CN109741088B - Advertisement hit rate estimation method, estimation device and server - Google Patents
Advertisement hit rate estimation method, estimation device and server Download PDFInfo
- Publication number
- CN109741088B CN109741088B CN201811524281.5A CN201811524281A CN109741088B CN 109741088 B CN109741088 B CN 109741088B CN 201811524281 A CN201811524281 A CN 201811524281A CN 109741088 B CN109741088 B CN 109741088B
- Authority
- CN
- China
- Prior art keywords
- advertisement
- preset
- client
- hit rate
- total
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Landscapes
- Information Transfer Between Computers (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The embodiment of the invention provides an advertisement hit rate estimation method, an advertisement hit rate estimation device and a server. In the method, aiming at each preset client, when each advertisement played by the preset client is monitored, whether the advertisement data of the advertisement is contained in a server cache corresponding to the preset client is judged, wherein the data in the server cache is set based on a target advertisement pre-distribution strategy of the advertisement hit rate to be estimated; updating the total advertisement putting times and the total advertisement hit times corresponding to each preset client according to the judgment result; calculating the advertisement hit rate corresponding to the target advertisement pre-distribution strategy based on the current total advertisement putting times and the total advertisement hit times; and when the preset estimation finishing condition is met, determining the advertisement hit rate estimation result of the target advertisement pre-distribution strategy according to the calculated advertisement hit rates. Therefore, the advertisement hit rate corresponding to the target advertisement pre-distribution strategy can be effectively estimated through the scheme.
Description
Technical Field
The invention relates to the technical field of internet, in particular to an advertisement hit rate estimation method, an estimation device and a server.
Background
At present, the situation of playing advertisements in a client of a video playing class is common. Generally, in order to not affect the speed of playing a feature film video and ensure that advertisement materials can be normally loaded, a server can issue an advertisement material list to a client according to an advertisement pre-distribution strategy; then, the client selects and caches the advertisement materials in the advertisement material list to the local in the process of watching the feature video by the user. Therefore, when the client plays the advertisement subsequently, the client can determine whether the advertisement material of the advertisement to be played is cached locally from the local cache, if so, the advertisement is directly played, and if not, the advertisement material is downloaded from the server in real time.
However, the inventor finds that the prior art has at least the following problems in the process of implementing the invention:
since what advertisement is played by the client for the user is determined according to the current user and the information such as the video watched by the user, once the advertisement pre-distribution strategy used by the server is not appropriate, the advertisement hit rate of the advertisement material pre-cached by the client is low, that is, only a small part of the advertisement material pre-cached by the client is played by the client. Thus, the data traffic of the user is wasted, and various local resources and network resources consumed for realizing the advertisement pre-distribution strategy are wasted. Therefore, the advertisement pre-distribution policy needs to be evaluated to decide whether the advertisement pre-distribution policy is appropriate.
When the advertisement pre-distribution strategy is evaluated, the advertisement hit rate corresponding to the advertisement pre-distribution strategy is an extremely important evaluation index. Therefore, how to effectively estimate the advertisement hit rate of the advertisement pre-distribution strategy is an urgent problem to be solved.
Disclosure of Invention
The embodiment of the invention aims to provide an advertisement hit rate estimation method, an advertisement hit rate estimation device and a server, so as to effectively estimate the advertisement hit rate of an advertisement pre-distribution strategy. The specific technical scheme is as follows:
an advertisement hit rate estimation method is applied to a server and comprises the following steps:
monitoring each predetermined client; each preset client uniquely corresponds to one server cache, and the server cache corresponding to each preset client is at least used for storing: when the preset distribution condition is met, advertisement data is set for the preset client based on a target advertisement pre-distribution strategy of the advertisement hit rate to be estimated;
aiming at each preset client, when each advertisement is monitored to be played by the preset client, judging whether the server cache corresponding to the preset client contains the advertisement data of the advertisement or not, updating the total advertisement putting times and the total advertisement hit times corresponding to each preset client according to a judgment result, and calculating the advertisement hit rate corresponding to the target advertisement pre-distribution strategy based on the current total advertisement putting times and the total advertisement hit times after updating;
and when a preset estimation end condition is met, determining an advertisement hit rate estimation result corresponding to the target advertisement pre-distribution strategy according to the calculated advertisement hit rates corresponding to the target advertisement pre-distribution strategy.
Optionally, the method further comprises:
and for each preset client, when the preset client is detected to meet the preset distribution condition, downloading advertisement data from a preset advertisement library to a server cache corresponding to the preset client according to the target advertisement pre-distribution strategy.
Optionally, the method further comprises:
and if so, storing the advertisement data corresponding to the advertisement into a server cache corresponding to the preset client.
Optionally, the detecting that the predetermined client meets the predetermined distribution condition includes:
and monitoring that the preset client requests a pre-distribution service from a pre-distribution server corresponding to the preset client.
Optionally, the updating the total advertisement delivery times and the total advertisement hit times corresponding to each predetermined client according to the determination result includes:
when the judgment result is yes, adding 1 to the total advertisement putting times and the total advertisement hit times corresponding to each preset client;
and when the judgment result is negative, adding 1 to the total advertisement putting times, and keeping the total advertisement hitting times unchanged.
Optionally, the calculating an advertisement hit rate corresponding to the target advertisement pre-distribution policy based on the current total number of advertisement impressions and the total number of advertisement hits includes:
and dividing the total number of times of the current advertisement hit by the total number of times of the current advertisement putting to obtain the advertisement hit rate corresponding to the target advertisement pre-distribution strategy.
Optionally, the preset predicted end condition includes:
receiving an estimated ending instruction input by a user; or
The preset estimated ending time comes; or
And the total number of times of advertisement putting reaches a preset number threshold.
An advertisement hit rate estimation device applied to a server, the device comprising: the device comprises a monitoring module, a calculating module and a determining module;
the monitoring module is used for monitoring each preset client; each preset client uniquely corresponds to one server cache, and the server cache corresponding to each preset client is at least used for storing: when the preset distribution condition is met, advertisement data is set for the preset client based on a target advertisement pre-distribution strategy of the advertisement hit rate to be estimated;
the calculation module is used for judging whether the server cache corresponding to the preset client contains the advertisement data of the advertisement or not when the preset client is monitored to play each advertisement aiming at each preset client, updating the total advertisement putting times and the total advertisement hit times corresponding to each preset client according to the judgment result, and calculating the advertisement hit rate corresponding to the target advertisement pre-distribution strategy based on the current total advertisement putting times and the total advertisement hit times after updating;
and the determining module is used for determining the advertisement hit rate estimation result corresponding to the target advertisement pre-distribution strategy according to each advertisement hit rate corresponding to the target advertisement pre-distribution strategy obtained through calculation when the preset estimation end condition is met.
Optionally, the apparatus further comprises: a downloading module;
and the downloading module is used for downloading the advertisement data from the preset advertisement library to the server cache corresponding to each preset client according to the target advertisement pre-distribution strategy when detecting that the preset client meets the preset distribution condition.
Optionally, the apparatus further comprises: a storage module;
and the storage module is used for storing the advertisement data corresponding to the advertisement into the server cache corresponding to the preset client when the judgment result of the calculation module is yes.
Optionally, the detecting that the predetermined client meets the predetermined distribution condition includes:
and monitoring that the preset client requests a pre-distribution service from a pre-distribution server corresponding to the preset client.
Optionally, the updating, by the computing module, the total number of advertisement impressions and the total number of advertisement hits corresponding to each of the predetermined clients according to the determination result includes:
when the judgment result of the calculation module is yes, adding 1 to the total advertisement putting times and the total advertisement hit times corresponding to each client;
and when the judgment result of the calculation module is negative, adding 1 to the total advertisement putting times, and keeping the total advertisement hitting times unchanged.
Optionally, the calculating module calculates the advertisement hit rate corresponding to the target advertisement pre-distribution policy based on the current total number of advertisement impressions and the total number of advertisement hits, and includes:
and dividing the total number of the current advertisement hits by the total number of the current advertisement putting times to obtain the advertisement hit rate corresponding to the target advertisement pre-distribution strategy.
Optionally, the preset predicted end condition includes:
receiving an estimated ending instruction input by a user; or
The preset estimated ending time comes; or
And the total number of times of advertisement putting reaches a preset number threshold.
A server comprises a processor, a communication interface, a memory and a communication bus, wherein the processor and the communication interface are used for realizing the communication between the processor and the memory through the communication bus;
a memory for storing a computer program;
and the processor is used for realizing the method steps of any advertisement hit rate estimation method when executing the program stored in the memory.
In yet another aspect of the present invention, there is also provided a computer-readable storage medium having stored therein instructions, which when executed on a computer, cause the computer to perform the method steps of any of the above advertisement hit rate estimation methods.
In yet another aspect of the present invention, the present invention also provides a computer program product containing instructions, which when run on a computer, causes the computer to perform the method steps of any of the above advertisement hit rate estimation methods.
The advertisement hit rate estimation method provided by the embodiment of the invention simulates the local cache of the preset client by constructing the server cache corresponding to each online preset client in the offline server, wherein the server cache stores advertisement data set by a target advertisement pre-distribution strategy based on the advertisement hit rate to be estimated, and further obtains the advertisement hit rate estimation result corresponding to the target advertisement pre-distribution strategy based on the comparison between the constructed server cache and the advertisement actually played by the preset client. Therefore, the advertisement hit rate estimation method provided by the embodiment of the invention can effectively estimate the advertisement hit rate of the target advertisement pre-distribution strategy, and further can provide reference for an evaluator of the target advertisement pre-distribution strategy in a link of evaluating the target advertisement pre-distribution strategy.
In addition, the advertisement hit rate estimation method provided by the embodiment of the invention only needs to monitor each preset client in the whole process of estimating the advertisement hit rate of the target advertisement pre-distribution strategy, and does not affect the advertisement played by each preset client and the advertisement pre-distribution strategy of the pre-distribution server corresponding to each preset client on line. Of course, it is not necessary for any product or method of practicing the invention to achieve all of the above-described advantages at the same time.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below.
Fig. 1 is a flowchart of an advertisement hit rate estimation method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an advertisement hit rate estimation apparatus according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a server according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention.
In order to effectively estimate the advertisement hit rate of an advertisement pre-distribution strategy, the embodiment of the invention provides an advertisement hit rate estimation method, an estimation device and a server.
It should be noted that the advertisement hit rate estimation method, the estimation device and the server provided by the embodiments of the present invention are used for estimating the advertisement hit rate of the target advertisement pre-distribution strategy. In the process of estimating the advertisement hit rate of the target advertisement pre-distribution strategy, the estimated advertisement hit rate of the target advertisement pre-distribution strategy is obtained by simulating and using the target advertisement pre-distribution strategy. In the process of simulating the use of the target advertisement pre-distribution strategy, the target advertisement pre-distribution strategy is not applied to the advertisement putting process of the client, and the advertisement putting of the client is still controlled by the advertisement pre-distribution strategy used by the pre-distribution server corresponding to the client, so the process of simulating the use of the target advertisement pre-distribution strategy is called the on-line simulation of the application of the target advertisement pre-distribution strategy; the process of pre-distributing advertisement data for the client by applying the advertisement pre-distribution strategy used by the pre-distribution server to the pre-distribution server corresponding to the client is called an online application advertisement pre-distribution strategy; the advertisement pre-distribution strategy used by the pre-distribution server is called as an online advertisement pre-distribution strategy, so that the online condition and the offline condition are distinguished in the process of describing the advertisement hit rate estimation method, the estimation device and the server provided by the embodiment of the invention in detail.
In addition, when the advertisement hit rate of the target advertisement predistribution strategy is estimated by using the advertisement hit rate estimating method, the estimating device and the server provided by the embodiment of the invention, a part of online clients are required to be selected as predetermined clients so as to simulate the application of the target advertisement predistribution strategy online. It should be noted that the selected advertisement played by the predetermined client is not affected by the target advertisement pre-distribution strategy. This can be seen in the course of the following detailed description of the invention.
The following describes a method, an apparatus and a server for estimating a hit rate of an advertisement according to an embodiment of the present invention in detail.
In a first aspect, a method for estimating an advertisement hit rate provided by an embodiment of the present invention is described in detail.
It should be noted that the execution subject of the advertisement hit rate estimation method provided by the embodiment of the present invention may be an advertisement hit rate estimation device, and the estimation device may be applied to a server. In a specific application, the server may be a specific server, or may be a server cluster formed by a plurality of servers.
As shown in fig. 1, an advertisement hit rate estimation method provided by an embodiment of the present invention includes the following steps:
s101: each subscribing client is monitored.
Each preset client uniquely corresponds to one server cache, and the server cache corresponding to each preset client is at least used for storing: and when the preset distribution condition is met, advertisement data is set for the preset client based on a target advertisement pre-distribution strategy of the advertisement hit rate to be estimated.
It will be appreciated that any client software that can play an advertisement may serve as the subscribing client. For example, the predetermined client may be video playing client software, audio playing client software, or game client software. Of course, instead of selecting a part of clients on the line as the predetermined clients, a test terminal or a test server installed with client software may be used to simulate the predetermined clients.
In addition, there are various selection modes of the clients on the selection line as the predetermined clients. Illustratively, the user id may be hashed and then modulo. For example, a client of a user having a hash (user _ id) mod 100 ═ 1 may be selected as the predetermined client. Here, hash is a hash algorithm, also called hash algorithm, which is an algorithm for converting an input of an arbitrary length into an output of a fixed length.
It should be noted that, the execution subject of a series of actions of detecting the predetermined distribution condition and setting the advertisement data for the predetermined client based on the target advertisement pre-distribution strategy of the advertisement hit rate to be estimated may be the advertisement hit rate estimation device or other devices besides the estimation device. When detecting that the predetermined client meets the predetermined distribution condition, the other device may determine the advertisement data corresponding to the predetermined client according to a target advertisement pre-distribution strategy of the advertisement hit rate to be pre-estimated, and store the advertisement data in the server cache corresponding to the predetermined client. For clarity of the scheme and clarity of layout, a specific implementation mode that the advertisement hit rate pre-estimation device detects a predetermined distribution condition and sets advertisement data for a predetermined client based on a target advertisement pre-distribution strategy of the advertisement hit rate to be pre-estimated is illustrated subsequently. It should be noted that the server cache may be a cache on a pre-distribution server corresponding to each predetermined client line, or may be a cache on a server to which an advertisement hit rate estimation device is applied, in addition to the pre-distribution servers. It can be understood that the server cache of the predetermined client is not infinite, but has an upper cache limit, and therefore, when the server cache of the predetermined client reaches the upper cache limit, the least recently used LRU principle may be adopted to delete part of the advertisement data in the server cache, that is, delete the least recently used advertisement data, and make up storage space for the newly stored advertisement data. For example, the server cache of each predetermined client may be set to only cache a predetermined number of advertisement data, and when the number of advertisement data in the server cache reaches an upper limit, old advertisement data in the server cache is deleted by using the LRU principle. It can be understood that, when deleting advertisement data in the server cache, a manner that several new advertisement data need to be cached and several old advertisement data are deleted correspondingly may be adopted.
S102: and aiming at each preset client, when each advertisement is played by the preset client, judging whether the server cache corresponding to the preset client contains the advertisement data of the advertisement or not, updating the total advertisement putting times and the total advertisement hit times corresponding to each preset client according to the judgment result, and calculating the advertisement hit rate corresponding to the target advertisement pre-distribution strategy based on the current total advertisement putting times and the total advertisement hit times after updating.
The advertisement data of the advertisement played by the preset client and the advertisement data set in the server cache can be advertisement material id, or advertisement material id plus the advertisement material, and the advertisement material can be video, picture or animation and the like.
In this step, there are various specific embodiments for determining whether the server cache corresponding to the predetermined client contains the advertisement data of the advertisement played by the predetermined client. For example, the advertisement material id of the advertisement played by the predetermined client may be compared with the advertisement material id stored in the server cache, so as to obtain the determination result.
It can be understood that, the estimated advertisement hit rate is not accurate enough by only counting the advertisement putting times and the advertisement hit times of a predetermined client. Therefore, the total number of advertisement impressions and the total number of advertisement hits are counted as the total number of advertisement impressions and the total number of advertisement hits of a plurality of predetermined clients.
In addition, since the advertisement data in the server cache corresponding to each predetermined client is set based on the target advertisement pre-distribution strategy, when the server cache corresponding to one predetermined client contains the advertisement data of the advertisement played by the predetermined client, the advertisement is hit on the behalf of the advertisement data set based on the target advertisement pre-distribution strategy. Accordingly, the total number of advertisement hits for the targeted advertisement predistribution strategy needs to be updated. Of course, each time such a determination is made for an advertisement played by a predetermined client, the total number of advertisement impressions also needs to be updated.
It can be understood that, in the embodiment of the present invention, the server cache is used to simulate the local cache of the client, and accordingly, whether the advertisement data in the server cache hits the advertisement played by the predetermined client is determined, and whether the local cache of the client hits the scene of the advertisement played by the client is also determined in the case of simulating the online advertisement pre-distribution policy.
And subsequently, a specific implementation mode of updating the total advertisement putting times and the total advertisement hitting times corresponding to each preset client according to the judgment result and calculating the advertisement hitting rate corresponding to the target advertisement pre-distribution strategy based on the current total advertisement putting times and the total advertisement hitting times is introduced for the sake of clear layout and clear scheme.
S103: and when the preset estimation end condition is met, determining an advertisement hit rate estimation result corresponding to the target advertisement pre-distribution strategy according to the calculated advertisement hit rates corresponding to the target advertisement pre-distribution strategy.
Since the advertisement hit rate of the target advertisement pre-distribution strategy is recalculated every time an advertisement is monitored to be played by a predetermined client in step S102, the operation of calculating the advertisement hit rate of the target advertisement pre-distribution strategy is continuously performed. At this time, in step S103, a predicted ending condition may be preset to terminate the continuous calculation. For clarity of the scheme and clarity of layout, the predetermined estimated ending condition is illustrated later.
It can be understood that the data size of each advertisement hit rate of the calculated target advertisement pre-distribution strategy is huge. The advertisement hit rate obtained by the last calculation, the total advertisement putting times and the total advertisement hit times are more in statistical quantity, and the estimated result is more reliable. Therefore, in an implementation manner, the step of determining an advertisement hit rate estimation result corresponding to the target advertisement pre-distribution policy according to each calculated advertisement hit rate corresponding to the target advertisement pre-distribution policy may include:
and determining the advertisement hit rate corresponding to the target advertisement pre-distribution strategy obtained by the last calculation as an advertisement hit rate estimation result corresponding to the target advertisement pre-distribution strategy.
In addition, in the step of evaluating the target advertisement pre-distribution strategy by an evaluator of the target advertisement pre-distribution strategy, the evaluator can compare each calculated advertisement hit rate with an expected advertisement hit rate or with advertisement hit rates of other advertisement pre-distribution strategies, so as to evaluate the target advertisement pre-distribution strategy. Therefore, in another implementation manner, the step of determining the advertisement hit rate estimation result corresponding to the target advertisement pre-distribution policy according to each calculated advertisement hit rate corresponding to the target advertisement pre-distribution policy may include:
and determining part of the advertisement hit rate which is obtained by calculation and corresponds to the target advertisement pre-distribution strategy and meets the preset screening condition as an advertisement hit rate estimation result corresponding to the target advertisement pre-distribution strategy.
For example, the predetermined filtering condition may be: the corresponding calculation time point is located in a preset time period, or the total number of advertisement putting and the total number of advertisement hitting are based on the preset number, and the like.
The advertisement hit rate estimation method provided by the embodiment of the invention simulates the local cache of the preset client by constructing the server cache corresponding to each preset client on each line in the offline server, wherein the server cache stores advertisement data generated by a target advertisement pre-distribution strategy based on the advertisement hit rate to be estimated, and further obtains the advertisement hit rate estimation result corresponding to the target advertisement pre-distribution strategy based on the comparison between the constructed server cache and the advertisement actually played by the preset client. Therefore, the advertisement hit rate estimation method provided by the embodiment of the invention can effectively estimate the advertisement hit rate of the target advertisement pre-distribution strategy, and further can provide reference for an evaluator of the target advertisement pre-distribution strategy in a link of evaluating the target advertisement pre-distribution strategy.
In addition, the advertisement hit rate estimation method provided by the embodiment of the invention only needs to monitor each preset client in the whole process of estimating the advertisement hit rate of the target advertisement pre-distribution strategy, and does not affect the advertisement played by each preset client and the advertisement pre-distribution strategy of the pre-distribution server corresponding to each preset client on line.
For clarity of the scheme and clear layout, the following illustrates a specific implementation manner in which the advertisement hit rate estimation device detects a predetermined distribution condition and sets advertisement data for a predetermined client based on a target advertisement pre-distribution strategy of the advertisement hit rate to be estimated.
Under the condition that the advertisement hit rate estimation device detects a preset distribution condition and sets advertisement data for a preset client based on a target advertisement pre-distribution strategy of the advertisement hit rate to be estimated, the advertisement hit rate estimation method provided by the embodiment of the invention can further comprise the following steps:
and for each preset client, downloading advertisement data from a preset advertisement library to a server cache corresponding to the preset client according to a target advertisement pre-distribution strategy when the preset distribution condition is detected to be met.
Here, the predetermined advertisement library may be a server on the content delivery network CDN. The advertisement data is downloaded from the CDN, so that bottlenecks and links which possibly influence the data transmission speed and stability on the Internet can be avoided, and the data transmission is faster and more stable.
In addition, the advertisement hit rate estimation device has various specific implementation modes for downloading advertisement data from a preset advertisement library to a server cache corresponding to a preset client according to a target advertisement pre-distribution strategy.
For example, a server applying the pre-estimation device may construct a pre-distribution request to request a corresponding pre-distribution service, then obtain an advertisement material list delivered by the pre-distribution service, and download corresponding advertisement data according to the content recorded in the advertisement material list. When the pre-distribution request is constructed, the advertisement material list issued by the target advertisement pre-distribution strategy can be constructed according to one or more monitored online data of each preset client, and correspondingly, the advertisement material list issued based on the constructed pre-distribution request is also issued. Wherein the online data may include: the system comprises a user id of a reservation client, information of whether a user of the reservation client is a high-level user VIP, a video id played by the reservation client, classification information of videos played by the reservation client, a network protocol IP address of a terminal device where the reservation client is located, development platform information of reservation client software, operating system version information of the reservation client software, an advertisement order id played by the reservation client, a request time of the reservation client for requesting to play an advertisement, pre-distribution service request information of the reservation client and the like.
It will be appreciated that the steps of constructing the pre-distribution request, requesting the pre-distribution service, obtaining the list of advertisement material, and downloading the advertisement data described above may all be performed by the server. For example, each step may be implemented by a single module of a server, or may be implemented by multiple modules of the server in cooperation. In addition, the steps may also be implemented by a server cluster composed of a plurality of servers, where each step may be implemented by one server in the server cluster, or may be implemented by cooperation of a plurality of servers in the server cluster.
In addition, optionally, in a case where the advertisement hit rate estimation device detects a predetermined distribution condition, and sets advertisement data for a predetermined client based on a target advertisement pre-distribution policy of the advertisement hit rate to be estimated, the advertisement hit rate estimation method provided in the embodiment of the present invention may further include:
in step S102, if the determination result is yes, the advertisement data corresponding to the advertisement played by the predetermined client is stored in the server cache corresponding to the predetermined client.
In practical applications, when a client plays a video or a series of videos, the advertisements played correspondingly are often the same advertisement. Therefore, the advertisement played by the predetermined client is stored in the server cache corresponding to the predetermined client, and when the next advertisement is played by the predetermined client, the next advertisement played by the predetermined client can be hit approximately.
In addition, there are a plurality of kinds of predetermined distribution conditions, and the predetermined distribution conditions are exemplified below.
Optionally, the predetermined distribution condition may include:
and monitoring that the preset client requests a pre-distribution service from a pre-distribution server corresponding to the preset client.
In practical application, whether a predetermined client requests a pre-distribution server corresponding to the predetermined client for pre-distribution service is determined, which may be determined according to pre-distribution service request information of the predetermined client in monitored online data when the predetermined client is monitored.
In addition, there are various kinds of pre-distribution service request information of a predetermined client. For example, the pre-distribution service request information of the predetermined client may include: the predetermined client requests the request information of the pre-patch advertisement.
The above is an exemplary illustration of a specific embodiment of detecting a predetermined distribution condition by an advertisement hit rate estimation means and setting advertisement data for a predetermined client based on a target advertisement pre-distribution policy of an advertisement hit rate to be estimated.
In order to make the layout clear and the scheme clear, the following introduces a specific implementation manner of updating the total advertisement delivery times and the total advertisement hit times corresponding to each predetermined client according to the judgment result, and calculating the advertisement hit rate corresponding to the target advertisement pre-distribution strategy based on the current total advertisement delivery times and the current total advertisement hit times.
Optionally, in a specific implementation manner, updating the total number of advertisement impressions and the total number of advertisement hits corresponding to each predetermined client according to the determination result may include:
when the judgment result is yes, adding 1 to the total advertisement putting times and the total advertisement hit times corresponding to each client;
and when the judgment result is negative, adding 1 to the total advertisement putting times, and keeping the total advertisement hitting times unchanged.
It is understood that, when the determination result is negative, the server cache of the predetermined client does not hit the advertisement played by the predetermined client, and thus, the total number of advertisement impressions is increased by 1 while keeping the total number of advertisement hits unchanged.
Therefore, the total times of advertisement putting and the total times of advertisement hitting are updated based on the real hitting situation, so that the result obtained by statistics after updating is real and effective.
In addition, calculating the advertisement hit rate corresponding to the target advertisement pre-distribution strategy based on the current total number of advertisement impressions and the total number of advertisement hits may include:
and dividing the updated total times of the advertisement hits by the updated total times of the advertisement putting to obtain the advertisement hit rate corresponding to the target advertisement pre-distribution strategy.
For clarity of the scheme and clarity of layout, the predetermined estimated ending condition is exemplified below.
Optionally, the preset predicted end condition may include:
receiving an estimated ending instruction input by a user; or
The preset estimated ending time comes; or
The total number of advertisement putting times reaches a preset time threshold value.
It can be understood that, when the user considers that the calculated advertisement hit rate is sufficient to accurately estimate the advertisement hit rate of the target advertisement pre-distribution strategy, an instruction for estimating the end may be input to stop calculating the advertisement hit rates of the target advertisement pre-distribution strategies. It should be noted that, the user here is not a user who intends to use the client, but a user who estimates the advertisement hit rate of the target advertisement pre-distribution policy by applying the advertisement hit rate estimation method provided by the embodiment of the present invention, and may be, for example, a designer or a tester of the target advertisement pre-distribution policy.
In addition, a timer can be set when the estimation is started, and when the timing of the timer is finished, namely the preset estimation end time comes, the calculation of each advertisement hit rate of the target advertisement pre-distribution strategy is finished.
Furthermore, a threshold value of the total number of target advertisement impressions may be preset at the beginning of estimation, so as to limit the upper limit of the total number of advertisement impressions. And when the total number of times of advertisement putting reaches the threshold value, finishing calculating each advertisement hit rate of the target advertisement pre-distribution strategy.
It can be understood that the three preset estimation end conditions can all realize the calculation of enough advertisement hit rate data, so that the advertisement hit rate of the target advertisement pre-distribution strategy can be accurately estimated.
In a second aspect, a device for estimating an advertisement hit rate according to an embodiment of the present invention is described in detail. As shown in fig. 2, the advertisement hit rate estimation apparatus provided in the embodiment of the present invention includes: a monitoring module 201, a calculation module 202 and a determination module 203.
The monitoring module 201 is configured to monitor each predetermined client; each preset client uniquely corresponds to one server cache, and the server cache corresponding to each preset client is at least used for storing: and when the preset distribution condition is met, advertisement data is set for the preset client based on a target advertisement pre-distribution strategy of the advertisement hit rate to be estimated.
And the calculating module 202 is configured to, for each predetermined client, when it is monitored that each advertisement is played by the predetermined client, determine whether advertisement data of the advertisement is included in a server cache corresponding to the predetermined client, update the total advertisement delivery times and the total advertisement hit times corresponding to each predetermined client according to a determination result, and calculate an advertisement hit rate corresponding to the target advertisement pre-distribution policy based on the current total advertisement delivery times and the current total advertisement hit times after the update.
The determining module 203 is configured to determine an advertisement hit rate estimation result corresponding to the target advertisement pre-distribution strategy according to each advertisement hit rate corresponding to the calculated target advertisement pre-distribution strategy when a preset estimation end condition is met.
Optionally, the device for estimating advertisement hit rate provided in the embodiment of the present invention may further include: a downloading module;
the downloading module is used for downloading advertisement data from a preset advertisement library to a server cache corresponding to each preset client according to the target advertisement pre-distribution strategy when detecting that the preset distribution conditions are met.
Optionally, the device for estimating advertisement hit rate provided in the embodiment of the present invention may further include: a storage module;
and the storage module is used for storing the advertisement data corresponding to the advertisement into the server cache corresponding to the preset client when the judgment result of the calculation module is yes.
Optionally, the detecting that the predetermined client meets the predetermined distribution condition may include:
and monitoring that the preset client requests a pre-distribution service from a pre-distribution server corresponding to the preset client.
Optionally, the updating, by the calculation module, the total number of advertisement impressions and the total number of advertisement hits corresponding to each of the predetermined clients according to the determination result may include:
when the judgment result of the calculation module is yes, adding 1 to the total advertisement putting times and the total advertisement hit times corresponding to each client;
and when the judgment result of the calculation module is negative, adding 1 to the total advertisement putting times, and keeping the total advertisement hitting times unchanged.
Optionally, the calculating module calculates the advertisement hit rate corresponding to the target advertisement pre-distribution policy based on the current total number of advertisement impressions and the total number of advertisement hits, and may include:
and dividing the total number of the current advertisement hits by the total number of the current advertisement putting times to obtain the advertisement hit rate corresponding to the target advertisement pre-distribution strategy.
Optionally, the preset predicted end condition may include:
receiving an estimated ending instruction input by a user; or
The preset estimated ending time comes; or
The total number of advertisement putting times reaches a preset time threshold value.
The advertisement hit rate estimation device provided by the embodiment of the invention simulates the local cache of the preset client by constructing the server cache corresponding to each preset client on each line in the server under the line, wherein the server cache stores advertisement data generated by a target advertisement pre-distribution strategy based on the advertisement hit rate to be estimated, and further obtains the advertisement hit rate estimation result corresponding to the target advertisement pre-distribution strategy based on the comparison between the constructed server cache and the advertisement actually played by the preset client. Therefore, the advertisement hit rate estimation device provided by the embodiment of the invention can effectively estimate the advertisement hit rate of the target advertisement pre-distribution strategy, and further can provide reference for an evaluator of the target advertisement pre-distribution strategy in a link of evaluating the target advertisement pre-distribution strategy.
In addition, the advertisement hit rate estimation device provided in the embodiment of the present invention only needs to monitor each predetermined client in the whole process of estimating the advertisement hit rate of the target advertisement pre-distribution strategy, and does not affect the advertisement played by each predetermined client, nor the advertisement pre-distribution strategy of the pre-distribution server corresponding to each predetermined client on line.
In a third aspect, an embodiment of the present invention further provides a server, as shown in fig. 3, including a processor 301, a communication interface 302, a memory 303, and a communication bus 304, where the processor 301, the communication interface 302, and the memory 303 complete communication with each other through the communication bus 304;
a memory 303 for storing a computer program;
the processor 301, when executing the program stored in the memory 303, implements the following steps:
monitoring each predetermined client; each preset client uniquely corresponds to one server cache, and the server cache corresponding to each preset client is at least used for storing: when the preset distribution condition is met, advertisement data is set for the preset client based on a target advertisement pre-distribution strategy of the advertisement hit rate to be estimated;
aiming at each preset client, when each advertisement played by the preset client is monitored, judging whether the server cache corresponding to the preset client contains the advertisement data of the advertisement or not, updating the total advertisement putting times and the total advertisement hit times corresponding to each preset client according to a judgment result, and calculating the advertisement hit rate corresponding to a target advertisement pre-distribution strategy based on the current total advertisement putting times and the total advertisement hit times after updating;
and when the preset estimation end condition is met, determining an advertisement hit rate estimation result corresponding to the target advertisement pre-distribution strategy according to each advertisement hit rate corresponding to the target advertisement pre-distribution strategy obtained through calculation.
Optionally, the method further comprises:
and for each preset client, when detecting that the preset client meets a preset distribution condition, downloading advertisement data from a preset advertisement library to a server cache corresponding to the preset client according to a target advertisement pre-distribution strategy.
Optionally, the method further comprises:
and if so, storing the advertisement data corresponding to the advertisement into a server cache corresponding to the preset client.
Optionally, detecting that the predetermined client meets the predetermined distribution condition includes:
and monitoring that the preset client requests a pre-distribution service from a pre-distribution server corresponding to the preset client.
Optionally, updating the total number of advertisement impressions and the total number of advertisement hits corresponding to each predetermined client according to the determination result, including:
when the judgment result is yes, adding 1 to the total advertisement putting times and the total advertisement hit times corresponding to each preset client;
and when the judgment result is negative, adding 1 to the total advertisement putting times, and keeping the total advertisement hitting times unchanged.
Optionally, calculating an advertisement hit rate corresponding to the target advertisement pre-distribution strategy based on the current total number of advertisement impressions and the total number of advertisement hits, including:
and dividing the total number of times of the current advertisement hit by the total number of times of the current advertisement putting to obtain the advertisement hit rate corresponding to the target advertisement pre-distribution strategy.
Optionally, the preset predicted end condition includes:
receiving an estimated ending instruction input by a user; or
The preset estimated ending time comes; or
The total number of advertisement putting times reaches a preset time threshold value.
The communication bus mentioned in the above server may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The communication interface is used for communication between the server and other devices.
The Memory may include a Random Access Memory (RAM) or a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the processor.
The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the Integrated Circuit may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component.
In yet another embodiment of the present invention, a computer-readable storage medium is provided, which has instructions stored therein, and when the instructions are executed on a computer, the instructions cause the computer to perform the method steps of any of the advertisement hit rate estimation methods described in the above embodiments.
In yet another embodiment of the present invention, there is also provided a computer program product comprising instructions which, when run on a computer, cause the computer to perform the method steps of any of the advertisement hit rate estimation methods described in the above embodiments.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, 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 identical elements in a process, method, article, or apparatus that comprises the element.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the device and server embodiments, since they are substantially similar to the method embodiments, the description is simple, and the relevant points can be referred to the partial description of the method embodiments.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.
Claims (15)
1. An advertisement hit rate estimation method is applied to an offline server, and comprises the following steps:
monitoring each predetermined client; each preset client uniquely corresponds to a server cache below one line, and the server cache corresponding to each preset client is at least used for storing: when the preset distribution condition is met, advertisement data is set for the preset client based on a target advertisement pre-distribution strategy of the advertisement hit rate to be estimated;
aiming at each preset client, when each advertisement is monitored to be played by the preset client, judging whether the server cache corresponding to the preset client contains the advertisement data of the advertisement or not, updating the total advertisement putting times and the total advertisement hit times corresponding to each preset client according to a judgment result, and calculating the advertisement hit rate corresponding to the target advertisement pre-distribution strategy based on the current total advertisement putting times and the total advertisement hit times after updating;
and when a preset estimation end condition is met, determining an advertisement hit rate estimation result corresponding to the target advertisement pre-distribution strategy according to the calculated advertisement hit rates corresponding to the target advertisement pre-distribution strategy.
2. The method of claim 1, further comprising:
and for each preset client, when the preset client is detected to meet the preset distribution condition, downloading advertisement data from a preset advertisement library to a server cache corresponding to the preset client according to the target advertisement pre-distribution strategy.
3. The method of claim 1, further comprising:
and if not, storing the advertisement data corresponding to the advertisement into a server cache corresponding to the preset client.
4. The method of claim 3, wherein the detecting that the predetermined client meets the predetermined distribution condition comprises:
and monitoring that the preset client requests a pre-distribution service from a pre-distribution server corresponding to the preset client.
5. The method according to claim 1, wherein the updating the total number of advertisement impressions and the total number of advertisement hits corresponding to each of the predetermined clients according to the determination result comprises:
when the judgment result is yes, adding 1 to the total advertisement putting times and the total advertisement hit times corresponding to each preset client;
and when the judgment result is negative, adding 1 to the total advertisement putting times, and keeping the total advertisement hitting times unchanged.
6. The method of claim 1, wherein calculating the advertisement hit rate corresponding to the target advertisement pre-distribution strategy based on the current total number of advertisement impressions and the total number of advertisement hits comprises:
and dividing the total number of times of the current advertisement hit by the total number of times of the current advertisement putting to obtain the advertisement hit rate corresponding to the target advertisement pre-distribution strategy.
7. The method of claim 1, wherein the predetermined pre-estimated termination condition comprises:
receiving an estimated ending instruction input by a user; or
The preset estimated ending time comes; or
And the total number of times of advertisement putting reaches a preset number threshold.
8. An advertisement hit rate estimation device, applied to an offline server, the device comprising: the device comprises a monitoring module, a calculating module and a determining module;
the monitoring module is used for monitoring each preset client; each preset client uniquely corresponds to a server cache below one line, and the server cache corresponding to each preset client is at least used for storing: when the preset distribution condition is met, advertisement data is set for the preset client based on a target advertisement pre-distribution strategy of the advertisement hit rate to be estimated;
the calculation module is used for judging whether the server cache corresponding to the preset client contains the advertisement data of the advertisement or not when the preset client is monitored to play each advertisement aiming at each preset client, updating the total advertisement putting times and the total advertisement hit times corresponding to each preset client according to the judgment result, and calculating the advertisement hit rate corresponding to the target advertisement pre-distribution strategy based on the current total advertisement putting times and the total advertisement hit times after updating;
and the determining module is used for determining the advertisement hit rate estimation result corresponding to the target advertisement pre-distribution strategy according to each advertisement hit rate corresponding to the target advertisement pre-distribution strategy obtained through calculation when the preset estimation end condition is met.
9. The apparatus of claim 8, further comprising: a downloading module;
and the downloading module is used for downloading the advertisement data from the preset advertisement library to the server cache corresponding to each preset client according to the target advertisement pre-distribution strategy when detecting that the preset client meets the preset distribution condition.
10. The apparatus of claim 8, further comprising: a storage module;
and the storage module is used for storing the advertisement data corresponding to the advertisement into the server cache corresponding to the preset client when the judgment result of the calculation module is negative.
11. The apparatus of claim 10, wherein the detecting that the predetermined client meets the predetermined distribution condition comprises:
and monitoring that the preset client requests a pre-distribution service from a pre-distribution server corresponding to the preset client.
12. The apparatus of claim 8, wherein the calculating module updates the total number of advertisement impressions and the total number of advertisement hits corresponding to each of the predetermined clients according to the determination result, and comprises:
when the judgment result of the calculation module is yes, adding 1 to the total advertisement putting times and the total advertisement hit times corresponding to each client;
and when the judgment result of the calculation module is negative, adding 1 to the total advertisement putting times, and keeping the total advertisement hitting times unchanged.
13. The apparatus of claim 8, wherein the calculating module calculates the advertisement hit rate corresponding to the target advertisement pre-distribution strategy based on the total number of current advertisement impressions and the total number of advertisement hits, and comprises:
and dividing the total number of the current advertisement hits by the total number of the current advertisement putting times to obtain the advertisement hit rate corresponding to the target advertisement pre-distribution strategy.
14. The apparatus of claim 8, wherein the predetermined pre-estimated termination condition comprises:
receiving an estimated ending instruction input by a user; or
The preset estimated ending time comes; or
And the total number of times of advertisement putting reaches a preset number threshold.
15. A server is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor and the communication interface are used for realizing the communication between the processor and the memory through the communication bus;
a memory for storing a computer program;
a processor for implementing the method steps of any of claims 1 to 7 when executing a program stored in the memory.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811524281.5A CN109741088B (en) | 2018-12-13 | 2018-12-13 | Advertisement hit rate estimation method, estimation device and server |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811524281.5A CN109741088B (en) | 2018-12-13 | 2018-12-13 | Advertisement hit rate estimation method, estimation device and server |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109741088A CN109741088A (en) | 2019-05-10 |
| CN109741088B true CN109741088B (en) | 2021-04-02 |
Family
ID=66359412
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811524281.5A Active CN109741088B (en) | 2018-12-13 | 2018-12-13 | Advertisement hit rate estimation method, estimation device and server |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109741088B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111311312A (en) * | 2020-01-20 | 2020-06-19 | 深圳市酷开网络科技有限公司 | Advertisement effect evaluation method, display terminal and computer-readable storage medium |
| CN112788133A (en) * | 2020-12-31 | 2021-05-11 | 上海卓悠网络科技有限公司 | Information interaction method and equipment based on advertisement |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2012049605A (en) * | 2010-08-24 | 2012-03-08 | Nec Corp | Access frequency estimation device, method, and program |
| CN108574685B (en) * | 2017-03-14 | 2021-08-03 | 华为技术有限公司 | Streaming media pushing method, device and system |
-
2018
- 2018-12-13 CN CN201811524281.5A patent/CN109741088B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN109741088A (en) | 2019-05-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106161569B (en) | Recommendation, buffer replacing method and the equipment of Web content | |
| CN107124630B (en) | Method and device for node data management | |
| JP5298331B2 (en) | Digital content distribution system and method | |
| US10348630B2 (en) | Load balancing based on load projections for events | |
| CN111417000B (en) | Method, device, electronic equipment and medium for switching video code rate | |
| CN109741088B (en) | Advertisement hit rate estimation method, estimation device and server | |
| CN108156257B (en) | Information pushing method and device | |
| JP2011507115A (en) | Distributing content data packages originated by users of a super peer-to-peer network | |
| US9319297B2 (en) | Long term metrics applied to multivariate testing | |
| CN103312733A (en) | Method and device for information processing | |
| CN107872715A (en) | A kind of method and device for showing displaying information | |
| CN110113642B (en) | ABS algorithm evaluation method and device | |
| CN113709530B (en) | Resource downloading method, system, electronic equipment and storage medium | |
| CN109067916B (en) | Online multimedia file downloading method and device and electronic equipment | |
| CN112837088B (en) | Advertisement putting method, advertisement putting device, advertisement putting medium and electronic equipment | |
| CN111753239B (en) | Resource distribution method and device, electronic equipment and storage medium | |
| US20100273558A1 (en) | Method of Determining Quality of Service for On-Line Gaming in a Network | |
| US11632588B2 (en) | Measuring the performance of a peer-managed content distribution network | |
| CN111526385B (en) | Video processing method and device, electronic equipment and storage medium | |
| CN112565829B (en) | Network scheduling method, device and system and readable storage medium | |
| US10742758B2 (en) | Communication analysis device, communication analysis method, and program recording medium | |
| CN117421069A (en) | Dynamic loading method, system, equipment and storage medium of internet applet | |
| CN111131864A (en) | Data transmission method, device and system | |
| CN109788326B (en) | Video resource pre-pushing method, device and system | |
| CN108574610B (en) | Pressure testing method and device, electronic equipment and medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |