CN109922358A - A kind of IPTV advertisement scheduling method considering replay times - Google Patents
A kind of IPTV advertisement scheduling method considering replay times Download PDFInfo
- Publication number
- CN109922358A CN109922358A CN201910250138.XA CN201910250138A CN109922358A CN 109922358 A CN109922358 A CN 109922358A CN 201910250138 A CN201910250138 A CN 201910250138A CN 109922358 A CN109922358 A CN 109922358A
- Authority
- CN
- China
- Prior art keywords
- advertisement
- user
- iptv
- program
- period
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention proposes a kind of IPTV advertisement scheduling method for considering replay times, comprising the following steps: following advertisement inventory is predicted according to original user click data；According to the relationship between user's buying intention and advertisement number of repetition, advertisement maximum number of repetitions is determined；Define the system parameter of IPTV advertisement scheduling model；Establish the IPTV advertisement scheduling Optimized model for influencing user's quantity purchase；Integral linear programming model is improved to the IPTV advertisement scheduling Optimized model of foundation；The supply volume in IPTV advertisement scheduling Optimized model under period dimension and program dimension is calculated, IPTV advertisement scheduling scheme is formed.The method of the invention maximizes advertisement when carrying out IPTV advertisement scheduling and launches the quantity purchase promoted, can bring economic well-being of workers and staff as big as possible for media companies, increase the income of advertiser, have good realistic meaning.
Description
Technical field
The present invention relates to IPTV (Internet protocol television, Internet Protocol Television) technical field,
A kind of more particularly to IPTV advertisement scheduling method for considering replay times.
Background technique
IPTV (Internet Protocol Television) i.e. Interactive Internet TV, by broadband cable network
It can be provided very well using the abundant program that CHINA RFTCOM Co Ltd provides as transmission medium using household common TV as display terminal
Source provides a user high quality, high interactive digital media service.At the same time, it is also mentioned to advertiser, network operator etc.
Market is supplied.Therefore how to break for commercialsy that miscellaneous advertisement is allowed effectively to be broadcast to user with very in IPTV
Important realistic meaning.
The process of existing IPTV advertisement scheduling method: IPTV Web TV company first can be according to the click data of user
Predict that (period angle is play time, and program angle is program category, and example is dynamic for acquisition period angle and program angle
Unrestrained, TV play) following advertisement inventory.Subsequent IPTV Web TV company can according to the advertisement inventory that prediction obtains to advertisement into
Row presell, advertiser can claim to exposure frequency, broadcast time, programme content, to form the contract of intention.IPTV net
Network TV and Radio Corporation is scheduled throwing according to three broadcasting period, program path and supply volume dimensions in the demand order of advertiser
It puts.That is IPTV Web TV company considers that the advertisement inventory of period angle is each to dispatch according to total supply volume of advertiser
A spending on ads for playing the period.Finally according to advertiser's program path demand, (i.e. advertiser needs to launch to target group
Advertisement, such as snacks brand specify children's programs, animation product), Web TV company is allocated each broadcasting period
Spending on ads is redistributed to different program paths.
In traditional IPTV advertisement scheduling, IPTV Web TV company and advertiser only focus on advertisement and always launch number
Amount number, it is believed that more in the supply volume for playing period and program path dispatching, advertiser can be created by advertisement
More economics well-being of workers and staff are made, but are had ignored for each spectators, different advertisement numbers of repetition is to generate different shadows
Loud.According to the conclusion of psychologist obtained to the analysis of many experiments object, when advertisement number of repetition is less, viewing time
The purchase that several increases can improve spectators is attempted, but when user repeats to see the number arrival certain amount of the same advertisement,
Boredom will be generated, and with the raising of viewing quantity, boredom also be will increase, buying intention can be risen inhibit instead
Effect.
Summary of the invention
To solve the above-mentioned problems of the prior art, the present invention proposes a kind of IPTV advertisement scheduling for considering replay times
Method is that advertiser carries out IPTV advertisement scheduling in IPTV Web TV company on the basis of taking into account advertiser's dispensing demand
When, the calculation method of IPTV advertisement scheduling is improved, calculating spectators are added and watch this factor of the number of repetition of advertisement, to dispensing
Quantity carries out reasonable distribution.
To realize the above-mentioned technical purpose, the invention adopts the following technical scheme:
A kind of IPTV advertisement scheduling method considering replay times, includes the following steps:
Step 1:IPTV Web TV company predicts following advertisement inventory according to original user click data；
Step 2: assuming first that in the method, when user's buying intention is greater than a certain determination value K, (K value is by city, company
The investigation of field department and estimation), user will generate buying behavior to the corresponding commodity of the advertisement.And according to user's buying intention with
Relationship between advertisement number of repetition determines advertisement maximum number of repetitions；
Step 3: defining the system parameter of IPTV advertisement scheduling model；
Step 4: establishing the IPTV advertisement scheduling Optimized model for influencing user's quantity purchase；
Step 5: integral linear programming model is improved to the IPTV advertisement scheduling Optimized model of foundation；
Step 6: calculating IPTV advertisement scheduling seismic responses calculated and go out the supply volume under period dimension and program dimension, i.e.,
IPTV advertisement scheduling scheme.
Further, in step 2, the relationship between user's buying intention and advertisement number of repetition is
Wherein, x indicates advertisement number of repetition, and PI indicates buying intention, g, b, and c, d are coefficient constant；
Number of repetition is usedIt indicates, buying intention PIauIt indicates, so buying intention and decision variable
xatpBetween functional relation are as follows:
Maximum number of repetitions Q be greater thanFirst positive integer, ε be it is one infinitely small
Number.
Further, in step S4, in IPTV advertisement scheduling Optimized model,
It maximizes quantity purchase and is expressed as formula
The influence of consideration is constrained to a1, a2, a3, a4, a5, wherein
Influence constraint a1: in period dimension, the practical quantity launched of advertisement is equal with the demand of advertiser, this relationship
It can be expressed as:
Influence constraint a2: in program dimension, the practical quantity launched of advertisement is equal with the demand of advertiser, this relationship
It can be expressed as:
It influences constraint a3: its click volume in the period mesh is no more than for total number of ads that each user launches,
This relationship can be expressed as:
It influences constraint a4: each advertisement a and is no more than Q to each user u supply volume, this relationship can be expressed as:
Influence constraint a5: defined variable sauIf PIau>=0-K, then sau=1, otherwise sau=0, i.e., advertisement to
The effect at family has reached a certain degree, will generate purchase, does not reach and does not just buy, is write as segmented version are as follows:
Or it indicates are as follows:
Influence constraint a6: for no distribution period and section destination locations, enabling the number of ads of distribution is 0, this relationship
It can be expressed as:
Further, step 5 specifically:
By PIauExpression formula bring into step 4 influence constraint a5, obtain formula (5.1)
For any K, have uniqueIt is corresponding to it, formula (5.1) is transformed into following formula:
SeparatelyFormula (5.2) abbreviation is
Constraint a5 is influenced in step 4 to be written as
Compared with the prior art, new method of the present invention maximizes advertisement when carrying out IPTV advertisement scheduling and launches the purchase promoted
Quantity is bought, this new IPTV advertisement scheduling method still can bring economic well-being of workers and staff as big as possible for media companies, simultaneously
The income of advertiser is also added, there is good realistic meaning.
Attached drawing table explanation
Fig. 1 is that the method for the invention calculates step schematic diagram；
Fig. 2 is that buying intention and advertisement number of repetition functional arrangement are quoted in the present invention；
Fig. 3 is advertisement putting quantity Service Efficiency in the case of two kinds of specific embodiment in the present invention；
Fig. 4 is that specific embodiment does not consider that the program of number of repetition launches distribution map in the present invention；
Fig. 5 is that specific embodiment considers that the program of number of repetition launches distribution map in the present invention.
Specific embodiment
To make the purpose of the present invention, technical solution and advantage are more clearly understood, and following specific embodiments are to the present invention
Further details of explanation.
As shown in Figure 1, a kind of IPTV advertisement scheduling method for considering replay times, includes the following steps:
Step 1:IPTV Web TV company predicts following advertisement inventory according to original user click data；
Step 2: the effectiveness indicator of advertisement number of repetition is the buying intention of user.In the present invention, it is assumed that when purchase
(K value is investigated and estimated by houses market department) when intention is greater than a certain determination value K is bought, user will be to the corresponding quotient of the advertisement
Product generate buying behavior.And according to the relationship between user's buying intention and advertisement number of repetition, determine that advertisement maximum repeats
Number；
Relationship between user's buying intention and advertisement number of repetition are as follows:
Wherein, x indicates advertisement number of repetition, and PI indicates buying intention, g, b, and c, d are coefficient constant, by acquisition number, ring
The interference of the factors such as border.
In the present invention, number of repetition is usedIt indicates, buying intention PIauIndicate, thus buying intention with certainly
Plan variable xatpBetween functional relation are as follows:
By obtaining the relational graph between buying intention and number of repetition as shown in fig. 2, it can be seen that with number of repetition
Increase, buying intention gradually increases, and limit is successively decreased, and when reaching maximum number of repetitions Q, buying intention levels off to one
Stationary value g+b.By the analysis to function, which can be substantially equal to maximum value, and never reach.Here Q meaning
Buying intention increase when being further added by for value caused by it is an infinitesimal several ε, the relationship between them are as follows:
The following are the obtaining value methods of Q value:
In addition, f (Q+1)-f (Q)≤ε then has:
b(1+e(c-d*Q))-b(1+e(c-d*(Q+1)))≤ε(1+e(c-d*Q))(1+e(c-d*(Q+1)))
Due to (1+e(c-d*Q))(1+e(c-d*(Q+1))) close to 1, therefore above equation can be written as:
b(1+e(c-d*Q))-b(1+e(c-d*(Q+1)))≤ε
be(c-d*Q)-be(c-d*(Q+1))≤ε
be(c-d*Q)(1-e-d)≤ε
Since d is greater than 0, so 1-e-dGreater than 0, obtain:
c-dQ≤lnε-lnb(1-e-d)
Since advertisement number of repetition must be integer, thus Q be greater thanFirst just
Integer, by the influence of coefficient b, c, d and ε.
Quantity purchase is finally maximized, formula can be expressed as
Step 3: define the system parameter of IPTV advertisement scheduling model:
A, u, t, p: advertisement number, Customs Assigned Number, when segment number, program code；
A, U, T, P: advertising aggregator, user's set, period set, program set；
m,n,Ma,Na: period packet numbering, program packet numbering, advertisement a specified period grouping set, advertisement a are specified
Program grouping set；
The period for including in the period grouping that the number that wide main a is required is m gathers, wherein m ∈ Ma；
The program set for including in the program grouping that the number that advertisement a is required is n, wherein n ∈ Na；
Ta: the set for all periods that advertisement a is required, wherein
Pa: all section destination aggregation (mda)s that advertisement a is required, wherein
Advertisement a requires the number of ads launched in the period grouping that number is m, wherein m ∈ Ma；
Advertisement a requires the number of ads launched in the program grouping that number is n, wherein n ∈ Na；
futp: each user u period t program p program request quantity；
Q: for an advertisement, to the maximum quantity of each user dispensing；
K: the buying intention threshold value of user's generation buying behavior；
W: one infinitely great positive number；
xautp: decision variable, advertisement a gives user u the practical number of ads launched in period t program p, for not specifying
Period and program, then the distribution number of ads defaulted be 0；
sau: intermediate variable indicates whether user u produces buying behavior to the corresponding commodity of advertisement a, no if being then 1
It is then 0；
PIau: intermediate variable, buying intention of the user u to advertisement a corresponding goods.
Step 4: establish the IPTV advertisement scheduling Optimized model for influencing user's quantity purchase:
Subject to
Step 5: integral linear programming model is improved to the IPTV advertisement scheduling Optimized model of foundation；
By PIauExpression formula bring into step 4 influence constraint a5, obtain formula (5.1)
Due to being all g, b, c, d, K constant, Yi Faxian has unique any KIt is corresponding to it.
Formula (5.1) can be transformed into following formula:
SeparatelyFormula (5.2) abbreviation is
It can be written as to influence constraint a5 in step 4
Step 6: calculating IPTV advertisement scheduling seismic responses calculated and go out the supply volume under period dimension and program dimension, i.e.,
IPTV advertisement scheduling scheme；
One shares 8 advertisements, 24 periods, 20 programs, 93 users in model case of the present invention, wherein altogether including 8
Period grouping and 12 program groupings.The present invention is directed to maximize advertisement scheduling model of the quantity purchase as target, is based on
The real data that certain IPTV Web TV company provides calls CPLEX to solve with MATLAB, and the problem used time two minutes or so
Find out optimal solution.
Result is divided from four supply volume Service Efficiency, period angle, program angle, quantity purchase angles below
Analysis.
(1) Service Efficiency
As shown in figure 3, each advertisement is real in 8 advertisements when considering number of repetition and not considering two kinds of number of repetition
The ratio of number of ads and quantity required that border is launched, i.e. supply volume Service Efficiency.It is whole in figure as can be seen that in the case of two kinds
Body Service Efficiency is consistent, and can all have the advertisement Service Efficiency of half is 100%, is fully satisfied.And most number of ads
Service Efficiency 80% or more.Wherein, the advertisement Service Efficiency that number is 2 and 4 is relatively low, especially No. 2 advertisements, or even discontented
20%, these publicity orders are that media companies bring economic well-being of workers and staff is extremely limited, in the case where quantity resource is certain, advertisement
Main can choose abandons signing this two orders, and leaves this partial amt for other orders to create bigger economic benefit
And social benefit.
Meanwhile in both cases, there are also little bit differents for Service Efficiency.It can be found that part does not consider the wide of number of repetition
Service Efficiency is accused than considering the slightly lower of number of repetition.
(2) quantity purchase
User's quantity purchase in the case of 3 two kinds of table
For each advertisement, in the case of two kinds shown in the purchase situation of user table 3 as above.It can be found that for different wide
For announcement, quantity purchase is different.In conjunction with Fig. 2, it can be found that the advertisement Service Efficiency that number is 2 is relatively low, and user buys number
It measures smaller.
In the case where not considering number of repetition, total quantity purchase is 79.It is total in the case where considering number of repetition
Quantity purchase be 81.Despite the presence of certain advertisements do not consider advertisement repeat when the more situation of quantity purchase, but from
Generally, total advertisement quantity purchase is compared and does not consider to increased when advertisement number of repetition.To demonstrate the model
Feasibility.
Number of repetition in the case of 4 two kinds of table
Table 4 is the advertisement number statistics launched in the case of the advertisement that number is 5 and 8 is two kinds to the user for having buying behavior
Table.When considering number of repetition, the number launched for each user for having buying behavior is 3 times, and 3 times here are experiment
Middle supply volume threshold k1, it is most suitable advertisement impressions.When not considering that advertisement repeats, then the quantity launched is greater than etc.
In 3 times, or even the quantity having both will cause the waste of advertising resource in this way, and can also cause the bored feelings of user much larger than 3 times
Thread.By observing the advertisement of other numbers, similarly there is above situation for discovery.
By the research above to quantity purchase and number of repetition, it can sum up and not consider that the Service Efficiency of number of repetition omits
It is following possible higher than having the reason of considering duplicate Service Efficiency: first, because the target of two problems is not consistent, do not considering
In the advertisement scheduling model of number of repetition, for not meeting advertiser's aggregate demand the case where introduces promise breaking punishment, so meeting
Meet the quantity demand of advertiser as much as possible；Second, in the result for not considering number of repetition, it need to only meet the number of advertiser
Amount demand causes to launch certain user a kind of situation that number of ads is too many it is not intended that the viewing of user is experienced, and
When considering advertisement number of repetition, the limitation that each user watches quantity has also been taken into account while meeting advertiser's quantitative requirement,
Reasonable utilization resource is accomplished.
(3) period angle
In both cases, 8 advertisements are specified launches period demand and corresponding quantitative requirement as shown in table 5, table 6,
Wherein actual packet quantity and substantial amt amount are the advertisement putting quantities that the final finishing solve obtains.Here each advertisement
The grouping of only one period.
Table 5 does not consider 8 ad break demand schedules when number of repetition
Table 6 considers 8 ad break demand schedules when number of repetition
In spite of replay times are considered, the advertisement putting quantity that number is 2 is all very low namely what first part discussed expires
Sufficient rate is relatively low, as discussed earlier, should not sign publicity orders, and should leave this partial amt for other and order
It is single.By observing the input situation of period, discovery has all launched advertisement to designated position, and non-designated position is not launched.
In addition, when thering are 3 advertisements not consider that the supply volume of number of repetition slightly above considers number of repetition, although full in this way
Sufficient rate is relatively high, but is found by the analysis to number of repetition, there is the situation excessive to some user's supply volume, this
Sample can reduce advertising results instead.
(4) program angle
Under both of these case, 8 advertisements are specified to launch program demand and corresponding quantitative requirement as shown in table 7, table 8,
Wherein actual packet quantity and substantial amt amount are the advertisement putting quantities that the final finishing solve obtains.
Table 7 does not consider 8 advertising programme demand schedules when number of repetition
Table 8 considers 8 advertising programme demand schedules when number of repetition
It is the same with period result, there are 3 advertisements to consider that the supply volume of numbers of repetition is slightly less than when not considering number of repetition.
By observing the input situation of program, discovery has all launched advertisement to designated position, and non-designated position is not launched.
For the advertisement that number is 1 and number is 3, its total quantity Service Efficiency known to first part is relatively high, but saves
The Service Efficiency that mesh is grouped n3, n6 is very low.In order to further understand program input situation, program is thrown in the case of having made two kinds
Distribution map is put, as shown in Figure 4,5.In the dispensing demand of this 8 advertisements, the number of programs being related in total is 20, by two
Figure is it can be seen that be all launched advertisement.
Comparison diagram 5, it can be found that the distribution of the program of Fig. 4 is relatively concentrated.For numbering the advertisement for being 7, this is wide
Announcement has an advertisement packet n11, and it includes above 20 programs that advertiser specifies program grouping altogether, launches 69 advertisements altogether.
In the result for considering advertisement number of repetition, No. 7 advertisements have launched 12 programs altogether, without only launching in the result of consideration
6 programs although meeting the requirement of total quantity can not reach advertising results expected from advertiser.
The considerations of by data and actual conditions, the reason of such case occur is in the result for not considering number of repetition
In, it need to only meet the quantitative requirement of advertiser, can't consider the viewing impression of user, cause to certain program dispensing
Quantity is excessive, and in addition program seldom or is then 0.In the case where considering the factor, it may be desirable to which more users touch
Advertisement.Under normal circumstances, different user likes the program difference of viewing, launches advertisement to more programs, there will be more
User has seen the advertisement, and when watched time reaches a certain value, the buying intention of user will reach buying intention threshold value, at this moment
User can generate buying behavior.
Operating bring enlightenment to practice to the above analysis for launching result is that the advertisement polyisomenism of media is very general
Time, but be not the advertising results that unlimited number of repetition has just centainly had, it, can be based on the click row of user in actually launching
To launch suitable number to it.
Claims (4)
1. a kind of IPTV advertisement scheduling method for considering replay times, which comprises the steps of:
Step 1: following advertisement inventory is predicted according to original user click data；
Step 2: according to the relationship between user's buying intention and advertisement number of repetition, determining advertisement maximum number of repetitions；
Step 3: defining the system parameter of IPTV advertisement scheduling model；
Step 4: establishing the IPTV advertisement scheduling Optimized model for influencing user's quantity purchase；
Step 5: integral linear programming model is improved to the IPTV advertisement scheduling Optimized model of foundation；
Step 6: calculating the supply volume in IPTV advertisement scheduling Optimized model under period dimension and program dimension, it is wide to form IPTV
Accuse scheduling scheme.
2. the method according to claim 1, wherein in step 2,
Relationship between user's buying intention and advertisement number of repetition is
Wherein, x indicates advertisement number of repetition, and PI indicates buying intention, g, b, and c, d are coefficient constant；
Number of repetition is usedIt indicates, buying intention PIauIt indicates, so buying intention and decision variable xatpIt
Between functional relation are as follows:
Maximum number of repetitions Q be greater thanFirst positive integer, ε be one it is infinitesimal
Number.
3. the method according to claim 1, wherein in step S4, in IPTV advertisement scheduling Optimized model,
It maximizes quantity purchase and is expressed as formula
The influence of consideration is constrained to a1, a2, a3, a4, a5, wherein
Influence constraint a1: in period dimension, the practical quantity launched of advertisement is equal with the demand of advertiser, and this relationship can be with
Expression are as follows:
Influence constraint a2: in program dimension, the practical quantity launched of advertisement is equal with the demand of advertiser, and this relationship can be with
Expression are as follows:
It influences constraint a3: its click volume in the period mesh is no more than for total number of ads that each user launches, it is this
Relationship can be expressed as:
It influences constraint a4: each advertisement a and is no more than Q to each user u supply volume, this relationship can be expressed as:
Influence constraint a5: defined variable sauIf PIau>=0-K, then sau=1, otherwise sau=0, i.e., advertisement is to user's
Effect has reached a certain degree, will generate purchase, does not reach and does not just buy, is write as segmented version are as follows:
Or it indicates are as follows:
Influence constraint a6: for no distribution period and section destination locations, enabling the number of ads of distribution is 0, and this relationship can be with
Expression are as follows:
In formula, a, u, t, p: advertisement number, Customs Assigned Number, when segment number, program code；
A, U, T, P: advertising aggregator, user's set, period set, program set；
m,n,Ma,Na: period packet numbering, program packet numbering, advertisement a specified period grouping set, advertisement a specified section
Mesh grouping set；
The period for including in the period grouping that the number that wide main a is required is m gathers, wherein m ∈ Ma；
The program set for including in the program grouping that the number that advertisement a is required is n, wherein n ∈ Na；
Ta: the set for all periods that advertisement a is required, wherein
Pa: all section destination aggregation (mda)s that advertisement a is required, wherein
Advertisement a requires the number of ads launched in the period grouping that number is m, wherein m ∈ Ma；
Advertisement a requires the number of ads launched in the program grouping that number is n, wherein n ∈ Na；
futp: each user u period t program p program request quantity；
Q: for an advertisement, to the maximum quantity of each user dispensing；
K: the buying intention threshold value of user's generation buying behavior；
W: one infinitely great positive number；
xautp: decision variable, advertisement a give user u the practical number of ads launched in period t program p, for do not specify when
Section and program, then the distribution number of ads defaulted are 0；
sau: intermediate variable, indicate user u whether buying behavior is produced to the corresponding commodity of advertisement a, if then be 1, otherwise for
0；
PIau: intermediate variable, buying intention of the user u to advertisement a corresponding goods.
4. according to the method described in claim 3, it is characterized in that, step 5 specifically:
By PIauExpression formula bring into step 4 influence constraint a5, obtain formula (5.1)
For any K, have uniqueIt is corresponding to it, formula (5.1) is transformed into following formula:
SeparatelyFormula (5.2) abbreviation is
Constraint a5 is influenced in step 4 to be written as
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910250138.XA CN109922358B (en) | 2019-03-29 | 2019-03-29 | IPTV advertisement scheduling method considering rebroadcast times |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910250138.XA CN109922358B (en) | 2019-03-29 | 2019-03-29 | IPTV advertisement scheduling method considering rebroadcast times |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109922358A true CN109922358A (en) | 2019-06-21 |
| CN109922358B CN109922358B (en) | 2020-12-08 |
Family
ID=66967713
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910250138.XA Active CN109922358B (en) | 2019-03-29 | 2019-03-29 | IPTV advertisement scheduling method considering rebroadcast times |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109922358B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110390567A (en) * | 2019-07-25 | 2019-10-29 | 秒针信息技术有限公司 | A kind of information methods of exhibiting, device, electronic equipment and readable storage medium storing program for executing |
| CN111401970A (en) * | 2020-04-09 | 2020-07-10 | 东风小康汽车有限公司重庆分公司 | Advertisement pushing method, device and system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070168254A1 (en) * | 2005-06-01 | 2007-07-19 | Google Inc. | Media Play Optimization |
| US20110010231A1 (en) * | 2001-12-14 | 2011-01-13 | Price William P | Audiovisual system and method for displaying segmented advertisements tailored to the characteristic viewing preferences of a user |
| CN102592235A (en) * | 2011-12-28 | 2012-07-18 | 北京品友互动信息技术有限公司 | Internet advertisement serving system |
| CN104469426A (en) * | 2014-12-01 | 2015-03-25 | 中国联合网络通信集团有限公司 | Scheduling method and system for multi-media video-on-demand content |
| CN107578287A (en) * | 2017-09-07 | 2018-01-12 | 北京奇虎科技有限公司 | The frequency control method and device of advertisement putting |
-
2019
- 2019-03-29 CN CN201910250138.XA patent/CN109922358B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110010231A1 (en) * | 2001-12-14 | 2011-01-13 | Price William P | Audiovisual system and method for displaying segmented advertisements tailored to the characteristic viewing preferences of a user |
| US20070168254A1 (en) * | 2005-06-01 | 2007-07-19 | Google Inc. | Media Play Optimization |
| CN102592235A (en) * | 2011-12-28 | 2012-07-18 | 北京品友互动信息技术有限公司 | Internet advertisement serving system |
| CN104469426A (en) * | 2014-12-01 | 2015-03-25 | 中国联合网络通信集团有限公司 | Scheduling method and system for multi-media video-on-demand content |
| CN107578287A (en) * | 2017-09-07 | 2018-01-12 | 北京奇虎科技有限公司 | The frequency control method and device of advertisement putting |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110390567A (en) * | 2019-07-25 | 2019-10-29 | 秒针信息技术有限公司 | A kind of information methods of exhibiting, device, electronic equipment and readable storage medium storing program for executing |
| CN111401970A (en) * | 2020-04-09 | 2020-07-10 | 东风小康汽车有限公司重庆分公司 | Advertisement pushing method, device and system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109922358B (en) | 2020-12-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10748174B1 (en) | Frequency optimization of advertisement insertion in media streams | |
| McPhillips et al. | Media convergence and the evolving media business model: An overview and strategic opportunities | |
| Napoli | The audience as product, consumer, and producer in the contemporary media marketplace | |
| JP6179866B2 (en) | How to set frequency limit for addressable content | |
| Nixon et al. | AI for audience prediction and profiling to power innovative TV content recommendation services | |
| US20100114664A1 (en) | Method And System For Developing And Evaluating And Marketing Products Through Use Of Intellectual Capital Derivative Rights | |
| WO2010049745A1 (en) | Audience measurement system | |
| CN109922358A (en) | A kind of IPTV advertisement scheduling method considering replay times | |
| Picard et al. | Platform proliferation and its implications for domestic content policies | |
| Luo et al. | The factors influencing sales in online celebrities' live streaming | |
| McKenzie et al. | Netflix chills and revamps its viewing metrics: Preliminary analysis and opportunities for research | |
| Ibrus et al. | Quantifying public value creation by public service media using big programming data | |
| Berte et al. | Opportunities of interactive formats for innovative advertising on digital television | |
| US20060248014A1 (en) | Method and system for scheduling tracking, adjudicating appointments and claims in a health services environmentand broadcasters | |
| James et al. | An examination of television consumption by racial and ethnic audiences in the us: Implications for multicultural media planning and media measurement | |
| Stiernstedt | Maximizing the power of entertainment. The audience commodity in contemporary radio | |
| Weber | Digitizing the dragon: challenges facing China's broadcasting industry | |
| Cho et al. | We want our MTV: glocalisation of cable content in China, Korea and Japan | |
| Yang | The introduction of South Korean reality shows in the Chinese market | |
| Zhu | The digital broadcasting culture in transition | |
| Saroso et al. | New Media Business: Converging ICT and Terrestrial Free To Air Television Business | |
| Calderón et al. | Distaste for Advertisements in Two-Sided Markets: Evidence from Free-to-Air TV | |
| Fernández-Robin et al. | Twitch Consumer Behavior and the Importance of Streaming Habits | |
| Xie et al. | Empirical analysis of factors influencing box office revenue of imported animated films: Based on data from 281 films from 2000 to 2023 | |
| Zhanga et al. | The Local Service Solution: A Business Transformation of Traditional Media Companies |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| EE01 | Entry into force of recordation of patent licensing contract | ||
| EE01 | Entry into force of recordation of patent licensing contract |
Application publication date: 20190621 Assignee: Zhejiang Taineng Technology Industry Co.,Ltd. Assignor: HANGZHOU DIANZI University Contract record no.: X2022980022905 Denomination of invention: An IPTV Advertising Scheduling Method Considering the Number of Replays Granted publication date: 20201208 License type: Common License Record date: 20221124 |