CN115471283A - Advertisement batch delivery method, device, equipment and storage medium - Google Patents
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Abstract
The invention relates to the field of artificial intelligence, and discloses a method, a device, equipment and a storage medium for batch advertisement delivery, which are used for improving advertisement delivery efficiency. The advertisement batch delivery method comprises the following steps: matching plan creation rules according to the advertisement creation quantity; creating a plurality of target advertisement plans according to plan creating rules, and grouping the plurality of target advertisement plans according to a plurality of delivery types to obtain an advertisement plan group; batch delivery is carried out on a plurality of target advertisement plans, and return data corresponding to each delivery type is obtained based on a preset time node; analyzing the putting effect of the returned data corresponding to each putting type to obtain the putting and recycling proportion corresponding to each putting type, and comparing the putting and recycling proportions corresponding to each putting type to obtain a comparison result; and generating an optimal delivery type according to the comparison result, acquiring an optimal advertisement plan in the optimal delivery type, and performing batch creation and delivery on the optimal advertisement plan.
Description
Technical Field
The invention relates to the field of artificial intelligence, in particular to a method, a device, equipment and a storage medium for batch advertisement delivery.
Background
The internet of things advertisement is put on the internet of things terminal through the internet of things advertisement platform. The method is a high-tech advertisement operation mode which is characterized in that advertisements are published or issued on the terminal of the Internet of things by using advertisement banners, text links and multimedia on the terminal of the Internet of things and are transmitted to users through the terminal of the Internet of things.
The existing scheme is characterized in that manual advertisement batch delivery is carried out through delivery personnel, and the efficiency of manual advertisement batch delivery is very low, so that the requirements for cost and running amount cannot be met by manual advertisement batch delivery, namely the efficiency of the existing scheme is low.
Disclosure of Invention
The invention provides a method, a device, equipment and a storage medium for batch advertisement delivery, which are used for improving the efficiency of advertisement delivery.
The invention provides a method for batch advertisement delivery, which comprises the following steps: receiving an advertisement putting request sent by a putting terminal, analyzing the advertisement putting request to obtain putting resource data, and performing data classification on the putting resource data to obtain a plurality of file data and a plurality of material data; determining the number of created advertisements according to the advertisement putting request, and matching a plan creation rule corresponding to the advertisement putting request according to the number of created advertisements, wherein the plan creation rule comprises: one file data corresponds to one material data, one file data corresponds to a plurality of material data, and a plurality of file data correspond to one material data; creating a plurality of target advertisement plans corresponding to the advertisement putting request according to the plan creating rule, and grouping the plurality of target advertisement plans according to a plurality of preset putting types to obtain an advertisement plan group corresponding to each putting type; carrying out batch delivery on the plurality of target advertisement plans according to the advertisement plan group corresponding to each delivery type, and acquiring return data corresponding to each delivery type based on a preset time node; analyzing the putting effect of the returned data corresponding to each putting type to obtain the putting and recycling proportion corresponding to each putting type, and comparing the putting and recycling proportions corresponding to each putting type to obtain a comparison result; and generating an optimal delivery type according to the comparison result, acquiring an optimal advertisement plan in the optimal delivery type, and performing batch creation and delivery on the optimal advertisement plan.
Optionally, in a first implementation manner of the first aspect of the present invention, the receiving an advertisement delivery request sent by a delivery terminal, analyzing the advertisement delivery request to obtain delivery resource data, and performing data classification on the delivery resource data to obtain a plurality of document data and a plurality of material data includes: receiving an advertisement putting request sent by a putting terminal, and analyzing the advertisement putting request to obtain an advertisement creating interface; receiving the delivered resource data uploaded by the delivery terminal based on the advertisement creating interface; and performing text recognition on the thrown resource data to obtain a plurality of file data, and performing material information recognition on the thrown resource data to obtain a plurality of material data.
Optionally, in a second implementation manner of the first aspect of the present invention, the determining, according to the advertisement placement request, an advertisement creation number, and matching, according to the advertisement creation number, a plan creation rule corresponding to the advertisement placement request, where the plan creation rule includes: one file data corresponds to one material data, one file data corresponds to a plurality of material data, and a plurality of file data correspond to one material data, and the method comprises the following steps: extracting creation data of the advertisement putting requests to obtain the number of created advertisements; carrying out magnitude matching on the advertisement creating quantity to obtain a target magnitude corresponding to the advertisement creating quantity; selecting a plan creation rule corresponding to the advertisement putting request from a preset creation rule base according to the target magnitude, wherein the plan creation rule comprises the following steps: one file data corresponds to one material data, one file data corresponds to a plurality of material data, and a plurality of file data correspond to one material data.
Optionally, in a third implementation manner of the first aspect of the present invention, the creating, according to the plan creation rule, a plurality of target advertisement plans corresponding to the advertisement delivery request, and grouping the plurality of target advertisement plans according to a plurality of preset delivery types to obtain an advertisement plan group corresponding to each delivery type includes: performing association configuration on the plurality of file data and the plurality of material data according to the plan creation rule to obtain a plurality of target advertisement plans corresponding to the advertisement putting request; performing delivery type mapping on the plurality of target advertisement plans to obtain a delivery type corresponding to each target advertisement plan; and grouping the plurality of target advertisement plans according to the delivery type corresponding to each target advertisement plan to obtain an advertisement plan group corresponding to each delivery type.
Optionally, in a fourth implementation manner of the first aspect of the present invention, the analyzing the delivery effect of the returned data corresponding to each delivery type to obtain a delivery and recovery ratio corresponding to each delivery type, and comparing the delivery and recovery ratios corresponding to each delivery type to obtain a comparison result includes: acquiring release output data corresponding to each release type; calculating the release recovery proportion corresponding to each release type according to the release output data and the return data corresponding to each release type; and sequencing and comparing the throwing recovery proportion corresponding to each throwing type to obtain a comparison result.
Optionally, in a fifth implementation manner of the first aspect of the present invention, the generating an optimal delivery type according to the comparison result, obtaining an optimal advertisement plan in the optimal delivery type, and performing batch creation and delivery on the optimal advertisement plan includes: selecting the releasing type with the highest releasing and recovering proportion from the plurality of releasing types as the optimal releasing type according to the comparison result; inquiring an optimal advertisement plan in the optimal delivery type; the optimal advertisement plans are copied in batches to obtain a plurality of optimal advertisement plans; and carrying out batch delivery on the optimal advertisement plans.
Optionally, in a sixth implementation manner of the first aspect of the present invention, the advertisement batch delivery method further includes: extracting the file keywords of the optimal advertisement plan to obtain target keywords; identifying the material type of the optimal advertisement plan to obtain a target material type; acquiring a plurality of target users from a preset user preference database according to the target keywords and the target material types; and performing advertisement putting by taking the plurality of target users as a target user group.
A second aspect of the present invention provides an advertisement batch delivery device, including: the receiving module is used for receiving an advertisement putting request sent by a putting terminal, analyzing the advertisement putting request to obtain putting resource data, and performing data classification on the putting resource data to obtain a plurality of file data and a plurality of material data; a creating module, configured to determine a number of created advertisements according to the advertisement delivery request, and match a plan creating rule corresponding to the advertisement delivery request according to the number of created advertisements, where the plan creating rule includes: one file data corresponds to one material data, one file data corresponds to a plurality of material data, and a plurality of file data correspond to one material data; the grouping module is used for creating a plurality of target advertisement plans corresponding to the advertisement putting request according to the plan creating rule and grouping the plurality of target advertisement plans according to a plurality of preset putting types to obtain an advertisement plan group corresponding to each putting type; the return module is used for carrying out batch delivery on the plurality of target advertisement plans according to the advertisement plan group corresponding to each delivery type and acquiring return data corresponding to each delivery type based on a preset time node; the analysis module is used for analyzing the putting effect of the returned data corresponding to each putting type to obtain a putting and recycling proportion corresponding to each putting type, and comparing the putting and recycling proportions corresponding to each putting type to obtain a comparison result; and the delivery module is used for generating an optimal delivery type according to the comparison result, acquiring an optimal advertisement plan in the optimal delivery type, and performing batch creation and delivery on the optimal advertisement plan.
Optionally, in a first implementation manner of the second aspect of the present invention, the receiving module is specifically configured to: receiving an advertisement putting request sent by a putting terminal, and analyzing the advertisement putting request to obtain an advertisement creating interface; receiving the delivered resource data uploaded by the delivery terminal based on the advertisement creating interface; and performing text recognition on the launched resource data to obtain a plurality of file data, and performing material information recognition on the launched resource data to obtain a plurality of material data.
Optionally, in a second implementation manner of the second aspect of the present invention, the creating module is specifically configured to: extracting creation data of the advertisement putting request to obtain the advertisement creation quantity; carrying out magnitude matching on the advertisement creating quantity to obtain a target magnitude corresponding to the advertisement creating quantity; selecting a plan creation rule corresponding to the advertisement putting request from a preset creation rule base according to the target magnitude, wherein the plan creation rule comprises the following steps: one file data corresponds to one material data, one file data corresponds to a plurality of material data, and a plurality of file data correspond to one material data.
Optionally, in a third implementation manner of the second aspect of the present invention, the grouping module is specifically configured to: performing association configuration on the plurality of file data and the plurality of material data according to the plan creation rule to obtain a plurality of target advertisement plans corresponding to the advertisement putting request; carrying out delivery type mapping on the plurality of target advertisement plans to obtain a delivery type corresponding to each target advertisement plan; and grouping the plurality of target advertisement plans according to the delivery type corresponding to each target advertisement plan to obtain an advertisement plan group corresponding to each delivery type.
Optionally, in a fourth implementation manner of the second aspect of the present invention, the analysis module is specifically configured to: acquiring release output data corresponding to each release type; calculating the release recovery proportion corresponding to each release type according to the release output data and the return data corresponding to each release type; and sequencing and comparing the throwing recovery proportion corresponding to each throwing type to obtain a comparison result.
Optionally, in a fifth implementation manner of the second aspect of the present invention, the releasing module is specifically configured to: selecting the releasing type with the highest releasing and recovering proportion from the plurality of releasing types as the optimal releasing type according to the comparison result; inquiring an optimal advertisement plan in the optimal delivery type; the optimal advertisement plans are copied in batches to obtain a plurality of optimal advertisement plans; and carrying out batch delivery on the optimal advertisement plans.
Optionally, in a sixth implementation manner of the second aspect of the present invention, the advertisement batch delivery apparatus further includes: the recognition module is used for extracting the language and scheme keywords of the optimal advertisement plan to obtain target keywords; identifying the material type of the optimal advertisement plan to obtain a target material type; acquiring a plurality of target users from a preset user preference database according to the target keywords and the target material types; and performing advertisement putting by taking the plurality of target users as a target user group.
The third aspect of the present invention provides an advertisement batch delivery device, including: a memory and at least one processor, the memory having instructions stored therein; the at least one processor invokes the instructions in the memory to cause the advertisement mass delivery device to execute the advertisement mass delivery method described above.
A fourth aspect of the present invention provides a computer-readable storage medium having stored therein instructions, which, when run on a computer, cause the computer to execute the above advertisement mass delivery method.
According to the technical scheme provided by the invention, the diversity of advertisement plan creation is improved by setting various plan creation rules and matching the plan creation rules corresponding to the advertisement putting requests according to the advertisement creation quantity, then batch putting is carried out on the target advertisement plans according to the advertisement plan group corresponding to each putting type, putting is carried out according to the target advertisement plans, the purpose of batch copying and putting of advertisements is achieved, return data corresponding to each putting type is obtained based on a preset time node, then putting recovery ratio analysis is carried out on the return data, the optimal putting type and the optimal advertisement plan are found, the optimal advertisement plan is used as the advertisement plan of batch putting, and the batch operation of advertisement putting is further improved.
Drawings
FIG. 1 is a diagram of an embodiment of a method for mass advertisement delivery according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of another embodiment of a batch advertisement delivery method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an embodiment of a device for mass advertisement delivery according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of another embodiment of a device for mass advertisement delivery according to an embodiment of the present invention;
fig. 5 is a schematic diagram of an embodiment of an advertisement batch delivery device in the embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a method, a device, equipment and a storage medium for batch advertisement delivery, which are used for improving the efficiency of advertisement delivery. The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," or "having," and any variations thereof, are intended to cover non-exclusive inclusions, 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, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
For convenience of understanding, a specific flow of the embodiment of the present invention is described below, with reference to fig. 1, an embodiment of a method for advertisement batch delivery in the embodiment of the present invention includes:
101. receiving an advertisement putting request sent by a putting terminal, analyzing the advertisement putting request to obtain putting resource data, and performing data classification on the putting resource data to obtain a plurality of file data and a plurality of material data;
it is to be understood that the execution subject of the present invention may be an advertisement mass delivery device, and may also be a terminal or a server, which is not limited herein. The embodiment of the present invention is described by taking a server as an execution subject.
Specifically, the server receives an advertisement delivery request sent by a delivery terminal, and analyzes the request to obtain a corresponding advertisement creation interface, it should be noted that the server delivers the advertisement and obtains corresponding delivery resource data through the advertisement creation interface, and then the server performs word segmentation and text recognition on the delivery resource data to obtain a plurality of corresponding case data and a plurality of word segmentation data, so that subsequent servers can deliver the advertisement in batches.
102. Determining the number of created advertisements according to the advertisement putting requests, and matching plan creating rules corresponding to the advertisement putting requests according to the number of created advertisements, wherein the plan creating rules comprise: one file data corresponds to one material data, one file data corresponds to a plurality of material data, and a plurality of file data correspond to one material data;
specifically, the server determines the advertisement creation number according to the advertisement delivery request, wherein when the server acquires a social relation advertisement audience data packet corresponding to the identity of the advertisement delivery request from the distributed storage database, the server acquires a set number of audience user information according to the social relation advertisement audience data packet, and respectively constructs a first index of each piece of audience user information to store the first index into the internal storage type storage database, wherein the first index is an index between the audience user information and the advertisement information, the identity of the audience user information is used as an index keyword, and plan creation rules corresponding to the advertisement delivery request are matched according to the advertisement creation number, and the plan creation rules include: one file data corresponds to one material data, one file data corresponds to a plurality of material data, and a plurality of file data correspond to one material data, so that the quality and the efficiency of advertisement putting can be improved. Moreover, the interference to common users can be reduced, and the user experience is improved.
103. Creating a plurality of target advertisement plans corresponding to the advertisement putting request according to a plan creating rule, and grouping the plurality of target advertisement plans according to a plurality of preset putting types to obtain an advertisement plan group corresponding to each putting type;
specifically, the server performs associated configuration on a plurality of document data and a plurality of material data according to a plan creation rule to obtain a plurality of target advertisement plans corresponding to the advertisement delivery request, a template in each template base is associated with a user preference tag to obtain advertisement data, and the advertisement data includes: searching a user preference label matched with the user characteristic information according to the product information of the advertisement and the user characteristic information of the target user of the advertisement, and acquiring a template associated with the user preference label from a template library; and at least acquiring advertisement materials according to the product information, adding the advertisement materials into the acquired template to generate an advertisement file, and grouping a plurality of target advertisement plans according to a plurality of preset launching types to obtain an advertisement plan group corresponding to each launching type.
104. Batch delivery is carried out on a plurality of target advertisement plans according to the advertisement plan group corresponding to each delivery type, and return data corresponding to each delivery type are obtained based on a preset time node;
the method comprises the steps of mapping the delivery types of a plurality of target advertisement plans to obtain the delivery type corresponding to each target advertisement plan, grouping the plurality of target advertisement plans according to the delivery type corresponding to each target advertisement plan to obtain an advertisement plan group corresponding to each delivery type, delivering the plurality of target advertisement plans in batches according to the advertisement plan group corresponding to each delivery type, and obtaining return data corresponding to each delivery type based on a preset time node.
105. Analyzing the putting effect of the returned data corresponding to each putting type to obtain the putting and recycling proportion corresponding to each putting type, and comparing the putting and recycling proportions corresponding to each putting type to obtain a comparison result;
specifically, the server acquires delivery basic parameters corresponding to the target advertisement and delivery effect parameters corresponding to each delivery day of delivery through collection, and introduces the parameters into a delivery cost algorithm model to calculate delivery costs of the target advertisement corresponding to delivery position dimensions, delivery time dimensions and delivery effect dimensions in each delivery day of delivery, so that comprehensive delivery costs corresponding to the target advertisement are calculated by combining the delivery costs of the dimensions, delivery recovery proportions corresponding to each delivery type are obtained, delivery recovery proportions corresponding to each delivery type are compared, comparison results are obtained, and the defect that the evaluation dimensions of the current advertisement delivery effect are too single is overcome.
106. And generating an optimal delivery type according to the comparison result, acquiring an optimal advertisement plan in the optimal delivery type, and performing batch creation and delivery on the optimal advertisement plan.
Specifically, the server generates an optimal delivery type according to the comparison result, determines an advertisement delivery scheme according to the region type and the advertisement delivery cost information, and performs advertisement delivery operation according to the advertisement delivery scheme. Therefore, the problems of manpower resource waste and low delivery yield caused by artificial planning of the advertisement delivery scheme can be avoided, and the yield caused by advertisement delivery can be improved on the basis of reducing the advertisement delivery cost.
In the embodiment of the invention, the diversity of the advertisement plan creation is improved by setting various plan creation rules and matching the plan creation rules corresponding to the advertisement putting requests according to the advertisement creation number, then batch putting is carried out on a plurality of target advertisement plans according to the advertisement plan group corresponding to each putting type, putting is carried out according to the target advertisement plans, the purpose of batch copying and putting of advertisements is achieved, return data corresponding to each putting type is obtained based on a preset time node, then putting recovery ratio analysis is carried out on the return data, the optimal putting type and the optimal advertisement plan are found, the optimal advertisement plan is used as the advertisement plan of batch putting, and the efficiency of batch putting of advertisements is further improved.
Referring to fig. 2, another embodiment of the advertisement batch delivery method according to the embodiment of the present invention includes:
201. receiving an advertisement putting request sent by a putting terminal, analyzing the advertisement putting request to obtain putting resource data, and performing data classification on the putting resource data to obtain a plurality of file data and a plurality of material data;
specifically, an advertisement putting request sent by a putting terminal is received, and the advertisement putting request is analyzed to obtain an advertisement creating interface; receiving the released resource data uploaded by the released terminal based on the advertisement creating interface; and performing text recognition on the thrown resource data to obtain a plurality of file data, and performing material information recognition on the thrown resource data to obtain a plurality of material data.
The method comprises the steps of analyzing a received advertisement putting request, determining a tree structure constructed by advertisement nodes and advertisement node information corresponding to the advertisement nodes, calling a creation interface according to the connection relation between the advertisement node information and the advertisement nodes in the tree structure, creating monitoring binding of the advertisement node data corresponding to the advertisement nodes and target advertisement node data in the advertisement node data, creating a plurality of file data corresponding to at least one advertisement link formed by the advertisement nodes in the tree structure based on the monitoring binding and the advertisement node data, and identifying material information of putting resource data to obtain a plurality of material data so as to create advertisements in subsequent batches.
202. Determining the number of created advertisements according to the advertisement putting requests, and matching plan creating rules corresponding to the advertisement putting requests according to the number of created advertisements, wherein the plan creating rules comprise: one file data corresponds to one material data, one file data corresponds to a plurality of material data, and a plurality of file data correspond to one material data;
specifically, creating data extraction is carried out on the advertisement putting requests to obtain the advertisement creating quantity; carrying out magnitude matching on the advertisement creating quantity to obtain a target magnitude corresponding to the advertisement creating quantity; selecting a plan creation rule corresponding to the advertisement putting request from a preset creation rule base according to the target magnitude, wherein the plan creation rule comprises the following steps: one file data corresponds to one material data, one file data corresponds to a plurality of material data, and a plurality of file data correspond to one material data.
The server extracts creation data of the advertisement putting requests to obtain advertisement creation quantity; the method comprises the steps of carrying out magnitude matching on advertisement creating quantities, obtaining target magnitude corresponding to the advertisement creating quantities, obtaining advertisement configuration information accessed by each user, creating a database and advertisement filtering rules, selecting plan creating rules corresponding to advertisement putting requests from a preset creating rule base according to the target magnitude, creating candidate creative sets, filtering the candidate creative sets, obtaining optimal advertisement creativity, carrying out network redirection skip, creating a click rate estimation model according to big data, analyzing aesthetic preferences, shopping preferences and game type style preferences of the users, displaying material contents which are most prone to advertisement conversion for the users through creative filtering and network redirection skip modes during each advertisement display, so as to attract the users to click advertisements, complete behaviors of purchasing, registering and the like, meet personalized requirements of the users, and directly improve the input-output ratio of the advertisement putting requests.
203. Performing association configuration on the plurality of file data and the plurality of material data according to a plan creation rule to obtain a plurality of target advertisement plans corresponding to the advertisement putting request;
204. performing delivery type mapping on the plurality of target advertisement plans to obtain a delivery type corresponding to each target advertisement plan;
205. grouping the plurality of target advertisement plans according to the delivery type corresponding to each target advertisement plan to obtain an advertisement plan group corresponding to each delivery type;
206. batch delivery is carried out on a plurality of target advertisement plans according to the advertisement plan group corresponding to each delivery type, and return data corresponding to each delivery type is obtained based on a preset time node;
specifically, the server performs association configuration on a plurality of file data and a plurality of material data according to a plan creation rule to obtain a plurality of target advertisement plans corresponding to the advertisement delivery request, wherein a template in each template base is associated with a user preference tag to obtain advertisement data, and the advertisement data includes: searching a user preference label matched with the user characteristic information according to the product information of the advertisement and the user characteristic information of the target user of the advertisement, and acquiring a template associated with the user preference label from a template library; the method comprises the steps of obtaining advertisement materials at least according to product information, adding the advertisement materials in an obtained template, generating an advertisement file, carrying out launch type mapping on a plurality of target advertisement plans to obtain a launch type corresponding to each target advertisement plan, grouping the plurality of target advertisement plans according to the launch type corresponding to each target advertisement plan to obtain an advertisement plan group corresponding to each launch type, carrying out batch launch on the plurality of target advertisement plans according to the advertisement plan group corresponding to each launch type, and obtaining return data corresponding to each launch type based on a preset time node.
207. Analyzing the delivery effect of the returned data corresponding to each delivery type to obtain a delivery and recovery ratio corresponding to each delivery type, and comparing the delivery and recovery ratios corresponding to each delivery type to obtain a comparison result;
specifically, the method comprises the steps of obtaining release output data corresponding to each release type; calculating the release recovery proportion corresponding to each release type according to the release output data and the return data corresponding to each release type; and sequencing and comparing the throwing recovery proportion corresponding to each throwing type to obtain a comparison result.
The server acquires release output data corresponding to each release type; calculating a delivery recovery ratio corresponding to each delivery type according to delivery output data and return data corresponding to each delivery type, receiving a delivery effect estimation request which indicates a target industry to which a target advertisement to be subjected to delivery effect estimation belongs, a target delivery channel and target time for requesting delivery effect estimation, determining effective duration of the advertisement delivered to the target industry in the target time in unit time of the target delivery channel, calculating total exposure number of the advertisement delivered to the target industry in unit time of the target delivery channel in the target time based on the effective duration and a preset advertisement loading rate, further calculating exposure number of the target advertisement in the target delivery channel in unit time in the target time according to the total exposure number, and finally, sequencing and comparing the delivery recovery ratios corresponding to each delivery type by a server to obtain a comparison result so as to realize the estimation of the advertisement delivery effect.
208. And generating an optimal delivery type according to the comparison result, acquiring an optimal advertisement plan in the optimal delivery type, and performing batch creation and delivery on the optimal advertisement plan.
Specifically, selecting an input type with the highest input recovery ratio from the plurality of input types as an optimal input type according to the comparison result; inquiring an optimal advertisement plan in the optimal delivery type; the optimal advertisement plans are copied in batches to obtain a plurality of optimal advertisement plans; and carrying out batch delivery on the optimal advertisement plans.
The server selects an advertisement type with the highest advertisement recovery ratio from the plurality of advertisement types as an optimal advertisement type according to the comparison result, responds to the advertisement delivery request, extracts a corresponding advertisement plan and advertisement cost from the advertisement delivery request, performs word segmentation processing on the advertisement plan to obtain advertisement plan keywords, matches the advertisement plan keywords with materials in a preset material library and material labels thereof to obtain target materials, and matches the advertisement plan keywords with user data and user labels thereof in a preset user database to obtain target clients; according to the target materials, the target customers and the advertisement cost, page advertisements are created and launched in batches, and finally the optimal advertisement plan in the optimal launching type is inquired; the optimal advertisement plans are copied in batches to obtain a plurality of optimal advertisement plans; the method comprises the steps of putting a plurality of optimal advertisement plans in batches, accurately matching target materials for creating advertisements in batches, and matching target users for putting, so that the problems that a certain amount of workers are required to operate, the putting efficiency is low and the putting is easy to miss in the existing advertisement putting mode are solved.
Optionally, performing file keyword extraction on the optimal advertisement plan to obtain a target keyword; identifying the material type of the optimal advertisement plan to obtain a target material type; acquiring a plurality of target users from a preset user preference database according to the target keywords and the target material types; and taking the target users as a target user group for advertising.
The method comprises the steps of obtaining a text to be extracted in an optimal advertisement plan, searching in an associated keyword library, matching keywords in the text to be extracted, determining all text sentence patterns and corresponding keyword combinations according to the text to be extracted and the keywords in the matched text to be extracted, and analyzing and determining the probability of the establishment of each text sentence pattern and the corresponding keyword combination according to a keyword probability network model; determining a keyword combination corresponding to the probability with the maximum probability median determined by analysis as a keyword combination extracted from a text to be extracted, and acquiring a plurality of target users from a preset user preference database according to target keywords and target material types; the method and the device have the advantages that the target users are used as the target user group for advertising, the response speed is high, the difficulty in extracting the text keywords is simplified, and the accuracy of the text keywords is improved.
In the embodiment of the invention, the diversity of the creation of the advertisement plans is improved by setting various plan creation rules and matching the plan creation rules corresponding to the advertisement putting requests according to the number of the created advertisements, then batch putting is carried out on a plurality of target advertisement plans according to the advertisement plan group corresponding to each putting type, putting is carried out according to the target advertisement plans, the purpose of batch copying and putting of the advertisements is achieved, the return data corresponding to each putting type is obtained based on the preset time node, then the putting recovery ratio analysis is carried out on the return data, the optimal putting type and the optimal advertisement plan are found, the optimal advertisement plan is used as the advertisement plan for batch putting, and the batch putting efficiency of the advertisements is further improved.
In the above description of the advertisement batch delivery method in the embodiment of the present invention, referring to fig. 3, an advertisement batch delivery device in the embodiment of the present invention is described below, and an embodiment of the advertisement batch delivery device in the embodiment of the present invention includes:
a receiving module 301, configured to receive an advertisement delivery request sent by a delivery terminal, parse the advertisement delivery request to obtain delivery resource data, and perform data classification on the delivery resource data to obtain multiple document data and multiple material data;
a creating module 302, configured to determine a number of created advertisements according to the advertisement delivery request, and match a plan creating rule corresponding to the advertisement delivery request according to the number of created advertisements, where the plan creating rule includes: one file data corresponds to one material data, one file data corresponds to a plurality of material data, and a plurality of file data correspond to one material data;
a grouping module 303, configured to create a plurality of target advertisement plans corresponding to the advertisement delivery request according to the plan creation rule, and group the plurality of target advertisement plans according to a plurality of preset delivery types to obtain an advertisement plan group corresponding to each delivery type;
a return module 304, configured to perform batch delivery on the multiple target advertisement plans according to the advertisement plan set corresponding to each delivery type, and obtain return data corresponding to each delivery type based on a preset time node;
an analysis module 305, configured to analyze the delivery effect of the returned data corresponding to each delivery type to obtain a delivery and recovery ratio corresponding to each delivery type, and compare the delivery and recovery ratios corresponding to each delivery type to obtain a comparison result;
and the delivery module 306 is configured to generate an optimal delivery type according to the comparison result, acquire an optimal advertisement plan in the optimal delivery type, and create and deliver the optimal advertisement plan in batch.
In the embodiment of the invention, by setting various plan creation rules and matching the plan creation rules corresponding to the advertisement putting requests according to the advertisement creation quantity, the diversity of advertisement plan creation is improved, then batch putting is carried out on the target advertisement plans according to the advertisement plan group corresponding to each putting type, putting is carried out according to the target advertisement plans, the purpose of batch copying and putting advertisements is achieved, return data corresponding to each putting type is obtained based on a preset time node, then putting recovery ratio analysis is carried out on the return data, the optimal putting type and the optimal advertisement plan are found, the optimal advertisement plan is used as the advertisement plan for batch putting, and the efficiency of batch putting advertisements is improved.
Referring to fig. 4, another embodiment of the device for batch advertisement delivery according to the embodiment of the present invention includes:
a receiving module 301, configured to receive an advertisement delivery request sent by a delivery terminal, parse the advertisement delivery request to obtain delivery resource data, and perform data classification on the delivery resource data to obtain multiple document data and multiple material data;
a creating module 302, configured to determine a number of created advertisements according to the advertisement delivery request, and match a plan creating rule corresponding to the advertisement delivery request according to the number of created advertisements, where the plan creating rule includes: one file data corresponds to one material data, one file data corresponds to a plurality of material data, and a plurality of file data correspond to one material data;
a grouping module 303, configured to create a plurality of target advertisement plans corresponding to the advertisement delivery request according to the plan creation rule, and group the plurality of target advertisement plans according to a plurality of preset delivery types to obtain an advertisement plan group corresponding to each delivery type;
a return module 304, configured to perform batch delivery on the multiple target advertisement plans according to the advertisement plan set corresponding to each delivery type, and obtain return data corresponding to each delivery type based on a preset time node;
an analysis module 305, configured to analyze the delivery effect of the returned data corresponding to each delivery type to obtain a delivery and recovery ratio corresponding to each delivery type, and compare the delivery and recovery ratios corresponding to each delivery type to obtain a comparison result;
and the delivery module 306 is configured to generate an optimal delivery type according to the comparison result, acquire an optimal advertisement plan in the optimal delivery type, and perform batch creation and delivery on the optimal advertisement plan.
Optionally, the receiving module 301 is specifically configured to: receiving an advertisement putting request sent by a putting terminal, and analyzing the advertisement putting request to obtain an advertisement creating interface; receiving the delivered resource data uploaded by the delivery terminal based on the advertisement creating interface; and performing text recognition on the thrown resource data to obtain a plurality of file data, and performing material information recognition on the thrown resource data to obtain a plurality of material data.
Optionally, the creating module 302 is specifically configured to: extracting creation data of the advertisement putting request to obtain the advertisement creation quantity; carrying out magnitude matching on the advertisement creating quantity to obtain a target magnitude corresponding to the advertisement creating quantity; selecting a plan creation rule corresponding to the advertisement putting request from a preset creation rule base according to the target magnitude, wherein the plan creation rule comprises the following steps: one file data corresponds to one material data, one file data corresponds to a plurality of material data, and a plurality of file data correspond to one material data.
Optionally, the grouping module 303 is specifically configured to: performing association configuration on the plurality of file data and the plurality of material data according to the plan creation rule to obtain a plurality of target advertisement plans corresponding to the advertisement putting request; carrying out delivery type mapping on the plurality of target advertisement plans to obtain a delivery type corresponding to each target advertisement plan; and grouping the plurality of target advertisement plans according to the delivery type corresponding to each target advertisement plan to obtain an advertisement plan group corresponding to each delivery type.
Optionally, the analysis module 305 is specifically configured to: acquiring release output data corresponding to each release type; calculating the release and recovery proportion corresponding to each release type according to the release output data and the return data corresponding to each release type; and sequencing and comparing the throwing recovery proportion corresponding to each throwing type to obtain a comparison result.
Optionally, the releasing module 306 is specifically configured to: selecting the releasing type with the highest releasing and recovering proportion from the plurality of releasing types as the optimal releasing type according to the comparison result; inquiring an optimal advertisement plan in the optimal delivery type; the optimal advertisement plans are copied in batches to obtain a plurality of optimal advertisement plans; and carrying out batch delivery on the optimal advertisement plans.
Optionally, the advertisement batch delivery device further includes:
the recognition module 307 is configured to perform pattern keyword extraction on the optimal advertisement plan to obtain a target keyword; identifying the material type of the optimal advertisement plan to obtain a target material type; acquiring a plurality of target users from a preset user preference database according to the target keywords and the target material types; and performing advertisement putting by taking the plurality of target users as a target user group.
In the embodiment of the invention, by setting various plan creation rules and matching the plan creation rules corresponding to the advertisement putting requests according to the advertisement creation quantity, the diversity of advertisement plan creation is improved, then batch putting is carried out on the target advertisement plans according to the advertisement plan group corresponding to each putting type, putting is carried out according to the target advertisement plans, the purpose of batch copying and putting advertisements is achieved, return data corresponding to each putting type is obtained based on a preset time node, then putting recovery ratio analysis is carried out on the return data, the optimal putting type and the optimal advertisement plan are found, the optimal advertisement plan is used as the advertisement plan for batch putting, and the efficiency of batch putting advertisements is improved.
Fig. 3 and fig. 4 describe the advertisement batch delivery device in the embodiment of the present invention in detail from the perspective of the modular functional entity, and the advertisement batch delivery device in the embodiment of the present invention is described in detail from the perspective of hardware processing.
Fig. 5 is a schematic structural diagram of an advertisement mass delivery device, according to an embodiment of the present invention, the advertisement mass delivery device 500 may have a relatively large difference due to different configurations or performances, and may include one or more processors (CPUs) 510 (e.g., one or more processors) and a memory 520, and one or more storage media 530 (e.g., one or more mass storage devices) storing applications 533 or data 532. Memory 520 and storage media 530 may be, among other things, transient or persistent storage. The program stored on storage medium 530 may include one or more modules (not shown), each of which may include a series of instruction operations for advertisement mass delivery device 500. Still further, processor 510 may be configured to communicate with storage medium 530 to execute a series of instruction operations in storage medium 530 on advertising mass delivery device 500.
The advertising mass delivery device 500 may also include one or more power supplies 540, one or more wired or wireless network interfaces 550, one or more input-output interfaces 560, and/or one or more operating systems 531, such as Windows Server, mac OS X, unix, linux, freeBSD, and the like. Those skilled in the art will appreciate that the configuration of the advertising mass delivery device shown in fig. 5 does not constitute a limitation of the advertising mass delivery device and may include more or less components than those shown, or some components in combination, or a different arrangement of components.
The invention further provides an advertisement batch delivery device, which comprises a memory and a processor, wherein the memory stores computer readable instructions, and the computer readable instructions, when executed by the processor, cause the processor to execute the steps of the advertisement batch delivery method in the embodiments.
The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium, and which may also be a volatile computer-readable storage medium, having stored therein instructions, which, when executed on a computer, cause the computer to execute the steps of the advertisement mass delivery method.
It can be clearly understood by those skilled in the art that, for convenience and simplicity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a portable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, an optical disk, or other various media capable of storing program codes.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. The advertisement batch delivery method is characterized by comprising the following steps:
receiving an advertisement putting request sent by a putting terminal, analyzing the advertisement putting request to obtain putting resource data, and performing data classification on the putting resource data to obtain a plurality of file data and a plurality of material data;
determining the number of created advertisements according to the advertisement putting request, and matching a plan creation rule corresponding to the advertisement putting request according to the number of created advertisements, wherein the plan creation rule comprises: one file data corresponds to one material data, one file data corresponds to a plurality of material data, and a plurality of file data correspond to one material data;
creating a plurality of target advertisement plans corresponding to the advertisement putting request according to the plan creating rule, and grouping the plurality of target advertisement plans according to a plurality of preset putting types to obtain an advertisement plan group corresponding to each putting type;
batch delivery is carried out on the plurality of target advertisement plans according to the advertisement plan group corresponding to each delivery type, and return data corresponding to each delivery type is obtained based on a preset time node;
analyzing the delivery effect of the returned data corresponding to each delivery type to obtain a delivery and recovery ratio corresponding to each delivery type, and comparing the delivery and recovery ratios corresponding to each delivery type to obtain a comparison result;
and generating an optimal delivery type according to the comparison result, acquiring an optimal advertisement plan in the optimal delivery type, and performing batch creation and delivery on the optimal advertisement plan.
2. The method of claim 1, wherein the receiving an advertisement delivery request sent by a delivery terminal, analyzing the advertisement delivery request to obtain delivery resource data, and performing data classification on the delivery resource data to obtain a plurality of document data and a plurality of material data comprises:
receiving an advertisement putting request sent by a putting terminal, and analyzing the advertisement putting request to obtain an advertisement creating interface;
receiving the delivered resource data uploaded by the delivery terminal based on the advertisement creating interface;
and performing text recognition on the thrown resource data to obtain a plurality of file data, and performing material information recognition on the thrown resource data to obtain a plurality of material data.
3. The advertisement batch delivery method according to claim 1, wherein the advertisement creation quantity is determined according to the advertisement delivery request, and a plan creation rule corresponding to the advertisement delivery request is matched according to the advertisement creation quantity, wherein the plan creation rule comprises: a file data corresponds to a material data, a file data corresponds to a plurality of material data and a plurality of file data correspond to a material data, including:
extracting creation data of the advertisement putting requests to obtain the number of created advertisements;
performing magnitude matching on the advertisement creating quantity to obtain a target magnitude corresponding to the advertisement creating quantity;
selecting a plan creation rule corresponding to the advertisement putting request from a preset creation rule base according to the target magnitude, wherein the plan creation rule comprises the following steps: one file data corresponds to one material data, one file data corresponds to a plurality of material data, and a plurality of file data correspond to one material data.
4. The method of claim 1, wherein the creating a plurality of target advertisement plans corresponding to the advertisement delivery request according to the plan creation rule, and grouping the plurality of target advertisement plans according to a plurality of preset delivery types to obtain an advertisement plan group corresponding to each delivery type comprises:
performing association configuration on the plurality of file data and the plurality of material data according to the plan creation rule to obtain a plurality of target advertisement plans corresponding to the advertisement putting request;
performing delivery type mapping on the plurality of target advertisement plans to obtain a delivery type corresponding to each target advertisement plan;
and grouping the plurality of target advertisement plans according to the delivery type corresponding to each target advertisement plan to obtain an advertisement plan group corresponding to each delivery type.
5. The advertisement batch delivery method according to claim 1, wherein the analyzing delivery effect of the returned data corresponding to each delivery type to obtain a delivery recovery ratio corresponding to each delivery type, and comparing the delivery recovery ratios corresponding to each delivery type to obtain a comparison result comprises:
acquiring release output data corresponding to each release type;
calculating the release recovery proportion corresponding to each release type according to the release output data and the return data corresponding to each release type;
and sequencing and comparing the feeding and recycling proportion corresponding to each feeding type to obtain a comparison result.
6. The advertisement batch delivery method according to claim 1, wherein the generating an optimal delivery type according to the comparison result, obtaining an optimal advertisement plan in the optimal delivery type, and performing batch creation and delivery on the optimal advertisement plan comprises:
selecting the releasing type with the highest releasing and recovering proportion from the plurality of releasing types as the optimal releasing type according to the comparison result;
inquiring an optimal advertisement plan in the optimal delivery type;
the optimal advertisement plans are copied in batches to obtain a plurality of optimal advertisement plans;
and carrying out batch delivery on the optimal advertisement plans.
7. The advertisement batch delivery method according to any one of claims 1 to 6, characterized in that the advertisement batch delivery method further comprises:
extracting the file keywords from the optimal advertisement plan to obtain target keywords;
identifying the material type of the optimal advertisement plan to obtain a target material type;
acquiring a plurality of target users from a preset user preference database according to the target keywords and the target material types;
and performing advertisement putting by taking the plurality of target users as a target user group.
8. The utility model provides an advertisement is put in batches device which characterized in that, advertisement is put in batches the device and is included:
the receiving module is used for receiving an advertisement putting request sent by a putting terminal, analyzing the advertisement putting request to obtain putting resource data, and performing data classification on the putting resource data to obtain a plurality of file data and a plurality of material data;
a creating module, configured to determine a number of created advertisements according to the advertisement delivery request, and match a plan creating rule corresponding to the advertisement delivery request according to the number of created advertisements, where the plan creating rule includes: one file data corresponds to one material data, one file data corresponds to a plurality of material data, and a plurality of file data correspond to one material data;
the grouping module is used for creating a plurality of target advertisement plans corresponding to the advertisement putting request according to the plan creating rule and grouping the plurality of target advertisement plans according to a plurality of preset putting types to obtain an advertisement plan group corresponding to each putting type;
the return module is used for carrying out batch delivery on the target advertisement plans according to the advertisement plan group corresponding to each delivery type and acquiring return data corresponding to each delivery type based on a preset time node;
the analysis module is used for analyzing the putting effect of the returned data corresponding to each putting type to obtain a putting and recycling proportion corresponding to each putting type, and comparing the putting and recycling proportions corresponding to each putting type to obtain a comparison result;
and the delivery module is used for generating an optimal delivery type according to the comparison result, acquiring an optimal advertisement plan in the optimal delivery type, and performing batch creation and delivery on the optimal advertisement plan.
9. The utility model provides an advertisement is put in batches equipment which characterized in that, advertisement is put in batches equipment and is included: a memory and at least one processor, the memory having instructions stored therein;
the at least one processor invokes the instructions in the memory to cause the advertisement mass delivery device to perform the advertisement mass delivery method of any of claims 1-7.
10. A computer-readable storage medium having instructions stored thereon, wherein the instructions, when executed by a processor, implement the method of mass delivery of advertisements of any of claims 1-7.
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