CN109345280A - Intelligent advertisement position put-on method and device based on big data analysis - Google Patents
Intelligent advertisement position put-on method and device based on big data analysis Download PDFInfo
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Abstract
The embodiment of the invention discloses a kind of intelligent advertisement position put-on method and device based on big data analysis, the advertisement dispensing that this method is carried out applied to internet platform.This method comprises: obtaining the pre- commercial audience feature for launching advertisement, obtain advertisement position audient's feature of at least one advertisement position, pre- dispensing advertisement is thrown to targeted advertisements position by the highest targeted advertisements position of the degree of correlation that advertisement position audient feature and the pre- commercial audience feature for launching advertisement are determined from least one advertisement position.Implement the embodiment of the present invention, can may launch advertisement in conjunction with commercial audience feature and advertisement position audient's feature to the advertisement position where the more interested audient of ad content to choose, realize the accurate dispensing of advertisement position, increase investment in advertising return rate.
Description
Technical field
The present invention relates to Internet technical field more particularly to a kind of intelligent advertisement position dispensing sides based on big data analysis
Method and device.
Background technique
Currently, with the rapid development of Internet technology, the advantages that the Internet media is wide, propagation efficiency is high with its audient
Have become the important channel that advertisement is launched by enterprise.Common, the advertisement of the Internet media industry is launched mainly using competing
Valence or the mode of business driving carry out.In practice, it has been found that often will appear advertisement throwing by the way of this dispensing advertisement
The position put can not precisely match the situation of user demand, so as to cause the low problem of investment in advertising return rate.
Summary of the invention
The embodiment of the present invention discloses a kind of intelligent advertisement position put-on method and device based on big data analysis, can be realized
The accurate dispensing of advertisement position, to increase investment in advertising return rate.
First aspect of the embodiment of the present invention discloses a kind of intelligent advertisement position put-on method based on big data analysis, comprising:
Obtain the pre- commercial audience feature for launching advertisement；
Obtain advertisement position audient's feature of at least one advertisement position；
The advertisement position audient feature and the pre- advertisement for launching advertisement are determined from advertisement position described at least one
The highest targeted advertisements position of the degree of correlation of audient's feature；
The pre- dispensing advertisement is thrown to the targeted advertisements position.
As an alternative embodiment, in first aspect of the embodiment of the present invention, the pre- dispensing advertisement of acquisition
Commercial audience feature, comprising:
Extract the pre- main information launched in advertisement；
The pre- ad content for launching advertisement is determined according to the main information；
Content characteristic analysis is carried out to the pre- ad content for launching advertisement, several content characteristics are obtained, if from described
Selected in dry content characteristic at least one content characteristic as it is described it is pre- launch advertisement commercial audience feature, described at least one
A content characteristic is the pre- corresponding body matter feature of ad content for launching advertisement.
As an alternative embodiment, in first aspect of the embodiment of the present invention, described at least one advertisement of acquisition
Advertisement position audient's feature of position, comprising:
At least one described advertisement position is obtained in the location information of media page；
According to the positional information, the record of user behavior caused by least one described advertisement position is obtained；
According to the user behavior of advertisement position described at least one record obtain at least one advertisement position advertisement position by
Many features.
As an alternative embodiment, in first aspect of the embodiment of the present invention, it is described according at least one
The user behavior record of advertisement position obtains advertisement position audient's feature of at least one advertisement position, comprising:
The user that user behavior record was generated at least one described advertisement position is divided into the user of respective advertisement position
In group, the behavior record set of the user group is obtained, the behavior record set of the user group includes every in the user group
The user behavior record of one user；
The user behavior of respective advertisement position is obtained according to the behavior record set of the user group of advertisement position described at least one
Analysis is as a result, obtain advertisement position audient's feature of respective advertisement position according to the user behavior analysis result.
As an alternative embodiment, in first aspect of the embodiment of the present invention, it is described according at least one
The behavior record set of the user group of advertisement position obtains the user behavior analysis of respective advertisement position as a result, according to the user behavior
Analyze advertisement position audient's feature that result obtains respective advertisement position, comprising:
According to the behavior record set of the user group of advertisement position described at least one, at least one advertisement position is obtained
At least one matched user behavior label of user group；
Statistics generates user behavior analysis list corresponding at least one described user behavior label, the user behavior
Analyzing list includes at least one described user behavior label；
At least one described user behavior label in the user behavior analysis list is calculated in affiliated label classification
Shared weight；
It is special according at least one described user behavior label and Weight Acquisition user corresponding with the user behavior label
Sign, and at least one described user characteristics is chosen as the advertisement position audient feature.
As an alternative embodiment, in first aspect of the embodiment of the present invention, it is described from wide described at least one
It accuses and determines that advertisement position audient feature and the highest target of the degree of correlation of the pre- commercial audience feature for launching advertisement are wide in position
Accuse position, comprising:
It determines to match with the pre- commercial audience feature for launching advertisement from advertisement position described at least one wide
Position is accused to obtain the first advertisement position set, and determines the advertisement position audient feature and institute from the first advertisement position set
State the highest targeted advertisements position of the degree of correlation of the pre- commercial audience feature for launching advertisement.
As an alternative embodiment, in first aspect of the embodiment of the present invention, it is described from wide described at least one
It accuses and determines that advertisement position audient feature and the highest target of the degree of correlation of the pre- commercial audience feature for launching advertisement are wide in position
Accuse position, comprising:
The advertisement position for being currently at idle state is selected from advertisement position described at least one to obtain the second advertisement position
Set, and determine from the second advertisement position set the advertisement position audient feature and the pre- advertisement for launching advertisement by
The highest targeted advertisements position of the degree of correlation of many features.
Second aspect of the embodiment of the present invention discloses a kind of intelligent advertisement position delivery device based on big data analysis, comprising:
First acquisition unit, for obtaining the pre- commercial audience feature for launching advertisement；
Second acquisition unit, for obtaining advertisement position audient's feature of at least one advertisement position；
Determination unit, for determining the advertisement position audient feature and the pre-cast from advertisement position described at least one
Put the highest targeted advertisements position of the degree of correlation of the commercial audience feature of advertisement；
Unit is launched, for the pre- dispensing advertisement to be thrown to the targeted advertisements that the determination unit is determined
Position.
As an alternative embodiment, in second aspect of the embodiment of the present invention, the first acquisition unit includes:
Subelement is extracted, for extracting the pre- main information launched in advertisement；
Determine subelement, the main information for extracting according to the extraction subelement determines the pre- dispensing
The ad content of advertisement；
First obtain subelement, for the determining subelement determine it is described it is pre- launch advertisement ad content into
The analysis of row content characteristic, obtains several content characteristics, and select at least one content characteristic from several content characteristics
As the pre- commercial audience feature for launching advertisement, at least one described content characteristic is in the pre- advertisement for launching advertisement
Hold corresponding body matter feature.
As an alternative embodiment, in second aspect of the embodiment of the present invention, the second acquisition unit includes:
Second obtains subelement, for obtaining at least one described advertisement position in the location information of media page；And according to
The location information obtains the record of user behavior caused by least one described advertisement position；
Subelement is analyzed, for obtaining the user's row at least one advertisement position that subelement obtains according to described second
Advertisement position audient's feature of at least one advertisement position is obtained for record.
As an alternative embodiment, the analysis subelement is used for root in second aspect of the embodiment of the present invention
It is described wide that the user behavior record for obtaining at least one advertisement position that subelement obtains according to described second obtains at least one
Accuse the mode of advertisement position audient's feature of position specifically:
The analysis subelement, for drawing the user for generating user behavior record at least one described advertisement position
In the user group for entering respective advertisement position, the behavior record set of the user group, the behavior record set of the user group are obtained
User behavior record including each user in the user group；According to the behavior of the user group of advertisement position described at least one
Set of records ends obtains the user behavior analysis of respective advertisement position as a result, obtaining respective advertisement according to the user behavior analysis result
Advertisement position audient's feature of position.
As an alternative embodiment, the analysis subelement is used for root in second aspect of the embodiment of the present invention
The user behavior analysis of respective advertisement position is obtained as a result, root according to the behavior record set of the user group of advertisement position described at least one
The mode of advertisement position audient's feature of respective advertisement position is obtained according to the user behavior analysis result specifically:
The analysis subelement is obtained for the behavior record set according to the user group of advertisement position described at least one
At least one matched user behavior label of the user group of at least one advertisement position；Statistics generates and at least one described use
The corresponding user behavior analysis list of family behavior label, the user behavior analysis list include at least one described user behavior
Label；It is shared in affiliated label classification to calculate at least one described user behavior label in the user behavior analysis list
Weight；It is special according at least one described user behavior label and Weight Acquisition user corresponding with the user behavior label
Sign, and at least one described user characteristics is chosen as the advertisement position audient feature.
As an alternative embodiment, in second aspect of the embodiment of the present invention, the determination unit includes:
First determines subelement, for determining from advertisement position described at least one and the pre- advertisement for launching advertisement
The advertisement position that audient's feature matches is determined from the first advertisement position set described with obtaining the first advertisement position set
The highest targeted advertisements position of the degree of correlation of advertisement position audient feature and the pre- commercial audience feature for launching advertisement；Alternatively,
Second determines subelement, for selecting the advertisement for being currently at idle state from advertisement position described at least one
Position to obtain the second advertisement position set, and determine from the second advertisement position set the advertisement position audient feature with it is described
The highest targeted advertisements position of the degree of correlation of the pre- commercial audience feature for launching advertisement.
The third aspect of the embodiment of the present invention discloses a kind of electronic equipment, including memory and processor, and the memory is deposited
Computer program is contained, the processor is realized any one in first aspect of the embodiment of the present invention when executing the computer program
Some or all of kind method step.
Fourth aspect of the embodiment of the present invention discloses a kind of computer readable storage medium, stores computer program, wherein
The computer program makes computer execute a kind of intelligence based on big data analysis disclosed in first aspect of the embodiment of the present invention
It can advertisement position put-on method.
The 5th aspect of the embodiment of the present invention discloses a kind of computer program product, when the computer program product is calculating
When being run on machine, so that the computer executes some or all of any one method of first aspect step.
The aspect of the embodiment of the present invention the 6th disclose a kind of using distribution platform, and the application distribution platform is for publication calculating
Machine program product, wherein when the computer program product is run on computers, so that the computer executes first party
Some or all of any one method in face step.
Compared with prior art, the embodiment of the present invention has the advantages that
In the embodiment of the present invention, the pre- commercial audience feature for launching advertisement is obtained, the advertisement of at least one advertisement position is obtained
Position audient's feature determines the commercial audience feature of advertisement position audient feature and pre- dispensing advertisement from least one advertisement position
The highest targeted advertisements position of the degree of correlation launches pre- advertisement and is thrown to targeted advertisements position, can in conjunction with commercial audience feature and
Advertisement position audient's feature may launch advertisement to the advertisement position where the more interested audient of ad content to choose, realize wide
The accurate dispensing of position is accused, investment in advertising return rate is increased.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to needed in the embodiment
Attached drawing is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the invention, for ability
For the those of ordinary skill of domain, without creative efforts, it can also be obtained according to these attached drawings other attached
Figure.
Fig. 1 is that a kind of process of intelligent advertisement position put-on method based on big data analysis disclosed by the embodiments of the present invention is shown
It is intended to；
Fig. 2 is the process of another intelligent advertisement position put-on method based on big data analysis disclosed by the embodiments of the present invention
Schematic diagram；
Fig. 3 is the process of another intelligent advertisement position put-on method based on big data analysis disclosed by the embodiments of the present invention
Schematic diagram；
Fig. 4 is that a kind of structure of intelligent advertisement position delivery device based on big data analysis disclosed by the embodiments of the present invention is shown
It is intended to；
Fig. 5 is the structure of another intelligent advertisement position delivery device based on big data analysis disclosed by the embodiments of the present invention
Schematic diagram；
Fig. 6 is the structure of another intelligent advertisement position delivery device based on big data analysis disclosed by the embodiments of the present invention
Schematic diagram；
Fig. 7 is the structural schematic diagram of a kind of electronic equipment disclosed by the embodiments of the present invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that the described embodiment is only a part of the embodiment of the present invention, instead of all the embodiments.Based on this
Embodiment in invention, every other reality obtained by those of ordinary skill in the art without making creative efforts
Example is applied, shall fall within the protection scope of the present invention.
It should be noted that term " includes " and " having " and their any changes in the embodiment of the present invention and attached drawing
Shape, it is intended that cover and non-exclusive include.Such as contain the process, method of a series of steps or units, system, product or
Equipment is not limited to listed step or unit, but optionally further comprising the step of not listing or unit or optional
Ground further includes the other step or units intrinsic for these process, methods, product or equipment.
The embodiment of the present invention discloses a kind of intelligent advertisement position put-on method and device based on big data analysis, can be realized
The accurate dispensing of advertisement position increases investment in advertising return rate.It is described in detail separately below.
Embodiment one
Referring to Fig. 1, Fig. 1 is a kind of intelligent advertisement position dispensing side based on big data analysis disclosed by the embodiments of the present invention
Method.As shown in Figure 1, being somebody's turn to do the intelligent advertisement position put-on method based on big data analysis may comprise steps of:
101, the pre- commercial audience feature for launching advertisement is obtained.
In the embodiment of the present invention, commercial audience feature may include life commodity industry, articles for babies, paper diaper and flower king
The feature relevant to ad content such as brand, in the embodiment of the present invention without limitation.
As an alternative embodiment, the commercial audience feature for obtaining pre- dispensing advertisement may include:
Advertisement progress content characteristic analysis is launched to pre-, the pre- ad data for launching advertisement is extracted according to content characteristic analysis
In key message；
Subcategory information corresponding with key message is obtained, and obtains major category information corresponding with subcategory information；Its
In, subcategory information and major category information collectively form merchandise classification information；And key message is deposited with merchandise classification information MAP
Storage；
The pre- commercial audience feature for launching advertisement is obtained according to major category information and subcategory information.
By implementing this optional embodiment, with the crucial letter for being included according to the pre- ad data for launching advertisement
Breath obtains the merchandise classification information with key message mapping storage, and it is special to obtain the pre- commercial audience for launching advertisement on this basis
Sign, and merchandise classification information includes major category information and subcategory information, thus obtains the advertisement more fully and having levels
Audient's feature improves the precision for obtaining commercial audience feature.
As another optional embodiment, obtaining the pre- commercial audience feature for launching advertisement may include:
Advertisement progress content characteristic analysis is launched to pre-, the pre- ad data for launching advertisement is extracted according to content characteristic analysis
In key message；
Major category information corresponding with key message is obtained, and obtains subcategory information corresponding with major category information；Its
In, subcategory information and major category information collectively form merchandise classification information；And key message is deposited with merchandise classification information MAP
Storage；
The pre- commercial audience feature for launching advertisement is obtained according to major category information and subcategory information.
In the embodiment of the present invention, the major category information of merchandise classification information can be trade information, merchandise classification information
Subcategory information can be brand message.Also, key message can be the key frame in ad data.
By implementing this optional embodiment, can be believed according to the key that the pre- ad data for launching advertisement be included
Breath obtains the merchandise classification information with key message mapping storage, and it is special to obtain the pre- commercial audience for launching advertisement on this basis
Sign, and merchandise classification information includes major category information and subcategory information, thus obtains the advertisement more fully and having levels
Audient's feature improves the precision for obtaining commercial audience feature.
102, advertisement position audient's feature of at least one advertisement position is obtained.
In the embodiment of the present invention, advertisement position audient's feature may include gender, age, life commodity and financial products etc.,
In the embodiment of the present invention without limitation.Also, the embodiment of the present invention is special for the commercial audience feature of acquisition and advertisement position audient
The quantity of sign is with no restrictions.
103, advertisement position audient feature and the pre- commercial audience feature for launching advertisement are determined from least one advertisement position
The highest targeted advertisements position of the degree of correlation.
In the embodiment of the present invention, advertisement position audient feature and pre- dispensing advertisement can be calculated using similarity calculation
Commercial audience feature the degree of correlation, and determine from least one advertisement position advertisement position audient feature and pre- launch advertisement
The highest targeted advertisements position of the degree of correlation of commercial audience feature.
104, pre- dispensing advertisement is thrown to targeted advertisements position.
As an alternative embodiment, pre- will launch advertisement and be thrown to targeted advertisements position and may include:
According to advertisement position audient's feature of targeted advertisements position, analysis obtains the highest mesh of audient's clicking rate of targeted advertisements position
Mark period, and the highest targeted advertisements form of audient's clicking rate of targeted advertisements position in the target time section；Wherein, mesh
It can be any wide in written form, graphic form, picture and text combining form, audio form and visual form etc. for marking advertisement form
Announcement form；
Pre- dispensing advertisement is adjusted to targeted advertisements form in the target time section, target is obtained and launches advertisement in advance；
Target is launched to advertisement in advance and is thrown to targeted advertisements position in the target time period.
Mesh can also be further analyzed after determining targeted advertisements position by implementing this optional embodiment
The advertisement position audient feature of advertisement position is marked to choose and launch the pre- target time section and targeted advertisements form for launching advertisement, so that
Pre- dispensing advertisement is thrown to targeted advertisements position according to targeted advertisements form in target time section, this process can be utmostly
Ground obtains the high of audient and clicks, to increase the spread scope of advertisement.
As it can be seen that implementing the intelligent advertisement position put-on method based on big data analysis described in Fig. 1, pre- dispensing advertisement is obtained
Commercial audience feature, obtain advertisement position audient's feature of at least one advertisement position, determined from least one advertisement position wide
The highest targeted advertisements position of the degree of correlation for accusing position audient feature and the pre- commercial audience feature for launching advertisement will launch advertisement throwing in advance
It puts to targeted advertisements position, can be in conjunction with commercial audience feature and advertisement position audient's feature, it may be to ad content more to choose
Advertisement position where interested audient launches advertisement, realizes the accurate dispensing of advertisement position, increases investment in advertising return rate.
Embodiment two
Referring to Fig. 2, Fig. 2 is that another intelligent advertisement position based on big data analysis disclosed by the embodiments of the present invention is launched
Method.As shown in Fig. 2, being somebody's turn to do the intelligent advertisement position put-on method based on big data analysis may comprise steps of:
201, the pre- main information launched in advertisement is extracted, and is determined in the pre- advertisement for launching advertisement according to main information
Hold.
In the embodiment of the present invention, main information can put the copy that advertisement includes for pre-cast, i.e., launch advertisement in advance
Key frame in ad data, or the pre- advertisement audio etc. launched advertisement and include, in the embodiment of the present invention without limitation.
202, content characteristic analysis is carried out to the pre- ad content for launching advertisement, obtains several content characteristics.
In the embodiment of the present invention, content characteristic analysis, available and advertisement are carried out to the pre- ad content for launching advertisement
The relevant feature of content, for example, several content characteristics may include automobile industry, company of Audi, vehicle price and vapour
Any combination in vehicle discharge capacity etc..
203, it is special as the pre- commercial audience for launching advertisement that at least one content characteristic is selected from several content characteristics
Sign.
In the embodiment of the present invention, at least one content characteristic is that the corresponding body matter of the pre- ad content for launching advertisement is special
Sign.
In the embodiment of the present invention, most important feature can be selected to launch the wide of advertisement as pre- from several content characteristics
Accuse audient's feature, and the embodiment of the present invention to the quantity of commercial audience feature without limitation, for example, can be special from several contents
Most important 10 content characteristics are chosen in sign as commercial audience feature.
As an alternative embodiment, selecting at least one content characteristic from several content characteristics as pre-cast
The commercial audience feature for putting advertisement may include:
In the related coefficient inquired in initialized data base between each content characteristic and the purchasing power of commercial audience；
The significant content characteristic of related coefficient is filtered out as object content feature, and the sequence successively decreased according to related coefficient
Object content feature is ranked up；
The object content feature before sequence is located at preset quantity is chosen as the pre- audient's feature for launching advertisement.
By implementing this optional embodiment, can choose between the purchasing power of commercial audience compared with degree of correlation
High content characteristic is as commercial audience feature, to improve investment in advertising return rate.
204, at least one advertisement position is obtained in the location information of media page.
In the embodiment of the present invention, at least one advertisement position can be the preset position in internet in the location information of media page
Confidence breath, and the location information can be transferred by initialized data base.Wherein, location information may include mould belonging to position
Scene information belonging to block message and position.Wherein, module information is the item property label of advertisement position, and module information can be with
Including any combination in financial module, life merchandise module, insurance module and automotive goods module etc., it also may include
His module, it is not limited in the embodiment of the present invention；Scene information is the page location label of advertisement position, and scene information can wrap
Include direct scene and association scene.Wherein, direct scene be user enter media page can the direct advertisement position that arrives of preview,
The layout of a page without columns in such as homepage, association scene are that user completes or carry out the advertisement position occurred after a certain operation.
205, according to location information, the record of user behavior caused by least one advertisement position is obtained.
In the embodiment of the present invention, user behavior record may include user's purchase, click, browsing, use or evaluate certain
The record of kind product.
206, the advertisement position audient spy for obtaining at least one advertisement position is recorded according to the user behavior of at least one advertisement position
Sign.
207, advertisement position audient feature and the pre- commercial audience feature for launching advertisement are determined from least one advertisement position
The highest targeted advertisements position of the degree of correlation.
208, pre- dispensing advertisement is thrown to targeted advertisements position.
As it can be seen that implement Fig. 2 described in the intelligent advertisement position put-on method based on big data analysis, can in conjunction with advertisement by
Many features and advertisement position audient's feature may launch extensively the advertisement position where the more interested audient of ad content to choose
It accuses, the accurate dispensing of advertisement position is realized, to increase investment in advertising return rate.
In addition, implementing the intelligent advertisement position put-on method based on big data analysis described in Fig. 2, pre- dispensing can be extracted
Main information in advertisement, and the pre- ad content for launching advertisement is determined according to main information, in ad content progress
Hold signature analysis, obtain several content characteristics, at least one content characteristic is selected from several content characteristics and is launched as pre-
The commercial audience feature of advertisement realizes the accurate analysis to ad content with this, and the standard for obtaining commercial audience feature can be improved
True property.
In addition, implement the intelligent advertisement position put-on method based on big data analysis described in Fig. 2, it can be according at least one
User behavior caused by a advertisement position records and analyzes to obtain advertisement position audient's feature of respective advertisement position, and combines at least one
Advertisement position audient's feature of advertisement position obtains advertisement position audient's feature of at least one advertisement position.This process passes through user's row
The accuracy for obtaining advertisement position audient feature can be improved to analyze.
Embodiment three
Referring to Fig. 3, Fig. 3 is that another intelligent advertisement position based on big data analysis disclosed by the embodiments of the present invention is launched
Method.As shown in figure 3, being somebody's turn to do the intelligent advertisement position put-on method based on big data analysis may comprise steps of:
301, the pre- main information launched in advertisement is extracted, and is determined in the pre- advertisement for launching advertisement according to main information
Hold.
302, content characteristic analysis is carried out to the pre- ad content for launching advertisement, obtains several content characteristics.
303, it is special as the pre- commercial audience for launching advertisement that at least one content characteristic is selected from several content characteristics
Sign.
In the embodiment of the present invention, at least one content characteristic is that the corresponding body matter of the pre- ad content for launching advertisement is special
Sign.
304, at least one advertisement position is obtained in the location information of media page.
305, according to location information, the record of user behavior caused by least one advertisement position is obtained.
In the embodiment of the present invention, user behavior record may include user's build-in attribute record and user behavior attribute note
Record, wherein user's build-in attribute record may include any combination in age, gender, region and income etc., also can wrap
Include other build-in attributes, in the embodiment of the present invention without limitation；User behavior attribute may include that user opens a certain function, use
Family binding business personnel operates, user participates in certain specific activity, user clicks certain content and user buys in certain product etc.
Any combination, also may include other behavior properties, in the embodiment of the present invention without limitation.
306, the user that user behavior record was generated at least one advertisement position is divided into the user of respective advertisement position
In group, the behavior record set of user group is obtained.
In the embodiment of the present invention, the behavior record set of user group includes the user behavior note of each user in user group
Record.
In the embodiment of the present invention, the same user may belong to multiple user groups.
307, according to the behavior record set of the user group of at least one advertisement position, the user of at least one advertisement position is obtained
At least one matched user behavior label of group.
308, statistics generates user behavior analysis list corresponding at least one user behavior label.
In the embodiment of the present invention, user behavior analysis list includes at least one user behavior label, is obtaining this at least
After one user behavior label, it can be classified by the Multidimensional Data Model pre-established to these user behavior labels
It arranges, obtains user behavior analysis list corresponding at least one user behavior label.
309, at least one the user behavior label calculated in user behavior analysis list is shared in affiliated label classification
Weight.
In the embodiment of the present invention, each user behavior label weight shared in affiliated label classification indicates user's row
For label percentage shared in its described label classification.For example, when user behavior label is " male ", the user behavior mark
Label classification belonging to label is " gender ", is if weight of the user behavior label in the label classification is calculated
20%, show that male's label of the advertisement position accounts for weight 20% and the women label of the advertisement position accounts for weight 80%.
310, special according at least one user behavior label and Weight Acquisition user corresponding with the user behavior label
Sign, and at least one user characteristics is chosen as advertisement position audient's feature.
In the embodiment of the present invention, user characteristics can be the form of " user behavior label+weight ", for example, a certain
Advertisement position audient's feature of advertisement position may include male 65%, women 35%, the age 25-30 years old user 30%, age 30-
50 years old users 35%, life commodity active 70% and financial products active 10% etc..
311, advertisement position audient feature and the pre- commercial audience feature for launching advertisement are determined from least one advertisement position
The highest targeted advertisements position of the degree of correlation.
As an alternative embodiment, determining advertisement position audient feature and pre- dispensing from least one advertisement position
The highest targeted advertisements position of the degree of correlation of the commercial audience feature of advertisement may include:
Determine the advertisement position to match with the commercial audience feature for launching advertisement in advance to obtain from least one advertisement position
The first advertisement position set, and determine from the first advertisement position set advertisement position audient feature and the pre- advertisement for launching advertisement by
The highest targeted advertisements position of the degree of correlation of many features.
By implementing this optional embodiment, the commercial audience feature phase with dispensing advertisement in advance can be first determined
The advertisement position matched determines advertisement position audient feature and pre- in the advertisement position to match with the pre- commercial audience feature for launching advertisement
The highest targeted advertisements position of the degree of correlation for launching the commercial audience feature of advertisement, reduces the range of determining targeted advertisements position, from
And improve the efficiency of determining targeted advertisements position.
As another optional embodiment, advertisement position audient feature and pre-cast are determined from least one advertisement position
The highest targeted advertisements position of the degree of correlation for putting the commercial audience feature of advertisement may include:
The advertisement position for being currently at idle state is selected from least one advertisement position to obtain the second advertisement position set,
And advertisement position audient feature is determined from the second advertisement position set and launches the degree of correlation of the commercial audience feature of advertisement in advance most
High targeted advertisements position.
By implementing this optional embodiment, can first determine the advertisement position for being currently at idle state, with
The degree of correlation of the commercial audience feature of advertisement position audient feature and pre- dispensing advertisement is determined in the advertisement position being in idle condition most
High targeted advertisements position, reduces the range of determining targeted advertisements position, to improve the efficiency of determining targeted advertisements position.
312, pre- dispensing advertisement is thrown to targeted advertisements position.
As it can be seen that implementing Fig. 3 described in the intelligent advertisement position put-on method based on big data analysis, can in conjunction with advertisement by
Many features and advertisement position audient's feature may launch extensively the advertisement position where the more interested audient of ad content to choose
It accuses, the accurate dispensing of advertisement position is realized, to increase investment in advertising return rate.
In addition, the intelligent advertisement position put-on method based on big data analysis described in implementing Fig. 3, may be implemented to advertisement
The accurate analysis of content, to improve the accuracy for obtaining commercial audience feature.
In addition, the intelligent advertisement position put-on method based on big data analysis described in implementing Fig. 3, passes through user behavior point
The accuracy for obtaining advertisement position audient feature can be improved in analysis.
In addition, the intelligent advertisement position put-on method based on big data analysis described in implementing Fig. 3, it can be according at least one
The behavior record set of the user group of a advertisement position obtains the user behavior analysis of at least one advertisement position as a result, obtaining with this
Advertisement position audient's feature of respective advertisement position further increases the accuracy for obtaining advertisement position audient feature.
In addition, implementing Fig. 3 described in the intelligent advertisement position put-on method based on big data analysis, can also obtain with extremely
The matched user behavior label of user group of a few advertisement position, and it is shared in label classification to calculate each user behavior label
Weight chosen extremely according to each user behavior label and Weight Acquisition user characteristics corresponding with the user behavior label
Few user characteristics are as advertisement position audient's feature.It is special that this process not only can obtain user according to user behavior label
Sign, can also be further combined with Weight Acquisition user characteristics corresponding with user behavior label, so that the user got
Feature is more accurate, and then further increases the accuracy for obtaining advertisement position audient feature.
Example IV
Referring to Fig. 4, Fig. 4 is a kind of structural representation of the dispensing control device of advertisement position disclosed by the embodiments of the present invention
Figure.As shown in figure 4, the dispensing control device 400 of the advertisement position may include:
First acquisition unit 401, for obtaining the pre- commercial audience feature for launching advertisement.
As an alternative embodiment, the commercial audience feature that first acquisition unit 401 obtains pre- dispensing advertisement can
To include:
First acquisition unit 401 launches advertisement progress content characteristic analysis to pre-, is analyzed according to content characteristic and extracts pre-cast
Put the key message in the ad data of advertisement；
First acquisition unit 401 obtains subcategory information corresponding with key message, and obtains corresponding with subcategory information
Major category information；Wherein, subcategory information and major category information collectively form merchandise classification information；And key message and commodity
Classification information mapping storage；
First acquisition unit 401 obtains the pre- commercial audience spy for launching advertisement according to major category information and subcategory information
Sign.
As another optional embodiment, first acquisition unit 401 obtains the pre- commercial audience feature for launching advertisement
May include:
First acquisition unit 401 launches advertisement progress content characteristic analysis to pre-, is analyzed according to content characteristic and extracts pre-cast
Put the key message in the ad data of advertisement；
First acquisition unit 401 obtains major category information corresponding with key message, and obtains corresponding with major category information
Subcategory information；Wherein, subcategory information and major category information collectively form merchandise classification information；And key message and commodity
Classification information mapping storage；
First acquisition unit 401 obtains the pre- commercial audience spy for launching advertisement according to major category information and subcategory information
Sign.
By implementing this optional embodiment, can be believed according to the key that the pre- ad data for launching advertisement be included
Breath obtains the merchandise classification information with key message mapping storage, and it is special to obtain the pre- commercial audience for launching advertisement on this basis
Sign, and merchandise classification information includes major category information and subcategory information, thus obtains the advertisement more fully and having levels
Audient's feature improves the precision for obtaining commercial audience feature.
Second acquisition unit 402, for obtaining advertisement position audient's feature of at least one advertisement position.
Determination unit 403, for determining advertisement position from least one advertisement position that second acquisition unit 402 is got
The highest target of the degree of correlation of the commercial audience feature for the pre- dispensing advertisement that audient's feature is got with first acquisition unit 401 is wide
Accuse position.
Unit 404 is launched, for pre- dispensing advertisement to be thrown to the targeted advertisements position that determination unit 403 is determined.
It can wrap as an alternative embodiment, launching unit 404 and pre- dispensing advertisement being thrown to targeted advertisements position
It includes:
Unit 404 is launched according to advertisement position audient's feature of targeted advertisements position, analysis obtains audient's point of targeted advertisements position
Hit the highest target time section of rate, and in the target time section targeted advertisements position the highest targeted advertisements of audient's clicking rate
Form；Wherein, targeted advertisements form can be written form, graphic form, picture and text combining form, audio form and visual form
Any advertisement form in；
It launches unit 404 to adjust pre- dispensing advertisement to targeted advertisements form in the target time section, obtains target pre-cast
Put advertisement；
Target is launched advertisement in advance and is thrown to targeted advertisements position in the target time period by dispensing unit 404.
Mesh can also be further analyzed after determining targeted advertisements position by implementing this optional embodiment
The advertisement position audient feature of advertisement position is marked to choose and launch the pre- target time section and targeted advertisements form for launching advertisement, so that
Pre- dispensing advertisement is thrown to targeted advertisements position according to targeted advertisements form in target time section, this process can be utmostly
Ground obtains the high of audient and clicks, to increase the spread scope of advertisement.
As it can be seen that implementing the dispensing control device of advertisement position described in Fig. 4, commercial audience feature and advertisement can be combined
Position audient's feature may launch advertisement to the advertisement position where the more interested audient of ad content to choose, realize advertisement position
Accurate dispensing, to increase investment in advertising return rate.
Embodiment five
Referring to Fig. 5, Fig. 5 is that another intelligent advertisement position based on big data analysis disclosed by the embodiments of the present invention is launched
The structural schematic diagram of device.Wherein, the intelligent advertisement position delivery device 400 shown in fig. 5 based on big data analysis is by Fig. 4 institute
What the optimization of intelligent advertisement position delivery device 400 based on big data analysis shown obtained, big data analysis is based on shown in Fig. 4
Intelligent advertisement position delivery device 400 compare, the intelligent advertisement position delivery device 400 shown in Fig. 5 based on big data analysis
In, first acquisition unit 401 may include:
Subelement 4011 is extracted, for extracting the main information in pre- dispensing advertisement.
Determine subelement 4012, the main information for extracting according to extraction subelement 4011 determines pre- dispensing advertisement
Ad content.
First obtains subelement 4013, for determine the ad content of pre- dispensing advertisement that subelement 4012 is determined into
The analysis of row content characteristic, obtains several content characteristics, and at least one content characteristic conduct is selected from several content characteristics
The pre- commercial audience feature for launching advertisement, at least one content characteristic are the pre- corresponding body matter of ad content for launching advertisement
Feature.
As an alternative embodiment, the first acquisition subelement 4013 selects at least one from several content characteristics
A content characteristic may include: as the pre- commercial audience feature for launching advertisement
First acquisition subelement 4013 inquires the purchasing power of each content characteristic and commercial audience in initialized data base
Between related coefficient；
First acquisition subelement 4013 filters out the significant content characteristic of related coefficient as object content feature, and according to
The sequence that related coefficient successively decreases is ranked up object content feature；
The first object content feature for obtaining before the selection sequence of subelement 4013 is located at preset quantity is used as pre- dispensing wide
Audient's feature of announcement.
By implementing this optional embodiment, can choose between the purchasing power of commercial audience compared with degree of correlation
High content characteristic is as commercial audience feature, to improve investment in advertising return rate.
Optionally, in the intelligent advertisement position delivery device 400 shown in Fig. 5 based on big data analysis, second obtains list
First 402 include:
Second obtains subelement 4021, for obtaining at least one advertisement position in the location information of media page；And according to
Location information obtains the record of user behavior caused by least one advertisement position.
Analyze subelement 4022, the user behavior of at least one advertisement position for obtaining according to second acquisition unit 4021
Record obtains advertisement position audient's feature of at least one advertisement position.
As it can be seen that implement Fig. 5 described in the intelligent advertisement position delivery device based on big data analysis, can in conjunction with advertisement by
Many features and advertisement position audient's feature may launch extensively the advertisement position where the more interested audient of ad content to choose
It accuses, the accurate dispensing of advertisement position is realized, to increase investment in advertising return rate.
In addition, implementing the intelligent advertisement position delivery device based on big data analysis described in Fig. 5, may be implemented to advertisement
The accurate analysis of content, to improve the accuracy for obtaining commercial audience feature.
In addition, implementing the intelligent advertisement position delivery device based on big data analysis described in Fig. 5, pass through user behavior point
The accuracy for obtaining advertisement position audient feature can be improved in analysis.
Embodiment six
Referring to Fig. 6, Fig. 6 is that another intelligent advertisement position based on big data analysis disclosed by the embodiments of the present invention is launched
The structural schematic diagram of device.Wherein, the intelligent advertisement position delivery device 400 shown in fig. 6 based on big data analysis is by Fig. 5 institute
What the optimization of intelligent advertisement position delivery device 400 based on big data analysis shown obtained, big data analysis is based on shown in fig. 5
Intelligent advertisement position delivery device 400 compare, the intelligent advertisement position delivery device 400 shown in Fig. 6 based on big data analysis
In, analysis subelement 4022 is used to record the advertisement for obtaining at least one advertisement position according to the user behavior of at least one advertisement position
The mode of position audient's feature is specifically as follows:
Subelement 4022 is analyzed, for the user for generating user behavior record at least one advertisement position to be divided into phase
It answers in the user group of advertisement position, obtains the behavior record set of user group, the behavior record set of user group includes in user group
The user behavior of each user records；Respective advertisement is obtained according to the behavior record set of the user group of at least one advertisement position
The user behavior analysis of position is as a result, obtain advertisement position audient's feature of respective advertisement position according to user behavior analysis result.
Optionally, analysis subelement 4022 is used to be obtained according to the behavior record set of the user group of at least one advertisement position
The user behavior analysis of respective advertisement position is as a result, obtain the advertisement position audient spy of respective advertisement position according to user behavior analysis result
The mode of sign is specifically as follows:
Subelement 4022 is analyzed, for the behavior record set according to the user group of at least one advertisement position, is obtained at least
At least one matched user behavior label of the user group of one advertisement position；Statistics generates and at least one user behavior label pair
The user behavior analysis list answered, user behavior analysis list include at least one user behavior label；Calculate user behavior point
Analyse the weight shared in affiliated label classification of at least one user behavior label in list；According at least one user behavior
Label and Weight Acquisition user characteristics corresponding with the user behavior label, and at least one user characteristics is chosen as advertisement
Position audient's feature.
It is further alternative, in the intelligent advertisement position delivery device 400 shown in Fig. 6 based on big data analysis, determine
Unit 403 may include:
First determines subelement 4031, the commercial audience for determining from least one advertisement position with launching advertisement in advance
The advertisement position that feature matches determines that advertisement position audient is special from the first advertisement position set to obtain the first advertisement position set
The highest targeted advertisements position of the degree of correlation of sign and the pre- commercial audience feature for launching advertisement；Alternatively,
Second determines subelement 4032, for selecting the advertisement for being currently at idle state from least one advertisement position
Advertisement position audient feature is determined from the second advertisement position set and launches advertisement in advance to obtain the second advertisement position set in position
The highest targeted advertisements position of the degree of correlation of commercial audience feature.
As it can be seen that implement Fig. 6 described in the intelligent advertisement position delivery device based on big data analysis, can in conjunction with advertisement by
Many features and advertisement position audient's feature may launch extensively the advertisement position where the more interested audient of ad content to choose
It accuses, the accurate dispensing of advertisement position is realized, to increase investment in advertising return rate.
In addition, implementing the intelligent advertisement position delivery device based on big data analysis described in Fig. 6, may be implemented to advertisement
The accurate analysis of content, to improve the accuracy for obtaining commercial audience feature.
In addition, implementing the intelligent advertisement position delivery device based on big data analysis described in Fig. 6, pass through user behavior point
The accuracy for obtaining advertisement position audient feature can be improved in analysis.
In addition, implement the intelligent advertisement position delivery device based on big data analysis described in Fig. 6, it can be according at least one
The behavior record set of the user group of a advertisement position obtains the user behavior analysis of at least one advertisement position as a result, obtaining with this
Advertisement position audient's feature of respective advertisement position further increases the accuracy for obtaining advertisement position audient feature.
In addition, implement Fig. 6 described in the intelligent advertisement position delivery device based on big data analysis, not only can according to
Family behavior label obtain user characteristics, can also further combined with Weight Acquisition user characteristics corresponding with user behavior label,
So that the user characteristics got are more accurate, and then further increase the accuracy for obtaining advertisement position audient feature.
In addition, implement Fig. 6 described in the intelligent advertisement position delivery device based on big data analysis, can first determine with
The advertisement position that the pre- commercial audience feature for launching advertisement matches, it is wide matching with the pre- commercial audience feature for launching advertisement
Accuse the highest targeted advertisements position of the degree of correlation that advertisement position audient feature and the pre- commercial audience feature for launching advertisement are determined in position, contracting
The small range of determining targeted advertisements position, to improve the efficiency of determining targeted advertisements position；Or it can first determine current
The advertisement position being in idle condition, with determine advertisement position audient feature in the advertisement position that is in idle condition and pre- launch advertisement
Commercial audience feature the highest targeted advertisements position of the degree of correlation, the range of determining targeted advertisements position is reduced, to improve
Determine the efficiency of targeted advertisements position.
Embodiment seven
Referring to Fig. 7, Fig. 7 is the structural schematic diagram of a kind of electronic equipment disclosed by the embodiments of the present invention.As shown in fig. 7,
The electronic equipment may include: memory and processor, and memory is stored with computer program, which is characterized in that processor is held
The step of any one intelligent advertisement position put-on method based on big data analysis of FIG. 1 to FIG. 3 is realized when row computer program.
The embodiment of the present invention discloses a kind of computer readable storage medium, stores computer program, wherein the computer
Program makes computer execute any one intelligent advertisement position put-on method based on big data analysis of FIG. 1 to FIG. 3.
A kind of computer program product is also disclosed in the embodiment of the present invention, wherein when computer program product on computers
When operation, so that computer executes some or all of the method in such as above each method embodiment step.
The embodiment of the present invention is also disclosed a kind of using distribution platform, wherein using distribution platform for issuing computer journey
Sequence product, wherein when computer program product is run on computers, so that computer executes such as the above each method embodiment
In some or all of method step.
In various embodiments of the present invention, it should be appreciated that magnitude of the sequence numbers of the above procedures are not meant to execute suitable
Successively, the execution sequence of each process should be determined by its function and internal logic the certainty of sequence, without coping with the embodiment of the present invention
Implementation process constitutes any restriction.
In embodiment provided by the present invention, it should be appreciated that " B corresponding with A " indicates that B is associated with A, can be with according to A
Determine B.It is also to be understood that determine that B is not meant to determine B only according to A according to A, it can also be according to A and/or other information
Determine B.
In addition, each functional unit in various embodiments of the present invention can integrate in one processing unit, it is also possible to
Each unit physically exists alone, and can also be integrated in one unit with two or more units.Above-mentioned integrated unit
Both it can take the form of hardware realization, can also realize in the form of software functional units.
If above-mentioned integrated unit is realized in the form of SFU software functional unit and when sold or used as an independent product,
It can store in a retrievable memory of computer.Based on this understanding, technical solution of the present invention substantially or
Person says all or part of of the part that contributes to existing technology or the technical solution, can be in the form of software products
It embodies, which is stored in a memory, including several requests are with so that a computer is set
Standby (can be personal computer, server or network equipment etc., specifically can be the processor in computer equipment) executes
Some or all of each embodiment above method of the invention step.
Those of ordinary skill in the art will appreciate that all or part of the steps in the various methods of above-described embodiment is can
It is completed with instructing relevant hardware by program, which can be stored in a computer readable storage medium, storage
Medium include read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory,
RAM), programmable read only memory (Programmable Read-only Memory, PROM), erasable programmable is read-only deposits
Reservoir (Erasable Programmable Read Only Memory, EPROM), disposable programmable read-only memory (One-
Time Programmable Read-Only Memory, OTPROM), the electronics formula of erasing can make carbon copies read-only memory
(Electrically-Erasable Programmable Read-Only Memory, EEPROM), CD-ROM (Compact
Disc Read-Only Memory, CD-ROM) or other disc memories, magnetic disk storage, magnetic tape storage or can
For carrying or any other computer-readable medium of storing data.
Above to a kind of intelligent advertisement position put-on method and device based on big data analysis disclosed by the embodiments of the present invention
It is described in detail, used herein a specific example illustrates the principle and implementation of the invention, the above reality
The explanation for applying example is merely used to help understand method and its core concept of the invention；Meanwhile for the general technology of this field
Personnel, according to the thought of the present invention, there will be changes in the specific implementation manner and application range, in conclusion this theory
Bright book content should not be construed as limiting the invention.
Claims (10)
1. a kind of intelligent advertisement position put-on method based on big data analysis characterized by comprising
Obtain the pre- commercial audience feature for launching advertisement；
Obtain advertisement position audient's feature of at least one advertisement position；
The advertisement position audient feature and the pre- commercial audience for launching advertisement are determined from advertisement position described at least one
The highest targeted advertisements position of the degree of correlation of feature；
The pre- dispensing advertisement is thrown to the targeted advertisements position.
2. the method according to claim 1, wherein the pre- commercial audience feature for launching advertisement of the acquisition, packet
It includes:
Extract the pre- main information launched in advertisement；
The pre- ad content for launching advertisement is determined according to the main information；
To it is described it is pre- launch advertisement ad content carry out content characteristic analysis, obtain several content characteristics, from it is described it is several in
Hold and selects at least one content characteristic in feature as the pre- commercial audience feature for launching advertisement, it is described at least one
Holding feature is the pre- corresponding body matter feature of ad content for launching advertisement.
3. method according to claim 1 or 2, which is characterized in that it is described obtain at least one advertisement position advertisement position by
Many features, comprising:
At least one described advertisement position is obtained in the location information of media page；
According to the positional information, the record of user behavior caused by least one described advertisement position is obtained；
The advertisement position audient spy for obtaining at least one advertisement position is recorded according to the user behavior of advertisement position described at least one
Sign.
4. according to the method described in claim 3, it is characterized in that, the user behavior according to advertisement position described at least one
Record obtains advertisement position audient's feature of at least one advertisement position, comprising:
The user that user behavior record was generated at least one described advertisement position is divided into the user group of respective advertisement position,
The behavior record set of the user group is obtained, the behavior record set of the user group includes that each in the user group is used
The user behavior at family records；
The user behavior analysis of respective advertisement position is obtained according to the behavior record set of the user group of advertisement position described at least one
As a result, obtaining advertisement position audient's feature of respective advertisement position according to the user behavior analysis result.
5. according to the method described in claim 4, it is characterized in that, the user group according to advertisement position described at least one
Behavior record set obtains the user behavior analysis of respective advertisement position as a result, obtaining according to the user behavior analysis result corresponding
Advertisement position audient's feature of advertisement position, comprising:
According to the behavior record set of the user group of advertisement position described at least one, the user of at least one advertisement position is obtained
At least one matched user behavior label of group；
Statistics generates user behavior analysis list corresponding at least one described user behavior label, the user behavior analysis
List includes at least one described user behavior label；
It is shared in affiliated label classification to calculate at least one described user behavior label in the user behavior analysis list
Weight；
According at least one described user behavior label and Weight Acquisition user characteristics corresponding with the user behavior label, and
At least one described user characteristics is chosen as the advertisement position audient feature.
6. method according to claim 1 or 2, which is characterized in that described to be determined from advertisement position described at least one
The highest targeted advertisements position of the degree of correlation of advertisement position audient feature and the pre- commercial audience feature for launching advertisement, comprising:
The advertisement position to match with the pre- commercial audience feature for launching advertisement is determined from advertisement position described at least one
To obtain the first advertisement position set, and determine from the first advertisement position set the advertisement position audient feature with it is described pre-
Launch the highest targeted advertisements position of the degree of correlation of the commercial audience feature of advertisement.
7. method according to claim 1 or 2, which is characterized in that described to be determined from advertisement position described at least one
The highest targeted advertisements position of the degree of correlation of advertisement position audient feature and the pre- commercial audience feature for launching advertisement, comprising:
The advertisement position for being currently at idle state is selected from advertisement position described at least one to obtain the second advertisement position set,
And determine that the advertisement position audient feature and the pre- commercial audience for launching advertisement are special from the second advertisement position set
The highest targeted advertisements position of the degree of correlation of sign.
8. a kind of intelligent advertisement position delivery device based on big data analysis characterized by comprising
First acquisition unit, for obtaining the pre- commercial audience feature for launching advertisement；
Second acquisition unit, for obtaining advertisement position audient's feature of at least one advertisement position；
Determination unit, for determining that the advertisement position audient feature and the pre- dispensing are wide from advertisement position described at least one
The highest targeted advertisements position of the degree of correlation of the commercial audience feature of announcement；
Unit is launched, for the pre- dispensing advertisement to be thrown to the targeted advertisements position that the determination unit is determined.
9. a kind of electronic equipment, including memory and processor, the memory are stored with computer program, which is characterized in that
The processor realizes the step of method described in any one of claims 1 to 7 when executing the computer program.
10. a kind of computer readable storage medium, which is characterized in that it stores computer program, and the computer program makes
Computer perform claim requires 1~7 described in any item intelligent advertisement position put-on methods based on big data analysis.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111105269A (en) * | 2019-11-29 | 2020-05-05 | 北京云测信息技术有限公司 | Advertisement putting processing method, device, equipment and storage medium |
| CN111242683A (en) * | 2020-01-10 | 2020-06-05 | 深圳市胜博恩科技有限公司 | Method and device for self-service delivery of advertisement content, storage medium and computer equipment |
| CN113360822A (en) * | 2021-06-03 | 2021-09-07 | 中国联合网络通信集团有限公司 | Activity delivery method, activity delivery device, terminal and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101694714A (en) * | 2009-09-22 | 2010-04-14 | 姚军利 | Precise advertisement delivery system and method |
| CN102637284A (en) * | 2012-02-07 | 2012-08-15 | 深圳市同洲视讯传媒有限公司 | Intelligent advertisement delivery system and method |
| CN106169140A (en) * | 2016-02-02 | 2016-11-30 | 华扬联众数字技术股份有限公司 | Advertisement placement method and system |
| CN106920128A (en) * | 2017-03-03 | 2017-07-04 | 加和（北京）信息科技有限公司 | A kind of advertisement placement method, business platform and system |
-
2018
- 2018-08-22 CN CN201810960788.9A patent/CN109345280A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101694714A (en) * | 2009-09-22 | 2010-04-14 | 姚军利 | Precise advertisement delivery system and method |
| CN102637284A (en) * | 2012-02-07 | 2012-08-15 | 深圳市同洲视讯传媒有限公司 | Intelligent advertisement delivery system and method |
| CN106169140A (en) * | 2016-02-02 | 2016-11-30 | 华扬联众数字技术股份有限公司 | Advertisement placement method and system |
| CN106920128A (en) * | 2017-03-03 | 2017-07-04 | 加和（北京）信息科技有限公司 | A kind of advertisement placement method, business platform and system |
Non-Patent Citations (2)
| Title |
|---|
| 青岛英谷教育科技股份有限公司: "《电子商务管理与运营》", 31 May 2012, 西安电子科技大学出版社, pages: 256 - 260 * |
| 高德: "《超级IP：互联网时代的跨界营销》", 30 September 2016, 中国出版集团现代出版社, pages: 105 - 112 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111105269A (en) * | 2019-11-29 | 2020-05-05 | 北京云测信息技术有限公司 | Advertisement putting processing method, device, equipment and storage medium |
| CN111105269B (en) * | 2019-11-29 | 2023-05-26 | 北京云测信息技术有限公司 | Advertisement delivery processing method, device, equipment and storage medium |
| CN111242683A (en) * | 2020-01-10 | 2020-06-05 | 深圳市胜博恩科技有限公司 | Method and device for self-service delivery of advertisement content, storage medium and computer equipment |
| CN113360822A (en) * | 2021-06-03 | 2021-09-07 | 中国联合网络通信集团有限公司 | Activity delivery method, activity delivery device, terminal and storage medium |
| CN113360822B (en) * | 2021-06-03 | 2023-06-20 | 中国联合网络通信集团有限公司 | Activity release method, device, terminal and storage medium |
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