CN113743703A - Information processing method and device and storage medium - Google Patents
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Abstract
The embodiment of the invention discloses an information processing method, an information processing device and a storage medium, wherein the information processing method comprises the steps of obtaining adjustment information of a target object, historical data distribution information of the target object and expected data of the target object in the current time period; determining initial distribution data corresponding to the next time period from the expected data according to the historical data distribution information and the adjustment information; determining the target competition participation probability of the target object in the next time slot according to the adjustment information, the initial distribution data, the initial competition participation probability and the time slot information; the initial competition-participating probability is the competition-participating probability of the target object in the current time period, and the time period information comprises the current time period and the next time period; and executing the participation process of the target object according to the target participation probability when the next time period is reached.
Description
Technical Field
The present invention relates to the field of information processing technologies, and in particular, to an information processing method and apparatus, and a storage medium.
Background
In recent years, with the development of internet technology, information of a target object can be promoted and advertised by using the internet technology, and a series of problems are caused.
In the prior art, when expected data of a target object is acquired, the expected data is averagely distributed according to the number of preset time periods to obtain average expected data, so that the target object is publicized and promoted according to the average expected data in each preset time period, the amount of user feedback data acquired when the target object is processed by using the average expected data is small, and the accuracy of processing the target object is reduced.
Disclosure of Invention
In order to solve the above technical problem, embodiments of the present invention are directed to providing an information processing method and apparatus, and a storage medium, which can improve accuracy when an information processing apparatus processes a target object.
The technical scheme of the invention is realized as follows:
an embodiment of the present application provides an information processing method, including:
acquiring adjustment information of a target object in a current time period, historical data distribution information of the target object and expected data of the target object;
according to the historical data distribution information and the adjustment information, determining initial distribution data corresponding to the next time period from the expected data;
determining the target competition participation probability of the target object in the next time slot according to the adjustment information, the initial distribution data, the initial competition participation probability and the time slot information; the initial competition participation probability is the competition participation probability of the target object in the current time period, and the time period information comprises the current time period and the next time period; and executing the participation process of the target object according to the target participation probability when the next time period is reached.
An embodiment of the present application provides an information processing apparatus, the apparatus including:
the device comprises an acquisition unit, a storage unit and a processing unit, wherein the acquisition unit is used for acquiring adjustment information of a target object in the current time period, historical data distribution information of the target object and expected data of the target object;
the determining unit is used for determining initial distribution data corresponding to the next time period from the expected data according to the historical data distribution information and the adjustment information; determining the target competition participation probability of the target object in the next time slot according to the adjustment information, the initial distribution data, the initial competition participation probability and the time slot information of the target object; the initial competition participation probability is the competition participation probability of the target object in the current time period, and the time period information comprises the current time period and the next time period; and executing the participation process of the target object according to the target participation probability when the next time period is reached.
An embodiment of the present application provides an information processing apparatus, the apparatus including:
the information processing system includes a memory, a processor, and a communication bus, the memory communicating with the processor through the communication bus, the memory storing an information processing program executable by the processor, and the processor executing the information processing method when the information processing program is executed.
The embodiment of the application provides a storage medium, which stores a computer program thereon and is applied to an information processing device, wherein the computer program is used for realizing the information processing method when being executed by a processor.
The embodiment of the invention provides an information processing method, an information processing device and a storage medium, wherein the information processing method comprises the following steps: acquiring adjustment information of a target object, historical data distribution information of the target object and expected data of the target object in the current time period; determining initial distribution data corresponding to the next time period from the expected data according to the historical data distribution information and the adjustment information; determining the target competition participation probability of the target object in the next time slot according to the adjustment information, the initial distribution data, the initial competition participation probability and the time slot information; the initial competition-participating probability is the competition-participating probability of the target object in the current time period, and the time period information comprises the current time period and the next time period; and executing the participation process of the target object according to the target participation probability when the next time period is reached. By adopting the method implementation scheme, the information processing device determines the initial distribution data of the target object from the expected data of the target object according to the adjustment information and the historical data distribution information of the target object by acquiring the adjustment information of the target object, and determines the target competition participation probability of the target object in the next time period according to the adjustment information, the initial distribution data, the initial competition participation probability and the time period information, so that the competition participation process of the target object in the next time period is executed according to the target competition participation probability, the feedback data volume of a user is increased, and the accuracy of the information processing device in processing the target object is improved.
Drawings
Fig. 1 is a flowchart of an information processing method according to an embodiment of the present application;
fig. 2 is a flowchart of an exemplary information processing method provided in an embodiment of the present application;
fig. 3 is a first schematic diagram illustrating a composition structure of an information processing apparatus according to an embodiment of the present disclosure;
fig. 4 is a schematic diagram illustrating a composition structure of an information processing apparatus according to an embodiment of the present application.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In the online advertising industry, the intelligent bid products ocpx (e.g., ocpc, ocpm, oca, tcpa) are products in the marketplace where advertiser usage and revenue size are large. In intelligent bidding products, the system automatically adjusts bids based on conversion effectiveness, an indicator of interest to the advertiser is the output/input ratio. When the investment cost of an advertiser is fixed, how to improve the output is a very worthy of research, and the common benefits of the platform and the advertiser can be optimized. Taking e-commerce advertisers as an example, usually, the advertiser pays attention to the target of placing an order, and the delivered advertisements are expected to bring as many orders as possible. However, the budget of a single advertiser is usually limited, and optimizing the output/input ratio is optimizing the effectiveness of ad placement under budget constraints (see below).
The budget of an advertiser is generally day-level consumption expected to stably deliver the advertisement according to own funds and delivery experience, but for the ocpx product, the advertisement delivery must pass through a cold start stage at the beginning, the data accumulation of the advertisement at the stage is less, the effect is not stable yet, the data accumulation needs to be performed by using a lower budget firstly, and after the threshold of data confidence is reached, the normal delivery stage is entered. In order to handle the special situation of cold start, the method adjusts the day budget set by the advertiser according to the released time length and the effect on the basis of the budget set by the advertiser.
In the normal delivery stage, the delivery effect of the advertisement is closely related to the traffic quality, and the distribution of the traffic quality is not uniform in the day, so the budget in the day should be allocated in proportion to the traffic quality. The general method is to allocate more budgets in the time period with good traffic quality, allocate less budgets in the time period with poor traffic quality, determine the budget in the current time period in advance, and calculate the competitive probability in the current time period through the budget in the current time period to control the traffic. The simplest method is to divide one day into 24 time slots according to hours, distribute the budget of the advertiser to each hour evenly, no more flow exists in the hour after the budget of the hour is spent, and take the flow with a certain participation probability under the new budget condition to the next hour again so as to ensure that the budget is smoothly spent in one day. Another budget allocation method is to allocate the advertiser budget according to the flow distribution of yesterday or the last few days, so as to ensure that the flow peak budget is high, and the advertiser can take more at the flow peak. A third approach is to have a dynamically adjusted flow control, i.e. to determine the budget and the participation probability for the next time period based on the ratio of the actual cost and the budget for the previous time period.
Current flow control techniques have some inherent drawbacks. If the particularity of the advertisement putting cold start stage is not considered, the advertisement with insufficient data accumulation is directly subjected to budget regulation. And like the technology of flow control per hour by allocating budget averagely according to hours, although the stable cost of budget is ensured, the situations that the budget is exhausted in a few hours and the flow cannot be taken in the later period are avoided, the averagely allocating method cannot allocate the budget according to the flow quality so as to control the flow, and is not suitable for an advertiser paying attention to the effect. Techniques for allocating budgets based on historical traffic distribution improve this problem so that advertisers can take more traffic at high traffic peaks, which are high traffic volumes, and the quality of the traffic may still be erratic and not very reliable in ensuring the effectiveness of the advertisement. At present, the most dynamically-adjusted flow control technology is applied to each large company, that is, the budget and the competition-participating probability of the next time period are determined according to the ratio of the actual cost to the budget of the previous time period, and the basic idea is that the flow distribution is continuously changed, the previous time period costs much, and the next time period allocates more budget. Although this method can quickly adjust the budget and the competition-participating probability according to the traffic distribution, the problem that the traffic quantity and the quality are not synchronous is still not considered.
Example one
An embodiment of the present application provides an information processing method, and fig. 1 is a first flowchart of the information processing method provided in the embodiment of the present application, and as shown in fig. 1, the information processing method may include:
s101, acquiring adjustment information of the target object in the current time period, historical data distribution information of the target object and expected data of the target object.
The information processing method provided by the embodiment of the application is suitable for the situation that the information processing device determines the target participation probability of the target object.
In the embodiment of the present application, the information processing apparatus may be implemented in various forms. For example, the information processing apparatus described in the present application may include apparatuses such as a mobile phone, a camera, a tablet computer, a notebook computer, a palmtop computer, a Personal Digital Assistant (PDA), a Portable Media Player (PMP), a navigation apparatus, a wearable device, a smart band, a pedometer, and the like, and apparatuses such as a Digital TV, a desktop computer, and the like.
In this embodiment of the present application, the target object may be an advertisement, specifically, the target object may be a clothing advertisement, may also be a food advertisement, and the target object may also be an advertisement of other goods, which may be specifically determined according to an actual situation, and this is not limited in this embodiment of the present application.
In this embodiment of the present application, if the target object is an advertisement, the target object may be an advertisement played on a tremble platform, may also be an advertisement played on a jingdong platform, and may also be an advertisement played on another platform, which may be specifically determined according to an actual situation, and this is not limited in this embodiment of the present application.
In the embodiment of the present application, in a Real Time Bidding (RTB) advertisement, whether an advertisement unit participates in Bidding at this Time is determined according to a Bidding probability.
In this embodiment, the adjustment information of the target object may be information obtained according to the current historical expected data and the current historical consumption information of the target object.
In the embodiment of the present application, the historical data allocation information may be a ratio between a total value of allocation information of the target object at the same time point in a past period of time and a total value of expected data of the target object in the past period of time.
For example, if the same time point is 8-9 points, the historical data allocation information may be data allocation information of the target object at 8-9 points per day in the past 5 days, if the data allocation information of the target object at 8-9 points per day in the past 5 days is 500 yuan, and if the expected data in the past 5 days is 2000 yuan, the historical data allocation information is a ratio between the data allocation information of the target object at 8-9 points per day in the past 5 days and the expected data in the past 5 days, that is, the historical data allocation information is 500: 2000: 1: 4.
In the embodiment of the present application, the expected data of the target object may be the expected spending information of the target object in the current day. For example, if the information processing apparatus acquires that the expected cost for the target object in one day is 2000 yuan, the desired data of the target object is 2000 yuan.
In the embodiment of the present application, the information processing apparatus needs to allocate the daily expected data of the target object to determine a plurality of time period cost information corresponding to a plurality of time periods within one day of the target object.
It should be noted that, a plurality of time periods correspond to a plurality of time period cost information in a one-to-one correspondence, where one time period corresponds to one time period cost information.
For example, the information processing apparatus may divide one day by hours to obtain 24 time periods, each of which has a duration of one hour.
In the embodiment of the present application, the information processing apparatus may calculate the initial allocation data and the target participation probability at a preset time point of each time period.
For example, the information processing apparatus may start calculating the initial allocation data and the target participation probability at an integral point of each time period; the information processing apparatus may also start calculating the initial allocation data and the target participation probability at 59 minutes of each time period; the information processing apparatus may also start to calculate the initial allocation data and the target bidding probability at other time points of each time period, which may be determined according to actual situations, and this is not limited in this embodiment of the application.
In this embodiment, the information processing apparatus may generate an acquisition instruction of the bid participation probability at a preset time point of each time period, and then the information processing apparatus may calculate the initial distribution data and the target bid participation probability according to the acquisition instruction of the bid participation probability.
In the embodiment of the application, before the information processing device acquires the adjustment information of the target object in the current time period, the information processing device also acquires the historical consumption information, the historical feedback quantity and the historical expected consumption information of the target object; the information processing device determines initial adjustment information according to the historical consumption information, the historical feedback quantity and the historical expected consumption information; the information processing device performs proportional and differential processing on the initial adjustment information to obtain adjustment information.
In this embodiment, in the present embodiment, the information processing apparatus determines the process of initial adjustment information according to the historical consumption information, the historical feedback quantity, and the historical expected consumption information, may obtain a quotient of the historical consumption information and the historical feedback quantity for the information processing apparatus to obtain the actual cost information of the target object, and then the information processing apparatus determines the difference between the actual cost information of the target object and the historical expected consumption information; the difference is divided by the historical expected consumption information to obtain adjustment information.
In the embodiment of the present application, the information processing apparatus determines the procedure of initial adjustment information based on the historical consumption information, the historical feedback amount, and the historical expected consumption information, as shown in equations (1) to (2):
cpa_diff＝(cpa-tcpa)/tcpa (1)
cpa＝cost/order_num (2)
wherein cpa _ diff is initial adjustment information; the cost is historical consumption information, namely current consumption information of the target object on the current day; order _ num is the historical feedback quantity, namely the current order quantity of the target object in the current day; tcpa is historical expected consumption information, i.e., historical expected cost per action (target cost per action) information of the target object; cpa is the actual cost per action information of the target object.
It should be noted that the meaning of cpa _ diff is in the dimension of transformation, i.e. the difference between cpa (actual cost) and tcpa (expected cost) of a single transformation. If cpa _ diff is greater than 0, it indicates that the actual cost is greater than the expected cost, and belongs to the over-cost state, and if cpa _ diff is less than or equal to 0, it indicates that the actual cost is less than the expected cost, and it is generally referred to as the achievement state.
It should be noted that, if the advertisement unit of the current target object is in an over-cost state, it indicates that the conversion amount brought by the current traffic is less than the expectation of the advertiser, the traffic quality cannot meet the demand of the advertiser, and the traffic quality is poor. If the current advertisement unit is in the achievement state, the conversion amount brought by the current flow is larger than or equal to the expectation of the advertiser, and the flow quality is good. The basic idea of ensuring the unit effect is that the amount is more when the flow quality is good, the amount is less when the flow quality is poor, and the budget is distributed to the time slot with good flow quality as much as possible on the premise that the cost in one day does not exceed the budget of an advertiser, so that the single conversion cost is as small as possible, and the advertising unit achieves the purpose as much as possible.
In the embodiment of the present application, the information processing apparatus performs proportional and differential processing on the initial adjustment information, as shown in formula (3):
delta＝c1*cpa_diff1+c2*(cpa_diff1-cpa_diff2) (3)
here, cpa _ diff1 is initial adjustment information, c1 cpa _ diff1 is a process in which the information processing apparatus performs a proportional process on the initial adjustment information, c2 (cpa _ diff1-cpa _ diff2) is a process in which the information processing apparatus performs a differential process on the initial adjustment information, and the information processing apparatus sums the process in which the initial adjustment information is subjected to the proportional process and the process in which the initial adjustment information is subjected to the differential process, thereby obtaining adjustment information.
It should be noted that cpa _ diff2 is initial adjustment information determined by an information processing apparatus in a time period, and cpa _ diff1-cpa _ diff2 is a difference value between two adjacent initial adjustment information determined by the information processing apparatus, and is used for representing a variation trend of the initial adjustment information; c1 is a first preset hyper-parameter when the information processing apparatus performs proportional processing on the initial adjustment information, and c2 is a second preset hyper-parameter when the information processing apparatus performs differential processing on the initial adjustment information.
It should be further noted that the first preset hyper-parameter and the second preset hyper-parameter are preset values and are values configured in the information processing apparatus, and the first preset hyper-parameter and the second preset hyper-parameter may also be values received before the information processing apparatus performs proportional and differential processing on the initial adjustment information, which may be determined specifically according to actual situations, and this is not limited in the embodiment of the present application.
In the embodiment of the present application, the information processing apparatus may determine the adjustment information once at intervals based on the historical consumption information, the historical expected consumption, and the historical expected consumption information. The time length of the period of time may be 1 minute, may also be 1s, may also be 0.5ms, and may also be other time lengths, which may be determined specifically according to actual situations, and this is not limited in this application.
And S102, determining initial distribution data corresponding to the next time period from the expected data according to the historical data distribution information and the adjustment information.
In the embodiment of the application, after the information processing device acquires the adjustment information of the target object, the historical data allocation information of the target object and the expected data of the target object in the current time period, the information processing device determines the initial allocation data corresponding to the next time period from the expected data according to the historical data allocation information and the adjustment information.
In an embodiment of the present application, a process of determining initial allocation data corresponding to a next time period from expected data according to historical data allocation information and adjustment information by an information processing apparatus includes: in the case where the historical consumption information of the target object is less than or equal to a preset threshold, the information processing apparatus determines initial distribution data from the desired data in accordance with the historical distribution information; acquiring a preset adjustment coefficient of a target object under the condition that the historical consumption information is larger than a preset threshold value; the information processing apparatus determines initial distribution data from the desired data based on the adjustment information, the historical data distribution information, and a preset adjustment coefficient.
It should be noted that the preset threshold is a threshold preset in the information processing apparatus, may be a threshold received by the information processing apparatus before the information processing apparatus determines the initial allocation data corresponding to the next time period from the expected data according to the historical data allocation information and the adjustment information, and may also be a threshold configured in the information processing apparatus, which may be determined specifically according to the actual situation, and the embodiment of the present application does not limit this.
In the embodiment of the present application, in a case that the historical consumption information is greater than the preset threshold, the information processing apparatus determines the process of initially allocating data according to the adjustment information, the expected data, and the historical data allocation information, and may obtain a product between a preset adjustment coefficient and the adjustment information for the information processing apparatus, then obtain a difference between the expected data and the product for the information processing apparatus, and finally determine a product between the historical data allocation information and the difference, thereby obtaining the initially allocated data.
In the embodiment of the present application, the information processing apparatus determines the procedure of initially allocating data according to the adjustment information, the expected data, and the historical data allocation information, as shown in formula (4):
hour_target＝(total_target-ADJUST_RATA*delta)*hour_rate (4)
wherein, the total _ target is the expected data of the target object; delta is adjustment information of a target object, specifically, the current cumulative delivery effect of a unit; the hour _ rate allocates information to the history data of the target object, that is: the hourly flow proportion of the large disk flow over the past n days; the method comprises the steps that a hour _ target is initial distribution data of a target object; the ADJUST _ RATA is a preset adjustment coefficient, i.e. a preset hyper-parameter, for adjusting the effect of the delivery effect on the preset adjustment, when the unit is expected to move greatly on the budget (expected data) of the advertiser, the value of the preset hyper-parameter is larger, and when the unit is expected to move less on the budget (expected data) of the advertiser, the value of the hyper-parameter is smaller.
S103, determining the target competition participation probability of the target object in the next time slot according to the adjustment information, the initial distribution data, the initial competition participation probability and the time slot information; the initial competition-participating probability is the competition-participating probability of the target object in the current time period, and the time period information comprises the current time period and the next time period; and executing the participation process of the target object according to the target participation probability when the next time period is reached.
In the embodiment of the application, after the information processing apparatus determines the initial distribution data corresponding to the next time slot from the expected data according to the historical data distribution information and the adjustment information, the information processing apparatus may determine the target competition probability of the target object in the next time slot according to the adjustment information, the initial distribution data, the initial competition probability and the time slot information.
It should be noted that the initial competition participating probability is the competition participating probability of the target object in the current time period; the time period information includes a current time period and a next time period.
In the embodiment of the application, the information processing device determines that the target competition participation probability of the target object in the next time slot is prior to the target competition participation probability of the target object according to the adjustment information, the initial distribution data, the initial competition participation probability and the time slot information, and the information processing device also obtains the time slot information, the preset adjustment step length and the initial competition participation probability of the target object; wherein the time period information includes current consumption information of the target object in a current time period. Correspondingly, the process that the information processing device determines the target competition participation probability of the target object in the next time slot according to the adjustment information, the initial distribution data, the initial competition participation probability and the time slot information comprises the following steps: the information processing device adjusts the initial distribution data according to the current consumption information, the adjustment information and a preset adjustment step length to obtain adjusted distribution data; and the information processing device determines the target participation probability according to the adjusted distribution data, the initial participation probability and the time period information.
In this embodiment of the present application, a process in which an information processing apparatus adjusts initial allocation data according to current consumption information, adjustment information, and a preset adjustment step length to obtain adjusted allocation data includes: the information processing device firstly obtains a product between a preset adjustment step length and adjustment information, and then obtains a difference value between a numerical value 1 and the product; the information processing apparatus obtains the target participation probability by obtaining a product between the initial distribution data and the difference value.
In the embodiment of the present application, the information processing apparatus determines a process of the adjusted distribution data according to the current consumption information, the initial distribution data, the adjustment information, and the preset adjustment step length, as shown in formula (5):
new_target＝old_target*(1-UPDATE_RATE*delta) (5)
wherein, the new _ target is the adjusted distribution data, namely the budget adjusted this time; old _ target is initial distribution data, namely budget before the adjustment; delta is the adjustment information of the target object; the UPDATE _ RATE is a preset adjustment step size, i.e., a hyper-parameter, which is a value configured in the information processing apparatus.
It should be noted that the UPDATE _ RATE indicates the adjustment step size, and the cold start phase and the normal phase are set separately. In particular, the first and second coating materials are,
a. the 0 o' clock initialization is adjusted on the hourly target consumption generated by day-level statistics, and on the last hourly target consumption at normal operation (non-cold start phase).
b. The new unit is adjusted on the preset hourly target consumption when it first enters the hourly target consumption adjustment.
UPDATE _ RATE can be set separately during up and down-regulation, and during cold start and normal phases to adapt to different situations, UPDATE _ RATE _ INC (hourly target consumption up adjustment step size), UPDATE _ RATE _ DEC (hourly target consumption down adjustment step size).
d. In order to avoid drastic changes of budget in adjacent time periods, the method sets the maximum amplitude of single adjustment, INCR _ RATE _ MAX (single upward adjustment maximum amplitude consumed by an hour target) and DECR _ RATE _ MAX (single downward adjustment maximum amplitude consumed by an hour target), and sets the upper and lower adjustment amplitudes in the cold start stage and the normal stage respectively.
In this embodiment of the present application, a process in which an information processing apparatus adjusts initial allocation data according to current consumption information, adjustment information, and a preset adjustment step length to obtain adjusted allocation data includes: the information processing device screens out target data with the maximum data value from the initial distribution data and the current consumption information; and the information processing device adjusts the target data by using the adjustment information and the preset adjustment step length to obtain the adjusted distribution data.
In this embodiment of the present application, the adjusting step includes a cold start adjusting step and a non-cold start adjusting step, and the information processing apparatus adjusts the target data by using the adjusting information and the preset adjusting step to obtain a process of adjusted distribution data, including: under the condition that the historical consumption information of the target object is smaller than or equal to a preset threshold value, adjusting the target data by using the adjustment information and the cold start adjustment step length to obtain adjusted distribution data; and under the condition that the historical consumption information is larger than the preset threshold value, adjusting the target data by using the adjustment information and the non-cold start adjustment step length to obtain adjusted distribution data.
It should be noted that the non-cold start adjustment step size is larger than the cold start adjustment step size.
In this embodiment of the present application, the process of determining the target participation probability by the information processing apparatus according to the adjusted distribution data, the initial participation probability, and the time period information includes: the information processing device determines a consumption error according to the time period information and the adjusted distribution data; the information processing device determines a target participation probability according to the initial participation probability, the consumption error and the current consumption information.
The time zone information includes current consumption information, a time span of the current time zone, a time span of the next time zone, and adjusted allocation data (target consumption of the next time zone).
It should be further noted that, the current consumption information: at 0 o' clock initialization each day: consumption from point 0 to the current time of day. And (3) during normal operation: consumption of the last time the program run ended timestamp to the current time.
It should also be noted that the time span of the current time period is: at 0 o' clock initialization each day: timestamp-0 point of the latest data that can be fetched. And (3) during normal operation: timestamp of the latest data that can be fetched-timestamp of the end of the last program run.
It should be further noted that, the adjusted allocation data: current hour target consumption-current hour cumulative consumption; time span of next time period: the length of the time from the current time to the next nearest hour.
In the embodiment of the present application, the process of determining the consumption error by the information processing apparatus according to the time period information and the adjusted distribution data includes determining a ratio of a time span of a next time period to a time span of a current time period by the information processing apparatus, then obtaining a product of the current consumption information and the ratio by the information processing apparatus, and finally obtaining the consumption error by the information processing apparatus according to a difference between the adjusted distribution data and the product.
As shown in equation (6):
residual＝c_next-c_last*(tm_next/tm_last) (6)
wherein, residual is a consumption error, and c _ next is adjusted distribution data c _ last, tm _ next, and tm _ last which are consumption information. Specifically, c _ last is the current consumption information, i.e., the actual cost of the current time window; tm _ next is the time span of the next time segment; tm _ last is the time span of the current time period.
In the embodiment of the present application, the information processing apparatus determines a first participation probability according to the initial participation probability, the consumption error and the current consumption information, as shown in formula (7):
r_next＝r_last*(c_last+residual)/c_last (7)
wherein, r _ last is the initial competition-participating probability, residual is the consumption error, c _ last is the current consumption information, and r _ next is the first competition-participating probability.
In the embodiment of the application, the process of determining the target participation probability by the information processing device according to the initial participation probability, the consumption error and the current consumption information comprises the steps of determining a first participation probability by the information processing device according to the initial participation probability, the consumption error and the current consumption information; screening the target competition participation probability with the maximum competition participation probability value from the first competition participation probability and the initial competition participation probability under the condition that the historical consumption information of the target object is smaller than or equal to a preset threshold value; and under the condition that the historical consumption information is larger than a preset threshold value, taking the first competition participation probability as a target competition participation probability.
It should be noted that, when the information processing apparatus determines that the historical consumption information of the target object is less than or equal to the preset threshold, the target object is in a cold start stage; and under the condition that the historical consumption information of the target object is determined to be larger than the preset threshold value, the target object is in a non-cold starting stage, namely the target object is in a normal putting stage.
It can be understood that, when the advertisement unit is in the cold start phase, the information processing device selects the maximum participation probability with the maximum participation probability value from the first participation probability and the initial participation probability as the target participation probability, so that the target participation probability is not adjusted downwards, and the data can be accumulated as soon as possible to enter the normal delivery phase.
It should be noted that, the value range of the target participation probability is 0 to 1, and the information processing device may randomly discard the flow in the next time period according to the target participation probability, thereby achieving the purpose of controlling the cost guarantee effect.
Illustratively, as shown in fig. 2, an embodiment of the present application provides a flowchart of an exemplary information processing method:
1. the information processing apparatus acquires historical consumption information, a historical feedback amount, and historical expected consumption information of a target object.
2. The information processing apparatus determines initial adjustment information based on the historical consumption information, the historical feedback amount, and the historical expected consumption information.
3. The information processing device performs proportional and differential processing on the initial adjustment information to obtain adjustment information.
4. The information processing apparatus acquires adjustment information of a target object in a current time period, historical data allocation information of the target object, and desired data of the target object.
5. In the case where the historical consumption information of the target object is less than or equal to the preset threshold, the information processing apparatus determines initial distribution data from the desired data in accordance with the historical distribution information.
6. In the case where the historical consumption information is greater than the preset threshold value, the information processing apparatus acquires a preset adjustment coefficient of the target object.
After step 4, the information processing apparatus may execute step 5 or may execute step 6.
7. The information processing apparatus determines initial distribution data from the desired data based on the adjustment information, the historical data distribution information, and a preset adjustment coefficient.
8. The information processing device acquires time period information, preset adjustment step length and initial competition participation probability of the target object.
It should be noted that step 8 may be directly performed after step 5; step 8 may also be performed after step 7.
It should be noted that the time period information includes current consumption information of the target object in the current time period.
9. The information processing device screens out target data having the largest data value from the initial allocation data and the current consumption information.
10. And under the condition that the historical consumption information of the target object is less than or equal to the preset threshold, the information processing device adjusts the target data by utilizing the adjustment information and the cold start adjustment step length to obtain the adjusted distribution data.
11. And under the condition that the historical consumption information is larger than the preset threshold value, the information processing device adjusts the target data by using the adjustment information and the non-cold-start adjustment step length to obtain adjusted distribution data.
After step 9, the information processing apparatus may execute step 10 or may execute step 11.
12. The information processing apparatus determines a consumption error based on the time period information and the adjusted distribution data.
It should be noted that step 12 may be directly performed after step 10; step 12 may also be performed after step 11.
13. The information processing device determines a first participation probability according to the initial participation probability, the consumption error and the current consumption information.
14. In the case where the historical consumption information of the target object is less than or equal to the preset threshold, the information processing apparatus screens a target participation probability having the highest participation probability value from among the first participation probability and the initial participation probability.
15. And in the case that the historical consumption information is larger than a preset threshold value, the information processing device takes the first competition participation probability as a target competition participation probability.
After step 13, the information processing apparatus may execute step 14 or may execute step 15.
It can be understood that the adjustment information of the target object is offline data information, the historical data distribution information of the target object, the expected data of the target object, the initial competition participation probability, the time period information and the like are real-time data information, the information processing device distributes the expected data of the target object by using the offline data information and the real-time data information to determine the target competition participation probability of the target object in the next time period, and when the next time period arrives, the competition participation process of the target object is executed according to the target competition participation probability, so that the information processing device can achieve the effect of minute level and continuously process the target object by taking minutes as a unit.
By performing online verification on the off-site advertising tcpa product in the method of the present application, the absolute value of the effect boost on the unit consuming confidence is shown in table 1:
TABLE 1 test data comparison table
| Cell achievement rate | Achievement rate of consumption | |
| Value of lift | 1.40％ | 4.80％ |
The method is adopted by the experimental group, the method is not adopted by the control group, the flow of the experimental group is consistent with that of the control group, and the other variables are consistent.
The unit achievement rate is the number of achieved units/total units, which is the most interesting index for advertisers.
The achievement rate of consumption, which is the achievement unit consumption/total consumption, is the most interesting index for the platform.
The experimental result shows that the method of the invention has positive effect, can be correctly realized and normally used in an industrial system, and has positive effect on the actual advertisement putting.
It can be understood that, the information processing apparatus determines initial distribution data of the target object from the expected data of the target object according to the adjustment information of the target object and the historical data distribution information, and determines the target competition probability of the target object in the next time period according to the adjustment information, the initial distribution data, the initial competition probability and the time period information, so as to execute the competition participation process of the target object in the next time period according to the target competition probability, increase the feedback data amount of the user, and improve the accuracy of the information processing apparatus in processing the target object.
Example two
Based on the idea of the invention together with the embodiments, the embodiments of the present application provide an information processing apparatus 1 corresponding to an information processing method; fig. 3 is a schematic diagram illustrating a first configuration of an information processing apparatus according to an embodiment of the present application, where the information processing apparatus 1 may include:
an obtaining unit 11, configured to obtain adjustment information of a target object in a current time period, historical data allocation information of the target object, and expected data of the target object;
a determining unit 12, configured to determine initial distribution data corresponding to a next time period from the expected data according to the historical data distribution information and the adjustment information; determining the target competition participation probability of the target object in the next time slot according to the adjustment information, the initial distribution data, the initial competition participation probability and the time slot information of the target object; the initial competition participation probability is the competition participation probability of the target object in the current time period, and the time period information comprises the current time period and the next time period; and executing the participation process of the target object according to the target participation probability when the next time period is reached.
In some embodiments of the present application, the apparatus further comprises a processing unit;
the acquiring unit 11 is configured to acquire historical consumption information, historical feedback quantity, and historical expected consumption information of the target object;
the determining unit 12 is configured to determine initial adjustment information according to the historical consumption information, the historical feedback quantity, and the historical expected consumption information;
and the processing unit is used for carrying out proportional and differential processing on the initial adjustment information to obtain the adjustment information.
In some embodiments of the present application, the apparatus further comprises an adjustment unit;
the obtaining unit 11 is configured to obtain time period information of the target object, a preset adjustment step length, and the initial competition participation probability, where the time period information includes current consumption information of the target object in a current time period;
correspondingly, the adjusting unit is configured to adjust the initial distribution data according to the current consumption information, the adjustment information, and the preset adjustment step length, so as to obtain adjusted distribution data;
the determining unit 12 is configured to determine the target auction participation probability according to the adjusted distribution data, the initial auction participation probability, and the time period information.
In some embodiments of the present application, the apparatus further comprises a screening unit;
the screening unit is used for screening out target data with the maximum data value from the initial distribution data and the current consumption information;
and the adjusting unit is used for adjusting the target data by using the adjusting information and the preset adjusting step length to obtain the adjusted distribution data.
In some embodiments of the present application, the preset adjustment step includes a cold start adjustment step and a non-cold start adjustment step;
the adjusting unit is configured to adjust the target data by using the adjustment information and the cold start adjustment step length to obtain the adjusted distribution data when the historical consumption information of the target object is less than or equal to a preset threshold; under the condition that the historical consumption information is larger than a preset threshold value, adjusting the target data by using the adjustment information and the non-cold-start adjustment step length to obtain the adjusted distribution data; the non-cold start adjustment step size is greater than the cold start adjustment step size.
In some embodiments of the present application, the determining unit 12 is configured to determine a consumption error according to the time period information and the adjusted distribution data; and determining the target competition participation probability according to the initial competition participation probability, the consumption error and the current consumption information.
In some embodiments of the present application, the determining unit 12 is configured to determine a first participation probability according to the initial participation probability, the consumption error and the current consumption information;
the screening unit is used for screening the target competition probability with the maximum competition probability value from the first competition participation probability and the initial competition participation probability under the condition that the historical consumption information of the target object is smaller than or equal to a preset threshold value; and taking the first participation probability as the target participation probability under the condition that the historical consumption information is larger than a preset threshold value.
In some embodiments of the present application, the obtaining unit 11 is configured to obtain a preset adjustment coefficient of the target object when the historical consumption information of the target object is greater than a preset threshold;
the determining unit 12 is configured to determine the initial distribution data from the expected data according to the adjustment information, the historical data distribution information, and the preset adjustment coefficient; and determining the initial distribution data from the expected data according to the historical distribution information when the historical consumption information is less than or equal to the preset threshold.
In practical applications, the obtaining Unit 11 and the determining Unit 14 may be implemented by a processor 13 on the information Processing apparatus 1, specifically implemented by a Central Processing Unit (CPU), an MPU (Microprocessor Unit), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), or the like; the above data storage may be realized by the memory 14 on the information processing apparatus 1.
An embodiment of the present invention further provides an information processing apparatus 1, and as shown in fig. 4, the information processing apparatus 1 includes: a processor 13, a memory 14 and a communication bus 15, the memory 14 communicating with the processor 13 through the communication bus 15, the memory 14 storing a program executable by the processor 13, the program, when executed, executing the information processing method as described above through the processor 13.
In practical applications, the Memory 14 may be a volatile Memory (volatile Memory), such as a Random-Access Memory (RAM); or a non-volatile Memory (non-volatile Memory), such as a Read-Only Memory (ROM), a flash Memory (flash Memory), a Hard Disk (Hard Disk Drive, HDD) or a Solid-State Drive (SSD); or a combination of the above types of memories and provides instructions and data to the processor 13.
An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, which, when executed by the processor 13, implements the information processing method as described above.
It can be understood that, the information processing apparatus determines initial distribution data of the target object from the expected data of the target object according to the adjustment information of the target object and the historical data distribution information, and determines the target competition probability of the target object in the next time period according to the adjustment information, the initial distribution data, the initial competition probability and the time period information, so as to execute the competition participation process of the target object in the next time period according to the target competition probability, increase the feedback data amount of the user, and improve the accuracy of the information processing apparatus in processing the target object.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention 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, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. 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.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention.
Claims (11)
1. An information processing method, characterized in that the method comprises:
acquiring adjustment information of a target object in a current time period, historical data distribution information of the target object and expected data of the target object;
according to the historical data distribution information and the adjustment information, determining initial distribution data corresponding to the next time period from the expected data;
determining the target competition participation probability of the target object in the next time slot according to the adjustment information, the initial distribution data, the initial competition participation probability and the time slot information; the initial competition participation probability is the competition participation probability of the target object in the current time period, and the time period information comprises the current time period and the next time period; and executing the participation process of the target object according to the target participation probability when the next time period is reached.
2. The method of claim 1, wherein before the obtaining the adjustment information of the target object in the current time period, the method further comprises:
acquiring historical consumption information, historical feedback quantity and historical expected consumption information of the target object;
determining initial adjustment information according to the historical consumption information, the historical feedback quantity and the historical expected consumption information;
and carrying out proportional and differential processing on the initial adjustment information to obtain the adjustment information.
3. The method of claim 1, wherein the determining the target bidding probability of the target object in the next time slot is performed according to the adjustment information, the initial allocation data, the initial bidding probability and the time slot information, and further comprising:
acquiring time period information, a preset adjustment step length and the initial competition participation probability of the target object, wherein the time period information comprises current consumption information of the target object in the current time period;
correspondingly, the determining the target competition participation probability of the target object in the next time slot according to the adjustment information, the initial distribution data, the initial competition participation probability and the time slot information includes:
adjusting the initial distribution data according to the current consumption information, the adjustment information and the preset adjustment step length to obtain adjusted distribution data;
and determining the target competition participation probability according to the adjusted distribution data, the initial competition participation probability and the time period information.
4. The method according to claim 3, wherein the adjusting the initial distribution data according to the current consumption information, the adjustment information, and the preset adjustment step size to obtain adjusted distribution data comprises:
screening out target data with the maximum data value from the initial distribution data and the current consumption information;
and adjusting the target data by using the adjustment information and the preset adjustment step length to obtain the adjusted distribution data.
5. The method according to claim 4, wherein the preset adjustment step includes a cold start adjustment step and a non-cold start adjustment step, and the adjusting the target data by using the adjustment information and the preset adjustment step to obtain the adjusted distribution data includes:
under the condition that the historical consumption information of the target object is smaller than or equal to a preset threshold value, adjusting the target data by using the adjustment information and the cold start adjustment step length to obtain the adjusted distribution data;
under the condition that the historical consumption information is larger than a preset threshold value, adjusting the target data by using the adjustment information and the non-cold-start adjustment step length to obtain the adjusted distribution data; the non-cold start adjustment step size is greater than the cold start adjustment step size.
6. The method of claim 3, wherein determining the target bid participation probability according to the adjusted distribution data, the initial bid participation probability and the time period information comprises:
determining a consumption error according to the time period information and the adjusted distribution data;
and determining the target competition participation probability according to the initial competition participation probability, the consumption error and the current consumption information.
7. The method of claim 6, wherein determining the target bid participation probability based on the initial bid participation probability, the consumption error, and the current consumption information comprises:
determining a first participation probability according to the initial participation probability, the consumption error and the current consumption information;
screening the target competition participation probability with the maximum competition participation probability value from the first competition participation probability and the initial competition participation probability under the condition that the historical consumption information of the target object is smaller than or equal to a preset threshold value;
and taking the first participation probability as the target participation probability under the condition that the historical consumption information is larger than a preset threshold value.
8. The method of claim 1, wherein determining initial allocation data corresponding to a next time period from the expected data according to the historical data allocation information and the adjustment information comprises:
determining the initial distribution data from the expected data according to the historical distribution information under the condition that the historical consumption information of the target object is less than or equal to a preset threshold value;
acquiring a preset adjustment coefficient of the target object under the condition that the historical consumption information is larger than a preset threshold value;
and determining the initial distribution data from the expected data according to the adjustment information, the historical data distribution information and the preset adjustment coefficient.
9. An information processing apparatus characterized in that the apparatus comprises:
the device comprises an acquisition unit, a storage unit and a processing unit, wherein the acquisition unit is used for acquiring adjustment information of a target object in the current time period, historical data distribution information of the target object and expected data of the target object;
the determining unit is used for determining initial distribution data corresponding to the next time period from the expected data according to the historical data distribution information and the adjustment information; determining the target competition participation probability of the target object in the next time slot according to the adjustment information, the initial distribution data, the initial competition participation probability and the time slot information of the target object; the initial competition participation probability is the competition participation probability of the target object in the current time period, and the time period information comprises the current time period and the next time period; and executing the participation process of the target object according to the target participation probability when the next time period is reached.
10. An information processing apparatus characterized in that the apparatus comprises:
a memory, a processor, and a communication bus, the memory in communication with the processor through the communication bus, the memory storing an information processing program executable by the processor, the information processing program when executed causing the processor to perform the method of any of claims 1 to 8.
11. A storage medium having stored thereon a computer program for application to an information processing apparatus, characterized in that the computer program, when executed by a processor, implements the method of any one of claims 1 to 8.
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