Preparation method of shampoo for preventing hair loss and related device

Abstract

The invention discloses a preparation method of shampoo for preventing hair loss and a related device. The method comprises the following steps: acquiring P types of shampoo for preventing hair loss; determining a test group corresponding to each anti-hair loss shampoo in the P anti-hair loss shampoo, and obtaining P test groups; acquiring test data of each test group in the P test groups to obtain P groups of test data; acquiring first attribute information of the target object; acquiring P groups of partial test data corresponding to the first attribute information from the P groups of test data; determining corresponding anti-hair loss effect evaluation parameters according to each part of test data in the P groups of part test data to obtain P anti-hair loss effect evaluation parameters; and selecting a maximum value from the P anti-hair loss effect evaluation parameters, and obtaining a target anti-hair loss shampoo corresponding to the maximum value from the P anti-hair loss shampoo. By adopting the embodiment of the invention, the appropriate shampoo can be adapted according to the personalized condition of the user.

Description

[0001] This application claims the priority of the Chinese patent application filed with the China Patent Office on April 19, 2024, with application number 202410477003.8 and application name “A method for preparing shampoo and related devices for preventing hair loss”, the entire contents of which are incorporated by reference in this application. Technical Field

[0002] The present application relates to the field of cosmetic technology or the field of automated shampoo preparation technology or the field of artificial intelligence technology, and specifically to a method for preparing shampoo for preventing hair loss and a related device. Background Art

[0003] In life, hair is an important part of a person's appearance. However, hair loss is also a common problem in life. Faced with a wide variety of shampoos, it is difficult to quickly adapt to a shampoo that suits oneself. Therefore, how to adapt the appropriate shampoo according to the user's personalized situation needs to be solved urgently. Summary of the invention

[0004] The embodiments of the present application provide a method for preparing shampoo for preventing hair loss and a related device, which can prepare shampoo suitable for the user's personal hair type, improve the user's hair washing and hair care efficiency, and also improve the user experience.

[0005] In a first aspect, an embodiment of the present application provides a method for preparing a shampoo for preventing hair loss, the method comprising:

[0006] Obtaining P types of anti-hair loss shampoos, wherein the anti-hair loss component parameters of each of the P types of anti-hair loss shampoos are different and the other shampoo configuration components are the same;

[0007] Determine a test group corresponding to each of the P types of anti-hair loss shampoos to obtain P test groups; each test group includes a plurality of test subjects; each test subject corresponds to a property information;

[0008] Acquire test data of each test group in the P test groups to obtain P groups of test data, each group of test data includes multiple test data sets, each test data set corresponds to multiple test data of a test object, and each test data includes hair data;

[0009] Obtaining first attribute information of a target object;

[0010] Acquire P groups of partial test data corresponding to the first attribute information from the P groups of test data, each group of partial test data includes at least one test data set, each test data set corresponds to a plurality of test data of a test object, and each test data includes hair data;

[0011] Determine a corresponding anti-hair loss effect evaluation parameter according to each portion of the P groups of partial test data, to obtain P anti-hair loss effect evaluation parameters;

[0012] Selecting a maximum value from the P anti-hair loss effect evaluation parameters, and obtaining a target anti-hair loss shampoo corresponding to the maximum value from the P types of anti-hair loss shampoos;

[0013] The target anti-hair loss shampoo is pushed to the target object.

[0014] In a second aspect, an embodiment of the present application provides a shampoo dispensing device for preventing hair loss, the device comprising: an acquisition unit, a determination unit and a push unit, wherein:

[0015] The acquisition unit is used to acquire P types of anti-hair loss shampoos, wherein the anti-hair loss component parameters of each of the P types of anti-hair loss shampoos are different and the other shampoo configuration components are the same;

[0016] The determination unit is used to determine a test group corresponding to each of the P types of anti-hair loss shampoos, to obtain P test groups; each test group includes a plurality of test subjects; each test subject corresponds to a property information;

[0017] The acquisition unit is further used to acquire test data of each test group in the P test groups to obtain P groups of test data, each group of test data includes multiple test data sets, each test data set corresponds to multiple test data of a test object, and each test data includes hair data;

[0018] The acquisition unit is further used to acquire first attribute information of the target object; acquire P groups of partial test data corresponding to the first attribute information from the P groups of test data, each group of partial test data includes at least one test data set, each test data set corresponds to multiple test data of a test object, and each test data includes hair data;

[0019] The determining unit is further used to determine a corresponding anti-hair loss effect evaluation parameter according to each portion of the P groups of partial test data, to obtain P anti-hair loss effect evaluation parameters;

[0020] The acquisition unit is further used to select a maximum value from the P anti-hair loss effect evaluation parameters, and acquire a target anti-hair loss shampoo corresponding to the maximum value from the P types of anti-hair loss shampoos;

[0021] The pushing unit is used to push the target anti-hair loss shampoo to the target object.

[0022] In a third aspect, an embodiment of the present application provides a shampoo preparation device for preventing hair loss, comprising a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the first aspect of the embodiment of the present application.

[0023] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps described in the first aspect of the embodiment of the present application.

[0024] In a fifth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in the first aspect of the embodiment of the present application. The computer program product may be a software installation package.

[0025] The implementation of the embodiments of the present application has the following beneficial effects:

[0026] It can be seen that the method and related devices for configuring shampoo for preventing hair loss described in the embodiments of the present application obtain P kinds of anti-hair loss shampoos, the anti-hair loss component parameters of each of the P kinds of anti-hair loss shampoos are different and the configuration components of other shampoos are the same, a test group corresponding to each of the P kinds of anti-hair loss shampoos is determined, and P test groups are obtained; each test group includes multiple test objects; each test object corresponds to an attribute information, test data of each test group in the P test groups are obtained, and P groups of test data are obtained, each group of test data includes multiple test data sets, each test data set corresponds to multiple test data of a test object, and each test data includes hair data, first attribute information of the target object is obtained, and the first attribute information corresponding to the first attribute information is obtained from the P groups of test data. P groups of partial test data are corresponding, each group of partial test data includes at least one test data set, each test data set corresponds to multiple test data of a test object, each test data includes hair data, and corresponding anti-hair loss effect evaluation parameters are determined according to each part of the test data in the P groups of partial test data to obtain P anti-hair loss effect evaluation parameters, a maximum value is selected from the P anti-hair loss effect evaluation parameters, and a target anti-hair loss shampoo corresponding to the maximum value is obtained from the P anti-hair loss shampoos, and the target anti-hair loss shampoo is pushed to the target object. In this way, anti-hair loss shampoos with different formulas can be tested, and the test data of suitable test objects can be adapted for users in need, and the anti-hair loss shampoo that best suits the users in need can be selected using these test data, that is, the suitable shampoo can be adapted according to the user's personalized situation. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0028] Figure 1 It is a schematic flow chart of a method for preparing a shampoo for preventing hair loss provided in an embodiment of the present application;

[0029] Figure 2 It is a structural schematic diagram of another shampoo dispensing device for preventing hair loss provided in an embodiment of the present application;

[0030] Figure 3 This is a block diagram of the functional units of a shampoo dispensing device for preventing hair loss provided in an embodiment of the present application. DETAILED DESCRIPTION

[0031] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but in a possible example also includes steps or units that are not listed, or in a possible example also includes other steps or units inherent to these processes, methods, products or devices.

[0032] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0033] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0034] In the embodiment of the present application, the shampoo configuration device for preventing hair loss can be set in a production plant to realize batch personalized shampoo configuration. The shampoo configuration device can also be set in a public place to realize retail shampoo, for example, to provide personalized shampoo configuration for hotels, guesthouses, and hair salons, and can also provide personalized shampoo for families. Of course, the shampoo configuration device for preventing hair loss can also be a server or other equipment.

[0035] See also Figure 1 , Figure 1 1 is a flow chart of a method for preparing a shampoo for preventing hair loss provided in an embodiment of the present application. As shown in the figure, the method for preparing a shampoo for preventing hair loss includes:

[0036] 101. Obtain P types of anti-hair loss shampoos, wherein the anti-hair loss ingredient parameters of each of the P types of anti-hair loss shampoos are different and the configuration ingredients of other shampoos are the same.

[0037] In the embodiment of the present application, P is an integer greater than 1. The anti-hair loss component parameter may include at least one of the following: anti-hair loss component type, anti-hair loss component ratio, etc., which are not limited here.

[0038] In a specific implementation, P types of anti-hair loss shampoos may be obtained, each of the P types of anti-hair loss shampoos having different anti-hair loss ingredient parameters and the other shampoos having the same configuration ingredients.

[0039] 102. Determine a test group corresponding to each of the P types of anti-hair loss shampoos to obtain P test groups; each test group includes multiple test subjects; and each test subject corresponds to an attribute information.

[0040] In the embodiment of the present application, the attribute information may include at least one of the following: gender, age, occupation, height, weight, physique, living habits, race, etc., which are not limited here.

[0041] In a specific implementation, each of the P types of anti-hair loss shampoos corresponds to a test group, and P test groups are obtained, each test group includes multiple test subjects; each test subject corresponds to a property information. Each test subject corresponds to a person.

[0042] 103. Acquire test data of each of the P test groups to obtain P groups of test data, each group of test data includes multiple test data sets, each test data set corresponds to multiple test data of a test object, and each test data includes hair data.

[0043] In an embodiment of the present application, test data of each test group in P test groups can be obtained to obtain P groups of test data, each group of test data includes multiple test data sets, each test data set corresponds to multiple test data of a test object, each test data includes hair data, and the hair data may include hair images, scalp data, etc., which are not limited here.

[0044] 104. Obtain first attribute information of the target object.

[0045] In an embodiment of the present application, the first attribute information of any target object can be obtained. The first attribute information may include at least one of the following: gender, age, occupation, height, weight, physique, living habits, race, etc., which are not limited here.

[0046] 105. Obtain P groups of partial test data corresponding to the first attribute information from the P groups of test data, each group of partial test data includes at least one test data set, each test data set corresponds to multiple test data of a test object, and each test data includes hair data.

[0047] In an embodiment of the present application, P groups of partial test data corresponding to the first attribute information can be obtained from P groups of test data, that is, partial test data corresponding to the first attribute information is selected from each group of test data in the P groups of test data to obtain P groups of partial test data, each group of partial test data includes at least one test data set, each test data set corresponds to multiple test data of a test object, and each test data includes hair data.

[0048] 106. Determine a corresponding anti-hair loss effect evaluation parameter according to each portion of the P groups of partial test data to obtain P anti-hair loss effect evaluation parameters.

[0049] In the embodiment of the present application, the anti-hair loss effect evaluation parameter is used to evaluate the quality of the anti-hair loss effect. The larger the anti-hair loss effect evaluation parameter is, the better the anti-hair loss effect is. Conversely, the smaller the anti-hair loss effect evaluation parameter is, the worse the anti-hair loss effect is.

[0050] In a specific implementation, the corresponding anti-hair loss effect evaluation parameter can be determined according to each part of the test data in the P groups of partial test data to obtain P anti-hair loss effect evaluation parameters.

[0051] Optionally, the above step 106, determining the corresponding anti-hair loss effect evaluation parameter according to each part of the test data in the P groups of partial test data to obtain P anti-hair loss effect evaluation parameters, may include the following steps:

[0052] 61. Obtain target partial test data, where the target partial test data is any test data in the P group of partial test data;

[0053] 62. Obtain a hair density parameter corresponding to the hair data of each test data set in the target portion of the test data, and obtain at least one hair density parameter of each test data set;

[0054] 63. Determine a target anti-hair loss effect evaluation parameter based on at least one hair density parameter of each test data set.

[0055] In an embodiment of the present application, taking the target part test data as an example, the target part test data is any test data in the P group of partial test data, then the target part test data can be obtained, and then the hair density parameters corresponding to the hair data of each test data set in the target part test data can be obtained, and at least one hair density parameter of each test data set can be obtained. Then, the target anti-hair loss effect evaluation parameter can be determined according to at least one hair density parameter of each test data set. In this way, the effect of each anti-hair loss shampoo can be accurately determined.

[0056] Further, optionally, the above step 63, determining the target anti-hair loss effect evaluation parameter according to at least one hair density parameter of each test data set, may include the following steps:

[0057] 631. Determine an anti-hair loss effect evaluation parameter corresponding to at least one hair density parameter of each test data set to obtain a plurality of anti-hair loss effect evaluation parameters;

[0058] 632. Determine the target anti-hair loss effect evaluation parameter according to the multiple anti-hair loss effect evaluation parameters.

[0059] In an embodiment of the present application, an anti-hair loss effect evaluation parameter corresponding to at least one hair density parameter of each test data set can be determined to obtain multiple anti-hair loss effect evaluation parameters, and then a target anti-hair loss effect evaluation parameter can be determined based on the multiple anti-hair loss effect evaluation parameters. For example, the mean of the multiple anti-hair loss effect evaluation parameters can be determined and the mean can be used as the target anti-hair loss effect evaluation parameter.

[0060] Further, optionally, each hair density parameter corresponds to a test time; the above step 631, determining the anti-hair loss effect evaluation parameter corresponding to at least one hair density parameter of each test data set to obtain multiple anti-hair loss effect evaluation parameters, may include the following steps:

[0061] A1. Perform fitting according to at least one hair density parameter of a first test data set and a corresponding test time to obtain a fitting straight line; the first test data set is any test data set in each of the test data sets;

[0062] A2. Obtaining the target slope of the fitting straight line;

[0063] A3. Determine the anti-hair loss effect evaluation parameter corresponding to the target slope.

[0064] Among them, the hair density parameter can be determined by calculating the hair content per unit area using image recognition technology.

[0065] In the embodiment of the present application, taking the first test data set as an example, the first test data set is any test data set in each test data set. Fitting can be performed according to at least one hair density parameter of the first test data set and the corresponding test time to obtain a fitting straight line. The horizontal axis of the fitting straight line is time, and the vertical axis is the hair density parameter. The target slope of the fitting straight line is obtained, and the mapping relationship between the preset slope and the anti-hair loss effect evaluation parameter can be pre-set, and then the anti-hair loss effect evaluation parameter corresponding to the target slope is determined according to the mapping relationship. That is, the anti-hair loss effect can be dynamically evaluated by fitting, which is helpful to accurately evaluate the anti-hair loss effect.

[0066] Further, optionally, each hair density parameter corresponds to a test time; the above step 631, determining the anti-hair loss effect evaluation parameter corresponding to at least one hair density parameter of each test data set to obtain multiple anti-hair loss effect evaluation parameters, may include the following steps:

[0067] B1. Determine the hair density parameter increments at adjacent test times according to at least one hair density parameter of the first test data set to obtain at least one hair density parameter increment; the second test data set is any one of the test data sets;

[0068] B2. determining the mean square error of the at least one hair density parameter increment to obtain a target mean square error;

[0069] B3. Determine the anti-hair loss effect evaluation parameter corresponding to the target mean square deviation.

[0070] In the embodiment of the present application, taking the second test data set as an example, the second test data set is any test data set in each test data set, and the hair density parameter increments of adjacent test times are determined according to at least one hair density parameter of the first test data set to obtain at least one hair density parameter increment, and the difference between the hair density parameter increments before and after the hair density parameter increment, and then the mean square error of at least one hair density parameter increment is determined to obtain the target mean square error. A mapping relationship between a preset mean square error and an anti-hair loss effect evaluation parameter can also be pre-set, and the anti-hair loss effect evaluation parameter corresponding to the target mean square error is determined based on the mapping relationship. In this way, the anti-hair loss effect can be dynamically evaluated based on the anti-hair loss effect after each user washes their hair, and the mean square error reflects the fluctuation change process after using the anti-hair loss shampoo, which helps to deeply reflect the actual anti-hair loss effect of the user.

[0071] Optionally, the above step 632, determining the target anti-hair loss effect evaluation parameter according to the multiple anti-hair loss effect evaluation parameters, may include the following steps:

[0072] S1. Obtaining second attribute information of the test object of each anti-hair loss effect evaluation parameter corresponding to the multiple anti-hair loss effect evaluation parameters to obtain multiple second attribute information;

[0073] S2, obtaining target second attribute information of the target object;

[0074] S3, determining a matching value between each second attribute information in the plurality of second attribute information and the target second attribute information, to obtain a plurality of matching values;

[0075] S4. Determine the weights corresponding to the multiple matching values ​​to obtain multiple weights;

[0076] S5. Perform a weighted operation on the multiple anti-hair loss effect evaluation parameters and the multiple weights to obtain the target anti-hair loss effect evaluation parameter.

[0077] In an embodiment of the present application, the second attribute information of the test object corresponding to each of the multiple anti-hair loss effect evaluation parameters can be obtained to obtain multiple second attribute information, and then the target second attribute information of the target object can be obtained. The matching value between each of the multiple second attribute information and the target second attribute information can also be determined to obtain multiple matching values, and then the weights corresponding to the multiple matching values ​​can be determined to obtain multiple weights. The larger the matching value, the larger the weight. The sum of the multiple weights is 1, and then the multiple anti-hair loss effect evaluation parameters and the multiple weights are weightedly calculated to obtain the target anti-hair loss effect evaluation parameters. In this way, the corresponding weights can be reasonably allocated based on the attribute correlation of the user, which is helpful to recommend a shampoo that deeply meets the user's personalized situation and helps to further ensure the anti-hair loss effect.

[0078] 107. Select a maximum value from the P anti-hair loss effect evaluation parameters, and obtain a target anti-hair loss shampoo corresponding to the maximum value from the P types of anti-hair loss shampoos.

[0079] In the embodiment of the present application, the maximum value can be selected from P anti-hair loss effect evaluation parameters, and the target anti-hair loss shampoo corresponding to the maximum value can be obtained from the P anti-hair loss shampoos. In this way, the shampoo that best suits the user's personalized situation can be selected, which helps to ensure the anti-hair loss effect.

[0080] 108. Push the target anti-hair loss shampoo to the target object.

[0081] In the embodiment of the present application, the target anti-hair loss shampoo can be directly pushed to the target object, that is, the target object can be recommended to use the target anti-hair loss shampoo. Of course, the target anti-hair loss shampoo can also be optimized based on the target object's own situation to obtain a shampoo that is more suitable for the target object, thereby deeply improving the anti-hair loss effect.

[0082] Optionally, the above step 108, pushing the target anti-hair loss shampoo to the target object, may include the following steps:

[0083] 81. Acquire target physiological state parameters of the target object;

[0084] 82. Determine a target optimization parameter corresponding to the target physiological state parameter;

[0085] 83. Optimize the anti-hair loss component parameters corresponding to the target anti-hair loss shampoo according to the target optimization parameters to obtain the target anti-hair loss component parameters;

[0086] 84. Replacing the anti-hair loss component parameters in the target anti-hair loss shampoo according to the target anti-hair loss component parameters to obtain an optimized anti-hair loss shampoo;

[0087] 85. Push the optimized anti-hair loss shampoo to the target object.

[0088] The target physiological state parameter may include at least one of the following: blood pressure, blood lipids, blood sugar, heart rate, allergic substances, etc., which are not limited here.

[0089] In an embodiment of the present application, the target physiological state parameters of the target object can be obtained, and the mapping relationship between the preset physiological state parameters and the optimization parameters can be pre-stored. Then, the target optimization parameters corresponding to the target physiological state parameters can be determined based on the mapping relationship, and then the anti-hair loss ingredient parameters corresponding to the target anti-hair loss shampoo can be optimized according to the target optimization parameters to obtain the target anti-hair loss ingredient parameters. Finally, the anti-hair loss ingredient parameters in the target anti-hair loss shampoo can be replaced according to the target anti-hair loss ingredient parameters to obtain the optimized anti-hair loss shampoo, and the optimized anti-hair loss shampoo can be pushed to the target object. In this way, a system that deeply meets the user's personalized situation, for example, physiological state, such as physical condition, excluding allergies, can be obtained, which helps to ensure the user's physical and mental health on the basis of preventing hair loss.

[0090] It can be seen that a method for configuring shampoo for preventing hair loss described in the embodiment of the present application obtains P kinds of anti-hair loss shampoos, wherein the anti-hair loss component parameters of each of the P kinds of anti-hair loss shampoos are different and the configuration components of other shampoos are the same, a test group corresponding to each of the P kinds of anti-hair loss shampoos is determined, and P test groups are obtained; each test group includes multiple test objects; each test object corresponds to an attribute information, test data of each test group in the P test groups is obtained, and P groups of test data are obtained, each group of test data includes multiple test data sets, each test data set corresponds to multiple test data of a test object, and each test data includes hair data, first attribute information of the target object is obtained, and the first attribute information corresponding to the first attribute information is obtained from the P groups of test data. P groups of partial test data, each group of partial test data includes at least one test data set, each test data set corresponds to multiple test data of a test object, each test data includes hair data, and corresponding anti-hair loss effect evaluation parameters are determined according to each part of the test data in the P groups of partial test data to obtain P anti-hair loss effect evaluation parameters, a maximum value is selected from the P anti-hair loss effect evaluation parameters, and a target anti-hair loss shampoo corresponding to the maximum value is obtained from the P anti-hair loss shampoos, and the target anti-hair loss shampoo is pushed to the target object. In this way, anti-hair loss shampoos with different formulas can be tested, and the test data of suitable test objects can be adapted for the users in need, and the anti-hair loss shampoo that best suits the users in need can be selected using these test data, that is, the suitable shampoo can be adapted according to the user's personalized situation.

[0091] In accordance with the above embodiment, please refer to Figure 2 , Figure 2 It is a structural schematic diagram of a shampoo dispensing device for preventing hair loss provided in an embodiment of the present application. As shown in the figure, the device includes a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor. In the embodiment of the present application, the program includes instructions for executing the following steps:

[0092] Obtaining P types of anti-hair loss shampoos, wherein the anti-hair loss component parameters of each of the P types of anti-hair loss shampoos are different and the other shampoo configuration components are the same;

[0093] Determine a test group corresponding to each of the P types of anti-hair loss shampoos to obtain P test groups; each test group includes a plurality of test subjects; each test subject corresponds to a property information;

[0094] Acquire test data of each test group in the P test groups to obtain P groups of test data, each group of test data includes multiple test data sets, each test data set corresponds to multiple test data of a test object, and each test data includes hair data;

[0095] Obtaining first attribute information of a target object;

[0096] Acquire P groups of partial test data corresponding to the first attribute information from the P groups of test data, each group of partial test data includes at least one test data set, each test data set corresponds to a plurality of test data of a test object, and each test data includes hair data;

[0097] Determine a corresponding anti-hair loss effect evaluation parameter according to each portion of the P groups of partial test data, to obtain P anti-hair loss effect evaluation parameters;

[0098] Selecting a maximum value from the P anti-hair loss effect evaluation parameters, and obtaining a target anti-hair loss shampoo corresponding to the maximum value from the P types of anti-hair loss shampoos;

[0099] The target anti-hair loss shampoo is pushed to the target object.

[0100] Optionally, in the aspect of determining the corresponding anti-hair loss effect evaluation parameter according to each portion of the P groups of partial test data to obtain P anti-hair loss effect evaluation parameters, the above program includes instructions for executing the following steps:

[0101] Acquire target partial test data, where the target partial test data is any test data in the P group of partial test data;

[0102] Acquire the hair density parameter corresponding to the hair data of each test data set in the target part test data, and obtain at least one hair density parameter of each test data set;

[0103] A target anti-hair loss effect evaluation parameter is determined according to at least one hair density parameter of each test data set.

[0104] Optionally, in determining the target anti-hair loss effect evaluation parameter according to at least one hair density parameter of each test data set, the program includes instructions for executing the following steps:

[0105] Determine an anti-hair loss effect evaluation parameter corresponding to at least one hair density parameter of each test data set to obtain a plurality of anti-hair loss effect evaluation parameters;

[0106] The target anti-hair loss effect evaluation parameter is determined according to the multiple anti-hair loss effect evaluation parameters.

[0107] Optionally, each hair density parameter corresponds to a test time; in determining the anti-hair loss effect evaluation parameter corresponding to at least one hair density parameter of each test data set to obtain a plurality of anti-hair loss effect evaluation parameters, the program includes instructions for executing the following steps:

[0108] Perform fitting according to at least one hair density parameter of a first test data set and a corresponding test time to obtain a fitting straight line; the first test data set is any test data set in each of the test data sets;

[0109] Obtaining a target slope of the fitted straight line;

[0110] Determine the anti-hair loss effect evaluation parameter corresponding to the target slope.

[0111] Optionally, each hair density parameter corresponds to a test time; in determining the anti-hair loss effect evaluation parameter corresponding to at least one hair density parameter of each test data set to obtain a plurality of anti-hair loss effect evaluation parameters, the program includes instructions for executing the following steps:

[0112] Determine the hair density parameter increments at adjacent test times according to at least one hair density parameter of the first test data set, to obtain at least one hair density parameter increment; the second test data set is any one of the test data sets;

[0113] determining a mean square error of the at least one hair density parameter increment to obtain a target mean square error;

[0114] Determine the anti-hair loss effect evaluation parameter corresponding to the target mean square deviation.

[0115] Optionally, in determining the target anti-hair loss effect evaluation parameter according to the multiple anti-hair loss effect evaluation parameters, the program includes instructions for executing the following steps:

[0116] Acquire second attribute information of the test object of each anti-hair loss effect evaluation parameter corresponding to the plurality of anti-hair loss effect evaluation parameters, to obtain a plurality of second attribute information;

[0117] Acquire target second attribute information of the target object;

[0118] Determine a matching value between each second attribute information in the plurality of second attribute information and the target second attribute information to obtain a plurality of matching values;

[0119] Determine weights corresponding to the multiple matching values ​​to obtain multiple weights;

[0120] The multiple anti-hair loss effect evaluation parameters are weightedly calculated with the multiple weights to obtain the target anti-hair loss effect evaluation parameters.

[0121] Optionally, in the aspect of pushing the target anti-hair loss shampoo to the target object, the above program includes instructions for executing the following steps:

[0122] Acquiring target physiological state parameters of the target object;

[0123] Determining target optimization parameters corresponding to the target physiological state parameters;

[0124] Optimizing the anti-hair loss component parameters corresponding to the target anti-hair loss shampoo according to the target optimization parameters to obtain the target anti-hair loss component parameters;

[0125] replacing the anti-hair loss component parameters in the target anti-hair loss shampoo according to the target anti-hair loss component parameters to obtain an optimized anti-hair loss shampoo;

[0126] The optimized anti-hair loss shampoo is pushed to the target object.

[0127] It can be seen that the shampoo configuration device for preventing hair loss described in the embodiment of the present application obtains P kinds of anti-hair loss shampoos, the anti-hair loss component parameters of each of the P kinds of anti-hair loss shampoos are different and the configuration components of other shampoos are the same, a test group corresponding to each of the P kinds of anti-hair loss shampoos is determined, and P test groups are obtained; each test group includes multiple test objects; each test object corresponds to an attribute information, test data of each test group in the P test groups is obtained, and P groups of test data are obtained, each group of test data includes multiple test data sets, each test data set corresponds to multiple test data of a test object, and each test data includes hair data, and first attribute information of the target object is obtained, and the first attribute information corresponding to the first attribute information is obtained from the P groups of test data. P groups of partial test data, each group of partial test data includes at least one test data set, each test data set corresponds to multiple test data of a test object, each test data includes hair data, and corresponding anti-hair loss effect evaluation parameters are determined according to each part of the test data in the P groups of partial test data to obtain P anti-hair loss effect evaluation parameters, a maximum value is selected from the P anti-hair loss effect evaluation parameters, and a target anti-hair loss shampoo corresponding to the maximum value is obtained from the P anti-hair loss shampoos, and the target anti-hair loss shampoo is pushed to the target object. In this way, anti-hair loss shampoos with different formulas can be tested, and the test data of suitable test objects can be adapted for the users in need, and the anti-hair loss shampoo that best suits the users in need can be selected using these test data, that is, the suitable shampoo can be adapted according to the user's personalized situation.

[0128] Figure 3 300 is a functional unit composition block diagram of a shampoo configuration device 300 for preventing hair loss involved in an embodiment of the present application. The shampoo configuration device 300 for preventing hair loss includes: an acquisition unit 301, a determination unit 302 and a push unit 303, wherein:

[0129] The acquisition unit 301 is used to acquire P types of anti-hair loss shampoos, wherein the anti-hair loss component parameters of each of the P types of anti-hair loss shampoos are different and the other shampoo configuration components are the same;

[0130] The determining unit 302 is used to determine a test group corresponding to each of the P types of anti-hair loss shampoos, to obtain P test groups; each test group includes a plurality of test subjects; each test subject corresponds to a property information;

[0131] The acquisition unit 301 is further used to acquire test data of each test group in the P test groups to obtain P groups of test data, each group of test data includes multiple test data sets, each test data set corresponds to multiple test data of a test object, and each test data includes hair data;

[0132] The acquisition unit 301 is further used to acquire first attribute information of the target object; acquire P groups of partial test data corresponding to the first attribute information from the P groups of test data, each group of partial test data includes at least one test data set, each test data set corresponds to multiple test data of a test object, and each test data includes hair data;

[0133] The determining unit 302 is further configured to determine a corresponding anti-hair loss effect evaluation parameter according to each portion of the P groups of partial test data, to obtain P anti-hair loss effect evaluation parameters;

[0134] The acquisition unit 301 is further configured to select a maximum value from the P anti-hair loss effect evaluation parameters, and acquire a target anti-hair loss shampoo corresponding to the maximum value from the P types of anti-hair loss shampoos;

[0135] The pushing unit 303 is used to push the target anti-hair loss shampoo to the target object.

[0136] Optionally, in determining the corresponding anti-hair loss effect evaluation parameter according to each portion of the P groups of partial test data to obtain P anti-hair loss effect evaluation parameters, the determining unit 302 is specifically used to:

[0137] Acquire target partial test data, where the target partial test data is any test data in the P group of partial test data;

[0138] Acquire the hair density parameter corresponding to the hair data of each test data set in the target part test data, and obtain at least one hair density parameter of each test data set;

[0139] A target anti-hair loss effect evaluation parameter is determined according to at least one hair density parameter of each test data set.

[0140] Further, optionally, in determining the target anti-hair loss effect evaluation parameter according to at least one hair density parameter of each test data set, the determining unit 302 is specifically configured to:

[0141] Determine an anti-hair loss effect evaluation parameter corresponding to at least one hair density parameter of each test data set to obtain a plurality of anti-hair loss effect evaluation parameters;

[0142] The target anti-hair loss effect evaluation parameter is determined according to the multiple anti-hair loss effect evaluation parameters.

[0143] Further, optionally, each hair density parameter corresponds to a test time; in determining the anti-hair loss effect evaluation parameter corresponding to at least one hair density parameter of each test data set to obtain a plurality of anti-hair loss effect evaluation parameters, the determining unit 302 is specifically used to:

[0144] Perform fitting according to at least one hair density parameter of a first test data set and a corresponding test time to obtain a fitting straight line; the first test data set is any test data set in each of the test data sets;

[0145] Obtaining a target slope of the fitted straight line;

[0146] Determine the anti-hair loss effect evaluation parameter corresponding to the target slope.

[0147] Further, optionally, each hair density parameter corresponds to a test time; in determining the anti-hair loss effect evaluation parameter corresponding to at least one hair density parameter of each test data set to obtain a plurality of anti-hair loss effect evaluation parameters, the determining unit 302 is specifically used to:

[0148] Determine the hair density parameter increments at adjacent test times according to at least one hair density parameter of the first test data set, to obtain at least one hair density parameter increment; the second test data set is any one of the test data sets;

[0149] determining a mean square error of the at least one hair density parameter increment to obtain a target mean square error;

[0150] Determine the anti-hair loss effect evaluation parameter corresponding to the target mean square deviation.

[0151] Optionally, in determining the target anti-hair loss effect evaluation parameter according to the multiple anti-hair loss effect evaluation parameters, the determining unit 302 is specifically configured to:

[0152] Acquire second attribute information of the test object of each anti-hair loss effect evaluation parameter corresponding to the plurality of anti-hair loss effect evaluation parameters, to obtain a plurality of second attribute information;

[0153] Acquire target second attribute information of the target object;

[0154] Determine a matching value between each second attribute information in the plurality of second attribute information and the target second attribute information to obtain a plurality of matching values;

[0155] Determine weights corresponding to the multiple matching values ​​to obtain multiple weights;

[0156] The multiple anti-hair loss effect evaluation parameters are weightedly calculated with the multiple weights to obtain the target anti-hair loss effect evaluation parameters.

[0157] Optionally, in the aspect of pushing the target anti-hair loss shampoo to the target object, the pushing unit 303 is specifically used for:

[0158] Acquiring target physiological state parameters of the target object;

[0159] Determining target optimization parameters corresponding to the target physiological state parameters;

[0160] Optimizing the anti-hair loss component parameters corresponding to the target anti-hair loss shampoo according to the target optimization parameters to obtain the target anti-hair loss component parameters;

[0161] replacing the anti-hair loss component parameters in the target anti-hair loss shampoo according to the target anti-hair loss component parameters to obtain an optimized anti-hair loss shampoo;

[0162] The optimized anti-hair loss shampoo is pushed to the target object.

[0163] It can be seen that the shampoo configuration device for preventing hair loss described in the embodiment of the present application obtains P kinds of anti-hair loss shampoos, the anti-hair loss component parameters of each of the P kinds of anti-hair loss shampoos are different and the configuration components of other shampoos are the same, a test group corresponding to each of the P kinds of anti-hair loss shampoos is determined, and P test groups are obtained; each test group includes multiple test objects; each test object corresponds to an attribute information, test data of each test group in the P test groups is obtained, and P groups of test data are obtained, each group of test data includes multiple test data sets, each test data set corresponds to multiple test data of a test object, and each test data includes hair data, first attribute information of the target object is obtained, and the first attribute information corresponding to the first attribute information is obtained from the P groups of test data. P groups of partial test data, each group of partial test data includes at least one test data set, each test data set corresponds to multiple test data of a test object, each test data includes hair data, and corresponding anti-hair loss effect evaluation parameters are determined according to each part of the test data in the P groups of partial test data to obtain P anti-hair loss effect evaluation parameters, a maximum value is selected from the P anti-hair loss effect evaluation parameters, and a target anti-hair loss shampoo corresponding to the maximum value is obtained from the P anti-hair loss shampoos, and the target anti-hair loss shampoo is pushed to the target object. In this way, anti-hair loss shampoos with different formulas can be tested, and the test data of suitable test objects can be adapted for the users in need, and the anti-hair loss shampoo that best suits the users in need can be selected using these test data, that is, the suitable shampoo can be adapted according to the user's personalized situation.

[0164] It can be understood that the functions of each program module of a shampoo preparation device for preventing hair loss in this embodiment can be specifically implemented according to the method in the above method embodiment, and its specific implementation process can refer to the relevant description of the above method embodiment, which will not be repeated here.

[0165] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, the computer program enables a computer to execute part or all of the steps of any method recorded in the above method embodiments, and the above computer includes a shampoo preparation device for preventing hair loss.

[0166] The present application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program can be operated to cause a computer to execute some or all of the steps of any method described in the above method embodiment. The computer program product can be a software installation package, and the computer includes a shampoo dispensing device for preventing hair loss.

[0167] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0168] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0169] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the above-mentioned units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0170] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0171] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0172] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the above-mentioned methods of each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or CD-ROM and other media that can store program codes.

[0173] A person skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (English: Read-Only Memory, abbreviated as: ROM), a random access memory (English: Random Access Memory, abbreviated as: RAM), a magnetic disk or an optical disk, etc.

[0174] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for preparing a shampoo for preventing hair loss, characterized in that: The method comprises: Obtaining P types of anti-hair loss shampoos, wherein the anti-hair loss component parameters of each of the P types of anti-hair loss shampoos are different and the other shampoo configuration components are the same; Determine a test group corresponding to each of the P types of anti-hair loss shampoos to obtain P test groups; each test group includes a plurality of test subjects; each test subject corresponds to a property information; Acquire test data of each test group in the P test groups to obtain P groups of test data, each group of test data includes multiple test data sets, each test data set corresponds to multiple test data of a test object, and each test data includes hair data; Obtaining first attribute information of a target object; Acquire P groups of partial test data corresponding to the first attribute information from the P groups of test data, each group of partial test data includes at least one test data set, each test data set corresponds to a plurality of test data of a test object, and each test data includes hair data; Determine a corresponding anti-hair loss effect evaluation parameter according to each portion of the P groups of partial test data, to obtain P anti-hair loss effect evaluation parameters; Selecting a maximum value from the P anti-hair loss effect evaluation parameters, and obtaining a target anti-hair loss shampoo corresponding to the maximum value from the P types of anti-hair loss shampoos; The target anti-hair loss shampoo is pushed to the target object.

2. The method according to claim 1, characterized in that The method of determining a corresponding anti-hair loss effect evaluation parameter according to each portion of the P groups of partial test data to obtain P anti-hair loss effect evaluation parameters includes: Acquire target partial test data, where the target partial test data is any test data in the P group of partial test data; Acquire the hair density parameter corresponding to the hair data of each test data set in the target part test data, and obtain at least one hair density parameter of each test data set; A target anti-hair loss effect evaluation parameter is determined according to at least one hair density parameter of each test data set.

3. The method according to claim 2, characterized in that The step of determining a target anti-hair loss effect evaluation parameter according to at least one hair density parameter of each test data set comprises: Determine an anti-hair loss effect evaluation parameter corresponding to at least one hair density parameter of each test data set to obtain a plurality of anti-hair loss effect evaluation parameters; The target anti-hair loss effect evaluation parameter is determined according to the multiple anti-hair loss effect evaluation parameters.

4. The method according to claim 3, characterized in that Each hair density parameter corresponds to a test time; the step of determining the anti-hair loss effect evaluation parameter corresponding to at least one hair density parameter of each test data set to obtain a plurality of anti-hair loss effect evaluation parameters includes: Perform fitting according to at least one hair density parameter of a first test data set and a corresponding test time to obtain a fitting straight line; the first test data set is any test data set in each of the test data sets; Obtaining a target slope of the fitted straight line; Determine the anti-hair loss effect evaluation parameter corresponding to the target slope.

5. The method according to claim 3, characterized in that: Each hair density parameter corresponds to a test time; the step of determining the anti-hair loss effect evaluation parameter corresponding to at least one hair density parameter of each test data set to obtain a plurality of anti-hair loss effect evaluation parameters includes: Determine the hair density parameter increments at adjacent test times according to at least one hair density parameter of the first test data set, to obtain at least one hair density parameter increment; the second test data set is any one of the test data sets; determining a mean square error of the at least one hair density parameter increment to obtain a target mean square error; Determine the anti-hair loss effect evaluation parameter corresponding to the target mean square deviation.

6. The method according to any one of claims 3 to 5, characterized in that: The step of determining the target anti-hair loss effect evaluation parameter according to the plurality of anti-hair loss effect evaluation parameters comprises: Acquire second attribute information of the test object of each anti-hair loss effect evaluation parameter corresponding to the plurality of anti-hair loss effect evaluation parameters, to obtain a plurality of second attribute information; Acquire target second attribute information of the target object; Determine a matching value between each second attribute information in the plurality of second attribute information and the target second attribute information to obtain a plurality of matching values; Determine weights corresponding to the multiple matching values ​​to obtain multiple weights; The multiple anti-hair loss effect evaluation parameters are weightedly calculated with the multiple weights to obtain the target anti-hair loss effect evaluation parameters.

7. The method according to any one of claims 1 to 5, characterized in that: The method of pushing the target anti-hair loss shampoo to the target object comprises: Acquiring target physiological state parameters of the target object; Determining target optimization parameters corresponding to the target physiological state parameters; Optimizing the anti-hair loss component parameters corresponding to the target anti-hair loss shampoo according to the target optimization parameters to obtain the target anti-hair loss component parameters; replacing the anti-hair loss component parameters in the target anti-hair loss shampoo according to the target anti-hair loss component parameters to obtain an optimized anti-hair loss shampoo; The optimized anti-hair loss shampoo is pushed to the target object.

8. A shampoo dispensing device for preventing hair loss, characterized in that: The device comprises: an acquisition unit, a determination unit and a push unit, wherein: The acquisition unit is used to acquire P types of anti-hair loss shampoos, wherein the anti-hair loss component parameters of each of the P types of anti-hair loss shampoos are different and the other shampoo configuration components are the same; The determining unit is used to determine a test group corresponding to each of the P types of anti-hair loss shampoos, to obtain P test groups; each test group includes a plurality of test subjects; each test subject corresponds to a property information; The acquisition unit is further used to acquire the test data of each test group in the P test groups to obtain P groups of test data, each group of test data includes multiple test data sets, each test data set corresponds to multiple test data of a test object, and each test data includes hair data; The acquisition unit is further used to acquire first attribute information of the target object; acquire P groups of partial test data corresponding to the first attribute information from the P groups of test data, each group of partial test data includes at least one test data set, each test data set corresponds to multiple test data of a test object, and each test data includes hair data; The determining unit is further used to determine a corresponding anti-hair loss effect evaluation parameter according to each portion of the P groups of partial test data, to obtain P anti-hair loss effect evaluation parameters; The acquisition unit is further used to select a maximum value from the P anti-hair loss effect evaluation parameters, and acquire a target anti-hair loss shampoo corresponding to the maximum value from the P types of anti-hair loss shampoos; The pushing unit is used to push the target anti-hair loss shampoo to the target object.

9. A shampoo preparation device for preventing hair loss, characterized in that: The method comprises a processor and a memory, wherein the memory is used to store one or more programs and is configured to be executed by the processor, wherein the programs include instructions for executing the steps in the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: A computer program for electronic data exchange is stored, wherein the computer program enables a computer to execute the method according to any one of claims 1 to 7.

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