CN117994009B - Digital product removes and fills a supplement system of selecting - Google Patents
Digital product removes and fills a supplement system of selecting Download PDFInfo
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- CN117994009B CN117994009B CN202410404581.9A CN202410404581A CN117994009B CN 117994009 B CN117994009 B CN 117994009B CN 202410404581 A CN202410404581 A CN 202410404581A CN 117994009 B CN117994009 B CN 117994009B
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- 230000005856 abnormality Effects 0.000 claims description 9
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Abstract
The invention relates to the technical field of data processing, in particular to a mobile recharging and selecting system for digital products, which comprises the following components: the data acquisition module is used for acquiring the consumption amount of each user for purchasing a plurality of weeks of each commodity and acquiring a week consumption amount sequence; the digital product analysis module is used for obtaining the bearing capacity of each user on the price of each commodity according to the distribution of the consumption of each commodity of each user; the digital product scoring module is used for obtaining the scoring weight of each user for simultaneously purchasing any two commodities according to the difference of the bearing capacity of each user on any two commodity prices on the consumption rule, and scoring each commodity by each user; and the intelligent recommending module is used for recommending the commodity. The invention optimizes the initial weight parameters and improves the accuracy of mobile recharging recommendation of the digital product.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a mobile recharging and selecting system for digital products.
Background
The mobile recharging of the digital product refers to a way of recharging by using a mobile phone, a tablet computer or other digital equipment through a mobile network or a wireless network, and comprises recharging of digital products such as mobile phone fees, flow, online payment and the like. With the popularization of smart phones and other digital products, the demands of people for a convenient, intelligent and rapid recharging mode are increasing. In order to make the mobile recharging of the digital product more flexible, the mobile recharging and selecting system of the digital product can realize intelligent recommendation through the daily recharging consumption record of the user.
In the conventional intelligent recommendation, the intelligent recommendation of the digital product can be realized through a weighted Slope One algorithm; however, when intelligent recommendation of the digital product is performed through the weighted Slope One algorithm, because different users have different consumption levels and consumption habits, if only the number of people who evaluate together is used as the weight in the weighted Slope One algorithm, deviation exists, so that deviation occurs in the result of predicting and scoring of the Slope One algorithm, and the accuracy of mobile recharging recommendation of the digital product is reduced.
Disclosure of Invention
The invention provides a mobile recharging and selecting system for digital products, which aims to solve the existing problems.
The invention relates to a digital product mobile recharging and selecting line which adopts the following technical scheme:
one embodiment of the invention provides a digital product mobile recharging and selecting system, which comprises the following modules:
The data acquisition module is used for acquiring the consumption amount of each user for purchasing a plurality of weeks of each commodity to form a weekly commodity consumption sequence, and acquiring the weekly consumption amount sequence of each user according to the weekly commodity consumption sequences of all commodities of each user;
The digital product analysis module is used for obtaining the bearing capacity of each user on the price of each commodity according to the difference of the consumption of each commodity on the adjacent weeks and the fluctuation of the consumption of each commodity on all weeks, obtaining a week consumption curve according to the week consumption sequence of each user, obtaining all extreme points of the week consumption curve, and correcting the bearing capacity of each user on the price of each commodity according to the gradient change between the adjacent extreme points in the week consumption curve of each user to obtain the bearing capacity of each user on the price of each commodity on the consumption rule;
The digital product scoring module is used for correcting the initial weight parameters according to the difference of the bearing capacity of each user on the price of any two commodities to obtain the scoring weight of each user for simultaneously purchasing any two commodities, and obtaining the scoring of each user for each commodity according to the scoring weight of each user for simultaneously purchasing any two commodities;
And the intelligent recommendation module is used for recommending the commodity according to the score of each commodity by each user.
Further, the obtaining the bearing capacity of each user to the price of each commodity according to the difference of the consumption amount of each commodity on the adjacent weeks and the fluctuation of the consumption amount of each commodity on all weeks comprises the following steps:
Calculating the product of the first abnormality factor of each commodity purchased by each user and the second abnormality factor of each commodity purchased by each user, and recording the result of the product as a first characteristic Will beThe bearing capacity of each user to each commodity price is recorded.
Further, the first anomaly factor for each commodity purchased by each user includes:
The calculation formula of the first anomaly factor for each user to purchase each commodity is as follows:
In the method, in the process of the invention, Represent the firstIndividual user pair numberThe individual commodity is at the firstThe amount of consumption per week is calculated,Represent the firstIndividual user pair numberThe average of the individual commodity's consumption over all weeks,Representing the total number of weeks each user consumed for each commodity,As a sign of the absolute value of the sign,Represent the firstIndividual user purchases the firstA first anomaly factor for the individual good.
Further, the second anomaly factor for each commodity purchased by each user includes:
The calculation formula of the second anomaly factor for each user to purchase each commodity is as follows:
In the method, in the process of the invention, Represent the firstIndividual user pair numberThe individual commodity is at the firstThe amount of consumption per week is calculated,Represent the firstIndividual user pair numberThe individual commodity is at the firstThe amount of consumption per week is calculated,Representing the total number of weeks each user consumed for each commodity,As a sign of the absolute value of the sign,Represent the firstIndividual user purchases the firstAnd a second anomaly factor for the individual good.
Further, the obtaining a weekly consumption curve according to the weekly consumption sequence of each user includes:
Establishing a reference coordinate system by taking a week serial number of a time sequence as a horizontal axis and taking a consumption sum of each week as a vertical axis; mapping data in the week consumption sequence of each user in a reference coordinate system, performing curve fitting on the week consumption sequence of each user by a least square method, and recording the fitted curve as a week consumption curve.
Further, according to the gradient change between adjacent extreme points in the weekly consumption curve of each user, correcting the bearing capacity of each user on each commodity price, and obtaining the bearing capacity of each user on each commodity price on the consumption rule, including:
the calculation formula of the bearing capacity of each commodity price of each user on the consumption rule is as follows:
In the method, in the process of the invention, Represent the firstIndividual user pair numberThe bearing capacity of the price of the individual goods,Represent the firstWeek consumption curve of individual userThe value of the horizontal axis corresponding to each extreme point,Represent the firstWeek consumption curve of individual userThe value of the horizontal axis corresponding to each extreme point,Represent the firstWeek consumption curve of individual userThe value of the vertical axis corresponding to each extreme point,Represent the firstWeek consumption curve of individual userThe value of the vertical axis corresponding to each extreme point,Representing the total number of all extreme points in the weekly consumption profile for each user,Represent the firstThe individual users are related to the first on the consumption ruleThe bearing capacity of the price of the individual goods,A linear normalization function is represented and,Is an absolute value sign.
Further, the correcting the initial weight parameter according to the difference of the bearing capacity of each user to any two commodity prices in the consumption rule to obtain the scoring weight of each user for simultaneously purchasing any two commodities comprises the following steps:
the calculation formula of the scoring weight of each user purchasing any two commodities simultaneously is as follows:
In the method, in the process of the invention, Represent the firstThe individual users are related to the first on the consumption ruleThe bearing capacity of the price of the individual goods,Represent the firstThe individual users are related to the first on the consumption ruleThe bearing capacity of the price of the individual goods,Represent the firstThe individual users purchase the firstPersonal commodity and the firstThe scoring weight of the individual items of merchandise,As a sign of the absolute value of the sign,Represents an exponential function with a base of a natural constant,Representing preset initial weight parameters.
Further, the step of obtaining the score of each user for each commodity according to the scoring weight of each user for simultaneously purchasing any two commodities comprises the following steps:
And according to the scoring weight of each user for purchasing any two commodities at the same time, the scoring of each user on each commodity is obtained through a weighted Slope One algorithm.
Further, the recommending the commodity according to the score of each commodity by each user comprises the following steps:
And sequencing all the commodities from large to small according to the scoring of each commodity by each user to obtain a commodity sequence of each user, and recommending the commodities to the user in sequence according to the sequence in the commodity sequence of each user.
Further, the collecting the consumption amount of each user for purchasing a plurality of weeks of each commodity to form a weekly commodity consumption sequence, and obtaining the weekly consumption amount sequence of each user according to the weekly commodity consumption sequence of all commodities of each user, including:
Collecting consumption amount of a plurality of continuous weeks for each user to purchase each commodity, and forming a weekly commodity consumption sequence according to the time sequence;
and adding the weekly commodity consumption sequences of all commodities of each user according to the corresponding weeks to obtain the weekly consumption value sequence of each user.
The technical scheme of the invention has the beneficial effects that: according to the invention, the bearing capacity of each user on the price of each commodity is obtained according to the difference of the consumption amount of each commodity on the adjacent weeks and the fluctuation of the consumption amount of each commodity on all weeks, so that the influence of consumption difference in different time periods is eliminated; according to gradient change between adjacent extreme points in the week consumption curve of each user, the bearing capacity of each user on the price of each commodity on the consumption rule is obtained, and the influence of consumption habit is eliminated; correcting the initial weight parameters according to the difference of the bearing capacity of each user on the price of any two commodities to obtain the scoring weight of each user for simultaneously purchasing any two commodities, obtaining the scoring of each user for each commodity according to the scoring weight of each user for simultaneously purchasing any two commodities, and finally recommending the commodities, so that the initial weight parameters are optimized, and the accuracy of mobile recharging recommendation of digital products is improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a block flow diagram of a mobile top-up product selection system for digital products according to the present invention.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following detailed description refers to the specific implementation, structure, characteristics and effects of a mobile recharging and selecting system for digital products according to the invention, which are provided by the invention, with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The following specifically describes a specific scheme of the mobile recharging and selecting system for digital products provided by the invention with reference to the accompanying drawings.
Referring to fig. 1, a block flow diagram of a mobile recharging and selecting system for digital products according to an embodiment of the invention is shown, the system includes the following blocks:
module 101: and a data acquisition module.
It should be noted that, in order to analyze the interest degree of each user in the digital product and complete the intelligent recommendation of the digital product, it is necessary to collect the consumption of each user, and perform the intelligent recommendation of the digital product according to the consumption.
Specifically, the consumption amount of each user purchasing each commodity in one year is collected at a time interval of one week, and the commodity consumption sequences of the weeks are formed according to the time sequence. And adding the weekly commodity consumption sequences of all commodities of each user according to the corresponding weeks to obtain the weekly consumption value sequence of each user.
So far, the weekly commodity consumption sequence and the weekly consumption amount sequence are obtained.
Module 102: and a digital product analysis module.
In general, the more the user scores a commodity, the more the user's history of evaluation of the commodity, so the user's score of the commodity can be considered to be more representative. Thus, the number of scores may be used as the weight, the more the number of scores, the higher the weight. However, since the purchase of each commodity may be different in some time due to the difference of the own assets, the weight may be corrected according to the difference of the commodity prices because the weight is greatly different only from the ratio of the number of scores.
It is further noted that when there is a large difference between each user purchasing items in different time periods due to the potential for payroll at one time node; that is, when the price of the commodity is high, there is a large difference in the consumption amount of the adjacent week, and when the price of the commodity is low, there is a small difference in the consumption amount of the adjacent week. The ability of each user to bear the price of each commodity can thus be analyzed based on the extent of fluctuation in the consumption amount of each user over all weeks and the difference in the consumption amounts of adjacent weeks.
Specifically, according to the fluctuation distribution of the consumption amount of each user for each commodity for all weeks, a first anomaly factor of each user purchasing each commodity is obtained, and is expressed as:
In the method, in the process of the invention, Represent the firstIndividual user pair numberThe individual commodity is at the firstThe amount of consumption per week is calculated,Represent the firstIndividual user pair numberThe average of the individual commodity's consumption over all weeks,Representing the total number of weeks each user consumed for each commodity,As a sign of the absolute value of the sign,Represent the firstIndividual user purchases the firstA first anomaly factor for the individual good.
Wherein,Representing the fluctuation degree of the consumption amount of each commodity of each user in all weeks, and when the fluctuation degree of the consumption amount is larger, representing that the consumption amount fluctuation is more abnormal, namely, the bearing capacity of the user on the commodity price is weaker; the smaller the fluctuation degree of the consumption amount is, the more normal the consumption amount fluctuation is, namely the stronger the bearing capacity of the user to the commodity price is.
Obtaining a second anomaly factor of each user purchasing each commodity according to the difference of the consumption amount of each commodity by each user on the adjacent weeks, and expressing the second anomaly factor as:
In the method, in the process of the invention, Represent the firstIndividual user pair numberThe individual commodity is at the firstThe amount of consumption per week is calculated,Represent the firstIndividual user pair numberThe individual commodity is at the firstThe amount of consumption per week is calculated,Representing the total number of weeks each user consumed for each commodity,As a sign of the absolute value of the sign,Represent the firstIndividual user purchases the firstAnd a second anomaly factor for the individual good.
Wherein,Representing the difference of the consumption amount of each commodity by each user on the adjacent weeks, and when the difference is larger, representing that the difference of the consumption amount is more abnormal, namely, the weaker the bearing capacity of the user on the commodity price is; when the difference is smaller, the difference representing the consumption amount is more normal, i.e., the user has a stronger bearing capacity for the commodity price.
According to the difference of the consumption amount of each commodity on the adjacent weeks and the fluctuation of the consumption amount of each commodity on all weeks, the bearing capacity of each user on the price of each commodity is obtained, and the bearing capacity is expressed as the following formula:
In the method, in the process of the invention, Represent the firstIndividual user purchases the firstA first anomaly factor for the individual good,Represent the firstIndividual user purchases the firstA second anomaly factor for the individual good,Represents an exponential function with a base of a natural constant,Represent the firstIndividual user pair numberCapability of bearing individual commodity prices.
When the first abnormality factor and the second abnormality factor are larger, namely the abnormality is represented, the bearing capacity of the user on the commodity price is weaker; when the first abnormality factor and the second abnormality factor are smaller, that is, the indication is more normal, the user's ability to bear the commodity price is stronger.
Thus, the bearing capacity of each user to each commodity price is obtained.
It should be noted that, the total consumption of the user generally has regularity, that is, in a certain period of time, the total consumption of the user gradually increases, and in a certain period of time, the total consumption of the user gradually decreases, but when the total consumption of the user purchasing all the commodities in a period of time does not change greatly, the purchasing power of the user is stronger; when the variation of the total amount of consumption of all the commodities purchased by the user over a period of time is large, it means that the purchasing power of the user is weak. But when the demand of a user on a commodity is stable, the more stable the price bearing capacity of the commodity is, the more strong the price bearing capacity of the commodity is; conversely, when the user's demand for a commodity is unstable, this indicates that the price of the commodity is less stable, and also indicates that the price of the commodity is less stable. Therefore, the bearing capacity of each user on each commodity price can be corrected according to the change condition of the total consumption amount of the user in all weeks, and the bearing capacity of each user on each commodity price on the consumption rule can be obtained.
Specifically, a reference coordinate system is established by taking a week serial number of a time sequence as a horizontal axis and taking a total consumption amount of each week as a vertical axis; mapping data in the week consumption sequence of each user in a reference coordinate system, performing curve fitting on the week consumption sequence of each user by using a five-degree polynomial through a least square method, marking the fitted curve as a week consumption curve, and obtaining all extreme points of the week consumption curve, wherein the extreme points comprise a maximum point and a minimum point. In this embodiment, curve fitting is performed using a fifth order polynomial, but is not particularly limited; the least square method is a known technique, and detailed description thereof is omitted herein.
Correcting the bearing capacity of each user to each commodity price according to the gradient change between adjacent extreme points in the week consumption curve of each user to obtain the bearing capacity of each user to each commodity price on the consumption rule, wherein the bearing capacity is expressed as follows by a formula:
In the method, in the process of the invention, Represent the firstIndividual user pair numberThe bearing capacity of the price of the individual goods,Represent the firstWeek consumption curve of individual userThe value of the horizontal axis corresponding to each extreme point,Represent the firstWeek consumption curve of individual userThe value of the horizontal axis corresponding to each extreme point,Represent the firstWeek consumption curve of individual userThe value of the vertical axis corresponding to each extreme point,Represent the firstWeek consumption curve of individual userThe value of the vertical axis corresponding to each extreme point,Representing the total number of all extreme points in the weekly consumption profile for each user,Represent the firstThe individual users are related to the first on the consumption ruleThe bearing capacity of the price of the individual goods,A linear normalization function is represented and,Is an absolute value sign.
Wherein,The inverse ratio of the gradient between two adjacent extreme points is represented, namely, when the value is larger, the gradient change between the two adjacent extreme points is smaller, namely, the bearing capacity of a user on commodity price is larger on a consumption rule; when the value is smaller, the gradient change between two adjacent extreme points is larger, namely the bearing capacity of the user on commodity price is smaller on the consumption rule.
It should be noted that the number of the substrates,The denominator of (2) cannot be 0 because the ordinate of the adjacent two extreme points is not identical, and thus the denominator cannot be equal to 0.
So far, the bearing capacity of each user on the price of each commodity on the consumption rule is obtained.
Module 103: and a digital product scoring module.
It should be noted that, when the difference of the bearing capacity of each user against any two commodity prices on the consumption rule is smaller, the higher the credibility predicted by the bearing capacity of the two commodity prices is indicated, the larger the scoring weight of the corresponding user against the purchased commodity is, whereas when the difference of the bearing capacity of each user against any two commodity prices on the consumption rule is larger, the lower the credibility predicted by the bearing capacity of the two commodity prices is indicated, the lower the scoring weight of the corresponding user against the purchased commodity is indicated.
Specifically, an initial weight parameter Q is preset, where the embodiment is described by taking q=100 as an example, and the embodiment is not limited specifically, where Q may be determined according to the specific implementation situation.
According to the difference of the bearing capacity of each user on the price of any two commodities on the consumption rule, the scoring weight of each user for simultaneously purchasing any two commodities is obtained, and the scoring weight is expressed as follows:
In the method, in the process of the invention, Represent the firstThe individual users are related to the first on the consumption ruleThe bearing capacity of the price of the individual goods,Represent the firstThe individual users are related to the first on the consumption ruleThe bearing capacity of the price of the individual goods,Represent the firstThe individual users purchase the firstPersonal commodity and the firstThe scoring weight of the individual items of merchandise,As a sign of the absolute value of the sign,Represents an exponential function with a base of a natural constant,Representing preset initial weight parameters.
Wherein,Representing the difference of bearing capacity of each user to any two commodity prices on a consumption rule, and when the difference is larger, representing that the reliability predicted by the bearing capacity of the two commodity prices is lower, the grading weight of the corresponding user to the purchased commodity is smaller; when the difference is smaller, the higher the reliability of prediction of the bearing capacity by the two commodity prices is expressed, the greater the scoring weight of the corresponding user for purchasing the commodity is.
So far, the scoring weight of each user buying any two commodities at the same time is obtained.
According to the scoring weight of any two commodities purchased by each user at the same time, scoring of each commodity by each user is obtained through a weighted Slope One algorithm; the weighted Slope One algorithm is a well-known technique, and will not be described in detail here.
Thus, the score of each commodity is obtained for each user.
Module 104: and an intelligent recommendation module.
And sequencing all the commodities from large to small according to the scoring of each commodity by each user to obtain a commodity sequence of each user, and recommending the commodities to the user in sequence according to the sequence in the commodity sequence of each user.
In this embodiment, a commodity is a digital product, and purchase of the commodity is recharging of the digital product.
This embodiment is completed.
The following examples were usedThe model is only used for representing that the result output by the negative correlation and the constraint model is inIn the section, other models with the same purpose can be replaced in the specific implementation, and the embodiment only usesThe model is described as an example, and is not particularly limited, whereinRefers to the input of the model.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the invention, but any modifications, equivalent substitutions, improvements, etc. within the principles of the present invention should be included in the scope of the present invention.
Claims (7)
1. A digital product mobile recharging option system, which is characterized by comprising the following modules:
The data acquisition module is used for acquiring the consumption amount of each user for purchasing a plurality of weeks of each commodity to form a weekly commodity consumption sequence, and acquiring the weekly consumption amount sequence of each user according to the weekly commodity consumption sequences of all commodities of each user;
The digital product analysis module is used for obtaining the bearing capacity of each user on the price of each commodity according to the difference of the consumption of each commodity on the adjacent weeks and the fluctuation of the consumption of each commodity on all weeks, obtaining a week consumption curve according to the week consumption sequence of each user, obtaining all extreme points of the week consumption curve, and correcting the bearing capacity of each user on the price of each commodity according to the gradient change between the adjacent extreme points in the week consumption curve of each user to obtain the bearing capacity of each user on the price of each commodity on the consumption rule;
the method for obtaining the bearing capacity of each user on the price of each commodity according to the difference of the consumption amount of each commodity on the adjacent weeks and the fluctuation of the consumption amount of each commodity on all weeks comprises the following steps:
Calculating the product of the first abnormality factor of each commodity purchased by each user and the second abnormality factor of each commodity purchased by each user, and recording the result of the product as a first characteristic Will beThe bearing capacity of each user to each commodity price is recorded;
Wherein, An exponential function that is based on a natural constant;
The method for obtaining the weekly expense curve according to the weekly expense sequence of each user comprises the following steps:
Establishing a reference coordinate system by taking a week serial number of a time sequence as a horizontal axis and taking a consumption sum of each week as a vertical axis; mapping data in the week consumption sequence of each user in a reference coordinate system, performing curve fitting on the week consumption sequence of each user by a least square method, and marking the fitted curve as a week consumption curve;
correcting the bearing capacity of each user to each commodity price according to the gradient change between adjacent extreme points in the week consumption curve of each user to obtain the bearing capacity of each user to each commodity price on the consumption rule, wherein the method comprises the following steps:
the calculation formula of the bearing capacity of each commodity price of each user on the consumption rule is as follows:
In the method, in the process of the invention, Represent the firstIndividual user pair numberThe bearing capacity of the price of the individual goods,Represent the firstWeek consumption curve of individual userThe value of the horizontal axis corresponding to each extreme point,Represent the firstWeek consumption curve of individual userThe value of the horizontal axis corresponding to each extreme point,Represent the firstWeek consumption curve of individual userThe value of the vertical axis corresponding to each extreme point,Represent the firstWeek consumption curve of individual userThe value of the vertical axis corresponding to each extreme point,Representing the total number of all extreme points in the weekly consumption profile for each user,Represent the firstThe individual users are related to the first on the consumption ruleThe bearing capacity of the price of the individual goods,A linear normalization function is represented and,Is an absolute value symbol;
The digital product scoring module is used for correcting the initial weight parameters according to the difference of the bearing capacity of each user on the price of any two commodities to obtain the scoring weight of each user for simultaneously purchasing any two commodities, and obtaining the scoring of each user for each commodity according to the scoring weight of each user for simultaneously purchasing any two commodities;
And the intelligent recommendation module is used for recommending the commodity according to the score of each commodity by each user.
2. The digital product mobile refill option system of claim 1, wherein said each user purchasing a first anomaly factor for each commodity comprises:
The calculation formula of the first anomaly factor for each user to purchase each commodity is as follows:
In the method, in the process of the invention, Represent the firstIndividual user pair numberThe individual commodity is at the firstThe amount of consumption per week is calculated,Represent the firstIndividual user pair numberThe average of the individual commodity's consumption over all weeks,Representing the total number of weeks each user consumed for each commodity,As a sign of the absolute value of the sign,Represent the firstIndividual user purchases the firstA first anomaly factor for the individual good.
3. The digital product mobile refill option system of claim 1, wherein said each user purchasing a second anomaly factor for each commodity comprises:
The calculation formula of the second anomaly factor for each user to purchase each commodity is as follows:
In the method, in the process of the invention, Represent the firstIndividual user pair numberThe individual commodity is at the firstThe amount of consumption per week is calculated,Represent the firstIndividual user pair numberThe individual commodity is at the firstThe amount of consumption per week is calculated,Representing the total number of weeks each user consumed for each commodity,As a sign of the absolute value of the sign,Represent the firstIndividual user purchases the firstAnd a second anomaly factor for the individual good.
4. The mobile recharging and selecting system for digital products according to claim 1, wherein the step of correcting the initial weight parameter according to the difference of the bearing capacity of each user to any two commodity prices in the consumption rule to obtain the scoring weight of each user for purchasing any two commodities at the same time comprises the following steps:
the calculation formula of the scoring weight of each user purchasing any two commodities simultaneously is as follows:
In the method, in the process of the invention, Represent the firstThe individual users are related to the first on the consumption ruleThe bearing capacity of the price of the individual goods,Represent the firstThe individual users are related to the first on the consumption ruleThe bearing capacity of the price of the individual goods,Represent the firstThe individual users purchase the firstPersonal commodity and the firstThe scoring weight of the individual items of merchandise,As a sign of the absolute value of the sign,Represents an exponential function with a base of a natural constant,Representing preset initial weight parameters.
5. The system of claim 1, wherein the step of obtaining the score of each user for each commodity according to the scoring weights of any two commodities purchased by each user simultaneously comprises:
And according to the scoring weight of each user for purchasing any two commodities at the same time, the scoring of each user on each commodity is obtained through a weighted Slope One algorithm.
6. The system of claim 1, wherein the recommending of the commodity according to the score of each commodity by each user comprises:
And sequencing all the commodities from large to small according to the scoring of each commodity by each user to obtain a commodity sequence of each user, and recommending the commodities to the user in sequence according to the sequence in the commodity sequence of each user.
7. The mobile digital product recharging and selecting system according to claim 1, wherein the acquiring the consumption amount of each user for purchasing each commodity for a plurality of weeks, forming a weekly commodity consumption sequence, and obtaining the weekly consumption amount sequence of each user according to the weekly commodity consumption sequences of all commodities of each user comprises:
Collecting consumption amount of a plurality of continuous weeks for each user to purchase each commodity, and forming a weekly commodity consumption sequence according to the time sequence;
and adding the weekly commodity consumption sequences of all commodities of each user according to the corresponding weeks to obtain the weekly consumption value sequence of each user.
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| CN202410404581.9A CN117994009B (en) | 2024-04-07 | Digital product removes and fills a supplement system of selecting |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114549046A (en) * | 2022-01-17 | 2022-05-27 | 北京滴普科技有限公司 | Sales prediction method, system, device and storage medium based on fusion model |
| CN116703533A (en) * | 2023-08-08 | 2023-09-05 | 深圳中天云联科技发展有限公司 | Business management data optimized storage analysis method |
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|---|---|---|---|---|
| CN114549046A (en) * | 2022-01-17 | 2022-05-27 | 北京滴普科技有限公司 | Sales prediction method, system, device and storage medium based on fusion model |
| CN116703533A (en) * | 2023-08-08 | 2023-09-05 | 深圳中天云联科技发展有限公司 | Business management data optimized storage analysis method |
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