CN111582952B - Scoring method, information pushing method and scoring system - Google Patents
Scoring method, information pushing method and scoring system Download PDFInfo
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Abstract
The invention discloses a scoring method, an information pushing method and a scoring system, and relates to the technical field of computers. The scoring method comprises the following steps: the scoring module scores the candidate target objects based on the scoring rule adopted currently; the judging module judges whether the distribution situation of the scoring result accords with a preset condition; if not, the adjustment module adjusts the currently adopted scoring rule until the distribution condition of the scoring result obtained based on the adjusted scoring rule meets the preset condition; if yes, the output module outputs the scoring result and/or the information of the target object screened out based on the scoring result. Through the steps, the scoring rule is adjusted according to the scoring result feedback mechanism, the system development and maintenance cost is reduced, the rationality and flexibility of scoring rule formulation are improved, and the problems that the screening result does not meet expectations and the like are solved.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a scoring method, an information pushing method, and a scoring system.
Background
With the development of internet technology, various online platforms (such as social APP, game APP, shopping APP, insurance and financial APP, etc.) are endless. In many application scenarios, there is a need to score a target object (such as an online platform user). For example, in a coupon issuing scenario, it is necessary to comprehensively analyze various information of users, determine user scores according to specified rules, divide the users into different sections according to the user scores, and give different preferential incentive policies to the users in different sections.
Taking a coupon issuing scenario as an example, in the prior art, when a target user is screened according to a specified rule, condition screening and rule checking are often performed through a conventional SQL (structured query language) statement. Because of complex service scene and numerous conditions, SQL sentences have high complexity and low development efficiency. Moreover, due to the existing stiffness of the rules, once the rules change, certain difficulties are brought to subsequent maintenance and modification.
In carrying out the invention, the inventors of the present invention found that: the adoption of a rule engine to implement a scoring system (such as a user scoring system) in a business can reduce the workload of developers to a certain extent. However, the existing scoring system still has the defects of stiff formulation of the scoring rules, inflexibility, incapability of knowing whether the formulated scoring rules are reasonable and the like, and further can cause the problems that the screening result does not meet expectations and the like.
Disclosure of Invention
In view of the above, the invention provides a scoring method, an information pushing method and a scoring system, which can reduce the system development and maintenance cost, improve the rationality and flexibility of scoring rule formulation, and solve the problem that the screening result does not accord with expectations.
To achieve the above object, according to a first aspect of the present invention, there is provided a scoring method.
The scoring method of the invention comprises the following steps: the scoring module scores the candidate target objects based on the currently adopted scoring rule so as to obtain scoring results of the candidate target objects; the judging module determines the distribution condition of the scoring result and judges whether the distribution condition of the scoring result accords with a preset condition; under the condition that the distribution condition of the scoring results does not accord with the preset condition, the adjustment module adjusts the scoring rule adopted currently until the distribution condition of the scoring results obtained based on the adjusted scoring rule accords with the preset condition; and under the condition that the distribution condition of the scoring result meets the preset condition, the output module outputs the scoring result and/or the information of the target object screened from the candidate target objects based on the scoring result.
Optionally, the method further comprises: before the scoring module scores the candidate target objects based on the currently adopted scoring rules, the scoring module receives a calling request and acquires the candidate target object data carried by the calling request and the currently adopted scoring rules from the calling request.
Optionally, the currently adopted scoring rules include variable rules and non-variable rules; the adjusting module adjusting the scoring rule currently adopted comprises: the adjustment module determines a variable rule of the scoring rules currently adopted and adjusts part or all of the variable rules.
Optionally, the determining module determines a distribution condition of the scoring result, and determining whether the distribution condition of the scoring result meets a preset condition includes: the judging module calculates the coverage rate of the candidate target objects with the scoring result in the first value range in all the candidate target objects; judging whether the coverage rate is in a second value range or not; under the condition that the coverage rate is in a second value range, confirming that the distribution condition of the scoring result meets a preset condition; and under the condition that the coverage rate is not in the second value range, confirming that the distribution condition of the scoring result does not accord with a preset condition.
Optionally, the calculating, by the determining module, coverage rates of candidate target objects with scoring results in the first value range in all candidate target objects includes: the judgment module constructs a histogram taking the scoring result as an abscissa and the number of candidate target objects as an ordinate; the judging module carries out normal distribution curve fitting according to the histogram to obtain a fitted normal distribution curve; and the judging module calculates the probability of the scoring result in the first value range according to the probability calculation formula of the fitted normal distribution curve, and takes the probability as the coverage rate of candidate target objects of the scoring result in the first value range in all candidate target objects.
Optionally, the step of adjusting the currently adopted scoring rule by the adjusting module when the distribution situation of the scoring result does not meet the preset condition includes: when the coverage rate is smaller than the lower threshold value of the second value range, the adjustment module carries out forward adjustment on the currently adopted scoring rule; the forward direction adjustment is an adjustment operation to increase the coverage; when the coverage rate is larger than the upper threshold value of the second value range, the adjustment module carries out reverse adjustment on the currently adopted scoring rule; the reverse adjustment is an adjustment operation to reduce the coverage.
To achieve the above object, according to a second aspect of the present invention, there is provided an information push method.
The information pushing method of the invention comprises the following steps: the information push system sends a call request to the scoring system; after receiving the call request, the scoring system scores the candidate target object based on the scoring rule adopted currently so as to obtain the scoring result of the candidate target object; the scoring system determines the distribution condition of the scoring result and judges whether the distribution condition of the scoring result accords with a preset condition; under the condition that the distribution condition of the scoring results does not accord with the preset condition, the scoring system adjusts the scoring rule adopted currently until the distribution condition of the scoring results obtained based on the adjusted scoring rule accords with the preset condition; outputting the scoring result and/or the information of the target objects screened from the candidate target objects based on the scoring result by a scoring system under the condition that the distribution condition of the scoring result meets the preset condition; and the information pushing system determines a target object according to the information output by the scoring system and pushes information aiming at the target object.
To achieve the above object, according to a third aspect of the present invention, there is provided a scoring system.
The scoring system of the present invention comprises: the scoring module is used for scoring the candidate target objects based on the scoring rule adopted currently so as to obtain scoring results of the candidate target objects; the judging module is used for determining the distribution condition of the scoring result and judging whether the distribution condition of the scoring result accords with a preset condition; the grading system is used for grading the grading rule adopted currently under the condition that the distribution condition of the grading result does not accord with the preset condition, until the distribution condition of the grading result obtained based on the grading rule after the regulation accords with the preset condition; and the output module is used for outputting the scoring result and/or the information of the target object screened from the candidate target objects based on the scoring result by the scoring system under the condition that the distribution condition of the scoring result meets the preset condition.
To achieve the above object, according to a fourth aspect of the present invention, there is provided an electronic apparatus.
The electronic device of the present invention includes: one or more processors; and a storage means for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the scoring method or the information pushing method of the present invention.
To achieve the above object, according to a fifth aspect of the present invention, a computer-readable medium is provided.
The computer readable medium of the present invention has stored thereon a computer program which, when executed by a processor, implements the scoring method or the information pushing method of the present invention.
One embodiment of the above invention has the following advantages or benefits: scoring the candidate target objects based on the currently adopted scoring rules by a scoring system; the scoring system determines whether the distribution situation of the scoring result meets preset conditions; if not, the scoring system adjusts the scoring rule adopted currently until the distribution condition of the scoring result obtained based on the adjusted scoring rule meets the preset condition; if yes, the scoring system outputs the scoring result and/or the information of the target object screened based on the scoring result, so that the scoring rule is adjusted according to a scoring result feedback mechanism, the system development and maintenance cost is reduced, the rationality and flexibility of scoring rule formulation are improved, and the problems that the screening result does not accord with expectations and the like are solved.
Further effects of the above-described non-conventional alternatives are described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
FIG. 1 is a schematic flow chart of a scoring method according to a first embodiment of the present invention;
FIG. 2 is a schematic flow chart of a scoring method according to a second embodiment of the present invention;
FIG. 3 is a schematic diagram of a scoring card according to an embodiment of the invention;
FIG. 4 is a schematic diagram of a fitted normal distribution curve according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of the major modules of a scoring system according to a third embodiment of the present invention;
FIG. 6 is an exemplary system architecture diagram in which embodiments of the present invention may be applied;
fig. 7 is a schematic diagram of a computer system suitable for use in implementing an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, in which various details of the embodiments of the present invention are included to facilitate understanding, and are to be considered merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
It is noted that embodiments of the invention and features of the embodiments may be combined with each other without conflict.
Fig. 1 is a schematic flow chart of a scoring method according to a first embodiment of the present invention. As shown in fig. 1, the scoring method in the embodiment of the present invention includes:
and step S101, scoring the candidate target object by a scoring module based on the scoring rule adopted currently so as to obtain a scoring result of the candidate target object.
Illustratively, the scoring module may be developed based on a rules engine. Wherein the rule engine is understood as a component embedded in an application, which enables the separation of business decisions from application code and the writing of business decisions using predefined semantic modules, which can accept data input, interpret business rules, and make business decisions according to the business rules.
In this step, the scoring module may automatically calculate a scoring result for the candidate target object based on the scoring rule currently employed and the data for the candidate target object. The candidate target object may be various service objects, for example, the candidate target object may be a user on an online platform, or the candidate target object may be various insurance products, or the candidate target object may be various coupons, or the like. The scoring rule is a rule according to which the candidate target object is scored. In specific implementation, the scoring rules are defined by specific businesses, and different scoring rules can be adopted in different business scenes. For example, in a business scenario in which coupons are sent, a scoring rule that is adopted for scoring a user may be set to: the user who has to purchase the insurance product on the platform must be older than 25 years old, etc.
Further, before step S101, the method according to the embodiment of the present invention may further include the following steps: the scoring module obtains the scoring rule currently adopted and the data of the candidate target object. In particular, the scoring module may trigger the "acquire the scoring rule currently employed and the data of the candidate target object" and subsequent operations after receiving the invocation request.
In an alternative embodiment, the call request carries the rule currently adopted and the data of the candidate target object. In this alternative embodiment, the scoring module may directly obtain the rules currently adopted and the candidate target object data carried by the call request from the call request.
In another optional embodiment, the call request carries a rule identifier and a candidate target object identifier. In this alternative embodiment, the scoring module may query a storage module (e.g., a database) based on the rule identification and candidate object identification to obtain data for the currently employed rule and candidate object.
Step S102, a judgment module determines the distribution condition of the scoring result.
Step S103, a judging module judges whether the distribution situation of the grading result meets preset conditions.
Considering that in an actual service scenario, the scoring rule adopted at present may not be reasonable enough, so that the number of the screened target objects is too large or too small to meet the service requirement. In view of this, in the embodiment of the present invention, a scoring result feedback mechanism is introduced, which is specifically implemented in step S102 and step S103, that is, whether the distribution situation of the scoring result meets the expectations is determined by determining the distribution situation of the scoring result, so as to know whether the currently adopted scoring rule is reasonable.
In an alternative embodiment, the distribution of the scoring results may be represented by coverage. In this alternative embodiment, step S102 specifically includes: calculating the coverage rate of the target objects with the scoring result in the first value range in all the target objects; the step S103 specifically includes: judging whether the coverage rate is in a second value range or not; under the condition that the coverage rate is in a second value range, confirming that the distribution condition of the scoring result meets a preset condition; and under the condition that the coverage rate is not in the second value range, confirming that the distribution condition of the scoring result does not accord with a preset condition. The first value range and the second value range may be one or more discrete values, or may be a continuous value interval. For example, in a coupon dispensing scenario, the first value range is a continuous value interval, such as (60 a, +++). The second range is a number, such as 30%.
In another alternative embodiment, the distribution of the scoring results may be represented by the number of some portion of candidate target objects. In this alternative embodiment, step S102 specifically includes: calculating the number of target objects (N 1 ) The method comprises the steps of carrying out a first treatment on the surface of the The step S103 specifically includes: judging the number N 1 Whether the first value range is within the second value range; at said number N 1 Under the condition of being in the second value range, confirming that the distribution condition of the scoring result meets the preset condition; at said number N 1 Not located in the second range of valuesIn this case, it is confirmed that the distribution of the scoring results does not meet the preset condition.
Further, if the determination result in step S103 is no, step S104 is executed; if the determination result in step S103 is yes, step S105 is executed.
And step S104, an adjustment module adjusts the scoring rule adopted currently.
In an alternative embodiment, the scoring rules currently employed include both variable rules and non-variable rules. For example, in a business scenario of coupon issuance, the non-variable rules in the scoring rules include: the variable rules in the scoring rules must include: the age of the user is greater than 25 years old, etc. In this alternative embodiment, step S104 includes: and determining variable rules in the scoring rules currently adopted, and adjusting part or all of the variable rules. In specific implementation, different identifications can be set for the non-variable rule and the variable rule in advance so as to facilitate subsequent distinguishing and searching of the variable rule in the scoring rule adopted currently, and further adjustment of the variable rule is carried out.
In another alternative embodiment, the scoring rules currently employed are all variable rules. In this alternative embodiment, some or all of the scoring rules currently employed may be directly adjusted.
Step S105, an output module outputs the scoring result and/or information of the target object screened from the candidate target objects based on the scoring result.
For example, when the users need to be scored in the coupon issuing scene, the scoring values of all the users obtained by the scoring system can be output, and the user list screened based on the scoring values can also be output. For example, if users with score values greater than 60 are targeted for coupon release, a list of these users is output.
In the embodiment of the invention, the candidate target objects are scored and screened through a scoring system comprising a scoring module, a judging module, an adjusting module and an output module, so that the system development and maintenance cost is reduced; further, the scoring rule is adjusted according to the scoring value feedback mechanism, so that the rationality and flexibility of scoring rule formulation are improved, and the problem that the screening result does not accord with expectations is solved.
Fig. 2 is a schematic flow chart of a scoring method according to a second embodiment of the present invention. As shown in fig. 2, the scoring method according to the embodiment of the present invention includes:
step 201, a scoring module receives a call request, and obtains candidate target object data carried by the call request and a scoring rule adopted currently from the call request.
The candidate target object may be various service objects, for example, the candidate target object may be a user of an online platform, or the candidate target object may be various insurance products, or the candidate target object may be various coupons, or the like. The data of the candidate target object may be attribute data of the candidate target object. For example, when the candidate target object is a user, the user attribute data may include: age, gender, region, school, marital status, and/or income level of the user, etc. In the specific implementation, for the case that the number of users is very large and the users cannot be fully loaded, a certain proportion of users can be randomly extracted to serve as candidate target objects. Wherein, the scoring rule is defined by specific business, and different business scenes can adopt different scoring rules. For example, in a business scenario of coupon issuance, the scoring rules may be: the user who has to purchase the insurance product on the platform must be older than 25 years old, etc.
Optionally, the call request may further carry the following parameter information: a first range of values, and a second range of values. The first value range is specifically a threshold range of a preset scoring result, and the second value range is specifically a threshold range of a preset coverage rate. The first value range and the second value range may be one or more discrete values, or may be a continuous value interval. For example, in a coupon dispensing scenario, the first range of values may be a continuous interval of values, such as (60 a, +++). The second range of values may be a number, such as 30%.
And step S202, scoring the candidate target object by a scoring module based on the scoring rule adopted currently so as to obtain a scoring result of the candidate target object.
In this step, the scoring module may automatically calculate a scoring result for the candidate target object based on the scoring rule currently employed and the data for the candidate target object. In an alternative example, to increase the flexibility of the scoring system, the scoring system may be configured by a scoring card function as shown in fig. 3. As shown in fig. 3, the scoring card shows, in the form of a two-dimensional list, respective attributes of candidate target objects, conditions of different sections set for the different attributes, and scores corresponding to the conditions of the respective sections. For example, the target object shown in fig. 3 is specifically an applicant, the attribute of the target object is specifically cholesterol, and the condition set for the attribute of cholesterol includes, with a corresponding score: cholesterol content is less than or equal to 125, corresponding score of 0 score; cholesterol content is greater than 125 and less than 200, corresponding to a score of 1; cholesterol content greater than or equal to 200 and less than 220, corresponding score of 2 points, and so on.
And step 203, the judging module calculates the coverage rate of the candidate target objects with the scoring result in the first value range in all the candidate target objects.
The normal distribution is an important distribution in probability theory. Numerous practical and theoretical analyses have shown that most random variables obey or approximately obey normal distributions. Such as measurement errors, student exam performance, height and weight of a person, quality data of a product, etc., may be considered to be subject to normal distribution. Actual calculation and experience show that the scoring values of the candidate target objects in the embodiment of the invention approximately follow normal distribution. In view of this, the coverage can be calculated by means of normal distribution curve fitting.
In an alternative embodiment, step S203 specifically includes: step 1 to step 3.
And step 1, constructing a histogram with the grading result as an abscissa and the number of candidate target objects as an ordinate by the judging module.
In a specific example, a histogram constructed according to step 1 is shown in fig. 4. In fig. 4, the x-axis coordinates represent scoring scores obtained according to the current rule, the y-axis coordinates represent the number of users participating in the scoring, and each rectangular bar in the histogram represents the number of users located in each scoring score interval.
And step 2, a judging module carries out normal distribution curve fitting according to the histogram so as to obtain a fitted normal distribution curve.
As shown in fig. 4, the curve in this figure is a normal distribution curve after fitting. Assuming that the mean of the user scoring scores shown in fig. 4 is denoted μ and the variance is denoted σ, the fitted normal distribution curve can be expressed as:
where x represents the scoring score obtained according to the current rule and f (x) represents the number of users participating in the scoring.
And 3, calculating the probability of the scoring result falling in a first value range according to a probability calculation formula of the fitted normal distribution curve by a judging module, and taking the probability as the coverage rate of the target objects with the scoring result in the first value range in all the target objects.
Wherein, the probability calculation formula of the normal distribution curve can be expressed as:
wherein p (a.ltoreq.x.ltoreq.b) represents the probability that the scoring value falls within the first value range [ a, b ].
In another alternative embodiment, step S203 specifically includes: for each candidate target object, judging whether the grading result is in the first value range one by one, counting the number of candidate target objects (set as N1) with the grading result in the first value range, and dividing the number of candidate target objects N1 by the total number of candidate target objects to obtain coverage rate.
Step S204, the judging module judges whether the coverage rate is in a second value range. Executing step S205 when the coverage rate is in a second value range; in the case where the coverage is not located in the second value range, step S206 is performed.
Step S205, an output module outputs the scoring result and/or information of the target object screened from the candidate target objects based on the scoring result.
For example, when the users need to be scored in the coupon issuing scene, the scoring values of all the users obtained by the scoring system can be output, and the user list screened based on the scoring values can also be output. For example, if users with score values greater than 60 are targeted for coupon release, a list of these users is output.
Step S206, the adjustment module adjusts the scoring rule adopted currently.
Illustratively, this step may include, in particular: when the coverage rate is smaller than the lower threshold value of the second value range, the adjustment module carries out forward adjustment on the currently adopted scoring rule; the forward direction adjustment is an adjustment operation to increase the coverage; when the coverage rate is larger than the upper threshold value of the second value range, the adjustment module carries out reverse adjustment on the currently adopted scoring rule; the reverse adjustment is an adjustment operation to reduce the coverage. It should be noted that, when the second value range is a numerical value, the upper limit threshold and the lower limit threshold are the same value; when the second value range is a continuous value interval, the upper threshold and the lower threshold are different values.
For example, in scoring the user, if the first range is set to a continuous range, such as (60, +++), the second value range is specifically set to a value, for example, 30%, so that when the proportion of the number of users with the score value greater than 60 to the total number of users is greater than 30%, the current scoring rule needs to be reversely adjusted, for example, the scoring rule is modified to be "a user who purchases 1 or more kinds of insurance products on the platform" to a user who purchases 3 or more kinds of insurance products on the platform "; when the proportion of the number of users with the score value of more than 60 to the total number of users is less than 30%, the current scoring rule needs to be adjusted in the forward direction, for example, the scoring rule is modified to be "the users who purchase the insurance products on the platform with the category of 3 or more" to be "the users who purchase the insurance products on the platform with the category of 1 or more".
After step S206, step S202 may be performed again until the distribution of the scoring results obtained based on the adjusted scoring rule meets the preset condition.
In the embodiment of the invention, the candidate target objects are scored and screened through the steps, and the scoring rule is adjusted when the distribution condition of the scoring result does not accord with the expectation, so that the system development and maintenance cost is reduced, the rationality and flexibility of scoring rule formulation are improved, and the problems that the screening result does not accord with the expectation and the like are solved.
Further, on the basis of the embodiment shown in fig. 1, the invention also provides an information pushing method. The information pushing method of the embodiment of the invention comprises the following steps:
step S301, the information push system sends a call request to the scoring system.
Illustratively, the invocation request may include data of the candidate target object, the scoring rule currently employed. The candidate target object may be a user of the online platform, and the data of the candidate target object may be attribute data of the user. For example, on a web site where an insurance product is sold, the candidate target object may be specifically a user who has purchased the insurance product recently (e.g., within a year) on the web site, and the attribute data of the user may include attribute data of age, gender, region, academy, marital status, and/or income level of the user.
Wherein the scoring rule is a rule according to which the candidate target object is scored. In specific implementation, the scoring rules are defined by specific businesses, and different scoring rules can be adopted in different business scenes. For example, in a business scenario in which coupons are sent, a scoring rule that is adopted for scoring a user may be set to: the user who has to purchase the insurance product on the platform must be older than 25 years old, etc.
And step S302, after receiving the call request, the scoring system scores the candidate target objects based on the currently adopted scoring rule so as to obtain scoring results of the candidate target objects.
In this step, the scoring system may automatically calculate the scoring results for the candidate target objects based on the scoring rules currently employed, as well as the data for the candidate target objects. For example, assuming that the candidate target object is an applicant, the scoring rule is: the score of each applicant can be calculated according to the cholesterol content of each applicant if the score corresponding to the cholesterol content is less than or equal to 125 is 0 score, the score corresponding to the cholesterol content is more than 125 and less than 200 is 1 score, and the score corresponding to the cholesterol content is more than or equal to 200 and less than 220 is 2 score.
Step S303, a scoring system determines the distribution condition of the scoring result and judges whether the distribution condition of the scoring result meets a preset condition.
Considering that in an actual service scenario, the scoring rule adopted at present may not be reasonable enough, so that the number of the screened target objects is too large or too small to meet the service requirement. In view of this, in the embodiment of the present invention, a scoring result feedback mechanism is introduced, which is specifically implemented in step S303, that is, by determining the distribution situation of the scoring result, it is determined whether the distribution situation of the scoring result meets the expectations, so as to know whether the currently adopted scoring rule is reasonable.
In an alternative embodiment, the distribution of the scoring results may be represented by coverage. In this alternative embodiment, step S303 specifically includes: calculating the coverage rate of the target objects with the scoring result in the first value range in all the target objects; judging whether the coverage rate is in a second value range or not; under the condition that the coverage rate is in a second value range, confirming that the distribution condition of the scoring result meets a preset condition; and under the condition that the coverage rate is not in the second value range, confirming that the distribution condition of the scoring result does not accord with a preset condition. The first value range and the second value range may be one or more discrete values, or may be a continuous value interval. For example, in a coupon dispensing scenario, the first value range is a continuous value interval, such as (60 a, +++). The second range is a number, such as 30%.
And step S304, when the distribution condition of the scoring results does not accord with the preset condition, the scoring system adjusts the currently adopted scoring rule until the distribution condition of the scoring results obtained based on the adjusted scoring rule accords with the preset condition.
In an alternative embodiment, the scoring rules currently employed include both variable rules and non-variable rules. For example, in a business scenario of coupon issuance, the non-variable rules in the scoring rules include: the variable rules in the scoring rules must include: the age of the user is greater than 25 years old, etc. In this alternative embodiment, the scoring system first determines the variable rules in the scoring rules currently employed and then adjusts some or all of the variable rules. In specific implementation, different identifications can be set for the non-variable rule and the variable rule in advance so as to facilitate subsequent distinguishing and searching of the variable rule in the scoring rule adopted currently, and further adjustment of the variable rule is carried out.
In another alternative embodiment, the scoring rules currently employed are all variable rules. In this alternative embodiment, the scoring system may directly make adjustments to some or all of the scoring rules currently employed.
And step S305, outputting the scoring result and/or the information of the target objects screened from the candidate target objects based on the scoring result by the scoring system under the condition that the distribution condition of the scoring result meets the preset condition.
In this step, the scoring system may send the scoring result and/or the information of the screened target object to an information pushing system. For example, when the users need to be scored in the coupon issuing scene, the scoring values of all the users obtained by the scoring system can be output, and the user list screened based on the scoring values can also be output. For example, if users with score values greater than 60 are targeted for coupon release, a list of these users is output.
Step S306, the information pushing system determines a target object according to the information output by the scoring system, and pushes information to the target object
In the coupon issuing scenario, when the scoring system outputs the scoring values of the users, the information pushing system may screen out a part of the users according to the scoring values of the users, and perform coupon pushing for the part of the users, for example, screen out the users with scoring values greater than 60 points, and perform coupon pushing for the part of the users; when the scoring system outputs the information of the users screened according to the scoring values, the coupon pushing can be directly carried out on the users.
In the embodiment of the invention, the scoring rule feedback mechanism is introduced, so that the scoring rule can be automatically and flexibly adjusted when the scoring rule does not meet the service requirement, the screened target object accords with the expectation, and the accuracy and the flexibility of information pushing are improved.
Fig. 5 is a schematic diagram of main modules of a scoring system according to a third embodiment of the present invention. As shown in fig. 5, the scoring system 500 according to the embodiment of the present invention includes: a scoring module 501, a judging module 502, an adjusting module 503 and an output module 504.
The scoring module 501 is configured to score the candidate target object based on the currently adopted scoring rule, so as to obtain a scoring result of the candidate target object.
Wherein the scoring system, and in particular scoring module 501, may be developed based on a rules engine. Wherein the rule engine is understood as a component embedded in an application, which enables the separation of business decisions from application code and the writing of business decisions using predefined semantic modules, which can accept data input, interpret business rules, and make business decisions according to the business rules.
Illustratively, the scoring module 501 may automatically calculate the scoring results for the candidate target objects based on the scoring rules currently employed and the data for the candidate target objects. The candidate target object may be various service objects, for example, the candidate target object may be a user on an online platform, or the candidate target object may be various insurance products, or the candidate target object may be various coupons, or the like. The scoring rule is a rule according to which the candidate target object is scored. In specific implementation, the scoring rules are defined by specific businesses, and different scoring rules can be adopted in different business scenes. For example, in a business scenario in which coupons are sent, a scoring rule that is adopted for scoring a user may be set to: the user who has to purchase the insurance product on the platform must be older than 25 years old, etc.
In an alternative example, the scoring module 501 may be further configured to obtain the currently adopted scoring rule and the data of the candidate target object before performing the step of scoring the candidate target object based on the currently adopted scoring rule. In particular, the scoring system may trigger the "acquire scoring rules currently employed and data of candidate target objects" and subsequent operations after receiving the invocation request.
In an alternative embodiment, the call request carries the rule currently adopted and the data of the candidate target object. In this alternative embodiment, the scoring module 501 may obtain the rules currently adopted and the candidate target object data carried by the scoring module directly from the call request.
In another optional embodiment, the call request carries a rule identifier and a candidate target object identifier. In this alternative embodiment, the scoring module may query a storage module (e.g., a database) based on the rule identification and candidate object identification to obtain data for the currently employed rule and candidate object.
The judging module 502 is configured to determine a distribution situation of the scoring result, and judge whether the distribution situation of the scoring result meets a preset condition.
Considering that in an actual service scenario, the scoring rule adopted at present may not be reasonable enough, so that the number of the screened target objects is too large or too small to meet the service requirement. In view of this, in the embodiment of the present invention, a scoring result feedback mechanism is introduced, specifically, a determining module determines a distribution situation of the scoring result, and determines whether the distribution situation of the scoring result meets an expectation, so as to know whether the current scoring rule is reasonable.
In an alternative embodiment, the distribution of the scoring results may be represented by coverage. In this alternative embodiment, the determining module 502 determines the distribution situation of the scoring result, and determines whether the distribution situation of the scoring result meets a preset condition specifically includes: the judging module 502 calculates the proportion, namely the coverage rate, of the candidate target objects with the scoring result in the first value range in all the candidate target objects; the judging module 502 judges whether the coverage rate is in a second value range; under the condition that the coverage rate is in a second value range, confirming that the distribution condition of the scoring result meets a preset condition; and under the condition that the coverage rate is not in the second value range, confirming that the distribution condition of the scoring result does not accord with a preset condition. The first value range and the second value range may be one or more discrete values, or may be a continuous value interval. For example, in a coupon dispensing scenario, the first range of values may be a continuous interval of values, such as (60 a, +++). The second range of values may be a number, such as 30%.
In another alternative embodiment, the distribution of the scoring results may be represented by the number of some portion of candidate target objects. In this alternative embodiment, the determining module 502 determines the distribution situation of the scoring result, and determines whether the distribution situation of the scoring result meets a preset condition specifically includes: the determination module 502 calculates the number of candidate target objects (which may be denoted as N) whose scoring result is within the first range of values 1 ) The method comprises the steps of carrying out a first treatment on the surface of the The judgment module 502 judges the number N 1 Whether the first value range is within the second value range; at said number N 1 Under the condition of being in the second value range, confirming that the distribution condition of the scoring result meets the preset condition; at said number N 1 And under the condition that the score is not in the second value range, confirming that the distribution condition of the score result does not accord with a preset condition.
The adjusting module 503 is configured to adjust the currently adopted scoring rule when the distribution situation of the scoring result does not meet the preset condition, until the distribution situation of the scoring result obtained based on the adjusted scoring rule meets the preset condition.
In an alternative embodiment, the scoring rules currently employed include both variable rules and non-variable rules. For example, in a coupon issuing scenario, the set non-variable rules include: must be the user who purchased the insurance product on the platform; the set variable rules include: the age of the user is greater than 25 years old, etc. In this alternative embodiment, the adjusting module 503 adjusts the scoring rule currently adopted includes: the adjustment module 503 determines a variable rule among the scoring rules currently employed and then adjusts some or all of the variable rules. In specific implementation, different identifications can be set for the non-variable rule and the variable rule in advance so as to facilitate subsequent distinguishing and searching of the variable rule in the current scoring rule and further adjust the variable rule.
In another alternative embodiment, the scoring rules currently employed are all variable rules. In this alternative embodiment, the adjustment module 503 may directly adjust some or all of the scoring rules currently employed.
And the output module 504 is configured to output the scoring result and/or information of a target object screened from the candidate target objects based on the scoring result when the distribution situation of the scoring result meets a preset condition.
For example, when the users need to be scored in the coupon issuing scene, the output module may output the scoring values of all the users obtained by the scoring system, or may output a list of users screened based on the scoring values. For example, if users with score values greater than 60 are targeted for coupon release, a list of these users may be output.
In the scoring system provided by the embodiment of the invention, the scoring module scores and screens the target object, so that the system development and maintenance cost is reduced; the scoring rule is adjusted by the judging module and the adjusting module according to the scoring result feedback mechanism, so that the rationality and flexibility of scoring rule formulation are improved, and the problem that the screening result does not accord with expectations is solved.
Fig. 6 illustrates an exemplary system architecture 600 in which a scoring method or scoring system of an embodiment of the present invention may be applied.
As shown in fig. 6, the system architecture 600 may include terminal devices 601, 602, 603, a network 604, and a server 605. The network 604 is used as a medium to provide communication links between the terminal devices 601, 602, 603 and the server 605. The network 604 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
A user may interact with the server 605 via the network 604 using the terminal devices 601, 602, 603 to receive or send messages, etc. Various communication client applications, such as insurance applications, shopping applications, web browser applications, search applications, instant messaging tools, mailbox clients, social platform software, etc., may be installed on the terminal devices 601, 602, 603.
The terminal devices 601, 602, 603 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablets, laptop and desktop computers, and the like.
The server 605 may be a server providing various services, such as a background management server providing support for insurance-type websites browsed by the user using the terminal devices 601, 602, 603. The background management server may analyze the received target object scoring request and the like, and feed back a processing result (such as the target object scoring result) to the terminal device.
It should be noted that, the scoring method provided in the embodiment of the present invention is generally executed by the server 605, and accordingly, the scoring system is generally disposed in the server 605.
It should be understood that the number of terminal devices, networks and servers in fig. 6 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 7, there is illustrated a schematic diagram of a computer system 700 suitable for use in implementing an electronic device of an embodiment of the present invention. The computer system shown in fig. 7 is only an example, and should not be construed as limiting the functionality and scope of use of the embodiments of the invention.
As shown in fig. 7, the computer system 700 includes a Central Processing Unit (CPU) 701, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 702 or a program loaded from a storage section 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the system 700 are also stored. The CPU 701, ROM 702, and RAM 703 are connected to each other through a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
The following components are connected to the I/O interface 705: an input section 706 including a keyboard, a mouse, and the like; an output portion 707 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage section 708 including a hard disk or the like; and a communication section 709 including a network interface card such as a LAN card, a modem, or the like. The communication section 709 performs communication processing via a network such as the internet. The drive 710 is also connected to the I/O interface 705 as needed. A removable medium 711 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 710 as necessary, so that a computer program read therefrom is mounted into the storage section 708 as necessary.
In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 709, and/or installed from the removable medium 711. The above-described functions defined in the system of the present invention are performed when the computer program is executed by a Central Processing Unit (CPU) 701.
The computer readable medium shown in the present invention may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules involved in the embodiments of the present invention may be implemented in software or in hardware. The described modules may also be provided in a processor, for example, as: a processor comprises a scoring module, a judging module, an adjusting module and an output module. The names of these modules do not constitute a limitation on the module itself in some cases, and for example, the scoring module may also be described as "a module that scores candidate target objects".
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be present alone without being fitted into the device. The computer-readable medium carries one or more programs which, when executed by one of the devices, cause the device to perform the following: the scoring module scores the candidate target objects based on the currently adopted scoring rule so as to obtain scoring results of the candidate target objects; the judging module determines the distribution condition of the scoring result and judges whether the distribution condition of the scoring result accords with a preset condition; under the condition that the distribution condition of the scoring results does not accord with the preset condition, the adjustment module adjusts the scoring rule adopted currently until the distribution condition of the scoring results obtained based on the adjusted scoring rule accords with the preset condition; and under the condition that the distribution condition of the scoring result meets the preset condition, the output module outputs the scoring result and/or the information of the target object screened from the candidate target objects based on the scoring result.
According to the technical scheme provided by the embodiment of the invention, the scoring rule can be adjusted according to the scoring result feedback mechanism, so that the system development and maintenance cost is reduced, the rationality and flexibility of rule formulation are improved, and the problems that the screening result does not accord with expectations and the like are solved.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives can occur depending upon design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (9)
1. A scoring method, the method comprising:
the scoring module scores the candidate target objects based on the currently adopted scoring rule so as to obtain scoring results of the candidate target objects;
the judging module determines the distribution condition of the scoring result and judges whether the distribution condition of the scoring result meets a preset condition, and the method comprises the following steps: the judgment module constructs a histogram taking the scoring result as an abscissa and the number of candidate target objects as an ordinate; the judging module carries out normal distribution curve fitting according to the histogram to obtain a fitted normal distribution curve; the judging module calculates the probability that the scoring result is positioned in a first value range according to a probability calculation formula of the fitted normal distribution curve, takes the probability as the coverage rate of candidate target objects of which the scoring result is positioned in the first value range in all candidate target objects, and judges whether the coverage rate is positioned in a second value range or not;
Under the condition that the distribution condition of the scoring results does not accord with the preset condition, the adjustment module adjusts the scoring rule adopted currently until the distribution condition of the scoring results obtained based on the adjusted scoring rule accords with the preset condition;
and under the condition that the distribution condition of the scoring result meets the preset condition, the output module outputs the scoring result and/or the information of the target object screened from the candidate target objects based on the scoring result.
2. The method according to claim 1, wherein the method further comprises:
before the scoring module scores the candidate target objects based on the currently adopted scoring rules, the scoring module receives a calling request and acquires the candidate target object data carried by the calling request and the currently adopted scoring rules from the calling request.
3. The method of claim 1, wherein the currently employed scoring rules include variable rules and non-variable rules; the adjusting module adjusting the scoring rule currently adopted comprises:
the adjustment module determines a variable rule of the scoring rules currently adopted and adjusts part or all of the variable rules.
4. The method of claim 2, wherein the determining module determining the distribution of the scoring results and determining whether the distribution of the scoring results meets a preset condition comprises:
the judging module calculates the coverage rate of the candidate target objects with the scoring result in the first value range in all the candidate target objects; judging whether the coverage rate is in a second value range or not; under the condition that the coverage rate is in a second value range, confirming that the distribution condition of the scoring result meets a preset condition; and under the condition that the coverage rate is not in the second value range, confirming that the distribution condition of the scoring result does not accord with a preset condition.
5. The method according to claim 1, wherein the step of adjusting the currently adopted scoring rule by the adjusting module when the distribution of the scoring result does not meet a preset condition includes:
when the coverage rate is smaller than the lower threshold value of the second value range, the adjustment module carries out forward adjustment on the currently adopted scoring rule; the forward direction adjustment is an adjustment operation to increase the coverage; when the coverage rate is larger than the upper threshold value of the second value range, the adjustment module carries out reverse adjustment on the currently adopted scoring rule; the reverse adjustment is an adjustment operation to reduce the coverage.
6. An information pushing method, characterized in that the method comprises:
the information push system sends a call request to the scoring system;
after receiving the call request, the scoring system scores the candidate target object based on the scoring rule adopted currently so as to obtain the scoring result of the candidate target object;
the scoring system determines the distribution condition of the scoring result and judges whether the distribution condition of the scoring result meets a preset condition, and the scoring system comprises: the judgment module constructs a histogram taking the scoring result as an abscissa and the number of candidate target objects as an ordinate; the judging module carries out normal distribution curve fitting according to the histogram to obtain a fitted normal distribution curve; the judging module calculates the probability that the scoring result is positioned in a first value range according to a probability calculation formula of the fitted normal distribution curve, takes the probability as the coverage rate of candidate target objects of which the scoring result is positioned in the first value range in all candidate target objects, and judges whether the coverage rate is positioned in a second value range or not;
under the condition that the distribution condition of the scoring results does not accord with the preset condition, the scoring system adjusts the scoring rule adopted currently until the distribution condition of the scoring results obtained based on the adjusted scoring rule accords with the preset condition;
Outputting the scoring result and/or the information of the target objects screened from the candidate target objects based on the scoring result by a scoring system under the condition that the distribution condition of the scoring result meets the preset condition;
and the information pushing system determines a target object according to the information output by the scoring system and pushes information aiming at the target object.
7. A scoring system, wherein the scoring system comprises:
the scoring module is used for scoring the candidate target objects based on the scoring rule adopted currently so as to obtain scoring results of the candidate target objects;
the judging module is used for determining the distribution condition of the scoring result and judging whether the distribution condition of the scoring result meets the preset condition or not, and comprises the following steps: the judgment module constructs a histogram taking the scoring result as an abscissa and the number of candidate target objects as an ordinate; the judging module carries out normal distribution curve fitting according to the histogram to obtain a fitted normal distribution curve; the judging module calculates the probability that the scoring result is positioned in a first value range according to a probability calculation formula of the fitted normal distribution curve, takes the probability as the coverage rate of candidate target objects of which the scoring result is positioned in the first value range in all candidate target objects, and judges whether the coverage rate is positioned in a second value range or not;
The grading system is used for grading the grading rule adopted currently under the condition that the distribution condition of the grading result does not accord with the preset condition, until the distribution condition of the grading result obtained based on the grading rule after the regulation accords with the preset condition;
and the output module is used for outputting the scoring result and/or the information of the target object screened from the candidate target objects based on the scoring result by the scoring system under the condition that the distribution condition of the scoring result meets the preset condition.
8. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs,
when executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1 to 6.
9. A computer readable medium on which a computer program is stored, characterized in that the program, when executed by a processor, implements the method according to any one of claims 1 to 6.
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