CN116029784A - Method, system, equipment and medium for intelligent arrangement of merchants in data platform - Google Patents
Method, system, equipment and medium for intelligent arrangement of merchants in data platform Download PDFInfo
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Abstract
The invention discloses a method, a system, equipment and a medium for intelligent arrangement of merchants in a data platform, wherein the method comprises the following steps: acquiring merchant data information and historical service information of a platform merchant; configuring a merchant ordering subparameter analysis algorithm and a merchant score statistical algorithm; calling a merchant sequencing subparameter analysis algorithm based on merchant data information and historical service information to obtain a first sequencing subparameter; calling a merchant score statistical algorithm based on the first sequencing subparameter to obtain a merchant sequencing score; based on the merchant sequencing score, adjusting the sequential arrangement of platform merchants in the platform; according to the method and the system for the distribution of the business, the comprehensive scores of the distributors can be accurately evaluated according to the scores, the distributors are sequentially ordered and displayed, the merchants with better comprehensiveness can be accurately reflected to be distributed based on the comprehensive scores, the method and the system are more suitable for a wider user group, the time for screening the merchants by most users is further reduced, and the steps and the complexity of the user operation data platform are reduced.
Description
Technical Field
The invention relates to the technical field of information sorting processing, in particular to the field of merchant information sorting processing of a data platform, and particularly relates to an intelligent arrangement method, system, equipment and medium for merchants in the data platform.
Background
At present, in most data platforms, the arrangement and pushing of merchant information can be performed according to a single user condition, for example, according to the distance information of the merchant, according to the historical purchase information of the user or according to the price information of the merchant, etc., and the arrangement and pushing mode has the following problems:
on one hand, the data base of the arrangement is single, each time of arrangement pushing is complicated and inflexible, the diversity of the data platform is continuously reduced, and meanwhile, the fatigue of the user is improved by repeatedly pushing the known data of the user;
on the other hand, under the arrangement pushing, for a part of user groups, for most users pursuing data variability, further merchant screening is needed to be conducted according to the needs of the users, so that the operation steps and operation time consumption of the users are improved, the use efficiency of the users is reduced, the use experience of the users is reduced, and the intelligence of a data platform is reduced;
On the other hand, the mode of carrying out merchant arrangement according to single information has mandatory property and differentiation property, is not beneficial to the operation of a data platform, and the merchant distribution in the data platform mostly has two-stage differentiation under a long period, so that double-flow loss of merchants and users in the data platform is finally caused;
in summary, the conventional arrangement method of merchants in the data platform is simple and complicated, has poor variability and flexibility, cannot truly play a role in recommendation, but rather reduces user experience to a certain extent, increases operation burden for users, is not suitable for all user groups, is unfavorable for long-term operation development of the data platform, is easy to cause differentiation of merchants, and reduces the enthusiasm of merchants.
Disclosure of Invention
The invention aims to solve the problems in the prior art that the business intelligent arrangement method, the system, the equipment and the medium in the data platform are simple and complex, the variability and the flexibility are poor, the recommendation effect cannot be really achieved, the experience of users can be reduced to a certain extent, the operation burden is increased for the users, the business intelligent arrangement method, the system, the equipment and the medium are not suitable for all user groups, the long-term operation development of the data platform is not facilitated, the differentiation of businesses is easy to be caused, and the aggressiveness of the businesses is reduced.
In order to solve the technical problems, the specific technical scheme of the invention is as follows:
in one aspect, the invention provides a method for intelligently arranging merchants in a data platform, which comprises the following steps:
initial configuration:
acquiring merchant data information and historical service information of a platform merchant; configuring a merchant ordering subparameter analysis algorithm and a merchant score statistical algorithm;
and (3) calculating a sequencing parameter:
calling the merchant sequencing subparameter analysis algorithm based on the merchant data information and the historical service information to obtain a first sequencing subparameter;
calculating merchant scores:
calling the merchant score statistical algorithm based on the first sequencing subparameter to obtain a merchant sequencing score;
sorting according to the division:
and adjusting the sequential arrangement of the platform merchants in the platform based on the merchant sequencing score.
As an improved solution, the merchant ordering subparameter analysis algorithm includes: callback rate algorithm, processing time length grade algorithm, bidding algorithm and distance grade algorithm;
the step of calling the merchant sequencing subparameter analysis algorithm based on the merchant data information and the historical service information to obtain a first sequencing subparameter, comprising:
calling the callback rate algorithm and the processing time length grade algorithm based on the historical service information to obtain callback rate parameters and processing time length grade parameters;
Invoking the bidding algorithm and the distance class algorithm based on the merchant data information to obtain bidding parameters and distance class parameters;
and enabling the callback rate parameter, the processing time length grade parameter, the bid parameter and the distance grade parameter to serve as the first sorting subparameter.
As an improved solution, the merchant score statistical algorithm includes:
setting a first weight proportion, a second weight proportion, a third weight proportion and a fourth weight proportion;
and carrying out weighted summation calculation processing on the callback rate parameter, the processing duration grade parameter, the bid parameter and the distance grade parameter based on the first weight proportion, the second weight proportion, the third weight proportion and the fourth weight proportion to obtain the merchant ordering score.
As an improved solution, the callback rate algorithm includes:
setting a first time period;
counting a first price inquiring clue quantity positioned in the first time period in the historical service information;
counting the callback amount of a first cable in the history service information, wherein the callback amount is positioned in the first time period;
calculating a first average cue amount based on the first time period and the first polling cue amount;
Calculating a first average callback amount based on the first time period and the first line cable callback amount;
and performing callback rate calculation based on the first price-inquiring cue amount, the first line callback amount, the first average cue amount and the first average callback amount to obtain callback rate parameters.
As an improved solution, the processing duration ranking algorithm includes:
setting a second time period and duration range class specification;
counting the total processing duration in the second time period in the historical service information;
calculating an average processing duration based on the second time period and the total processing duration;
and matching the processing duration grade parameter based on the average processing duration and the duration range grade specification.
As an improvement, the bidding algorithm includes:
acquiring merchant member consumption data, merchant annual consumption data and merchant advertisement consumption data in the merchant data information;
setting a plurality of weight parameters respectively corresponding to the merchant member consumption data, the merchant annual consumption data and the merchant advertisement consumption data;
and carrying out weighted summation calculation based on the merchant member consumption data, the merchant annual consumption data, the merchant advertisement consumption data and a plurality of weight parameters to obtain the bidding parameters.
As an improvement, the distance level algorithm includes:
acquiring merchant position information in the merchant data information;
confirming reference user position information;
calculating merchant spacing data based on the merchant location information and the reference user location information;
setting a pitch range grade specification;
the distance class parameter is matched based on the merchant spacing data and the spacing range class specification.
On the other hand, the invention also provides an intelligent arrangement system for merchants in the data platform, which comprises the following steps:
the system comprises an initial configuration module, a sorting parameter calculation module, a merchant score calculation module and a sorting module;
the initial configuration module is used for acquiring merchant data information and historical service information of a platform merchant, and configuring a merchant ordering sub-parameter analysis algorithm and a merchant score statistical algorithm;
the sorting parameter calculation module is used for calling the merchant sorting subparameter analysis algorithm according to the merchant data information and the historical service information to obtain a first sorting subparameter;
the merchant score calculation module is used for calling the merchant score statistical algorithm according to the first sequencing subparameter to obtain a merchant sequencing score;
And the sorting module is used for adjusting the sequential arrangement of the platform merchants in the platform according to the merchant sorting score.
In another aspect, the present invention further provides a computer readable storage medium, where a computer program is stored, where the computer program when executed by a processor implements the steps of the method for intelligent arrangement of merchants in the data platform.
In another aspect, the present invention further provides a computer device, where the computer device includes a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete communication with each other through the communication bus;
wherein:
a memory for storing a computer program;
and the processor is used for executing the steps of the intelligent arrangement method of the merchant in the data platform by running the program stored in the memory.
The technical scheme of the invention has the beneficial effects that:
1. according to the intelligent distribution method for merchants in the data platform, accurate assessment of the comprehensive scores of the distributors can be achieved according to the scores, and further the distributors are orderly sequenced and displayed, so that service enthusiasm of the distributors can be improved, meanwhile, merchants with good comprehensiveness can be accurately reflected to conduct distribution based on the comprehensive scores, the comprehensive performance is high, the method is more suitable for wider user groups, and further time for screening merchants by most users is reduced.
2. According to the intelligent distribution system for merchants in the data platform, through the mutual coordination of the initial configuration module, the sorting parameter calculation module, the merchant score calculation module and the sorting module, the accurate evaluation of the comprehensive scores of the distributors according to the scores is further realized, the distributors are further orderly sorted and displayed, the service enthusiasm of the distributors can be improved, meanwhile, merchants with better comprehensiveness can be accurately reflected to be distributed based on the comprehensive scores, the comprehensiveness is more suitable for a wider user group, the time for most users to screen the merchants is further reduced, the most accurate pushing result is calculated for the users through the data algorithm, so that the user experience is improved to the greatest extent, the user's requirements are met, the steps and the complexity of the user operation data platform are reduced, the convenience of the user in selecting the distributors is improved, the operation time consumption of the users is saved, the service efficiency of the data platform is improved, the merchants in the sorting of the data platform have the service enthusiasm, the enthusiasm and the service enthusiasm of the merchants are improved, the service enthusiasm of the merchants are facilitated to the users, the users are convenient to use, and the users have high fairness and high value, and the application to the data platform is suitable for different data platforms.
3. The computer readable storage medium can realize the coordination of the initial configuration module, the sorting parameter calculation module, the merchant score calculation module and the sorting module, so as to realize the intelligent arrangement method of merchants in the data platform.
4. The computer equipment can realize the storage and execution of the computer readable storage medium, thereby realizing the intelligent arrangement method of the merchants in the data platform.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for intelligent arrangement of merchants in a data platform according to embodiment 1 of the present invention;
FIG. 2 is a detailed flow chart of the intelligent configuration method of merchants in the data platform according to embodiment 1 of the present invention;
FIG. 3 is a schematic diagram of a merchant intelligent configuration system in a data platform according to embodiment 2 of the present invention;
FIG. 4 is a schematic diagram of a computer device according to embodiment 4 of the present invention;
the labels in the drawings are illustrated as follows:
1501. a processor; 1502. a communication interface; 1503. a memory; 1504. a communication bus.
Detailed Description
The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby making clear and defining the scope of the present invention.
In the description of the present invention, it should be noted that the described embodiments of the present invention are some, but not all embodiments of the present invention; all other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The terms first, second and the like in the description and in the claims and in the above-described figures, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments described herein may be capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, apparatus, article, or device that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or device.
Example 1
The embodiment provides a method for intelligent arrangement of merchants in a data platform, as shown in fig. 1 and 2, comprising the following steps:
s100, initial configuration specifically comprises the following steps:
s110, acquiring merchant data information and historical service information of a platform merchant; configuring a merchant ordering subparameter analysis algorithm and a merchant score statistical algorithm;
s200, calculating the sorting parameters, wherein the method specifically comprises the following steps:
s210, calling the merchant sequencing subparameter analysis algorithm based on the merchant data information and the historical service information to obtain a first sequencing subparameter;
s300, calculating the score of the merchant, which specifically comprises the following steps:
s310, calling the merchant score statistical algorithm based on the first sequencing subparameter to obtain a merchant sequencing score;
s400, sorting according to the partitions, specifically comprising:
s410, adjusting the sequential arrangement of the platform merchants in the platform based on the merchant sequencing score.
As one embodiment of the present invention, the merchant ordering sub-parameter analysis algorithm includes: callback rate algorithm, processing time length grade algorithm, bidding algorithm and distance grade algorithm; the step of calling the merchant sequencing subparameter analysis algorithm based on the merchant data information and the historical service information to obtain a first sequencing subparameter, comprising: in this embodiment, the historical service information includes, but is not limited to, in the historical time, communication time information between the merchant and the user, communication quantity information between the merchant and the user, price inquiring time information of the user, price inquiring quantity information of the user, and service process information when the merchant serves the user; merchant data information including, but not limited to, basic location information, qualification information, business scope information, consumption information in the platform, etc. of the merchant; calling the callback rate algorithm and the processing time length grade algorithm based on the historical service information to obtain callback rate parameters and processing time length grade parameters; invoking the bidding algorithm and the distance class algorithm based on the merchant data information to obtain bidding parameters and distance class parameters; the callback rate parameter, the processing time length grade parameter, the bid parameter and the distance grade parameter are used as the first sorting subparameter; specifically, the method is mainly applied to display sequencing of motorcycle/vehicle dealers, in the embodiment, bidding scores, distance scores, callback rate scores and processing time scores of the dealers are accurately calculated respectively through a self-grinding algorithm, and comprehensive scores of the dealers are accurately evaluated according to a plurality of scores, so that the dealers are orderly sequenced and displayed, service enthusiasm of the dealers can be improved, meanwhile, time of screening merchants by users is reduced through accurate sequencing calculation, and the most accurate pushing result is displayed for the users through data algorithm calculation, so that user experience is improved to the greatest extent, requirements of the users are met, complexity of operating a data platform by the users is reduced, convenience of selecting the dealers by the users is improved, service efficiency of the data platform is improved, user viscosity, enthusiasm and service viscosity of the data platform are improved, and convenience is brought to the users and the merchants are standardized;
As an embodiment of the present invention, the callback rate algorithm includes: setting a first time period; counting a first price inquiring clue quantity positioned in the first time period in the historical service information; counting the callback amount of a first cable in the history service information, wherein the callback amount is positioned in the first time period; calculating a first average cue amount based on the first time period and the first polling cue amount; calculating a first average callback amount based on the first time period and the first line cable callback amount; performing callback rate calculation based on the first price-inquiring clue amount, the first line callback amount, the first average clue amount and the first average callback amount to obtain callback rate parameters; in practical application, the callback rate algorithm has the following embodiments, for example: the preset user can inquire the dealer vehicle through the APP to generate an inquiry clue, and the dealer can dial a user phone to conduct business connection; therefore, the callback rate score is obtained by counting the thread amount (i.e. the first line callback amount) of the dealer callback and the generated thread amount (i.e. the first price-inquiring thread amount) within 30 days (i.e. the first time period), and calculating the thread amount (i.e. the first line callback amount) of the dealer callback/the generated thread amount (i.e. the first price-inquiring thread amount); in the algorithm, in order to make the score smoother, a final total callback rate score (i.e. callback rate parameter) = (first line callback amount + average callback amount)/(first price-polling cue amount + average cue amount), wherein the average callback amount is the cue amount of callback of a dealer per 30 days; the average cue amount is the first cue amount of price inquiry per 30 days; correspondingly, by adopting the algorithm, the more accurate merchant callback rate can be obtained;
As an embodiment of the present invention, the processing duration ranking algorithm includes: setting a second time period and duration range class specification; counting the total processing duration in the second time period in the historical service information; calculating an average processing duration based on the second time period and the total processing duration; matching the processing duration level parameter based on the average processing duration and the duration range level specification; this process duration scale is in practical use, and by way of example, there are the following embodiments: setting the time between the inquiry of the dealer vehicle by the user through the APP and the callback of the dealer to the user as the processing time length, and adding the processing time length by counting data of 30 days (namely a second time period) to obtain the total processing time length; then, calculating to obtain average treatment duration according to the total treatment duration/30 days; the time length range grade specification divides the time length into N grades, and the score of each grade is different, in the embodiment, the average processing time length is set as x, and the score is 10 minutes when x is 0 minutes and less than or equal to 10 minutes; 10 minutes < x.ltoreq.20 minutes, score 6; 20 minutes < x.ltoreq.30 minutes, score 4; 30 minutes < x.ltoreq.40 minutes, score 2; in this embodiment, the score may be set according to specific requirements, and the foregoing score is merely exemplary, so that the service of the merchant may be evaluated more accurately and in a data manner according to the score of the processing duration of the merchant;
As an embodiment of the present invention, the bidding algorithm includes: acquiring merchant member consumption data, merchant annual consumption data and merchant advertisement consumption data in the merchant data information; setting a plurality of weight parameters respectively corresponding to the merchant member consumption data, the merchant annual consumption data and the merchant advertisement consumption data; performing weighted summation calculation based on the merchant member consumption data, the merchant annual consumption data, the merchant advertisement consumption data and a plurality of weight parameters to obtain the bidding parameters; this bidding algorithm, when actually applied, has the following implementation as an example: acquiring payment amount data of a dealer on an APP platform, wherein the payment amount data comprises member grade fees (namely merchant member consumption data), clue annual package fees (namely merchant annual consumption data), dealer advertising fees (namely merchant annual consumption data) and the like; firstly, calculating average cost of various types of cost according to weeks, and further converting the weekly expense amount respectively corresponding to the membership grade cost, the clue annual package cost and the distributor advertising cost to obtain membership weekly expense, annual package weekly expense and advertising cost Zhou Xiaofei; corresponding weights are respectively set for the membership grade cost, the lead annual package cost and the dealer advertising cost, and in the embodiment, the weight of the membership grade cost is 1%, the weight of the lead annual package cost is 2%, and the weight of the dealer advertising cost is 3%; therefore, finally, the bidding parameter obtained by the weighted summation calculation=1% + consumption of the member week+2% + consumption of the annual package Zhou Xiaofei +consumption of the advertising week+3%, and in this embodiment, each weight may be set according to the actual requirement, and the foregoing weight is only one embodiment; the investment degree of the merchant to the platform can be calculated through the bidding algorithm, so that the service investment of the merchant can be calculated more accurately and in a data mode, and the service investment degree and the service capability of the merchant can be estimated more accurately;
As an embodiment of the present invention, the distance ranking algorithm includes: acquiring merchant position information in the merchant data information; confirming reference user position information; calculating merchant spacing data based on the merchant location information and the reference user location information; setting a pitch range grade specification; matching the distance class parameter based on the merchant spacing data and the spacing range class specification; this distance level algorithm is actually applied, and as an example, there are the following embodiments: the method estimates the score of a merchant according to the distance between a user and a dealer, and calculates the distance (merchant distance data) between the user position (namely, reference user position information) and the merchant position (merchant position information) according to the position of the user (namely, reference user position information) which needs merchant sorting pushing in a platform; the subsequent interval range grade specification divides the interval into N grades, the scores of each grade are different, and the matching of the distance grade parameters of the commercial tenant can be carried out according to the interval range grade specification; in the present embodiment, the pitch range class specification includes: setting the score corresponding to merchant spacing data <10 km as 1 score; setting the score corresponding to merchant spacing data of less than or equal to 10 and less than 20 km to be 0.8 score; setting the score corresponding to the merchant spacing data of less than or equal to 20 and less than 30 kilometers to be 0.5 score; setting the score corresponding to 30-40 km of merchant spacing data as 0.3 score; setting the score corresponding to merchant spacing data of less than or equal to 40 and less than 50 km to be 0.2 score; setting the score corresponding to the merchant spacing data of which the score is not less than 50 to be 0.1 score; in this embodiment, the score may be set according to specific requirements, and the foregoing score is merely taken as an example, so that, according to the distance score of the merchant, convenience between the merchant and the user can be evaluated more accurately and in a data manner, so that the merchant with service convenience is better screened for the user, and user experience is improved;
As one embodiment of the present invention, the merchant score statistical algorithm includes: setting a first weight proportion, a second weight proportion, a third weight proportion and a fourth weight proportion; performing weighted summation calculation processing on the callback rate parameter, the processing duration grade parameter, the bid parameter and the distance grade parameter based on the first weight proportion, the second weight proportion, the third weight proportion and the fourth weight proportion to obtain the merchant ordering score; correspondingly, in practical application, the merchant score statistical algorithm has the following embodiments, by way of example: obtaining a score of a final dealer according to the callback rate parameter, the processing duration grade parameter, the bid parameter and the distance grade parameter according to a certain proportion, wherein the score is equal to a first weight proportion of the bid parameter, a second weight proportion of the distance grade parameter, a third weight proportion of the distance grade parameter, and a fourth weight proportion of the processing duration grade parameter; finally, the method can order the dealers more reasonably, can further improve the service awareness of the dealers, can preferentially recommend the dealers with good service and moderate distance to the users, and improves the user browsing consultation experience.
Example 2
The present embodiment provides an intelligent configuration system for merchants in a data platform, as shown in fig. 3, based on the same inventive concept as the intelligent configuration method for merchants in a data platform described in embodiment 1, including: the system comprises an initial configuration module, a sorting parameter calculation module, a merchant score calculation module and a sorting module;
the initial configuration module is used for acquiring merchant data information and historical service information of a platform merchant, and configuring a merchant ordering sub-parameter analysis algorithm and a merchant score statistical algorithm;
the sorting parameter calculation module is used for calling the merchant sorting subparameter analysis algorithm according to the merchant data information and the historical service information to obtain a first sorting subparameter;
as one embodiment of the present invention, the merchant ordering sub-parameter analysis algorithm includes: callback rate algorithm, processing time length grade algorithm, bidding algorithm and distance grade algorithm;
as an embodiment of the present invention, the ranking parameter calculating module invokes the merchant ranking sub-parameter analysis algorithm based on the merchant data information and the historical service information to obtain a first ranking sub-parameter, including: the ordering parameter calculation module calls the callback rate algorithm and the processing time length grade algorithm based on the historical service information to obtain callback rate parameters and processing time length grade parameters; the ordering parameter calculation module calls the bidding algorithm and the distance grade algorithm based on the merchant data information to obtain bidding parameters and distance grade parameters; the sorting parameter calculation module enables the callback rate parameter, the processing time length grade parameter, the bid parameter and the distance grade parameter to serve as the first sorting subparameter.
As an embodiment of the present invention, the callback rate algorithm includes: the sorting parameter calculation module sets a first time period; the sorting parameter calculation module counts first price-inquiring clues positioned in the first time period in the historical service information; the ordering parameter calculation module counts the callback amount of the first cable in the first time period in the historical service information; a ranking parameter calculating module calculates a first average cue amount based on the first time period and the first polling cue amount; the sorting parameter calculation module calculates a first average callback amount based on the first time period and the first cable callback amount; and the sorting parameter calculation module calculates callback rate based on the first price-inquiring cue quantity, the first line callback quantity, the first average cue quantity and the first average callback quantity, and obtains the callback rate parameter.
As an embodiment of the present invention, the processing duration ranking algorithm includes: the sorting parameter calculation module sets a second time period and duration range grade specification; the ordering parameter calculation module counts the total processing time length in the second time period in the history service information; the sorting parameter calculation module calculates average processing duration based on the second time period and the total processing duration; the ranking parameter calculating module matches the processing duration grade parameter based on the average processing duration and the duration range grade specification.
As an embodiment of the present invention, the bidding algorithm includes: the ordering parameter calculation module acquires merchant member consumption data, merchant annual consumption data and merchant advertisement consumption data in the merchant data information; the sorting parameter calculation module sets a plurality of weight parameters respectively corresponding to the merchant member consumption data, the merchant annual consumption data and the merchant advertisement consumption data; and the ordering parameter calculation module performs weighted summation calculation based on the merchant member consumption data, the merchant annual consumption data, the merchant advertisement consumption data and a plurality of weight parameters to obtain the bidding parameters.
As an embodiment of the present invention, the distance ranking algorithm includes: the sorting parameter calculation module acquires merchant position information in the merchant data information; the sorting parameter calculation module confirms the reference user position information; the sorting parameter calculation module calculates merchant spacing data based on the merchant position information and the reference user position information; the sorting parameter calculation module sets a spacing range grade specification; the ranking parameter calculation module matches the distance rank parameter based on the merchant spacing data and the spacing range rank specification.
The merchant score calculation module is used for calling the merchant score statistical algorithm according to the first sequencing subparameter to obtain a merchant sequencing score;
as one embodiment of the present invention, the merchant score statistical algorithm includes: the merchant score calculation module sets a first weight proportion, a second weight proportion, a third weight proportion and a fourth weight proportion; and the merchant score calculation module performs weighted summation calculation processing on the callback rate parameter, the processing duration grade parameter, the bid parameter and the distance grade parameter based on the first weight proportion, the second weight proportion, the third weight proportion and the fourth weight proportion to obtain the merchant sorting score.
And the sorting module is used for adjusting the sequential arrangement of the platform merchants in the platform according to the merchant sorting score.
Example 3
The present embodiment provides a computer-readable storage medium including:
the storage medium is used for storing computer software instructions for implementing the intelligent configuration method of the commercial tenant in the data platform described in the above embodiment 1, and the computer software instructions include a program for executing the above program set for the intelligent configuration method of the commercial tenant in the data platform; specifically, the executable program may be built in the intelligent configuration system of the merchant in the data platform described in embodiment 2, so that the intelligent configuration system of the merchant in the data platform may implement the intelligent configuration method of the merchant in the data platform described in embodiment 1 by executing the built-in executable program.
Further, the computer readable storage medium provided in the present embodiment may be any combination of one or more readable storage media, where the readable storage media includes an electric, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof.
Example 4
The present embodiment provides an electronic device, as shown in fig. 4, which may include: the device comprises a processor 1501, a communication interface 1502, a memory 1503 and a communication bus 1504, wherein the processor 1501, the communication interface 1502 and the memory 1503 are in communication with each other through the communication bus 1504.
A memory 1503 for storing a computer program;
the processor 1501 is configured to execute the computer program stored in the memory 1503 to implement the steps of the intelligent configuration method for merchants in the data platform described in the above embodiment 1.
As an embodiment of the present invention, the communication bus mentioned by the above-mentioned terminal may be a peripheral component interconnect standard (Peripheral Component Interconnect, abbreviated as PCI) bus or an extended industry standard architecture (Extended Industry Standard Architecture, abbreviated as EISA) bus, or the like. The communication bus may be classified as an address bus, a data bus, a control bus, or the like. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus.
As an embodiment of the present invention, a communication interface is used for communication between the terminal and other devices.
As an embodiment of the present invention, the memory may include a random access memory (Random Access Memory, abbreviated as RAM) or may include a non-volatile memory (non-volatile memory), such as at least one disk memory. Optionally, the memory may also be at least one memory device located remotely from the aforementioned processor.
As an embodiment of the present invention, the above-mentioned processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, abbreviated as CPU), a network processor (Network Processor, abbreviated as NP), and the like; but also digital signal processors (Digital Signal Processing, DSP for short), application specific integrated circuits (Application Specific Integrated Circuit, ASIC for short), field-programmable gate arrays (Field-Programmable Gate Array, FPGA for short) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.
Compared with the prior art, the method, the system, the equipment and the medium for intelligent distribution of merchants in the data platform can accurately evaluate the comprehensive scores of the distributors according to the scores, further orderly sort and display the distributors, so that the service enthusiasm of the distributors can be improved, meanwhile, the merchants with better comprehensiveness can be accurately reflected to carry out distribution based on the comprehensive scores, the comprehensiveness is more suitable for wider user groups, and further, the time for screening the merchants by most users is reduced.
It should be understood that, in the various embodiments herein, the sequence number of each process described above does not mean the sequence of execution, and the execution sequence of each process should be determined by its functions and internal logic, and should not constitute any limitation on the implementation process of the embodiments herein.
It should also be understood that in embodiments herein, the term "and/or" is merely one relationship that describes an associated object, meaning that three relationships may exist. For example, a and/or B may represent: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided herein, it should be understood that the disclosed systems, devices, and methods may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. In addition, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices, or elements, or may be an electrical, mechanical, or other form of connection.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the elements may be selected according to actual needs to achieve the objectives of the embodiments herein.
In addition, each functional unit in the embodiments herein may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solutions herein are essentially or portions contributing to the prior art, or all or portions of the technical solutions may be embodied in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments herein. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing description is only illustrative of the present invention and is not intended to limit the scope of the invention, and all equivalent structures or equivalent processes or direct or indirect application in other related technical fields are included in the scope of the present invention.
Claims (10)
1. The intelligent arrangement method for the merchants in the data platform is characterized by comprising the following steps of:
initial configuration:
acquiring merchant data information and historical service information of a platform merchant; configuring a merchant ordering subparameter analysis algorithm and a merchant score statistical algorithm;
and (3) calculating a sequencing parameter:
calling the merchant sequencing subparameter analysis algorithm based on the merchant data information and the historical service information to obtain a first sequencing subparameter;
calculating merchant scores:
calling the merchant score statistical algorithm based on the first sequencing subparameter to obtain a merchant sequencing score;
sorting according to the division:
and adjusting the sequential arrangement of the platform merchants in the platform based on the merchant sequencing score.
2. The intelligent arrangement method for merchants in a data platform according to claim 1, wherein:
the merchant ordering subparameter analysis algorithm comprises the following steps: callback rate algorithm, processing time length grade algorithm, bidding algorithm and distance grade algorithm;
The step of calling the merchant sequencing subparameter analysis algorithm based on the merchant data information and the historical service information to obtain a first sequencing subparameter, comprising:
calling the callback rate algorithm and the processing time length grade algorithm based on the historical service information to obtain callback rate parameters and processing time length grade parameters;
invoking the bidding algorithm and the distance class algorithm based on the merchant data information to obtain bidding parameters and distance class parameters;
and enabling the callback rate parameter, the processing time length grade parameter, the bid parameter and the distance grade parameter to serve as the first sorting subparameter.
3. The intelligent arrangement method for merchants in a data platform according to claim 2, wherein:
the merchant score statistical algorithm comprises the following steps:
setting a first weight proportion, a second weight proportion, a third weight proportion and a fourth weight proportion;
and carrying out weighted summation calculation processing on the callback rate parameter, the processing duration grade parameter, the bid parameter and the distance grade parameter based on the first weight proportion, the second weight proportion, the third weight proportion and the fourth weight proportion to obtain the merchant ordering score.
4. The intelligent arrangement method for merchants in a data platform according to claim 2, wherein:
the callback rate algorithm comprises the following steps:
setting a first time period;
counting a first price inquiring clue quantity positioned in the first time period in the historical service information;
counting the callback amount of a first cable in the history service information, wherein the callback amount is positioned in the first time period;
calculating a first average cue amount based on the first time period and the first polling cue amount;
calculating a first average callback amount based on the first time period and the first line cable callback amount;
and performing callback rate calculation based on the first price-inquiring cue amount, the first line callback amount, the first average cue amount and the first average callback amount to obtain callback rate parameters.
5. The intelligent arrangement method for merchants in a data platform according to claim 2, wherein:
the processing duration level algorithm comprises the following steps:
setting a second time period and duration range class specification;
counting the total processing duration in the second time period in the historical service information;
calculating an average processing duration based on the second time period and the total processing duration;
And matching the processing duration grade parameter based on the average processing duration and the duration range grade specification.
6. The intelligent arrangement method for merchants in a data platform according to claim 2, wherein:
the bidding algorithm comprises:
acquiring merchant member consumption data, merchant annual consumption data and merchant advertisement consumption data in the merchant data information;
setting a plurality of weight parameters respectively corresponding to the merchant member consumption data, the merchant annual consumption data and the merchant advertisement consumption data;
and carrying out weighted summation calculation based on the merchant member consumption data, the merchant annual consumption data, the merchant advertisement consumption data and a plurality of weight parameters to obtain the bidding parameters.
7. The intelligent arrangement method for merchants in a data platform according to claim 2, wherein:
the distance level algorithm comprises the following steps:
acquiring merchant position information in the merchant data information;
confirming reference user position information;
calculating merchant spacing data based on the merchant location information and the reference user location information;
setting a pitch range grade specification;
the distance class parameter is matched based on the merchant spacing data and the spacing range class specification.
8. The intelligent arrangement system for merchants in a data platform is characterized by comprising the following components: the system comprises an initial configuration module, a sorting parameter calculation module, a merchant score calculation module and a sorting module;
the initial configuration module is used for acquiring merchant data information and historical service information of a platform merchant, and configuring a merchant ordering sub-parameter analysis algorithm and a merchant score statistical algorithm;
the sorting parameter calculation module is used for calling the merchant sorting subparameter analysis algorithm according to the merchant data information and the historical service information to obtain a first sorting subparameter;
the merchant score calculation module is used for calling the merchant score statistical algorithm according to the first sequencing subparameter to obtain a merchant sequencing score;
and the sorting module is used for adjusting the sequential arrangement of the platform merchants in the platform according to the merchant sorting score.
9. A computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and when the computer program is executed by a processor, the steps of the method for intelligently arranging merchants in the data platform according to any one of claims 1 to 7 are implemented.
10. The computer equipment is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus;
Wherein:
a memory for storing a computer program;
a processor for executing the steps of the method for intelligent distribution of merchants in a data platform according to any one of claims 1 to 7 by running a program stored on a memory.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116228077A (en) * | 2023-05-06 | 2023-06-06 | 广州一链通互联网科技有限公司 | Intelligent ordering method and system for container logistics products based on Internet |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116228077A (en) * | 2023-05-06 | 2023-06-06 | 广州一链通互联网科技有限公司 | Intelligent ordering method and system for container logistics products based on Internet |
| CN116228077B (en) * | 2023-05-06 | 2023-08-15 | 广州一链通互联网科技有限公司 | Intelligent ordering method and system for container logistics products based on Internet |
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