CN108446910A - A kind of air control decision system, method and equipment - Google Patents
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Abstract
This specification embodiment discloses a kind of air control decision system, method and equipment.The method includes：Trade company's target under different scenes and relevant feature are acquired, is mapped feature and trade company target by optimization algorithm, obtains mapping relations for client's progress air control decision to trade company.
Description
Technical Field
The present disclosure relates to the field of computer software technologies, and in particular, to a wind control decision system, a method, and a device.
Background
With the rapid development of computer and internet technologies, many services can be performed on the internet, such as a lease service, an online purchase service, a life payment service, and the like based on an online payment platform or an online credit platform. In order to improve the transaction security in the business, the platform often makes a wind-controlled decision on the merchant and its customers who are to perform the transaction.
In the prior art, if a merchant is checked by a platform in advance, the security is relatively high, and in this case, the wind control decision of a customer of the merchant is mainly considered; specifically, for the strategy of the wind control decision, a specific strategy version is developed manually according to specific classification in advance when strategy iteration is performed, and the strategy is generally divided into several general strategies such as large-amount, medium-amount and small-amount according to commodity values due to limitation of industrial diversity and workload of strategy developers.
Based on the prior art, a better applicability wind control decision scheme is needed.
Disclosure of Invention
The embodiment of the specification provides a wind control decision system, a method and equipment, which are used for solving the following technical problems: a more adaptable wind control decision scheme is needed.
In order to solve the above technical problem, the embodiments of the present specification are implemented as follows:
an embodiment of this specification provides a wind control decision system, including:
the target module is used for acquiring merchant targets in various scenes to obtain a merchant target set;
the characteristic module is used for acquiring various characteristics related to the merchant target to obtain a characteristic set;
and the computing module is used for establishing a mapping relation between one or more characteristics and a specified merchant target by utilizing an optimization algorithm according to the merchant target set and the characteristic set and is used for carrying out a wind control decision on the merchant customer.
An embodiment of the present specification provides a wind control decision method, including:
acquiring merchant targets under various scenes to obtain a merchant target set;
collecting various characteristics related to a merchant target to obtain a characteristic set;
and establishing a mapping relation between one or more characteristics and the specified merchant target by utilizing an optimization algorithm according to the merchant target set and the characteristic set, and carrying out a wind control decision on the merchant customer.
An embodiment of this specification provides a wind control decision device, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring merchant targets under various scenes to obtain a merchant target set;
collecting various characteristics related to a merchant target to obtain a characteristic set;
and establishing a mapping relation between one or more characteristics and the specified merchant target by utilizing an optimization algorithm according to the merchant target set and the characteristic set, and carrying out a wind control decision on the merchant customer.
The embodiment of the specification adopts at least one technical scheme which can achieve the following beneficial effects: the characteristic mapping relation suitable for the target can be intelligently obtained according to the personalized target of the merchant and used as a strategy basis, and further the client of the merchant can be effectively subjected to wind control decision, so that the application scene is wide, and the technical problems can be partially or completely solved.
Drawings
In order to more clearly illustrate the embodiments of the present specification or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present specification, and for those skilled in the art, other drawings can be obtained according to the drawings without any creative effort.
Fig. 1 is a schematic diagram of an overall architecture involved in a practical application scenario of the solution of the present specification;
fig. 2 is a schematic structural diagram of a wind control decision system provided in an embodiment of the present disclosure;
fig. 3 is a schematic diagram of an operating principle of a wind control decision system provided in an embodiment of the present disclosure;
fig. 4 is a schematic flow chart of a wind control decision method provided in an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of a wind control decision device provided in an embodiment of the present disclosure.
Detailed Description
The embodiment of the specification provides a wind control decision system, a method and equipment.
In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any inventive step based on the embodiments of the present disclosure, shall fall within the scope of protection of the present application.
The background is further described with respect to a deposit rental free service as an example. Currently, many merchants provide credit-based deposit-free rental services, and allow customers to rent items without paying a deposit, for example, renting mobile phones, renting unmanned planes, renting umbrellas, and the like, as long as the customers' credit reaches a certain degree. The platform for evaluating credit, that is, the platform for making a pneumatic decision, needs to consider personalized targets of different merchants to better serve the merchants, where the personalized targets may include different targets between different industries, or different targets between different merchants in the same industry, and specifically includes different targets when a merchant operates a service in a single scene (for example, only renting a mobile phone) and operates a service in a mixed scene (for example, renting an unmanned aerial vehicle or an umbrella). The targets are such as: customer overdue rate, customer successful transaction rate, deviation objective, etc.
A major pain point of the wind control decision platform in providing the above decision service for the merchant lies in the lack of a whole set of intelligent policy implementation schemes, which are mainly expressed in that: the industry classification is complex, and the scene modes are various; the data sources are few and the richness is insufficient; the risk types are complex and various; and in the face of risk conditions, the wind control iteration efficiency is low, and the like.
The scheme of the specification specifically aims to solve the problems of complexity, diversity, low efficiency and incapability of timely controlling risks faced by business related business wind control of merchants, an effective system is provided for the merchants to efficiently meet the intelligent risk control requirement, meanwhile, due to the expandability of the whole system, an external mechanism can select to place an accessed data source into the system, so that the overall wind control strategy is further optimized, a new system is expandable, easy to configure and capable of effectively and quickly deriving, and the wind control strategy is a huge change.
Fig. 1 is a schematic diagram of an overall architecture related to the solution of the present specification in a practical application scenario. The whole framework mainly comprises three parts: each client, a wind control decision server and each business client. The wind control decision server provides wind control decision service for the customer and/or the merchant, and the wind control decision result directly influences whether the current transaction between the customer and the merchant can be continued. And the wind control decision server establishes a mapping relation between various characteristics and the merchant target for wind control decision. The wind control decision server is provided by, for example, a third party payment platform, a bank, or an e-commerce platform.
It should be noted that the architecture in fig. 1 is exemplary. The subject served by the wind control decision server is not limited to the merchant and the customer thereof, for example, in a social business, the subject can serve both parties in the social business; and so on.
Based on the above general description and the overall architecture, the following describes the aspects of the present specification in detail.
Fig. 2 is a schematic structural diagram of a wind control decision system according to an embodiment of the present disclosure. The system may be mounted on a device serving as a server or a terminal having sufficient capability.
The system in fig. 2 comprises: the target module 201, the feature module 202 and the calculation module 203, the numbers of the modules are not limited to the present application, and for brevity, the numbers are omitted when the modules are explained later.
The target module is used for acquiring merchant targets in various scenes to obtain a merchant target set;
the characteristic module is used for acquiring various characteristics related to the merchant target to obtain a characteristic set;
and the computing module is used for establishing a mapping relation between one or more characteristics and a specified merchant target by utilizing an optimization algorithm according to the merchant target set and the characteristic set and is used for carrying out a wind control decision on the merchant customer.
In the embodiments of the present description, there are various scene division manners, and the scene division manners may be selected according to actual needs. Two ways of division are listed as examples.
First, the scenes are divided according to business contents and industries of merchants. For example, as described above, if a merchant operates only one content (for example, only rents a mobile phone), it can be regarded as a single scene, and if a user operates multiple contents (for example, rents an unmanned aerial vehicle and an umbrella) at the same time, it can be regarded as a mixed scene formed by multiple corresponding single scenes.
And secondly, dividing scenes according to the scale and the region of the commercial tenant. For example, according to historical turnover or popularity values, all merchants are classified in a ladder manner, and each classified grade is regarded as a scene.
Different single or hybrid scenarios, and different merchants may correspond to different merchant objectives.
In the embodiments of the present specification, two of the merchant objectives listed above are further explained.
The customer overdue rate is one of important targets concerned by the merchant in the rental business, and under an ideal condition, the merchant naturally expects that the customer overdue rate is as low as possible, but the overdue rate is difficult to be as low as 0 in practical application, so the merchant has certain tolerance, for example, if the psychological expectation of the merchant is that the customer overdue rate is not higher than 3%, the psychological expectation is the merchant target of the merchant.
Further consider the customer successful transaction rate. If the customer requirements are too high for a simple pursuit of a lower customer overdue rate, resulting in many potential customers being rejected after the pneumatic decision, and thus possibly making the customer successful transaction rate too low, it is also a nuisance for the merchant. Therefore, customer successful transaction rate is often also one of the important objectives of merchant concern.
Of course, besides the overdue rate of the customer and the successful transaction rate of the customer, other indexes can be used for representing the merchant target, such as the monthly income of the shop, the idle rate of the rental goods and the like.
In order to facilitate acquisition of the merchant target, the target module may be docked with each merchant terminal, and further, the merchant target may be directly acquired from the merchant in real time or offline, the merchant may set relevant information and policies at the merchant terminal so as to facilitate acquisition by the target module, and of course, the merchant may also actively feed the merchant target back to the target module, thereby further saving acquisition time; besides, the method can acquire the target by adopting modes of model prediction, data mining, experience-based manual configuration and the like without depending on the merchant, and the acquired target is regarded as the merchant target. The former mode has the advantages of high reliability and rich data; the latter approach is well integrated, representative, and scalable.
In embodiments of the present description, the features associated with the merchant objective may directly or indirectly affect whether the merchant objective can be achieved.
Such as including one or more of customer characteristics, transaction characteristics, merchant characteristics. Customer characteristics such as age, occupation, historical transaction data, merchant ratings, credit data, etc. of the customer; the transaction characteristics are, for example, the transaction amount, the transaction time, the transaction frequency, and the like of the current transaction; the merchant characteristics are the popularity value, the monthly average transaction number, the return rate, the new product delivery rate and the like of the merchant.
In the embodiments of the present specification, the optimization algorithm may be a neural network algorithm, a linear programming algorithm, a bayesian optimization algorithm, or the like.
By utilizing an optimization algorithm, the merchant target can be mapped to one or more characteristics, so that when the wind control decision is made, the influence degree of the current customer on the merchant target can be presumed according to the obtained mapping relation and the corresponding characteristic data of the current customer, and further, the proper wind control decision can be realized. The optimization goal in mapping is, for example, to minimize the merchant target error, or may also minimize the merchant target error on the premise that a certain condition (a calculation amount condition, a feature quantity condition, or the like) is satisfied, and so on.
Through the system of fig. 2, a feature mapping relationship adapted to a merchant can be intelligently obtained according to the personalized target of the merchant, and is used as a policy basis, so that a client of the merchant can be effectively subjected to a wind control decision, the applicable scenarios are wide, and the technical problem can be partially or completely solved, so that the technical problem can be partially or completely solved.
Based on the system of fig. 2, the present specification also provides some specific embodiments of the system, and further embodiments, which are described below.
The embodiment of the present specification provides a schematic diagram of an operation principle of the system in fig. 2 in a practical application scenario, as shown in fig. 3.
In fig. 3, the block indicated by "Y target" corresponds to the target block described above, the block indicated by "X feature" serves as the feature block described above, and the block indicated by "optimization algorithm" serves as the calculation block described above.
The uppermost box represents the merchant side, and it can be seen that each merchant has its own policy, which may reflect different scenes of the merchant and the merchant target, for example, merchant a has N scenes of 1-N, and these information may be fed back to the target module in real time or offline.
The target module collects the merchant target in a merchant feedback mode, and can collect the merchant target in modes of model prediction, rule deletion, manual check and the like, and processes the collected merchant target such as cleaning, integration and the like, so that a merchant target set is obtained.
The characteristic module acquires customer characteristics, transaction characteristics, merchant characteristics and the like in real time or offline to obtain a characteristic set.
The collected merchant goals and characteristics may be passed to a calculation module for calculation based on an optimization algorithm. The block of the "optimization algorithm" shows a plurality of models corresponding to the optimization algorithm, each model may have its applicable scenario, the optimization process may include training and adjusting the corresponding model, and the trained model may reflect the mapping relationship.
When the current customer is decided, the wind control decision is realized by acquiring corresponding characteristic data and substituting the characteristic data into the model for calculation, and a decision result is obtained and returned to the merchant.
In the embodiment of the present specification, for a given business target, there are usually many features related to the business target, and if all the features are considered when establishing the mapping relationship, the processing efficiency may be affected, and the subsequent wind control decision efficiency may also be affected. Therefore, a part of relatively important features can be specified in advance based on manual experience to be used for establishing the mapping relation, and more intelligently, a part of features can be mined in a non-manual mode such as feature engineering and the like to be used for establishing the mapping relation.
In embodiments of the present specification, it has been mentioned above that the optimization goal at the time of mapping may be to minimize the merchant goal error. In this case, the calculating module establishes a mapping relationship between one or more features and the specified merchant target by using an optimization algorithm according to the merchant target set and the feature set, and specifically may include:
the computing module determines one or more features in the set of features and obtains a merchant target specified in the set of merchant targets; establishing a mapping relation between the one or more characteristics and the merchant target by optimizing with the minimized merchant target error as an optimization target by utilizing an optimization algorithm; and calculating the estimated data according to the one or more characteristics in the optimization process.
For example, when the merchant target is set for a single scene, the merchant target error minimum can be expressed as a mathematical formula: min (Y _ i-function _ i (X _ j)); y _ i and X _ j respectively represent variables corresponding to the mapped merchant targets and variables corresponding to the features, function _ i (X _ j) represents estimated data calculated according to the features, and specific contents of Y _ i, X _ j, and function _ i may be different for different scenes.
In practical applications, merchants may also operate in a mixed manner, in which case, a single merchant target may be set for a mixed scenario including at least two sub-scenarios, each sub-scenario has a corresponding merchant sub-target, and the merchant sub-targets are also included in the merchant target set. The calculating module establishes a mapping relationship between one or more features and a specified merchant target by using an optimization algorithm according to the merchant target set and the feature set, and specifically may include:
the calculation module determines merchant sub-targets corresponding to sub-scenes contained in a mixed scene of the designated merchant target and the weight of each sub-scene according to the merchant target set; and establishing a mapping relation between one or more characteristics and a specified merchant target by utilizing an optimization algorithm according to the characteristic set, the determined merchant sub-targets and the weight.
Referring to the above example, in the mixed scenario, the minimum merchant target error may be expressed as follows by a mathematical formula: min (Y _ a-function _ a (Σ (Y _ i-function _ i (X _ j))); wherein, Y _ a represents a variable corresponding to a deviation target of a merchant target population in a mixed scene, Y _ i represents a variable corresponding to a merchant sub-target of the merchant target, and function _ a (Σ (Y _ i-function _ i (X _ j))) represents an estimated deviation calculated according to errors of each sub-target.
For ease of understanding, the description is made in conjunction with an example. Assuming that the merchant is very interested in the overdue rate of the customer, for example, Y _ i may be set as a variable indicating whether the customer is overdue for 7 days or more, X _ j may be set as a variable indicating the number of past business applications of the customer for 1 day, and so on.
Assuming that the merchant conducts mixed operation, the method respectively comprises the following steps: business A (renting unmanned aerial vehicle) and business B (renting umbrella); respectively corresponding to a sub-scene, and the service income proportion is respectively 0.3 and 0.7 as the scene weight. Y _ i and X _ j under the sub-scene corresponding to the A service are respectively marked as Ya _ i and Xa _ j, and Y _ i and X _ j under the sub-scene corresponding to the B service are respectively marked as Yb _ i and Xb _ j. For example, Ya _ i is a variable indicating whether or not 7 days or more have elapsed, Yb _ i is a variable indicating whether or not 10 days or more have elapsed, Xa _ j is a variable indicating the number of applications for the past 1 day, and Xb _ j is a variable indicating the number of applications for the past 30 days. The merchant target error minimum is then expressed as:
min(Y_a-(0.3*(Ya_i-function_a(Xa_j))+0.7*(Yb_i-function_b(Xb_j))))。
based on the same idea, the embodiment of the present specification further provides a corresponding wind control decision method, and fig. 4 is a schematic flow diagram of the method.
The method in fig. 4 comprises the following steps:
s402: and acquiring merchant targets under various scenes to obtain a merchant target set.
S404: various features related to the merchant target are collected to obtain a feature set.
S406: and establishing a mapping relation between one or more characteristics and the specified merchant target by utilizing an optimization algorithm according to the merchant target set and the characteristic set, and carrying out a wind control decision on the merchant customer.
In the embodiment of the present specification, the merchant targets in various scenarios are collected in at least one of the following manners: and the merchant feeds back, predicts the model, deletes the rule and checks manually in real time or off line.
In embodiments of the present description, the features include at least one of: customer characteristics, transaction characteristics, merchant characteristics.
In the embodiment of the present specification, the one or more features are pre-specified in the feature set or obtained by feature engineering mining.
In an embodiment of this specification, the establishing, according to the merchant target set and the feature set, a mapping relationship between one or more features and a specified merchant target by using an optimization algorithm may specifically include:
determining one or more features in the set of features and obtaining a merchant target specified in the set of merchant targets; establishing a mapping relation between the one or more characteristics and the merchant target by optimizing with the minimized merchant target error as an optimization target by utilizing an optimization algorithm; and calculating the estimated data according to the one or more characteristics in the optimization process.
In an embodiment of the present specification, if a single merchant target is set for a mixed scene including at least two sub-scenes, the merchant target set includes merchant sub-targets respectively corresponding to the sub-scenes;
the establishing, according to the merchant target set and the feature set, a mapping relationship between one or more features and a specified merchant target by using an optimization algorithm may specifically include:
according to the merchant target set, determining merchant sub-targets corresponding to sub-scenes contained in a mixed scene of the designated merchant target and the weight of each sub-scene; and establishing a mapping relation between one or more characteristics and a specified merchant target by utilizing an optimization algorithm according to the characteristic set, the determined merchant sub-targets and the weight.
In this embodiment of the present specification, after establishing the mapping relationship between the one or more features and the specified merchant target, the following may be further performed:
collecting characteristic data for a customer making a service request to a merchant; and calculating according to the characteristic data and the mapping relation to determine whether the specified merchant target can be reached, and realizing a wind control decision for the customer based on a calculation result.
Based on the same idea, the embodiment of the present specification further provides a corresponding apparatus.
A wind control decision device of an embodiment of this specification includes:
the first data module is used for acquiring merchant targets in various scenes to obtain a merchant target set;
the second data module is used for acquiring various characteristics related to the merchant target to obtain a characteristic set;
and the decision module is used for establishing a mapping relation between one or more characteristics and the specified merchant target by utilizing an optimization algorithm according to the merchant target set and the characteristic set and carrying out a wind control decision on the merchant customer.
Based on the same idea, an embodiment of the present specification further provides a corresponding wind control decision device, and fig. 5 is a schematic structural diagram of the device, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring merchant targets under various scenes to obtain a merchant target set;
collecting various characteristics related to a merchant target to obtain a characteristic set;
and establishing a mapping relation between one or more characteristics and the specified merchant target by utilizing an optimization algorithm according to the merchant target set and the characteristic set, and carrying out a wind control decision on the merchant customer.
The processor and the memory may communicate via a bus.
Based on the same idea, embodiments of the present specification further provide a corresponding non-volatile computer storage medium, in which computer-executable instructions are stored, where the computer-executable instructions are configured to:
acquiring merchant targets under various scenes to obtain a merchant target set;
collecting various characteristics related to a merchant target to obtain a characteristic set;
and establishing a mapping relation between one or more characteristics and the specified merchant target by utilizing an optimization algorithm according to the merchant target set and the characteristic set, and carrying out a wind control decision on the merchant customer.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the embodiments of the apparatus, the device, and the nonvolatile computer storage medium, since they are substantially similar to the embodiments of the method, the description is simple, and for the relevant points, reference may be made to the partial description of the embodiments of the method.
The apparatus, the device, the nonvolatile computer storage medium, and the method provided in the embodiments of the present specification correspond to each other, and therefore, the apparatus, the device, and the nonvolatile computer storage medium also have advantageous technical effects similar to those of the corresponding method.
In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Language Description Language), traffic, pl (core unified Programming Language), HDCal, JHDL (Java Hardware Description Language), langue, Lola, HDL, laspam, hardsradware (Hardware Description Language), vhjhd (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.
The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functions of the various elements may be implemented in the same one or more software and/or hardware implementations of the present description.
As will be appreciated by one skilled in the art, the present specification embodiments may be provided as a method, system, or computer program product. Accordingly, embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.
The description has been presented with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the description. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
This description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The above description is only an example of the present specification, and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (15)
1. A wind control decision system, comprising:
the target module is used for acquiring merchant targets in various scenes to obtain a merchant target set;
the characteristic module is used for acquiring various characteristics related to the merchant target to obtain a characteristic set;
and the computing module is used for establishing a mapping relation between one or more characteristics and a specified merchant target by utilizing an optimization algorithm according to the merchant target set and the characteristic set and is used for carrying out a wind control decision on the merchant customer.
2. The system of claim 1, the goal module collects merchant goals in various scenarios using at least one of: and the merchant feeds back, predicts the model, deletes the rule and checks manually in real time or off line.
3. The system of claim 1, the features comprising at least one of: customer characteristics, transaction characteristics, merchant characteristics.
4. The system of claim 1, wherein the one or more features are pre-specified in the feature set or mined by feature engineering.
5. The system according to claim 1, wherein the calculation module establishes a mapping relationship between one or more features and a specified merchant target by using an optimization algorithm according to the merchant target set and the feature set, and specifically includes:
the computing module determines one or more features in the set of features and obtains a merchant target specified in the set of merchant targets;
establishing a mapping relation between the one or more characteristics and the merchant target by optimizing with the minimized merchant target error as an optimization target by utilizing an optimization algorithm;
and calculating the estimated data according to the one or more characteristics in the optimization process.
6. The system according to claim 1, wherein if a single merchant target is set for a mixed scene including at least two sub-scenes, the merchant target set includes merchant sub-targets respectively corresponding to the sub-scenes;
the calculation module establishes a mapping relationship between one or more features and a specified merchant target by using an optimization algorithm according to the merchant target set and the feature set, and specifically includes:
the calculation module determines merchant sub-targets corresponding to sub-scenes contained in a mixed scene of the designated merchant target and the weight of each sub-scene according to the merchant target set;
and establishing a mapping relation between one or more characteristics and a specified merchant target by utilizing an optimization algorithm according to the characteristic set, the determined merchant sub-targets and the weight.
7. The system of claim 1, the computing module further to perform:
collecting characteristic data for a customer making a service request to a merchant;
and calculating according to the characteristic data and the mapping relation to determine whether the specified merchant target can be reached, and realizing a wind control decision for the customer based on a calculation result.
8. A wind control decision method, comprising:
acquiring merchant targets under various scenes to obtain a merchant target set;
collecting various characteristics related to a merchant target to obtain a characteristic set;
and establishing a mapping relation between one or more characteristics and the specified merchant target by utilizing an optimization algorithm according to the merchant target set and the characteristic set, and carrying out a wind control decision on the merchant customer.
9. The method of claim 8, wherein the merchant targets in various scenarios are collected in at least one of the following ways: and the merchant feeds back, predicts the model, deletes the rule and checks manually in real time or off line.
10. The method of claim 8, the features comprising at least one of: customer characteristics, transaction characteristics, merchant characteristics.
11. The method of claim 8, wherein the one or more features are pre-specified in the feature set or mined by feature engineering.
12. The method according to claim 8, wherein the establishing a mapping relationship between one or more features and a specified merchant target by using an optimization algorithm according to the merchant target set and the feature set specifically comprises:
determining one or more features in the set of features and obtaining a merchant target specified in the set of merchant targets;
establishing a mapping relation between the one or more characteristics and the merchant target by optimizing with the minimized merchant target error as an optimization target by utilizing an optimization algorithm;
and calculating the estimated data according to the one or more characteristics in the optimization process.
13. The method according to claim 8, wherein if a single merchant target is set for a mixed scene including at least two sub-scenes, the merchant target set includes merchant sub-targets respectively corresponding to the sub-scenes;
the establishing of the mapping relationship between one or more features and the specified merchant target by using an optimization algorithm according to the merchant target set and the feature set specifically includes:
according to the merchant target set, determining merchant sub-targets corresponding to sub-scenes contained in a mixed scene of the designated merchant target and the weight of each sub-scene;
and establishing a mapping relation between one or more characteristics and a specified merchant target by utilizing an optimization algorithm according to the characteristic set, the determined merchant sub-targets and the weight.
14. The method of claim 8, after establishing the mapping between the one or more features and the specified merchant objective, the method further comprising:
collecting characteristic data for a customer making a service request to a merchant;
and calculating according to the characteristic data and the mapping relation to determine whether the specified merchant target can be reached, and realizing a wind control decision for the customer based on a calculation result.
15. A wind-controlled decision-making apparatus, comprising:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring merchant targets under various scenes to obtain a merchant target set;
collecting various characteristics related to a merchant target to obtain a characteristic set;
and establishing a mapping relation between one or more characteristics and the specified merchant target by utilizing an optimization algorithm according to the merchant target set and the characteristic set, and carrying out a wind control decision on the merchant customer.
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| CN201810113984.2A CN108446910A (en) | 2018-02-05 | 2018-02-05 | A kind of air control decision system, method and equipment |
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| CN201810113984.2A CN108446910A (en) | 2018-02-05 | 2018-02-05 | A kind of air control decision system, method and equipment |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110032881A (en) * | 2018-12-28 | 2019-07-19 | 阿里巴巴集团控股有限公司 | A kind of data processing method, device, equipment and medium |
| CN112184235A (en) * | 2020-09-04 | 2021-01-05 | 支付宝(杭州)信息技术有限公司 | Wind control data changing method and device |
| CN116029557A (en) * | 2023-03-27 | 2023-04-28 | 北京白龙马云行科技有限公司 | Network about car wind control method, system, computer equipment and storage medium |
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| CN107330785A (en) * | 2017-07-10 | 2017-11-07 | 广州市触通软件科技股份有限公司 | A kind of petty load system and method based on the intelligent air control of big data |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107330785A (en) * | 2017-07-10 | 2017-11-07 | 广州市触通软件科技股份有限公司 | A kind of petty load system and method based on the intelligent air control of big data |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110032881A (en) * | 2018-12-28 | 2019-07-19 | 阿里巴巴集团控股有限公司 | A kind of data processing method, device, equipment and medium |
| CN110032881B (en) * | 2018-12-28 | 2023-09-22 | 创新先进技术有限公司 | Data processing method, device, equipment and medium |
| CN112184235A (en) * | 2020-09-04 | 2021-01-05 | 支付宝(杭州)信息技术有限公司 | Wind control data changing method and device |
| CN112184235B (en) * | 2020-09-04 | 2022-05-13 | 支付宝(杭州)信息技术有限公司 | Wind control data changing method and device |
| CN116029557A (en) * | 2023-03-27 | 2023-04-28 | 北京白龙马云行科技有限公司 | Network about car wind control method, system, computer equipment and storage medium |
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