CN113506146B - Data adjusting method and device and computer readable storage medium - Google Patents
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Abstract
The embodiment of the disclosure provides a data adjusting method, a device and a computer readable storage medium, wherein the data adjusting method comprises the following steps: acquiring historical data of promotion parameters of a promotion target, wherein the promotion parameters are used for indicating promotion effects and promotion costs of the promotion target; predicting the promotion parameters according to the historical data to obtain predicted values of the promotion parameters; determining a comprehensive change rate and an amplitude change rate of the promotion parameters according to the predicted values and the historical data of the promotion parameters, wherein the comprehensive change rate is used for indicating the change trend of the promotion parameters, and the amplitude change rate is used for indicating the change amplitude of the promotion parameters; and adjusting the bidding of the promotion target according to the comprehensive change rate and the amplitude change rate of the promotion parameters. Because the variation trend and the variation amplitude of the popularization parameters are comprehensively considered, the adjustment of the bidding is more accurate, the cost can be better controlled, and the popularization effect is improved.
Description
Technical Field
The disclosed embodiments relate to the field of computer technologies, and in particular, to a data adjusting method and apparatus, and a computer-readable storage medium.
Background
With the development of the internet, a lot of information promotion is realized on line, in the process of information promotion, for example, advertisement promotion, advertisement position bidding is generally needed, because the on-line promotion is more convenient, the bidding process can be completed through a network platform, and advertisers participating in bidding set bids manually by means of promoting staff based on historical data. However, in the process of realizing the bid promotion, a large amount of manpower is consumed, the promotion cost is high, and the effect is poor.
Disclosure of Invention
In view of this, the embodiments of the present disclosure provide a data adjusting method, an apparatus, and a computer-readable storage medium, so as to overcome the defects of high promotion cost and poor effect in the process of promoting bidding.
In a first aspect, an embodiment of the present disclosure provides a data adjustment method, which includes: acquiring historical data of promotion parameters of a promotion target, wherein the promotion parameters are used for indicating promotion effects and promotion costs of the promotion target; predicting the promotion parameters according to the historical data to obtain predicted values of the promotion parameters; determining a comprehensive change rate and an amplitude change rate of the promotion parameters according to the predicted values and the historical data of the promotion parameters, wherein the comprehensive change rate is used for indicating the change trend of the promotion parameters, and the amplitude change rate is used for indicating the change amplitude of the promotion parameters; and adjusting the bidding of the promotion target according to the comprehensive change rate and the amplitude change rate of the promotion parameters.
In a second aspect, an embodiment of the present disclosure provides a data adjusting apparatus, which includes: the system comprises an acquisition module, a display module and a display module, wherein the acquisition module is configured to acquire historical data of promotion parameters of a promotion target, and the promotion parameters are used for indicating promotion effects and promotion costs of the promotion target; the prediction module is configured to predict the promotion parameters according to the historical data to obtain predicted values of the promotion parameters; the determining module is configured to determine a comprehensive change rate and an amplitude change rate of the promotion parameters according to the predicted values and the historical data of the promotion parameters, wherein the comprehensive change rate is used for indicating the change trend of the promotion parameters, and the amplitude change rate is used for indicating the change amplitude of the promotion parameters; and the adjusting module is configured to adjust the bidding of the promotion target according to the comprehensive change rate and the amplitude change rate of the promotion parameters.
In a third aspect, an embodiment of the present disclosure provides an electronic device, which includes: at least one processor and a memory. The memory stores at least one program that, when executed by the at least one processor, causes the at least one processor to implement a method according to an embodiment of the disclosure.
In a fourth aspect, the disclosed embodiments provide a computer-readable storage medium having stored thereon a computer program, which, when executed by a processor, causes the processor to implement a method according to an embodiment of the present disclosure.
The data adjusting method, the data adjusting device and the computer-readable storage medium provided by the embodiment of the disclosure acquire historical data of promotion parameters of a promotion target, wherein the promotion parameters are used for indicating promotion effects and promotion costs of the promotion target; predicting the promotion parameters according to the historical data to obtain predicted values of the promotion parameters; determining a comprehensive change rate and an amplitude change rate of the promotion parameters according to the predicted values and the historical data of the promotion parameters, wherein the comprehensive change rate is used for indicating the change trend of the promotion parameters, and the amplitude change rate is used for indicating the change amplitude of the promotion parameters; and adjusting the bidding of the promotion target according to the comprehensive change rate and the amplitude change rate of the promotion parameters. Because historical data are analyzed, bidding of the promotion target is automatically adjusted, too much labor is not required, the comprehensive change rate and the amplitude change rate are respectively calculated, the change trend and the change amplitude of the promotion parameters are comprehensively considered, the bidding is adjusted more accurately, the cost can be controlled better, and the promotion effect is improved.
Drawings
Some specific embodiments of the disclosed embodiments are described in detail below by way of example and not by way of limitation with reference to the accompanying drawings. The same reference numbers in the drawings identify the same or similar elements or components. Those skilled in the art will appreciate that the drawings are not necessarily drawn to scale. In the drawings:
FIG. 1 is a flow chart of a method of data conditioning according to an embodiment of the present disclosure;
fig. 2 is a schematic view of an application scenario of a data adjustment method according to an embodiment of the disclosure;
FIG. 3 is a schematic diagram of a price adjustment strategy according to an embodiment of the present disclosure;
FIG. 4 is a block diagram of a data adjustment device according to an embodiment of the present disclosure;
fig. 5 is a block diagram of an electronic device according to an embodiment of the disclosure.
Detailed Description
The following further describes specific implementations of the embodiments of the present disclosure with reference to the drawings of the embodiments of the present disclosure.
Fig. 1 is a flow chart of a data adjustment method according to an embodiment of the present disclosure. The data adjusting method comprises the following steps:
101. and acquiring historical data of popularization parameters of the popularization target.
It should be noted that the promotion target may be any one of the things to be promoted, for example, the promotion target may be an advertisement, recruitment information, a person finding inspiring, a thing finding enlightenment, and the like, and the promotion content of the promotion target is not limited by the present disclosure. The popularization target can be embodied in various forms such as characters, pictures, videos and the like.
It should be further noted that the promotion parameters are used to indicate promotion effects and promotion costs of promotion targets, the number of the promotion parameters may be one or more, and optionally, in an example, the promotion parameters include: one or more of click through volume, click through rate, and promotional cost. The click rate is used for expressing the click browsing times of clicking the information of the browsing promotion target; the click rate is used to indicate the ratio of the number of clicked views of the information of the promotion target to the number of views of the page where the link of the information of the promotion target is located.
Optionally, in an example, a link is generated based on information of the promotion target, the link is set in one or more web pages, the link of the promotion target can be seen in a process that a user browses the web pages, a number of times of clicking the link to browse is a click rate, and a ratio of the click rate to the number of times of browsing the web pages is the click rate.
The promotion cost is used to represent a promotion price for browsing information of a promotion target once, and optionally, in one example, the promotion cost is used to indicate a cost paid by an advertiser by clicking a link of a promotion target once.
Optionally, in a specific example, the historical data of the promotion parameter may include values of the promotion parameter at different times and in different periods historically. Illustratively, a period may be a day, a week, or a month, and a period may include a plurality of times. For example, taking the click rate as an example, the click rate at the current time may be the accumulated number of clicks from the starting time of the current cycle to the current time; for another example, the click volume of the previous cycle may be the number of clicks accumulated from the start time of the previous cycle to the end time of the previous cycle.
102. And predicting the promotion parameters according to the historical data to obtain the predicted values of the promotion parameters.
The predicted value is used to indicate a result of predicting a value of the promotion parameter at the next time. For example, the predicted value of the click rate is used to indicate the click rate at the next predicted time; for another example, the predicted value of the promotion cost is used to represent the promotion cost at the next moment of prediction.
Optionally, in a specific example, predicting the popularization parameter according to the historical data, and obtaining the predicted value of the popularization parameter includes: calculating historical data of the promotion parameters according to a clustering algorithm to obtain at least two classification intervals of the promotion parameters; based on at least two classification intervals, calculating historical data of the promotion parameters according to a classification algorithm to predict the classification intervals of the promotion parameters at a preset time in the future; and taking the predicted classification interval as a predicted value of the promotion parameter. The future preset time is, for example, the next time. It should be noted that the clustering algorithm and the classification algorithm may form a neural network model, and the prediction using the neural network model is more suitable for the actual situation. Optionally, the clustering algorithm is configured to classify the values of the popularization parameter to obtain at least two classification intervals, and a mean value of the values in each classification interval may be used as a value of the classification interval. For example, the value of the promotion parameter may be [1,10], the value of [1,3] may be a classification interval, the value of (3, 6) may be a classification interval, the value of [1,3] may be 2, the value of [ 3,6] may be 4.5, or 4 or 5, the value of [ 7,10] may be 8.5, or 8 or 9, the classification algorithm is used to predict the classification interval of the value of the promotion parameter at the next time, and the prediction value may be the classification interval of the predicted promotion parameter.
103. And determining the comprehensive change rate and the amplitude change rate of the promotion parameters according to the predicted values and the historical data of the promotion parameters.
The comprehensive change rate is used for indicating the change trend of the promotion parameters, namely indicating that the promotion parameters become larger or smaller; the amplitude change rate is used for indicating the change amplitude of the promotion parameter, namely indicating the change amount of the promotion parameter.
Optionally, in an implementation manner, determining a comprehensive change rate and an amplitude change rate of the promotion parameter according to the predicted value and the historical data of the promotion parameter includes: determining a comprehensive change rate according to the predicted value and the historical data of the promotion parameter; and determining the amplitude change rate based on the predicted value of the promotion parameter and the true value of the current moment. Here, two specific examples are listed to illustrate how the integrated change rate and the amplitude change rate are determined, respectively.
Optionally, in a first example, determining the comprehensive change rate based on the predicted value and the historical data of the promotion parameter includes: according to the predicted value and the historical data of the promotion parameter, determining the same-ratio change rate of the historical preset time period of the promotion parameter and the ring ratio change rate of the previous preset time of the current preset time period; and taking the weighted value of the same-ratio change rate and the ring-ratio change rate as the comprehensive change rate. Specifically, the historical preset time period may be the previous day, and the previous preset time of the current preset time period may be the previous time of the current day, for such a situation, because the same-ratio change rate of the previous day and the ring ratio change rate of the previous time are combined, the comprehensive change rate can more accurately reflect the change condition of the popularization parameter. It should be noted that, a weighted value is obtained by performing weighted summation according to the same-ratio change rate of the previous cycle and the ring-ratio change rate of the previous time of the current cycle, and the weighted value is used as a comprehensive change rate, in this example, a day is used as a cycle to describe the historical preset time period and the previous preset time of the current preset time period, which does not represent that the disclosure is limited thereto. In this example, the integrated rate of change may be calculated according to equation one:
Wherein, w1And w2Is a weight value.
Optionally, in the second example, with reference to the specific example of step 102, determining the amplitude change rate based on the predicted value of the promotion parameter and the true value of the current time includes: acquiring a difference value between a predicted value of the promotion parameter and a true value of the current moment; and taking the ratio of the difference value to the amplitude value of the classification interval in which the promotion parameter is positioned as the amplitude change rate. It should be noted that the true value at the current time may be a value of a classification interval in which the numerical value of the promotion parameter is located at the current time, and the amplitude value of one classification interval is a difference between a maximum value and a minimum value of the classification interval, that is, a numerical value change amplitude of the one classification interval. In this example, the amplitude change rate may be calculated according to equation two:
104. And adjusting the bidding of the promotion target according to the comprehensive change rate and the amplitude change rate of the promotion parameters.
Optionally, in an implementation, adjusting the bid of the promotion target according to the comprehensive change rate and the breadth change rate of the promotion parameter includes: determining an adjustment strategy of bidding of the promotion target according to at least one of the comprehensive change rate and the amplitude change rate; and adjusting the bidding price of the promotion target according to the adjustment strategy and the amplitude modulation rate, wherein the amplitude modulation rate is used for indicating the adjustment amplitude of the bidding price of the promotion target.
It should be noted that the adjustment policy may include a cost policy and an effect policy, where the cost policy is a policy for controlling cost, and the effect policy is a policy for improving popularization effect. The cost strategy preferentially reduces the cost, and the effect strategy preferentially improves the popularization effect. Because the adjustment strategy is determined according to the comprehensive change rate and the amplitude change, the adjustment strategy is ensured to adapt to the change trend of the current popularization parameter, and then the bidding is adjusted according to the adjustment strategy and the amplitude modulation rate, so that the bidding adjustment is more accurate. Optionally, two specific examples are listed here for further detailed description.
Optionally, in the first example, the combined change rate and the amplitude change rate may indicate whether the cost of the promotion target is increased or not, whether the promotion effect is promoted or not, and determine the adjustment policy according to the change condition of the cost and the effect. Illustratively, the adjustment strategy for determining the bid price of the promotion target according to at least one of the comprehensive change rate and the amplitude change rate comprises the following steps: determining a cost strategy as an adjustment strategy in response to the comprehensive change rate and the amplitude change rate indicating that the cost increase value of the promotion target is greater than the effect increase value of the promotion target; and determining the effect strategy as an adjustment strategy in response to the comprehensive change rate and the amplitude change rate indicating that the effect reduction value of the promotion target is greater than the cost reduction value of the promotion target. It should be noted that this is only an example, and the adjustment policy may be determined in other ways. For example, a cost policy may be determined as an adjustment policy when the cost increases; for another example, the effect policy may be determined as the adjustment policy when the cost is reduced; for another example, when the promotion effect is improved, the cost strategy is determined as an adjustment strategy; as another example, when the promotion effect is reduced, the effect policy is determined as the adjustment policy.
Optionally, in a second example, the method further comprises: and determining the amplitude modulation rate of bidding of the promotion target based on the current bidding and the bidding upper limit of the promotion target. The scale rate is used to indicate the magnitude of the bid adjustment. Optionally, in connection with a specific example of step 102, the amplitude modulation rate may be calculated according to the formula three:
The data adjustment method described in conjunction with the above steps 101-104 is described in detail herein by taking a specific application scenario as an example. As shown in fig. 2, fig. 2 is a schematic view of an application scenario of a data adjusting method according to an embodiment of the present disclosure, where in the application scenario, a promotion parameter includes one or more of a click rate, and a promotion cost. As shown in fig. 2, the system to which the data adjustment method is applied includes a data layer 201, a model layer 202, and a policy layer 203. The data layer 201 comprises click rate 2011, click rate 2012 and promotion cost 2013; the model layer 202 comprises a clustering algorithm 2021 and a classification algorithm 2022, and prediction of various promotion parameters contained in the data layer 201 can be realized by utilizing the classification algorithm 2022; policy level 203 includes cost policy 2031, effect policy 2032, and amplitude modulation rate 2033.
The data adjustment method described in conjunction with the system structure shown in fig. 2 and the steps 101-104 is exemplified here by taking the advertisement as an example of the promotion target.
Firstly, data construction is carried out, and based on browsing records of a user on an advertisement on a preset platform, click rate and promotion cost (which can also be called consumption data, namely cost paid by an advertiser when the user clicks the advertisement once) of the advertisement are counted. And the user data of the user, such as gender ratio, age ratio, consumption capability distribution, occupation distribution, marital situation and the like, which are dynamically updated in multiple dimensions can be acquired. Because the data of the user at different times are counted and the future data are predicted, the data are all processed into time class data, including popularization parameters and user data of about 1 day, about 3 days, about 7 days, about 15 days and about 30 days, and popularization parameters and user data of the same hour of the previous hour, the same day and the same day.
And then model prediction is carried out, each promotion parameter in the three promotion parameters is classified through a clustering algorithm (k-means), the mean value of each classification interval is used as the value of the classification interval, and then the value of the classification interval where each promotion parameter value in one hour in the future is predicted by using a classification algorithm such as eXtreme Gradient Boosting (XGboost for short).
Then determining a price adjustment strategy, and determining a comprehensive change rate and an amplitude change rate; determining an adjustment strategy according to the comprehensive change rate and the amplitude change rate; and adjusting the bid according to the amplitude modulation rate and the adjustment strategy. Specifically, reference may be made to fig. 3, where fig. 3 is a schematic diagram of a price adjustment strategy according to an embodiment of the present disclosure. Firstly, comparing the click rate with the comprehensive change rate 301 of the promotion cost; then 4 comprehensive comparison results are obtained, namely a click rate is increased and promotion cost is increased 3021, a click rate is decreased and promotion cost is decreased 3022, a click rate is increased and promotion cost is decreased 3023, and a click rate is decreased and promotion cost is increased 3024; then comparing the click rate with the amplitude change rate of the promotion cost to obtain 2 amplitude comparison results, namely an amplitude change rate 3031 when the click rate amplitude change rate is greater than the promotion cost and an amplitude change rate 3032 when the click rate amplitude change rate is less than the promotion cost; and further determining click rate change conditions including click rate rise 3041 and click rate fall 3042 based on the comprehensive comparison result and the amplitude comparison result, and determining a price adjustment strategy according to the comprehensive comparison result, the amplitude comparison result and the click rate change condition. Exemplarily, the following steps are carried out:
(one), for the increase of click rate and the increase of promotion cost 3021
If the click rate amplitude change rate is larger than the amplitude change rate of the promotion cost and the click rate rises, the price is not adjusted based on the effect strategy;
if the click rate amplitude change rate is larger than the amplitude change rate of the promotion cost and the click rate is reduced, adjusting the bid upwards based on the effect strategy;
if the click rate amplitude change rate is smaller than the amplitude change rate of the promotion cost and the click rate is increased, the bid price is adjusted downwards based on the cost strategy;
if the click rate amplitude change rate is smaller than the amplitude change rate of the promotion cost and the click rate is reduced, when the click rate amplitude change rate (reducing amplitude) is larger than the promotion cost amplitude change rate (increasing amplitude), the price is adjusted upwards based on the effect strategy, and when the click rate amplitude change rate (reducing amplitude) is smaller than the promotion cost amplitude change rate (increasing amplitude), the price is adjusted downwards based on the cost strategy;
(II) the click rate is reduced and the promotion cost is reduced 3022
If the click rate amplitude change rate is larger than the amplitude change rate of the promotion cost and the click rate rises, the price is not adjusted based on the cost strategy;
if the click rate amplitude change rate is larger than the amplitude change rate of the promotion cost and the click rate is reduced, adjusting the bid upwards based on the effect strategy;
if the click rate amplitude change rate is smaller than the amplitude change rate of the promotion cost and the click rate rises, the price is not adjusted based on the cost strategy;
if the click rate amplitude change rate is smaller than the amplitude change rate of the promotion cost and the click rate is reduced, when the click rate amplitude change rate (amplitude reduction) is larger than the amplitude change rate (amplitude reduction) of the promotion cost, price is adjusted upwards based on an effect strategy, and when the click rate amplitude change rate (amplitude reduction) is smaller than the amplitude change rate (amplitude reduction) of the promotion cost, price is not adjusted based on a cost strategy;
(III) increasing click rate and reducing promotion cost 3023
If the click rate rises, price is not adjusted based on the cost strategy;
if the click rate is decreased, when the click rate amplitude change rate (decreased amplitude) is greater than the promotion cost amplitude change rate (decreased amplitude), price is adjusted upwards based on the effect strategy, and when the click rate amplitude change rate (decreased amplitude) is less than the promotion cost amplitude change rate (decreased amplitude), price is not adjusted based on the cost strategy;
(IV) click rate reduction and promotion cost increase 3024
If the click rate rises, adjusting the bid downward based on a cost strategy;
if the click rate is decreased, when the click rate is greater than the promotion cost rate, the bid is adjusted up based on the effect strategy, and when the click rate is less than the promotion cost rate, the bid is adjusted down based on the cost strategy.
It should be noted that, based on the cost strategy, the price adjustment amplitude can be the same as the comprehensive change rate of the promotion cost; when based on the effect strategy, the price adjustment amplitude can be the same as the comprehensive change rate of the click rate. Of course, this is merely an example.
The data adjusting method of the embodiment of the disclosure acquires historical data of promotion parameters of a promotion target, wherein the promotion parameters are used for indicating promotion effects and promotion costs of the promotion target; predicting the promotion parameters according to the historical data to obtain predicted values of the promotion parameters; calculating a comprehensive change rate and an amplitude change rate of the promotion parameters according to the predicted values and the historical data of the promotion parameters, wherein the comprehensive change rate is used for indicating the change trend of the promotion parameters, and the amplitude change rate is used for indicating the change amplitude of the promotion parameters; and adjusting the bidding of the promotion target according to the comprehensive change rate and the amplitude change rate of the promotion parameters. Because historical data are analyzed, bidding of the promotion target is automatically adjusted, too much labor is not required, the comprehensive change rate and the amplitude change rate are respectively calculated, the change trend and the change amplitude of the promotion parameters are comprehensively considered, the bidding is adjusted more accurately, the cost can be controlled better, and the promotion effect is improved.
The embodiment of the present disclosure provides a data adjusting apparatus, configured to perform the data adjusting method described in the foregoing embodiment, as shown in fig. 4, where the data adjusting apparatus 40 includes:
an obtaining module 401 configured to obtain historical data of a promotion parameter of a promotion target, where the promotion parameter is used to indicate a promotion effect and a promotion cost of the promotion target;
the prediction module 402 is configured to predict the promotion parameters according to the historical data to obtain predicted values of the promotion parameters;
a determining module 403, configured to determine, according to the predicted value and the historical data of the promotion parameter, a comprehensive change rate and an amplitude change rate of the promotion parameter, where the comprehensive change rate is used to indicate a change trend of the promotion parameter, and the amplitude change rate is used to indicate a change amplitude of the promotion parameter;
an adjustment module 404 configured to adjust the bids of the promotional goals based on the aggregate rate of change and the magnitude rate of change of the promotional parameters.
Optionally, in some embodiments of the present disclosure, the prediction module 402 is configured to perform an operation on the historical data of the popularization parameter according to a clustering algorithm to obtain at least two classifications of the popularization parameter; and based on at least two classification intervals, calculating historical data of the promotion parameters according to a classification algorithm to predict the classification interval of the promotion parameters at a future moment, and taking the predicted classification interval as a predicted value of the promotion parameters.
Optionally, in some embodiments of the present disclosure, the determining module 403 is configured to determine a comprehensive rate of change based on the predicted value of the promotion parameter and the historical data; and determining the amplitude change rate based on the predicted value of the promotion parameter and the true value of the current moment.
Optionally, in some embodiments of the present disclosure, the determining module 403 is configured to determine, according to the predicted value and the historical data of the promotion parameter, a same-ratio change rate of a historical preset time period of the promotion parameter and a ring-ratio change rate of a previous preset time of a current preset time period; and taking the weighted values of the same-ratio change rate and the ring-ratio change rate as the comprehensive change rate.
Optionally, in some embodiments of the present disclosure, the determining module 403 is configured to obtain a difference between the predicted value of the promotion parameter and the true value of the current time, and use a ratio of the difference to the amplitude value of the classification interval in which the promotion parameter is located as the amplitude change rate.
Optionally, in some embodiments of the present disclosure, the adjusting module 404 is configured to determine an adjusting strategy for bidding of the promotion objective according to at least one of the composite rate of change and the amplitude rate of change; and adjusting the bidding price of the promotion target according to the adjustment strategy and the amplitude modulation rate, wherein the amplitude modulation rate is used for indicating the adjustment amplitude of the bidding price of the promotion target.
Optionally, in some embodiments of the present disclosure, the adjusting module 404 is configured to determine the cost policy as the adjusting policy in response to the combined rate of change and the amplitude rate of change indicating that the cost increase value of the promotion target is greater than the effect increase value of the promotion target; and determining the effect strategy as an adjustment strategy in response to the comprehensive change rate and the amplitude change rate indicating that the effect reduction value of the promotion target is greater than the cost reduction value of the promotion target.
Optionally, in some embodiments of the present disclosure, the adjusting module 404 is further configured to determine an amplitude modulation rate of the bid of the promotional objective based on the current bid and the upper bid limit of the promotional objective.
Optionally, in some embodiments of the present disclosure, the promotion parameter includes: one or more of click through volume, click through rate, and promotional cost.
The data adjusting device of the embodiment of the disclosure acquires historical data of promotion parameters of a promotion target, wherein the promotion parameters are used for indicating promotion effects and promotion costs of the promotion target; predicting the promotion parameters according to the historical data to obtain predicted values of the promotion parameters; determining a comprehensive change rate and an amplitude change rate of the promotion parameters according to the predicted values and the historical data of the promotion parameters, wherein the comprehensive change rate is used for indicating the change trend of the promotion parameters, and the amplitude change rate is used for indicating the change amplitude of the promotion parameters; and adjusting the bidding of the promotion target according to the comprehensive change rate and the amplitude change rate of the promotion parameters. Because historical data are analyzed, bidding of the promotion target is automatically adjusted, too much labor is not required, the comprehensive change rate and the amplitude change rate are respectively determined, the change trend and the change amplitude of the promotion parameters are comprehensively considered, the bidding is adjusted more accurately, the cost can be controlled better, and the promotion effect is improved.
Based on the data adjustment method described in the foregoing embodiment, an embodiment of the present disclosure provides an electronic device, configured to execute the data adjustment method described in the foregoing embodiment, and as shown in fig. 5, the electronic device 50 includes: at least one processor (processor)502, memory 504, bus 506, and communication Interface 508.
Wherein:
the processor 502, communication interface 508, and memory 504 communicate with each other via a communication bus 506.
A communication interface 508 for communicating with other devices.
The processor 502 is configured to execute the program 510, and may specifically execute the relevant steps in the method described in the foregoing embodiment.
In particular, program 510 may include program code that includes computer operating instructions.
The processor 502 may be a central processing unit CPU, or an application Specific Integrated circuit asic, or one or more Integrated circuits configured to implement embodiments of the present disclosure. The electronic device comprises one or more processors, which can be the same type of processor, such as one or more CPUs; or may be different types of processors such as one or more CPUs and one or more ASICs.
The memory 504 is used for storing the program 510. Memory 504 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
The electronic equipment of the embodiment of the disclosure acquires historical data of promotion parameters of a promotion target, wherein the promotion parameters are used for indicating promotion effects and promotion costs of the promotion target; predicting the promotion parameters according to the historical data to obtain predicted values of the promotion parameters; determining a comprehensive change rate and an amplitude change rate of the promotion parameters according to the predicted values and the historical data of the promotion parameters, wherein the comprehensive change rate is used for indicating the change trend of the promotion parameters, and the amplitude change rate is used for indicating the change amplitude of the promotion parameters; and adjusting the bidding of the promotion target according to the comprehensive change rate and the amplitude change rate of the promotion parameters. Because historical data are analyzed, bidding of the promotion target is automatically adjusted, too much labor is not required, the comprehensive change rate and the amplitude change rate are respectively determined, the change trend and the change amplitude of the promotion parameters are comprehensively considered, the bidding is adjusted more accurately, the cost can be controlled better, and the promotion effect is improved.
Based on the data adjustment method described in the above embodiments, the present disclosure provides a computer-readable storage medium having a computer program stored thereon, where the computer program, when executed by a processor, causes the processor to implement the data adjustment method described in the embodiments of the present disclosure.
The data adjustment apparatus of the embodiments of the present disclosure exists in various forms, including but not limited to:
(1) a mobile communication device: such devices are characterized by mobile communications capabilities and are primarily targeted at providing voice, data communications. Such terminals include: smart phones (e.g., iphones), multimedia phones, functional phones, and low-end phones, among others.
(2) Ultra mobile personal computer device: the equipment belongs to the category of personal computers, has calculation and processing functions and generally has the characteristic of mobile internet access. Such terminals include: PDA, MID, and UMPC devices, etc., such as ipads.
(3) A portable entertainment device: such devices can display and play multimedia content. This type of device comprises: audio, video players (e.g., ipods), handheld game consoles, electronic books, and smart toys and portable car navigation devices.
(4) And other electronic equipment with data interaction function.
Thus, particular embodiments of the present subject matter have been described. Other embodiments are within the scope of the following claims. In some cases, the actions recited in the claims can be performed in a different order 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 be advantageous.
The apparatuses and modules 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. The functionality of the various elements may be implemented in the same one or more software and/or hardware implementations in practicing the disclosure.
As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present disclosure 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 present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the disclosure. 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.
As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present disclosure 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 disclosure 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 transactions or implement particular abstract data types. The present disclosure may also be practiced in distributed computing environments where transactions 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 disclosure and is not intended to limit the present disclosure. Various modifications and variations of this disclosure will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure should be included in the scope of the claims of the present disclosure.
Claims (10)
1. A method for adjusting data, comprising:
acquiring historical data of promotion parameters of a promotion target, wherein the promotion parameters are used for indicating promotion effects and promotion costs of the promotion target;
predicting the promotion parameters according to the historical data to obtain predicted values of the promotion parameters;
determining a comprehensive change rate and an amplitude change rate of the promotion parameters according to the predicted values of the promotion parameters and the historical data, wherein the comprehensive change rate is used for indicating the change trend of the promotion parameters, and the amplitude change rate is used for indicating the change amplitude of the promotion parameters; and
adjusting the bidding of the promotion target according to the comprehensive change rate and the amplitude change rate of the promotion parameters;
the adjusting the bidding of the promotion target according to the comprehensive change rate and the amplitude change rate of the promotion parameters comprises the following steps:
determining an adjustment strategy of the bidding of the promotion target according to at least one of the comprehensive change rate and the amplitude change rate;
adjusting the bid price of the promotion target according to the adjustment strategy and the amplitude modulation rate, wherein the amplitude modulation rate is used for indicating the adjustment amplitude of the bid price of the promotion target, the adjustment strategy comprises a cost strategy and an effect strategy, the cost strategy is a strategy for controlling cost, and the effect strategy is a strategy for improving promotion effect;
the determining an adjustment strategy of the bidding of the promotion target according to at least one of the comprehensive change rate and the amplitude change rate comprises the following steps:
determining a cost strategy as the adjustment strategy in response to the overall rate of change and the indication of the rate of change of amplitude that the cost increase value of the promotion objective is greater than the effect increase value of the promotion objective; and
and responding to the comprehensive change rate and the amplitude change rate indication, wherein the effect reduction value of the promotion target is larger than the cost reduction value of the promotion target, and determining an effect strategy as the adjustment strategy.
2. The method according to claim 1, wherein the predicting the promotion parameter according to the historical data to obtain a predicted value of the promotion parameter includes:
calculating the historical data of the promotion parameters according to a clustering algorithm to obtain at least two classification intervals of the promotion parameters;
based on the at least two classification intervals, calculating historical data of the promotion parameters according to a classification algorithm to predict the classification interval of the promotion parameters at a preset time in the future; and
and taking the predicted classification interval as the predicted value of the promotion parameter.
3. The method of claim 1, wherein determining the aggregate rate of change and the amplitude rate of change of the promotion parameter based on the predicted value of the promotion parameter and the historical data comprises:
determining the comprehensive change rate based on the predicted value of the promotion parameter and the historical data; and
and determining the amplitude change rate based on the predicted value of the promotion parameter and the true value of the current moment.
4. The method of claim 3, wherein determining the aggregate rate of change based on the predicted values for the promotion parameters and the historical data comprises:
according to the predicted value and the historical data of the promotion parameter, determining the same-ratio change rate of the historical preset time period of the promotion parameter and the ring ratio change rate of the previous preset time of the current preset time period; and
and taking the weighted value of the same-ratio change rate and the ring-ratio change rate as the comprehensive change rate.
5. The method according to claim 3, wherein the determining the amplitude change rate based on the predicted value of the promotion parameter and the true value of the current time comprises:
obtaining a difference value between the predicted value of the promotion parameter and the true value of the current moment; and
and taking the ratio of the difference value to the amplitude value of the classification interval in which the promotion parameter is positioned as the amplitude change rate.
6. The method of claim 1, further comprising:
and determining the amplitude modulation rate of the bidding of the promotion target based on the current bidding and the bidding upper limit of the promotion target.
7. The method of claim 1, wherein the promotion parameters include: one or more of click through volume, click through rate, and promotional cost.
8. A data conditioning apparatus, comprising:
the system comprises an acquisition module, a display module and a display module, wherein the acquisition module is configured to acquire historical data of promotion parameters of a promotion target, and the promotion parameters are used for indicating promotion effects and promotion costs of the promotion target;
the prediction module is configured to predict the promotion parameters according to the historical data to obtain predicted values of the promotion parameters;
the determining module is configured to determine a comprehensive change rate and an amplitude change rate of the promotion parameters according to the predicted values of the promotion parameters and the historical data, wherein the comprehensive change rate is used for indicating the change trend of the promotion parameters, and the amplitude change rate is used for indicating the change amplitude of the promotion parameters; and
the adjusting module is configured to adjust the bidding of the promotion target according to the comprehensive change rate and the amplitude change rate of the promotion parameters;
wherein the adjustment module is further configured to:
in response to the comprehensive rate of change and the indication of the amplitude rate of change, determining a cost strategy as an adjustment strategy, wherein the cost increase value of the promotion target is greater than the effect increase value of the promotion target; and determining an effect strategy as the adjustment strategy in response to the overall rate of change and the indication of the rate of change of amplitude that the effect reduction value of the promotion objective is greater than the cost reduction value of the promotion objective; and adjusting the bidding price of the promotion target according to the adjustment strategy and the amplitude modulation rate, wherein the amplitude modulation rate is used for indicating the adjustment amplitude of the bidding price of the promotion target, the adjustment strategy can comprise a cost strategy and an effect strategy, the cost strategy is a strategy for controlling the cost, and the effect strategy is a strategy for improving the promotion effect.
9. An electronic device, comprising:
at least one processor; and the number of the first and second groups,
a memory for storing a plurality of data to be transmitted,
wherein the memory stores at least one program that, when executed by the at least one processor, causes the at least one processor to implement the data adjustment method of any one of claims 1-7.
10. A computer-readable storage medium, having stored thereon a computer program which, when executed by a processor, causes the processor to carry out a data adjustment method according to any one of claims 1 to 7.
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| US20170046749A1 (en) * | 2015-07-30 | 2017-02-16 | Venkateswarlu Kolluri | One-click promotional advertising |
| CN111340561A (en) * | 2020-03-04 | 2020-06-26 | 深圳前海微众银行股份有限公司 | Information click rate calculation method, device, equipment and readable storage medium |
| CN111598631A (en) * | 2020-06-05 | 2020-08-28 | 上海智子信息科技股份有限公司 | Cross-channel keyword price optimization method with effect target oriented |
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| CN104851023A (en) * | 2015-05-07 | 2015-08-19 | 容一飞 | Real-time bidding online feedback control method and system |
| CN109034445A (en) * | 2018-06-08 | 2018-12-18 | 广东红海湾发电有限公司 | A kind of market-oriented electric power management system and method |
| CN111105269A (en) * | 2019-11-29 | 2020-05-05 | 北京云测信息技术有限公司 | Advertisement putting processing method, device, equipment and storage medium |
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