Skincare product formula determination method, system, and device

Abstract

The present application pertains to the technical field of skincare product formula determination and particularly relates to a skincare product formula determination method, system, and device. The skincare product formula determination method comprises: acquiring a user's purchase data and feedback data; analyzing the user's purchase data to obtain skincare preference information, wherein the skincare preference information is used for reflecting the orientation effect and main ingredients of a skincare product that the user needs; analyzing the feedback data to obtain a skin improvement trajectory; and determining, on the basis of the skincare preference information and the skin improvement trajectory, a skincare product formula. This method can identify users' specific preferences and requirements regarding skincare products. The method can timely track dynamic changes in users' skin condition, ensuring that formulas align closely with users' current skin requirements. The method can scientifically match active ingredients to formulas to avoid ineffective ingredients or ingredients that may cause adverse reactions, ensuring that recommended skincare products do not only meet users' personal requirements.

Description

Skincare product formulation determination methods, systems and equipment Technical Field

[0001] This application belongs to the technical field of skin care product formulation determination, and in particular relates to a method, system and equipment for determining skin care product formulation. Background Technology

[0002] With the improvement of people's living standards and consumers' pursuit of beauty, the skincare market has experienced rapid development. In today's market environment where skincare concepts are becoming increasingly popular, consumers' demands for skincare products are no longer limited to basic maintenance functions, but rather they pay more attention to the targeted nature, safety, and effectiveness of the products.

[0003] However, the market is flooded with a wide variety of skincare products, causing consumers considerable confusion in their choices. Furthermore, traditional skincare product manufacturing often relies on extensive market research and general consumer classifications, neglecting the significant differences in individual skin characteristics and the changing skin conditions and needs over time. This "one-size-fits-all" approach fails to meet modern consumers' pursuit of personalized skincare solutions, leading to blind selection and uncertainty in product effectiveness. Summary of the Invention

[0004] This application provides a method, system, and device for determining skincare product formulations, which can solve the problem that traditional skincare product manufacturing cannot meet modern consumers' pursuit of personalized skincare solutions, leading to blind selection of skincare products and uncertainty of their effects.

[0005] In a first aspect, embodiments of this application provide a method for determining a skincare product formulation, including:

[0006] Acquire user consumption data and feedback data; wherein, the user consumption data is used to reflect the time and type of skin care products purchased by users within a preset historical time period, and the feedback data is used to reflect the user's experience with the purchased skin care products, evaluation of their effects, and changes in their skin;

[0007] Based on the analysis of the user consumption data, skincare preference information is obtained; wherein, the skincare preference information is used to reflect the targeted effects and main ingredients of the skincare products needed by the user;

[0008] The feedback data is analyzed to obtain a skin improvement trajectory; wherein, the skin improvement trajectory is used to reflect the changes in the user's skin condition;

[0009] The skincare product formulation is determined based on the skincare preference information and the skin improvement trajectory.

[0010] The technical solutions described in this application embodiment have at least the following technical effects:

[0011] The skincare product formulation determination method provided in this application obtains user consumption data reflecting the time and type of skincare products purchased by users within a preset historical period, as well as feedback data reflecting users' usage experience, effect evaluation, and skin changes of the purchased skincare products. Then, based on the user consumption data, skincare preference information reflecting the targeted effects and main ingredients of the skincare products needed by the user is obtained. Next, based on the feedback data, a skin improvement trajectory reflecting changes in the user's skin condition is obtained. Finally, the skincare product formulation is determined based on the skincare preference information and the skin improvement trajectory. This method, through meticulous analysis of users' consumption habits and feedback information, can capture users' specific preferences and needs for skincare products; by analyzing the skin improvement trajectory, it can promptly grasp the dynamic changes in users' skin conditions, ensuring that the formulation closely matches the user's current skin needs; and by combining users' skincare preference information and skin improvement status, it can scientifically match effective ingredients with the formulation, avoiding ineffective or potentially adverse ingredients, ensuring that the recommended skincare products not only meet the user's personalized needs.

[0012] In one possible implementation of the first aspect, the step of analyzing the user consumption data to obtain skincare preference information includes:

[0013] The user consumption data is analyzed based on a preset analysis period within the preset historical time to obtain multiple skincare preference periods; wherein, the skincare preference period is used to reflect one of the preset analysis periods within the preset historical time.

[0014] Based on the skincare preference cycle, skincare preference information is obtained through analysis.

[0015] In one possible implementation of the first aspect, the step of analyzing the skincare preference cycle to obtain skincare preference information includes:

[0016] Based on the skincare preference cycle, key feature preferences are determined; wherein, the key feature preferences include the key moments when users purchase skincare products and the combination patterns of preferred ingredients;

[0017] Based on the analysis of the key moments and the combination patterns, skincare preference information is obtained.

[0018] In one possible implementation of the first aspect, the step of analyzing the key moments and the combination patterns to obtain skincare preference information includes:

[0019] Based on the analysis of the aforementioned combination rules, a dispersion value is obtained; wherein, the dispersion value is used to reflect the concentration of preferred ingredients and skin care product types;

[0020] The dispersion value is compared with a preset threshold. If the dispersion value is less than or equal to the preset threshold, skincare preference information is determined according to the combination rule.

[0021] In one possible implementation of the first aspect, the step of analyzing the skincare preference information based on the key moments and the combination rules further includes:

[0022] If the dispersion value is greater than the preset threshold, then the key skin care needs are determined by analysis based on the key moments; wherein, the key skin care needs are used to reflect the user's skin care preferences during seasonal changes or special events.

[0023] Determine whether the current moment belongs to the key moment. If the current moment belongs to the key moment, then the key skincare need is determined as skincare preference information.

[0024] If the current moment does not belong to the key moment, the skincare preference information is obtained by analyzing the most recent consumption data in the user's consumption data.

[0025] In one possible implementation of the first aspect, the step of analyzing according to the combination rule to obtain the dispersion value includes:

[0026] Based on the frequency of occurrence of the combination components in each group according to the combination rules, a sequence of combination components is obtained.

[0027] The combined components with frequencies higher than a preset value are selected to obtain the analysis sequence;

[0028] The analysis is performed based on the skincare preference cycle corresponding to the combined ingredients in the analysis sequence to obtain a first dispersion value;

[0029] The combined components with frequencies lower than the preset frequency are statistically analyzed to obtain a discrete sequence;

[0030] The second degree of dispersion value is obtained by analyzing the proportion of the combined components in the combined component sequence in the discrete sequence;

[0031] The dispersion value is obtained based on the first dispersion value and the second dispersion value.

[0032] In one possible implementation of the first aspect, the step of analyzing the feedback data to obtain the skin improvement trajectory includes:

[0033] The feedback data is input into the learning model to obtain the skin improvement trajectory; wherein, the learning model is trained by multiple sets of training data, and each set of training data includes the feedback data and the skin improvement trajectory.

[0034] In one possible implementation of the first aspect, determining the skincare product formulation based on the skincare preference information and the skin improvement trajectory includes:

[0035] Based on the positive change points in skin condition in the skin improvement trajectory, information on highly effective ingredients is obtained; wherein, the positive change points in skin condition are used to reflect the corresponding skin care time and skin care product type for which the user's skin has improved, and the information on highly effective ingredients is used to reflect the ingredients that can have a beneficial effect on the user's skin;

[0036] The current skin condition is determined by analyzing the most recent feedback information in the skin improvement trajectory.

[0037] The skincare product formula is determined based on the information of the highly effective ingredients, the current skin condition, and the skincare preference information.

[0038] The step of determining the skincare product formula based on the high-efficiency ingredient information, the current skin condition, and the skincare preference information includes:

[0039] The information on highly effective ingredients is filtered based on the current skin condition to obtain information on effective ingredients; wherein, the information on effective ingredients reflects the ingredients that can have a beneficial effect on the user's current skin.

[0040] The skincare product formulation is determined based on a combination of the information on the active ingredients and the information on skincare preferences.

[0041] Secondly, embodiments of this application provide a skincare product formulation determination system, including:

[0042] The acquisition module is used to acquire user consumption data and feedback data; wherein, the user consumption data is used to reflect the time and type of skin care products purchased by users within a preset historical time period, and the feedback data is used to reflect the user's experience with the purchased skin care products, evaluation of their effects, and changes in their skin.

[0043] The first analysis module is used to analyze the user consumption data to obtain skincare preference information; wherein, the skincare preference information is used to reflect the targeted effects and main ingredients of the skincare products needed by the user;

[0044] The second analysis module is used to analyze the feedback data to obtain the skin improvement trajectory; wherein, the skin improvement trajectory is used to reflect the changes in the user's skin condition;

[0045] The determination module is used to determine the skincare product formula based on the skincare preference information and the skin improvement trajectory.

[0046] Thirdly, embodiments of this application provide a skincare product formulation determination device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method described in any one of the first aspects above.

[0047] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in any one of the first aspects above.

[0048] Fifthly, embodiments of this application provide a computer program product that, when run on a skincare product formulation determining device, causes the skincare product formulation determining device to perform the skincare product formulation determining method described in any one of the first aspects.

[0049] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1 is a flowchart illustrating the skincare product formulation determination method provided in an embodiment of this application;

[0052] Figure 2 is a schematic diagram of the implementation process of step S200 in the skin care product formulation determination method provided in the embodiments of this application;

[0053] Figure 3 is a schematic diagram of the implementation process of step S220 in the skin care product formulation determination method provided in the embodiments of this application;

[0054] Figure 4 is a schematic diagram of the implementation process of step S222 in the skin care product formulation determination method provided in the embodiments of this application;

[0055] Figure 5 is a schematic diagram of the implementation process of step S2221 in the skin care product formulation determination method provided in the embodiments of this application;

[0056] Figure 6 is a schematic diagram of the implementation process of step S400 in the skin care product formulation determination method provided in the embodiments of this application;

[0057] Figure 7 is a schematic diagram of the implementation process of step S430 in the skin care product formulation determination method provided in the embodiments of this application;

[0058] Figure 8 is a schematic diagram of the skin care product formulation determination system provided in an embodiment of this application;

[0059] Figure 9 is a schematic diagram of the structure of the skin care product formula determination device provided in the embodiment of this application. Detailed Implementation

[0060] To better understand the skin care product formulation determination method provided in the embodiments of this application, the specific implementation process of the skin care product formulation determination method provided in the embodiments of this application will be described by way of example below.

[0061] Figure 1 shows a schematic flowchart of the skin care product formulation determination method provided in the embodiments of this application. The skin care product formulation determination method includes:

[0062] S100, acquire user consumption data and feedback data; among which, user consumption data is used to reflect the time and type of skin care products purchased by users within a preset historical period, and feedback data is used to reflect users' feelings about using the purchased skin care products, their evaluation of the effects, and changes in their skin.

[0063] It is understandable that data can be obtained by collecting user consumption and feedback data from major e-commerce platforms; it can also be obtained through questionnaires and satisfaction surveys, etc., but it is not limited to these methods.

[0064] S200 analyzes user consumption data to obtain skincare preference information; this information reflects the targeted effects and main ingredients of the skincare products the user desires.

[0065] It's understandable that by aggregating the types of skincare products from user consumption data, and then aggregating all the ingredients of all the aggregated skincare products to obtain ingredient summary data, ingredients that have exceeded a preset frequency can be extracted and identified as main ingredients. Alternatively, ingredients that have exceeded a preset frequency within the main ingredient group can be selected and identified as main ingredients, and so on, but not limited to these methods. The targeted effects of each skincare product can be determined by its main ingredients. For example, if the main ingredient is hyaluronic acid, the targeted effect might be moisturizing; if the main ingredient is salicylic acid, the targeted effect might be anti-aging, and so on.

[0066] In one possible implementation, referring to Figure 2, in step S200, user consumption data is analyzed to obtain skincare preference information, including:

[0067] S210, based on user consumption data, analyzes it according to a preset analysis period within a preset historical time to obtain multiple skincare preference periods; wherein, the skincare preference period is used to reflect one of the preset analysis periods within the preset historical time.

[0068] It's understandable that the preset historical time and preset analysis cycle are both preset values. These can be manually entered, obtained from a skincare product database, etc., but are not limited to these methods. A skincare product database refers to a database containing preset historical times and preset analysis cycles. This data can be obtained through laboratory experiments, on-site measurements and monitoring, and past experience. After acquisition, the collected data is organized, classified, and archived, useful information and patterns are extracted, and the relevant data is then saved into the database to form a skincare product database. For example, assuming a preset historical time of 3 years and a preset analysis cycle of 6 months, then every 6 months within these three years constitutes a skincare preference cycle, and so on.

[0069] S220 analyzes skincare preference cycles to obtain skincare preference information.

[0070] This setup allows for analysis of users' preferences for specific effects or ingredients within each cycle. For example, if a user frequently purchases moisturizing products containing hyaluronic acid during a certain cycle, it indicates a strong need for moisturizing during that cycle. At the same time, it identifies the ingredient combinations that users prefer in different cycles, thus understanding their overall preferences for skincare formulas.

[0071] In one possible implementation, referring to Figure 3, in step S220, skincare preference information is obtained by analyzing the skincare preference cycle, including:

[0072] S221, Analyze the skincare preference cycle to determine key feature preferences; among which, key feature preferences include the key moments when users purchase skincare products and the combination patterns of preferred ingredients.

[0073] It's understandable that "critical moments" refer to the specific times when users are inclined to purchase skincare products within a skincare preference cycle. These could be related to holidays, seasonal changes, promotional activities, or personal habits (such as payday). "Combination patterns" refer to the combinations of skincare ingredients preferred by users in different cycles. For example, users might prefer to buy products containing both hyaluronic acid and vitamin E during dry seasons to enhance moisturizing and antioxidant effects. Time series analysis can be used to analyze each skincare preference cycle, identifying periods of high and low purchase activity. These high-frequency periods are often associated with specific user needs or external factors (such as holidays and seasonal changes), and the timeframes within these high-frequency periods are defined as critical moments. By statistically analyzing the ingredients in each skincare preference cycle and applying association rule algorithms (such as the Apriori algorithm), strong correlations between ingredients can be identified to reveal the combination patterns of preferred ingredients by users.

[0074] S222 analyzes key moments and combination patterns to obtain skincare preference information.

[0075] This setup, through key moments and combination patterns, can reflect users' purchasing behavior and ingredient preferences at different times. The resulting skincare preference information can accurately identify users' needs and preferences for skincare products, thereby satisfying their psychological and physiological needs.

[0076] In one possible implementation, referring to Figure 4, in step S222, analysis is performed based on key moments and combination patterns to obtain skincare preference information, including:

[0077] S2221, based on the combination rules, the dispersion value is obtained; among which, the dispersion value is used to reflect the concentration of preferred ingredients and skin care product types.

[0078] As we can understand it, the dispersion value is a quantitative indicator that helps us understand how users distribute their preferences when choosing ingredients and types of skincare products. Specifically, if a user's preferences are highly concentrated on a few ingredients or product types, the dispersion value is low, indicating that the user's choices are relatively fixed and show a clear preference tendency. Conversely, if a user's preferences are widely dispersed across multiple ingredients and product types, the dispersion value is high, meaning that the user enjoys trying different kinds of products and may not have a particularly fixed preference pattern. For example, the dispersion value ranges from 1 to 10, where 1 indicates that the user's preferences are very concentrated, possibly focusing almost exclusively on one or a very few ingredients and skincare product types, while 10 indicates that the user's preferences are extremely dispersed, involving various ingredients and different types of skincare products without showing a particularly obvious preference concentration trend, and so on.

[0079] In one possible implementation, referring to Figure 5, in step S2221, the discreteness value is obtained by analyzing the combination rules, including:

[0080] S22211, based on the frequency of occurrence of each group of combination components in the combination rules, the combination component sequence is obtained.

[0081] Understandably, the first step is to organize all collected user preference data and count the frequency of each ingredient combination (referring to the combination of specific ingredients or skincare product types). Then, these ingredients are sorted from highest to lowest frequency to form an ingredient combination sequence.

[0082] S22212, filter out the combination components with frequencies higher than the preset frequency to obtain the analysis sequence.

[0083] It is understandable that a preset frequency is a pre-defined value. It can be set manually, obtained from a skincare product database, etc., but is not limited to these methods. The combination ingredient sequence is A, B, C, D, E, F, G, with frequencies of 10, 8, 5, 4, 3, 2, 1 respectively. When the preset frequency is 5, the analysis sequence is A, B, C, and so on.

[0084] S22213, based on the skincare preference cycle corresponding to the combined ingredients in the analysis sequence, the first dispersion value is obtained.

[0085] It's understandable that analyzing the timing of purchases of each ingredient combination in a sequence can reveal a user's dependence on those ingredients. For example, given the performance of sequences A, B, and C across different skincare preference cycles, the lower the first degree of dispersion value, the lower the dispersion value. If A maintains a stable demand across all skincare preference cycles, B has demand in one or a few fixed skincare preference cycles, and C has demand in several unrelated skincare preference cycles, the first degree of dispersion value is relatively high. If A, B, and C all have demand in several unrelated skincare preference cycles, the first degree of dispersion value is even higher, and so on.

[0086] S22214, statistically analyze the combination components with frequencies lower than the preset frequency to obtain a discrete sequence.

[0087] It can be understood that the combination component sequence is A, B, C, D, E, F, G, and the frequencies of occurrence are 10, 8, 5, 4, 3, 2, 1 respectively. When the preset frequency is 5, the discrete sequence is D, E, F, G, and so on.

[0088] S22215, based on the proportion of the combined components in the discrete sequence to the combined components in the combined component sequence, the second dispersion value is obtained.

[0089] It is understandable that, assuming the combined component sequence is A, B, C, D, E, F, G, with frequencies of occurrence of 10, 8, 5, 4, 3, 2, 1 respectively, and a preset frequency of 5, then the discrete sequence is D, E, F, G, with a proportion of 30% [(4+3+2+1)÷(10+8+5+4+3+2+1)], and so on. The larger the proportion, the larger the second degree of dispersion value.

[0090] S22216, the dispersion value is obtained based on the first dispersion value and the second dispersion value.

[0091] It can be understood that the dispersion value = (first dispersion value + second dispersion value) ÷ 2. Assuming the first dispersion value is 2 and the second dispersion value is 6, then the dispersion value is 4 [(2+6) ÷ 2], and so on.

[0092] This setup allows us to understand users' mainstream preferences and dependence on skincare products by analyzing the performance of high-frequency combination components (i.e., the analysis sequence) and low-frequency combination components (discrete sequence) across two dimensions during the skincare preference cycle. This provides quantitative data support for determining skincare product formulations.

[0093] S2222a: The dispersion value is compared with a preset threshold. If the dispersion value is less than or equal to the preset threshold, the skin care preference information is determined according to the combination rule.

[0094] It's understandable that a preset threshold is a pre-defined value. It can be set manually, obtained from a skincare product database, or other methods, but it's not limited to these. When the dispersion value is less than or equal to the preset threshold, it indicates that user preferences are relatively fixed and concentrated. At this point, based on the previously analyzed combination patterns (i.e., combinations of frequently selected main ingredients and product types), skincare preference information can be directly determined for subsequent personalized recommendations or product design.

[0095] In one possible implementation, referring to Figure 4, step S222 involves analyzing key moments and combination patterns to obtain skincare preference information, and also includes:

[0096] S2222b, if the dispersion value is greater than the preset threshold, then the key skin care needs are determined by analyzing the key moments; whereby the key skin care needs are used to reflect the user's skin care preferences during seasonal changes or special events.

[0097] It is understandable that when the dispersion value is greater than the preset threshold, it indicates that users' skin care needs are more diversified and they do not have a particular preference for certain ingredients or types of skin care products. At this time, it is necessary to turn to analyzing key moments, that is, to find the special skin care needs that users show during specific periods. This helps to identify seasonal preferences or skin care solutions for specific environments.

[0098] S2223a, determine whether the current moment is a critical moment. If the current moment is a critical moment, then identify the key skincare needs as skincare preference information.

[0099] It's understandable that "current moment" refers to the moment when the user is using the skincare product. This can be estimated from the order and production information provided by the user. If the current moment is a critical moment, then the specific skincare needs related to that moment (such as enhanced moisturizing, sun protection, or anti-allergy) will be directly used as the current skincare preference information to respond to the user's immediate needs.

[0100] S2223b: If the current moment is not a critical moment, then analyze the most recent consumption data in the user's consumption data to obtain skincare preference information.

[0101] Understandably, if a user's skincare needs are diverse, and the current moment isn't a critical one, the system will instead refer to the user's most recent purchase history, analyzing their preferences for ingredients and product types to guide their recent skincare choices. This ensures that even under normal circumstances, skincare advice can be provided that aligns with the user's current situation.

[0102] The S300 analyzes feedback data to obtain a skin improvement trajectory; this trajectory reflects changes in the user's skin condition.

[0103] Understandably, the first step is to extract key information from the feedback data. This key information can include the user's description of their skin condition and their immediate feelings after using skincare products, such as "dry," "oily," "sensitive," and "reduced acne," which directly reflect changes in skin condition. Feelings like "fast absorption," "no irritation," and "obvious moisturizing effect" indirectly reflect the product's impact on the skin. Next, the specific time points in the user's feedback where significant changes in skin condition occurred, as well as the duration of the effect, are identified. Then, this information is arranged chronologically to form a time series, tracking the continuous changes in the user's skin condition over time to obtain the skin improvement trajectory. This process may involve quantification, converting qualitative descriptions like "dry" and "oily" into a 1-5 scale, where 1 represents poor skin condition, 3 represents average skin condition, and 5 represents excellent skin condition. For example, a user might comment, "My skin feels much more moisturized recently, the previous dryness has greatly improved, and the oiliness has also decreased. It must be the new moisturizing lotion that's working; it feels very comfortable to use, there's no irritation, and the moisturizing effect is very obvious." Based on this feedback, key information was extracted. The user mentioned that their skin was "much more moisturized," "the previous dryness has greatly improved," and "the oiliness has also decreased." This indicates that both the dryness and oiliness of the skin have decreased, moving towards a healthier state. The user's feedback that "it feels very comfortable to use, with no irritation and a noticeable moisturizing effect" indicates that the product is highly comfortable and has good moisturizing properties, positively impacting the skin. Assuming the user's skin dryness was previously rated 2 (poor), it has now improved to 4 (good), and the oiliness has decreased from a possible 3 (moderate) to 2 (less oily). Since the user explicitly stated that the comfort and moisturizing effects were "very noticeable," they can be rated 5 (excellent). The specific date of the user's feedback or the start date of using the new product was recorded as the starting point for improvement. If subsequent feedback mentions that this improvement continues, the duration is recorded. This period is marked on a timeline, increasing the dryness rating from 2 to 4 and the oiliness rating from 3 to 2, while also marking the point where the moisturizing effect and comfort reached the highest level of 5. This creates a time-series trajectory of skin improvement, visually demonstrating the positive changes in skin condition.

[0104] In one possible implementation, in step S300, the skin improvement trajectory is obtained by analyzing the feedback data, including:

[0105] S310, The feedback data is input into the learning model to obtain the skin improvement trajectory; wherein, the learning model is trained by multiple sets of training data, and each set of training data includes feedback data and skin improvement trajectory.

[0106] Understandably, the first step is to clean and preprocess the collected feedback data to ensure data quality. This includes removing invalid or erroneous feedback, filling in missing values, and standardizing text descriptions to help the model better understand and learn from the data. Next, useful features are labeled from the feedback data. These features may include user-described skin conditions (e.g., dryness, oiliness), feelings after using the product (e.g., fast absorption, no irritation), product usage frequency, and duration. Then, a training set is constructed using historical data, with each training data point containing user feedback information and corresponding skin improvement trajectory labels. The skin improvement trajectory labels may be quantitative indicators of skin condition (e.g., changes in skin hydration, sebum secretion levels, sensitivity scores, etc.) over time, or direct improvement level assessments. The trained and validated learning model is then applied to new feedback data. After inputting user feedback information, the model outputs a predicted skin improvement trajectory.

[0107] S400 determines skincare product formulations based on skincare preference information and skin improvement trajectory.

[0108] Skincare preference information represents a user's active intentions and preferences when choosing skincare products, including their preferred skincare effects (such as moisturizing, anti-aging, and acne treatment), favorite ingredients (such as hyaluronic acid and vitamin C), preferred product forms (such as lotions and serums), and preferences for non-efficacy factors such as brand, texture, and fragrance. Skin improvement trajectories, on the other hand, reveal the actual changes in a user's skin condition by analyzing user feedback data, including when and what skincare measures led to positive improvements, and which ingredients or products had significant positive effects on the user's skin. This provides an objective basis for understanding the characteristics and responses of a user's skin. Based on the user's current skin improvement needs (indicated by the skin improvement trajectory) and their preferred skincare effects and ingredients (from skincare preference information), a skincare formula can be customized to meet both current skin improvement needs and the user's personal preferences. For example, if the skin improvement trajectory shows that the user's skin barrier was significantly strengthened after using a moisturizing product containing ceramides, and the user's preferences emphasize a preference for natural ingredients, then the formula might choose a moisturizing product containing ceramides and emphasizing naturally derived ingredients. As users' skin conditions change and their skincare preferences evolve, skincare product formulas will be adjusted accordingly to ensure they continue to meet user needs. For example, if skin improvement trajectories show that seasonal changes exacerbate dryness, even if moisturizing is not a primary consideration for users, more potent moisturizing ingredients will be added to the formula to address their current skin condition.

[0109] In one possible implementation, referring to Figure 6, in step S400, the skincare product formulation is determined based on skincare preference information and skin improvement trajectory, including:

[0110] S410 analyzes the positive changes in skin condition along the skin improvement trajectory to obtain information on highly effective ingredients. The positive changes in skin condition reflect the corresponding skincare time and type of skincare products that improved the user's skin, while the information on highly effective ingredients reflects the ingredients that have a beneficial effect on the user's skin.

[0111] As we can understand it, a positive change point in skin condition refers to the point in time when the score on the skin improvement trajectory rises from low to high. This point in time includes the duration and type of skincare products used by the user. By analyzing the type of skincare product, we can identify highly effective ingredients that play a key role in improving the user's skin. For example, if user feedback shows a significant reduction in skin brightness and dark spots after using a serum containing Vitamin C, then Vitamin C is identified as a highly effective ingredient. This process helps identify ingredients that effectively promote skin health, laying the foundation for subsequent personalized formulation design.

[0112] S420 analyzes the most recent feedback information in the skin improvement trajectory to determine the current skin condition.

[0113] Understandably, recent feedback best reflects a user's current skin condition, including any potential new problems or trends of continued improvement. This step ensures that recommended skincare formulations match the user's current needs, avoiding the risk of making decisions based on outdated information. For example, the most recent feedback was: "My skin became a bit dry recently due to the changing seasons, but after using this brand's moisturizer, the dryness was significantly relieved, and my skin looks fuller and more radiant, although my T-zone is still a little oily." Based on this feedback, the current skin condition can be summarized as: overall skin texture is improving, and the main problem has shifted from dryness to mild dryness with slight oiliness in the T-zone. Therefore, when determining skincare formulations, the focus is on products that combine moisturizing and regulating the oil balance in the T-zone, while maintaining or enhancing skin radiance, ensuring that the recommended skincare regimen closely matches the user's current needs and avoiding over- or under-care.

[0114] S430 determines skincare product formulations based on information on high-efficiency ingredients, current skin condition, and skincare preferences.

[0115] Understandably, information on high-efficiency ingredients provides the foundation for improving skin condition, while the current skin condition ensures the formulation's targeting. Skincare preference information encompasses the user's personal preferences, such as those for product texture, fragrance, brand, or specific ingredients. For example, if the high-efficiency ingredients are Vitamin C and hyaluronic acid, the current skin condition requires deep hydration and brightening, and the user prefers natural and organic products, then the formulation will include these high-efficiency ingredients, selecting naturally derived raw materials where possible, while ensuring the product's texture and feel match the user's preferences. Through such comprehensive consideration, the resulting skincare formulation is both effective and considerate, making it more likely to achieve user satisfaction and long-term use.

[0116] In one possible implementation, referring to Figure 7, in step S430, the skincare product formulation is determined based on the information of highly effective ingredients, current skin condition, and skincare preferences, including:

[0117] S431, based on the current skin condition, the information on highly effective ingredients is filtered to obtain the information on effective ingredients; among which, the information on effective ingredients is used to reflect the ingredients that can have a beneficial effect on the user's current skin.

[0118] This process involves analyzing a user's current skin condition to identify the most pressing skin problems and characteristics that need to be addressed. For example, if the user's skin is currently dry and slightly sensitive, then moisturizing and soothing ingredients should be prioritized. Next, the most suitable ingredients for the current skin condition are selected from the previously identified high-efficiency ingredient information. This means that not all highly effective ingredients are suitable for the current situation; rather, those that directly target the current skin problems (such as ceramides and hyaluronic acid for dryness, and chamomile extract for sensitivity) should be chosen. Through this step, the resulting "effective ingredient information" is tailored to the user's current skin condition, ensuring the targeted and effective use of the ingredients.

[0119] S432 determines skincare product formulations based on a combination of information on active ingredients and skincare preferences.

[0120] It's understandable that skincare preference information includes users' preferences for product texture, scent, brand, and ingredient origin (such as natural or organic). For example, if a user prefers natural ingredients and dislikes an oily feel, the formula design will prioritize including effective ingredients extracted from plants and choosing a refreshing gel or lotion texture. This stage requires balancing effectiveness with personalized needs, ensuring the formula is both scientifically sound and efficient, while also meeting the user's personal preferences and usage habits, thus improving the user experience and product acceptance. Through such comprehensive consideration, the customized skincare formula not only solves the user's skin problems but also aligns with their personal skincare philosophy and lifestyle, making it easier to maintain long-term use and achieve optimal skincare results.

[0121] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0122] Corresponding to the skincare product formulation determination method described in the above embodiments, this application also provides a skincare product formulation determination system. Each module of this system can implement each step of the skincare product formulation determination method. Figure 8 shows a structural block diagram of the skincare product formulation determination system provided in this application embodiment. For ease of explanation, only the parts relevant to this application embodiment are shown.

[0123] Referring to Figure 8, the skincare product formulation determination system includes:

[0124] The acquisition module is used to acquire user consumption data and feedback data. The user consumption data reflects the time and type of skincare products purchased by users within a preset historical period, while the feedback data reflects users' feelings about using the purchased skincare products, their evaluation of the effects, and changes in their skin.

[0125] The first analysis module is used to analyze user consumption data to obtain skincare preference information; among which, skincare preference information is used to reflect the targeted effects and main ingredients of the skincare products needed by the user.

[0126] The second analysis module is used to analyze the feedback data to obtain the skin improvement trajectory; the skin improvement trajectory is used to reflect the changes in the user's skin condition.

[0127] The determination module is used to determine skincare product formulations based on skincare preference information and skin improvement trajectory.

[0128] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0129] Those skilled in the art will understand that, for the sake of convenience and brevity, the above-described module division is merely an example. In practical applications, the above functions can be assigned to different modules as needed, that is, the internal structure of the system can be divided into different modules to complete all or part of the functions described above. The modules in the embodiments can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0130] This application also provides a skincare product formulation determination device. Figure 9 is a schematic diagram of the structure of a skincare product formulation determination device 6 provided in an embodiment of this application. As shown in Figure 9, the skincare product formulation determination device 6 of this embodiment includes: at least one processor 60 (only one is shown in Figure 9), at least one memory 61 (only one is shown in Figure 9), and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60. When the processor 60 executes the computer program 62, it causes the skincare product formulation determination device 6 to implement the steps in any of the above-described skincare product formulation determination method embodiments, or causes the skincare product formulation determination device 6 to implement the functions of each module in the above-described system embodiments.

[0131] For example, the computer program 62 may be divided into one or more modules / units, which are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program 62 in the skincare product formulation determination device 6.

[0132] The skincare product formulation determination device 6 can be a desktop computer, laptop, handheld computer, or cloud server, etc. This skincare product formulation determination device may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that Figure 9 is merely an example of the skincare product formulation determination device 6 and does not constitute a limitation on it. It may include more or fewer components than shown, or combine certain components, or use different components; for example, it may also include input / output devices, network access devices, buses, etc.

[0133] The processor 60 can be a Central Processing Unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0134] In some embodiments, the memory 61 may be an internal storage unit of the skincare product formulation determining device 6, such as a hard drive or memory of the skincare product formulation determining device 6. In other embodiments, the memory 61 may be an external storage device of the skincare product formulation determining device 6, such as a plug-in hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the skincare product formulation determining device 6. Furthermore, the memory 61 may include both internal storage units and external storage devices of the skincare product formulation determining device 6. The memory 61 is used to store operating systems, applications, bootloaders, data, and other programs, such as the program code of computer programs. The memory 61 can also be used to temporarily store data that has been output or will be output.

[0135] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0136] This application provides a computer program product that, when run on a skincare product formulation determination device 6, enables the skincare product formulation determination device 6 to perform the steps described in any of the above method embodiments.

[0137] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to a skincare product formulation determination device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0138] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0139] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for determining a skincare product formula, characterized in that, include: Acquire user consumption data and feedback data; wherein, the user consumption data is used to reflect the time and type of skin care products purchased by users within a preset historical time period, and the feedback data is used to reflect the user's experience with the purchased skin care products, evaluation of their effects, and changes in their skin; Based on the analysis of the user consumption data, skincare preference information is obtained; wherein, the skincare preference information is used to reflect the targeted effects and main ingredients of the skincare products needed by the user; The feedback data is analyzed to obtain a skin improvement trajectory; wherein, the skin improvement trajectory is used to reflect the changes in the user's skin condition; The skincare product formulation is determined based on the skincare preference information and the skin improvement trajectory.

2. The method for determining a skincare product formulation as described in claim 1, characterized in that, The step of analyzing the user consumption data to obtain skincare preference information includes: The user consumption data is analyzed based on a preset analysis period within the preset historical time to obtain multiple skincare preference periods; wherein, the skincare preference period is used to reflect one of the preset analysis periods within the preset historical time. Based on the skincare preference cycle, skincare preference information is obtained through analysis.

3. The method for determining a skincare product formulation as described in claim 2, characterized in that, The analysis based on the skincare preference cycle to obtain skincare preference information includes: Based on the skincare preference cycle, key feature preferences are determined; wherein, the key feature preferences include the key moments when users purchase skincare products and the combination patterns of preferred ingredients; Based on the analysis of the key moments and the combination patterns, skincare preference information is obtained.

4. The method for determining a skincare product formulation as described in claim 3, characterized in that, The analysis based on the key moments and the combination patterns yields skincare preference information, including: Based on the analysis of the aforementioned combination rules, a dispersion value is obtained; wherein, the dispersion value is used to reflect the concentration of preferred ingredients and skin care product types; The dispersion value is compared with a preset threshold. If the dispersion value is less than or equal to the preset threshold, skincare preference information is determined according to the combination rule.

5. The method for determining a skincare product formulation as described in claim 4, characterized in that, The step of analyzing the key moments and the combination patterns to obtain skincare preference information also includes: If the dispersion value is greater than the preset threshold, then the key skin care needs are determined by analysis based on the key moments; wherein, the key skin care needs are used to reflect the user's skin care preferences during seasonal changes or special events. Determine whether the current moment belongs to the key moment. If the current moment belongs to the key moment, then the key skincare need is determined as skincare preference information. If the current moment does not belong to the key moment, the skincare preference information is obtained by analyzing the most recent consumption data in the user's consumption data.

6. The method for determining a skincare product formulation as described in claim 4, characterized in that, The analysis based on the combined rules to obtain the dispersion value includes: Based on the frequency of occurrence of the combination components in each group according to the combination rules, a sequence of combination components is obtained. The combined components with frequencies higher than a preset value are selected to obtain the analysis sequence; The analysis is performed based on the skincare preference cycle corresponding to the combined ingredients in the analysis sequence to obtain a first dispersion value; The combined components with frequencies lower than the preset frequency are statistically analyzed to obtain a discrete sequence; The second degree of dispersion value is obtained by analyzing the proportion of the combined components in the combined component sequence in the discrete sequence; The dispersion value is obtained based on the first dispersion value and the second dispersion value.

7. The method for determining a skincare product formulation as described in claim 1, characterized in that, The step of analyzing the feedback data to obtain the skin improvement trajectory includes: The feedback data is input into the learning model to obtain the skin improvement trajectory; wherein, the learning model is trained by multiple sets of training data, and each set of training data includes the feedback data and the skin improvement trajectory.

8. The method for determining a skincare product formulation as described in claim 1, characterized in that, The step of determining the skincare product formula based on the skincare preference information and the skin improvement trajectory includes: Based on the positive change points in skin condition in the skin improvement trajectory, information on highly effective ingredients is obtained; wherein, the positive change points in skin condition are used to reflect the corresponding skin care time and skin care product type for which the user's skin has improved, and the information on highly effective ingredients is used to reflect the ingredients that can have a beneficial effect on the user's skin; The current skin condition is determined by analyzing the most recent feedback information in the skin improvement trajectory. The skincare product formula is determined based on the information of the highly effective ingredients, the current skin condition, and the skincare preference information. The step of determining the skincare product formula based on the high-efficiency ingredient information, the current skin condition, and the skincare preference information includes: The information on highly effective ingredients is filtered based on the current skin condition to obtain information on effective ingredients; wherein, the information on effective ingredients reflects the ingredients that can have a beneficial effect on the user's current skin. The skincare product formulation is determined based on a combination of the information on the active ingredients and the information on skincare preferences.

9. A skincare product formulation determination system, characterized in that, include: The acquisition module is used to acquire user consumption data and feedback data; wherein, the user consumption data is used to reflect the time and type of skin care products purchased by users within a preset historical time period, and the feedback data is used to reflect the user's experience with the purchased skin care products, evaluation of their effects, and changes in their skin. The first analysis module is used to analyze the user consumption data to obtain skincare preference information; wherein, the skincare preference information is used to reflect the targeted effects and main ingredients of the skincare products needed by the user; The second analysis module is used to analyze the feedback data to obtain the skin improvement trajectory; wherein, the skin improvement trajectory is used to reflect the changes in the user's skin condition; The determination module is used to determine the skincare product formula based on the skincare preference information and the skin improvement trajectory.

10. A skincare product formulation determination device, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method as claimed in any one of claims 1 to 8.

Images