KR20210026222A - The System For Providing Customized Cosmetics - Google Patents

Abstract

The present invention relates to a customized cosmetics manufacturing system for the skin beauty industry, which enables skin care specialists with professional knowledge about cosmetics to manufacture and supply customized cosmetics that are optimized for needs in fields. The present invention includes: a subscription module where a skin beauty industry expert inputs expert information; a storage module including an item DB receiving the input of and storing manufacturable cosmetics item information and an ingredient DB receiving the input of and storing information on an ingredient that can be contained in cosmetics; a selection module including an item selection unit where the expert selects at least one of the item information, an ingredient selection unit where the expert selects at least one of the ingredient information, a quantity determination unit where the expert inputs manufacturing capacity and a manufacturing quantity, and an order sheet generation unit generating an order sheet including the selected item information, the selected ingredient information, the input manufacturing capacity, and the input manufacturing quantity; a payment module where the expert makes a payment with respect to the order sheet; a cosmetics manufacturing module manufacturing customized cosmetics based on the order sheet; and a providing module providing the manufactured customized cosmetics for the expert.

Description

The System For Providing Customized Cosmetics for the skin beauty industry

The present invention is a customized cosmetics manufacturing system for the skin beauty industry, which enables a skin beauty industry expert with professional knowledge about cosmetics to manufacture and supply customized cosmetics optimized for their needs. Provides a manufacturing system.

Cosmetics are produced according to several typical types, such as oily skin, normal skin, and dry skin. Therefore, if a person with oily skin uses cosmetics for dry skin, side effects may occur, so each person must select a cosmetic product suitable for his or her skin type. In addition, some ingredients included in cosmetics may cause various side effects such as causing skin aging or cancer when used for a long time. In addition, some customers may cause an allergy reaction or skin troubles such as acne due to certain ingredients included in cosmetics.

However, in general, people do not know exactly what kind of skin type they have and what ingredients cause troubles on their skin, so they choose cosmetics according to the recommendations of cosmetics salesmen. However, since cosmetics salespeople do not have specialized knowledge about the effects of ingredients constituting cosmetics, it is difficult to recommend cosmetics that are suitable for customers' personal preferences, skin conditions, and specific matters (for example, allergic reactions, etc.).

Therefore, in order to solve this problem, Korean Patent Laid-Open No. 10-2017-0111859 discloses a method for providing customized cosmetics.

The present invention relates to a method for providing customized cosmetics for a buyer to easily purchase and use cosmetics optimized for them according to their skin type or taste, comprising the steps of: selecting a cosmetic material by the buyer; A step of preparing a cream formulation base for manufacturing a cream-type cosmetic by mixing an oily component, an aqueous component, and an emulsifier by a seller; And adding and mixing the cosmetic material selected by the purchaser in the cream formulation base to the cream formulation base prepared in the above step by the seller to the cream formulation base, and the purchaser to himself/herself according to his or her skin type or taste. Optimized cosmetics can be easily purchased and used.

However, going further from here, by enabling skin care professionals with specialized knowledge about cosmetics to manufacture and supply customized cosmetics optimized for their needs, the effectiveness of target marketing to customers is enhanced while at the same time enhancing the effective effect. In the case of a customized cosmetic manufacturing system targeting the skin beauty industry, it is in need of development.

The present invention was conceived to overcome the problems of the above technology, and tailored cosmetics for the skin beauty industry, which enables a skin beauty industry expert with professional knowledge about cosmetics to manufacture and supply customized cosmetics optimized for their needs. Its main purpose is to provide a manufacturing system.

Furthermore, it is intended to further increase the convenience of manufacturing customized cosmetics by allowing experts to individually select the safety grade and functional purpose of the components when producing customized cosmetics.

In addition, an additional purpose is to be able to manufacture customized cosmetics optimized for individual experts by allowing additional individual requests of experts to be reflected when manufacturing customized cosmetics.

In addition, by automating the analysis of individual requests, the subjective value judgment, taste and preferences of experts hidden in individual requests can be reflected in cosmetic manufacturing.

In addition, it is to improve the accuracy of the analysis by presenting a new text analysis method in the analysis of individual requests.

In order to achieve the above object, a customized cosmetic manufacturing system for the skin beauty industry of the present invention comprises: a subscription module receiving expert information from a skin beauty industry expert; A storage module including an item DB for receiving and storing item information of a cosmetic product that can be manufactured, and an ingredient DB for receiving and storing component information that can be included in the cosmetic product; An item selection unit for selecting at least one of the item information from the expert, an ingredient selection unit for selecting at least one of the component information from the expert, and a quantity determination receiving input of the manufacturing capacity and the manufacturing quantity from the expert A selection module including an order form generation unit for generating an order form including a unit and the selected item information, the component information, and the input production capacity and the production quantity; A payment module for receiving payment for the order form from the expert; A cosmetic manufacturing module for manufacturing customized cosmetic products based on the order form; It characterized in that it comprises a; providing module for providing the manufactured customized cosmetics to the expert.

In addition, the system. A component classification module comprising a rating classifier for classifying a plurality of component information into at least two or more rating groups; further comprising, the component selection section, a rating selection in which at least one of the rating groups is selected from the expert. Part and. And a component selection part for selecting at least one of the component information belonging to the rating group selected by the expert, and the order form further includes the selected rating group.

In addition, the component classification module further includes a purpose classification unit for secondary classification of the component information belonging to each of the rating groups into a plurality of purpose-specific groups, and the component selection unit includes: Further comprising a purpose selection part for selecting a group for each purpose, the component selection part, at least one of the component information belonging to the group for each purpose selected by the expert is selected, the order form, the group for each purpose It characterized in that it further comprises.

Furthermore, the selection module further includes an additional request unit for receiving individual request information from the expert, and the order form further includes the individual request information.

The customized cosmetic manufacturing system for the skin beauty industry according to the present invention,

1) We provide a customized cosmetic manufacturing system for the skin beauty industry, which allows each skin beauty industry expert with specialized knowledge about cosmetics to manufacture and supply customized cosmetics optimized for their needs,

2) When manufacturing customized cosmetics, the convenience of manufacturing customized cosmetics was enhanced by allowing experts to individually select the safety grade and functional purpose of the ingredients.

3) When manufacturing customized cosmetics, additional individual requests from experts can be reflected, so that more customized cosmetics optimized for each expert can be manufactured.

4) By automating the analysis of individual requests, the subjective value judgment, tastes, preferences, etc. of experts hidden in individual requests can be reflected in cosmetics manufacturing.

5) In analyzing individual requests, it has the effect of increasing the accuracy of the analysis by presenting a new text analysis method.

1 is a conceptual diagram showing a schematic configuration of a customized cosmetic manufacturing system for the skin beauty industry of the present invention.
Figure 2 is a block diagram showing the configuration of a customized cosmetic manufacturing system for the skin beauty industry of the present invention.
Figure 3 is a process diagram of a customized cosmetic manufacturing system for the skin beauty industry of the present invention.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. The accompanying drawings are not drawn to scale, and the same reference numerals in each drawing refer to the same components.

1 is a conceptual diagram showing a schematic configuration of a customized cosmetic manufacturing system for the skin beauty industry of the present invention.

First of all, in the present invention, the term skin care professional (2) refers to a person who is engaged in the skin care industry, and generally, a dermatologist or other dermatologist operating a skin care room such as esthetics, as well as the skin care business It means the one who provides it. The system 10 of the present invention allows the expert 2 to provide customized cosmetics according to the needs of the skin beauty industry expert 2, so that the expert 2 can sell the cosmetics tailored to the customer. In this case, it goes without saying that the expert (2) may be a general individual or a group (company).

The main server 1 of the present invention is a series of subjects (central control server) for implementing the system 10 of the present invention, and includes a server PC and a network communication network. In addition, the main server 1 has a central processing unit (CPU) and a program that can be executed in the central processing unit on a hardware basis having storage means such as memory and hard disk, that is, software is installed to execute this software. A series of specific configurations of software will be described later as constituent units such as'module','part', and'part'.

This main server 1 performs a function of supplying customized cosmetics to skin care professionals 2 (abbreviated as experts 2) through the system 10 of the present invention, and furthermore, it is possible to manufacture cosmetics. Of course, it is possible to have a function of controlling the manufacture of cosmetics by enabling network communication with the facilities of the cosmetics factory 3 provided separately so as to be possible.

The configuration of such a'module' or'part' or'interface' or'part' is installed and stored in the storage means of the main server 1, software running through CPU and memory, or hardware such as FPGA or ASIC. Means the work composition of. In this case, the configuration of'module','unit', and'interface' is not meant to be limited to hardware, and may be configured to be in an addressable storage medium or configured to reproduce one or more processors. As an example,'module' or'sub' or'interface' refers to components such as software components, object-oriented software components, class components and task components, processes, functions, and properties. S, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays and variables.

The functions provided by these'module' or'sub' or'interface' may be combined into a smaller number of components and'sub' or'module', or additional components and'sub' or'module' Can be further separated.

In addition, the main server 1 refers to all kinds of hardware devices including at least one processor, and may be understood as encompassing a software configuration operating in the corresponding hardware device according to an embodiment. For example, a computing device as an example of a server may be understood as including all of a smartphone, a tablet PC, a desktop, a laptop, and a user client and an application running on each device, but is not limited thereto.

The detailed configuration of the customized cosmetic manufacturing system 10 for the skin beauty industry will be described with reference to the drawings as follows.

FIG. 2 is a block diagram showing the configuration of a customized cosmetics manufacturing system 10 for the skin beauty industry of the present invention, and FIG. 3 is a process diagram of the customized cosmetics manufacturing system 10 for the skin beauty industry of the present invention. .

Referring to FIG. 3 along with FIG. 2, the customized cosmetic manufacturing system 10 for the skin care industry of the present invention is basically a subscription module 100, a storage module 200, a selection module 300, and It may be configured to include a module 400 and a providing module 500, and may further include an additional component such as a component classification module 600 and an individual request analysis module 700.

The subscription module 100 is a program or a separate Internet site, an application, or an expert (2) on the paper in order to enable the skin care professional 2 of the present invention to use the customized cosmetic manufacturing system 10 of the present invention. Performs the function of allowing information to be entered. At this time, the expert (2) information should be able to basically include the subscriber's name/business name, business type, address, phone number, and e-mail address.

The storage module 200 performs a function of storing information on items of cosmetics for manufacturing customized cosmetics of the present invention, information on components constituting cosmetics, etc. in a database, and can be referred to as an aggregate of a series of databases. I can. This storage module 200 basically includes an item DB 210 and an ingredient DB 220.

Item DB 210 is a database that receives and stores item information, which is information on items, of types of cosmetics that can be manufactured through the system 10 of the present invention. In this case, examples of items are toners, essences, and cleansers. , Cream, mask pack, and the like. In addition, as detailed item information, the cleanser may be further divided into cleansing oil, foam cleanser, cleansing water, cleansing tissue, etc. and stored. At this time, the subject who inputs item information into the item DB 210 may basically be the administrator of the system 10, and furthermore, the skin beauty industry expert 2 inputs new item information into the item DB 210 for registration processing. Of course it is also possible.

Ingredient DB 220 is a component constituting a cosmetic, that is, a component used in the manufacture of cosmetics, which receives a plurality of component information that can be included in the cosmetic and stores it in the database. At this time, examples of the component DB 220 may include purified water, glycerin, ethanol, betaine, lactic acid, sodium hyaluronate, hyaluronic acid, glycolic acid, triethanolamine, and the like. Even if not, all of the constituents used in the manufacture of conventional cosmetics may be input and stored in the ingredient DB 220 as constituent information of the present invention. In addition, the subject who inputs component information in the component DB 220 may be the system 10 administrator, and furthermore, the skin beauty industry expert (2) enters the newly developed component information into the component DB 220 and registers it. Of course, it is also possible to process.

At this time, in the system 10 of the present invention, it is also possible to separately classify the component information registered in the ingredient DB 220 to promote convenience in manufacturing customized cosmetics. To this end, the system 10 of the present invention A component classification module 600 may be further included. The component classification module 600 may be configured to include a grade classification unit 610 and a purpose classification unit 620 as a detailed configuration.

The rating classification unit 610 performs a function of classifying a plurality of the component information into at least two or more rating groups, and in this case, the rating group may be divided into organic/non-organic farming, etc., and furthermore, current cosmetics It is an EWG grade that judges the risk level of a component, and can be divided into grade groups such as Grade 1 to Grade 9. Alternatively, it is also possible to separately classify cosmetic components on the system 10 of the present invention and assign a (safety/medium/dangerous) grade group. Accordingly, the components constituting the cosmetics are grouped according to the degree of risk through this, so that they can be used more conveniently when configuring the ingredients for the manufacture of cosmetics. For example, if component information is classified into 9 grade groups of grades 1 to 9 according to the EWG risk level, purified water is grade 1 group, citric acid grade 2 group, aluminum distearate grade 3 group, and vaseline The 4th grade group and Linalul belong to the 5th grade group.

The purpose classification unit 620 classifies and processes the component information constituting the cosmetic into a plurality of purpose-specific groups according to functional purposes, and the component information belonging to each of the rating groups is secondary to a plurality of purpose-specific groups. It performs the function of sorting. For example, component information can be classified into groups by purpose such as moisturizing, whitening, elasticity, and soothing. For example, glycerin belongs to the moisturizing group, and it can be subdivided into the first grade group-the moisturizing group because it is the first grade in the EWG grade. Niacinamide belongs to the whitening group, and at the same time, it can be subdivided into the first grade group-the whitening group because it is the first grade in the EWG grade. Allantoin can belong to the true group. In addition, if the efficacy of specific component information is both whitening and moisturizing, it is of course possible to classify the corresponding component information to be included in the whitening group and the moisturizing group at the same time. In accordance with the classification by purpose, the components constituting cosmetics are grouped according to their functional purpose, so that they can be more conveniently used when constituting ingredients for the manufacture of cosmetics.

The selection module 300 performs a function of providing a customized option so that the skin beauty industry expert 2 can select and manufacture cosmetics optimized for his/her needs. Basically, the item selection unit 310, ingredient selection It may be configured to include a unit 320, a quantity determination unit 330, and an order form generation unit 340.

The item selection unit 310 receives at least one of the item information registered in the item DB 210 of the present invention from the expert 2, and at this time, the expert 2 selects the cosmetic item to be provided. It may be entered directly, or after listing item information, at least one of them may be selected by the expert (2). If the expert (2) wants to manufacture toner, he selects the toner from the item information.

The component selection unit 320 performs a function of selecting at least one of the component information registered in the component DB 220 of the present invention from the expert 2. At this time, in order to select the component information, the entire component information registered in the component DB 220 may be provided to the expert (2) and then only desired component information may be selected. And it is possible to more conveniently select components by using a classification system of groups by purpose. To this end, the component selection unit 320 may further include a grade selection part 321, a purpose selection part 323, and an ingredient selection part 322.

The rating selection part 321 performs a function of selecting at least one of the rating groups from the expert 2, and the expert 2 selects any one of the rating groups classified according to their needs and It is to be able to manufacture cosmetics by using them. For example, if you want organic cosmetics, you can select the organic grade group, if you want safe cosmetics with low risk of ingredients, you can select a grade group with a low risk grade, or if you want cosmetics with a compromised selling price with cost reduction. It is possible to allow an expert (2) to select a rating group that meets the needs.

The purpose selection part 323 performs a function of receiving the purpose-specific group selected from the expert (2) who selected the grade group, and various cosmetics such as whitening/soothing/moisturizing from the expert (2) who selected the manufacturing grade of the cosmetics. According to the functional purpose of, at least one of the groups by purpose may be selected.

The component selection part 322 performs a function of selecting at least one of the component information belonging to the rating group selected from the expert (2) or the rating group selected from the expert (2) and the purpose-specific group. , Through this, the expert (2) can manufacture cosmetics with an ingredient composition optimized for the person. Alternatively, it is also possible to configure the basic as a whole selection in consideration of manufacturing convenience, and to exclude it from selection so as not to include unnecessary component information from the expert (2).

The quantity determination unit 330 performs a function of receiving input of the manufacturing capacity and quantity of cosmetics to be manufactured from the expert 2. In this case, the manufacturing capacity is the capacity of one cosmetic product, and may be generally in g or ml, and the quantity may be input as desired by the expert 2. Further, it is possible to allow the quantity determination unit 330 to select a container type (tube type, pumping type, glass bottle, plastic bottle, etc.) of the cosmetic product.

The order form generation unit 340 includes the component information selected from the expert 2, the input item information, the manufacturing capacity, the manufacturing quantity, further information on the grade group and information on the purpose-specific group, as described later. It performs the function of generating an order form including the relevant information based on individual requests to be made. This order form is used to manufacture customized cosmetics for experts 2 in the cosmetic factory 3 through a manufacturing module to be described later.

The manufacturing module 400 manufactures customized cosmetics based on the order form, and manufactures corresponding item information based on the order form as much as the manufacturing capacity and manufacturing quantity, and at the same time reflects the selected component information. . This manufacturing module 400 is implemented by sending an order form to the cosmetic factory 3 to allow the cosmetic factory 3 to manufacture customized cosmetics optimized for the needs of the expert 2.

The providing module 500 serves to provide the customized cosmetics manufactured in the cosmetic factory 3 described above to the expert 2 described above. Experts (2) can sell customized cosmetics optimized for their needs by receiving and using the customized cosmetics for sale.

Taking one step further from such a customized cosmetic manufacturing configuration, the selection module 300 of the present invention may receive individual requests from the expert 2. To this end, the selection module 300 of the present invention may include an additional request unit 350 that receives individual request information from an expert. In this case, the individual requests input through the additional request unit 350 may be, for example, clinical trial data production, silicone-free, specific formulation types, or other items necessary for the manufacture of cosmetics. These additional requests can be processed by listing some of the items that can be added by default and then selecting some of them from the expert (2) and reflecting them in the order form. In this case, the order form can reflect individual requests when manufacturing customized cosmetics, including individual requests.

In addition, individual requests may be input as text, not simply optional. Such text may be a simple text, but in order to reflect the needs of the expert (2) as much as possible, detailed text input may be optimized to manufacture customized cosmetics that meet the needs as much as possible. Therefore, it is also possible to receive detailed text as an additional request, analyze it to generate analysis information, and reflect it in the order form.

To this end, the system 10 of the present invention may further include an individual request analysis module 700 that analyzes and processes the individual request to generate analysis information, and the individual request analysis module 700 When the analysis information is generated through analysis, the analysis information may be further reflected in the order form.

At this time, the individual request analysis module 700 should perform a function of analyzing the text of the individual request to analyze the needs of the expert (2). You should be able to extract keywords. In this case, various text analysis methods can be used. In the case of the problem of extracting a representative keyword within such text, since uncertainty is inherent, an efficient method should be used when extracting the keyword. Therefore, the individual request analysis module 700 of the present invention analyzes and processes the individual requests based on fuzzy inference in this text analysis, and generates analysis information on the representative effects of the customized cosmetics to be manufactured. . In this case, in the case of fuzzy inference, it has the advantage of inferring keywords in a way that is as similar as possible to the way humans think, because rules that use approximate and subjective values and data that may be ambiguous and incomplete are created and the data is analyzed. . Therefore, fuzzy reasoning can be usefully applied when generating analysis information on the representative effect of customized cosmetics, which can be a representative keyword reflecting the field of interest of the expert (2) in the individual request subjectively input by the expert (2).

At this time, the individual request analysis module 700 includes a term extraction unit 710, a frequency determination unit 720, an importance calculation unit 730, a representative designation unit 740, a similarity calculation unit 750, and a weight calculation unit ( 760), an additional designation unit 770, and an analysis information generation unit 780 may be included.

The term extracting unit 710 performs a function of extracting a plurality of basic terms from the text constituting the individual request. In this case, the basic term generally means a noun included in a sentence. In the customized cosmetics manufacturing system 10 of the invention, words related to subjective feelings or value judgment of the expert 2 can also be reflected in the analysis information calculation, so the basic terms in the present invention include adjectives as well as nouns. .

The frequency determination unit 720 performs a function of identifying the frequency for each of the basic terms. In this case, if the frequency is simplified, the number of times the basic term appears in the text of the individual request entered by the expert 2 Means. That is, if the word'moisturizing' appears 3 times in the text of the individual request, the frequency is 3. The concept of this basic frequency is judged as the basic frequency. However, further subdividing and grasping the frequency to perform fuzzy inference based on the frequency. To this end, the frequency determination unit 720 may include a basic frequency calculation part 721 and a text frequency calculation part 722.

The basic frequency calculation part 721 performs a function of grasping the basic frequency for each basic term, and the basic frequency mentioned above appears in the text of the individual request input by the expert (2). Means one number of times.

The text frequency calculation part 722 performs a function of identifying the text frequency for each of the basic terms. In this case, the text frequency refers to the entire text input by the system 10, that is, the entire individual request. It means the number of times the basic term appears in.

In other words, when a total of 3 individual requests of the 1st individual request / 2nd individual request / 3rd individual request are accumulated in the system 10 of the present invention, the word'moisturizing' in the 1st individual request Suppose a case where the word'moisturizing' appears 3 times in the individual request number 2, and the word'moisturizing' appears 2 times in the individual request number 3. In this case, the basic frequency for the basic term'moisturizing' in the individual request 3 is 2 and the text frequency is 6.

The importance calculation unit 730 calculates the importance for each of the basic terms by performing fuzzy inference on the basic terms based on the basic frequency and the frequency including the text frequency identified by the above-described frequency identification unit 720. As performing a function, the importance calculation unit 730 basically includes a first calculation part 731, a second calculation part 732, a third calculation part 733, an input value calculation part 734, and a fuzzy calculation part. It may be configured to include (735).

The first calculation part 731 performs a function of performing normalization for applying a fuzzy inference rule on a basic frequency, which is the most basic concept among the concepts of frequency. In the fuzzy inference rule, since a normalized value is required to generate the input value of the fuzzy control, it can be referred to as a process of performing it. The calculation of the first normalization frequency through the first calculation part 731 may be performed through Equation 1 below.

Equation 1,

는 용어

에 대한 제1 정규화 빈도,

는 용어

의 기본 빈도수,

는 용어

의 텍스트 빈도수를 의미한다.here,

Is the term

The first normalized frequency for,

Is the term

The default frequency of,

Is the term

Means the frequency of the text of the text.

The second calculation part 732 prepares for generating an input value for fuzzy calculation by performing normalization on the text frequency, which is another concept among the concepts of frequency. In this case, the calculation of the second normalization frequency through the second calculation part 732 may be performed through Equation 2 below.

Equation 2,

는 용어

에 대한 제2 정규화 빈도,

는 용어

의 텍스트 빈도수,

은 시스템(10)에 입력된 개별요청사항의 총 개수를 의미한다.here,

Is the term

The second normalized frequency for,

Is the term

Text frequency of,

Denotes the total number of individual requests entered into the system 10.

The third calculation part 733 performs a function of calculating a third normalization frequency by performing normalization on the reciprocal of the text frequency, that is, the normalization for the reciprocal of the text frequency, that is, the inverse document frequency is the third calculation part ( 733) to perform a preparation work for fuzzy calculation, which will be described later. In this case, the calculation of the third normalization frequency through the third calculation part 733 may be performed through Equation 3 below.

Equation 3,

는 용어

에 대한 제3 정규화 빈도,

는 용어

의 텍스트 빈도수를 의미한다.here,

Is the term

The third normalized frequency for,

Is the term

Means the frequency of the text of the text.

The first calculation part 731, the second calculation part 732, and the third calculation part 733 as described above perform a function of generating input variables for fuzzy inference by performing normalization for fuzzy calculation in different ways. do. In this case, not all variables are normalized in the same way, but different frequencies or the number of texts that may be related to each variable are reflected in normalization, so that a more standardized value can be obtained.

The input value calculation part 734 performs a function of calculating a first input value, a second input value, and a third input value by fuzzifying the first normalization frequency, the second normalization frequency, and the third normalization frequency. , The calculated first, second, and third normalization frequencies are fuzzy in a form suitable for fuzzy inference, and an input value is calculated through the fuzzy inference. In this case, there is no particular limitation on the method of fuzzing, but it is preferable to perform fuzzing using a triangular or quadrangular purge number, and to calculate an input value therethrough. This may refer to the conventional fuzzy inference, so a detailed description will be omitted.

The fuzzy calculation part 735 applies a fuzzy inference rule to the first input value, the second input value, and the third input value and defuzzys them to calculate the importance of each basic term. In this case, the method of applying the fuzzy inference rule is not limited, but preferably, the first input described above to the membership function of their previous unit for each fuzzy rule generated according to the number of fuzzy determined in the input value calculation part 734. After applying the value, the second input value, and the third input value, the minimum value is taken. After that, the obtained values are classified into groups, and a fuzzy value is generated by taking the maximum value of the fuzzy value for each group. Thereafter, various conventional methods may be used for defuzzification, but most preferably, the importance of the corresponding basic term is calculated by applying defuzzification using the center of gravity method to the generated plurality of fuzzy values.

The representative designation unit 740 of the individual request analysis module 700 performs a function of designating at least one representative term from among the basic terms according to the high and low levels of importance calculated through the above-described importance calculation unit 730. That is, terms with high importance are designated as representative terms, and in this case, the representative terms may be one or more.

Furthermore, it is possible to further designate not only the primary designated representative terms, but also additional designation of representative terms. In this case, when additional representative terms are designated, some of the basic terms with high similarity to the first designated representative terms may be additionally designated as representative terms. To this end, the individual request analysis module 700 may further include a similarity calculation unit 750, a weight calculation unit 760, and an additional designation unit 770.

The similarity calculation unit 750 performs a function of calculating a frequency similarity between the designated representative term and the basic term. At this time, the reason for calculating the frequency similarity is that, in the case of the text, which is basically an individual request, no matter what expert (2), the content of interest, that is, a common theme for the ingredients and effects of cosmetics. Therefore, each individual request contains general, detailed, or partial content on the subject of cosmetics. Therefore, if the initial designated representative term is judged as the core term of the individual request, there is a high probability that other basic terms related to this will also appear together, and the similarity in the frequency distribution can be used to calculate the representative term. . Accordingly, the similarity of the frequency distribution is calculated as frequency similarity, and the frequency similarity is calculated based on Equation 4 below.

Equation 4,

는

번째 대표용어와

번째 기본용어 사이에서 산출된 빈도 유사도,

는 조정 상수,

는 상기 대표지정부(740)에서 지정된 대표용어의 수,

는

번째 대표용어의 기본 빈도수,

는

번째 기본용어의 기본 빈도수를 의미한다.here,

Is

First representative term and

Frequency similarity calculated between the first basic terms,

Is the adjustment constant,

Is the number of representative terms designated by the representative designation government 740,

Is

The basic frequency of the first representative term,

Is

Refers to the basic frequency of the first basic term.

Therefore, through Equation 4, the degree of association between the representative term and the basic term that is not classified as a representative term is calculated as a number, and the closer this value is to 1, the higher the similarity. In other words, it means that the degree of relevance is high, and the closer to 0, the lower the degree of similarity, that is, the degree of relevance is also low. In the case of the above-described variable, the adjustment constant may be set by the administrator of the system 10, and the size of the number is not limited, but an integer value between 5 and 15 may be preferably set as the adjustment constant.

The weight calculation unit 760 performs a function of calculating a weight for each of the basic terms based on the calculated frequency similarity. In this case, preferably, the higher the frequency similarity is, the higher the weight is calculated, and in the easiest way, a value obtained by multiplying the above-described inverse document frequency by the frequency similarity may be calculated as the weight.

The additional designation unit 770 performs a function of additionally designating a representative term among basic terms by reflecting a weight on the importance based on the above-described weight.After multiplying the importance by a weight, the representative term is selected based on the high and low values. Additional designation will be made.

Finally, the analysis information generation unit 780 performs a function of generating analysis information on the representative effect of the customized cosmetic based on the representative terminology generated as described above. For example, if the representative terms are moisturizing, drying, and tightening, the representative effect is moisturized and analysis information is also provided as a keyword of moisturizing, so that the effect of moisturizing can be reflected when the order is reflected. It was able to reflect the needs contained in the request.

As described so far, the configuration and operation of the customized cosmetic manufacturing system for the skin beauty industry according to the present invention is expressed in the above description and drawings, but this is only an example, and the spirit of the present invention is shown in the above description and drawings. It is not limited, and of course, various changes and changes are possible within the scope of the technical spirit of the present invention.

1: Main Server 2: Expert
3: cosmetic factory 10: system
100: subscription module 200: storage module
210: Item DB 220: Ingredient DB
300: selection module 310: item selection unit
320: Ingredient selection unit 321: Grade selection part
322: ingredient selection part 323: purpose selection part
330: quantity determination unit 340: order form generation unit
350: additional request 400: manufacturing module
500: provided module 600: component classification module
610: rating classification unit 620: purpose classification unit
700: individual request analysis module 710: term extraction unit
720: frequency identification unit 721: basic frequency calculation part
722: Text frequency calculation part 730: Importance calculation part
731: first calculation part 732: second calculation part
733: third calculation part 734: input value calculation part
735: Fuzzy calculation part 740: Representative designated government
750: similarity calculation unit 760: weight calculation unit
770: Additional designated government 780: Analysis information generation unit

Claims (13)

As a customized cosmetic manufacturing system targeting the skin beauty industry,
A subscription module for receiving expert information from a skin beauty industry expert;
A storage module including an item DB for receiving and storing item information of a manufacturable cosmetic product and an ingredient DB for receiving and storing component information that can be included in the cosmetic product;
An item selection unit receiving at least one of the item information for producing customized cosmetics from the expert, an ingredient selection unit receiving at least one of the component information from the expert, and the manufacturing capacity and quantity of manufacture from the expert A selection module comprising: a quantity determining unit receiving an input; and an order book generation unit generating an order form including the selected component information, the received item information, the manufacturing capacity, and the manufacturing quantity;
A manufacturing module for manufacturing customized cosmetics based on the order form;
A system for manufacturing customized cosmetics for the skin beauty industry, comprising: a providing module for providing the manufactured customized cosmetics to the expert. The method of claim 1,
The system is.
A component classification module comprising a classification unit for classifying a plurality of the component information into at least two or more rating groups; further comprising,
The component selection unit,
A rating selection part that receives at least one of the rating groups selected by the expert;
Includes a component selection part for selecting at least one of the component information belonging to the grade group selected by the expert,
The above order form,
A system for manufacturing customized cosmetics for the skin beauty industry, characterized in that it further comprises the selected grade group. The method of claim 2,
The component classification module,
Further comprising a purpose classification unit for secondary classification of the component information belonging to each of the rating groups into a plurality of purpose-specific groups,
The component selection unit,
Further comprising a purpose selection part for receiving the purpose-specific group selected from the expert who selected the grade group,
The above ingredient selection part,
At least one of the component information belonging to the purpose-specific group selected by the expert is selected,
The above order form,
A system for manufacturing customized cosmetics for the skin beauty industry, characterized in that it further comprises the purpose-specific group. The method of claim 1,
The selection module,
Further comprising an additional request unit for receiving individual request information from the expert,
The above order form,
A system for manufacturing customized cosmetics for the skin beauty industry, characterized in that it further comprises the individual requests. The method of claim 4,
The additional request unit,
Receive text-based individual requests from the experts,
The system,
An individual request analysis module that analyzes and processes the individual request to generate analysis information; further comprising,
The above order form,
A system for manufacturing customized cosmetics for the skin beauty industry, characterized in that it further comprises the analysis information. The method of claim 5,
The individual request analysis module,
A customized cosmetic manufacturing system for the skin beauty industry, characterized in that analyzing and processing the individual request based on fuzzy inference to generate analysis information on the representative effect of the customized cosmetic to be manufactured. The method of claim 6,
The individual request analysis module,
A term extraction unit that extracts a plurality of basic terms from text, and
A frequency identification unit for grasping the frequency for each of the basic terms, and
An importance calculation unit that calculates importance for each of the basic terms by performing fuzzy inference on the basic terms based on the frequency number, and
A representative designating government that designates at least one representative term from among the basic terms according to the high and low of the importance, and
And an analysis information generation unit that generates analysis information on the representative effect of the customized cosmetics based on the representative terminology. The method of claim 7,
The frequency determination unit,
A basic frequency calculation part for grasping the basic frequency for each of the basic terms; and
Includes a text frequency calculation part for grasping the text frequency for each of the basic terms,
The importance calculation unit,
A first calculation part for calculating a first normalized frequency by performing normalization on the basic frequency;
A second calculation part for calculating a second normalization frequency by performing normalization on the text frequency, and
A third calculation part for calculating a third normalization frequency by performing normalization on the reciprocal of the text frequency; and
An input value calculation part for calculating a first input value, a second input value, and a third input value by fuzzifying the first normalization frequency, the second normalization frequency, and the third normalization frequency;
And a fuzzy calculation part for calculating the importance of each basic term by applying a fuzzy reasoning rule to the first input value, the second input value, and the third input value and defuzzying it. A customized cosmetic manufacturing system for customers. The method of claim 8,
The first normalization frequency is,
Customized cosmetic manufacturing system for the skin beauty industry, characterized in that calculated through the following equation (1).
Equation 1,

(here,

Is the term

The first normalized frequency for,

Is the term

The default frequency of,

Is the term

Text frequency) The method of claim 8,
The second normalization frequency is,
A system for manufacturing customized cosmetics for the skin beauty industry, characterized in that it is calculated through Equation 2 below.
Equation 2,

(here,

Is the term

The second normalized frequency for,

Is the term

Text frequency of,

Is the total number of individual requests entered into the system) The method of claim 8,
The third normalization frequency is,
A customized cosmetic manufacturing system for the skin beauty industry, characterized in that it is calculated through the following Equation 3.
Equation 3,

(here,

Is the term

The third normalized frequency for,

Is the term

Text frequency) The method of claim 8,
The individual request analysis module,
A similarity calculation unit that calculates a frequency similarity between the designated representative term and the basic term, and
A weight calculation unit that calculates a weight for each of the basic terms based on the frequency similarity, and
A system for manufacturing customized cosmetics for the skin beauty industry, characterized in that it further comprises an additional designator for additionally designating the representative term among the basic terms based on the weight. The method of claim 12,
The similarity calculation unit,
A customized cosmetic manufacturing system for the skin beauty industry, characterized in that the frequency similarity is calculated based on Equation 4 below.
Equation 4,

(here,

Is

First representative term and

Frequency similarity calculated between the first basic terms,

Is the adjustment constant,

Is the number of representative terms designated by the representative designated government,

Is

The basic frequency of the first representative term,

Is

Basic frequency of the first basic term)

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