chocolate' or cocoa Asia when used as beverage.
With the development of social science and technology, people gradually develop from stall sales to network sales, but people still stay selling produced fixed chocolate, cannot analyze chocolate data according to relevant information and data of chocolate purchased by users on line, cannot automatically generate a formula of new chocolate suitable for the users, and therefore a chocolate formula generating system based on user taste is provided.
Disclosure of Invention
The invention aims to provide a chocolate formula generating system based on user taste, which is characterized in that a collecting unit is used for collecting information related to chocolate browsing in a user account record, automatically acquiring browsing information and transmitting the browsing information to a matching analysis unit; the matching analysis unit acquires the user account information and the user identity information from the database and performs data analysis operation together with browsing information to obtain name data, age data, sex data, raw material data, price data, raw material price, account data, shop type data, browsing frequency data, chocolate variety data, raw material data, purchase data, price data, good evaluation frequency data, time data, poor evaluation frequency data and raw material price, the account browsing information acquired by the acquisition unit and the related information stored in the database are calibrated in sequence through the setting of the matching analysis unit, the calibrated related data are classified, the data are quickly identified and acquired, the time consumed by identification is saved, the working efficiency is improved, and through the setting of the taste selection unit and the formula generation unit, the collected related data are subjected to data analysis, chocolate selection is carried out according to the data analysis result, and the selected chocolate is subjected to formula calculation, so that a new formula is obtained, the accuracy of data analysis is improved, the persuasive force of the data is increased, the time consumed by analysis is saved, and the working efficiency is improved.
The technical problem to be solved by the invention is as follows:
(1) how to calibrate the account browsing information collected by the collection unit and the related information stored in the database in sequence through the setting of the matching analysis unit and classify the calibrated related data so as to solve the problem that the collected data cannot be identified quickly in the prior art;
(2) according to the method, the problem that formula synthesis cannot be performed according to users in the prior art is solved by how to perform data analysis on collected related data through the arrangement of the taste selection unit and the formula generation unit, perform chocolate selection according to the result of the data analysis, and perform formula calculation on the selected chocolate to obtain a new formula.
The purpose of the invention can be realized by the following technical scheme: a chocolate formula generation system based on user taste comprises a collection unit, a database, a matching analysis unit, a taste selection unit, a formula generation unit and intelligent equipment;
the acquisition unit is used for acquiring chocolate browsing related information in the user account record, automatically acquiring browsing information and transmitting the browsing information to the matching analysis unit;
the matching analysis unit obtains the user account information and the user identity information from the database, performs data analysis operation on the user account information and the user identity information together with browsing information to obtain name data, age data, sex data, raw material data, price data, raw material price, account data, shop type data, browsing frequency data, chocolate type data, raw material data, purchase data, price data, good appraisal frequency data, time data, poor appraisal frequency data and raw material price, transmits the name data, the age data, the sex data, the raw material data, the price data and the raw material price together to the formula generation unit, and transmits the account data, the shop type data, the browsing frequency data, the chocolate type data, the raw material data, the purchase data, the price data, the good appraisal frequency data, The time data, the poor evaluation frequency data and the raw material price are transmitted to a taste selection unit;
the taste selecting unit is used for selecting account number data, shop type data, browsing frequency data, chocolate variety data, raw material data, purchasing data, price data, favorable evaluation frequency data, time data, bad evaluation frequency data and raw material prices to obtain total value sequencing and transmitting the total value sequencing to the formula generating unit;
the formula generation unit is used for carrying out generation operation on the total value sequencing, the extracted name data, the extracted age data, the extracted gender data, the extracted raw material data, the extracted price data and the extracted raw material price to obtain a customized signal and a recommended signal, and transmitting the customized signal and the recommended signal to the intelligent equipment;
and the intelligent equipment receives the customization signal and the recommendation signal and reminds the user.
As a further improvement of the invention: the specific operation process of the data analysis operation comprises the following steps:
the method comprises the following steps: acquiring user account information, marking account numbers of users in the user account information as account data, and marking the account data as ZHi, wherein i is 1,2,3.. n 1;
step two: acquiring user identity information, calibrating a name of a user therein as name data, marking the name data as XMi, i 1,2,3.. No. n1, calibrating an age size of the user therein as age data, marking the age data as NNi, i 1,2,3.. No. n1, calibrating whether the user therein is male or female as gender data, and marking the gender data as XBi, i 1,2,3.. No. n 1;
step three: the method comprises the steps of obtaining browsing information, marking the types of shops browsed in the browsing information as shop type data, marking the shop type data as LXi, i is 1,2,3.. n1, marking the times of browsing the shops browsed in the browsing information as browsing time data, marking the browsing time data as LCi, i is 1,2,3.. n1, marking the types of chocolate in the shops in the browsing information as chocolate type data, marking the chocolate type data as QZi, i is 1,2,3.. n1, marking the component raw materials of each kilogram of the chocolate in the browsing information as raw material data, marking the raw material data as YILv, i is 1,2,3.. n1, v is 1,2,3.. n2, marking the types of users in the browsing information as purchase data, and marking the purchase data as I GMi, i is 3.. n1, the number of times that the user evaluates the chocolate to more than four stars is marked as the good evaluation number data, and the number of times of good evaluation data is marked as HPi, i 1,2,3.. n1, the number of times in which the user has marked chocolate evaluation as samsung and below is marked as bad evaluation data, and the bad scoring number data is labeled as CPi, i 1,2,3.. n1, the unit price of the chocolate therein is calibrated as the price data, and the price data is marked as JGi, i 1,2,3.. n1, the time point at which the chocolate is browsed through the store is marked as time data, marking the time data as SJi, wherein i is 1,2,3.. No. n1, marking the price corresponding to the raw material data in the time data as the raw material price, and marking the raw material price as YJi, wherein i is 1,2,3.. No. n 1;
step four: the method comprises the following steps of obtaining the account number data, name data, time data, age data, gender data, shop type data, browsing times data, chocolate variety data, raw material data, purchasing data, price data, good evaluation times data, poor evaluation times data and raw material prices, and classifying the obtained data into categories, wherein the category is specifically as follows:
firstly, extracting account data, classifying corresponding shop type data into the account data, dividing corresponding browsing frequency data, chocolate variety data, raw material data, purchase data, price data, good evaluation frequency data, time data, poor evaluation frequency data and raw material prices into the shop type data, and secondly, dividing age data and gender data into name data, wherein the name data correspond to the account data one by one;
step five: name data, age data, gender data, raw material data, price data and raw material prices are extracted, account number data, store type data, browsing times data, chocolate variety data, raw material data, purchase data, price data, goodness data, time data, badness data and raw material prices are extracted.
As a further improvement of the invention: the specific operation process of the selection operation comprises the following steps:
k1: acquiring account data, extracting time data in the account data, respectively marking two different time points as SJ1 and SJ2 according to the time data, and bringing the time points into a difference calculation formula, thereby calculating a time difference value SDifference (D)And the calculation formula for calculating the time difference specifically comprises: sDifference (D)The browsing times data in the time difference are extracted as SJ1 to SJ2, and are substituted into the calculation formula together with the time difference:
wherein L isFrequency converterThe obtained category data and the purchase data are brought into a calculation formula together, which is expressed as a browsing rating:
wherein G isAccount forAnd (3) expressing the ratio of the purchase data, acquiring the good evaluation frequency data and the bad evaluation frequency data, and bringing the good evaluation frequency data and the bad evaluation frequency data into a calculation formula:
wherein HAccount forExpressed as the score-good ratio and substituted into the calculation: cAccount for＝1-HAccount forWherein, CAccount forExpressed as the poor score fraction;
k2: extracting browsing evaluation rate, purchase data ratio, good evaluation ratio and poor evaluation ratio of the user in different time periods, and sequencing the browsing evaluation rate, purchase data ratio, good evaluation ratio and poor evaluation ratio in a descending order to obtain browsing evaluation rate sequencing, purchase data ratio sequencing, good evaluation ratio sequencing and poor evaluation ratio sequencing, assigning names of chocolate sequences corresponding to the browsing evaluation rate sequencing, the purchase data ratio sequencing and the good evaluation ratio sequencing, wherein the second assignment is smaller than the first assignment, the third assignment is smaller than the second assignment, and so on, the assignments in the poor evaluation ratio sequencing are opposite, namely the first assignment is smaller than the second assignment, the second assignment is smaller than the third assignment, selecting a chocolate type, and calculating the chocolate type in the browsing evaluation rate sequencing, the purchase data ratio sequencing, and sequencing, And (4) carrying out total value calculation on the assignment of the good evaluation ratio ranking and the poor evaluation ratio ranking, and ranking the total values of the chocolates of different types from large to small so as to obtain a total value ranking.
As a further improvement of the invention: the specific operation process of the generating operation is as follows:
h1: acquiring planting sorting, selecting chocolate types of the first three in the total value sorting, selecting corresponding price data, and bringing the price data into a calculation formula:
wherein, PPrice ofExpressed as the mean of the chocolate price data, i.e. the price mean;
h2: acquiring chocolate raw material data of the first three in the total value sequence, selecting components with the same raw materials, calibrating the components into necessary component data, and calibrating the rest different raw materials into taste component data;
h3: acquiring necessary component data, taste component data and raw material price data, calculating the total price of the necessary components according to the necessary component data and the raw material price data, calibrating the total price as a necessary price, and bringing the necessary price and a price mean value into a calculation formula together: calculating the proportion distribution of the taste components, and calibrating the proportion distribution of the taste components and the data of the necessary components as the data of the formula raw materials;
h4: calibrating corresponding account data, namely name data, of the formula raw material data, recommending the formula raw material data, generating a customized signal, extracting corresponding age data and gender data according to the corresponding name data, recommending the formula raw material data to users with corresponding ages and genders, and generating a recommendation signal.
As a further improvement of the invention: the intelligent device is specifically a tablet computer.
The invention has the beneficial effects that:
(1) the acquisition unit acquires information related to chocolate browsing in the user account record, automatically acquires browsing information and transmits the browsing information to the matching analysis unit; the matching analysis unit is used for sequentially calibrating the account browsing information collected by the collection unit and the related information stored in the database through the setting of the matching analysis unit, classifying the calibrated related data, rapidly identifying and obtaining the data, saving the time consumed by identification and improving the working efficiency.
(2) Selecting account number data, shop type data, browsing times data, chocolate variety data, raw material data, purchasing data, price data, favorable evaluation times data, time data, poor evaluation times data and raw material prices through the setting of a taste selection unit to obtain total value sequencing, and transmitting the total value sequencing to a formula generation unit; the formula generation unit performs generation operation on the total value sorting, the extracted name data, the extracted age data, the extracted gender data, the extracted raw material data, the extracted price data and the extracted raw material price to obtain a customized signal and a recommended signal, and transmits the customized signal and the recommended signal to the intelligent equipment; through the arrangement of the taste selecting unit and the formula generating unit, data analysis is carried out on the collected related data, chocolate selection is carried out according to the result of the data analysis, and formula calculation is carried out on the selected chocolate, so that a new formula is obtained, the accuracy of the data analysis is improved, the persuasion degree of the data is increased, the time consumed by analysis is saved, and the working efficiency is improved.
Drawings
The invention will be further described with reference to the accompanying drawings.
FIG. 1 is a system block diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the invention relates to a chocolate formula generating system based on user taste, which comprises an acquisition unit, a database, a matching analysis unit, a taste selection unit, a formula generating unit and an intelligent device;
the acquisition unit is used for acquiring chocolate browsing related information in the user account record, automatically acquiring browsing information and transmitting the browsing information to the matching analysis unit;
the matching analysis unit acquires the user account information and the user identity information from the database and performs data analysis operation together with browsing information, and the specific operation process of the data analysis operation is as follows:
the method comprises the following steps: acquiring user account information, marking account numbers of users in the user account information as account data, and marking the account data as ZHi, wherein i is 1,2,3.. n 1;
step two: acquiring user identity information, calibrating a name of a user therein as name data, marking the name data as XMi, i 1,2,3.. No. n1, calibrating an age size of the user therein as age data, marking the age data as NNi, i 1,2,3.. No. n1, calibrating whether the user therein is male or female as gender data, and marking the gender data as XBi, i 1,2,3.. No. n 1;
step three: the method comprises the steps of obtaining browsing information, marking the types of shops browsed in the browsing information as shop type data, marking the shop type data as LXi, i is 1,2,3.. n1, marking the times of browsing the shops browsed in the browsing information as browsing time data, marking the browsing time data as LCi, i is 1,2,3.. n1, marking the types of chocolate in the shops in the browsing information as chocolate type data, marking the chocolate type data as QZi, i is 1,2,3.. n1, marking the component raw materials of each kilogram of the chocolate in the browsing information as raw material data, marking the raw material data as YILv, i is 1,2,3.. n1, v is 1,2,3.. n2, marking the types of users in the browsing information as purchase data, and marking the purchase data as I GMi, i is 3.. n1, the number of times that the user evaluates the chocolate to more than four stars is marked as the good evaluation number data, and the number of times of good evaluation data is marked as HPi, i 1,2,3.. n1, the number of times in which the user has marked chocolate evaluation as samsung and below is marked as bad evaluation data, and the bad scoring number data is labeled as CPi, i 1,2,3.. n1, the unit price of the chocolate therein is calibrated as the price data, and the price data is marked as JGi, i 1,2,3.. n1, the time point at which the chocolate is browsed through the store is marked as time data, marking the time data as SJi, wherein i is 1,2,3.. No. n1, marking the price corresponding to the raw material data in the time data as the raw material price, and marking the raw material price as YJi, wherein i is 1,2,3.. No. n 1;
step four: the method comprises the following steps of obtaining the account number data, name data, time data, age data, gender data, shop type data, browsing times data, chocolate variety data, raw material data, purchasing data, price data, good evaluation times data, poor evaluation times data and raw material prices, and classifying the obtained data into categories, wherein the category is specifically as follows:
firstly, extracting account data, classifying corresponding shop type data into the account data, dividing corresponding browsing frequency data, chocolate variety data, raw material data, purchase data, price data, good evaluation frequency data, time data, poor evaluation frequency data and raw material prices into the shop type data, and secondly, dividing age data and gender data into name data, wherein the name data correspond to the account data one by one;
step five: name data, age data, gender data, raw material data, price data and raw material prices are extracted and transmitted to a formula generating unit, and account data, shop type data, browsing times data, chocolate variety data, raw material data, purchase data, price data, goodness data, time data, poor-scoring times data and raw material prices are transmitted to a taste selecting unit;
the taste selection unit is used for selecting account number data, shop type data, browsing frequency data, chocolate variety data, raw material data, purchase data, price data, favorable evaluation frequency data, time data, bad evaluation frequency data and raw material prices, and the specific operation process of the selection operation is as follows:
k1: acquiring account data, extracting time data in the account data, respectively marking two different time points as SJ1 and SJ2 according to the time data, and bringing the time points into a difference calculation formula, thereby calculating a time difference value SDifference (D)And the calculation formula for calculating the time difference specifically comprises: sDifference (D)The browsing times data in the time difference are extracted as SJ1 to SJ2, and are substituted into the calculation formula together with the time difference:
wherein L isFrequency converterThe obtained category data and the purchase data are brought into a calculation formula together, which is expressed as a browsing rating:
wherein G isAccount forAnd (3) expressing the ratio of the purchase data, acquiring the good evaluation frequency data and the bad evaluation frequency data, and bringing the good evaluation frequency data and the bad evaluation frequency data into a calculation formula:
wherein HAccount forExpressed as the score-good ratio and substituted into the calculation: cAccount for＝1-HAccount forWherein，CAccount forExpressed as the poor score fraction;
k2: extracting browsing evaluation rate, purchase data ratio, good evaluation ratio and poor evaluation ratio of the user in different time periods, and sequencing the browsing evaluation rate, purchase data ratio, good evaluation ratio and poor evaluation ratio in a descending order to obtain browsing evaluation rate sequencing, purchase data ratio sequencing, good evaluation ratio sequencing and poor evaluation ratio sequencing, assigning names of chocolate sequences corresponding to the browsing evaluation rate sequencing, the purchase data ratio sequencing and the good evaluation ratio sequencing, wherein the second assignment is smaller than the first assignment, the third assignment is smaller than the second assignment, and so on, the assignments in the poor evaluation ratio sequencing are opposite, namely the first assignment is smaller than the second assignment, the second assignment is smaller than the third assignment, selecting a chocolate type, and calculating the chocolate type in the browsing evaluation rate sequencing, the purchase data ratio sequencing, and sequencing, Carrying out total value calculation on the assignment of the good evaluation ratio sequence and the poor evaluation ratio sequence, and sequencing the total values of different types of chocolates from large to small so as to obtain a total value sequence;
k3: the extracted total value is sorted and transmitted to a formula generating unit;
the formula generating unit is used for carrying out generating operation on the total value sequencing, the extracted name data, the extracted age data, the extracted gender data, the extracted raw material data, the extracted price data and the extracted raw material price, and the specific operation process of the generating operation is as follows:
h1: acquiring planting sorting, selecting chocolate types of the first three in the total value sorting, selecting corresponding price data, and bringing the price data into a calculation formula:
wherein, PPrice ofExpressed as the mean of the chocolate price data, i.e. the price mean;
h2: acquiring chocolate raw material data of the first three in the total value sequence, selecting components with the same raw materials, calibrating the components into necessary component data, and calibrating the rest different raw materials into taste component data;
h3: acquiring necessary component data, taste component data and raw material price data, calculating the total price of the necessary components according to the necessary component data and the raw material price data, calibrating the total price as a necessary price, and bringing the necessary price and a price mean value into a calculation formula together: calculating the proportion distribution of the taste components, and calibrating the proportion distribution of the taste components and the data of the necessary components as the data of the formula raw materials;
h4: calibrating corresponding account data, namely name data, of the formula raw material data, recommending the formula raw material data to generate a customized signal, extracting corresponding age data and gender data according to the corresponding name data, recommending the formula raw material data to users with corresponding ages and genders, and generating a recommendation signal;
h5: transmitting the customized signal and the recommended signal to the intelligent equipment together;
the intelligent device receives the customization signal and the recommendation signal and reminds a user, and the intelligent device is a tablet computer.
When the chocolate matching analysis device works, the acquisition unit acquires information related to chocolate browsing in the user account record, automatically acquires browsing information and transmits the browsing information to the matching analysis unit; the matching analysis unit acquires the user account information and the user identity information from the database, performs data analysis operation on the user account information and the user identity information together with browsing information to obtain name data, age data, gender data, raw material data, price data, raw material price, account data, store type data, browsing frequency data, chocolate variety data, raw material data, purchase data, price data, good evaluation frequency data, time data, poor evaluation frequency data and raw material price, transmits the name data, the age data, the gender data, the raw material data, the price data and the raw material price together to the formula generation unit, and transmits the account data, the store type data, the browsing frequency data, the chocolate variety data, the raw material data, the purchase data, the price data, the good evaluation frequency data, The time data, the poor evaluation frequency data and the raw material price are transmitted to a taste selection unit; the taste selecting unit selects account data, shop type data, browsing times data, chocolate variety data, raw material data, purchasing data, price data, good evaluation times data, time data, poor evaluation times data and raw material prices to obtain total value sequencing, and transmits the total value sequencing to the formula generating unit; the formula generation unit performs generation operation on the total value sorting, the extracted name data, the extracted age data, the extracted gender data, the extracted raw material data, the extracted price data and the extracted raw material price to obtain a customized signal and a recommended signal, and transmits the customized signal and the recommended signal to the intelligent equipment; and the intelligent equipment receives the customization signal and the recommendation signal and reminds the user.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (5)
1. A chocolate formula generating system based on user taste is characterized by comprising a collecting unit, a database, a matching analysis unit, a taste selecting unit, a formula generating unit and intelligent equipment;
the acquisition unit is used for acquiring chocolate browsing related information in the user account record, automatically acquiring browsing information and transmitting the browsing information to the matching analysis unit;
the matching analysis unit obtains the user account information and the user identity information from the database, performs data analysis operation on the user account information and the user identity information together with browsing information to obtain name data, age data, sex data, raw material data, price data, raw material price, account data, shop type data, browsing frequency data, chocolate type data, raw material data, purchase data, price data, good appraisal frequency data, time data, poor appraisal frequency data and raw material price, transmits the name data, the age data, the sex data, the raw material data, the price data and the raw material price together to the formula generation unit, and transmits the account data, the shop type data, the browsing frequency data, the chocolate type data, the raw material data, the purchase data, the price data, the good appraisal frequency data, The time data, the poor evaluation frequency data and the raw material price are transmitted to a taste selection unit;
the taste selecting unit is used for selecting account number data, shop type data, browsing frequency data, chocolate variety data, raw material data, purchasing data, price data, favorable evaluation frequency data, time data, bad evaluation frequency data and raw material prices to obtain total value sequencing and transmitting the total value sequencing to the formula generating unit;
the formula generation unit is used for carrying out generation operation on the total value sequencing, the extracted name data, the extracted age data, the extracted gender data, the extracted raw material data, the extracted price data and the extracted raw material price to obtain a customized signal and a recommended signal, and transmitting the customized signal and the recommended signal to the intelligent equipment;
and the intelligent equipment receives the customization signal and the recommendation signal and reminds the user.
2. The chocolate recipe generation system according to claim 1, wherein the specific operation process of the data analysis operation is:
the method comprises the following steps: acquiring user account information, marking account numbers of users in the user account information as account data, and marking the account data as ZHi, wherein i is 1,2,3.. n 1;
step two: acquiring user identity information, calibrating a name of a user therein as name data, marking the name data as XMi, i 1,2,3.. No. n1, calibrating an age size of the user therein as age data, marking the age data as NNi, i 1,2,3.. No. n1, calibrating whether the user therein is male or female as gender data, and marking the gender data as XBi, i 1,2,3.. No. n 1;
step three: the method comprises the steps of obtaining browsing information, marking the types of shops browsed in the browsing information as shop type data, marking the shop type data as LXi, i is 1,2,3.. n1, marking the times of browsing the shops browsed in the browsing information as browsing time data, marking the browsing time data as LCi, i is 1,2,3.. n1, marking the types of chocolate in the shops in the browsing information as chocolate type data, marking the chocolate type data as QZi, i is 1,2,3.. n1, marking the component raw materials of each kilogram of the chocolate in the browsing information as raw material data, marking the raw material data as YILv, i is 1,2,3.. n1, v is 1,2,3.. n2, marking the types of users in the browsing information as purchase data, and marking the purchase data as I GMi, i is 3.. n1, the number of times that the user evaluates the chocolate to more than four stars is marked as the good evaluation number data, and the number of times of good evaluation data is marked as HPi, i 1,2,3.. n1, the number of times in which the user has marked chocolate evaluation as samsung and below is marked as bad evaluation data, and the bad scoring number data is labeled as CPi, i 1,2,3.. n1, the unit price of the chocolate therein is calibrated as the price data, and the price data is marked as JGi, i 1,2,3.. n1, the time point at which the chocolate is browsed through the store is marked as time data, marking the time data as SJi, wherein i is 1,2,3.. No. n1, marking the price corresponding to the raw material data in the time data as the raw material price, and marking the raw material price as YJi, wherein i is 1,2,3.. No. n 1;
step four: the method comprises the following steps of obtaining the account number data, name data, time data, age data, gender data, shop type data, browsing times data, chocolate variety data, raw material data, purchasing data, price data, good evaluation times data, poor evaluation times data and raw material prices, and classifying the obtained data into categories, wherein the category is specifically as follows:
firstly, extracting account data, classifying corresponding shop type data into the account data, dividing corresponding browsing frequency data, chocolate variety data, raw material data, purchase data, price data, good evaluation frequency data, time data, poor evaluation frequency data and raw material prices into the shop type data, and secondly, dividing age data and gender data into name data, wherein the name data correspond to the account data one by one;
step five: name data, age data, gender data, raw material data, price data and raw material prices are extracted, account number data, store type data, browsing times data, chocolate variety data, raw material data, purchase data, price data, goodness data, time data, badness data and raw material prices are extracted.
3. The chocolate recipe generation system based on user taste as claimed in claim 1, wherein the specific operation process of the selecting operation is:
k1: acquiring account data, extracting time data in the account data, respectively marking two different time points as SJ1 and SJ2 according to the time data, and bringing the time points into a difference calculation formula, thereby calculating a time difference value SDifference (D)And the calculation formula for calculating the time difference specifically comprises: sDifference (D)The browsing times data in the time difference are extracted as SJ1 to SJ2, and are substituted into the calculation formula together with the time difference:
wherein L isFrequency converterThe obtained category data and the purchase data are brought into a calculation formula together, which is expressed as a browsing rating:
wherein G isAccount forAnd (3) expressing the ratio of the purchase data, acquiring the good evaluation frequency data and the bad evaluation frequency data, and bringing the good evaluation frequency data and the bad evaluation frequency data into a calculation formula:
wherein HAccount forExpressed as the score-good ratio and substituted into the calculation: cAccount for＝1-HAccount forWherein, CAccount forExpressed as the poor score fraction;
k2: extracting browsing evaluation rate, purchase data ratio, good evaluation ratio and poor evaluation ratio of the user in different time periods, and sequencing the browsing evaluation rate, purchase data ratio, good evaluation ratio and poor evaluation ratio in a descending order to obtain browsing evaluation rate sequencing, purchase data ratio sequencing, good evaluation ratio sequencing and poor evaluation ratio sequencing, assigning names of chocolate sequences corresponding to the browsing evaluation rate sequencing, the purchase data ratio sequencing and the good evaluation ratio sequencing, wherein the second assignment is smaller than the first assignment, the third assignment is smaller than the second assignment, and so on, the assignments in the poor evaluation ratio sequencing are opposite, namely the first assignment is smaller than the second assignment, the second assignment is smaller than the third assignment, selecting a chocolate type, and calculating the chocolate type in the browsing evaluation rate sequencing, the purchase data ratio sequencing, and sequencing, And (4) carrying out total value calculation on the assignment of the good evaluation ratio ranking and the poor evaluation ratio ranking, and ranking the total values of the chocolates of different types from large to small so as to obtain a total value ranking.
4. The chocolate recipe generation system based on user taste as claimed in claim 1, wherein the specific operation process of the generation operation is:
h1: acquiring planting sorting, selecting chocolate types of the first three in the total value sorting, selecting corresponding price data, and bringing the price data into a calculation formula:
wherein, PPrice ofExpressed as the mean of the chocolate price data, i.e. the price mean;
h2: acquiring chocolate raw material data of the first three in the total value sequence, selecting components with the same raw materials, calibrating the components into necessary component data, and calibrating the rest different raw materials into taste component data;
h3: acquiring necessary component data, taste component data and raw material price data, calculating the total price of the necessary components according to the necessary component data and the raw material price data, calibrating the total price as a necessary price, and bringing the necessary price and a price mean value into a calculation formula together: calculating the proportion distribution of the taste components, and calibrating the proportion distribution of the taste components and the data of the necessary components as the data of the formula raw materials;
h4: calibrating corresponding account data, namely name data, of the formula raw material data, recommending the formula raw material data, generating a customized signal, extracting corresponding age data and gender data according to the corresponding name data, recommending the formula raw material data to users with corresponding ages and genders, and generating a recommendation signal.
5. The chocolate recipe generation system based on user taste as claimed in claim 1, wherein the smart device is embodied as a tablet computer.
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| CN202010934768.1A CN112070583A (en) | 2020-09-08 | 2020-09-08 | Chocolate formula generation system based on user taste |
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