CN113807891A - Advertisement putting processing method and device - Google Patents
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Abstract
The invention discloses an advertisement putting processing method and device, and relates to the technical field of computers. One specific implementation mode of the method comprises the steps of receiving a basic bid combination, obtaining a marketing combination optimization model, and calling a basic bid combination rounding interface to obtain a rounded basic bid combination by utilizing a first-order Taylor approximate estimation rounding algorithm; and sending the rounded basic bid combination to a platform to execute an online advertisement putting program. Therefore, the method and the device can solve the problems that the marketing effect of the online advertisement putting program of the existing platform is poor and the service guarantee cannot be met.
Description
Technical Field
The invention relates to the technical field of computers, in particular to an advertisement putting processing method and device.
Background
When an advertiser launches an online advertisement on an online advertisement marketing platform (hereinafter referred to as a platform), an advertisement channel needs to be selected (such as searching, recommending, displaying and the like), an advertisement plan is established, and an advertisement plan budget is set. Under one plan, a plurality of advertisement units can be arranged, and the bidding price of each auction of each advertisement unit is determined by the product of the basic bidding price and the premium system.
Platforms typically limit the granularity of the base bid, e.g., requiring that the base bid must be an integer multiple of 0.1-tuple. The basic bid output by the existing intelligent bidding system generally does not meet the requirement of platform granularity. For example outputting a base bid of 0.4325 dollars. Thus, the output of the intelligent bidding system is typically rounded up (e.g., rounded up, rounded down, rounded up (i.e., rounded) to meet the granularity requirements for placing the base bid.
In the process of implementing the invention, the inventor finds that at least the following problems exist in the prior art:
the existing rounding scheme is applied to the basic bid output by the intelligent bidding system, so that the constraint of the online advertisement putting service can not be guaranteed to be still obeyed. For example, if the bids for all ad units are rounded up, the resulting total cost may be caused to exceed the total budget limit. Moreover, the existing rounding scheme does not consider the influence of bid changes on the overall marketing target of cross-advertising units in the online advertising process of the platform, and the application of the existing rounding scheme can possibly deteriorate the overall marketing effect.
Disclosure of Invention
In view of this, embodiments of the present invention provide an advertisement delivery processing method and apparatus, which can solve the problems that the marketing effect of an online advertisement delivery program of an existing platform is poor and service guarantees cannot be met.
To achieve the above object, according to an aspect of the embodiments of the present invention, there is provided an advertisement delivery processing method, including receiving a basic bid combination, obtaining a marketing combination optimization model, and further invoking a basic bid combination rounding interface to obtain a rounded basic bid combination by using a first-order taylor approximation estimation rounding algorithm; and sending the rounded basic bid combination to a platform to execute an online advertisement putting program.
Optionally, after receiving the basic bid combination, the method includes:
and acquiring a marketing objective function and a business constraint function according to the basic bidding combination to generate a marketing combination optimization model.
Optionally, according to the basic bid combination, a preset function interface is called, and then a marketing objective function and a business constraint function corresponding to the basic bid combination are obtained.
Optionally, invoking a base bid combination rounding interface to obtain a rounded base bid combination by using a first-order taylor approximation estimation rounding algorithm, including:
according to the basic bid combination and the marketing combination optimization model, calculating influence information on the marketing combination optimization model after the basic bid of each advertising unit in the basic bid combination is rounded by utilizing a first-order Taylor approximate estimation rounding algorithm;
and acquiring a preset planning model, and obtaining and outputting an optimal rounded basic bid combination based on the influence information.
Optionally, obtaining a preset planning model, and obtaining an optimal rounded basic bid combination based on the influence information includes:
and calling a mixed integer linear programming solver, taking the programming model and the influence information as input, and solving the optimal rounded basic bid combination.
Optionally, obtaining a preset planning model, and obtaining an optimal rounded basic bid combination based on the influence information includes:
substituting the influence information into a planning model, and adopting a heuristic greedy algorithm to carry out iterative solution; and selecting one advertisement unit basic bid in the basic bid combination for rounding each iteration, and minimizing a business constraint function in the marketing combination optimization model by rounding each iteration until all the advertisement unit basic bids are rounded to obtain the optimal rounded basic bid combination.
Optionally, the planning model is configured as a 0-1 planning model.
In addition, the invention also provides an advertisement putting processing device, which comprises an acquisition module, a display module and a display module, wherein the acquisition module is used for receiving the basic bidding combination, acquiring a marketing combination optimization model, and further calling a basic bidding combination rounding interface to obtain a rounded basic bidding combination by utilizing a first-order Taylor approximate estimation rounding algorithm; and the processing module is used for sending the rounded basic bid combination to a platform so as to execute an online advertisement putting program.
One embodiment of the above invention has the following advantages or benefits: the invention can realize the basic bid rounding considering the service constraint of the whole advertisement unit combination, namely, a TMM (touch Point Mixed Modeling, marketing combination optimization) model is established, the marketing effect changes (such as cost, conversion, GMV and the like) caused by rounding up and down of each advertisement unit in the marketing combination are respectively carried out, and approximate estimation is carried out based on a first-order Taylor approximate principle; therefore, a planning model is established to obtain an advertisement unit combination and integration scheme which maximizes a marketing target on the premise of not damaging business constraints; in addition, a heuristic algorithm scheme or a mixed integer linear programming solver is provided for efficiently solving the programming model; therefore, the rounded platform online advertisement delivery meets the business constraint, the influence of rounding on the whole marketing effect is considered globally, and the degradation of the marketing effect caused by rounding is controlled. In addition, the method is presented in a specific interface form, the basic bidding combination and the TMM model are input, and the rounded basic bidding combination is output, so that efficient calling and safety guarantee are facilitated.
Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
fig. 1 is a schematic diagram of a main flow of an advertisement placement processing method according to a first embodiment of the present invention;
fig. 2 is a schematic diagram of a main flow of an advertisement placement processing method according to a second embodiment of the present invention;
fig. 3 is a schematic diagram of a main flow of an advertisement placement processing method according to a third embodiment of the present invention;
fig. 4 is a schematic diagram of main blocks of an advertisement placement processing apparatus according to an embodiment of the present invention;
FIG. 5 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;
fig. 6 is a schematic block diagram of a computer system suitable for use in implementing a terminal device or server of an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Fig. 1 is a schematic diagram of a main flow of an advertisement placement processing method according to a first embodiment of the present invention, and as shown in fig. 1, the advertisement placement processing method includes:
and S101, receiving a basic bid combination, obtaining a marketing combination optimization model, and calling a basic bid combination rounding interface to obtain a rounded basic bid combination by utilizing a first-order Taylor approximation estimation rounding algorithm.
In some embodiments, after receiving the base bid combination, comprising: obtaining a marketing objective function and a business constraint function according to the basic bidding combination to generate a marketing combination optimization model, namely a TMM (marketing combination optimization) model:
subject to fi(x)≥0，for i＝1，...，m
x is a base bid vector representing a base bid combination, wherein each dimension represents a base bid for an advertising unit within a marketing combination; f. of0(x) And estimating the marketing target performance corresponding to the basic bidding combination x for the marketing target function. Such as total GMV, total conversion, etc.; f. ofi(x) For the traffic constraint function, f needs to be ensuredi(x) ≧ 0, and i ≧ 1, …, m to achieve a business constraint, e.g., a total budget constraint can be written as fi(x) The total budget-total cost (x) is more than or equal to 0.
It should be noted that a function interface is specially provided, so that a preset function interface can be called to obtain a marketing objective function and a business constraint function corresponding to a basic bid combination. In addition, the marketing objective function and the business constraint function may be collectively referred to as an effect function.
As another embodiment, the step of calling the base bid combination rounding interface to obtain the rounded base bid combination by using the first-order taylor approximation estimation rounding algorithm may include: according to the basic bid combination and the marketing combination optimization model, calculating influence information on the marketing combination optimization model after the basic bid of each advertising unit in the basic bid combination is rounded by utilizing a first-order Taylor approximate estimation rounding algorithm; and then obtaining a preset planning model, and obtaining and outputting an optimal rounded basic bid combination based on the influence information. It should be noted that the present invention provides a set of basic bids across ad units, and for any basic bid, two kinds of rounding are considered: round up and round down. For example: rounding to 0.43, assuming the rounding granularity is 0.1, then 0.07 may be added to round up to 0.5, and 0.03 may be reduced to round down to 0.4. If n advertisement units exist in the marketing combination, a high-efficiency rounding process is realized by utilizing a first-order Taylor approximation principle and a planning model-based solution, and a scheme (namely a marketing combination optimization model) which accords with business constraints and maximizes a marketing target is selected from the high-efficiency rounding process.
In a further embodiment, the invention adopts a first-order Taylor approximate estimation rounding algorithm, can realize low cost and respectively influences the marketing objective function and the business constraint function. If the result of rounding the base bid combination x is denoted as x + Δ x, then the effect of this rounding on the effect function (i.e., marketing objective function or business constraint function) can be calculated using a first order Taylor approximation rounding algorithm:
wherein, the effect function f is 0i(x) As marketing objective function, i is 1, …, m time effect function fi(x) As a function of traffic constraints.
As a function of the effect fi(x) The gradient of (a), on the right of the equation, is the vector inner product, and is the result of multiplying each component of the gradient by each component of Δ x and then summing, indicating that the effect of rounding of each ad unit on the final effect variation is approximately independently additive. Thus, the function f for each effect when rounding up and down the advertisement unit j can be calculated in advancei(x) Influence information of (2):
wherein the content of the first and second substances,
the ith effect function f is rounded up or rounded down for the advertisement unit j respectivelyi(x) The change of (2):
wherein i is 0,1, …, m; j is 1, …, n;
represents rounding up;
indicating a rounding down.
Preferably, the planning model is configured as a 0-1 planning model. The specific implementation process comprises the following steps: to obtain
Then, a 0-1 planning model is established to obtain the optimal rounding combination, wherein the 0-1 planning model is as follows:
yj∈{0，1}，for j＝1，...，n.
round-up direction decision variable y of advertisement unit jjIs a variable from 0 to 1 when yj1 means that ad unit j should be rounded up; y isj0 indicates that ad unit j should be rounded down.
In a further embodiment, a Mixed Integer Linear Programming solver, i.e., a Mixed Integer Linear Programming (mlp) solver, is called, and the Programming model and the influence information are used as inputs to find the optimal rounded basic bid combination. Or substituting the influence information into the planning model, and adopting a heuristic greedy algorithm to carry out iterative solution.
Preferably, in the process of iterative solution by adopting a heuristic greedy algorithm, one advertisement unit basic bid in the basic bid combination is selected for rounding each iteration, and the service constraint function in the marketing combination optimization model is minimized by rounding each time until all advertisement unit basic bids are rounded, so that the optimal rounded basic bid combination is obtained.
It should be noted that the smaller the value of the business constraint function is, the constraint is "tight", whereas it is described as "loose". The heuristic algorithm adopts greedy method iteration to select one unit for rounding at a time, and constraint is tightened as much as possible and still holds each round until all units are rounded completely. As an embodiment, the specific calculation execution process may be:
assume an initial set
Indicating the remaining ad units. When in use
Temporal computation set
Is composed of
In (1), rounding up all ad units that have tightened the constraint and remain true alone includes: if it is not
Then pair
The middle advertisement unit respectively and independently rounds up (upward and downward are calculated), and an advertisement unit j which enables the constraint of the business constraint function to be the tightest and the rounding direction of the advertisement unit j are found; otherwise
Without the presence of advertising units and rounding directions that simultaneously tighten the constraint and remain true, can be used in
And finding out the advertisement unit j and the rounding direction thereof, wherein the single rounding action can maximize the current most tightly constrained service constraint function value. Finally, a round-off direction is applied to the advertisement unit j, from the set
The ad unit j is removed.
And step S102, sending the rounded basic bid combination to a platform so as to execute an online advertisement putting program.
In an embodiment, the rounded basic bid combination obtained in step S101 may be sent to the platform, so that the platform may start an online advertisement delivery program to perform bid marketing based on the rounded basic bid combination.
In conclusion, the advertisement putting processing method of the invention adopts the first-order Taylor approximation principle to quickly estimate the rounding effect; moreover, a planning model is constructed to optimally solve the rounding, so that a marketing objective function is maximized on the premise of ensuring the establishment of constraint; moreover, the heuristic algorithm for solving the scene 0-1 planning rounding model by high-efficiency approximation is adopted, and is based on the constraint corresponding to the optimal solution in the optimization model, and the constraint is generally tighter than the constraint corresponding to the general solution; meanwhile, the invention is completely suitable for the marketing combination optimization scene subject to business constraint, namely, the online advertisement putting business constraint can be maintained, and the result of marketing target degradation is controlled.
Fig. 2 is a schematic diagram of a main flow of an advertisement delivery processing method according to a second embodiment of the present invention, applied to an intelligent bidding system, and the advertisement delivery processing method may include:
the method comprises the steps of obtaining a basic bidding combination and a corresponding TMM model, calling a basic bidding combination rounding interface, taking the basic bidding combination and the TMM model as input, outputting the rounded basic bidding combination, and then sending the rounded basic bidding combination to a platform to execute an online advertisement putting program.
After the basic bid combination rounding interface is called, the input basic bid combination and the TMM model can be used for obtaining the influence information of each advertisement unit in the basic bid combination after the basic bid is rounded on the TMM model by utilizing a first-order Taylor approximate estimation rounding algorithm, namely, the rounding effect. And then solving an optimal rounding combination through the established 0-1 planning model, wherein an open source or commercial MILP solver or a heuristic greedy algorithm is adopted for iterative solution when the optimal rounding combination is solved.
Fig. 3 is a schematic diagram of a main flow of an advertisement placement processing method according to a third embodiment of the present invention, and the advertisement placement processing method may include:
step S301, receiving a basic bid combination and calling a preset function interface.
Step S302, a marketing objective function and a business constraint function corresponding to the basic bidding combination are obtained, and a marketing combination optimization model is generated.
Step S303, a basic bid combination rounding interface is called.
And step S304, according to the basic bid combination and the marketing combination optimization model, calculating influence information on the marketing combination optimization model after the basic bid of each advertisement unit in the basic bid combination is rounded by utilizing a first-order Taylor approximate estimation rounding algorithm.
Step S305, call 0-1 planning model.
Step S306, determining whether the number of advertisement units in the basic bid combination is greater than a preset number threshold, if so, performing step S307, otherwise, performing step S308.
In the embodiment, the step S307 may be directly adopted for solving when the number of advertisement units is small, but the step S308 may accurately solve and simultaneously achieve a fast response when the number of advertisement units is large.
And S307, substituting the influence information into the planning model, adopting a heuristic greedy algorithm to carry out iterative solution to obtain a rounded basic bid combination, and then carrying out S309.
In the embodiment, the heuristic greedy algorithm iterative solution is adopted to round the basic bid of one advertisement unit in the basic bid combination selected in each iteration, and the service constraint function in the marketing combination optimization model is minimized in each round until the basic bids of all advertisement units are rounded, so that the optimal rounded basic bid combination is obtained.
Step S308, calling a mixed integer linear programming solver, taking the programming model and the influence information as input, solving the optimal rounded basic bid combination, and then performing step S309.
Step S309, the rounded basic bid combination is sent to a platform to execute an online advertisement putting program.
Fig. 4 is a schematic diagram of main blocks of an advertisement placement processing apparatus according to an embodiment of the present invention, and as shown in fig. 4, the advertisement placement processing apparatus 400 includes an acquisition module 401 and a processing module 402. The obtaining module 401 receives the basic bid combination, obtains a marketing combination optimization model, and further calls a basic bid combination rounding interface to obtain a rounded basic bid combination by using a first-order taylor approximation estimation rounding algorithm; the processing module 402 sends the rounded basic bid combination to the platform to execute the online advertisement delivery program.
In some embodiments, after the obtaining module 401 receives the base bid combination, it includes:
and acquiring a marketing objective function and a business constraint function according to the basic bidding combination to generate a marketing combination optimization model.
In some embodiments, the obtaining module 401 is further configured to:
and calling a preset function interface according to the basic bidding combination, and further acquiring a marketing target function and a business constraint function corresponding to the basic bidding combination.
In some embodiments, the obtaining module 401 invokes the base bid combination rounding interface to obtain a rounded base bid combination using a first order taylor approximation pre-estimation rounding algorithm, including:
according to the basic bid combination and the marketing combination optimization model, calculating influence information on the marketing combination optimization model after the basic bid of each advertising unit in the basic bid combination is rounded by utilizing a first-order Taylor approximate estimation rounding algorithm; and acquiring a preset planning model, and obtaining and outputting an optimal rounded basic bid combination based on the influence information.
In some embodiments, the obtaining module 401 obtains a preset planning model, and finds an optimal rounded basic bid combination based on the influence information, including:
and calling a mixed integer linear programming solver, taking the programming model and the influence information as input, and solving the optimal rounded basic bid combination.
In some embodiments, the obtaining module 401 obtains a preset planning model, and finds an optimal rounded basic bid combination based on the influence information, including:
substituting the influence information into a planning model, and adopting a heuristic greedy algorithm to carry out iterative solution; and selecting one advertisement unit basic bid in the basic bid combination for rounding each iteration, and minimizing a business constraint function in the marketing combination optimization model by rounding each iteration until all the advertisement unit basic bids are rounded to obtain the optimal rounded basic bid combination.
In some embodiments, the planning model is configured as a 0-1 planning model.
It should be noted that the advertisement delivery processing method and the advertisement delivery processing apparatus according to the present invention have a corresponding relationship in the specific implementation content, and therefore the repetitive content is not described again.
Fig. 5 illustrates an exemplary system architecture 500 to which an advertisement placement processing method or an advertisement placement processing apparatus according to an embodiment of the present invention may be applied.
As shown in fig. 5, the system architecture 500 may include terminal devices 501, 502, 503, a network 504, and a server 505. The network 504 serves to provide a medium for communication links between the terminal devices 501, 502, 503 and the server 505. Network 504 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 501, 502, 503 to interact with a server 505 over a network 504 to receive or send messages or the like. Various communication client applications may be installed on the terminal devices 501, 502, 503.
The terminal devices 501, 502, 503 may be various electronic devices having an advertisement delivery processing screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 505 may be a server providing various services, such as a back-office management server (for example only) providing support for users utilizing the terminal devices 501, 502, 503. The backend management server may analyze and perform other processing on the received data such as the product information query request, and feed back a processing result (for example, target push information, product information — just an example) to the terminal device.
It should be noted that the advertisement placement processing method provided by the embodiment of the present invention is generally executed by the server 505, and accordingly, the computing device is generally disposed in the server 505.
It should be understood that the number of terminal devices, networks, and servers in fig. 5 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 6, a block diagram of a computer system 600 suitable for use with a terminal device implementing an embodiment of the invention is shown. The terminal device shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 6, the computer system 600 includes a Central Processing Unit (CPU)601 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM603, various programs and data necessary for the operation of the computer system 600 are also stored. The CPU601, ROM602, and RAM603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input section 605 including a keyboard, a mouse, and the like; an output portion 606 including, for example, a Cathode Ray Tube (CRT), a liquid crystal advertising processor (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The driver 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted in the storage section 608 as necessary.
In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 611. The computer program performs the above-described functions defined in the system of the present invention when executed by the Central Processing Unit (CPU) 601.
It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor includes an acquisition module and a processing module. Wherein the names of the modules do not in some cases constitute a limitation of the module itself.
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to receive a base bid combination, obtain a marketing combination optimization model, and invoke a base bid combination rounding interface to obtain a rounded base bid combination using a first order taylor approximation predictive rounding algorithm; and sending the rounded basic bid combination to a platform to execute an online advertisement putting program.
According to the technical scheme of the embodiment of the invention, the problems that the marketing effect of the on-line advertisement putting program of the existing platform is poor and the service guarantee cannot be met can be solved.
The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An advertisement placement processing method, comprising:
receiving a basic bid combination, acquiring a marketing combination optimization model, and calling a basic bid combination rounding interface to obtain a rounded basic bid combination by utilizing a first-order Taylor approximate estimation rounding algorithm;
and sending the rounded basic bid combination to a platform to execute an online advertisement putting program.
2. The method of claim 1, wherein receiving the base bid combination comprises:
and acquiring a marketing objective function and a business constraint function according to the basic bidding combination to generate a marketing combination optimization model.
3. The method of claim 2, comprising:
and calling a preset function interface according to the basic bidding combination, and further acquiring a marketing target function and a business constraint function corresponding to the basic bidding combination.
4. The method of claim 1, wherein invoking the base bid combination rounding interface to obtain a rounded base bid combination using a first order taylor approximation pre-estimation rounding algorithm comprises:
according to the basic bid combination and the marketing combination optimization model, calculating influence information on the marketing combination optimization model after the basic bid of each advertising unit in the basic bid combination is rounded by utilizing a first-order Taylor approximate estimation rounding algorithm;
and acquiring a preset planning model, and obtaining and outputting an optimal rounded basic bid combination based on the influence information.
5. The method of claim 4, wherein obtaining a predetermined planning model, and finding an optimal rounded base bid combination based on the impact information comprises:
and calling a mixed integer linear programming solver, taking the programming model and the influence information as input, and solving the optimal rounded basic bid combination.
6. The method of claim 4, wherein obtaining a predetermined planning model, and finding an optimal rounded base bid combination based on the impact information comprises:
substituting the influence information into a planning model, and adopting a heuristic greedy algorithm to carry out iterative solution; and selecting one advertisement unit basic bid in the basic bid combination for rounding each iteration, and minimizing a business constraint function in the marketing combination optimization model by rounding each iteration until all the advertisement unit basic bids are rounded to obtain the optimal rounded basic bid combination.
7. The method according to any one of claims 4-6, comprising:
the planning model is configured as a 0-1 planning model.
8. An advertisement placement processing apparatus, comprising:
the acquisition module is used for receiving the basic bid combination, acquiring a marketing combination optimization model and calling a basic bid combination rounding interface to obtain a rounded basic bid combination by utilizing a first-order Taylor approximation estimation rounding algorithm;
and the processing module is used for sending the rounded basic bid combination to a platform so as to execute an online advertisement putting program.
9. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-7.
10. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-7.
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