CN117495453A - Method and device for processing popularization resources and storage medium - Google Patents
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Abstract
The application discloses a processing method, a processing device and a storage medium for popularization resources, which can be applied to the field of maps or Internet of vehicles. Acquiring target popularization resources and associated reference popularization resources; obtaining output indexes aiming at execution information configuration and a plurality of comparison dimensions and calling corresponding effect data; dividing the popularization resource set into positive popularization resources and negative popularization resources according to the effect data; and then, configuring the execution information of the target popularization resource according to the difference between the positive direction and the negative direction. Therefore, the automatic configuration process of the promotion resource execution information is realized, and the execution information adopts forward action information with obvious difference, so that the forward action information is beneficial to the propagation of the promotion information, the effectiveness of the execution information is ensured, and the configuration efficiency of the promotion resource execution information is improved.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a method and an apparatus for processing a popularization resource, and a storage medium.
Background
With the high-speed development of network technology, network media gradually becomes a mainstream popularization resource. The promotion resource is an information medium for showing to users, such as news, advertisement or public welfare propaganda, etc., and how to effectively promote the promotion resource becomes a difficult problem.
Generally, data integration and summarization can be manually performed by observing each dimension information of each popularization resource, and then the rule of integrating data is obtained through experience of operators and configuration of follow-up popularization resource execution information is performed.
However, the efficiency of manually configuring the execution information of the popularization resource is low, the analyzed advertisement strategy output strongly depends on the experience of operators, the execution of the batch popularization process is difficult, and the efficiency of configuring the execution information of the popularization resource is affected.
Disclosure of Invention
In view of this, the present application provides a method for processing promotion resources, which can effectively improve efficiency of execution information configuration of promotion resources.
The first aspect of the present application provides a method for processing a popularization resource, which can be applied to a system or a program including a processing function of the popularization resource in a terminal device, and specifically includes:
acquiring target popularization resources;
determining a reference popularization resource associated with the target popularization resource to integrate the target popularization resource and the reference popularization resource as a popularization resource set;
acquiring an output index aiming at execution information configuration and a plurality of comparison dimensions, and calling effect data corresponding to popularization resources in the popularization resource set under the output index;
Dividing the popularization resource set into positive popularization resources and negative popularization resources according to the effect data;
determining the difference degrees of the positive popularization resource and the negative popularization resource under a plurality of comparison dimensions according to the effect data;
if the difference degree meets a preset condition, configuring the execution information of the target popularization resource according to action information of the forward popularization resource in a plurality of comparison dimensions, wherein the action information is used for indicating popularization operations executed on the target popularization resource in each comparison dimension, and the execution information comprises at least one action information.
Optionally, in some possible implementations of the present application, the dividing the popularization resource set into a positive resource and a negative resource according to the effect data includes:
determining an index value sequence of the popularization resource set under at least one output index according to the effect data;
determining an average value of values in the index value sequence;
dividing the popularization resources with index values larger than or equal to the average value in the popularization resource set into the forward resources;
and dividing the popularization resources with index values smaller than the average value in the popularization resource set into the negative resources.
Optionally, in some possible implementations of the present application, the determining, according to the effect data, a degree of difference between the positive promotion resource and the negative promotion resource in a plurality of contrast dimensions includes:
carrying out standardization processing on the effect data to obtain weighted data;
determining action categories contained in a comparison dimension in response to configuration of a plurality of comparison dimensions;
voting statistics are carried out according to the action categories based on the weighted data, so that voting weight information under each action category is determined;
and determining the difference degree of the positive popularization resource and the negative popularization resource under the corresponding comparison dimension according to the difference value of the voting weight information under each action category.
Optionally, in some possible implementations of the present application, the normalizing the effect data to obtain weighted data includes:
acquiring a first reference value and a second reference value in the effect data, wherein the positions of the first reference value and the second reference value in a numerical ordering queue corresponding to the effect data are different;
determining a reference difference between the first reference value and the second reference value;
Configuring a first formula based on the second reference value and the reference difference value to call the first formula to perform standardized processing on the effect data corresponding to the forward promotion resource to obtain forward weighting information;
configuring a second formula based on the first reference value and the reference difference value to call the second formula to perform standardized processing on the effect data corresponding to the negative popularization resource to obtain negative weighting information;
and integrating the positive weighting information and the negative weighting information to obtain the weighting data.
Optionally, in some possible implementations of the present application, the determining, in response to the configuration of the plurality of comparison dimensions, an action category included in the comparison dimensions includes:
determining a range of values contained by the contrasting dimension in response to configuration of a plurality of contrasting dimensions;
and carrying out average division on the numerical range to obtain the action category.
Optionally, in some possible implementations of the present application, the dividing the numerical range by average to obtain the action category includes:
acquiring history configuration information corresponding to the comparison dimension;
determining distribution information containing various numerical values in the comparison dimension based on the historical configuration information;
And carrying out average division according to the concentrated distribution range indicated by the distribution information to obtain the action category.
Optionally, in some possible implementations of the present application, the determining, in response to the configuration of the plurality of comparison dimensions, an action category included in the comparison dimensions includes:
acquiring configuration of a target object on a network class dimension and a product class dimension;
determining a network transmission object indicated by the network class dimension;
acquiring network resource information allocated for the network transmission object so as to determine an action category contained in the network resource information;
and acquiring promotion content configuration information indicated by the product dimension to determine action categories contained in the promotion content configuration information.
Optionally, in some possible implementations of the present application, if the degree of difference meets a preset condition, configuring the execution information of the target popularization resource according to the action information of the forward popularization resource in a plurality of comparison dimensions includes:
determining positive accumulated votes corresponding to the positive popularization resources and negative accumulated votes corresponding to the negative popularization resources according to the effect information;
Average value calculation is carried out on the positive accumulated votes and the negative accumulated votes so as to determine a difference threshold value corresponding to the preset condition;
if the difference degree is greater than or equal to the difference threshold value and the target popularization resource is divided into the negative popularization resource, configuring execution information of the target popularization resource according to action information of the positive popularization resource in a plurality of comparison dimensions.
Optionally, in some possible implementations of the present application, the configuring the execution information of the target popularization resource according to the action information of the forward popularization resource in a plurality of the comparison dimensions includes:
acquiring the action information of the forward promotion resource under a plurality of comparison dimensions;
determining an execution numerical range corresponding to the action information;
and extracting the execution information of the intermediate value configuration target popularization resource corresponding to the execution numerical range.
Optionally, in some possible implementations of the present application, the obtaining the target popularization resource includes:
acquiring a popularization object identifier input by a target object;
and traversing the resources based on the popularization object identification to determine the target popularization resources.
Optionally, in some possible implementations of the present application, the determining a reference promotion resource associated with the target promotion resource to integrate the target promotion resource and the reference promotion resource as a promotion resource set includes:
acquiring industry information corresponding to the target popularization resource;
determining candidate popularization resources related to industries corresponding to the target popularization resources according to the industry information;
matching the candidate popularization resources based on the flow information corresponding to the target popularization resources to determine the reference popularization resources associated with the target popularization resources;
integrating the target popularization resource and the reference popularization resource into the popularization resource set.
Optionally, in some possible implementations of the present application, the method further includes:
classifying the execution information according to the comparison dimension to obtain display information;
displaying the display information on a target interface;
and responding to the selection operation of the target object on the display information in the target interface, and executing the execution information corresponding to the selection operation on the target popularization resource.
A second aspect of the present application provides a processing apparatus for promoting resources, including:
The acquisition unit is used for acquiring target popularization resources;
the determining unit is used for determining a reference popularization resource associated with the target popularization resource to integrate the target popularization resource and the reference popularization resource into a popularization resource set;
the acquisition unit is further used for acquiring output indexes and a plurality of comparison dimensions aiming at execution information configuration, and invoking effect data corresponding to popularization resources in the popularization resource set under the output indexes;
the processing unit is used for dividing the popularization resource set into positive popularization resources and negative popularization resources according to the effect data;
the processing unit is further used for determining the difference degree of the positive popularization resource and the negative popularization resource under a plurality of comparison dimensions according to the effect data;
the processing unit is further configured to configure the execution information of the target popularization resource according to action information of the forward popularization resource in a plurality of comparison dimensions if the difference degree meets a preset condition, where the action information is used to indicate popularization operations performed on the target popularization resource in each comparison dimension, and the execution information includes at least one action information.
Optionally, in some possible implementations of the present application, the processing unit is specifically configured to determine, according to the effect data, an index value sequence of the popularization resource set under at least one of the output indexes;
the processing unit is specifically configured to determine an average value of values in the index value sequence;
the processing unit is specifically configured to divide the popularization resource with the index value greater than or equal to the average value in the popularization resource set into the forward resource;
the processing unit is specifically configured to divide the popularization resource with the index value smaller than the average value in the popularization resource set into the negative resource.
Optionally, in some possible implementations of the present application, the processing unit is specifically configured to perform normalization processing on the effect data to obtain weighted data;
the processing unit is specifically configured to determine an action category contained in the comparison dimension in response to configuration of a plurality of comparison dimensions;
the processing unit is specifically configured to perform voting statistics according to the action categories based on the weighted data, so as to determine voting weight information under each action category;
the processing unit is specifically configured to determine, according to the difference value of the voting weight information under each action category, a difference degree between the positive popularization resource and the negative popularization resource under the corresponding comparison dimension.
Optionally, in some possible implementation manners of the present application, the processing unit is specifically configured to obtain a first reference value and a second reference value in the effect data, where the first reference value and the second reference value are located in different positions in a numerical ranking queue corresponding to the effect data;
the processing unit is specifically configured to determine a reference difference value between the first reference value and the second reference value;
the processing unit is specifically configured to configure a first formula based on the second reference value and the reference difference value, so as to call the first formula to perform standardized processing on the effect data corresponding to the forward promotion resource to obtain forward weighting information;
the processing unit is specifically configured to configure a second formula based on the first reference value and the reference difference value, so as to call the second formula to perform standardized processing on the effect data corresponding to the negative popularization resource to obtain negative weighting information;
the processing unit is specifically configured to integrate the positive weighting information and the negative weighting information to obtain the weighting data.
Optionally, in some possible implementations of the present application, the processing unit is specifically configured to determine a range of values contained in the comparison dimension in response to a configuration of a plurality of the comparison dimensions;
The processing unit is specifically configured to divide the numerical range on average, so as to obtain the action category.
Optionally, in some possible implementation manners of the present application, the processing unit is specifically configured to obtain history configuration information corresponding to the comparison dimension;
the processing unit is specifically configured to determine distribution information including each numerical value in the comparison dimension based on the historical configuration information;
the processing unit is specifically configured to divide the centralized distribution range indicated by the distribution information on average, so as to obtain the action category.
Optionally, in some possible implementations of the present application, the processing unit is specifically configured to obtain a configuration of the target object for a network class dimension and a product class dimension;
the processing unit is specifically configured to determine a network transmission object indicated by the network class dimension;
the processing unit is specifically configured to obtain network resource information allocated to the network transmission object, so as to determine an action category included in the network resource information;
the processing unit is specifically configured to obtain promotion content configuration information indicated by the product dimension, so as to determine an action category contained in the promotion content configuration information.
Optionally, in some possible implementation manners of the present application, the processing unit is specifically configured to determine, according to the effect information, a positive accumulated vote corresponding to the positive popularization resource and a negative accumulated vote corresponding to the negative popularization resource;
the processing unit is specifically configured to perform average calculation on the positive accumulated votes and the negative accumulated votes, so as to determine a difference threshold corresponding to the preset condition;
the processing unit is specifically configured to configure execution information of the target popularization resource according to action information of the forward popularization resource in a plurality of comparison dimensions if the difference degree is greater than or equal to the difference threshold and the target popularization resource is divided into the negative popularization resource.
Optionally, in some possible implementations of the present application, the processing unit is specifically configured to obtain the action information of the forward promotion resource in a plurality of comparison dimensions;
the processing unit is specifically configured to determine an execution numerical range corresponding to the action information;
the processing unit is specifically configured to extract the execution information of the intermediate value configuration target popularization resource corresponding to the execution numerical range.
Optionally, in some possible implementation manners of the present application, the acquiring unit is specifically configured to acquire a promotion object identifier input by a target object;
the obtaining unit is specifically configured to perform resource traversal based on the promotion object identifier, so as to determine the target promotion resource.
Optionally, in some possible implementation manners of the present application, the determining unit is specifically configured to obtain industry information corresponding to the target popularization resource;
the determining unit is specifically configured to determine candidate popularization resources related to industries corresponding to the target popularization resources according to the industry information;
the determining unit is specifically configured to match the candidate popularization resources based on flow information corresponding to the target popularization resource, so as to determine the reference popularization resource associated with the target popularization resource;
the determining unit is specifically configured to integrate the target popularization resource and the reference popularization resource into the popularization resource set.
Optionally, in some possible implementation manners of the present application, the processing unit is specifically configured to classify the execution information according to the comparison dimension to obtain the display information;
The processing unit is specifically used for displaying the display information on a target interface;
the processing unit is specifically configured to respond to a selection operation of a target object on the display information in the target interface, and execute execution information corresponding to the selection operation on the target popularization resource.
A third aspect of the present application provides a computer device comprising: a memory, a processor, and a bus system; the memory is used for storing program codes; the processor is configured to execute the processing method of the promotion resource according to the first aspect or any one of the first aspects according to an instruction in the program code.
A fourth aspect of the present application provides a computer-readable storage medium having instructions stored therein that, when executed on a computer, cause the computer to perform the method of processing a promotional resource of the first aspect or any of the first aspects described above.
According to one aspect of the present application, there is provided a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions, so that the computer device performs the processing method of the promotion resource provided in the above-mentioned first aspect or various optional implementations of the first aspect.
From the above technical solutions, the embodiments of the present application have the following advantages:
acquiring target popularization resources; then determining a reference popularization resource associated with the target popularization resource, and integrating the target popularization resource and the reference popularization resource into a popularization resource set; obtaining output indexes aiming at execution information configuration and a plurality of comparison dimensions, and calling corresponding effect data of popularization resources in a popularization resource set under the output indexes; dividing the popularization resource set into positive popularization resources and negative popularization resources according to the effect data; then determining the difference degree of the forward promotion resource and the negative promotion resource under a plurality of comparison dimensions according to the effect data; if the difference degree meets the preset condition, configuring execution information of the target popularization resource according to action information of the forward popularization resource in a plurality of comparison dimensions, wherein the action information is used for indicating popularization operation executed on the target popularization resource in each comparison dimension, and the execution information comprises at least one action information. Therefore, the automatic configuration process of the promotion resource execution information is realized, the execution information of the target promotion resource is subjected to reference configuration by adopting the reference promotion resource, and forward action information is adopted for the items with obvious differences in the reference configuration process, so that the forward action information is beneficial to the propagation of the promotion information, the effectiveness of the execution information is ensured, and the configuration efficiency of the promotion resource execution information is improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present application, and that other drawings may be obtained according to the provided drawings without inventive effort to a person skilled in the art.
FIG. 1 is a network architecture diagram of the operation of a processing system for promoting resources;
fig. 2 is a flowchart of a process of popularizing resources according to an embodiment of the present application;
FIG. 3 is a flowchart of a method for processing promotion resources according to an embodiment of the present application;
fig. 4 is a schematic view of a scenario of a method for processing a promotion resource according to an embodiment of the present application;
fig. 5 is a schematic view of a scenario of another method for processing a promotional resource according to an embodiment of the present application;
FIG. 6 is a flowchart of another method for processing promotion resources according to an embodiment of the present application;
fig. 7 is a flowchart of another method for processing promotion resources according to an embodiment of the present application;
fig. 8 is a schematic view of a scenario of another method for processing promotion resources according to an embodiment of the present application;
Fig. 9 is a schematic structural diagram of a processing device for promoting resources according to an embodiment of the present application;
fig. 10 is a schematic structural diagram of a terminal device according to an embodiment of the present application;
fig. 11 is a schematic structural diagram of a server according to an embodiment of the present application.
Detailed Description
The embodiment of the application provides a method for processing popularization resources and a related device, which can be applied to a system or a program containing the processing function of the popularization resources in terminal equipment, and the method comprises the steps of obtaining target popularization resources; then determining a reference popularization resource associated with the target popularization resource, and integrating the target popularization resource and the reference popularization resource into a popularization resource set; obtaining output indexes aiming at execution information configuration and a plurality of comparison dimensions, and calling corresponding effect data of popularization resources in a popularization resource set under the output indexes; dividing the popularization resource set into positive popularization resources and negative popularization resources according to the effect data; then determining the difference degree of the forward promotion resource and the negative promotion resource under a plurality of comparison dimensions according to the effect data; if the difference degree meets the preset condition, configuring execution information of the target popularization resource according to action information of the forward popularization resource in a plurality of comparison dimensions, wherein the action information is used for indicating popularization operation executed on the target popularization resource in each comparison dimension, and the execution information comprises at least one action information. Therefore, the automatic configuration process of the promotion resource execution information is realized, the execution information of the target promotion resource is subjected to reference configuration by adopting the reference promotion resource, and forward action information is adopted for the items with obvious differences in the reference configuration process, so that the forward action information is beneficial to the propagation of the promotion information, the effectiveness of the execution information is ensured, and the configuration efficiency of the promotion resource execution information is improved.
The terms "first," "second," "third," "fourth" and the like in the description and in the claims of this application and in the above-described figures, if any, 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 embodiments of the present application described herein may be capable of operation in sequences other than those illustrated or described herein, for example. Furthermore, the terms "comprises," "comprising," and "includes" and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.
First, some terms that may appear in the embodiments of the present application will be explained.
Consumption: the amount the advertiser spends placing the advertisement.
oCPA advertisement: an intelligent automatic bidding strategy for effect advertisements. The advertiser may select a particular optimization objective (e.g., activation, placement, form reservation) and provide a desired average conversion cost. The system can estimate the conversion value of each display through machine learning according to conversion data reported by an advertiser, automatically bid, and deduct fees according to clicking.
Optimization target: the advertiser will want target object behavior to be achieved by this marketing campaign, and the model will look for users more prone to these behaviors, such as payment, key page browsing and attention to public numbers, etc., based on the set optimization goals.
It should be understood that the method for processing the popularization resource provided by the application can be applied to a system or a program containing a processing function of the popularization resource in the terminal device, for example, advertisement management, specifically, the processing system of the popularization resource can be operated in a network architecture shown in fig. 1, as shown in fig. 1, a network architecture diagram operated by the processing system of the popularization resource, as can be known from the figure, the processing system of the popularization resource can provide a processing process of the popularization resource with a plurality of information sources, namely, a server side configures a target popularization resource, so that the target popularization resource is displayed in various terminals according to a proper popularization effect; it will be appreciated that various terminal devices are shown in fig. 1, the terminal devices may be computer devices, in the actual scenario, there may be more or less terminal devices participating in the process of popularizing resources, and the specific number and types are not limited herein, and in addition, one server is shown in fig. 1, but in the actual scenario, there may also be participation of multiple servers, where the specific number of servers is determined by the actual scenario.
In this embodiment, the server may be an independent physical server, or may be a server cluster or a distributed system formed by a plurality of physical servers, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDNs, and basic cloud computing services such as big data and artificial intelligence platforms. The terminal may be, but is not limited to, a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, a smart voice interaction device, a smart home appliance, a vehicle-mounted terminal, and the like. The terminals and servers may be directly or indirectly connected by wired or wireless communication, and the terminals and servers may be connected to form a blockchain network, which is not limited herein.
It will be appreciated that the processing system of the promotional resource described above may be operable on a personal mobile terminal, for example: the application can be used as advertisement management, can also be run on a server, and can also be used as a process for running on a third party device to provide popularization resources so as to obtain a processing result of the popularization resources of the information source; the specific processing system for popularizing resources may be in a program form and may also be operated as a system component in the device, or may also be used as a cloud service program, where the specific operation mode is determined by an actual scenario and is not limited herein.
With the high-speed development of network technology, network media gradually becomes a mainstream popularization resource. The promotion resource is an information medium for showing to users, such as news, advertisement or public welfare propaganda, etc., and how to effectively promote the promotion resource becomes a difficult problem.
Generally, data integration and summarization can be manually performed by observing each dimension information of each popularization resource, and then the rule of integrating data is obtained through experience of operators and configuration of follow-up popularization resource execution information is performed.
However, the efficiency of manually configuring the execution information of the popularization resource is low, the analyzed advertisement strategy output strongly depends on the experience of operators, the execution of the batch popularization process is difficult, and the efficiency of configuring the execution information of the popularization resource is affected.
In order to solve the above problems, the present application proposes a method for processing a promotion resource, where the method is applied to a flow frame of processing a promotion resource shown in fig. 2, as shown in fig. 2, and is a flow frame diagram of processing a promotion resource provided in an embodiment of the present application, and a reference promotion resource set similar to a target promotion resource is determined by analyzing a target promotion resource input by a server side, so as to obtain a reference set; and further, carrying out difference degree calculation on the popularization resources in the reference set under a plurality of dimensions, and configuring dimension configurations with obvious differences in the execution information of the target popularization resources, so that popularization of the target popularization resources according to the execution information is carried out.
It can be understood that the method provided by the application can be a program writing method, which is used as a processing logic in a hardware system, and can also be used as a processing device of a popularization resource, and the processing logic is realized in an integrated or external mode. As an implementation manner, the processing device of the popularization resource obtains the target popularization resource; then determining a reference popularization resource associated with the target popularization resource, and integrating the target popularization resource and the reference popularization resource into a popularization resource set; obtaining output indexes aiming at execution information configuration and a plurality of comparison dimensions, and calling corresponding effect data of popularization resources in a popularization resource set under the output indexes; dividing the popularization resource set into positive popularization resources and negative popularization resources according to the effect data; then determining the difference degree of the forward promotion resource and the negative promotion resource under a plurality of comparison dimensions according to the effect data; if the difference degree meets the preset condition, configuring execution information of the target popularization resource according to action information of the forward popularization resource in a plurality of comparison dimensions, wherein the action information is used for indicating popularization operation executed on the target popularization resource in each comparison dimension, and the execution information comprises at least one action information. Therefore, the automatic configuration process of the promotion resource execution information is realized, the execution information of the target promotion resource is subjected to reference configuration by adopting the reference promotion resource, and forward action information is adopted for the items with obvious differences in the reference configuration process, so that the forward action information is beneficial to the propagation of the promotion information, the effectiveness of the execution information is ensured, and the configuration efficiency of the promotion resource execution information is improved.
With reference to fig. 3, fig. 3 is a flowchart of a method for processing a promotion resource, where the method may be executed by a server or a terminal, and the embodiment of the present application at least includes the following steps:
301. and obtaining target popularization resources.
In this embodiment, the target promotion resource is a promotion resource to be promoted, and the expected promotion effect is achieved by configuring a promotion policy (execution information) of the target promotion resource.
Specifically, the target promotion resource may be in the form of advertisement, news or other media; for the scene that the target popularization resource is an advertisement, the target popularization resource can be an oCPA advertisement, namely an advertisement adjusted by an intelligent automatic bidding strategy aiming at the effect advertisement; in addition, the media content form of the target popularization resource can be pictures, videos and the like, and the specific media content form is determined according to actual scenes.
In one possible scenario, the target promotion resource may be obtained by a promotion object identification ID, that is, a promotion object identification input by a target object is firstly obtained, where the target object may be a user, a terminal or other input object; and then traversing the resources based on the promotion object identification to determine the target promotion resources.
It will be appreciated that the promotion object identification may be a bulk upload object indicating a promotion resource (advertisement), such as a single advertisement ID or multiple advertisement IDs, or a collection of IDs for multiple advertisements; the promotion object identifier can also be the name of the advertiser, so that all advertisement IDs under the name of the advertiser are extracted, and the processing efficiency of the target promotion resource is improved.
In the embodiment, the effect of optimizing popularization is achieved by carrying out strategy configuration on the target popularization resource, the specific processing process is shown in a scene framework in fig. 4, and fig. 4 is a scene schematic diagram of a method for processing the popularization resource, which is provided by the embodiment of the application; the diagram shows that the information configuration is firstly carried out in the strategy configuration process, and specifically comprises the configuration of target popularization resources, the configuration of reference popularization resources, the configuration of comparison dimensions and the configuration of output indexes; then, carrying out difference degree calculation based on the information configuration, wherein the difference degree calculation process adopts effect data corresponding to output indexes, carries out positive and negative resource division based on the effect data, carries out multi-dimensional comparison on the divided positive and negative resources, and further carries out difference degree judgment on each dimension so as to determine a difference significant item; furthermore, the strategy output process can be performed, namely the configuration of the execution information is performed according to the action information corresponding to the difference significant item, wherein each reference popularization resource is sequenced according to consumption, so that the allocable information of the popularization resource is ensured; therefore, the automatic strategy generation process can be completed, and popularization operation is performed in response to the manually selected or automatically pushed strategy.
Through the scene architecture, various dimensions of the user target advertisement and other advertisements of the same type are compared in an information configuration range defined by a user, such as category dimensions including flow information, service provider information, advertisement base information, crowd information, product application information, commodity information, material information, landing page information and the like, and a comparison result is output at the front end. The system further outputs dependent indexes such as click rate or conversion rate and the like according to the user-defined strategies, all advertisements in the comparison pool are divided into positive and negative parts expressed on the indexes, the difference degree of each index is calculated through a difference degree model, if the index has obvious difference between the positive and negative directions and the target advertisement falls into a negative interval, a corresponding positive strategy is output to the user, and the user can select the system to automatically implement the strategy or manually implement the strategy subsequently.
302. And determining a reference popularization resource associated with the target popularization resource to integrate the target popularization resource and the reference popularization resource as a popularization resource set.
In this embodiment, the reference promotion resource is a promotion resource similar to the target promotion resource, and may be specifically a promotion resource of the same type, the same industry, or a specified target; the action information with good popularization effect under each comparison dimension can be extracted through the configuration of the reference popularization resource, so that references are provided for the strategy configuration process of the target popularization resource.
Specifically, for determining the popularization resource set, industry information, such as finance, education, games, etc., corresponding to the target popularization resource can be acquired first; then determining candidate popularization resources related to industries corresponding to the target popularization resources according to the industry information; considering that the flow rate is an important consideration dimension in the effect evaluation index of the popularization resource, the candidate popularization resource can be matched based on the flow rate information corresponding to the target popularization resource so as to determine the reference popularization resource associated with the target popularization resource, thereby improving the reference value of the similar resource; further, the target popularization resource and the reference popularization resource can be integrated into a popularization resource set.
303. And acquiring output indexes aiming at execution information configuration and a plurality of comparison dimensions, and calling effect data corresponding to popularization resources in the popularization resource set under the output indexes.
In this embodiment, the output index is a policy output dependency index, that is, the output index is configured according to the output policy, and the output index is used to evaluate the high quality degree of the popularization effect of the output policy; specifically, the output index may include a click rate, an exposure rate, a conversion rate, and other parameter indexes for evaluating the effect in the popularization process of the popularization resource, and the effect data is numerical data corresponding to the output index, for example, the effect data indicates that the click rate is 0.6.
In one possible scenario, the comparison dimension includes a network class dimension and a product class dimension, where the network class dimension is used to indicate a feature dimension corresponding to various network resource object configurations in a promotion process of promoting the resource, and the product class dimension is a configuration dimension of a product or a promotion target indicated by the promotion resource.
Specifically, the network class dimension may include traffic information (e.g., traffic posted on various media platforms or social software), facilitator information (e.g., agent name/license plate, etc.), and the like; the product dimension may include dimensions such as advertisement base information (e.g., promotion target/depth optimization target, etc.), crowd information (e.g., gender/age/region, etc.), product application information (e.g., bidding strategy/whether to expand, etc.), commodity information (e.g., commodity class four, etc.), material information (e.g., picture or video advertisement/creative form, etc.), and landing page information (e.g., landing page type, etc.), and the comparison result of multiple advertisements such as target advertisement and similar advertisement on these dimensions may be realized by one filtering operation, thereby improving the data processing efficiency.
304. And dividing the popularization resource set into positive popularization resources and negative popularization resources according to the effect data.
In this embodiment, the forward promotion resource is a promotion resource having a forward promotion effect on the promotion effect in the promotion resource set, and the reverse promotion resource is the reverse promotion resource.
Specifically, the division of the forward promotion resource and the negative promotion resource can be performed through a fixed threshold, for example, the output index is the conversion rate, and the promotion resource with the conversion rate greater than or equal to 0.6 is specified as the forward promotion resource, and the promotion resource with the conversion rate less than 0.6 is specified as the negative promotion resource.
Further, considering that the effect data of different popularization resource types may correspond to different evaluation standards, the method can also be performed by numerical average value indicated by the effect data, that is, firstly, determining an index value sequence of the popularization resource set under at least one output index according to the effect data, for example, the output index is conversion rate, and the index value sequence is a conversion rate numerical value sequence corresponding to each popularization resource in the popularization resource set; then determining the average value of the values in the index value sequence; further dividing the popularization resources with index values larger than or equal to the average value in the popularization resource set into forward resources; and the popularization resources with index values smaller than the average value in the popularization resource set are divided into negative resources, so that the effectiveness of the positive popularization resources and the negative popularization resources is improved.
In one possible scenario, the output index is the conversion rate, and the index value sequence includes k1=0.5, k2=0.4, k3=0.6, k4=0.2, k5=0.3, thenTherefore, the positive promotion resources are k1, k2 and k3, and the negative promotion resources are k4 and k5.
305. And determining the difference degree of the forward promotion resource and the negative promotion resource under a plurality of comparison dimensions according to the effect data.
In this embodiment, the calculation process of the difference degree is to calculate the corresponding effect data under each comparison dimension respectively, specifically, the difference degree may be 0.8-0.5=0.3 by calculating the absolute difference between the positive popularization resource and the negative popularization resource, for example, the conversion rate of the positive popularization resource is 0.8 and the conversion rate of the negative popularization resource is 0.5 in the comparison process of dimension 1.
In one possible scenario, in order to improve the representativeness of the difference between the data of the positive popularization resource and the negative popularization resource, the difference value may be calculated after the normalization processing of the data; specifically, the effect data may be first normalized, for example, min-max normalized, to obtain weighted data; then, responding to the configuration of a plurality of comparison dimensions, and determining action categories contained in the comparison dimensions; voting statistics are carried out according to action categories based on the weighted data, so that voting weight information under each action category is determined; and further determining the difference degree of the positive popularization resource and the negative popularization resource under the corresponding comparison dimension according to the difference value of the voting weight information under each action category.
Optionally, since the negative advertisement weight value is a negative value, the representativeness of the difference degree can be improved, so that the min-max standardization algorithm needs to be optimized, that is, for the first reference value and the second reference value in the first obtained effect data, the positions of the first reference value and the second reference value in the numerical ranking queue corresponding to the effect data are different, for example, the first reference value is a max value, the second reference value is a min value, and the specific ranking position can be other positions, for example, the value with the second last or last value; then determining a reference difference value between the first reference value and the second reference value; further, a first formula is configured based on the second reference value and the reference difference value, so that effect data corresponding to the forward promotion resource is standardized by calling the first formula to obtain forward weighting information; configuring a second formula based on the first reference value and the reference difference value to call the second formula to perform standardized processing on the effect data corresponding to the negative popularization resource to obtain negative weighting information; the positively weighted information and negatively weighted information are then integrated to obtain weighted data. Wherein the first formula and the second formula may be expressed as:
wherein, min and max are the same in the positive and negative direction calculation process, and are respectively the minimum value and the maximum value of the data column.
In one possible scenario, the above process of performing the difference degree calculation based on the voting weight information may refer to an example in which the output index is the conversion rate, and the comparison dimension is the bidding strategy, and the comparison dimension includes two types of actions, namely a and B. Specific effect data indicates a conversion rate k1=0.5, k2=0.4, k3=0.6, k4=0.2, k5=0.3, thenSo positive is k1, k2, k3, negative is k4, k5, where max=max (k 1 … k 5) =0.6; min=min (k 1 … k 5) =0.2.
Then, in the calculation process of the voting weight information under each action category, the m values of the category index classification are voted, and the following formula can be referred to:
wherein m is adopted as the jth advertisement in the formula i And participating in calculation, wherein m indicates each action category.
Statistics of voting information can be performed with reference to the above formula, i.e., weight 1=0.75, weight 2=0.5, weight 3=1, weight 4= -1, weight 5= -0.75.
So for action class a, B, the a bid strategy is selected as indicated by k1k3 in the comparison dimension; k2k4k5 selects the B bid strategy, then:
voting weight information ma=weight 1+weight 3=1.75 for action class a;
voting weight information mb=weight 2+weight4+weight 5= -1.25 for action class B;
The calculation formula of the difference degree is as follows:
diff＝max(m 1 ,...,m i )-min(m 1 ,...,m i )
i.e. diff=ma-mb=3.
The above embodiments describe a scenario in which the action index indicated by the comparison dimension is of a category, and in some possible scenarios, the action index indicated by the comparison dimension is of a continuous value, for example 1-10,; for a scene of consecutive values, a range of values encompassed by a comparison dimension may be determined in response to a configuration of a plurality of comparison dimensions; and then, the numerical range is divided evenly to obtain action categories, for example, continuous numerical values 1-9 are divided into three sections, namely 1-3, 3-6 and 6-9, and then the action indexes indicated by the comparison dimension are used for calculating the difference degree calculation process of the categories.
Optionally, considering that the distribution of the continuous values may be relatively wide, in order to avoid the influence of abnormal data on the calculation process of the difference degree, historical configuration information corresponding to the comparison dimension may be obtained; then determining distribution information containing each numerical value in the comparison dimension based on the historical configuration information; and carrying out average division according to the concentrated distribution range indicated by the distribution information to obtain action categories, so as to carry out average division processing on the numerical value range in the numerical value distribution set, and taking the action index indicated by the comparison dimension as a category difference degree calculation process.
In addition, the determining process of the action category of the comparison dimension can be performed based on the dimension type contained in the comparison dimension, namely, firstly, the configuration of the target object to the network dimension and the product dimension is obtained; then determining network transmission objects indicated by the network class dimension, such as published media platforms and the like; then obtaining the network resource information allocated for the network transmission object to determine the action category contained in the network resource information, such as the configuration strategy of the flow, the selection of the service provider and the like; and acquiring promotion content configuration information indicated by product dimension to determine action categories contained in the promotion content configuration information, such as promotion target crowd, promotion product classification information and the like, so as to improve accuracy of the action categories.
It can be appreciated that the process of the above-mentioned difference calculation may be packaged as a difference model, that is, the process of performing the above-mentioned difference calculation by the difference model; according to the embodiment, the difference degree model in the difference degree calculation process is used for calculating each dimension, forward and standardized operation strategies can be produced, operators can select a system mode to finish execution of the operation strategies in batches, a whole set of operation schemes of strategy output and systematic strategy landing is achieved, and the operation efficiency is improved, and meanwhile the advertisement distributable information of a platform is further improved.
306. If the difference degree meets the preset condition, the execution information of the target popularization resource is configured according to the action information of the forward popularization resource in a plurality of comparison dimensions.
In this embodiment, the action information is used to indicate a promotion operation performed on the target promotion resource under each comparison dimension, where the execution information includes at least one action information, that is, the execution information may be composed of a plurality of action information, for example, the plurality of action information included in the execution information is a service provider selection a, the flow is configured on the media platform B, and the promotion target crowd is C.
Specifically, for the judgment that the difference degree meets the preset condition, that is, whether the difference is significant or not, the positive accumulated votes corresponding to the positive popularization resources and the negative accumulated votes corresponding to the negative popularization resources can be determined according to the effect information; then, carrying out average value calculation on the positive accumulated votes and the negative accumulated votes to determine a difference threshold value corresponding to a preset condition; if the difference degree is greater than or equal to the difference threshold value and the target popularization resource is divided into negative popularization resources, the execution information of the target popularization resource is configured according to the action information of the positive popularization resource in a plurality of comparison dimensions, so that the action with negative influence on the popularization effect in the target popularization resource is removed, and the action is updated to be the positive action, so that the popularization effect is improved.
Optionally, for the configuration of the variance threshold, for accumulating the average variance of the votes, the calculation formula is:
wherein weight is Forward direction For forward accumulated voting, weight Negative going Accumulated votes for negative direction.
If diff is larger than or equal to beta, the advertisement is considered to have obvious difference in the dimension, and when the target advertisement takes the value m t ≠max(m 1 ,…,m i ) When outputting the operation strategy: the targeted advertisement is suggested to take max (m 1 ,…,m i ) And (5) acting.
In addition, for a scene in which the action category is a continuous value, an intermediate value of the category value range can be selected as the action information to perform configuration of the execution information. Firstly, acquiring action information of forward promotion resources under a plurality of contrast dimensions; then determining an execution numerical value range corresponding to the action information; and extracting the execution information of the intermediate value configuration target popularization resource corresponding to the execution numerical range.
In a possible scenario, for the comparison dimension involved in the above-mentioned difference calculation process and the corresponding action category, fig. 5 may be used to illustrate, and fig. 5 is a schematic view of a scenario of another method for processing promotion resources provided in an embodiment of the present application; the figure shows the comparison dimension which may participate in the calculation, and the sub-dimension which the comparison dimension contains, in order to facilitate the configuration of the policy output by the operator. In the configuration process of the comparison dimension, the sub-dimension under the comparison dimension selected by the user can be fully selected, so that the configuration efficiency is improved.
In another possible scenario, the configuration process of the policy may be exposed, that is, the execution information is classified according to a comparison dimension, for example, classified according to a dimension division in fig. 5, so as to obtain exposed information, for example, policy 1 and policy 2; then displaying the display information on a target interface; and responding to the selection operation of the target object on the display information in the target interface, and executing the execution information corresponding to the selection operation on the target popularization resource.
As can be seen from the above embodiments, the target popularization resource is obtained; then determining a reference popularization resource associated with the target popularization resource, and integrating the target popularization resource and the reference popularization resource into a popularization resource set; obtaining output indexes aiming at execution information configuration and a plurality of comparison dimensions, and calling corresponding effect data of popularization resources in a popularization resource set under the output indexes; dividing the popularization resource set into positive popularization resources and negative popularization resources according to the effect data; then determining the difference degree of the forward promotion resource and the negative promotion resource under a plurality of comparison dimensions according to the effect data; if the difference degree meets the preset condition, configuring execution information of the target popularization resource according to action information of the forward popularization resource in a plurality of comparison dimensions, wherein the action information is used for indicating popularization operation executed on the target popularization resource in each comparison dimension, and the execution information comprises at least one action information. Therefore, the automatic configuration process of the promotion resource execution information is realized, the execution information of the target promotion resource is subjected to reference configuration by adopting the reference promotion resource, and forward action information is adopted for the items with obvious differences in the reference configuration process, so that the forward action information is beneficial to the propagation of the promotion information, the effectiveness of the execution information is ensured, and the configuration efficiency of the promotion resource execution information is improved.
The following description is made in connection with a scenario in which promotion content is an advertisement. Referring to fig. 6, fig. 6 is a flowchart of another method for processing promotion resources according to an embodiment of the present application, where the embodiment of the present application at least includes the following steps:
601. a targeted advertisement is entered.
In this embodiment, the target advertisement is the target promotion resource in the embodiment shown in fig. 3, and the related feature description may be referred to. The target advertisement can be obtained through single advertisement ID, multiple advertisement IDs or batch uploading, and all advertisement IDs under the name of the advertiser can be extracted as target advertisements based on the name of the advertiser.
602. And (5) screening the similar advertisements.
In this embodiment, the similar advertisement is the reference promotion resource in the embodiment shown in fig. 3, and the related feature description may be referred to.
Specifically, the screening of the similar advertisements is limited to specific industries, specific flow rates, specific optimization targets and the like; since the advertisement can be a picture or a video, the advertisement can also be screened from the perspective of the display parameters, for example, the media content type is screened, i.e. the like advertisement of the video advertisement is a video advertisement.
603. The comparison time is defined.
In this embodiment, the defined contrast time may be a fixed time, for example, approximately 7 days, approximately 3 days, etc.; the dynamic range may also be used, for example, the comparison time may be an activity time range corresponding to the target advertisement, or an activity time range when the heat information reaches the threshold, and the specific time range is determined by the actual scene and is not limited herein.
604. And (5) comparing dimension configurations.
In this embodiment, the comparison dimension includes traffic information (media platform or social software, etc.), service provider information (agent name/license plate, etc.), advertisement base information (promotion target/depth optimization target, etc.), crowd information (gender/age/region, etc.), product application information (bid strategy/whether to expand, etc.), commodity information (commodity class four, etc.), material information (picture or video advertisement/creative form, etc.), landing page information (landing page type, etc.), etc.
Specifically, the dimension to be compared is selected, the related personnel can select the dimension from the complete dimensions in a self-defined manner, and if the dimension is not selected, all the dimensions are displayed by default.
605. Policy output relies on index configuration.
In this embodiment, steps 601-605 are a configuration process entered by the user, and specific inputs include entering targeted advertisements (such advertisements become targeted advertisements): the client inputs a single advertisement ID, or inputs a plurality of advertisement IDs in batches, or inputs the name of the advertiser, namely all the advertisement IDs under the advertiser; (may be bidding oCPA advertisements, while contractual advertisements may not be configured within contrast).
Specifically, the policy output dependency index is the output index in the embodiment shown in fig. 3, and the related feature description may be referred to, so the policy output dependency index may be click rate, conversion rate, exposure, and the like.
It can be understood that single selection or multiple selection can be performed on the click rate and the conversion rate, and in a multiple selection scenario, the effect data corresponding to the output index is calculated based on the selected multiple indexes, for example, the click rate and the conversion rate are selected as the output index, wherein the click rate is 0.5, the conversion rate is 0.2, and the effect data is the effect parameter=0.5+0.2=0.7, so that the calculation process of the multiple attention indexes can be considered, and the policy configuration efficiency is improved.
606. And calling a difference degree model to calculate the difference degree based on the comparison dimension.
In this embodiment, step 606 is a process of system calculation. The configuration of the variance model is described with reference to the variance calculation in the embodiment shown in fig. 3.
Specifically, the difference calculating process is shown in fig. 7, and fig. 7 is a flowchart of another method for processing promotion resources provided in the embodiment of the present application; comprises the following steps:
step 1: and extracting corresponding data from each data platform according to the comparison dimension input by the user. The category data of the comparison dimension can be integrated according to the granularity of the advertisement ID, such as single advertisement, aggregated advertisement and advertiser to determine the category data of the comparison dimension.
Step 2: and calculating each contrast dimension by using a difference degree model.
The difference degree model is an algorithm for measuring the difference degree of positive and negative samples in each dimension, according to a policy dependency index input by a user, each advertisement is divided into two parts, namely 1 (positive direction) and 0 (negative direction), wherein the positive direction is an advertisement larger than or equal to the average value of the index, the negative direction is an advertisement smaller than the average value of the index, the system starts to calculate from the first dimension until all dimensions are calculated, the dimensions are divided into a category dimension and a continuous dimension, the category dimension is a category such as "whether or not", "ABC", and the like, the continuous dimension is a continuous number, for example, a number of 0-10, and the like, and the calculation methods are slightly different for the two types of dimensions.
Specifically, for a scene in which the action category is a classification index, the sum of the number of target advertisements and similar advertisements is assumed to be n, the classification of the category index is assumed to be m (for example, whether m=2, abc, m=3), and the result value of the policy-dependent index value input by the user on each advertisement is k 1 ,…,k n Average value isThe calculation steps are as follows:
the advertisements are divided into two categories according to the average value of the policy-dependent indicators input by the user
/>
Assuming that the dependency index is conversion, and k1=0.5, k2=0.4, k3=0.6, k4=0.2, k5=0.3, then Positive ads are k1, k2, k3 and negative ads are k4, k5.
And then calculating voting weight information of each advertisement, wherein the positive advertisement weight value is positive, the negative advertisement weight value is negative, and the calculation formula is as follows:
in the above formula, min and max are the same in the positive and negative direction calculation process and are respectively the minimum value and the maximum value of the data column, so that max=max (k 1 … k 5) =0.6; min=min (k 1 … k 5) =0.2.
Voting is then performed on the m values of the category indicator classification:
wherein m is adopted as the jth advertisement in the formula i And then the calculation is participated, namely the following steps: weight 1=0.75, weight 2=0.5, weight 3=1, weight 4= -1, weight 5= -0.75.
Since the contrast dimension is the bid strategy and the action type is two types A and B, wherein k1k3 selects the bid strategy A; the k2k4k 5B-selective bidding strategy, therefore, can be:
mA＝weight1+weight3＝1.75；
mB＝weight2+weight4+weight5＝-1.25；
so that the degree of difference diff=ma-mb=3 can be obtained;
since the difference threshold β= [ (weight 1+weight2+weight 3) - (weight 4+weight 5) ] ≡2=4 ≡2=2;
so diff > = β, i.e. 3> = 2 holds; that is, the advertisements are considered to have significant differences in the dimension of the bid policy, and if the target advertisement bid policy selects B, the selection A is suggested
In addition, for a scene with a continuous dimension action category of a comparison dimension, the continuous dimension value can be equally divided into p segments, the p value of the embodiment is 4, and the operation strategy is output by the subsequent calculation according to the category dimension calculation mode: in turn, up-or down-scaling the targeted advertisement to max (m 1 ,…,m i ) Thereby optimizing the policy of the targeted advertisement.
Further, each dimension is calculated through traversal, an operation strategy set of the target advertisement is finally obtained and displayed on a front page, a user can select a plurality of strategies by himself, the clicking system executes the strategies, and then the advertisement related system automatically executes the strategies. For example, the delivery end automatically adjusts the bid up or down, the delivery strategy is adjusted from stable to preferential, the delivery flow is changed, and the like.
Step 3: if the difference degree under the comparison dimension is greater than or equal to the threshold value, and the target advertisement is a negative resource.
The result of the target advertisement in the comparison dimension is a bad result, and the bad result indicates that the corresponding action information is executed in the comparison dimension and the expected popularization effect cannot be achieved.
Step 4: the action information is retained.
And if the difference degree under the contrast dimension is smaller than the threshold value or the target advertisement is a forward resource, the action information can be reserved, so that the data processing amount is reduced.
Step 5: and adding into a strategy pool. Thereby completing the policy configuration process based on the difference degree calculation.
607. And outputting the data representation of each advertisement under each contrast dimension.
In this embodiment, the data representation under each comparison dimension arranges the similar advertisements by default according to the descending order of consumption, so as to improve the allocable information of the popularization resource, and the specific data representation form can be used for expanding the table display shown in fig. 5.
608. And outputting the operation strategy.
In this embodiment, the operations with significant differences obtained by the above configuration are integrated, so that execution information can be obtained, and the execution information may also be referred to as an operation policy.
609. And selecting and clicking the system to execute.
In this embodiment, the policy selection process may be performed with reference to an interface shown in fig. 8, and fig. 8 is a schematic view of a scenario of another method for processing promotion resources provided in this embodiment of the present application; the figure shows that a user can conduct targeted strategy configuration by selecting classified strategy display information A1, and a further click system executes A2 to apply the selected strategy to the promotion process of the target advertisement.
610. The system enforces the policy.
In this embodiment, steps 607-610 are the process of system output. The comparison results of a plurality of advertisements such as target advertisements, similar advertisements and the like in the dimensions can be realized through one-time screening operation, and the data processing efficiency is improved; in addition, the embodiment calculates each dimension by using the difference degree model, forward and standardized operation strategies can be produced, operators can finish execution of the operation strategies in batches in a systematic mode, a whole set of operation schemes of strategy output and systematic strategy landing are realized, and the advertisement distributable information of the platform is further improved while the operation efficiency is improved.
In order to better implement the above-described aspects of the embodiments of the present application, the following also provides related devices for implementing the above-described aspects. Referring to fig. 9, fig. 9 is a schematic structural diagram of a processing apparatus for promoting resources, where the processing apparatus 900 for promoting resources includes:
an obtaining unit 901, configured to obtain a target popularization resource;
a determining unit 902, configured to determine a reference promotion resource associated with the target promotion resource, so as to integrate the target promotion resource and the reference promotion resource into a promotion resource set;
the obtaining unit 901 is further configured to obtain an output index and a plurality of comparison dimensions for executing information configuration, and call effect data corresponding to a promotion resource in the promotion resource set under the output index;
a processing unit 903, configured to divide the promotion resource set into a forward promotion resource and a backward promotion resource according to the effect data;
the processing unit 903 is further configured to determine, according to the effect data, a degree of difference between the positive popularization resource and the negative popularization resource in a plurality of the comparison dimensions;
the processing unit 903 is further configured to configure the execution information of the target promotion resource according to the action information of the forward promotion resource in the multiple comparison dimensions if the difference degree meets a preset condition, where the action information is used to indicate a promotion operation performed on the target promotion resource in each of the comparison dimensions, and the execution information includes at least one action information.
Optionally, in some possible implementations of the present application, the processing unit 903 is specifically configured to determine, according to the effect data, an index value sequence of the popularization resource set under at least one of the output indexes;
the processing unit 903 is specifically configured to determine an average value of the values in the index value sequence;
the processing unit 903 is specifically configured to divide the popularization resource with the index value greater than or equal to the average value in the popularization resource set into the forward resource;
the processing unit 903 is specifically configured to divide the popularization resource with the index value smaller than the average value in the popularization resource set into the negative resource.
Optionally, in some possible implementations of the present application, the processing unit 903 is specifically configured to perform normalization processing on the effect data to obtain weighted data;
the processing unit 903 is specifically configured to determine an action category included in the comparison dimension in response to the configuration of the plurality of comparison dimensions;
the processing unit 903 is specifically configured to perform voting statistics according to the action category based on the weighted data, so as to determine voting weight information under each action category;
the processing unit 903 is specifically configured to determine, according to the difference value of the voting weight information under each action category, a degree of difference between the positive popularization resource and the negative popularization resource under the corresponding comparison dimension.
Optionally, in some possible implementations of the present application, the processing unit 903 is specifically configured to obtain a first reference value and a second reference value in the effect data, where the first reference value and the second reference value are located in different positions in a numerical ranking queue corresponding to the effect data;
the processing unit 903 is specifically configured to determine a reference difference between the first reference value and the second reference value;
the processing unit 903 is specifically configured to configure a first formula based on the second reference value and the reference difference value, so as to call the first formula to perform standardization processing on the effect data corresponding to the forward promotion resource to obtain forward weighting information;
the processing unit 903 is specifically configured to configure a second formula based on the first reference value and the reference difference value, so as to call the second formula to perform standardization processing on the effect data corresponding to the negative popularization resource to obtain negative weighting information;
the processing unit 903 is specifically configured to integrate the positive weighting information and the negative weighting information to obtain the weighted data.
Optionally, in some possible implementations of the present application, the processing unit 903 is specifically configured to determine a range of values contained in the comparison dimension in response to a configuration of a plurality of the comparison dimensions;
The processing unit 903 is specifically configured to divide the numerical range evenly to obtain the action category.
Optionally, in some possible implementations of the present application, the processing unit 903 is specifically configured to obtain historical configuration information corresponding to the comparison dimension;
the processing unit 903 is specifically configured to determine distribution information including each numerical value in the comparison dimension based on the history configuration information;
the processing unit 903 is specifically configured to divide the central distribution range indicated by the distribution information on average, so as to obtain the action category.
Optionally, in some possible implementations of the present application, the processing unit 903 is specifically configured to obtain a configuration of the target object for a network class dimension and a product class dimension;
the processing unit 903 is specifically configured to determine a network transmission object indicated by the network class dimension;
the processing unit 903 is specifically configured to obtain network resource information allocated to the network transmission object, so as to determine an action class included in the network resource information;
the processing unit 903 is specifically configured to obtain promotion content configuration information indicated by the product dimension, so as to determine an action category included in the promotion content configuration information.
Optionally, in some possible implementations of the present application, the processing unit 903 is specifically configured to determine, according to the effect information, a positive accumulated vote corresponding to the positive popularization resource and a negative accumulated vote corresponding to the negative popularization resource;
the processing unit 903 is specifically configured to perform average calculation on the positive accumulated vote and the negative accumulated vote, so as to determine a difference threshold corresponding to the preset condition;
the processing unit 903 is specifically configured to configure execution information of the target popularization resource according to action information of the positive popularization resource in a plurality of the comparison dimensions if the difference degree is greater than or equal to the difference threshold and the target popularization resource is divided into the negative popularization resource.
Optionally, in some possible implementations of the present application, the processing unit 903 is specifically configured to obtain the action information of the forward promotion resource in a plurality of the contrast dimensions;
the processing unit 903 is specifically configured to determine an execution numerical range corresponding to the action information;
the processing unit 903 is specifically configured to extract the intermediate value corresponding to the execution numerical range to configure the execution information of the target popularization resource.
Optionally, in some possible implementations of the present application, the acquiring unit 901 is specifically configured to acquire a promotion object identifier input by a target object;
The obtaining unit 901 is specifically configured to perform resource traversal based on the promotion object identifier, so as to determine the target promotion resource.
Optionally, in some possible implementations of the present application, the determining unit 902 is specifically configured to obtain industry information corresponding to the target popularization resource;
the determining unit 902 is specifically configured to determine, according to the industry information, a candidate popularization resource related to the industry corresponding to the target popularization resource;
the determining unit 902 is specifically configured to match the candidate popularization resource based on flow information corresponding to the target popularization resource, so as to determine the reference popularization resource associated with the target popularization resource;
the determining unit 902 is specifically configured to integrate the target promotion resource and the reference promotion resource into the promotion resource set.
Optionally, in some possible implementations of the present application, the processing unit 903 is specifically configured to classify the execution information according to the comparison dimension to obtain the display information;
the processing unit 903 is specifically configured to display the display information on a target interface;
the processing unit 903 is specifically configured to respond to a selection operation of the target object on the presentation information in the target interface, and execute execution information corresponding to the selection operation on the target promotion resource.
Acquiring target popularization resources; then determining a reference popularization resource associated with the target popularization resource, and integrating the target popularization resource and the reference popularization resource into a popularization resource set; obtaining output indexes aiming at execution information configuration and a plurality of comparison dimensions, and calling corresponding effect data of popularization resources in a popularization resource set under the output indexes; dividing the popularization resource set into positive popularization resources and negative popularization resources according to the effect data; then determining the difference degree of the forward promotion resource and the negative promotion resource under a plurality of comparison dimensions according to the effect data; if the difference degree meets the preset condition, configuring execution information of the target popularization resource according to action information of the forward popularization resource in a plurality of comparison dimensions, wherein the action information is used for indicating popularization operation executed on the target popularization resource in each comparison dimension, and the execution information comprises at least one action information. Therefore, the automatic configuration process of the promotion resource execution information is realized, the execution information of the target promotion resource is subjected to reference configuration by adopting the reference promotion resource, and forward action information is adopted for the items with obvious differences in the reference configuration process, so that the forward action information is beneficial to the propagation of the promotion information, the effectiveness of the execution information is ensured, and the configuration efficiency of the promotion resource execution information is improved.
The embodiment of the present application further provides a terminal device, as shown in fig. 10, which is a schematic structural diagram of another terminal device provided in the embodiment of the present application, for convenience of explanation, only a portion related to the embodiment of the present application is shown, and specific technical details are not disclosed, and please refer to a method portion of the embodiment of the present application. The terminal may be any terminal device including a mobile phone, a tablet computer, a personal digital assistant (personal digital assistant, PDA), a point of sale (POS), a vehicle-mounted computer, and the like, taking the terminal as an example of the mobile phone:
fig. 10 is a block diagram showing a part of the structure of a mobile phone related to a terminal provided in an embodiment of the present application. Referring to fig. 10, the mobile phone includes: radio Frequency (RF) circuitry 1010, memory 1020, input unit 1030, display unit 1040, sensor 1050, audio circuitry 1060, wireless fidelity (wireless fidelity, wiFi) module 1070, processor 1080, and power source 1090. It will be appreciated by those skilled in the art that the handset construction shown in fig. 10 is not limiting of the handset and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
The following describes the components of the mobile phone in detail with reference to fig. 10:
the RF circuit 1010 may be used for receiving and transmitting signals during a message or a call, and particularly, after receiving downlink information of a base station, the signal is processed by the processor 1080; in addition, the data of the design uplink is sent to the base station. Typically, the RF circuitry 1010 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier (low noise amplifier, LNA), a duplexer, and the like. In addition, the RF circuitry 1010 may also communicate with networks and other devices via wireless communications. The wireless communications may use any communication standard or protocol including, but not limited to, global system for mobile communications (global system of mobile communication, GSM), general packet radio service (general packet radio service, GPRS), code division multiple access (code division multiple access, CDMA), wideband code division multiple access (wideband code division multiple access, WCDMA), long term evolution (long term evolution, LTE), email, short message service (short messaging service, SMS), and the like.
The memory 1020 may be used to store software programs and modules that the processor 1080 performs various functional applications and data processing of the handset by executing the software programs and modules stored in the memory 1020. The memory 1020 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data (such as audio data, phonebook, etc.) created according to the use of the handset, etc. In addition, memory 1020 may include high-speed random access memory and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state memory device.
The input unit 1030 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the handset. In particular, the input unit 1030 may include a touch panel 1031 and other input devices 1032. The touch panel 1031, also referred to as a touch screen, may collect touch operations thereon or thereabout by a user (e.g., operations of the user on the touch panel 1031 or thereabout by using any suitable object or accessory such as a finger, a stylus, etc., and spaced touch operations within a certain range on the touch panel 1031) and drive the corresponding connection device according to a predetermined program. Alternatively, the touch panel 1031 may include two parts, a touch detection device and a touch controller. The touch detection device detects the touch azimuth of a user, detects a signal brought by touch operation and transmits the signal to the touch controller; the touch controller receives touch information from the touch detection device and converts it into touch point coordinates, which are then sent to the processor 1080 and can receive commands from the processor 1080 and execute them. Further, the touch panel 1031 may be implemented in various types such as resistive, capacitive, infrared, and surface acoustic wave. The input unit 1030 may include other input devices 1032 in addition to the touch panel 1031. In particular, other input devices 1032 may include, but are not limited to, one or more of a physical keyboard, function keys (e.g., volume control keys, switch keys, etc.), a track ball, a mouse, a joystick, etc.
The display unit 1040 may be used to display information input by a user or information provided to the user and various menus of the mobile phone. The display unit 1040 may include a display panel 1041, and alternatively, the display panel 1041 may be configured in the form of a liquid crystal display (liquid crystal display, LCD), an organic light-emitting diode (OLED), or the like. Further, the touch panel 1031 may overlay the display panel 1041, and when the touch panel 1031 detects a touch operation thereon or thereabout, the touch panel is transferred to the processor 1080 to determine a type of touch event, and then the processor 1080 provides a corresponding visual output on the display panel 1041 according to the type of touch event. Although in fig. 10, the touch panel 1031 and the display panel 1041 are two independent components to implement the input and output functions of the mobile phone, in some embodiments, the touch panel 1031 and the display panel 1041 may be integrated to implement the input and output functions of the mobile phone.
The handset may also include at least one sensor 1050, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor may adjust the brightness of the display panel 1041 according to the brightness of ambient light, and the proximity sensor may turn off the display panel 1041 and/or the backlight when the mobile phone moves to the ear. As one of the motion sensors, the accelerometer sensor can detect the acceleration in all directions (generally three axes), and can detect the gravity and direction when stationary, and can be used for applications of recognizing the gesture of a mobile phone (such as horizontal and vertical screen switching, related games, magnetometer gesture calibration), vibration recognition related functions (such as pedometer and knocking), and the like; other sensors such as gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc. that may also be configured with the handset are not described in detail herein.
Audio circuitry 1060, a speaker 1061, and a microphone 1062 may provide an audio interface between a user and a cell phone. Audio circuit 1060 may transmit the received electrical signal after audio data conversion to speaker 1061 for conversion by speaker 1061 into an audio signal output; on the other hand, microphone 1062 converts the collected sound signals into electrical signals, which are received by audio circuit 1060 and converted into audio data, which are processed by audio data output processor 1080 for transmission to, for example, another cell phone via RF circuit 1010 or for output to memory 1020 for further processing.
WiFi belongs to a short-distance wireless transmission technology, and a mobile phone can help a user to send and receive emails, browse webpages, access streaming media and the like through a WiFi module 1070, so that wireless broadband Internet access is provided for the user. Although fig. 10 shows a WiFi module 1070, it is understood that it does not belong to the necessary constitution of the handset, and can be omitted entirely as required within the scope of not changing the essence of the invention.
Processor 1080 is the control center of the handset, connects the various parts of the entire handset using various interfaces and lines, and performs various functions and processes of the handset by running or executing software programs and/or modules stored in memory 1020 and invoking data stored in memory 1020, thereby performing overall monitoring of the handset. Optionally, processor 1080 may include one or more processing units; alternatively, processor 1080 may integrate an application processor primarily handling operating systems, user interfaces, applications, etc., with a modem processor primarily handling wireless communications. It will be appreciated that the modem processor described above may not be integrated into processor 1080.
The handset further includes a power source 1090 (e.g., a battery) for powering the various components, optionally in logical communication with the processor 1080 via a power management system, such as for managing charge, discharge, and power consumption by the power management system.
Although not shown, the mobile phone may further include a camera, a bluetooth module, etc., which will not be described herein.
In the embodiment of the present application, the processor 1080 included in the terminal also has a function of executing each step of the page processing method as described above.
Referring to fig. 11, fig. 11 is a schematic structural diagram of a server according to an embodiment of the present application, where the server 1100 may have a relatively large difference due to different configurations or performances, and may include one or more central processing units (central processing units, CPU) 1122 (e.g., one or more processors) and a memory 1132, and one or more storage media 1130 (e.g., one or more mass storage devices) storing application programs 1142 or data 1144. Wherein the memory 1132 and the storage medium 1130 may be transitory or persistent. The program stored on the storage medium 1130 may include one or more modules (not shown), each of which may include a series of instruction operations on a server. Still further, the central processor 1122 may be provided in communication with a storage medium 1130, executing a series of instruction operations in the storage medium 1130 on the server 1100.
The server 1100 may also include one or more power supplies 1126, one or more wired or wireless network interfaces 1150, one or more input-output interfaces 1158, and/or one or more operating systems 1141, such as Windows Server, mac OS XTM, unixTM, linuxTM, freeBSDTM, etc.
The steps performed by the management apparatus in the above-described embodiments may be based on the server structure shown in fig. 11.
In an embodiment of the present application, a computer readable storage medium is further provided, where processing instructions of a promotion resource are stored, which when executed on a computer, cause the computer to perform steps performed by a processing device of the promotion resource in the method described in the foregoing embodiment shown in fig. 3 to 8.
There is further provided in an embodiment of the present application a computer program product comprising processing instructions for promoting a resource, which when run on a computer causes the computer to perform the steps performed by the processing means for promoting a resource in the method described in the embodiment shown in the foregoing fig. 3 to 8.
The embodiment of the application also provides a processing system of the popularization resource, and the processing system of the popularization resource can comprise a processing device of the popularization resource in the embodiment described in fig. 9, or terminal equipment in the embodiment described in fig. 10, or a server described in fig. 11.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, 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 units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. 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 application 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 computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in whole or in part in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a processing means of a promotional resource, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The above embodiments are merely for illustrating the technical solution of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.
Claims (15)
1. The method for processing the popularization resource is characterized by comprising the following steps:
acquiring target popularization resources;
determining a reference popularization resource associated with the target popularization resource to integrate the target popularization resource and the reference popularization resource as a popularization resource set;
acquiring an output index aiming at execution information configuration and a plurality of comparison dimensions, and calling effect data corresponding to popularization resources in the popularization resource set under the output index;
dividing the popularization resource set into positive popularization resources and negative popularization resources according to the effect data;
determining the difference degrees of the positive popularization resource and the negative popularization resource under a plurality of comparison dimensions according to the effect data;
If the difference degree meets a preset condition, configuring the execution information of the target popularization resource according to action information of the forward popularization resource in a plurality of comparison dimensions, wherein the action information is used for indicating popularization operations executed on the target popularization resource in each comparison dimension, and the execution information comprises at least one action information.
2. The method of claim 1, wherein the partitioning the set of promotional resources into positive resources and negative resources according to the effect data comprises:
determining an index value sequence of the popularization resource set under at least one output index according to the effect data;
determining an average value of values in the index value sequence;
dividing the popularization resources with index values larger than or equal to the average value in the popularization resource set into the forward resources;
and dividing the popularization resources with index values smaller than the average value in the popularization resource set into the negative resources.
3. The method of claim 1, wherein the determining the degree of difference between the positive promotional resource and the negative promotional resource in a plurality of contrasting dimensions from the effect data comprises:
Carrying out standardization processing on the effect data to obtain weighted data;
determining action categories contained in a comparison dimension in response to configuration of a plurality of comparison dimensions;
voting statistics are carried out according to the action categories based on the weighted data, so that voting weight information under each action category is determined;
and determining the difference degree of the positive popularization resource and the negative popularization resource under the corresponding comparison dimension according to the difference value of the voting weight information under each action category.
4. A method according to claim 3, wherein said normalizing said effect data to obtain weighted data comprises:
acquiring a first reference value and a second reference value in the effect data, wherein the positions of the first reference value and the second reference value in a numerical ordering queue corresponding to the effect data are different;
determining a reference difference between the first reference value and the second reference value;
configuring a first formula based on the second reference value and the reference difference value to call the first formula to perform standardized processing on the effect data corresponding to the forward promotion resource to obtain forward weighting information;
Configuring a second formula based on the first reference value and the reference difference value to call the second formula to perform standardized processing on the effect data corresponding to the negative popularization resource to obtain negative weighting information;
and integrating the positive weighting information and the negative weighting information to obtain the weighting data.
5. A method according to claim 3, wherein said determining, responsive to a configuration of a plurality of said contrasting dimensions, a category of action contained by said contrasting dimensions comprises:
determining a range of values contained by the contrasting dimension in response to configuration of a plurality of contrasting dimensions;
and carrying out average division on the numerical range to obtain the action category.
6. The method of claim 5, wherein the equally dividing the range of values to obtain the action category comprises:
acquiring history configuration information corresponding to the comparison dimension;
determining distribution information containing various numerical values in the comparison dimension based on the historical configuration information;
and carrying out average division according to the concentrated distribution range indicated by the distribution information to obtain the action category.
7. A method according to claim 3, wherein said determining, responsive to a configuration of a plurality of said contrasting dimensions, a category of action contained by said contrasting dimensions comprises:
Acquiring configuration of a target object on a network class dimension and a product class dimension;
determining a network transmission object indicated by the network class dimension;
acquiring network resource information allocated for the network transmission object so as to determine an action category contained in the network resource information;
and acquiring promotion content configuration information indicated by the product dimension to determine action categories contained in the promotion content configuration information.
8. The method of claim 1, wherein if the degree of difference satisfies a preset condition, configuring the execution information of the target popularization resource according to the action information of the forward popularization resource in the plurality of comparison dimensions, includes:
determining positive accumulated votes corresponding to the positive popularization resources and negative accumulated votes corresponding to the negative popularization resources according to the effect information;
average value calculation is carried out on the positive accumulated votes and the negative accumulated votes so as to determine a difference threshold value corresponding to the preset condition;
if the difference degree is greater than or equal to the difference threshold value and the target popularization resource is divided into the negative popularization resource, configuring execution information of the target popularization resource according to action information of the positive popularization resource in a plurality of comparison dimensions.
9. The method of claim 8, wherein the configuring the execution information of the target promotion resource according to the action information of the forward promotion resource in the plurality of comparison dimensions comprises:
acquiring the action information of the forward promotion resource under a plurality of comparison dimensions;
determining an execution numerical range corresponding to the action information;
and extracting the execution information of the intermediate value configuration target popularization resource corresponding to the execution numerical range.
10. The method of claim 1, wherein the obtaining the target promotional resource comprises:
acquiring a popularization object identifier input by a target object;
and traversing the resources based on the popularization object identification to determine the target popularization resources.
11. The method of claim 1, wherein the determining the reference promotion resource associated with the target promotion resource to integrate the target promotion resource and the reference promotion resource as a promotion resource set comprises:
acquiring industry information corresponding to the target popularization resource;
determining candidate popularization resources related to industries corresponding to the target popularization resources according to the industry information;
Matching the candidate popularization resources based on the flow information corresponding to the target popularization resources to determine the reference popularization resources associated with the target popularization resources;
integrating the target popularization resource and the reference popularization resource into the popularization resource set.
12. The method according to any one of claims 1-11, further comprising:
classifying the execution information according to the comparison dimension to obtain display information;
displaying the display information on a target interface;
and responding to the selection operation of the target object on the display information in the target interface, and executing the execution information corresponding to the selection operation on the target popularization resource.
13. A processing apparatus for promoting a resource, comprising:
the acquisition unit is used for acquiring target popularization resources;
the determining unit is used for determining a reference popularization resource associated with the target popularization resource to integrate the target popularization resource and the reference popularization resource into a popularization resource set;
the acquisition unit is further used for acquiring output indexes and a plurality of comparison dimensions aiming at execution information configuration, and invoking effect data corresponding to popularization resources in the popularization resource set under the output indexes;
The processing unit is used for dividing the popularization resource set into positive popularization resources and negative popularization resources according to the effect data;
the processing unit is further used for determining the difference degree of the positive popularization resource and the negative popularization resource under a plurality of comparison dimensions according to the effect data;
the processing unit is further configured to configure the execution information of the target popularization resource according to action information of the forward popularization resource in a plurality of comparison dimensions if the difference degree meets a preset condition, where the action information is used to indicate popularization operations performed on the target popularization resource in each comparison dimension, and the execution information includes at least one action information.
14. A computer device, the computer device comprising a processor and a memory:
the memory is used for storing program codes; the processor is configured to execute the method for processing a promotional resource according to any of claims 1 to 12 according to instructions in the program code.
15. A computer program product comprising computer programs/instructions stored on a computer readable storage medium, characterized in that the computer programs/instructions in the computer readable storage medium, when executed by a processor, implement the steps of the method of processing promotional resources according to any of the preceding claims 1-12.
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