CN112667892B - Information recommendation method, device, server and storage medium - Google Patents
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Abstract
The disclosure relates to an information recommendation method, an information recommendation device, a server and a storage medium, and relates to the technical field of data processing, so as to at least solve the problem of how to guarantee the accuracy of oriented crowd in the related technology. The method comprises the following steps: obtaining work conversion rate and at least one behavior operation conversion rate of an account number in the statistical duration; the method comprises the steps of obtaining a behavior operation conversion rate, wherein the work conversion rate is the conversion rate of target works in works of preset categories, the behavior operation conversion rate is the conversion rate of target works corresponding to target behavior operations, the target behavior operations are behavior operations recorded by an account in the works of the preset categories, and different behavior operations correspond to different behavior operation conversion rates; determining the duty ratio of each behavior operation conversion rate in the work conversion rate; according to the determined duty ratio of each behavior operation conversion rate in the work conversion rate, determining the attention degree of the account number to the works of the preset category; and when the attention degree is greater than or equal to the attention degree threshold value, putting the work to be put into the account.
Description
Technical Field
The disclosure relates to the technical field of data processing, and in particular relates to an information recommendation method, an information recommendation device, a server and a storage medium.
Background
At present, in the process of delivering a work, crowd-oriented processing is generally performed on the work to determine an oriented crowd of the work (the oriented crowd comprises potential audiences related to the work); the work is then put in a targeted population.
Therefore, crowd orientation is a very important link in the work throwing process, and the accuracy of the oriented crowd is closely related to the work throwing effect. Therefore, it is important to ensure the accuracy of the oriented crowd.
Disclosure of Invention
The disclosure provides an information recommendation method, an information recommendation device, a server and a storage medium, so as to at least solve the problem of how to guarantee the accuracy of a directional crowd in the related technology.
The technical scheme of the present disclosure is as follows:
according to a first aspect of an embodiment of the present disclosure, there is provided an information recommendation method, including: and obtaining the work conversion rate and at least one behavior operation conversion rate of the account number in the statistical duration. The method comprises the steps of obtaining a behavior operation conversion rate, wherein the work conversion rate is the conversion rate of target works in works of preset categories, the behavior operation conversion rate is the conversion rate of target works corresponding to target behavior operations, the target behavior operations are behavior operations recorded by an account in the works of the preset categories, and different behavior operations correspond to different behavior operation conversion rates. Determining the duty ratio of each behavior operation conversion rate in the work conversion rate; and determining the attention degree of the account number to the preset class-of-purpose works according to the determined duty ratio of each behavior operation conversion rate in the work conversion rate. And when the attention degree is greater than or equal to the attention degree threshold value, putting the work to be put into the account. Wherein the category to which the work to be put belongs is a preset category.
In one implementation manner, the "obtaining the at least one behavioral operation conversion rate within the statistical duration" may be specifically implemented by the following steps: acquiring at least one target behavior operation executed by an account in a preset category in the statistical duration; inquiring the behavior operation conversion rate corresponding to each target behavior operation in the corresponding relation between the target behavior operation and the behavior operation conversion rate, and determining at least one behavior operation conversion rate in the statistical duration.
In one embodiment, the step of obtaining the correspondence relationship includes: obtaining conversion data, namely a first account total number and a second account total number; the conversion data comprise conversion operation data recorded by the account numbers on the target works, wherein the total number of the first account numbers is the number of the account numbers recorded with the target behavior operation in the preset type target works, the total number of the second account numbers is the number of the account numbers recorded with the target behavior operation in the preset type target works, and the target operation is executed on the target works; determining the behavior operation conversion rate corresponding to the target behavior operation as the ratio of the total number of the second account to the total number of the first account; and generating a corresponding relation containing the behavior operation conversion rate corresponding to each target behavior operation.
In one implementation manner, the above-mentioned "obtaining the conversion rate of the work in the statistical duration" may be specifically implemented by the following steps: obtaining conversion data in the statistical time length, and obtaining the total number of the third account numbers and the total number of the fourth account numbers; the conversion data comprise conversion operation data recorded by the account numbers on the target works, wherein the total number of the third account numbers is the number of the account numbers with the behavior operation recorded in the works of the preset category in the statistical time length, the total number of the fourth account numbers is the number of the account numbers with the behavior operation recorded in the works of the preset category in the statistical time length, and the conversion operation is recorded on the target works; and determining the work conversion rate in the statistical time length as the duty ratio of the total number of the fourth account number in the total number of the third account number.
In one embodiment, the above-mentioned "determining the ratio of each behavioural operation conversion rate to the work conversion rate" may be specifically achieved by: determining a difference between each behavioural operation conversion rate and the work conversion rate; and determining the duty ratio of each behavior operation conversion rate in the work conversion rate according to the determined difference value and the work conversion rate.
In one embodiment, the above-described duty cycle satisfies the following formula:
Wherein,representing the duty cycle, action_ cvr representing the behavioural conversion rate, avg_ cvr representing the work conversion rate.
In one implementation manner, the "determining the attention of the account number to the preset class of target works according to the determined duty ratio of each behavior operation conversion rate in the work conversion rate" may be specifically implemented by the following steps: acquiring the number of unit time contained in the statistical duration; and determining the attention degree of the account number to the preset class destination works according to the determined duty ratio and quantity.
In one embodiment, the above-mentioned attention satisfies the following formula:
wherein S is x Representing the degree of attention, T representing the number, n representing the total number of target behavior operations performed by the account in the works of the preset category,representing the duty ratio of the behavior operation conversion rate corresponding to the target behavior operation i in the work conversion rate, wherein i is an integer and i epsilon [1, n ]]0 < a.ltoreq.1, 0 < b.ltoreq.1, and a+b=1.
According to a second aspect of the embodiments of the present disclosure, there is provided an information recommendation apparatus including: an acquisition unit and a processing unit.
The acquisition unit is configured to acquire at least one behavior operation conversion rate of the work conversion rate and the account number in the statistical duration; the method comprises the steps of obtaining a target behavior operation conversion rate, wherein the work conversion rate is the conversion rate of target works in works of preset categories, the behavior operation conversion rate is the conversion rate of target works corresponding to target behavior operations, the target behavior operations are behavior operations executed by an account in the works of preset categories, and different behavior operations correspond to different behavior operation conversion rates; a processing unit configured to determine a ratio of the behavioural operation conversion rate acquired by each acquisition unit in the work conversion rate acquired by the acquisition unit; the processing unit is further configured to determine the attention degree of the account number to the works of the preset category according to the determined duty ratio of each behavior operation conversion rate in the work conversion rate; the processing unit is further configured to put the work to be put into the account when the attention degree is greater than or equal to the attention degree threshold value; wherein the category to which the work to be put belongs is a preset category.
In one implementation manner, the obtaining unit is specifically configured to obtain at least one target behavior operation performed by the account in the works of the preset category in the statistical duration; the processing unit is specifically configured to query the behavior operation conversion rate corresponding to the target behavior operation acquired by each acquisition unit in the corresponding relation between the target behavior operation and the behavior operation conversion rate, and determine at least one behavior operation conversion rate within the statistical duration.
In one embodiment, the acquisition unit, the method comprises the steps of acquiring conversion data, wherein the total number of first accounts and the total number of second accounts are specifically configured; the conversion data comprise conversion operation data recorded by the account numbers on the target works, wherein the total number of the first account numbers is the number of the account numbers recorded with the target behavior operation in the preset type target works, the total number of the second account numbers is the number of the account numbers recorded with the target behavior operation in the preset type target works, and the target operation is executed on the target works; the processing unit is specifically configured to determine that the behavioral operation conversion rate corresponding to the target behavioral operation is the ratio of the total number of the second account numbers acquired by the acquisition unit to the total number of the first account numbers acquired by the acquisition unit; the processing unit is specifically configured to generate a corresponding relation containing the behavior operation conversion rate corresponding to each target behavior operation.
In one embodiment, the acquisition unit, the method comprises the steps of specifically acquiring conversion data in a statistical time length, wherein the total number of third accounts and the total number of fourth accounts; the conversion data comprise conversion operation data recorded by the account numbers on the target works, wherein the total number of the third account numbers is the number of the account numbers with the behavior operation recorded in the works of the preset category in the statistical time length, the total number of the fourth account numbers is the number of the account numbers with the behavior operation recorded in the works of the preset category in the statistical time length, and the conversion operation is recorded on the target works; the processing unit is specifically configured to determine that the work conversion rate in the statistical duration is the duty ratio of the total number of the fourth account numbers acquired by the acquisition unit in the total number of the third account numbers acquired by the acquisition unit.
In one embodiment, the processing unit is specifically configured to determine a difference between the behavioural operation conversion rate acquired by each acquisition unit and the work conversion rate acquired by the acquisition unit; and the processing unit is specifically configured to determine the duty ratio of each behavior operation conversion rate in the work conversion rate according to the determined difference value and the work conversion rate acquired by the acquisition unit.
In one embodiment, the duty cycle satisfies the following formula:
Wherein,representing the duty cycle, action_ cvr representing the behavioural conversion rate, avg_ cvr representing the work conversion rate.
In one embodiment, the obtaining unit is specifically configured to obtain the number of unit times included in the statistical duration; the processing unit is specifically configured to determine the attention degree of the account number to the preset target works according to the determined duty ratio and the number acquired by the acquisition unit.
In one embodiment, the attention satisfies the following formula:
wherein S is x Representing the degree of attention, T representing the number, n representing the total number of target behavior operations performed by the account in the works of the preset category,representing the duty ratio of the behavior operation conversion rate corresponding to the target behavior operation i in the work conversion rate, wherein i is an integer and i epsilon [1, n ]]0 < a.ltoreq.1, 0 < b.ltoreq.1, and a+b=1.
According to a third aspect of embodiments of the present disclosure, there is provided a server comprising:
a processor; a memory for storing the processor-executable instructions; wherein the processor is configured to execute the instructions to implement the information recommendation method provided in the first aspect.
According to a fourth aspect of embodiments of the present disclosure, there is provided a computer-readable storage medium, which when executed by a processor of a server provided in the third aspect, enables the server to perform the information recommendation method provided in the first aspect.
According to a fifth aspect of embodiments of the present disclosure, there is provided a computer program product comprising, when run on a computer, causing the computer to perform the information recommendation method as set forth in the design of the first aspect.
The technical scheme provided by the embodiment of the disclosure at least brings the following beneficial effects:
according to the information recommendation method, the duty ratio of each behavior operation conversion rate in the work conversion rate can be determined according to at least one behavior operation conversion rate of the work conversion rate and the account number of the preset category. And then, according to the determined duty ratio of each behavior operation conversion rate in the work conversion rate, determining the attention degree of the account number to the preset class of target works. When the attention degree is determined to be greater than or equal to the attention degree threshold value and the category to which the work to be put belongs is a preset category, the work to be put is put into the account, so that at least one account for putting the work to be put can be selected according to the attention degree, and the problem of orienting the crowd is solved. Meanwhile, as the attention degree of each account in the oriented crowd is greater than or equal to the attention degree threshold, the conversion rate of works to be put in can be improved, and the problem of how to guarantee the accuracy of the oriented crowd in the related technology is solved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure and do not constitute an undue limitation on the disclosure.
FIG. 1 is an architecture diagram of an implementation environment, shown in accordance with an exemplary embodiment.
Fig. 2 is one of flowcharts illustrating an information recommendation method according to an exemplary embodiment.
FIG. 3 is a second flowchart illustrating a method of recommending information according to an exemplary embodiment.
Fig. 4 is a third flowchart illustrating a method of recommending information according to an exemplary embodiment.
FIG. 5 is a schematic diagram showing a table of total endorsements versus behavioural operation conversion, according to an example embodiment.
FIG. 6 is a schematic diagram illustrating a table of total forwarding number versus behavioural operation conversion rate, according to an example embodiment.
Fig. 7 is one of schematic structural diagrams of an information recommendation apparatus according to an exemplary embodiment.
Fig. 8 is a second schematic diagram showing a structure of an information recommendation apparatus according to an exemplary embodiment.
Detailed Description
In order to enable those skilled in the art to better understand the technical solutions of the present disclosure, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.
It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the foregoing figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the disclosure described herein may be capable of operation in sequences other than those illustrated or described herein. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present disclosure as detailed in the accompanying claims.
In the embodiment of the disclosure, the works of the preset category may be pure videos or images which are made by the account numbers of the provided works and do not contain any description information, and other account numbers for obtaining the works of the preset category can only understand the content of the works of the preset category through self understanding. The works of the preset category can also be videos or images which are produced by the account and carry corresponding text or voice description information so as to explain or spread the expressed resource contents to other accounts, and for the graphic works containing the description information, the actual contents of the graphic resources can be determined according to the description information. The graphic works refer to videos or images containing text and/or voice description information.
Crowd targeting refers to the process of screening out potential audience members most relevant to a work to be delivered (also referred to as a target work). The potential audience may also be referred to as a targeted user, specifically, a potential receiver that receives the target work with a high probability, or a potential receiver that receives the target work with a high probability and performs a conversion operation (such as filling in a form, downloading a preset application program, or communicating with a preset account number) on the target work. Research has shown that the accuracy of crowd targeting in delivering target works is generally proportional to the work conversion rate (CVR) or click rate (predicted click through rate, CTR) of the target works; that is, the higher the accuracy of crowd orientation, the higher the work conversion rate of the target work. The work conversion rate may also be called exposure rate, which is the ratio of the number of actual exposure users in a specified crowd to the total number of users of a directed crowd, where the actual exposure users refer to the number of users who have conversion operations on a target work in a statistical period of time; the work conversion rate can be used for measuring how many proportion of users in the directional crowd actually have the actual target works, namely the work conversion rate can be used for measuring the proportion of users in the directional crowd actually seeing the target works. For example, if the total number of users of the targeted population is 500, and if the number of users who have conversion operations on the target work within a statistical period is 450, then the work conversion rate (exposure rate) is equal to 450/500=90%; if the number of users who have a conversion operation on the target work for a statistical period is 200, the work conversion rate (exposure rate) is equal to 200/500=40%. The statistical duration may be set according to actual service requirements, which is not particularly limited by the present disclosure.
Therefore, crowd orientation is an important link in the process of putting works to be put in; the process of crowd targeting is not available from both the perspective of the delivering user (i.e., the user who has a need to deliver the work to be delivered) and from the perspective of the traffic party (e.g., the information recommendation system). For example, for a delivery master, a low exposure means that the budget of the delivery of the work to be delivered is not effectively consumed and a population of users of sufficient size cannot be reached; while for the flow regime, low exposure rates can affect the benefits. Therefore, in order to better perform crowd orientation to improve the conversion rate of works, the embodiment of the disclosure provides an information recommendation method; the information recommendation method can be applied to an information recommendation system, wherein the information recommendation system is a system which can provide an information recommendation media platform and can deliver works on the information recommendation media platform for delivering users.
Fig. 1 is an architecture diagram of an implementation environment in which the following information recommendation method may be applied, as shown in fig. 1, according to an exemplary embodiment. The implementation environment comprises a delivery user 01, a server 02 and a directional crowd 03 (comprising N users, wherein N is an integer greater than or equal to 0). When the delivering user 01 wants to determine the targeted crowd 03 of the work to be delivered, a crowd targeting request may be sent to a background server (hereinafter referred to as a server) through the front end of the information recommendation system, as shown in fig. 1. After receiving the crowd orientation request, the server 02 may respond to the crowd orientation request to execute the above information recommendation method to determine a preset category to which the work to be delivered belongs, and a degree of interest of each user in the work of the preset category, and further determine an oriented crowd 03 interested in the work to be delivered according to the degree of interest.
In one implementation, the server 02 may be a server, a server cluster formed by a plurality of servers, or a cloud computing service center. The server 02 may include a processor, memory, network interfaces, and the like.
Based on this, in the information recommendation method provided in the embodiments of the present disclosure, according to at least one behavior operation conversion rate of a work conversion rate and an account number of a preset category, a ratio of each behavior operation conversion rate in the work conversion rate may be determined. And then, according to the determined duty ratio of each behavior operation conversion rate in the work conversion rate, determining the attention degree of the account number to the preset class of target works. When the attention degree is determined to be greater than or equal to the attention degree threshold value and the category to which the work to be put belongs is a preset category, the work to be put is put into the account, so that at least one account for putting the work to be put can be selected according to the attention degree, the problem of orienting people is solved, the work conversion rate of the work to be put is improved, the user experience is ensured, the problem of ensuring the accuracy of the oriented people in the related technology is solved, and the specific implementation process is as follows:
The execution body of the information recommendation method provided in the embodiment of the present disclosure may be the information recommendation device, and the information recommendation device may be a server, or may be a functional module and/or a functional entity capable of implementing the information recommendation method in the server, which may be specifically determined according to actual use requirements, where embodiments of the present disclosure are not limited. An information recommendation method provided by the embodiment of the present disclosure will be described below by taking an execution subject as an information recommendation apparatus as an example.
Those skilled in the art will appreciate that the above servers are only examples, and that other devices, either now present or in the future, may be adapted for use with the present disclosure, and are intended to be within the scope of the present disclosure, and are hereby incorporated by reference.
The data referred to in this disclosure may be data authorized by the user or sufficiently authorized by the parties.
An exemplary description of an information recommendation method provided by the embodiments of the present disclosure is provided below with reference to the accompanying drawings.
Fig. 2 is a flowchart illustrating an information recommendation method according to an exemplary embodiment, which is used in an information recommendation apparatus as shown in fig. 2, and includes the following S11-S14.
S11, the information recommendation device acquires the work conversion rate and at least one behavior operation conversion rate of the account number in the statistical duration. The method comprises the steps of obtaining a behavior operation conversion rate, wherein the work conversion rate is the conversion rate of target works in works of preset categories, the behavior operation conversion rate is the conversion rate of target works corresponding to target behavior operations, the target behavior operations are behavior operations recorded by an account in the works of the preset categories, and different behavior operations correspond to different behavior operation conversion rates.
In one implementation, the classification of works in the prior art is not accurate enough, so that the work conversion rate of the account number to the works of the preset category cannot be accurately obtained. Thus, there is a need to build a complete classification hierarchy for works. Specifically, the preset category of the attribution of the works can be determined according to the preset classification model, so that the works can be classified more accurately, and the preset category of the attribution of the works can be determined. The training process of the category classification model is as follows:
the information recommending device acquires a training sample work and a labeling result of the training sample work. The training sample works correspond to the same keyword, the category comprises at least one keyword, and the labeling result comprises a preset category to which the training sample works belong;
The information recommending device inputs the training sample work into a preset algorithm.
The information recommending device determines whether a predicted result of the training sample work output by the preset algorithm is matched with a labeling result or not based on the preset algorithm.
And when the predicted result is not matched with the labeling result, the information recommendation device repeatedly and circularly updates the network parameters of the preset algorithm until the model converges to obtain the category classification model.
The preset algorithm may be BERT (Bidirectional Encoder Representation from Transformers), or FastText, for example.
Specifically, the preset category includes at least any one of a primary category, a secondary category, and a tertiary category in order.
For example, when it is necessary to classify works of education class, if the preset class includes a primary class, a secondary class, and a tertiary class, the primary class may be basic education, the secondary class is primary education, and the tertiary class is a grade.
When the work of the mother and infant is required to be classified, if the categories include a primary category, a secondary category and a tertiary category, the primary category can be mother and infant, the secondary category is infant, and the tertiary category is 0-12 months.
The foregoing description of the preset categories is merely exemplary, and may be specifically set according to actual needs, which is not specifically limited by the present disclosure.
Specifically, the action operation includes at least one of viewing duration, appreciation, praise, forwarding, comment, attention, click, payment, form submission, and search.
By way of example, assuming that user A endorses 3 times on preset category work 1 and forwards 3 times on preset category work 1, user A endorses 2 times on preset category work 2 and forwards 1 time on preset category work 2, user A endorses 5 times on preset category work 3 and forwards 3 times on preset category work 3, the user's target behavior on preset category work operates as praise 10 (3+2+5) times and forwards 7 (3+1+3) times.
In one implementation manner, the information recommendation device may obtain each behavior operation of the user on the preset class destination work in the statistical duration through the data source as shown in table 1.
TABLE 1
In one implementation manner, the information recommendation method provided in the embodiment of the present disclosure may also classify the author of each work in the preset categories, such as a teacher who is engaged in primary education or a teacher of a vocational education training institution, based on natural language processing (Natural Language Processing, NLP), so as to determine the preset category to which each author belongs.
Specifically, keywords may be determined according to short text matching and/or text classification, and authors with a certain range (each author corresponds to at least one label (also referred to as a keyword)) may be defined according to the keywords, and then classification is performed on each author through fasttest, and erroneous data is marked and iterated continuously, so as to obtain a category classification model.
S12, the information recommendation device determines the duty ratio of each behavior operation conversion rate in the work conversion rate.
S13, the information recommendation device determines the attention degree of the account number to the preset target works according to the determined duty ratio of each behavior operation conversion rate in the work conversion rate.
S14, the information recommendation device puts the work to be put into the account under the condition that the attention degree is larger than or equal to the attention degree threshold value. Wherein the category to which the work to be put belongs is a preset category.
As can be seen from the foregoing, the information recommendation method according to the embodiment of the present disclosure determines, according to the conversion rate of the work of the preset category and the conversion rate of at least one behavior operation of the account, the attention of the account to the work of the preset category. When the attention degree is determined to be greater than or equal to the attention degree threshold value and the category to which the work to be put belongs is a preset category, the work to be put is put into the account, so that the work conversion rate of the work to be put is improved, the experience of a user is ensured, and the problem of how to ensure the accuracy of the oriented crowd in the related technology is solved.
In an embodiment, in conjunction with fig. 2, as shown in fig. 3, S11 may be specifically implemented by S110 and S111 described below.
S110, the information recommendation device acquires at least one target behavior operation executed by the account in the works of the preset category in the statistical duration.
S111, the information recommendation device queries the behavior operation conversion rate corresponding to each target behavior operation in the corresponding relation between the target behavior operation and the behavior operation conversion rate, and determines at least one behavior operation conversion rate in the statistical duration.
As can be seen from the foregoing, according to the information recommendation method provided by the embodiment of the present disclosure, through a predetermined correspondence, the information recommendation device may query the behavior operation conversion rate corresponding to each target behavior operation in the correspondence, determine at least one behavior operation conversion rate within a statistical duration, and conveniently determine at least one behavior operation conversion rate of each account within the statistical duration, thereby improving user experience.
In an implementation manner, in conjunction with fig. 3, as shown in fig. 4, the information recommendation method provided in the embodiment of the disclosure further includes S15, S16, and S17.
S15, the information recommendation device acquires conversion data, and the total number of the first account numbers and the total number of the second account numbers. The conversion data comprise data of conversion operations recorded by the account numbers on the target works, wherein the total number of the first account numbers is the number of the account numbers with the target behavior operations recorded in the target works of the preset type, the total number of the second account numbers is the number of the account numbers with the target behavior operations recorded in the target works of the preset type, and the target operations are executed on the target works.
In one implementation manner, when the information recommending device acquires the conversion data, a form filling record in the statistical duration can be acquired in the background. The form filling record records the conversion operation of the account number on the target work.
S16, the information recommendation device determines that the behavior operation conversion rate corresponding to the target behavior operation is the ratio of the total number of the second account numbers to the total number of the first account numbers.
S17, the information recommendation device generates a corresponding relation containing the behavior operation conversion rate corresponding to each target behavior operation.
In one implementation manner, the correspondence may be a relationship table, and the information recommendation device may generate the relationship table including a behavior operation conversion rate corresponding to each target behavior operation, so as to determine, when at least one target behavior operation performed by the account in a work of a preset category is obtained, at least one behavior operation conversion rate of the account by querying, in the relationship table of the target behavior operation and the behavior operation conversion rate, the behavior operation conversion rate corresponding to each target behavior operation.
For example, education based on preset categories, converting data into form data, behavior operation as praise, corresponding relationship as a relationship table, and generating the relationship table as follows:
1. And acquiring the total praise number of each account number praise on the basic education work within the statistical duration, and form data.
2. The total number of accounts with a total number of endorsements N (i.e., the total number of first accounts) is obtained. N is an integer greater than or equal to 0.
3. In the form data, the account number with the total number of points being N is queried, and the total number of the account number of the conversion operation (namely, the total number of the second account number) exists.
4. And determining the behavior operation conversion rate corresponding to the total praise number N as the ratio of the total number of the second account numbers to the total number of the first account numbers. Wherein the behavioural operation conversion rate for each total endorsement is shown in table 2.
TABLE 2
| Total praise number | 1 | 2 | …… | N |
| Behavioural operation conversion | a | b | …… | c |
5. The relationship table is plotted according to the behavioral operation conversion rate for each total endorsement recorded in table 2.
The relationship table is shown in fig. 5, for example.
Specifically, the obtaining manner of the corresponding relationship of other behavior operations is the same as that of the corresponding relationship of the praise, and is not described herein.
The above description of the correspondence is merely an exemplary description, and the correspondence may be specifically determined according to actual requirements, which is not specifically limited by the present disclosure.
As can be seen from the foregoing, in the information recommendation method provided by the embodiment of the present disclosure, by obtaining the conversion data, it can be determined whether the user has generated the conversion operation on the target work, so that the total number of the second account numbers can be determined based on the conversion data. Then, the behavioral operation conversion rate corresponding to one target behavioral operation can be calculated as the ratio of the total number of the second account number to the total number of the first account number. And finally, generating a corresponding relation containing the behavior operation conversion rate corresponding to each target behavior operation according to the behavior operation conversion rate corresponding to each target behavior operation, so that the subsequent use is convenient.
In an embodiment, in conjunction with fig. 2, as shown in fig. 3, the above step S11 may be specifically implemented by the following S112 and S113.
S112, the information recommendation device acquires conversion data in the statistical time duration, and the total number of the third account numbers and the total number of the fourth account numbers. The conversion data comprise conversion operation data recorded by the account numbers on the target works, the total number of the third account numbers is the number of the account numbers with the behavior operation recorded in the works of the preset category in the statistical time, the total number of the fourth account numbers is the number of the account numbers with the behavior operation recorded in the works of the preset category in the statistical time, and the conversion operation is recorded on the target works.
Specifically, the method for obtaining the converted data in S112 is similar to the method for obtaining the converted data in S15, and will not be described here again.
S113, the information recommendation device determines that the work conversion rate in the statistical time length is the duty ratio of the total number of the fourth account number in the total number of the third account number.
Illustratively, for education based on preset categories, converting data into form data, and determining the conversion rate of the work includes the following steps:
1. the total number of accounts that have behavioural operations on the underlying educational work (i.e., the third account total number) within the statistical duration is obtained, as well as form data.
2. The form data is queried for the total number of the account numbers (namely the fourth account number) with the conversion operation in the account numbers with the behavior operation on the basic educational works within the statistical duration.
3. And determining the work conversion rate in the statistical time length as the duty ratio of the total number of the fourth account number in the total number of the third account number.
According to the information recommendation method provided by the embodiment of the disclosure, whether the user has generated conversion operation on the target work can be determined by acquiring the conversion data, so that the total number of fourth account numbers can be determined based on the conversion data. And then, determining the work conversion rate in the statistical time length as the duty ratio of the total number of the fourth account number in the total number of the third account number. Further, a duty cycle of each behavioral operational conversion of the account number in the work conversion may be determined based on the work conversion. And then, according to the duty ratio of each behavior operation conversion rate of the account number in the work conversion rate, determining the attention degree of the account number to the works of the preset category, and conveniently improving the work conversion rate of the works to be put in the follow-up process.
In an embodiment, in conjunction with fig. 2, as shown in fig. 3, S12 may be specifically implemented by S120 and S121 described below.
S120, the information recommendation device determines the difference value between each behavior operation conversion rate and the work conversion rate.
S121, the information recommending device determines the duty ratio of each behavior operation conversion rate in the work conversion rate according to the determined difference value and the work conversion rate.
As can be seen from the foregoing, according to the information recommendation method provided by the embodiment of the present disclosure, by calculating the difference between each behavior operation conversion rate and the work conversion rate, the duty ratio of each behavior operation conversion rate in the work conversion rate can be determined according to the determined difference and the work conversion rate. And then, according to the duty ratio of each behavior operation conversion rate of the account number in the work conversion rate, determining the attention degree of the account number to the works of the preset category, and conveniently improving the work conversion rate of the works to be put in the follow-up process.
In one embodiment, the above-described duty cycle satisfies the following formula:
wherein,representing the duty cycle, action_ cvr representing the behavioural conversion rate, avg_ cvr representing the work conversion rate.
As can be seen from the above, the information recommendation method provided by the embodiment of the present disclosure can determine the duty ratio of each behavioural operation conversion rate in the work conversion rate by calculating each difference value and the duty ratio in the work conversion rate. And then, according to the duty ratio of each behavior operation conversion rate of the account number in the work conversion rate, determining the attention degree of the account number to the works of the preset category, and conveniently improving the work conversion rate of the works to be put in the follow-up process. In an embodiment, in conjunction with fig. 2, as shown in fig. 3, S13 may be specifically implemented by S130 and S131 described below.
S130, the information recommendation device acquires the number of unit time contained in the statistical duration.
In one possible process, the unit time is the time of day, and if the statistical duration is one week, the number of unit times contained in the statistical duration is equal to 7.
S131, the information recommendation device determines the attention degree of the account number to the preset class destination works according to the determined duty ratio and the determined quantity.
As can be seen from the foregoing, according to the information recommendation method provided by the embodiment of the present disclosure, by calculating the number of unit time included in the statistical duration, the attention degree of the account number to the preset class destination works can be determined according to the determined duty ratio and number, so that the conversion rate of the works to be put in later is conveniently improved.
In one embodiment, the above-mentioned attention satisfies the following formula:
wherein S is x Represents the attention degree, T represents the numberN represents the total number of target behavior operations performed by the account in the work of the preset category,representing the duty ratio of the behavior operation conversion rate corresponding to the target behavior operation i in the work conversion rate, wherein i is an integer and i epsilon [1, n ]]0 < a.ltoreq.1, 0 < b.ltoreq.1, and a+b=1.
As can be seen from the foregoing, according to the information recommendation method provided by the embodiment of the present disclosure, based on the formula that the attention degree meets, the attention degree of the account number to the preset target works can be determined according to the number of unit time contained in the statistical duration and at least one behavior operation conversion force of the account number in the statistical duration, so that the work conversion rate of the subsequent works to be put can be improved.
Fig. 7 is a block diagram illustrating an information recommendation apparatus according to an exemplary embodiment. Referring to fig. 7, the information recommendation apparatus 10 includes an acquisition unit 101 and a processing unit 102.
An obtaining unit 101 configured to obtain a work conversion rate and at least one behavioral operation conversion rate of an account number within a statistical duration; the method comprises the steps of obtaining a target behavior operation conversion rate, wherein the work conversion rate is the conversion rate of target works in works of preset categories, the behavior operation conversion rate is the conversion rate of target works corresponding to target behavior operations, the target behavior operations are behavior operations executed by an account in the works of preset categories, and different behavior operations correspond to different behavior operation conversion rates; a processing unit 102 configured to determine a ratio of the behavioral operation conversion rate acquired by each acquisition unit 101 in the work conversion rate acquired by the acquisition unit 101; the processing unit 102 is further configured to determine the attention degree of the account number to the works of the preset category according to the determined duty ratio of each behavior operation conversion rate in the work conversion rate; the processing unit 102 is further configured to put the work to be put into the account when the attention degree is greater than or equal to the attention degree threshold; wherein the category to which the work to be put belongs is a preset category.
In an implementation manner, the obtaining unit 101 is specifically configured to obtain at least one target behavior operation performed by the account in the work of the preset category in the statistical duration; the processing unit 102 is specifically configured to query the behavior operation conversion rate corresponding to the target behavior operation acquired by each acquiring unit 101 in the correspondence relationship between the target behavior operation and the behavior operation conversion rate, and determine at least one behavior operation conversion rate within the statistical duration.
In one implementation manner, the obtaining unit 101 is specifically configured to obtain the conversion data, the first account number total number and the second account number total number; the conversion data comprise conversion operation data recorded by the account numbers on the target works, wherein the total number of the first account numbers is the number of the account numbers recorded with the target behavior operation in the preset type target works, the total number of the second account numbers is the number of the account numbers recorded with the target behavior operation in the preset type target works, and the target operation is executed on the target works; a processing unit, specifically configured to determine a behavioral operation conversion rate corresponding to the target behavioral operation as a ratio of the total number of the second accounts acquired by the acquisition unit 101 to the total number of the first accounts acquired by the acquisition unit 101; the processing unit is specifically configured to generate a corresponding relation containing the behavior operation conversion rate corresponding to each target behavior operation.
In one implementation manner, the obtaining unit 101 is specifically configured to obtain conversion data in the statistical duration, a third account total number and a fourth account total number; the conversion data comprise conversion operation data recorded by the account numbers on the target works, wherein the total number of the third account numbers is the number of the account numbers with the behavior operation recorded in the works of the preset category in the statistical time length, the total number of the fourth account numbers is the number of the account numbers with the behavior operation recorded in the works of the preset category in the statistical time length, and the conversion operation is recorded on the target works; the processing unit 102 is specifically configured to determine that the conversion rate of works in the statistical duration is the ratio of the total number of fourth accounts acquired by the acquisition unit 101 to the total number of third accounts acquired by the acquisition unit 101.
In one embodiment, the processing unit 102 is specifically configured to determine a difference between the behavioural operation conversion rate acquired by each acquisition unit 101 and the work conversion rate acquired by the acquisition unit 101; the processing unit 102 is specifically configured to determine the duty ratio of each behavior operation conversion rate in the work conversion rate according to the determined difference value and the work conversion rate acquired by the acquisition unit 101.
In one embodiment, the duty cycle satisfies the following formula:
wherein,representing the duty cycle, action_ cvr representing the behavioural conversion rate, avg_ cvr representing the work conversion rate.
In one embodiment, the obtaining unit 101 is specifically configured to obtain the number of unit times included in the statistical duration; the processing unit 102 is specifically configured to determine, according to the determined duty ratio and the number acquired by the acquiring unit 101, a degree of attention of the account to the preset-class destination work.
In one embodiment, the attention satisfies the following formula:
wherein S is x Representing the degree of attention, T representing the number, n representing the total number of target behavior operations performed by the account in the works of the preset category,representing the duty ratio of the behavior operation conversion rate corresponding to the target behavior operation i in the work conversion rate, wherein i is an integer and i epsilon [1, n ]]0 < a.ltoreq.1, 0 < b.ltoreq.1, and a+b=1.
Of course, the information recommendation device 10 provided by the embodiment of the present disclosure includes, but is not limited to, the above-described modules, for example, the information recommendation device 10 may further include the storage unit 105. The storage unit 105 may be used for storing the program code of the writing information recommending means 10, and may also be used for storing data generated by the writing information recommending means 10 during operation, such as data in a writing request, etc.
In addition, when the information recommendation device 10 provided in the above embodiment is implemented, only the division of the above functional modules is used for illustration, and in practical application, the above functional allocation may be performed by different functional modules according to needs, that is, the internal structure of the information recommendation device 10 is divided into different functional modules to perform all or part of the functions described above.
Fig. 8 is a schematic structural diagram of an information recommendation device 10 according to an embodiment of the present disclosure, and as shown in fig. 8, the information recommendation device 10 may include: at least one processor 51, a memory 52, a communication interface 53 and a communication bus 54.
The following describes each constituent element of the information recommendation apparatus 10 in detail with reference to fig. 8:
the processor 51 is a control center of the information recommendation apparatus 10, and may be one processor or a collective name of a plurality of processing elements. For example, processor 51 is a central processing unit (Central Processing Unit, CPU), but may also be an integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits configured to implement embodiments of the present disclosure, such as: one or more DSPs, or one or more field programmable gate arrays (Field Programmable Gate Array, FPGAs).
In a particular implementation, processor 51 may include one or more CPUs, such as CPU0 and CPU1 shown in FIG. 8, as an example. Also, as an example, the information recommendation apparatus 10 may include a plurality of processors, such as the processor 51 and the processor 55 shown in fig. 8. Each of these processors may be a Single-core processor (Single-CPU) or a Multi-core processor (Multi-CPU). A processor herein may refer to one or more devices, circuits, and/or processing cores for processing data (e.g., computer program instructions).
The Memory 52 may be, but is not limited to, a Read-Only Memory (ROM) or other type of static storage device that can store static information and instructions, a random access Memory (Random Access Memory, RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), a compact disc (Compact Disc Read-Only Memory, CD-ROM) or other optical disk storage, optical disk storage (including compact disc, laser disc, optical disc, digital versatile disc, blu-ray disc, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. The memory 52 may be stand alone and be coupled to the processor 51 via a communication bus 54. Memory 52 may also be integrated with processor 51.
In a specific implementation, the memory 52 is used to store data in the present invention and to execute software programs of the present invention. The processor 51 may perform various functions of the air conditioner by running or executing a software program stored in the memory 52 and calling data stored in the memory 52.
The communication interface 53 uses any transceiver-like means for communicating with other devices or communication networks, such as a radio access network (Radio Access Network, RAN), a wireless local area network (Wireless Local Area Networks, WLAN), a terminal, a cloud, etc. The communication interface 53 may comprise a receiving unit implementing a receiving function.
The communication bus 54 may be an industry standard architecture (Industry Standard Architecture, ISA) bus, an external device interconnect (Peripheral Component Interconnect, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in fig. 8, but not only one bus or one type of bus.
As an example, in connection with fig. 7, the acquisition unit 101 in the information recommendation device 10 realizes the same function as the communication interface 53 in fig. 8, the processing unit 102 realizes the same function as the processor 51 in fig. 8, and the storage unit 103 realizes the same function as the memory 52 in fig. 8.
Another embodiment of the present invention also provides a computer-readable storage medium having stored therein instructions which, when executed on a computer, cause the computer to perform the method shown in the above-described method embodiment.
In some embodiments, the disclosed methods may be implemented as computer program instructions encoded on a computer-readable storage medium in a machine-readable format or encoded on other non-transitory media or articles of manufacture.
In an exemplary embodiment, the disclosed embodiments also provide a storage medium including instructions, such as a memory 102 including instructions, executable by the processor 101 of the information recommendation device 10 to perform the above-described method. Alternatively, the storage medium may be a non-transitory computer readable storage medium, which may be, for example, read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, and the like.
In an exemplary embodiment, the disclosed embodiments also provide a computer program product comprising one or more instructions executable by the processor 101 of the information recommendation device 10 to perform the above-described method.
From the foregoing description of the embodiments, it will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of functional modules is illustrated, and in practical application, the above-described functional allocation may be implemented by different functional modules according to needs, i.e. the internal structure of the apparatus is divided into different functional modules to implement all or part of the functions described above.
In the several embodiments provided in the present disclosure, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another apparatus, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and the parts displayed as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed in a plurality of different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present disclosure may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a readable storage medium. Based on such understanding, the technical solution of the embodiments of the present disclosure may be essentially or a part contributing to the prior art or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, including several instructions to cause a device (may be a single-chip microcomputer, a chip or the like) or a processor (processor) to perform all or part of the steps of the methods described in the embodiments of the present disclosure. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk, etc.
The foregoing is merely a specific embodiment of the disclosure, but the protection scope of the disclosure is not limited thereto, and any changes or substitutions within the technical scope of the disclosure should be covered by the protection scope of the disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.
Claims (14)
1. An information recommendation method, comprising:
obtaining work conversion rate and at least one behavior operation conversion rate of an account number in the statistical duration; the work conversion rate is the conversion rate of target works in works of preset categories, the behavior operation conversion rate is the conversion rate of the target works corresponding to target behavior operations, the target behavior operations are behavior operations recorded by the account in the works of the preset categories, and different behavior operations correspond to different behavior operation conversion rates;
determining a duty cycle of each of the behavioural operation conversions in the work conversion;
determining the attention degree of the account number to the works of the preset category according to the determined duty ratio of each behavior operation conversion rate in the work conversion rate;
when the attention degree is greater than or equal to an attention degree threshold value, putting works to be put into the account; wherein the category to which the work to be put belongs is the preset category.
2. The information recommendation method according to claim 1, wherein the obtaining at least one behavioral operation conversion rate within the statistical time period includes:
acquiring at least one target behavior operation executed by the account in the preset class destination work within the statistical time length;
inquiring the behavior operation conversion rate corresponding to each target behavior operation in the corresponding relation between the target behavior operation and the behavior operation conversion rate, and determining at least one behavior operation conversion rate in the statistical duration.
3. The information recommendation method according to claim 2, wherein the obtaining step of the correspondence relation includes:
obtaining conversion data, namely a first account total number and a second account total number; the conversion data comprise data of conversion operations recorded by accounts on the target works, the total number of the first accounts is the number of the accounts with the target behavior operations recorded in the preset type of target works, the total number of the second accounts is the number of the accounts with the target behavior operations recorded in the preset type of target works, and the target behavior operations are executed on the target works;
Determining that the behavior operation conversion rate corresponding to the target behavior operation is the ratio of the total number of the second account to the total number of the first account;
and generating a corresponding relation containing the behavior operation conversion rate corresponding to each target behavior operation.
4. The information recommendation method of claim 1, wherein the obtaining the conversion rate of the work within the statistical duration comprises:
obtaining conversion data in the statistical time length, and obtaining the total number of the third account numbers and the total number of the fourth account numbers; the conversion data comprise conversion operation data recorded by accounts on the target works, the total number of the third accounts is the number of the accounts with behavior operations recorded in the preset type target works in the statistical time period, the total number of the fourth accounts is the number of the accounts with behavior operations recorded in the preset type target works in the statistical time period, and the conversion operation data are recorded on the target works;
and determining the work conversion rate in the statistical time length as the duty ratio of the total number of the fourth account number in the total number of the third account number.
5. The information recommendation method according to claim 1, wherein the determining the attention of the account number to the preset-class destination work according to the determined duty ratio of each behavior operation conversion rate in the work conversion rate includes:
Acquiring the number of unit time contained in the statistical duration;
and determining the attention degree of the account to the preset class destination works according to the determined duty ratio and the number.
6. The information recommendation method according to claim 5, wherein the attention degree satisfies the following formula:
wherein S is x Representing the attention degree, T representing the number, n representing the total number of target behavior operations performed by the account in the preset class of destination works,representing the duty ratio of the behavior operation conversion rate corresponding to the target behavior operation i in the work conversion rate, wherein i is an integer and i epsilon [1, n ]]A is more than or equal to 0 and less than or equal to 1, b is more than or equal to 0 and less than or equal to 1, and a+b=1.
7. An information recommendation device, characterized by comprising: an acquisition unit and a processing unit;
the acquisition unit is configured to acquire at least one behavior operation conversion rate of the work conversion rate and the account number in the statistical duration; the work conversion rate is the conversion rate of target works in works of preset categories, the behavior operation conversion rate is the conversion rate of the target works corresponding to target behavior operations, the target behavior operations are behavior operations executed by the account in the works of preset categories, and different behavior operations correspond to different behavior operation conversion rates;
The processing unit is configured to determine a ratio of the behavior operation conversion rate acquired by each of the acquisition units in the work conversion rate acquired by the acquisition unit;
the processing unit is further configured to determine the attention degree of the account number to the works of the preset category according to the determined duty ratio of each behavior operation conversion rate in the work conversion rate;
the processing unit is further configured to put the work to be put into the account when the attention degree is greater than or equal to an attention degree threshold; wherein the category to which the work to be put belongs is the preset category.
8. The information recommendation device according to claim 7, wherein the obtaining unit is specifically configured to obtain at least one target behavior operation performed by the account in the preset class destination work within the statistical duration;
the processing unit is specifically configured to query the behavior operation conversion rate corresponding to the target behavior operation obtained by each obtaining unit in the corresponding relation between the target behavior operation and the behavior operation conversion rate, and determine at least one behavior operation conversion rate within the statistical duration.
9. The information recommendation device according to claim 8, wherein the obtaining unit is specifically configured to obtain conversion data, a first account number total number and a second account number total number; the conversion data comprise data of conversion operations recorded by accounts on the target works, the total number of the first accounts is the number of the accounts with the target behavior operations recorded in the preset type of target works, the total number of the second accounts is the number of the accounts with the target behavior operations recorded in the preset type of target works, and the target behavior operations are executed on the target works;
the processing unit is specifically configured to determine that the behavioral operation conversion rate corresponding to the target behavioral operation is the ratio of the total number of the second account numbers acquired by the acquisition unit to the total number of the first account numbers acquired by the acquisition unit;
the processing unit is specifically configured to generate a corresponding relation containing the behavior operation conversion rate corresponding to each target behavior operation.
10. The information recommendation apparatus according to claim 7, wherein the acquisition unit, the method comprises the steps of specifically acquiring conversion data in the statistical time length, and acquiring the total number of third accounts and the total number of fourth accounts; the conversion data comprise conversion operation data recorded by accounts on the target works, the total number of the third accounts is the number of the accounts with behavior operations recorded in the preset type target works in the statistical time period, the total number of the fourth accounts is the number of the accounts with behavior operations recorded in the preset type target works in the statistical time period, and the conversion operation data are recorded on the target works;
The processing unit is specifically configured to determine that the work conversion rate in the statistical duration is the duty ratio of the total number of the fourth account number acquired by the acquisition unit in the total number of the third account number acquired by the acquisition unit.
11. The information recommendation device according to claim 7, wherein the acquisition unit is specifically configured to acquire the number of unit times contained in the statistical duration;
the processing unit is specifically configured to determine the attention degree of the account number to the preset target works according to the determined duty ratio and the number acquired by the acquisition unit.
12. The information recommendation device of claim 11, wherein the attention degree satisfies the following formula:
wherein S is x Representing the attention degree, T representing the number, n representing the total number of target behavior operations performed by the account in the preset class of destination works,representing the duty ratio of the behavior operation conversion rate corresponding to the target behavior operation i in the work conversion rate, wherein i is an integer and i epsilon [1, n ]]A is more than or equal to 0 and less than or equal to 1, b is more than or equal to 0 and less than or equal to 1, and a+b=1.
13. A server, comprising:
a processor;
A memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the information recommendation method of any of claims 1-6.
14. A computer readable storage medium, characterized in that instructions in the storage medium, when executed by a processor of a server, enable the server to perform the information recommendation method according to any of claims 1-6.
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