CN112053197B - Advertisement playing method and system based on big data and advertisement service platform - Google Patents

Advertisement playing method and system based on big data and advertisement service platform Download PDF

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CN112053197B
CN112053197B CN202010991029.6A CN202010991029A CN112053197B CN 112053197 B CN112053197 B CN 112053197B CN 202010991029 A CN202010991029 A CN 202010991029A CN 112053197 B CN112053197 B CN 112053197B
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CN112053197A (en
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梁玉娣
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HUNAN TRYINE TECHNOLOGY Co.,Ltd.
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Hunan Tryine Technology Co ltd
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Abstract

The invention relates to the technical field of big data and multimedia, in particular to an advertisement playing method and system based on big data and an advertisement service platform. According to the method and the device, iterative mapping of the advertisement carousel rule is carried out on the advertisement delivery strategy information in the candidate video playing information, continuous updating of the carousel content service of the advertisement carousel rule is achieved, and the advertisement program characteristics and the corresponding delivery influence heat characteristics are fused to configure the preset advertisement control script, so that the accuracy of advertisement distribution of the configured preset advertisement control script is higher, the data processing efficiency is greatly improved, and the analysis efficiency of the advertisement distribution is further improved.

Description

Advertisement playing method and system based on big data and advertisement service platform
Technical Field
The invention relates to the technical field of big data and multimedia, in particular to an advertisement playing method and system based on big data and an advertisement service platform.
Background
In people's daily life, various advertisements are ubiquitous, the advertisement market is turning from mass marketing to mass marketing, and in the era that products and consumers are subdivided continuously, the limitations of traditional media cannot effectively distinguish target audience groups of products.
In the traditional advertisement distribution scheme, the characteristics of advertisement distribution can be acquired in a way that business personnel analyze advertisement content, so that advertisements which are more in line with the interests of the advertisement display equipment are distributed for the advertisement display equipment based on the characteristics.
However, through research of the inventor, it is found that the time cost of artificial advertisement content analysis is extremely high, and the analysis efficiency is difficult to achieve the expected effect, so that the accuracy of advertisement distribution and the analysis efficiency of advertisement distribution are greatly influenced.
Disclosure of Invention
In order to overcome at least the above disadvantages in the prior art, an object of the present invention is to provide an advertisement playing method, system and advertisement service platform based on big data, which can implement continuous update of carousel content service of advertisement carousel rules by performing iterative mapping of advertisement delivery policy information in candidate video playing information, and configure a preset advertisement control script by fusing advertisement program characteristics and corresponding delivery influence heat characteristics, so that the accuracy of advertisement distribution of the configured preset advertisement control script is higher, the efficiency of data processing is greatly improved, and the analysis efficiency of advertisement distribution is further improved.
In a first aspect, the present invention provides an advertisement playing method based on big data, which is applied to an advertisement service platform, wherein the advertisement service platform is in communication connection with a plurality of advertisement display devices, and the method includes:
acquiring candidate video playing information, and performing advertisement stream configuration and advertisement carousel rule addition on the candidate video playing information to obtain a corresponding candidate advertisement stream configuration set, wherein the candidate video playing information is video playing information of video interest elements corresponding to big data operation data of the advertisement display equipment in a preset time period;
analyzing the candidate advertisement stream configuration set to obtain an advertisement space display node set and corresponding advertisement carousel control information, and determining the advertisement space display node set of which the advertisement carousel control information meets a preset information stream display strategy as a candidate advertisement display control;
traversing the candidate advertisement stream configuration set according to the candidate advertisement display control, circularly updating the carousel content service of the advertisement carousel rule, adding a carousel content queue to the candidate advertisement stream configuration set meeting the candidate advertisement display control, and extracting advertisement program characteristics and corresponding delivery influence heat characteristics in the candidate advertisement stream configuration set to which the carousel content queue is added;
and configuring a preset advertisement control script according to the advertisement program characteristics, the delivery influence heat characteristics and the carousel content queue to obtain a configured preset advertisement control script, and performing advertisement distribution of corresponding advertisement control nodes of the played video corresponding to the candidate video playing information on a candidate advertisement stream configuration set based on the configured preset advertisement control script.
In a possible implementation manner of the first aspect, the step of parsing the candidate advertisement stream configuration set to obtain an advertisement space display node set and corresponding advertisement carousel control information, and determining an advertisement space display node set of which the advertisement carousel control information meets a preset information stream display policy as the candidate advertisement display control includes:
analyzing the candidate advertisement stream configuration set to obtain a corresponding advertisement space display node set;
acquiring first candidate carousel control information of an advertisement carousel rule and global carousel control information of the advertisement carousel rule contained in each advertisement space display node set;
determining corresponding first advertisement carousel control information according to the inclusion relation between the first candidate carousel control information and the global carousel control information;
and determining the advertisement space display node set of which the first advertisement carousel control information matches a preset carousel subscription rule as a candidate advertisement display control.
In a possible implementation manner of the first aspect, the step of performing advertisement stream configuration and advertisement carousel rule addition on the candidate video playing information to obtain a corresponding candidate advertisement stream configuration set includes:
performing advertisement stream configuration operation on the candidate video playing information to obtain a corresponding advertisement stream configuration set;
acquiring a carousel content service of an advertisement carousel rule, and determining the carousel content service in the advertisement stream configuration set;
and mapping corresponding advertisement carousel rules for the carousel content service in the advertisement stream configuration set to obtain a corresponding candidate advertisement stream configuration set.
In a possible implementation manner of the first aspect, the step of circularly updating a carousel content service of an advertisement carousel rule by traversing the candidate advertisement stream configuration set according to the candidate advertisement display control includes:
determining an advertisement putting strategy information set matched with the advertisement space display node set of the candidate advertisement display control in the candidate advertisement flow configuration set;
acquiring second candidate carousel control information of the advertisement carousel rules and global carousel control information of the advertisement carousel rules, which are contained in each advertisement putting strategy information set, and determining corresponding second advertisement carousel control information according to the inclusion relation between the second candidate carousel control information and the global carousel control information;
determining an advertisement putting strategy information set of which the second advertisement carousel control information covers a preset putting subscription range as a candidate advertisement putting strategy information set, performing advertisement carousel rule mapping on advertisement putting strategy information in the candidate advertisement putting strategy information set according to the candidate advertisement display control, and updating a carousel content service of the advertisement carousel rule;
and re-executing the step of obtaining second candidate carousel control information of the advertisement carousel rules and global carousel control information of the advertisement carousel rules contained in each advertisement putting strategy information set, iteratively mapping the advertisement carousel rules on the advertisement putting strategy information in the candidate advertisement putting strategy information set, and updating the carousel content service of the advertisement carousel rules until the iteration times meet a preset iteration threshold.
In a possible implementation manner of the first aspect, the step of performing advertisement carousel rule mapping on the advertisement delivery policy information in the candidate advertisement delivery policy information set according to the candidate advertisement display control and updating a carousel content service of the advertisement carousel rule includes:
acquiring a mapping rule for performing advertisement carousel rule mapping on each advertisement display control node in the candidate advertisement display control;
and performing advertisement carousel rule mapping on the advertisement putting strategy information in the candidate advertisement putting strategy information set according to the mapping rule and an advertisement display control node, and updating the carousel content service of the advertisement carousel rule.
In a possible implementation manner of the first aspect, the step of extracting an advertisement program feature and a corresponding impression influence heat feature in a candidate ad stream configuration set of an add carousel content queue includes:
determining advertisement program characteristics of the candidate advertisement stream configuration set of the carousel content adding queue;
and calculating the impression influence heat characteristic of the candidate advertisement flow configuration set of the adding carousel content queue.
In a possible implementation manner of the first aspect, the step of calculating a placement impact heat characteristic of a candidate ad stream configuration set for adding a carousel content queue includes:
acquiring historical distribution frequency of candidate advertisement putting strategy information in a candidate advertisement flow configuration set added with a carousel content queue, and acquiring the number of total carousel content queues appearing in the candidate video playing information;
determining corresponding content hotspot information according to the inclusion relation between the historical distribution frequency of the candidate advertisement putting strategy information and the number of the total carousel content queues;
acquiring the global content hotspot number in the candidate video playing information and acquiring the candidate content hotspot number containing the candidate advertisement putting strategy information;
calculating hot content information corresponding to the same hot spot number of the global content hot spot number and the candidate content hot spot number, and calculating hot word frequency characteristics of the hot content information corresponding to the same hot spot number to obtain a corresponding hot word frequency characteristic result;
and fusing the content hotspot information with hotspot word frequency feature results to obtain influence factors of the candidate advertisement delivery strategy information, and combining the influence factors corresponding to the advertisement delivery strategy information in the same candidate advertisement stream configuration set to generate delivery influence heat features.
In a possible implementation manner of the first aspect, the video playing information of the video interest element is obtained through the following steps:
acquiring at least one video operation object set from big data operation data of the advertisement display equipment in a preset time period, wherein each advertisement operation element in each video operation object set belongs to the same advertisement scheduling, and each advertisement operation element corresponds to an operation jump page under the advertisement scheduling;
identifying interest points of the video operation object sets on the basis of the operation jump pages under the advertising schedule to obtain the interest point characteristics and the corresponding interest weights of the video operation object sets;
according to the interest point characteristics and the corresponding interest weights, video playing tracing information of the advertisement scheduling period corresponding to each advertisement operation element is determined;
and determining candidate video interest objects corresponding to each advertisement scheduling period by adopting an artificial intelligence model according to the video playing tracing information of the advertisement scheduling period corresponding to each advertisement operation element, generating strategy configuration information of a video playing strategy corresponding to the big data operation data according to the candidate video interest objects corresponding to each advertisement scheduling period, and pushing the video playing information of the corresponding video interest elements to the advertisement display equipment according to the strategy configuration information of the video playing strategy.
In a possible implementation manner of the first aspect, the step of determining, according to the interest point features and the corresponding interest weights, video playing tracing information of an advertisement schedule to which each advertisement operation element corresponds includes:
screening the interest point characteristics according to the interest point characteristics and the corresponding interest weights to obtain target interest point characteristics larger than preset interest weights;
acquiring a first video playing tracing object set corresponding to a first interest point service and a second video playing tracing object set corresponding to a second interest point service on a target interest point feature, wherein the first video playing tracing object set comprises a plurality of interest point tracing nodes for interest point tracing of a related interest track in the target interest point feature by the first interest point service, the second video playing tracing object set comprises a plurality of interest point tracing nodes for interest point tracing of a related interest track in the target interest point feature by the second interest point service, and each interest point tracing node comprises a plurality of tracing object coverage information;
clustering a plurality of interest point tracing nodes in the first video playing tracing object set based on a preset interest point tracing node category to obtain a clustered first video playing tracing object set; the preset interest point tracing node type belongs to types corresponding to the plurality of tracing object coverage information;
combining the coverage information of each retroactive object corresponding to each preset interest point retroactive node category in the clustered first video playing retroactive object set into a first initial interest point retroactive node set;
noise removal is carried out on the first initial interest point tracing node set to obtain a first interest point tracing node set, and therefore a first interest point tracing node set corresponding to the preset interest point tracing node category set is obtained;
combining all tracing object coverage information in the first interest point tracing node set into a first tracing object coverage information set corresponding to the first interest point service, wherein the first tracing object coverage information set corresponds to a preset interest point tracing node type set, and the preset interest point tracing node type is a set formed by all interest point tracing node types used for interest point tracing;
extracting, from the second video playing tracing object set, each tracing object coverage information corresponding to each preset interest point tracing node category in the preset interest point tracing node category set, and combining the tracing object coverage information into a second tracing object coverage information set corresponding to the second interest point service, where the second tracing object coverage information set corresponds to the preset interest point tracing node category set, and the first tracing object coverage information set and the second tracing object coverage information set are sets composed of tracing object coverage information extracted from the corresponding video playing tracing object sets, respectively;
determining a characteristic segment label of the same tracing object covering information between the first tracing object covering information set and the second tracing object covering information set, and obtaining a label service description vector from a label service interval corresponding to the characteristic segment label;
when the label service description vector covers a preset description vector range, determining the first interest point service and the second interest point service as interest point tracing units;
using any two interest point elements in the target interest point feature as a first interest point service and a second interest point service to perform interest point tracing crawling, and obtaining a feature segment set with interest point tracing behaviors in the target interest point feature until the detection of the interest point elements in the target interest point feature is completed;
taking the feature segment labels of the interest point elements in the feature segment set as candidate target labels;
taking the feature segment labels of the interest point elements corresponding to the target interest point features as candidate global labels;
calculating the label distribution of the candidate target label and the candidate global label to obtain a label distribution characteristic corresponding to the target interest point characteristic;
and when the label distribution characteristics meet a preset distribution trend, determining the playing content formed by the label distribution characteristics corresponding to the target interest point characteristics as video playing tracing information of the advertisement schedule corresponding to each advertisement operation element.
In a second aspect, an embodiment of the present invention further provides an advertisement playing system based on big data, which is applied to an advertisement service platform, where the advertisement service platform is in communication connection with a plurality of advertisement display devices, and the system includes:
the configuration adding module is used for acquiring candidate video playing information, and performing advertisement stream configuration and advertisement carousel rule addition on the candidate video playing information to obtain a corresponding candidate advertisement stream configuration set, wherein the candidate video playing information is video playing information of video interest elements corresponding to big data operation data of the advertisement display equipment in a preset time period;
the analysis module is used for analyzing the candidate advertisement stream configuration set to obtain an advertisement space display node set and corresponding advertisement carousel control information, and determining the advertisement space display node set of which the advertisement carousel control information meets a preset information stream display strategy as a candidate advertisement display control;
the updating module is used for traversing the candidate advertisement flow configuration set according to the candidate advertisement display control, circularly updating the carousel content service of the advertisement carousel rule, adding a carousel content queue to the candidate advertisement flow configuration set meeting the candidate advertisement display control, and extracting advertisement program characteristics and corresponding delivery influence heat characteristics in the candidate advertisement flow configuration set added with the carousel content queue;
and the advertisement distribution module is used for configuring a preset advertisement control script according to the advertisement program characteristics, the delivery influence heat characteristics and the carousel content queue to obtain a configured preset advertisement control script, and distributing advertisements of corresponding advertisement control nodes for playing videos corresponding to the candidate video playing information to the candidate advertisement stream configuration set based on the configured preset advertisement control script.
In a third aspect, an embodiment of the present invention further provides a method and a system for playing an advertisement based on big data, where the method and the system for playing an advertisement based on big data include an advertisement service platform and a plurality of advertisement display devices in communication connection with the advertisement service platform;
the advertisement service platform is used for acquiring candidate video playing information, and performing advertisement stream configuration and advertisement carousel rule addition on the candidate video playing information to obtain a corresponding candidate advertisement stream configuration set, wherein the candidate video playing information is video playing information of video interest elements corresponding to big data operation data of the advertisement display equipment in a preset time period;
the advertisement service platform is used for analyzing the candidate advertisement stream configuration set to obtain an advertisement space display node set and corresponding advertisement carousel control information, and determining the advertisement space display node set of which the advertisement carousel control information meets a preset information stream display strategy as a candidate advertisement display control;
the advertisement service platform is used for traversing the candidate advertisement flow configuration set according to the candidate advertisement display control, circularly updating the carousel content service of the advertisement carousel rule, adding a carousel content queue to the candidate advertisement flow configuration set meeting the candidate advertisement display control, and extracting advertisement program characteristics and corresponding delivery influence heat characteristics in the candidate advertisement flow configuration set added with the carousel content queue;
and the advertisement service platform is used for configuring a preset advertisement control script according to the advertisement program characteristics, the delivery influence heat characteristics and the carousel content queue to obtain a configured preset advertisement control script, and performing advertisement distribution of corresponding advertisement control nodes for playing videos corresponding to the candidate video playing information on a candidate advertisement stream configuration set based on the configured preset advertisement control script.
In a fourth aspect, an embodiment of the present invention further provides an advertisement service platform, where the advertisement service platform includes a processor, a machine-readable storage medium, and a network interface, where the machine-readable storage medium, the network interface, and the processor are connected through a bus system, the network interface is used for being communicatively connected with at least one advertisement presentation device, the machine-readable storage medium is used for storing a program, an instruction, or a code, and the processor is used for executing the program, the instruction, or the code in the machine-readable storage medium to execute the method for playing an advertisement based on big data in the first aspect or any one of the possible implementation manners in the first aspect.
In a fifth aspect, an embodiment of the present invention provides a computer-readable storage medium, where instructions are stored in the computer-readable storage medium, and when the instructions are executed, the computer is caused to execute the big data based advertisement playing method in the first aspect or any one of the possible implementation manners of the first aspect.
Based on any one of the above aspects, the invention acquires the candidate video playing information to perform advertisement stream configuration and advertisement carousel rule addition, so as to obtain a corresponding candidate advertisement stream configuration set; calculating the candidate advertisement stream configuration set to obtain an advertisement space display node set and advertisement carousel control information, and determining the advertisement space display node set of which the advertisement carousel control information meets a preset information stream display strategy as a candidate advertisement display control; circularly updating the carousel content service of the advertisement carousel rule for the candidate advertisement stream configuration set according to the candidate advertisement display control; adding a carousel content queue for a candidate advertisement stream configuration set meeting the candidate advertisement display control, and extracting advertisement program characteristics and release influence heat characteristics in the candidate advertisement stream configuration set added with the carousel content queue; and configuring the preset advertisement control script according to the advertisement program characteristics, the delivery influence heat characteristics and the carousel content queue to obtain the configured preset advertisement control script, and performing advertisement distribution of corresponding advertisement control nodes of the played video corresponding to the candidate video playing information on the candidate advertisement stream configuration set. Therefore, iterative mapping of the advertisement carousel rule is carried out on the advertisement delivery strategy information in the candidate video playing information, continuous updating of the carousel content service of the advertisement carousel rule is achieved, the advertisement program characteristics and the corresponding delivery influence heat degree characteristics are fused to configure the preset advertisement control script, the accuracy of advertisement distribution of the preset advertisement control script after configuration is higher, the data processing efficiency is greatly improved, and the analysis efficiency of the advertisement distribution is further improved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a schematic view of an application scenario of a big data-based advertisement playing method system according to an embodiment of the present invention;
fig. 2 is a schematic flowchart of a big data-based advertisement playing method according to an embodiment of the present invention;
fig. 3 is a functional module schematic diagram of a system for playing an advertisement based on big data according to an embodiment of the present invention;
fig. 4 is a block diagram illustrating a structure of an advertisement service platform for implementing the above-mentioned advertisement playing method based on big data according to an embodiment of the present invention.
Detailed Description
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings used in the description of the embodiments will be briefly described below. It is obvious that the drawings in the following description are only examples or embodiments of the present description, and that for a person skilled in the art, the present description can also be applied to other similar scenarios on the basis of these drawings without inventive effort. Unless otherwise apparent from the context, or otherwise indicated, like reference numbers in the figures refer to the same structure or operation.
It should be understood that "system", "unit" and/or "module" as used in this specification is a method for distinguishing different components, elements, parts or assemblies at different levels. However, other words may be substituted by other expressions if they accomplish the same purpose.
As used in this specification and the appended claims, the terms "a," "an," "the," and/or "the" are not intended to be inclusive in the singular, but rather are intended to be inclusive in the plural, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements.
Flow charts are used in this description to illustrate operations performed by a system according to embodiments of the present description. It should be understood that the preceding or following operations are not necessarily performed in the exact order in which they are performed. Rather, the various steps may be processed in reverse order or simultaneously. Meanwhile, other operations may be added to the processes, or a certain step or several steps of operations may be removed from the processes.
Fig. 1 is an interaction diagram of a system 10 for playing an advertisement based on big data according to an embodiment of the present invention. The big data based advertisement playing method system 10 may include an advertisement service platform 100 and an advertisement presentation device 200 communicatively connected to the advertisement service platform 100. The big data based advertisement broadcasting method system 10 shown in fig. 1 is only one possible example, and in other possible embodiments, the big data based advertisement broadcasting method system 10 may also include only one of the components shown in fig. 1 or may also include other components.
In this embodiment, the internet of things cloud advertisement service platform 100 and the advertisement display device 200 in the big data based advertisement playing method system 10 may execute the big data based advertisement playing method described in the following method embodiment in a matching manner, and the detailed description of the following method embodiment may be referred to in the execution steps of the specific advertisement service platform 100 and the advertisement display device 200.
To solve the technical problem in the foregoing background art, fig. 2 is a schematic flow chart of an advertisement playing method based on big data according to an embodiment of the present invention, and the advertisement playing method based on big data according to the present embodiment may be executed by the advertisement service platform 100 shown in fig. 1, and the following describes the advertisement playing method based on big data in detail.
Step S110, obtaining candidate video playing information, and performing advertisement stream configuration and advertisement carousel rule addition on the candidate video playing information to obtain a corresponding candidate advertisement stream configuration set.
And step S120, analyzing the candidate advertisement stream configuration set to obtain an advertisement space display node set and corresponding advertisement carousel control information, and determining the advertisement space display node set of which the advertisement carousel control information meets a preset information stream display strategy as a candidate advertisement display control.
Step S130, traversing the candidate advertisement flow configuration set according to the candidate advertisement display control, circularly updating the carousel content service of the advertisement carousel rule, adding a carousel content queue to the candidate advertisement flow configuration set meeting the candidate advertisement display control, and extracting advertisement program characteristics and corresponding delivery influence heat characteristics in the candidate advertisement flow configuration set added with the carousel content queue.
And S140, configuring a preset advertisement control script according to the advertisement program characteristics, the delivery influence heat characteristics and the carousel content queue to obtain a configured preset advertisement control script, and performing advertisement distribution of corresponding advertisement control nodes of the played videos corresponding to the candidate video playing information on a candidate advertisement stream configuration set based on the configured preset advertisement control script.
In this embodiment, the candidate video playing information may be video playing information of a video interest element corresponding to the big data operation data of the advertisement display device 200 in a preset time period. For example, the advertisement display device 200 may be disposed at different service points (e.g., banks, shopping malls, residential outlets, etc.) to provide various consulting services for the user, and the user may automatically generate big data operation data through the advertisement display terminal 200 during browsing operation to obtain video playing information of video interest elements.
In this embodiment, the advertisement delivery policy information may refer to policy information generated in a specific advertisement delivery process for measuring a service of each advertisement tag, and the advertisement carousel rule may refer to carousel rule information used for performing a push policy reference in the specific advertisement delivery process, for example, may refer to carousel rule configuration information after performing service setting according to a preset defined advertisement queue.
In this embodiment, each advertisement space display node in the advertisement space display node set may be configured to represent advertisement space information specifically referred to in a subsequent advertisement allocation process, and the corresponding advertisement carousel control information may refer to content arrangement information of carousel control pre-configured before the advertisement space display node serves as a subsequent advertisement space positioning process.
In this embodiment, the carousel content service may refer to an operation service included in carousel control in a subsequent carousel control process, each operation service may correspond to one carousel content queue, the advertisement program feature may be used to represent a feature of an advertisement program in a subsequent push process, a corresponding delivery influence heat degree feature may be used to represent a reference heat degree of the advertisement program, a definition rule of a specific reference heat degree is not limited, and a flexible design may be performed based on the prior art.
In this embodiment, in step S140, the preset advertisement control script may be configured according to the advertisement program characteristic and the delivery influence heat characteristic, so as to obtain the configured preset advertisement control script. For example, the advertisement program feature, the impression influence heat degree feature and the carousel content queue may be input into a preset advertisement control script to be configured to obtain a corresponding information carousel content queue set, and the information carousel content queue is compared with the carousel content queue, and then the script configuration content of the preset advertisement control script is continuously updated according to the comparison difference, so that the advertisement distribution of the corresponding advertisement control node of the played video corresponding to the candidate video playing information may be performed on the candidate advertisement stream configuration set based on the configured preset advertisement control script. For example, a corresponding candidate carousel content queue may be obtained for the candidate ad stream configuration set based on the configured preset ad control script, and then, based on the push source content related to the candidate carousel content queue, the ad distribution of the corresponding ad control node that plays the video corresponding to the candidate video play information may be performed.
Based on the above steps, the embodiment performs iterative mapping of the advertisement carousel rule on the advertisement delivery strategy information in the candidate video playing information, so as to realize continuous update of the carousel content service of the advertisement carousel rule, and combines the advertisement program characteristics and the corresponding delivery influence heat characteristics to configure the preset advertisement control script, so that the accuracy of advertisement distribution of the configured preset advertisement control script is higher, the data processing efficiency is greatly improved, and the analysis efficiency of the advertisement distribution is further improved.
In one possible implementation, step S120 may be implemented by the following exemplary substeps, which are described in detail below.
And a substep S121, analyzing the candidate advertisement stream configuration set to obtain a corresponding advertisement space display node set.
And a substep S122 of obtaining first candidate carousel control information of the advertisement carousel rule and global carousel control information of the advertisement carousel rule contained in each advertisement space display node set.
And a substep S123 of determining corresponding first advertisement carousel control information according to the inclusion relationship between the first candidate carousel control information and the global carousel control information.
And a substep S124, determining the advertisement space display node set of which the first advertisement carousel control information matches the preset carousel subscription rule as a candidate advertisement display control.
In one possible implementation, step S110 may be implemented by the following exemplary substeps, which are described in detail below.
And a substep S111, performing advertisement stream configuration operation on the candidate video playing information to obtain a corresponding advertisement stream configuration set.
And a substep S112, acquiring the carousel content service of the advertisement carousel rule, and determining the carousel content service in the advertisement stream configuration set.
And a substep S113, mapping corresponding advertisement carousel rules for the carousel content service in the advertisement stream configuration set to obtain a corresponding candidate advertisement stream configuration set.
In one possible implementation manner, for step S130, in the process of traversing the candidate advertisement stream configuration set according to the candidate advertisement exhibition control and circularly updating the carousel content service of the advertisement carousel rule, the following exemplary sub-steps may be implemented, which are described in detail below.
And the substep S131, determining an advertisement putting strategy information set matched with the advertisement space display node set of the candidate advertisement display control in the candidate advertisement stream configuration set.
And a substep S132, obtaining second candidate carousel control information of the advertisement carousel rule and global carousel control information of the advertisement carousel rule included in each advertisement delivery strategy information set, and determining corresponding second advertisement carousel control information according to an inclusion relationship between the second candidate carousel control information and the global carousel control information.
And a substep S133, determining an advertisement putting strategy information set of which the second advertisement carousel control information covers a preset putting subscription range as a candidate advertisement putting strategy information set, performing advertisement carousel rule mapping on the advertisement putting strategy information in the candidate advertisement putting strategy information set according to the candidate advertisement display control, and updating the carousel content service of the advertisement carousel rule.
For example, a mapping rule for performing advertisement carousel rule mapping on each advertisement presentation control node in the candidate advertisement presentation control may be obtained. And then, according to the mapping rule, performing advertisement carousel rule mapping on the advertisement putting strategy information in the candidate advertisement putting strategy information set according to the advertisement display control node, and updating the carousel content service of the advertisement carousel rule.
And a substep S134, re-executing the step of obtaining the second candidate carousel control information of the advertisement carousel rule and the global carousel control information of the advertisement carousel rule contained in each advertisement putting strategy information set, iteratively performing advertisement carousel rule mapping on the advertisement putting strategy information in the candidate advertisement putting strategy information set, and updating the carousel content service of the advertisement carousel rule until the iteration times meet a preset iteration threshold.
In one possible implementation, for step S130, in extracting the commercial program feature and the corresponding impression influence heat feature in the candidate ad stream configuration set of the add carousel content queue, the following exemplary sub-steps may be implemented, which are described in detail below.
Sub-step S135, determining the ad program characteristics of the candidate ad stream configuration set that adds the carousel content queue.
And a substep S136, calculating the impression influence heat characteristic of the candidate advertisement flow configuration set for adding the carousel content queue.
For example, the historical distribution frequency of the candidate advertisement putting strategy information in the candidate advertisement stream configuration set added with the carousel content queue may be obtained, and the total number of the carousel content queues appearing in the candidate video playing information may be obtained. And then, determining corresponding content hotspot information according to the inclusion relation between the historical distribution frequency of the candidate advertisement putting strategy information and the number of the total carousel content queues. On the basis, the global content hotspot number in the candidate video playing information is obtained, the candidate content hotspot number containing the candidate advertisement putting strategy information is obtained, hotspot content information corresponding to the same hotspot number of the global content hotspot number and the candidate content hotspot number is calculated, hotspot word-frequency characteristics of the hotspot content information corresponding to the same hotspot number are calculated, and corresponding hotspot word-frequency characteristic results are obtained. And then, fusing the content hotspot information with hotspot word frequency feature results to obtain influence factors of the candidate advertisement delivery strategy information, and combining the influence factors corresponding to the advertisement delivery strategy information in the same candidate advertisement stream configuration set to generate delivery influence heat features.
In one possible implementation, for step S110, the video playing information of the video interest element may be obtained through the following exemplary sub-steps, which are described in detail below.
Step S101, at least one video operation object set is obtained from big data operation data of the advertisement display equipment in a preset time period.
And S102, identifying interest points of the video operation object sets based on the operation jump pages under the advertisement scheduling period to obtain the interest point characteristics and the corresponding interest weights of the video operation object sets.
And step S103, determining video playing tracing information of the advertisement scheduling period corresponding to each advertisement operation element according to the interest point characteristics and the corresponding interest weights.
And step S104, determining candidate video interest objects corresponding to each advertisement scheduling period by adopting an artificial intelligence model according to the video playing tracing information of the advertisement scheduling period to which each advertisement operation element corresponds, and generating strategy configuration information of a video playing strategy corresponding to the big data operation data according to the candidate video interest objects corresponding to each advertisement scheduling period.
In this embodiment, each advertisement operation element in each video operation object set belongs to the same advertisement scheduling, and each advertisement operation element corresponds to an operation jump page under the advertisement scheduling to which it belongs. For example, the advertisement operation elements of which the advertisement schedules belong to the same advertisement schedule may be obtained from the big data operation data of the advertisement display device in a preset time period, and the advertisement operation elements belonging to each advertisement schedule may be determined as the corresponding video operation object set.
Illustratively, a plurality of advertisement operation elements can be included in the big data operation data, each advertisement operation element can refer to a region division set formed by a video region and a graphic region which are related to operation behaviors, and the region division set formed by the video region and the graphic region can be used for representing different information with special identification in the operation process of the actual big data-based advertisement playing. Similarly, for different advertisement operation elements, the types of the corresponding advertisement schedules are different, so that the advertisement schedules can correspond to a certain advertisement schedule one to one, that is, the advertisement schedules can be used to represent the tag types of the advertisement scheduling stage.
In this embodiment, the interest point may be used to represent interest content that may represent a business scenario service associated with the interest point, the interest point feature may be used to represent an interest content set corresponding to the interest point, and the corresponding interest weight may be used to represent a frequency of delivery that the interest content set corresponding to the interest point has a content hotspot of an advertisement service between the associated advertisement schedule and the associated advertisement schedule.
In this embodiment, the video playing tracing information may be used to represent record information in units of tracing service ranges of generated interest point tracing behaviors, so that candidate video interest objects corresponding to each advertisement ranking may be determined by using an artificial intelligence model according to the video playing tracing information of the advertisement ranking to which each advertisement operation element corresponds, and the candidate video interest objects are used to represent thermalization items (for example, items with operation cycle times exceeding two times) in the interest point tracing process, so that policy configuration information of a video playing policy corresponding to big data operation data may be generated specifically according to the candidate video interest objects corresponding to each advertisement ranking.
Based on the design, the embodiment extracts the interest point characteristics of each video operation object set in an interest point identification mode, and determines the video playing tracing information of the advertisement scheduling period to which each advertisement operation element belongs based on the interest weight, so that each operation jump page is converted into an effective push prediction basis. Therefore, according to the video playing tracing information of the advertisement scheduling period to which each advertisement operation element corresponds, an artificial intelligence model is adopted to determine a candidate video interest object corresponding to each advertisement scheduling period, strategy configuration information of a video playing strategy corresponding to the big data operation data is generated according to the candidate video interest object corresponding to each advertisement scheduling period, and the video playing information of the corresponding video interest element is pushed to the advertisement display equipment according to the strategy configuration information of the video playing strategy, so that request response recommendation can be effectively combined with the specific type of the advertisement scheduling period according to the big data operation data, and the prediction precision of advertisement distribution is improved.
In one possible implementation, such as for step S102, this may be achieved by the following exemplary sub-steps, described in detail below.
And step S1021, traversing the advertisement operation elements in the video operation object set for each video operation object set, extracting operation jump migration information of each operation jump page fused with the advertisement scheduling period to which the video operation object set belongs from the advertisement operation elements, and determining jump service information corresponding to the video operation object set according to the extracted operation jump migration information.
And a substep S1022, removing the setting description information included in each operation jump migration information in the jump service information, performing video playing service distribution splitting on the operation jump migration information from which the setting description information is removed, obtaining first jump service information, and determining the strength of the interest point of each video playing service distribution according to the jump service heat degree of the video playing service distribution in the operation jump migration information included in the first jump service information.
For example, the skip service heat of the video playing service distributed in the operation skip transition information included in the first skip service information may refer to a length of the video playing service distributed in the operation skip transition information included in the first skip service information, where the overlap section portion exists.
And a substep S1023, removing video playing service distribution with the strength of the interest point being smaller than a preset threshold value of the strength of the interest point in the first skipping service information to obtain second skipping service information, taking the video playing service distribution with the strength of the interest point not smaller than the preset threshold value of the strength of the interest point as first video playing service distribution to obtain a first video playing service distribution map, and determining a second video playing service distribution map which corresponds to each first video playing service distribution and is formed by video playing service distributions which are connected after the first video playing service distribution according to matching information of each first video playing service distribution in the second skipping service information in the first video playing service distribution map.
And a substep S1024 of judging whether the second video playing service distribution map is empty, if the second video playing service distribution map is empty, circularly returning, and if the second video playing service distribution map is not empty, counting the strength of the interest points of each video playing service distribution in the second video playing service distribution map, and judging whether the strength of the interest points of each video playing service distribution meets the minimum interest point strength condition.
And a substep S1025, if the strength of the interest point of the video playing service distribution does not meet the minimum interest point strength condition, circularly returning, if the strength of the interest point of the video playing service distribution meets the minimum interest point strength condition, splicing the video playing service distribution with the first video playing service distribution corresponding to the second video playing service distribution map to obtain a new first video playing service distribution, determining the second video playing service distribution map of the new first video playing service distribution, and performing circular identification on the second video playing service distribution map corresponding to the new first video playing service distribution to obtain all candidate first video playing service distributions meeting the minimum interest point strength condition and corresponding interest point strengths.
For example, the data returned in the loop is all candidate first video playing service distributions and corresponding interest point intensities which are currently obtained and meet the minimum interest point intensity condition, all candidate first video playing service distributions and corresponding interest point intensities which meet the minimum interest point intensity condition are obtained, the candidate first video playing service distributions are used as interest point features of the video operation object set, and the interest point intensities of the candidate first video playing service distributions in the second video playing service distribution map are used as interest weights corresponding to the interest point features.
In a possible implementation manner, for step S103, in order to accurately and comprehensively determine the interest point elements having the interest point tracing behavior, thereby improving the coverage and accuracy of interest point tracing crawling, and effectively determining the video playing tracing information of the advertisement schedule to which each advertisement operation element corresponds, the following exemplary sub-steps may be implemented. The detailed description is as follows.
And a substep S1031, screening the interest point features according to the interest point features and the corresponding interest weights to obtain target interest point features larger than preset interest weights.
In the substep S1032, a first video playing traceability object set corresponding to the first interest point service and a second video playing traceability object set corresponding to the second interest point service on the target interest point feature are obtained.
For example, the first video playing tracing object set includes a plurality of interest point tracing nodes for performing interest point tracing on a related interest track in the target interest point feature by the first interest point service, the second video playing tracing object set includes a plurality of interest point tracing nodes for performing interest point tracing on a related interest track in the target interest point feature by the second interest point service, and each interest point tracing node includes a plurality of tracing object coverage information.
And a substep S1033 of clustering a plurality of interest point tracing nodes in the first video playing tracing object set based on the preset interest point tracing node category to obtain a clustered first video playing tracing object set. The preset interest point tracing node type belongs to types corresponding to the plurality of tracing object coverage information.
And a substep S1034, combining the coverage information of each retroactive object corresponding to each preset interest point retroactive node type in the clustered first video playing retroactive object set into a first initial interest point retroactive node set.
And a substep S1035 of performing noise removal on the first initial interest point tracing node set to obtain a first interest point tracing node set, thereby obtaining a first interest point tracing node set corresponding to the preset interest point tracing node category set, and combining all tracing object coverage information in the first interest point tracing node set into a first tracing object coverage information set corresponding to the first interest point service.
For example, the first tracing object coverage information set corresponds to a preset interest point tracing node category set, and the preset interest point tracing node category type is a set formed by all interest point tracing node categories used for interest point tracing crawling.
In the substep S1036, from the second video playing traceability object set, each traceability object coverage information corresponding to each preset interest point traceability node category in the preset interest point traceability node category set is extracted and combined into a second traceability object coverage information set corresponding to the second interest point service.
For example, the second tracing object coverage information set corresponds to a preset interest point tracing node category set, and the first tracing object coverage information set and the second tracing object coverage information set are respectively sets composed of tracing object coverage information extracted from corresponding video playing tracing object sets.
And a substep S1037, determining a feature segment label of the same tracing object coverage information between the first tracing object coverage information set and the second tracing object coverage information set, obtaining a label service description vector from a label service interval corresponding to the feature segment label, and determining the first interest point service and the second interest point service as an interest point tracing unit when the label service description vector covers a preset description vector range.
And a substep S1038, using any two interest point elements in the target interest point feature as a first interest point service and a second interest point service to perform interest point tracing crawling, and obtaining a feature segment set with interest point tracing behaviors in the target interest point feature until the detection between the interest point elements in the target interest point feature is completed.
And a substep S1039, using the feature segment labels of the interest point elements in the feature segment set as candidate target labels, using the feature segment labels of the interest point elements corresponding to the target interest point features as candidate global labels, calculating label distribution of the candidate target labels and the candidate global labels, obtaining label distribution features corresponding to the target interest point features, and when the label distribution features meet a preset distribution trend, determining playing contents formed by the label distribution features corresponding to the target interest point features as video playing tracing information of the advertisement ranking corresponding to each advertisement operation element.
Based on the steps, when the interest point elements with the interest point tracing behavior trace back the interest points, the same tracing object coverage information exists between the corresponding interest point tracing nodes; therefore, when the interest point tracing crawling is performed, a video playing tracing object set formed by a plurality of interest point tracing nodes of the interest point elements is acquired, whether interest point tracing behaviors exist in the interest point elements is determined according to whether common attribute conditions exist between tracing object coverage information sets corresponding to operation sets among the interest point elements, and whether the interest point elements are interest point tracing units is determined.
In a possible implementation manner, further aiming at step S104, for example, in the process of determining candidate video interest objects corresponding to each advertisement schedule by using an artificial intelligence model according to the video playing tracing back information of the advertisement schedule to which each advertisement operation element corresponds, the following exemplary sub-steps can be implemented, which are described in detail below.
And a substep S1041 of obtaining corresponding advertisement material content and an initial content field of the advertisement material content from the video playing tracing information of the advertisement scheduling period to which each advertisement operation element corresponds.
And the substep S1042 is used for predicting the content of the advertisement material according to the pre-trained artificial intelligence model to obtain a predicted content field.
And a substep S1043 of comparing the initial content field with the predicted content field to obtain field association information.
And a substep S1044 of determining candidate video interest objects corresponding to each advertisement schedule by adopting an artificial intelligence model according to the field association information.
For example, candidate tracking thermalization items corresponding to each entry matching node may be obtained from the field association information, and each candidate tracking thermalization item is used as a candidate video interest object corresponding to each advertisement schedule determined by using an artificial intelligence model in a manner of clustering and arranging.
Fig. 3 is a schematic functional module diagram of an advertisement playing system 300 based on big data according to an embodiment of the present invention, and in this embodiment, functional modules of the advertisement playing system 300 based on big data may be divided according to a method embodiment executed by the advertisement service platform 100, that is, the following functional modules corresponding to the advertisement playing system 300 based on big data may be used to execute each method embodiment executed by the advertisement service platform 100. The big data based advertisement broadcasting system 300 may include a configuration adding module 310, a parsing module 320, an updating module 330, and an advertisement allocating module 340, and the functions of the functional modules of the big data based advertisement broadcasting system 300 are described in detail below.
The configuration adding module 310 is configured to obtain candidate video playing information, and perform advertisement stream configuration and advertisement carousel rule addition on the candidate video playing information to obtain a corresponding candidate advertisement stream configuration set, where the candidate video playing information is video playing information of a video interest element corresponding to big data operation data of the advertisement display device 200 in a preset time period. The configuration adding module 310 may be configured to perform the step S110, and as for a detailed implementation of the configuration adding module 310, reference may be made to the detailed description of the step S110.
The parsing module 320 is configured to parse the candidate advertisement stream configuration set to obtain an advertisement space display node set and corresponding advertisement carousel control information, and determine an advertisement space display node set of which the advertisement carousel control information meets a preset information stream display policy as a candidate advertisement display control. The parsing module 320 may be configured to perform the step S120, and the detailed implementation manner of the parsing module 320 may refer to the detailed description of the step S120.
And the updating module 330 is configured to traverse the candidate advertisement stream configuration set according to the candidate advertisement display control, circularly update the carousel content service of the advertisement carousel rule, add a carousel content queue to the candidate advertisement stream configuration set satisfying the candidate advertisement display control, and extract advertisement program features and corresponding delivery influence heat features in the candidate advertisement stream configuration set to which the carousel content queue is added. The updating module 330 may be configured to perform the step S130, and the detailed implementation of the updating module 330 may refer to the detailed description of the step S130.
And the advertisement distribution module 340 is configured to configure the preset advertisement control script according to the advertisement program characteristics, the delivery influence heat characteristics, and the carousel content queue to obtain the configured preset advertisement control script, and perform advertisement distribution of the corresponding advertisement control node for playing the video corresponding to the candidate video playing information to the candidate advertisement stream configuration set based on the configured preset advertisement control script. The advertisement distribution module 340 may be configured to perform the step S140, and the detailed implementation manner of the advertisement distribution module 340 may refer to the detailed description of the step S140.
It should be noted that the division of the modules of the above system is only a logical division, and the actual implementation may be wholly or partially integrated into one physical entity, or may be physically separated. And these modules can be realized in the form of software called by processing element; or may be implemented entirely in hardware; and part of the modules can be realized in the form of calling software by the processing element, and part of the modules can be realized in the form of hardware. For example, the configuration adding module 310 may be a separately established processing element, or may be implemented by being integrated into a chip of the system, or may be stored in a memory of the system in the form of program code, and a processing element of the system calls and executes the functions of the configuration adding module 310. Other modules are implemented similarly. In addition, all or part of the modules can be integrated together or can be independently realized. The processing element described herein may be an integrated circuit having signal processing capabilities. In implementation, each step of the above method or each module above may be implemented by an integrated logic circuit of hardware in a processor element or an instruction in the form of software.
For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more microprocessors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), among others. For another example, when some of the above modules are implemented in the form of a processing element scheduler code, the processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor that can call program code. As another example, these modules may be integrated together, implemented in the form of a system-on-a-chip (SOC).
Fig. 4 is a schematic diagram illustrating a hardware structure of the advertisement serving platform 100 for implementing the big data based advertisement playing method according to an embodiment of the present invention, and as shown in fig. 4, the advertisement serving platform 100 may include a processor 110, a machine-readable storage medium 120, a bus 130, and a transceiver 140.
In a specific implementation process, at least one processor 110 executes computer-executable instructions stored in the machine-readable storage medium 120 (for example, the configuration adding module 310, the parsing module 320, the updating module 330, and the advertisement allocating module 340 included in the big data based advertisement playing system 300 shown in fig. 3), so that the processor 110 may execute the big data based advertisement playing method according to the above method embodiment, where the processor 110, the machine-readable storage medium 120, and the transceiver 140 are connected through the bus 130, and the processor 110 may be configured to control transceiving actions of the transceiver 140, so as to perform data transceiving with the advertisement presentation device 200.
For a specific implementation process of the processor 110, reference may be made to the above-mentioned various method embodiments executed by the advertisement service platform 100, which implement principles and technical effects are similar, and this embodiment is not described herein again.
In the embodiment shown in fig. 4, it should be understood that the Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor, or in a combination of the hardware and software modules within the processor.
The machine-readable storage medium 120 may comprise high-speed RAM memory and may also include non-volatile storage NVM, such as at least one disk memory.
The bus 130 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus 130 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, the buses in the figures of the present invention are not limited to only one bus or one type of bus.
In addition, an embodiment of the present invention further provides a readable storage medium, where the readable storage medium stores computer execution instructions, and when a processor executes the computer execution instructions, the advertisement playing method based on big data is implemented.
Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be regarded as illustrative only and not as limiting the present specification. Various modifications, improvements and adaptations to the present description may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present specification and thus fall within the spirit and scope of the exemplary embodiments of the present specification.
Also, the description uses specific words to describe embodiments of the description. Such as "one possible implementation," "one possible example," and/or "exemplary" means that a particular feature, structure, or characteristic described in connection with at least one embodiment of the specification is included. Therefore, it is emphasized and should be appreciated that two or more references to "one possible implementation," "one possible example," and/or "exemplary" in various places throughout this specification are not necessarily referring to the same embodiment. Furthermore, some features, structures, or characteristics of one or more embodiments of the specification may be combined as appropriate.
Finally, it should be understood that the embodiments described herein are merely illustrative of the principles of the embodiments of the present disclosure. Other variations are also possible within the scope of the present description. Thus, by way of example, and not limitation, alternative configurations of the embodiments of the specification can be considered consistent with the teachings of the specification. Accordingly, the embodiments of the present description are not limited to only those embodiments explicitly described and depicted herein.

Claims (9)

1. An advertisement playing method based on big data is applied to an advertisement service platform, and the advertisement service platform is in communication connection with a plurality of advertisement display devices, and the method comprises the following steps:
acquiring candidate video playing information, and performing advertisement stream configuration and advertisement carousel rule addition on the candidate video playing information to obtain a corresponding candidate advertisement stream configuration set, wherein the candidate video playing information is video playing information of video interest elements corresponding to big data operation data of the advertisement display equipment in a preset time period;
analyzing the candidate advertisement stream configuration set to obtain an advertisement space display node set and corresponding advertisement carousel control information, and determining the advertisement space display node set of which the advertisement carousel control information meets a preset information stream display strategy as a candidate advertisement display control;
traversing the candidate advertisement stream configuration set according to the candidate advertisement display control, circularly updating the carousel content service of the advertisement carousel rule, adding a carousel content queue to the candidate advertisement stream configuration set meeting the candidate advertisement display control, and extracting advertisement program characteristics and corresponding delivery influence heat characteristics in the candidate advertisement stream configuration set to which the carousel content queue is added;
configuring a preset advertisement control script according to the advertisement program characteristics, the delivery influence heat characteristics and the carousel content queue to obtain a configured preset advertisement control script, and performing advertisement distribution of corresponding advertisement control nodes of the played video corresponding to the candidate video playing information on a candidate advertisement stream configuration set based on the configured preset advertisement control script;
the method comprises the following steps of configuring a preset advertisement control script according to the advertisement program characteristics, the delivery influence heat characteristics and the carousel content queue to obtain a configured preset advertisement control script, and performing advertisement distribution of corresponding advertisement control nodes of the played videos corresponding to the candidate video playing information on a candidate advertisement stream configuration set based on the configured preset advertisement control script, wherein the steps comprise:
inputting advertisement program characteristics, delivery influence heat characteristics and a carousel content queue into a preset advertisement control script for configuration to obtain a corresponding information carousel content queue set, comparing the information carousel content queue set with the carousel content queue set, continuously updating script configuration content of the preset advertisement control script according to comparison difference to obtain a configured preset advertisement control script, obtaining a corresponding candidate carousel content queue from a candidate advertisement stream configuration set based on the configured preset advertisement control script, and performing advertisement distribution of corresponding advertisement control nodes for playing videos corresponding to the candidate video playing information based on push source content related to the candidate carousel content queue;
wherein, the step of traversing the candidate advertisement stream configuration set according to the candidate advertisement display control and circularly updating the carousel content service of the advertisement carousel rule comprises the following steps:
determining an advertisement putting strategy information set matched with the advertisement space display node set of the candidate advertisement display control in the candidate advertisement flow configuration set;
acquiring second candidate carousel control information of the advertisement carousel rules and global carousel control information of the advertisement carousel rules, which are contained in each advertisement putting strategy information set, and determining corresponding second advertisement carousel control information according to the inclusion relation between the second candidate carousel control information and the global carousel control information;
determining an advertisement putting strategy information set of which the second advertisement carousel control information covers a preset putting subscription range as a candidate advertisement putting strategy information set, performing advertisement carousel rule mapping on advertisement putting strategy information in the candidate advertisement putting strategy information set according to the candidate advertisement display control, and updating a carousel content service of the advertisement carousel rule;
and re-executing the step of obtaining second candidate carousel control information of the advertisement carousel rules and global carousel control information of the advertisement carousel rules contained in each advertisement putting strategy information set, iteratively mapping the advertisement carousel rules on the advertisement putting strategy information in the candidate advertisement putting strategy information set, and updating the carousel content service of the advertisement carousel rules until the iteration times meet a preset iteration threshold.
2. The big data-based advertisement playing method according to claim 1, wherein the step of parsing the candidate advertisement stream configuration set to obtain an advertisement space display node set and corresponding advertisement carousel control information, and determining an advertisement space display node set of which the advertisement carousel control information satisfies a preset information stream display policy as a candidate advertisement display control comprises:
analyzing the candidate advertisement stream configuration set to obtain a corresponding advertisement space display node set;
acquiring first candidate carousel control information of an advertisement carousel rule and global carousel control information of the advertisement carousel rule contained in each advertisement space display node set;
determining corresponding first advertisement carousel control information according to the inclusion relation between the first candidate carousel control information and the global carousel control information;
and determining the advertisement space display node set of which the first advertisement carousel control information matches a preset carousel subscription rule as a candidate advertisement display control.
3. The big data based advertisement playing method according to claim 1, wherein the step of performing advertisement stream configuration and advertisement carousel rule addition on the candidate video playing information to obtain a corresponding candidate advertisement stream configuration set comprises:
performing advertisement stream configuration operation on the candidate video playing information to obtain a corresponding advertisement stream configuration set;
acquiring a carousel content service of an advertisement carousel rule, and determining the carousel content service in the advertisement stream configuration set;
and mapping corresponding advertisement carousel rules for the carousel content service in the advertisement stream configuration set to obtain a corresponding candidate advertisement stream configuration set.
4. The big data-based advertisement playing method according to claim 1, wherein the step of performing advertisement carousel rule mapping on the advertisement putting strategy information in the candidate advertisement putting strategy information set according to the candidate advertisement display control and updating a carousel content service of advertisement carousel rules comprises:
acquiring a mapping rule for performing advertisement carousel rule mapping on each advertisement display control node in the candidate advertisement display control;
and performing advertisement carousel rule mapping on the advertisement putting strategy information in the candidate advertisement putting strategy information set according to the mapping rule and an advertisement display control node, and updating the carousel content service of the advertisement carousel rule.
5. The big data based advertisement playing method according to any one of claims 1 to 3, wherein the step of extracting the advertisement program features and the corresponding advertisement impact heat features in the candidate advertisement stream configuration set of the adding carousel content queue comprises:
determining the advertisement program characteristics of the candidate advertisement stream configuration set of the added carousel content queue, wherein the advertisement program characteristics are the characteristic information of the advertisement stream content corresponding to each advertisement stream label in the candidate advertisement stream configuration set of the added carousel content queue;
calculating the release influence heat characteristic of a candidate advertisement flow configuration set added with a carousel content queue;
the step of calculating the impression influence heat characteristics of the candidate advertisement flow configuration set for adding the carousel content queue includes:
acquiring historical distribution frequency of candidate advertisement putting strategy information in a candidate advertisement flow configuration set added with a carousel content queue, and acquiring the number of total carousel content queues appearing in the candidate video playing information;
determining corresponding content hotspot information according to the inclusion relation between the historical distribution frequency of the candidate advertisement putting strategy information and the number of the total carousel content queues;
acquiring the global content hotspot number in the candidate video playing information and acquiring the candidate content hotspot number containing the candidate advertisement putting strategy information;
calculating hot content information corresponding to the same hot spot number of the global content hot spot number and the candidate content hot spot number, and calculating hot word frequency characteristics of the hot content information corresponding to the same hot spot number to obtain a corresponding hot word frequency characteristic result;
and fusing the content hotspot information with hotspot word frequency feature results to obtain influence factors of the candidate advertisement delivery strategy information, and combining the influence factors corresponding to the advertisement delivery strategy information in the same candidate advertisement stream configuration set to generate delivery influence heat features.
6. The big data based advertisement broadcasting method according to claim 1, wherein the video broadcasting information of the video interest element is obtained by the following steps:
acquiring at least one video operation object set from big data operation data of the advertisement display equipment in a preset time period, wherein each advertisement operation element in each video operation object set belongs to the same advertisement scheduling, and each advertisement operation element corresponds to an operation jump page under the advertisement scheduling;
identifying interest points of the video operation object sets on the basis of the operation jump pages under the advertising schedule to obtain the interest point characteristics and the corresponding interest weights of the video operation object sets;
according to the interest point characteristics and the corresponding interest weights, video playing tracing information of the advertisement scheduling period corresponding to each advertisement operation element is determined;
and determining candidate video interest objects corresponding to each advertisement scheduling period by adopting an artificial intelligence model according to the video playing tracing information of the advertisement scheduling period corresponding to each advertisement operation element, generating strategy configuration information of a video playing strategy corresponding to the big data operation data according to the candidate video interest objects corresponding to each advertisement scheduling period, and pushing the video playing information of the corresponding video interest elements to the advertisement display equipment according to the strategy configuration information of the video playing strategy.
7. The advertisement playing method based on big data as claimed in claim 6, wherein the step of determining the video playing tracing information of the advertisement scheduling period to which each advertisement operation element corresponds according to the interest point feature and the corresponding interest weight comprises:
screening the interest point characteristics according to the interest point characteristics and the corresponding interest weights to obtain target interest point characteristics larger than preset interest weights;
acquiring a first video playing tracing object set corresponding to a first interest point service and a second video playing tracing object set corresponding to a second interest point service on a target interest point feature, wherein the first video playing tracing object set comprises a plurality of interest point tracing nodes for interest point tracing of a related interest track in the target interest point feature by the first interest point service, the second video playing tracing object set comprises a plurality of interest point tracing nodes for interest point tracing of a related interest track in the target interest point feature by the second interest point service, and each interest point tracing node comprises a plurality of tracing object coverage information;
clustering a plurality of interest point tracing nodes in the first video playing tracing object set based on a preset interest point tracing node category to obtain a clustered first video playing tracing object set; the preset interest point tracing node type belongs to types corresponding to the plurality of tracing object coverage information;
combining the coverage information of each retroactive object corresponding to each preset interest point retroactive node category in the clustered first video playing retroactive object set into a first initial interest point retroactive node set;
noise removal is carried out on the first initial interest point tracing node set to obtain a first interest point tracing node set, and therefore a first interest point tracing node set corresponding to the preset interest point tracing node category set is obtained;
combining all tracing object coverage information in the first interest point tracing node set into a first tracing object coverage information set corresponding to the first interest point service, wherein the first tracing object coverage information set corresponds to a preset interest point tracing node type set, and the preset interest point tracing node type is a set formed by all interest point tracing node types used for interest point tracing;
extracting, from the second video playing tracing object set, each tracing object coverage information corresponding to each preset interest point tracing node category in the preset interest point tracing node category set, and combining the tracing object coverage information into a second tracing object coverage information set corresponding to the second interest point service, where the second tracing object coverage information set corresponds to the preset interest point tracing node category set, and the first tracing object coverage information set and the second tracing object coverage information set are sets composed of tracing object coverage information extracted from the corresponding video playing tracing object sets, respectively;
determining a characteristic segment label of the same tracing object covering information between the first tracing object covering information set and the second tracing object covering information set, and obtaining a label service description vector from a label service interval corresponding to the characteristic segment label;
when the label service description vector covers a preset description vector range, determining the first interest point service and the second interest point service as interest point tracing units;
using any two interest point elements in the target interest point feature as a first interest point service and a second interest point service to perform interest point tracing crawling, and obtaining a feature segment set with interest point tracing behaviors in the target interest point feature until the detection of the interest point elements in the target interest point feature is completed;
taking the feature segment labels of the interest point elements in the feature segment set as candidate target labels;
taking the feature segment labels of the interest point elements corresponding to the target interest point features as candidate global labels;
calculating the label distribution of the candidate target label and the candidate global label to obtain a label distribution characteristic corresponding to the target interest point characteristic;
and when the label distribution characteristics meet a preset distribution trend, determining the playing content formed by the label distribution characteristics corresponding to the target interest point characteristics as video playing tracing information of the advertisement schedule corresponding to each advertisement operation element.
8. An advertisement playing system based on big data is characterized in that the advertisement playing system is applied to an advertisement service platform, the advertisement service platform is in communication connection with a plurality of advertisement display devices, and the system comprises:
the configuration adding module is used for acquiring candidate video playing information, and performing advertisement stream configuration and advertisement carousel rule addition on the candidate video playing information to obtain a corresponding candidate advertisement stream configuration set, wherein the candidate video playing information is video playing information of video interest elements corresponding to big data operation data of the advertisement display equipment in a preset time period;
the analysis module is used for analyzing the candidate advertisement stream configuration set to obtain an advertisement space display node set and corresponding advertisement carousel control information, and determining the advertisement space display node set of which the advertisement carousel control information meets a preset information stream display strategy as a candidate advertisement display control;
the updating module is used for traversing the candidate advertisement flow configuration set according to the candidate advertisement display control, circularly updating the carousel content service of the advertisement carousel rule, adding a carousel content queue to the candidate advertisement flow configuration set meeting the candidate advertisement display control, and extracting advertisement program characteristics and corresponding delivery influence heat characteristics in the candidate advertisement flow configuration set added with the carousel content queue;
the advertisement distribution module is used for configuring a preset advertisement control script according to the advertisement program characteristics, the delivery influence heat characteristics and the carousel content queue to obtain a configured preset advertisement control script, and performing advertisement distribution of corresponding advertisement control nodes of the played videos corresponding to the candidate video playing information on a candidate advertisement stream configuration set based on the configured preset advertisement control script;
the method for configuring the preset advertisement control script according to the advertisement program characteristics, the delivery influence heat characteristics and the carousel content queue to obtain the configured preset advertisement control script, and performing advertisement distribution of corresponding advertisement control nodes of the played video corresponding to the candidate video playing information on the candidate advertisement stream configuration set based on the configured preset advertisement control script comprises the following steps:
inputting advertisement program characteristics, delivery influence heat characteristics and a carousel content queue into a preset advertisement control script for configuration to obtain a corresponding information carousel content queue set, comparing the information carousel content queue set with the carousel content queue set, continuously updating script configuration content of the preset advertisement control script according to comparison difference to obtain a configured preset advertisement control script, obtaining a corresponding candidate carousel content queue from a candidate advertisement stream configuration set based on the configured preset advertisement control script, and performing advertisement distribution of corresponding advertisement control nodes for playing videos corresponding to the candidate video playing information based on push source content related to the candidate carousel content queue;
the method for traversing the candidate advertisement stream configuration set according to the candidate advertisement display control and circularly updating the carousel content service of the advertisement carousel rule comprises the following steps:
determining an advertisement putting strategy information set matched with the advertisement space display node set of the candidate advertisement display control in the candidate advertisement flow configuration set;
acquiring second candidate carousel control information of the advertisement carousel rules and global carousel control information of the advertisement carousel rules, which are contained in each advertisement putting strategy information set, and determining corresponding second advertisement carousel control information according to the inclusion relation between the second candidate carousel control information and the global carousel control information;
determining an advertisement putting strategy information set of which the second advertisement carousel control information covers a preset putting subscription range as a candidate advertisement putting strategy information set, performing advertisement carousel rule mapping on advertisement putting strategy information in the candidate advertisement putting strategy information set according to the candidate advertisement display control, and updating a carousel content service of the advertisement carousel rule;
and re-executing the step of obtaining second candidate carousel control information of the advertisement carousel rules and global carousel control information of the advertisement carousel rules contained in each advertisement putting strategy information set, iteratively mapping the advertisement carousel rules on the advertisement putting strategy information in the candidate advertisement putting strategy information set, and updating the carousel content service of the advertisement carousel rules until the iteration times meet a preset iteration threshold.
9. An advertisement service platform, comprising a processor, a machine-readable storage medium, and a network interface, wherein the machine-readable storage medium, the network interface, and the processor are connected via a bus system, the network interface is configured to be communicatively connected to at least one advertisement presentation device, the machine-readable storage medium is configured to store a program, instructions, or codes, and the processor is configured to execute the program, instructions, or codes in the machine-readable storage medium to perform the big data based advertisement playing method according to any one of claims 1 to 7.
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