CN114639051A - Advertisement short video quality evaluation method and system based on big data analysis and storage medium - Google Patents
Advertisement short video quality evaluation method and system based on big data analysis and storage medium Download PDFInfo
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
- G06F40/284—Lexical analysis, e.g. tokenisation or collocates
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/44—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream, rendering scenes according to MPEG-4 scene graphs
- H04N21/44008—Processing of video elementary streams, e.g. splicing a video clip retrieved from local storage with an incoming video stream, rendering scenes according to MPEG-4 scene graphs involving operations for analysing video streams, e.g. detecting features or characteristics in the video stream
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/80—Generation or processing of content or additional data by content creator independently of the distribution process; Content per se
- H04N21/81—Monomedia components thereof
- H04N21/812—Monomedia components thereof involving advertisement data
Abstract
The invention discloses a method, a system and a storage medium for evaluating the quality of advertisement short videos based on big data analysis, wherein the method analyzes the coefficient conforming to the theme of the title information of the title video in each advertisement short video to be evaluated according to the title information of the title video in each advertisement short video to be evaluated, simultaneously acquiring related parameters and video time points of each video frame image in each advertisement short video to be evaluated, analyzing video content playing influence coefficients of each advertisement short video to be evaluated, and the comprehensive production quality coefficient of each advertisement short video to be evaluated is obtained by evaluation according to the matching number of the video frame images in each advertisement short video to be evaluated, and corresponding processing is carried out after comparison and analysis, so that comprehensive evaluation is realized according to the multidimensional quality influence factors of the advertisement short video, the problem that the conventional method has certain limitation is broken, and the reliability and accuracy of the advertisement short video production quality evaluation result are effectively guaranteed.
Description
Technical Field
The invention relates to the technical field of advertisement short video quality evaluation, in particular to an advertisement short video quality evaluation method and system based on big data analysis and a storage medium.
Background
The advertisement is an important way for popularizing company products and improving brand awareness. Due to the popularity of media such as television, network and the like, the advertisement short video audience is very wide, and the advertisement short video audience is an important advertisement form. In the current society, commercial competition is increasingly intense, and enterprises urgently need to know the production quality and the putting effect of advertisement short videos.
At present, the existing method for evaluating the production quality of the advertisement short video mainly considers the conformity of the whole content of the advertisement short video and the planned theme, and does not consider the theme conformity of the head video in the advertisement short video, so that the problem of insufficient expressive force of the head video theme in the advertisement short video exists, the content which is interested by a user cannot be quickly embodied, the user cannot be attracted to continuously watch the advertisement short video, the conflict psychology of the user on the advertisement short video is enhanced to a great extent, the watching experience and satisfaction of the user are reduced, and the whole production quality of the advertisement short video is further influenced.
The existing advertisement short video production quality evaluation method mainly focuses on evaluating the planning theme conformity of advertisement short videos, and cannot realize comprehensive evaluation according to multi-dimensional quality influence factors of the advertisement short videos, so that the existing method has certain limitation, cannot effectively guarantee the reliability and accuracy of advertisement short video production quality evaluation results, further influences the expected delivery effect of the advertisement short videos at the later stage, and further influences the advertisement short video production economic cost, the delivery economic cost and the time cost of enterprises.
In order to solve the above problems, a method, a system and a storage medium for evaluating the quality of advertisement short videos based on big data analysis are designed.
Disclosure of Invention
The invention aims to provide a method, a system and a storage medium for evaluating the quality of advertisement short videos based on big data analysis, which solve the problems in the background technology.
The technical scheme adopted by the invention for solving the technical problems is as follows:
in a first aspect, the invention provides a method for evaluating quality of an advertisement short video based on big data analysis, which comprises the following steps:
s1, acquiring the short advertisement video titles: acquiring a leader video in each short video to be evaluated according to the playing time length of each short video to be evaluated;
s2, comparing and analyzing title information of the titles: extracting the head video speech information in each short video of the advertisement to be evaluated, comparing the head video speech information with preset planning topic information of each short video of the advertisement to be evaluated, and analyzing a coefficient which is in line with the topic information of the head video speech information in each short video of the advertisement to be evaluated;
s3, video frame image related parameter processing: dividing each short video of the advertisement to be evaluated into each video frame image, acquiring relevant parameters of each video frame image in each short video of the advertisement to be evaluated, and processing to obtain a parameter influence weight index of each video frame image in each short video of the advertisement to be evaluated;
s4, video frame image clipping fluency analysis: acquiring video time points corresponding to video frame images in the advertisement short videos to be evaluated, and comparing and analyzing the clipping fluency weight indexes of the video frame images in the advertisement short videos to be evaluated;
s5, analyzing the video content playing influence coefficient: analyzing a video content playing influence coefficient of each advertisement short video to be evaluated according to the parameter influence weight index and the clipping fluency weight index of each video frame image in each advertisement short video to be evaluated;
s6, video frame image contrast processing: extracting preset product display images corresponding to the advertisement short videos to be evaluated, comparing and screening the video frame image matching quantity in the advertisement short videos to be evaluated, and analyzing the product display image matching quantity of the advertisement short videos to be evaluated;
s7, evaluating the production quality of the advertisement short video: and evaluating the comprehensive production quality coefficient of each advertisement short video to be evaluated, comparing the comprehensive production quality coefficient with a preset advertisement short video production quality coefficient threshold value, and performing corresponding processing according to the comparison result.
Further, the detailed steps in step S1 are as follows:
numbering each short advertisement video to be evaluated in sequence according to a production time sequence, wherein the number of each short advertisement video to be evaluated is 1,2,. once, i,. once, n;
acquiring the playing time of each short video of the advertisement to be evaluated, and analyzing the leader time of each short video of the advertisement to be evaluated based on the preset leader time ratio of the short video of the advertisement;
according to the leader duration of each short video of the advertisement to be evaluated, the leader video of each short video of the advertisement to be evaluated is obtained, and the leader video of each short video of the advertisement to be evaluated is marked as aiI is 1,2, and n, i is represented as the ith advertisement short video to be evaluated.
Further, in the step S2, the analysis of the coefficient of matching topic of the title video speech information in each advertisement short video to be evaluated includes the specific analysis steps:
extracting the lines information of the head videos in the short videos of the advertisements to be evaluated, extracting the preset planning subject information of the short videos of the advertisements to be evaluated in the advertisement short video planning database, comparing the lines information of the head videos in the short videos of the advertisements to be evaluated with the preset planning subject information of the short videos corresponding to the advertisements to be evaluated to obtain the conformity between the lines information of the head videos in the short videos of the advertisements to be evaluated and the preset planning subject information, and marking the conformity between the lines information of the head videos in the short videos of the advertisements to be evaluated and the preset planning subject information as theta alphai；
Coefficient according with theme for analyzing head video speech information in each short video to be evaluated
Wherein muθExpressed as an index of influence, θ, corresponding to a predetermined conformityStandard of meritThe preset short video line information and the standard conformity threshold value of the planned subject information are expressed.
Further, the corresponding detailed step in step S3 includes:
dividing each short video of the advertisement to be evaluated into each video in turn according to the video playing sequenceFrame images, obtaining relevant parameters of each video frame image in each advertisement short video to be evaluated, wherein the relevant parameters comprise resolution, frame rate, pixels and definition, and respectively marking the resolution, the frame rate, the pixels and the definition of each video frame image in each advertisement short video to be evaluated as w1bij、w2bij、w3bij、w4bijJ is 1,2, and m, j is represented as the jth video frame image;
analyzing parameter influence weight index of each video frame image in each advertisement short video to be evaluated
Wherein λ is1、λ2、λ3、λ4Respectively expressed as weight influence factors corresponding to preset image resolution, image frame rate, image pixel and image definition, and lambda1+λ2+λ3+λ4＝1，w1bSign、w2bSign board、w3bSign board、w4bSignRespectively representing the standard resolution, the standard frame rate, the standard pixel and the standard definition corresponding to the preset video frame image.
Further, in the step S4, the clipping fluency weighting index of each video frame image in each advertisement short video to be evaluated is analyzed by comparison, and the specific analysis manner is as follows:
acquiring video time points corresponding to the video frame images in the advertisement short videos to be evaluated, and marking the video time points corresponding to the video frame images in the advertisement short videos to be evaluated as tibj；
Substituting the video time points corresponding to the video frame images in the short videos of the advertisements to be evaluated into a formula
Obtaining the clipping fluency weight index of each video frame image in each advertisement short video to be evaluated
η1、η2Respectively expressed as preset clip fluency impact factors, tibj+1Is represented as the video time point, t, corresponding to the j +1 video frame image in the ith advertisement short video to be evaluatedibj-1Is expressed as the video time point, delta t, corresponding to the j-1 video frame image in the ith advertisement short video to be evaluatedAllow forExpressed as allowed time point error values between preset video frame images.
Further, the corresponding detailed step in step S5 includes:
the parameter influence weight index epsilon b 'of each video frame image in each advertisement short video to be evaluated'ijAnd the clipping fluency weight index of each video frame image in each short video to be evaluated
Substitution formula
Obtaining the video content playing influence coefficient xi of each advertisement short video to be evaluated2aiWhere m is expressed as the number of divided video frame images, β1、β2Respectively expressed as preset video content playing influence factors, and beta1+β2＝1。
Further, in the step S6, the product display image matching coefficients of each advertisement short video to be evaluated are analyzed in a specific analysis manner:
comparing each video frame image in each advertisement short video to be evaluated with a preset product display image corresponding to the corresponding advertisement short video to be evaluated, if the preset product display image corresponding to the advertisement short video to be evaluated appears in a certain video frame image in a certain advertisement short video to be evaluated, matching the video frame image in the advertisement short video to be evaluated with the corresponding preset product display image, counting the matching number of the video frame images in the advertisement short video to be evaluated, and marking the matching number of the video frame images in the advertisement short video to be evaluated as zai；
Analysis of each to be assessedProduct display image matching coefficients for short videos of price advertisements
Wherein δ is expressed as a preset product display image matching impact factor, zPreset ofExpressed as a preset video frame image matching number threshold, and e is expressed as a constant.
Further, the step S7 of evaluating the comprehensive production quality coefficient of each advertisement short video to be evaluated includes:
matching topic coefficient xi of head video speech information in each short video to be evaluated1aiAnd the video content playing influence coefficient xi of each advertisement short video to be evaluated2aiMatching coefficient xi of product display images of short videos of advertisements to be evaluated3aiSubstituting into the advertisement short video production quality evaluation formula psii＝γ1*ξ1ai+γ2*ξ2ai+γ3*ξ3aiTo obtain the comprehensive production quality coefficient psi of each advertisement short video to be evaluatediWherein γ is1、γ2、γ3Respectively expressed as preset advertisement short video production quality influence factors, and gamma1+γ2+γ3＝1。
In a second aspect, the present invention further provides a short video analysis processing system, including:
an advertisement short video head video acquisition module: the system comprises a video acquisition module, a video display module and a video display module, wherein the video acquisition module is used for acquiring a leader video in each short video to be evaluated according to the playing time length of each short video to be evaluated;
the film head video speech information comparison analysis module: the system comprises a video processing module, a theme analysis module and a theme analysis module, wherein the video processing module is used for extracting the title video speech information in each short video to be evaluated, comparing the title video speech information with the preset planned theme information of each short video to be evaluated, and analyzing the coefficient of the title video speech information in each short video to be evaluated, which accords with the theme;
advertisement short video planning database: the system comprises a storage module, a processing module and a display module, wherein the storage module is used for storing preset planning theme information and preset product display images of short videos of advertisements to be evaluated;
the video frame image related parameter processing module: the system comprises a video processing unit, a parameter influence weight index processing unit and a parameter evaluation unit, wherein the video processing unit is used for dividing each advertisement short video to be evaluated into each video frame image, acquiring relevant parameters of each video frame image in each advertisement short video to be evaluated, and processing to obtain the parameter influence weight index of each video frame image in each advertisement short video to be evaluated;
video frame image clipping fluency analysis module: the video time point corresponding to each video frame image in each advertisement short video to be evaluated is obtained, and the clipping fluency weighting index of each video frame image in each advertisement short video to be evaluated is contrasted and analyzed;
the video content playing influence coefficient analysis module: the video content playing influence coefficient analysis module is used for analyzing the video content playing influence coefficient of each advertisement short video to be evaluated according to the parameter influence weight index and the clipping fluency weight index of each video frame image in each advertisement short video to be evaluated;
the video frame image contrast processing module: the system is used for extracting preset product display images corresponding to the advertisement short videos to be evaluated, comparing and screening the matching number of video frame images in the advertisement short videos to be evaluated, and analyzing the matching number of the product display images of the advertisement short videos to be evaluated;
the advertisement short video production quality evaluation module: and the comprehensive production quality coefficient is used for evaluating the comprehensive production quality coefficient of each advertisement short video to be evaluated, comparing the comprehensive production quality coefficient with a preset advertisement short video production quality coefficient threshold value, and carrying out corresponding processing according to the comparison result.
In a third aspect, the present invention further provides a storage medium, where a computer program is burned in the storage medium, and when the computer program runs in a memory of a server, the advertisement short video quality evaluation method based on big data analysis according to the present invention is implemented.
Compared with the prior art, the advertisement short video quality evaluation method, the advertisement short video quality evaluation system and the storage medium based on big data analysis have the following beneficial effects:
according to the advertisement short video quality evaluation method, the advertisement short video quality evaluation system and the storage medium based on big data analysis, the head video in each advertisement short video to be evaluated is obtained, the coefficient of the consistent theme of the head video speech information in each advertisement short video to be evaluated is analyzed according to the head video speech information in each advertisement short video to be evaluated, so that the problem of insufficient expression of the head video theme in the advertisement short video is effectively avoided, the content which the user is interested in can be quickly embodied, the user is further attracted to continuously watch the advertisement short video, the conflict psychology of the user on the advertisement short video is further eliminated, the watching experience and satisfaction of the user are improved, and the overall production quality of the advertisement short video is guaranteed to the greatest extent.
According to the advertisement short video quality evaluation method, system and storage medium based on big data analysis, relevant parameters and video time points of video frame images in each advertisement short video to be evaluated are obtained, the video content playing influence coefficient of each advertisement short video to be evaluated is analyzed, the comprehensive production quality coefficient of each advertisement short video to be evaluated is obtained through evaluation by combining the matching number of the video frame images in each advertisement short video to be evaluated, and corresponding processing is carried out after comparison and analysis, so that comprehensive evaluation according to the multidimensional quality influence factors of the advertisement short videos is realized, the problem that the existing method has certain limitation is broken, the reliability and accuracy of the advertisement short video production quality evaluation result are effectively guaranteed, the expected delivery effect of the advertisement short videos at the later stage is guaranteed, and meanwhile, the economic cost for producing the advertisement short videos of enterprises can be avoided to a certain extent, Economic cost of delivery and time cost loss.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow diagram of the process of the present invention;
fig. 2 is a system module connection diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, a first aspect of the present invention provides a short video analysis processing method, including the following steps:
s1, acquiring the advertisement short video leader video: and acquiring the leader video in each short video to be evaluated according to the playing time length of each short video to be evaluated.
In this embodiment, the detailed specific steps in step S1 are as follows:
numbering each short advertisement video to be evaluated in sequence according to a production time sequence, wherein the number of each short advertisement video to be evaluated is 1,2,. once, i,. once, n;
acquiring the playing time of each short video of the advertisement to be evaluated, and analyzing the leader time of each short video of the advertisement to be evaluated based on the preset leader time ratio of the short video of the advertisement;
according to the leader duration of each short video of the advertisement to be evaluated, the leader video of each short video of the advertisement to be evaluated is obtained, and the leader video of each short video of the advertisement to be evaluated is marked as aiI is 1,2, and n, i is represented as the ith advertisement short video to be evaluated.
In a possible design, the above analysis formula of the leader duration of each short video of the advertisement to be evaluated is Ti′＝kPreparation of*Ti，Ti' bit length, k, of the ith advertisement short video to be evaluatedPreparation ofExpressed as the ratio of the preset advertisement short video title duration to the preset advertisement short video title duration, TiAnd the display time is represented as the playing time of the ith advertisement short video to be evaluated.
S2, comparing and analyzing title information of the film leader video: and extracting the head video speech information in each short video of the advertisement to be evaluated, comparing the head video speech information with preset planning topic information of each short video of the advertisement to be evaluated, and analyzing a coefficient which is in accordance with the topic of the head video speech information in each short video of the advertisement to be evaluated.
In this embodiment, in the step S2, the analyzing step includes the following specific steps:
extracting the lines information of the head videos in the short videos of the advertisements to be evaluated, extracting the preset planning subject information of the short videos of the advertisements to be evaluated in the advertisement short video planning database, comparing the lines information of the head videos in the short videos of the advertisements to be evaluated with the preset planning subject information of the short videos corresponding to the advertisements to be evaluated to obtain the conformity between the lines information of the head videos in the short videos of the advertisements to be evaluated and the preset planning subject information, and marking the conformity between the lines information of the head videos in the short videos of the advertisements to be evaluated and the preset planning subject information as theta alphai；
Coefficient according with theme for analyzing head video speech information in each short video to be evaluated
Wherein muθExpressed as an index of influence, θ, corresponding to a predetermined conformityStandard of meritThe standard conformity threshold value of the preset short video speech information and the planned subject information is expressed.
In a possible design, the above-mentioned obtaining of the conformity between the speech information of the leader video in each advertisement short video to be evaluated and the corresponding preset planning topic information includes the following specific obtaining modes:
performing word segmentation processing on the speech information of the head video in each advertisement short video to be evaluated to obtain each effective word in the speech information of the head video in each advertisement short video to be evaluated;
comparing each effective word in the first video speech information of each advertisement short video to be evaluated with each preset effective word in the preset planning subject information of the corresponding advertisement short video to be evaluated, counting the matching number of the first video speech information of each advertisement short video to be evaluated and the effective words of the corresponding preset planning subject information, and comparing each advertisement short video to be evaluatedThe matching number of the effective words of the video lines information of the middle film head and the corresponding preset planning subject information is marked as xi；
Keyword extraction is carried out on the speech information of the head video in each short video of the advertisement to be evaluated, and each keyword in the speech information of the head video in each short video of the advertisement to be evaluated is obtained;
extracting all near-meaning keywords corresponding to the keywords in the preset planning subject information of each short video to be evaluated in the advertisement short video planning database, comparing all the keywords in the first video station word information of each short video to be evaluated with all the near-meaning keywords in the preset planning subject information of the corresponding short video to be evaluated, counting the matching number of the first video station word information in each short video to be evaluated and the near-meaning keywords corresponding to the preset planning subject information, and marking the matching number of the first video station word information in each short video to be evaluated and the near-meaning keywords corresponding to the preset planning subject information as yi；
Analyzing the conformity of the speech information of the leader video in each short video of the advertisement to be evaluated and the corresponding preset planning subject information
Wherein alpha is1、α2Respectively expressed as a predetermined conformity factor, xPreparation ofThe number of valid word matches, y, expressed as preset short video line information and planned topic informationPreparation ofThe matching number of the near meaning keywords is expressed as the preset short video speech information and the planned subject information.
It should be noted that, in the invention, by acquiring the leader video in each short video to be evaluated, and analyzing the coefficient of topic conformity of the leader video speech information in each short video to be evaluated according to the leader video speech information in each short video to be evaluated, the problem of insufficient expressive force of the leader video topic in the short video to be evaluated is effectively avoided, the content which the user is interested in can be quickly expressed, the user is further attracted to continuously watch the short video, the conflict psychology of the user on the short video to be evaluated is further eliminated, the watching experience and satisfaction of the user are improved, and the overall production quality of the short video to be evaluated is greatly ensured.
S3, video frame image related parameter processing: dividing each short video of the advertisement to be evaluated into each video frame image, obtaining relevant parameters of each video frame image in each short video of the advertisement to be evaluated, and processing to obtain parameter influence weight indexes of each video frame image in each short video of the advertisement to be evaluated.
In this embodiment, the specific detailed step in step S3 includes:
dividing each advertisement short video to be evaluated into each video frame image in sequence according to the video playing sequence, obtaining relevant parameters of each video frame image in each advertisement short video to be evaluated, wherein the relevant parameters comprise resolution, frame rate, pixels and definition, and respectively marking the resolution, the frame rate, the pixels and the definition of each video frame image in each advertisement short video to be evaluated as w1bij、w2bij、w3bij、w4bijJ is 1,2, and m, j is represented as the jth video frame image;
analyzing parameter influence weight index of each video frame image in each advertisement short video to be evaluated
Wherein λ is1、λ2、λ3、λ4Respectively expressed as weight influence factors corresponding to preset image resolution, image frame rate, image pixel and image definition, and lambda1+λ2+λ3+λ4＝1，w1bSign board、w2bSign board、w3bSign、w4bSign boardRespectively representing the standard resolution, the standard frame rate, the standard pixel and the standard definition corresponding to the preset video frame image.
S4, video frame image clipping fluency analysis: and acquiring video time points corresponding to the video frame images in the advertisement short videos to be evaluated, and comparing and analyzing the clipping fluency weight indexes of the video frame images in the advertisement short videos to be evaluated.
In this embodiment, in the step S4, the clipping fluency weighting index of each video frame image in each advertisement short video to be evaluated is analyzed by comparison, and the specific analysis manner is as follows:
acquiring video time points corresponding to video frame images in each short video of the advertisement to be evaluated, and marking the video time points corresponding to the video frame images in each short video of the advertisement to be evaluated as tibj；
Substituting the video time points corresponding to the video frame images in the short videos of the advertisements to be evaluated into a formula
Obtaining the clipping fluency weight index of each video frame image in each advertisement short video to be evaluated
η1、η2Respectively expressed as preset clip fluency impact factors, tibj+1Is represented as the video time point, t, corresponding to the j +1 video frame image in the ith advertisement short video to be evaluatedibj-1Is expressed as the video time point, delta t, corresponding to the j-1 video frame image in the ith advertisement short video to be evaluatedAllow forExpressed as allowed time point error values between preset video frame images.
S5, analyzing the video content playing influence coefficient: and analyzing the video content playing influence coefficient of each advertisement short video to be evaluated according to the parameter influence weight index and the clipping fluency weight index of each video frame image in each advertisement short video to be evaluated.
In this embodiment, the specific detailed step in step S5 includes:
the parameter influence weight index epsilon b 'of each video frame image in each advertisement short video to be evaluated'ijAnd the clipping fluency weight index of each video frame image in each short video to be evaluated
Substitution formula
Obtaining the video content playing influence coefficient xi of each advertisement short video to be evaluated2aiWhere m is expressed as the number of divided video frame images, β1、β2Respectively expressed as preset video content playing influence factors, and beta1+β2＝1。
S6, video frame image contrast processing: and extracting preset product display images corresponding to the advertisement short videos to be evaluated, comparing and screening the video frame image matching quantity in the advertisement short videos to be evaluated, and analyzing the product display image matching quantity of the advertisement short videos to be evaluated.
In this embodiment, in the step S6, the product display image matching coefficients of each advertisement short video to be evaluated are analyzed in a specific analysis manner:
comparing each video frame image in each advertisement short video to be evaluated with a preset product display image corresponding to the corresponding advertisement short video to be evaluated, if the preset product display image corresponding to the advertisement short video to be evaluated appears in a certain video frame image in a certain advertisement short video to be evaluated, matching the video frame image in the advertisement short video to be evaluated with the corresponding preset product display image, counting the matching number of the video frame images in the advertisement short video to be evaluated, and marking the matching number of the video frame images in the advertisement short video to be evaluated as zai；
Product display image matching coefficient for analyzing short videos of advertisements to be evaluated
Wherein δ is expressed as a preset product display image matching impact factor, zPreset ofExpressed as a preset video frame image matching number threshold, and e is expressed as a constant.
S7, evaluating the production quality of the advertisement short video: and evaluating the comprehensive production quality coefficient of each advertisement short video to be evaluated, comparing the comprehensive production quality coefficient with a preset advertisement short video production quality coefficient threshold value, and performing corresponding processing according to the comparison result.
In this embodiment, the evaluating the comprehensive production quality coefficient of each advertisement short video to be evaluated in step S7 includes:
matching topic coefficient xi of head video speech information in each short video to be evaluated1aiAnd the video content playing influence coefficient xi of each advertisement short video to be evaluated2aiMatching coefficient xi of product display images of short videos of advertisements to be evaluated3aiSubstituting into the advertisement short video production quality evaluation formula psii＝γ1*ξ1ai+γ2*ξ2ai+γ3*ξ3aiTo obtain the comprehensive production quality coefficient psi of each advertisement short video to be evaluatediWherein γ is1、γ2、γ3Respectively expressed as preset advertisement short video production quality influence factors, and gamma1+γ2+γ3＝1。
In a possible design, the step S7 performs corresponding processing according to the comparison result, including:
and comparing the comprehensive production quality coefficient of each short video to be evaluated with a preset advertisement short video production quality coefficient threshold, if the comprehensive production quality coefficient of a certain short video to be evaluated is greater than or equal to the preset advertisement short video production quality coefficient threshold, indicating that the production quality of the short video to be evaluated is qualified, and if the comprehensive production quality coefficient of the short video to be evaluated is less than the preset advertisement short video production quality coefficient threshold, indicating that the production quality of the short video to be evaluated is unqualified, then re-producing and evaluating the short video to be evaluated.
It should be noted that, the invention analyzes the video content playing influence coefficient of each advertisement short video to be evaluated by obtaining the relevant parameters and video time points of each video frame image in each advertisement short video to be evaluated, and the comprehensive production quality coefficient of each advertisement short video to be evaluated is evaluated and obtained by combining the matching number of the video frame images in each advertisement short video to be evaluated, after the comparison and analysis, the corresponding processing is carried out, thereby realizing the comprehensive evaluation according to the multi-dimensional quality influence factors of the advertisement short video, breaking the problem that the prior method has certain limitation, thereby effectively ensuring the reliability and the accuracy of the evaluation result of the production quality of the advertisement short video, ensuring the expected delivery effect of the advertisement short video at the later stage, meanwhile, the economic cost of making the advertisement short videos, the economic cost of putting the advertisements and the loss of time cost can be avoided to a certain extent.
In a second aspect, the invention further provides an advertisement short video quality evaluation system based on big data analysis, which comprises an advertisement short video head video acquisition module, a head video word information comparison and analysis module, an advertisement short video planning database, a video frame image related parameter processing module, a video frame image editing and fluency analysis module, a video content playing influence coefficient analysis module, a video frame image comparison and processing module and an advertisement short video production quality evaluation module;
the short advertisement video title information comparison analysis module is respectively connected with the short advertisement video planning database and the short advertisement video production quality evaluation module, the video frame image editing and smoothness analysis module is respectively connected with the video frame image related parameter processing module and the video content playing influence coefficient analysis module, the video content playing influence coefficient analysis module is respectively connected with the video frame image related parameter processing module and the short advertisement video production quality evaluation module, and the video frame image comparison processing module is respectively connected with the short advertisement video planning database, the video frame image related parameter processing module and the short advertisement video production quality evaluation module;
the advertisement short video head video acquisition module is used for acquiring a head video in each advertisement short video to be evaluated according to the playing time length of each advertisement short video to be evaluated;
the film head video speech information comparison and analysis module is used for extracting film head video speech information in each short video to be evaluated, comparing the extracted film head video speech information with preset planning topic information of each short video to be evaluated, and analyzing a coefficient which is in accordance with the topic of the film head video speech information in each short video to be evaluated;
the advertisement short video planning database is used for storing preset planning subject information and preset product display images of the advertisement short videos to be evaluated;
the video frame image related parameter processing module is used for dividing each advertisement short video to be evaluated into each video frame image, acquiring related parameters of each video frame image in each advertisement short video to be evaluated, and processing to obtain a parameter influence weight index of each video frame image in each advertisement short video to be evaluated;
the video frame image clipping fluency analysis module is used for acquiring video time points corresponding to video frame images in the advertisement short videos to be evaluated, and comparing and analyzing clipping fluency weight indexes of the video frame images in the advertisement short videos to be evaluated;
the video content playing influence coefficient analysis module is used for analyzing the video content playing influence coefficient of each advertisement short video to be evaluated according to the parameter influence weight index and the clipping fluency weight index of each video frame image in each advertisement short video to be evaluated;
the video frame image comparison processing module is used for extracting preset product display images corresponding to the advertisement short videos to be evaluated, comparing and screening the matching number of the video frame images in the advertisement short videos to be evaluated, and analyzing the matching number of the product display images of the advertisement short videos to be evaluated;
the advertisement short video production quality evaluation module is used for evaluating the comprehensive production quality coefficient of each advertisement short video to be evaluated, comparing the comprehensive production quality coefficient with a preset advertisement short video production quality coefficient threshold value, and carrying out corresponding processing according to the comparison result.
In a third aspect, the present invention further provides a storage medium, where a computer program is recorded in the storage medium, and when the computer program runs in a memory of a server, the method for evaluating quality of an advertisement short video based on big data analysis according to the present invention is implemented.
The foregoing is merely exemplary and illustrative of the principles of the present invention and various modifications, additions and substitutions of the specific embodiments described herein may be made by those skilled in the art without departing from the principles of the present invention or exceeding the scope of the claims set forth herein.
Claims (10)
1. A method for evaluating the quality of advertisement short videos based on big data analysis is characterized by comprising the following steps:
s1, acquiring the advertisement short video leader video: acquiring a leader video in each short video to be evaluated according to the playing time length of each short video to be evaluated;
s2, comparing and analyzing title information of the film leader video: extracting the head video speech information in each short video of the advertisement to be evaluated, comparing the head video speech information with preset planning topic information of each short video of the advertisement to be evaluated, and analyzing a coefficient which is in line with the topic information of the head video speech information in each short video of the advertisement to be evaluated;
s3, video frame image related parameter processing: dividing each short video of the advertisement to be evaluated into each video frame image, acquiring relevant parameters of each video frame image in each short video of the advertisement to be evaluated, and processing to obtain a parameter influence weight index of each video frame image in each short video of the advertisement to be evaluated;
s4, video frame image clipping fluency analysis: acquiring video time points corresponding to video frame images in the advertisement short videos to be evaluated, and comparing and analyzing the clipping fluency weight indexes of the video frame images in the advertisement short videos to be evaluated;
s5, analyzing the video content playing influence coefficient: analyzing a video content playing influence coefficient of each advertisement short video to be evaluated according to the parameter influence weight index and the clipping fluency weight index of each video frame image in each advertisement short video to be evaluated;
s6, video frame image contrast processing: extracting preset product display images corresponding to the advertisement short videos to be evaluated, comparing and screening the video frame image matching quantity in the advertisement short videos to be evaluated, and analyzing the product display image matching quantity of the advertisement short videos to be evaluated;
s7, evaluating the production quality of the advertisement short video: and evaluating the comprehensive production quality coefficient of each advertisement short video to be evaluated, comparing the comprehensive production quality coefficient with a preset advertisement short video production quality coefficient threshold value, and performing corresponding processing according to the comparison result.
2. The method for evaluating the quality of the advertisement short video based on the big data analysis as claimed in claim 1, wherein: the detailed steps in step S1 are as follows:
numbering each short advertisement video to be evaluated in sequence according to a production time sequence, wherein the number of each short advertisement video to be evaluated is 1,2,. once, i,. once, n;
acquiring the playing time of each short video of the advertisement to be evaluated, and analyzing the leader time of each short video of the advertisement to be evaluated based on the preset leader time ratio of the short video of the advertisement;
according to the leader duration of each short video of the advertisement to be evaluated, the leader video of each short video of the advertisement to be evaluated is obtained, and the leader video of each short video of the advertisement to be evaluated is marked as aiI is 1,2, and n, i is represented as the ith advertisement short video to be evaluated.
3. The method for evaluating the quality of the advertisement short video based on the big data analysis as claimed in claim 1, wherein: in the step S2, the subject matching coefficient of the title video speech information in each short video to be evaluated is analyzed, and the specific analysis steps include:
extracting the lines information of the head videos in the short videos of the advertisements to be evaluated, extracting the preset planning subject information of the short videos of the advertisements to be evaluated in the advertisement short video planning database, comparing the lines information of the head videos in the short videos of the advertisements to be evaluated with the preset planning subject information of the short videos corresponding to the advertisements to be evaluated to obtain the conformity between the lines information of the head videos in the short videos of the advertisements to be evaluated and the preset planning subject information, and marking the conformity between the lines information of the head videos in the short videos of the advertisements to be evaluated and the preset planning subject information as theta alphai；
Coefficient of subject of film head video lines information in each short video to be evaluated is analyzed
Wherein muθExpressed as an influence index, θ, corresponding to a predetermined conformityStandard of meritThe preset short video line information and the standard conformity threshold value of the planned subject information are expressed.
4. The method for evaluating the quality of the advertisement short video based on the big data analysis as claimed in claim 1, wherein: the corresponding detailed steps in step S3 include:
dividing each advertisement short video to be evaluated into each video frame image in sequence according to the video playing sequence, obtaining relevant parameters of each video frame image in each advertisement short video to be evaluated, wherein the relevant parameters comprise resolution, frame rate, pixels and definition, and respectively marking the resolution, the frame rate, the pixels and the definition of each video frame image in each advertisement short video to be evaluated as w1bij、w2bij、w3bij、w4bijJ is 1,2, and m, j is represented as the jth video frame image;
analyzing parameter influence weight index of each video frame image in each advertisement short video to be evaluated
Wherein λ is1、λ2、λ3、λ4Respectively expressed as weight influence factors corresponding to preset image resolution, image frame rate, image pixel and image definition, and lambda1+λ2+λ3+λ4＝1，w1bSign board、w2bSign board、w3bSign board、w4bSign boardRespectively representing the standard resolution, the standard frame rate, the standard pixel and the standard definition corresponding to the preset video frame image.
5. The method for evaluating the quality of the advertisement short video based on the big data analysis as claimed in claim 1, wherein: in the step S4, the clipping fluency weighting index of each video frame image in each advertisement short video to be evaluated is contrastively analyzed, and the specific analysis mode is as follows:
acquiring video time points corresponding to video frame images in each short video of the advertisement to be evaluated, and marking the video time points corresponding to the video frame images in each short video of the advertisement to be evaluated as tibj；
Substituting video time points corresponding to video frame images in short videos of advertisements to be evaluated into a formula
Obtaining the clipping fluency weight index of each video frame image in each advertisement short video to be evaluated
η1、η2Respectively expressed as preset clip fluency impact factors, tibj+1Is represented as the video time point, t, corresponding to the j +1 video frame image in the ith advertisement short video to be evaluatedibj-1Is expressed as the video time point, delta t, corresponding to the j-1 video frame image in the ith advertisement short video to be evaluatedAllow forExpressed as allowed time point error values between preset video frame images.
6. The method for evaluating the quality of the advertisement short video based on the big data analysis as claimed in claim 1, wherein: the corresponding detailed steps in step S5 include:
the parameter influence weight index epsilon b 'of each video frame image in each advertisement short video to be evaluated'ijAnd the clipping fluency weight index of each video frame image in each short video to be evaluated
Substitution formula
Obtaining the video content playing influence coefficient xi of each advertisement short video to be evaluated2aiWhere m is expressed as the number of divided video frame images, β1、β2Respectively expressed as preset video content playing influence factors, and beta1+β2＝1。
7. The method for evaluating the quality of the advertisement short video based on the big data analysis as claimed in claim 1, wherein: in the step S6, product display image matching coefficients of the advertisement short videos to be evaluated are analyzed, and the specific analysis mode is as follows:
comparing each video frame image in each advertisement short video to be evaluated with a preset product display image corresponding to the corresponding advertisement short video to be evaluated, if the preset product display image corresponding to the advertisement short video to be evaluated appears in a certain video frame image in a certain advertisement short video to be evaluated, matching the video frame image in the advertisement short video to be evaluated with the corresponding preset product display image, counting the matching number of the video frame images in the advertisement short video to be evaluated, and marking the matching number of the video frame images in the advertisement short video to be evaluated as zai；
Product display image matching coefficient for analyzing short videos of advertisements to be evaluated
Wherein δ is expressed as a preset product display image matching impact factor, zPresetExpressed as a preset video frame image matching quantity threshold value, and e is expressed as a constant.
8. The method for evaluating the quality of the advertisement short video based on the big data analysis as claimed in claim 1, wherein: the step S7 of evaluating the comprehensive production quality coefficient of each advertisement short video to be evaluated includes:
matching topic coefficient xi of head video line word information in each short video to be evaluated1aiAnd the video content playing influence coefficient xi of each advertisement short video to be evaluated2aiMatching coefficient xi of product display images of short videos of advertisements to be evaluated3aiSubstituting into the advertisement short video production quality evaluation formula psii＝γ1*ξ1ai+γ2*ξ2ai+γ3*ξ3aiTo obtain the comprehensive production quality coefficient psi of each advertisement short video to be evaluatediWherein γ is1、γ2、γ3Respectively expressed as preset advertisement short video production quality influence factors, and gamma1+γ2+γ3＝1。
9. An advertisement short video quality evaluation system based on big data analysis, comprising:
an advertisement short video head video acquisition module: the system is used for acquiring the leader video in each short video to be evaluated according to the playing time length of each short video to be evaluated;
the film head video speech information comparison analysis module: the system comprises a video processing module, a theme analysis module and a theme analysis module, wherein the video processing module is used for extracting the title video speech information in each short video to be evaluated, comparing the title video speech information with the preset planned theme information of each short video to be evaluated, and analyzing the coefficient of the title video speech information in each short video to be evaluated, which accords with the theme;
advertisement short video planning database: the system comprises a storage module, a processing module and a display module, wherein the storage module is used for storing preset planning subject information and preset product display images of advertisement short videos to be evaluated;
the video frame image related parameter processing module: the system comprises a video evaluation unit, a parameter influence weight index processing unit, a parameter evaluation unit and a parameter evaluation unit, wherein the video evaluation unit is used for dividing each short advertisement video to be evaluated into each video frame image, acquiring relevant parameters of each video frame image in each short advertisement video to be evaluated, and processing to obtain the parameter influence weight index of each video frame image in each short advertisement video to be evaluated;
video frame image clipping fluency analysis module: the video time point corresponding to each video frame image in each advertisement short video to be evaluated is obtained, and the clipping fluency weight index of each video frame image in each advertisement short video to be evaluated is contrasted and analyzed;
the video content playing influence coefficient analysis module: the video content playing influence coefficient analysis module is used for analyzing the video content playing influence coefficient of each advertisement short video to be evaluated according to the parameter influence weight index and the clipping fluency weight index of each video frame image in each advertisement short video to be evaluated;
the video frame image contrast processing module: the system is used for extracting preset product display images corresponding to the advertisement short videos to be evaluated, comparing and screening the matching number of video frame images in the advertisement short videos to be evaluated, and analyzing the matching number of the product display images of the advertisement short videos to be evaluated;
the advertisement short video production quality evaluation module: and the comprehensive production quality coefficient is used for evaluating the comprehensive production quality coefficient of each advertisement short video to be evaluated, comparing the comprehensive production quality coefficient with a preset advertisement short video production quality coefficient threshold value, and performing corresponding processing according to the comparison result.
10. A storage medium, characterized by: the storage medium is burned with a computer program, and when the computer program runs in a memory of a server, the method for evaluating the quality of the advertisement short video based on the big data analysis according to any one of claims 1 to 8 is implemented.
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