CN107103485A - It is a kind of that method and system is recommended according to the automatic advertising of movie theatre visitor information - Google Patents
It is a kind of that method and system is recommended according to the automatic advertising of movie theatre visitor information Download PDFInfo
- Publication number
- CN107103485A CN107103485A CN201710007725.7A CN201710007725A CN107103485A CN 107103485 A CN107103485 A CN 107103485A CN 201710007725 A CN201710007725 A CN 201710007725A CN 107103485 A CN107103485 A CN 107103485A
- Authority
- CN
- China
- Prior art keywords
- mrow
- msub
- visitor
- movie theatre
- advertisement
- 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
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
- G06Q30/0261—Targeted advertisements based on user location
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
- G06Q30/0269—Targeted advertisements based on user profile or attribute
- G06Q30/0271—Personalized advertisement
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Accounting & Taxation (AREA)
- Development Economics (AREA)
- Strategic Management (AREA)
- Finance (AREA)
- Game Theory and Decision Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a kind of according to the automatic advertising of movie theatre visitor information recommendation method and system, including step：Merchant advertisement information is obtained, and merchant advertisement information is classified；The visitor's identity information of the movie theatre in following certain period of time is obtained, the visitor's identity information includes any one of age, location, sex or multinomial；Obtain the consumption information data of the user of different identity；According to the consumption information data of the user of the visitor's identity information of movie theatre and different identity in following certain period of time, it is determined that the visitor of movie theatre is to the interest-degrees of different advertisements in following certain period of time；According to interest-degree of the visitor of the movie theatre in following certain period of time to different advertisements, calculate in the advertising results for pushing different advertisements in following certain period of time in movie theatre；According to obtained advertising results, in following certain period of time in movie theatre advertisement.The present invention can lift the level of intelligence of advertisement recommendation, and the advertisement being adapted under big data background is recommended.
Description
Technical field
The invention discloses a kind of according to the automatic advertising of movie theatre visitor information recommendation method and system, it is related to calculating advertisement
Learn technical field.
Background technology
In past 5 years Chinese Digital motion picture screen quantity in rapid growth, the five-year will keep growing trend, it is contemplated that
Screen number is up to 50,000 pieces within 2019.Box office total value steady-state growth, it is contemplated that by 2019, the big screen advertisement annual income total value in the whole nation
Up to 6,500,000,000.
At present, the ad system of movie theatre is utilized to the personal information of the advertising objective crowd of following certain period of time and not enough filled
Point.Advertising results still have the space of larger lifting.
The content of the invention
The technical problems to be solved by the invention are that providing a kind of automatic advertising recommends method and system, for solving mesh
The ad system of preceding movie theatre is due to the problem of the personal information on advertising objective crowd influences advertising results using not abundant enough.
To achieve the above objectives there is provided a kind of according to the automatic advertising of movie theatre visitor information recommendation method and system.This
The technical scheme of the embodiment of invention is as follows：
The embodiments of the invention provide a kind of according to the automatic advertising of movie theatre visitor information recommendation method, including following step
Suddenly：
Step 101：Merchant advertisement information is obtained, and merchant advertisement information is classified；
Step 102：The visitor's identity information of the movie theatre in following certain period of time is obtained, the visitor's identity information includes
Any one of age, location, sex are multinomial；
Step 103：Obtain the consumption information data of the user of different identity；
Step 104：According in following certain period of time the user of the visitor's identity information of movie theatre and different identity disappear
Charge information data, it is determined that the visitor of movie theatre is to the interest-degrees of different advertisements in following certain period of time；
Step 105：According to interest-degree of the visitor of the movie theatre in following certain period of time to different advertisements, calculated in future
The advertising results of different advertisements are pushed in certain period of time in movie theatre；
Step 106：According to obtained advertising results, in following certain period of time in movie theatre advertisement.
In one embodiment, the step 102 includes：
The movie ticket ordering information of the movie theatre is obtained from movie theatre seat reservation system, the movie ticket ordering information includes movie ticket correspondence
Film reproduction time and buy the subscriber identity information of the movie ticket, the film reproduction time is in following certain period of time
Interior, the subscriber identity information includes any one of age, location, sex or multinomial；
The subscriber identity information is defined as the visitor's identity information.
In one embodiment, the consumption information data in step 103, during comprising age, location, sex, consumption
Between, consumption area and consumption any one of content or multinomial.
In one embodiment, step 104 includes:
Interest-degree of the visitor to different advertisements of the movie theatre in following certain period of time is calculated according to the first calculation formula；
First calculation formula is：
Wherein, RUIFor interest-degrees of visitor's classification U to advertisement classification I, its value is represented in U class visitors to I between 0-1
The ratio between total number of persons of series advertisements number interested and U class visitors；PUkRepresent interest-degrees of visitor's classification U to potential classification k；
QkIThe weight shared by advertisement classification I in potential classification k is represented, weight is higher, and advertisement classification I, which is got over, can be expressed as the potential classification；
After the number of potential classification is specified, potential classification is obtained by computer by counting automatic cluster；Visitor's classification U is by visitor's body
Part information is determined；RUIThe consumption information data for the visitor that middle partial data passes through different identity are determined；Remainder data are by PUk
And QkICalculating is obtained；PUkAnd QkIObtained by minimizing loss function, the loss function is：
Wherein, C is loss function, and S is by RUIThe part of middle determination and the part composition of random sampling assignment, λ is regularization
The factor, can be by repeatedly testing acquisition.
In one embodiment, step 105 includes:
Calculated according to the second calculation formula in the advertising results for pushing different advertisements in following certain period of time in movie theatre；
Second calculation formula is：
Wherein, EF (I) represents advertisement classification I advertising results；N is the sum of visitor's classification, SGN () function representation variable
Sign symbol, RUIInterest-degree of the people to advertisement I of U classes is represented, its value is between 0-1, PUFor the number of U class visitors, δ
For adjustable interest-degree threshold value, the expression advertisement that interest-degree is higher than this value is preferable to its effect；α and β is adjustable regulatory factor,
Represent the influence in non-crowd interested of non-linear effects and advertisement of crowd's quantity respectively, α be more than or equal to 1, β be more than 0 and
It is more than 0 and less than 1 less than 1+ δ or β.
The embodiments of the invention provide a kind of automatic advertising commending system according to movie theatre visitor information, the system includes：
Advertising message processing module, for obtaining merchant advertisement information and classifying to merchant advertisement information；
Visitor information processing module, the visitor's identity information for obtaining the movie theatre in following certain period of time, the visit
Objective identity information includes any one of age, location, sex or multinomial；
Consumption information processing module, the consumption information data of the user for obtaining different identity；
Interest-degree computing module, for the visitor's identity information and different identity according to the movie theatre in following certain period of time
User consumption information data, it is determined that the visitor of movie theatre is to the interest-degrees of different advertisements in following certain period of time；
Advertising results computing module, for interest of the visitor according to the movie theatre in following certain period of time to different advertisements
Degree, is calculated in the advertising results for pushing different advertisements in following certain period of time in movie theatre；
Advertisement pushing module, for according to obtained advertising results, in following certain period of time in movie theatre advertisement.
In one embodiment,
Visitor information processing module, the movie ticket ordering information for obtaining the movie theatre from movie theatre seat reservation system, the shadow
Ticket ordering information includes the corresponding film reproduction time of movie ticket and buys the subscriber identity information of the movie ticket, and the film is played
Time is in following certain period of time, and the subscriber identity information includes any one of age, location, sex or many
；The subscriber identity information is defined as the visitor's identity information.
In one embodiment, the consumption information data, include age, location, sex, consumption time, consumption
Any one of region and consumption content are multinomial.
In one embodiment, the interest-degree computing module, for being calculated according to the first calculation formula following certain
Interest-degree of the visitor of movie theatre to different advertisements in period；
First calculation formula is：
Wherein, RUIFor interest-degrees of visitor's classification U to advertisement classification I, its value is represented in U class visitors to I between 0-1
The ratio between total number of persons of series advertisements number interested and U class visitors；PUkRepresent interest-degrees of visitor's classification U to potential classification k；
QkIThe weight shared by advertisement classification I in potential classification k is represented, weight is higher, and advertisement classification I, which is got over, can be expressed as the potential classification；
After the number of potential classification is specified, potential classification is obtained by computer by counting automatic cluster；Visitor's classification U is by visitor's body
Part information is determined；RUIThe consumption information data for the visitor that middle partial data passes through different identity are determined；Remainder data are by PUk
And QkICalculating is obtained；PUkAnd QkIObtained by minimizing loss function, the loss function is：
Wherein, C is loss function, and S is by RUIThe part of middle determination and the part composition of random sampling assignment, λ is regularization
The factor, can be by repeatedly testing acquisition.
In one embodiment, advertising results computing module, for being calculated according to the second calculation formula in the timing of future one
Between in movie theatre push the advertising results of different advertisements in section；
Second calculation formula is：
Wherein, EF (I) represents advertisement classification I advertising results；N is the sum of visitor's classification, SGN () function representation variable
Sign symbol, RUIInterest-degree of the people to advertisement I of U classes is represented, its value is between 0-1, PUFor the number of U class visitors, δ
For adjustable interest-degree threshold value, the expression advertisement that interest-degree is higher than this value is preferable to its effect；α and β is adjustable regulatory factor,
Represent the influence in non-crowd interested of non-linear effects and advertisement of crowd's quantity respectively, α be more than or equal to 1, β be more than 0 and
It is more than 0 and less than 1 less than 1+ δ or β.
The above method provided in an embodiment of the present invention, can shift to an earlier date Accurate Prediction which advertisement in following certain period of time
Preferable advertising results can be realized when movie theatre is pushed so that can push this in movie theatre in time in following certain period of time
A little advertisements, improve the advertising results of movie theatre advertisement.
Brief description of the drawings
Fig. 1 is the flow chart that automatic advertising according to embodiments of the present invention recommends method；
Fig. 2 is the schematic diagram of automatic advertising commending system according to embodiments of the present invention.
Embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, it is right below in conjunction with drawings and Examples
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
Fig. 1 is the flow chart that a kind of automatic advertising according to embodiments of the present invention recommends method.
In step 101, merchant advertisement information is obtained, and classified.Merchant advertisement information based on trade classification information,
Such as it is by ad classification：Cultural medium, the vehicles, food and drink, electronics computer, real estate, telecommunications service, banking and insurance business,
Fashion, airline travel, retail service etc..More detailed impression of classifying is better.In one embodiment of the invention, businessman is wide
Accuse information and be divided into cultural medium, the vehicles, electronics computer, real estate.
In step 102, the visitor's identity information of the movie theatre in following certain period of time is obtained, visitor's identity information includes year
Any one of age, location, sex are multinomial.It is, of course, also possible to including other identity informations, such as name.
In one embodiment, step 102 can be embodied as following steps A1-A2：
Step A1, the movie ticket ordering information from movie theatre seat reservation system acquisition movie theatre, movie ticket ordering information include movie ticket correspondence
Film reproduction time and purchase movie ticket subscriber identity information, film reproduction time is in following certain period of time, user
Identity information includes any one of age, location, sex or multinomial；
Step A2, above-mentioned subscriber identity information is defined as above-mentioned visitor's identity information.
At present, movie theatre has corresponding movie theatre seat reservation system, and user can realize the telecommunication network in movie theatre seat reservation system
Booking, movie theatre seat reservation system can be stored with the subscriber identity information of each user and the unique identities identification code such as mobile phone of the user
Number.When a user buys movie ticket by movie theatre seat reservation system, the user need to provide unique identities to movie theatre seat reservation system
Identification code, so that movie theatre seat reservation system can know the subscriber identity information of the user according to the unique identities identification code received,
And can record the corresponding film reproduction time of movie ticket that the user is bought.Movie theatre seat reservation system can be by the user identity of the user
Information film reproduction time corresponding with the movie ticket that the user is bought, is stored as movie ticket Ticketing information.
It has purchased in the user for the film movie ticket played in following certain period of time in a movie theatre, can be considered in following certain
The visitor occurred in period in the movie theatre.
In step 103：Obtain the consumption information data of the user of different identity.
When obtaining consumption information data, the consumption information data of the user of movie theatre region can be obtained, such as without movie theatre
The consumption information data of the user of region, may be selected the consumption information number of the user in the region close with movie theatre region
According to consumption information data can include any one of age, location, sex, consumption time, consumption area and consumption content
Or it is multinomial.Movie theatre region can be with city, area, county, small towns or street where movie theatre；Can also be centered on movie theatre
The default kilometer range of circumference in region, preset milimeter number and can be set, for example, may be configured as 20 kilometers of circumference.
In step 104：According to the user of the visitor's identity information of movie theatre and different identity in following certain period of time
Consumption information data, it is determined that the visitor of movie theatre is to the interest-degrees of different advertisements in following certain period of time.
In one embodiment, step 104 can be embodied as：Calculated according to the first calculation formula in following certain period of time
Interest-degree of the visitor of movie theatre to different advertisements；
First calculation formula is：
Wherein, RUIFor interest-degrees of visitor's classification U to advertisement classification I, its value is represented in U class visitors to I between 0-1
The ratio between total number of persons of series advertisements number interested and U class visitors；PUkRepresent interest-degrees of visitor's classification U to potential classification k；
QkIThe weight shared by advertisement classification I in potential classification k is represented, weight is higher, and advertisement classification I, which is got over, can be expressed as the potential classification；
After the number of potential classification is specified, potential classification is obtained by computer by counting automatic cluster；Visitor's classification U is by visitor's body
Part information is determined；RUIThe consumption information data for the visitor that middle partial data passes through different identity are determined；Remainder data are by PUk
And QkICalculating is obtained；PUkAnd QkIObtained by minimizing loss function, the loss function is：
Wherein, C is loss function, and S is by RUIThe part of middle determination and the part composition of random sampling assignment, λ is regularization
The factor, can be by repeatedly testing acquisition.
In another embodiment, step 104 can also be replaced by following operating procedure：Obtained from outside database
Interest-degree of the visitor prestored to different advertisements.
In step 105：According to interest-degree of the visitor of the movie theatre in following certain period of time to different advertisements, calculate in not
Carry out the advertising results in the different advertisements of movie theatre push in certain period of time.
In one embodiment, step 105 can be embodied as：Calculated according to the second calculation formula in following certain period of time
The advertising results of different advertisements are pushed in movie theatre；
Second calculation formula is：
Wherein, EF (I) represents advertisement classification I advertising results；N is the sum of visitor's classification, SGN () function representation variable
Sign symbol, RUIInterest-degree of the people to advertisement I of U classes is represented, its value is between 0-1, PUFor the number of U class visitors, δ
For adjustable interest-degree threshold value, the expression advertisement that interest-degree is higher than this value is preferable to its effect；α and β is adjustable regulatory factor,
α is more than or equal to 1, β and is more than 0 and is more than 0 and less than 1 less than 1+ δ or β, represent respectively crowd's quantity non-linear effects and
Influence of the advertisement in non-crowd interested.
In step 106：According to obtained advertising results, in following certain period of time in movie theatre advertisement.
In one embodiment, advertising results highest or advertising results can be reached to the advertisement of preset standard, in
Pushed in following certain period of time in movie theatre.Can be that any in movie theatre can be in the equipment of releasing advertisements during push
Push, for example, play the TV or electricity on self-help ticket-buying machine, the self ticket taking machine in the screen of film, movie theatre, movie theatre interior wall
Sub- display screen etc..
The above method provided in an embodiment of the present invention, can shift to an earlier date Accurate Prediction which advertisement in following certain period of time
Preferable advertising results can be realized when movie theatre is pushed so that can push this in movie theatre in time in following certain period of time
A little advertisements, improve the advertising results of movie theatre advertisement.
One embodiment of the present of invention is as follows：
In step 201, merchant advertisement information is obtained, and classified.
For example, merchant advertisement information is classified as：Cultural medium, the vehicles, electronics computer, real estate.
In step 202：Obtain the visitor's identity information of the movie theatre in following certain period of time.
For example, current time is on November 15th, 2016, movie theatre is the sturdy pines movie theatre positioned at Beijing, and the movie theatre is 2016
On November 17,9 in:00 to 12:00 this period (i.e. following certain period of time), play film《The midfield war of Billy's woods grace
Thing》, by abovementioned steps A1-A2, it is informed in 17 days 9 November in 2016:00 to 12:Sturdy pines shadow is appeared in 00 this period
The statistics of the visitor's identity information of institute is：
15-25 Sui：100 people
26-35 Sui：200 people
36-45 Sui：50 people
In step 203：Obtain the consumption information data of the user of different identity.
For example, sturdy pines movie theatre region is taken as Chaoyang District, Beijing City, from certain shopping website, Chaoyang District, Beijing City is obtained
The data of the user of interior each age group commodity of interest are：
| Concern number accounting | Cultural medium | The vehicles | Electronics computer | Real estate |
| 15-25 Sui | It is unknown | 0.2 | 0.75 | It is unknown |
| 26-35 Sui | 0.2 | It is unknown | It is unknown | 0.35 |
| 36-45 Sui | 0.3 | It is unknown | It is unknown | 0.3 |
In step 204：According to the user of the visitor's identity information of movie theatre and different identity in following certain period of time
Consumption information data, it is determined that the visitor of movie theatre is to the interest-degrees of different advertisements in following certain period of time.
It can such as be calculated according to foregoing first calculation formula：
| RUI | Cultural medium | The vehicles | Electronics computer | Real estate |
| 15-25 Sui | 0.1 | 0.2 | 0.75 | 0.2 |
| 26-35 Sui | 0.2 | 0.5 | 0.6 | 0.35 |
| 36-45 Sui | 0.3 | 0.5 | 0.3 | 0.3 |
In step 205：According to interest-degree of the visitor of the movie theatre in following certain period of time to different advertisements, calculate in not
Carry out the advertising results in the different advertisements of movie theatre push in certain period of time.
δ=0.15, α=1, β=0.1 in foregoing second calculation formula is set, can be with using foregoing second calculation formula
Try to achieve the advertising results of different advertisements：
In step 206：According to obtained advertising results, in following certain period of time in movie theatre advertisement.Due to electricity
The advertising results of sub- computer product are preferable, so in following certain period of time, the computer advertisement of electronics is pushed in movie theatre.
Fig. 2 is a kind of schematic diagram of automatic advertising commending system according to embodiments of the present invention；
Included according to a kind of automatic advertising commending system of the present invention：
Advertising message processing module 301, for obtaining merchant advertisement information and classifying to merchant advertisement information；Visitor
Message processing module 302, for obtaining merchant advertisement information and classifying to merchant advertisement information；Consumption information processing module
303, the consumption information data of the user for obtaining different identity；Interest-degree computing module 304, for according to following certain
The consumption information data of the user of the visitor's identity information of movie theatre and different identity in period, it is determined that in following certain period of time
Interest-degree of the visitor of interior movie theatre to different advertisements；Advertising results computing module 305, for according in following certain period of time
The visitor of movie theatre is calculated in the advertisement effect for pushing different advertisements in following certain period of time in movie theatre the interest-degree of different advertisements
Really；Advertisement pushing module 306, for according to obtained advertising results, in following certain period of time in movie theatre advertisement.
Visitor information processing module 302, the movie ticket ordering information for obtaining the movie theatre from movie theatre seat reservation system is described
Movie ticket ordering information includes the corresponding film reproduction time of movie ticket and buys the subscriber identity information of the movie ticket, and the film is broadcast
Putting the time is in following certain period of time, the subscriber identity information include any one of age, location, sex or
It is multinomial；The subscriber identity information is defined as the visitor's identity information.
The consumption information data, comprising in age, location, sex, consumption time, consumption area and consumption content
Any one or multinomial.
The interest-degree computing module 304, for calculating the movie theatre in following certain period of time according to the first calculation formula
Visitor to the interest-degrees of different advertisements；
First calculation formula is：
Wherein, RUIFor interest-degrees of visitor's classification U to advertisement classification I, its value is represented in U class visitors to I between 0-1
The ratio between total number of persons of series advertisements number interested and U class visitors；PUkRepresent interest-degrees of visitor's classification U to potential classification k；
QkIThe weight shared by advertisement classification I in potential classification k is represented, weight is higher, and advertisement classification I, which is got over, can be expressed as the potential classification；
After the number of potential classification is specified, potential classification is obtained by computer by counting automatic cluster；Visitor's classification U is by visitor's body
Part information is determined；RUIThe consumption information data for the visitor that middle partial data passes through different identity are determined；Remainder data are by PUk
And QkICalculating is obtained；PUkAnd QkIObtained by minimizing loss function, the loss function is：
Wherein, C is loss function, and S is by RUIThe part of middle determination and the part composition of random sampling assignment, λ is regularization
The factor, can be by repeatedly testing acquisition.
Wherein, advertising results computing module 305, for according to the second calculation formula calculate in following certain period of time
Movie theatre pushes the advertising results of different advertisements；
Second calculation formula is：
Wherein, EF (I) represents advertisement classification I advertising results；N is the sum of visitor's classification, SGN () function representation variable
Sign symbol, RUIInterest-degree of the people to advertisement I of U classes is represented, its value is between 0-1, PUFor the number of U class visitors, δ
For adjustable interest-degree threshold value, the expression advertisement that interest-degree is higher than this value is preferable to its effect；α and β is adjustable regulatory factor,
Represent the influence in non-crowd interested of non-linear effects and advertisement of crowd's quantity respectively, α be more than or equal to 1, β be more than 0 and
It is more than 0 and less than 1 less than 1+ δ or β.
Using the above-mentioned desirable embodiment according to the present invention as enlightenment, pass through above-mentioned description, ordinary skill
Personnel can carry out various changes and amendments without departing from the scope of the technological thought of the present invention' completely.This invention
Technical scope be not limited to content on specification, it is necessary to its technical model is determined according to right
Enclose.
Claims (10)
1. a kind of recommend method according to the automatic advertising of movie theatre visitor information, it is characterised in that comprises the following steps：
Step 101：Merchant advertisement information is obtained, and merchant advertisement information is classified；
Step 102：The visitor's identity information of the movie theatre in following certain period of time is obtained, the visitor's identity information includes year
Any one of age, location, sex are multinomial；
Step 103：Obtain the consumption information data of the user of different identity；
Step 104：According to the consumption letter of the user of the visitor's identity information of movie theatre and different identity in following certain period of time
Data are ceased, it is determined that the visitor of movie theatre is to the interest-degrees of different advertisements in following certain period of time；
Step 105：According to interest-degree of the visitor of the movie theatre in following certain period of time to different advertisements, calculate in following certain
The advertising results of different advertisements are pushed in period in movie theatre；
Step 106：According to obtained advertising results, in following certain period of time in movie theatre advertisement.
2. according to the method described in claim 1, it is characterised in that the step 102 includes：
The movie ticket ordering information of the movie theatre is obtained from movie theatre seat reservation system, the movie ticket ordering information includes the corresponding electricity of movie ticket
Shadow reproduction time and the subscriber identity information for buying the movie ticket, the film reproduction time are in following certain period of time,
The subscriber identity information includes any one of age, location, sex or multinomial；
The subscriber identity information is defined as the visitor's identity information.
3. the method as described in claim 1, it is characterised in that
Consumption information data in step 103, comprising in age, location, sex, consumption time, consumption area and consumption
Any one of appearance is multinomial.
4. according to the method described in claim 1, it is characterised in that step 104 includes:
Interest-degree of the visitor to different advertisements of the movie theatre in following certain period of time is calculated according to the first calculation formula；
First calculation formula is：
<mrow>
<msub>
<mi>R</mi>
<mrow>
<mi>U</mi>
<mi>I</mi>
</mrow>
</msub>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>K</mi>
</munderover>
<msub>
<mi>P</mi>
<mrow>
<mi>U</mi>
<mi>k</mi>
</mrow>
</msub>
<msub>
<mi>Q</mi>
<mrow>
<mi>k</mi>
<mi>I</mi>
</mrow>
</msub>
</mrow>
Wherein, RUIFor interest-degrees of visitor's classification U to advertisement classification I, its value represents wide to I classes in U class visitors between 0-1
The ratio between total number of persons of announcement number interested and U class visitors；PUkRepresent interest-degrees of visitor's classification U to potential classification k；QkITable
Show the weight shared by advertisement classification I in potential classification k, weight is higher, and advertisement classification I, which is got over, can be expressed as the potential classification；Work as finger
After the number of fixed potential classification, potential classification is obtained by computer by counting automatic cluster；Visitor's classification U is believed by visitor's identity
Breath is determined；RUIThe consumption information data for the visitor that middle partial data passes through different identity are determined；Remainder data are by PUkAnd QkI
Calculating is obtained；PUkAnd QkIObtained by minimizing loss function, the loss function is：
<mrow>
<mi>C</mi>
<mo>=</mo>
<munder>
<mi>&Sigma;</mi>
<mrow>
<mo>(</mo>
<mi>U</mi>
<mo>,</mo>
<mi>I</mi>
<mo>)</mo>
<mo>&Element;</mo>
<mi>S</mi>
</mrow>
</munder>
<msup>
<mrow>
<mo>(</mo>
<mrow>
<msub>
<mi>R</mi>
<mrow>
<mi>U</mi>
<mi>I</mi>
</mrow>
</msub>
<mo>-</mo>
<munderover>
<mi>&Sigma;</mi>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>K</mi>
</munderover>
<msub>
<mi>P</mi>
<mrow>
<mi>U</mi>
<mi>k</mi>
</mrow>
</msub>
<msub>
<mi>Q</mi>
<mrow>
<mi>k</mi>
<mi>I</mi>
</mrow>
</msub>
</mrow>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>+</mo>
<mi>&lambda;</mi>
<mrow>
<mo>(</mo>
<mrow>
<mfrac>
<mn>1</mn>
<msup>
<mi>&lambda;</mi>
<mn>2</mn>
</msup>
</mfrac>
<mo>+</mo>
<munder>
<mi>&Sigma;</mi>
<mrow>
<mo>(</mo>
<mi>U</mi>
<mo>,</mo>
<mi>I</mi>
<mo>)</mo>
<mo>&Element;</mo>
<mi>S</mi>
</mrow>
</munder>
<msup>
<msub>
<mi>P</mi>
<mrow>
<mi>U</mi>
<mi>k</mi>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<munder>
<mi>&Sigma;</mi>
<mrow>
<mo>(</mo>
<mi>U</mi>
<mo>,</mo>
<mi>I</mi>
<mo>)</mo>
<mo>&Element;</mo>
<mi>S</mi>
</mrow>
</munder>
<msup>
<msub>
<mi>Q</mi>
<mrow>
<mi>k</mi>
<mi>I</mi>
</mrow>
</msub>
<mn>2</mn>
</msup>
</mrow>
<mo>)</mo>
</mrow>
</mrow>
Wherein, C is loss function, and S is by RUIThe part of middle determination and the part composition of random sampling assignment, λ is regularization factors,
Can be by repeatedly testing acquisition.
5. according to the method described in claim 1, it is characterised in that step 105 includes:
Calculated according to the second calculation formula in the advertising results for pushing different advertisements in following certain period of time in movie theatre；
Second calculation formula is：
<mrow>
<mi>E</mi>
<mi>F</mi>
<mrow>
<mo>(</mo>
<mi>I</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mi>&Sigma;</mi>
<mrow>
<mi>U</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<mo>{</mo>
<mo>&lsqb;</mo>
<mfrac>
<mn>1</mn>
<mn>2</mn>
</mfrac>
<mo>+</mo>
<mrow>
<mo>(</mo>
<mfrac>
<mn>1</mn>
<mn>2</mn>
</mfrac>
<mo>)</mo>
</mrow>
<mo>&times;</mo>
<mi>S</mi>
<mi>G</mi>
<mi>N</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>R</mi>
<mrow>
<mi>U</mi>
<mi>I</mi>
</mrow>
</msub>
<mo>-</mo>
<mi>&delta;</mi>
<mo>)</mo>
</mrow>
<mo>&rsqb;</mo>
<mo>&CenterDot;</mo>
<mrow>
<mo>(</mo>
<msup>
<msub>
<mi>P</mi>
<mi>U</mi>
</msub>
<mi>&alpha;</mi>
</msup>
<mo>&CenterDot;</mo>
<mo>(</mo>
<mrow>
<mn>1</mn>
<mo>+</mo>
<msub>
<mi>R</mi>
<mrow>
<mi>U</mi>
<mi>I</mi>
</mrow>
</msub>
</mrow>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mo>&lsqb;</mo>
<mfrac>
<mn>1</mn>
<mn>2</mn>
</mfrac>
<mo>+</mo>
<mrow>
<mo>(</mo>
<mfrac>
<mn>1</mn>
<mn>2</mn>
</mfrac>
<mo>&times;</mo>
<mi>S</mi>
<mi>G</mi>
<mi>N</mi>
<mo>(</mo>
<mi>&delta;</mi>
<mo>-</mo>
<msub>
<mi>R</mi>
<mrow>
<mi>U</mi>
<mi>I</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>&rsqb;</mo>
<mo>&CenterDot;</mo>
<mi>&beta;</mi>
<mo>&CenterDot;</mo>
<msub>
<mi>P</mi>
<mi>U</mi>
</msub>
<mo>)</mo>
<mo>}</mo>
</mrow>
Wherein, EF (I) represents advertisement classification I advertising results；N is the sum of visitor's classification, and SGN () function representation variable is just
Minus symbol, RUIInterest-degree of the people to advertisement I of U classes is represented, its value is between 0-1, PUFor the number of U class visitors, δ is can
The interest-degree threshold value of tune, interest-degree is preferable to its effect higher than the expression advertisement of this value；α and β is adjustable regulatory factor, respectively
Influence of the non-linear effects and advertisement of expression crowd's quantity in non-crowd interested, α is more than or equal to 1, β and is more than 0 and less than 1
+ δ or β is more than 0 and less than 1.
6. a kind of automatic advertising commending system according to movie theatre visitor information, it is characterised in that the system includes：
Advertising message processing module, for obtaining merchant advertisement information and classifying to merchant advertisement information；
Visitor information processing module, the visitor's identity information for obtaining the movie theatre in following certain period of time, visitor's body
Part information includes any one of age, location, sex or multinomial；
Consumption information processing module, the consumption information data of the user for obtaining different identity；
Interest-degree computing module, for the use according to the visitor's identity information of movie theatre and different identity in following certain period of time
The consumption information data at family, it is determined that the visitor of movie theatre is to the interest-degrees of different advertisements in following certain period of time；
Advertising results computing module, for interest-degree of the visitor according to the movie theatre in following certain period of time to different advertisements,
Calculate in the advertising results for pushing different advertisements in following certain period of time in movie theatre；
Advertisement pushing module, for according to obtained advertising results, in following certain period of time in movie theatre advertisement.
7. system according to claim 6, it is characterised in that
The visitor information processing module, the movie ticket ordering information for obtaining the movie theatre from movie theatre seat reservation system, the shadow
Ticket ordering information includes the corresponding film reproduction time of movie ticket and buys the subscriber identity information of the movie ticket, and the film is played
Time is in following certain period of time, and the subscriber identity information includes any one of age, location, sex or many
；The subscriber identity information is defined as the visitor's identity information.
8. system according to claim 6, it is characterised in that
The consumption information data, include appointing in age, location, sex, consumption time, consumption area and consumption content
One or more.
9. system according to claim 6, it is characterised in that
The interest-degree computing module, the visitor couple for calculating the movie theatre in following certain period of time according to the first calculation formula
The interest-degree of different advertisements；
First calculation formula is：
<mrow>
<msub>
<mi>R</mi>
<mrow>
<mi>U</mi>
<mi>I</mi>
</mrow>
</msub>
<mo>=</mo>
<munderover>
<mo>&Sigma;</mo>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>K</mi>
</munderover>
<msub>
<mi>P</mi>
<mrow>
<mi>U</mi>
<mi>k</mi>
</mrow>
</msub>
<msub>
<mi>Q</mi>
<mrow>
<mi>k</mi>
<mi>I</mi>
</mrow>
</msub>
</mrow>
Wherein, RUIFor interest-degrees of visitor's classification U to advertisement classification I, its value represents wide to I classes in U class visitors between 0-1
The ratio between total number of persons of announcement number interested and U class visitors；PUkRepresent interest-degrees of visitor's classification U to potential classification k；QkITable
Show the weight shared by advertisement classification I in potential classification k, weight is higher, and advertisement classification I, which is got over, can be expressed as the potential classification；Work as finger
After the number of fixed potential classification, potential classification is obtained by computer by counting automatic cluster；Visitor's classification U is believed by visitor's identity
Breath is determined；RUIThe consumption information data for the visitor that middle partial data passes through different identity are determined；Remainder data are by PUkAnd QkI
Calculating is obtained；PUkAnd QkIObtained by minimizing loss function, the loss function is：
<mrow>
<mi>C</mi>
<mo>=</mo>
<munder>
<mi>&Sigma;</mi>
<mrow>
<mo>(</mo>
<mi>U</mi>
<mo>,</mo>
<mi>I</mi>
<mo>)</mo>
<mo>&Element;</mo>
<mi>S</mi>
</mrow>
</munder>
<msup>
<mrow>
<mo>(</mo>
<mrow>
<msub>
<mi>R</mi>
<mrow>
<mi>U</mi>
<mi>I</mi>
</mrow>
</msub>
<mo>-</mo>
<munderover>
<mi>&Sigma;</mi>
<mrow>
<mi>k</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>K</mi>
</munderover>
<msub>
<mi>P</mi>
<mrow>
<mi>U</mi>
<mi>k</mi>
</mrow>
</msub>
<msub>
<mi>Q</mi>
<mrow>
<mi>k</mi>
<mi>I</mi>
</mrow>
</msub>
</mrow>
<mo>)</mo>
</mrow>
<mn>2</mn>
</msup>
<mo>+</mo>
<mi>&lambda;</mi>
<mrow>
<mo>(</mo>
<mrow>
<mfrac>
<mn>1</mn>
<msup>
<mi>&lambda;</mi>
<mn>2</mn>
</msup>
</mfrac>
<mo>+</mo>
<munder>
<mi>&Sigma;</mi>
<mrow>
<mo>(</mo>
<mi>U</mi>
<mo>,</mo>
<mi>I</mi>
<mo>)</mo>
<mo>&Element;</mo>
<mi>S</mi>
</mrow>
</munder>
<msup>
<msub>
<mi>P</mi>
<mrow>
<mi>U</mi>
<mi>k</mi>
</mrow>
</msub>
<mn>2</mn>
</msup>
<mo>+</mo>
<munder>
<mi>&Sigma;</mi>
<mrow>
<mo>(</mo>
<mi>U</mi>
<mo>,</mo>
<mi>I</mi>
<mo>)</mo>
<mo>&Element;</mo>
<mi>S</mi>
</mrow>
</munder>
<msup>
<msub>
<mi>Q</mi>
<mrow>
<mi>k</mi>
<mi>I</mi>
</mrow>
</msub>
<mn>2</mn>
</msup>
</mrow>
<mo>)</mo>
</mrow>
</mrow>
Wherein, C is loss function, and S is by RUIThe part of middle determination and the part composition of random sampling assignment, λ is regularization factors,
Can be by repeatedly testing acquisition.
10. system according to claim 6, it is characterised in that
The advertising results computing module, for according to the second calculation formula calculate in following certain period of time movie theatre push
The advertising results of different advertisements；
Second calculation formula is：
<mrow>
<mi>E</mi>
<mi>F</mi>
<mrow>
<mo>(</mo>
<mi>I</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<munderover>
<mi>&Sigma;</mi>
<mrow>
<mi>U</mi>
<mo>=</mo>
<mn>1</mn>
</mrow>
<mi>N</mi>
</munderover>
<mo>{</mo>
<mo>&lsqb;</mo>
<mfrac>
<mn>1</mn>
<mn>2</mn>
</mfrac>
<mo>+</mo>
<mrow>
<mo>(</mo>
<mfrac>
<mn>1</mn>
<mn>2</mn>
</mfrac>
<mo>)</mo>
</mrow>
<mo>&times;</mo>
<mi>S</mi>
<mi>G</mi>
<mi>N</mi>
<mrow>
<mo>(</mo>
<msub>
<mi>R</mi>
<mrow>
<mi>U</mi>
<mi>I</mi>
</mrow>
</msub>
<mo>-</mo>
<mi>&delta;</mi>
<mo>)</mo>
</mrow>
<mo>&rsqb;</mo>
<mo>&CenterDot;</mo>
<mrow>
<mo>(</mo>
<msup>
<msub>
<mi>P</mi>
<mi>U</mi>
</msub>
<mi>&alpha;</mi>
</msup>
<mo>&CenterDot;</mo>
<mo>(</mo>
<mrow>
<mn>1</mn>
<mo>+</mo>
<msub>
<mi>R</mi>
<mrow>
<mi>U</mi>
<mi>I</mi>
</mrow>
</msub>
</mrow>
<mo>)</mo>
<mo>)</mo>
</mrow>
<mo>+</mo>
<mo>&lsqb;</mo>
<mfrac>
<mn>1</mn>
<mn>2</mn>
</mfrac>
<mo>+</mo>
<mrow>
<mo>(</mo>
<mfrac>
<mn>1</mn>
<mn>2</mn>
</mfrac>
<mo>&times;</mo>
<mi>S</mi>
<mi>G</mi>
<mi>N</mi>
<mo>(</mo>
<mi>&delta;</mi>
<mo>-</mo>
<msub>
<mi>R</mi>
<mrow>
<mi>U</mi>
<mi>I</mi>
</mrow>
</msub>
<mo>)</mo>
</mrow>
<mo>&rsqb;</mo>
<mo>&CenterDot;</mo>
<mi>&beta;</mi>
<mo>&CenterDot;</mo>
<msub>
<mi>P</mi>
<mi>U</mi>
</msub>
<mo>)</mo>
<mo>}</mo>
</mrow>
Wherein, EF (I) represents advertisement classification I advertising results；N is the sum of visitor's classification, and SGN () function representation variable is just
Minus symbol, RUIInterest-degree of the people to advertisement I of U classes is represented, its value is between 0-1, PUFor the number of U class visitors, δ is can
The interest-degree threshold value of tune, interest-degree is preferable to its effect higher than the expression advertisement of this value；α and β is adjustable regulatory factor, respectively
Influence of the non-linear effects and advertisement of expression crowd's quantity in non-crowd interested, α is more than or equal to 1, β and is more than 0 and less than 1
+ δ or β is more than 0 and less than 1.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710007725.7A CN107103485B (en) | 2017-01-05 | 2017-01-05 | Automatic advertisement recommendation method and system according to cinema visitor information |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710007725.7A CN107103485B (en) | 2017-01-05 | 2017-01-05 | Automatic advertisement recommendation method and system according to cinema visitor information |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107103485A true CN107103485A (en) | 2017-08-29 |
| CN107103485B CN107103485B (en) | 2020-12-25 |
Family
ID=59676481
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710007725.7A Expired - Fee Related CN107103485B (en) | 2017-01-05 | 2017-01-05 | Automatic advertisement recommendation method and system according to cinema visitor information |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107103485B (en) |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107798567A (en) * | 2017-11-21 | 2018-03-13 | 成都高德唯斯科技股份有限公司 | Brand message method for pushing, device and electronic equipment |
| CN108460125A (en) * | 2018-02-26 | 2018-08-28 | 影核（北京）网络科技有限公司 | A method of carrying out displaying labeling classification for movie theatre user |
| CN108766278A (en) * | 2018-05-15 | 2018-11-06 | 三星电子（中国）研发中心 | A kind of electronic guide board method for information display and device |
| CN109118270A (en) * | 2018-07-12 | 2019-01-01 | 北京猫眼文化传媒有限公司 | A kind of data extraction method and device |
| CN111695009A (en) * | 2019-03-11 | 2020-09-22 | 浙江莲荷科技有限公司 | Information display method and device |
| CN112333483A (en) * | 2020-10-27 | 2021-02-05 | 北京智能广宣科技有限公司 | Intelligent adjustment method and system for cinema advertisement play list |
| CN112767015A (en) * | 2021-01-07 | 2021-05-07 | 上海鸿研物流技术有限公司 | Information charging method and system based on logistics appliances |
| CN113269594A (en) * | 2021-06-08 | 2021-08-17 | 绍兴市壹点通传媒有限公司 | Cinema advertisement management method and system based on big data |
| CN113781124A (en) * | 2020-09-18 | 2021-12-10 | 北京智能广宣科技有限公司 | Intelligent adjustment method for cinema advertisement play list |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1413329A (en) * | 1999-08-13 | 2003-04-23 | 电影播放公司 | System and method for digitally providing and displaying advertisement information to cinemas and theaters |
| CN1864161A (en) * | 2003-09-03 | 2006-11-15 | Google公司 | Determining and/or using location information in an ad system |
| US20100042501A1 (en) * | 2008-08-12 | 2010-02-18 | Hsiu-Ling Lee | Method and apparatus for controlling content within a network |
| CN101951441A (en) * | 2010-09-16 | 2011-01-19 | 中国联合网络通信集团有限公司 | Mobile telephone advertisement delivery method and equipment |
| CN102201187A (en) * | 2010-03-23 | 2011-09-28 | 深圳华北工控股份有限公司 | Method for directionally advertising |
| CN102640514A (en) * | 2009-06-22 | 2012-08-15 | 西恩沃尔有限公司 | Method for interactive digital cinema system |
| CN103218729A (en) * | 2012-01-18 | 2013-07-24 | 现代自动车株式会社 | Method for providing advertisement based on location and system for providing advertisement |
| CN105303998A (en) * | 2014-07-24 | 2016-02-03 | 北京三星通信技术研究有限公司 | Method, device and equipment for playing advertisements based on inter-audience relevance information |
| CN105355158A (en) * | 2015-11-12 | 2016-02-24 | 日立电梯（中国）有限公司 | Elevator advertisement posting method and system |
| CN105574730A (en) * | 2014-10-10 | 2016-05-11 | 中兴通讯股份有限公司 | Internet of Things big data platform-based intelligent user portrait method and device |
| CN105844502A (en) * | 2016-05-20 | 2016-08-10 | 广州市莱麦互联网科技有限公司 | Information release method, device and system based on cloud and positioning technology |
| CN105989374A (en) * | 2015-03-03 | 2016-10-05 | 阿里巴巴集团控股有限公司 | Online model training method and equipment |
| CN106022865A (en) * | 2016-05-10 | 2016-10-12 | 江苏大学 | Goods recommendation method based on scores and user behaviors |
-
2017
- 2017-01-05 CN CN201710007725.7A patent/CN107103485B/en not_active Expired - Fee Related
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1413329A (en) * | 1999-08-13 | 2003-04-23 | 电影播放公司 | System and method for digitally providing and displaying advertisement information to cinemas and theaters |
| CN1864161A (en) * | 2003-09-03 | 2006-11-15 | Google公司 | Determining and/or using location information in an ad system |
| US20100042501A1 (en) * | 2008-08-12 | 2010-02-18 | Hsiu-Ling Lee | Method and apparatus for controlling content within a network |
| CN102640514A (en) * | 2009-06-22 | 2012-08-15 | 西恩沃尔有限公司 | Method for interactive digital cinema system |
| CN102201187A (en) * | 2010-03-23 | 2011-09-28 | 深圳华北工控股份有限公司 | Method for directionally advertising |
| CN101951441A (en) * | 2010-09-16 | 2011-01-19 | 中国联合网络通信集团有限公司 | Mobile telephone advertisement delivery method and equipment |
| CN103218729A (en) * | 2012-01-18 | 2013-07-24 | 现代自动车株式会社 | Method for providing advertisement based on location and system for providing advertisement |
| CN105303998A (en) * | 2014-07-24 | 2016-02-03 | 北京三星通信技术研究有限公司 | Method, device and equipment for playing advertisements based on inter-audience relevance information |
| CN105574730A (en) * | 2014-10-10 | 2016-05-11 | 中兴通讯股份有限公司 | Internet of Things big data platform-based intelligent user portrait method and device |
| CN105989374A (en) * | 2015-03-03 | 2016-10-05 | 阿里巴巴集团控股有限公司 | Online model training method and equipment |
| CN105355158A (en) * | 2015-11-12 | 2016-02-24 | 日立电梯（中国）有限公司 | Elevator advertisement posting method and system |
| CN106022865A (en) * | 2016-05-10 | 2016-10-12 | 江苏大学 | Goods recommendation method based on scores and user behaviors |
| CN105844502A (en) * | 2016-05-20 | 2016-08-10 | 广州市莱麦互联网科技有限公司 | Information release method, device and system based on cloud and positioning technology |
Non-Patent Citations (3)
| Title |
|---|
| QI LIU: ""A SURVEY OF CONTEXT-AWARE MOBILE RECOMMENDATIONS"", 《INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING》 * |
| 刘树栋: ""基于位置的移动社会化网络推荐技术研究"", 《中国博士学位论文全文数据库（电子期刊）信息科技辑》 * |
| 荆羽纯: ""一种基于学习自动机的推荐算法改进"", 《计算机应用研究》 * |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107798567A (en) * | 2017-11-21 | 2018-03-13 | 成都高德唯斯科技股份有限公司 | Brand message method for pushing, device and electronic equipment |
| CN107798567B (en) * | 2017-11-21 | 2023-06-20 | 成都高德唯斯科技股份有限公司 | Brand information pushing method and device and electronic equipment |
| CN108460125A (en) * | 2018-02-26 | 2018-08-28 | 影核（北京）网络科技有限公司 | A method of carrying out displaying labeling classification for movie theatre user |
| CN108766278A (en) * | 2018-05-15 | 2018-11-06 | 三星电子（中国）研发中心 | A kind of electronic guide board method for information display and device |
| CN108766278B (en) * | 2018-05-15 | 2020-06-05 | 三星电子（中国）研发中心 | Electronic guideboard information display method and device |
| CN109118270A (en) * | 2018-07-12 | 2019-01-01 | 北京猫眼文化传媒有限公司 | A kind of data extraction method and device |
| CN109118270B (en) * | 2018-07-12 | 2021-04-06 | 北京猫眼文化传媒有限公司 | Data extraction method and device |
| CN111695009A (en) * | 2019-03-11 | 2020-09-22 | 浙江莲荷科技有限公司 | Information display method and device |
| CN113781124A (en) * | 2020-09-18 | 2021-12-10 | 北京智能广宣科技有限公司 | Intelligent adjustment method for cinema advertisement play list |
| CN113781124B (en) * | 2020-09-18 | 2024-04-02 | 北京智能广宣科技有限公司 | Intelligent adjustment method for cinema advertisement play list |
| CN112333483A (en) * | 2020-10-27 | 2021-02-05 | 北京智能广宣科技有限公司 | Intelligent adjustment method and system for cinema advertisement play list |
| CN112767015A (en) * | 2021-01-07 | 2021-05-07 | 上海鸿研物流技术有限公司 | Information charging method and system based on logistics appliances |
| CN113269594A (en) * | 2021-06-08 | 2021-08-17 | 绍兴市壹点通传媒有限公司 | Cinema advertisement management method and system based on big data |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107103485B (en) | 2020-12-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107103485A (en) | It is a kind of that method and system is recommended according to the automatic advertising of movie theatre visitor information | |
| US11657411B1 (en) | System, method, software and data structure for independent prediction of attitudinal and message responsiveness, and preferences for communication media, channel, timing, frequency, and sequences of communications, using an integrated data repository | |
| US9727927B2 (en) | Prediction of user response to invitations in a social networking system based on keywords in the user's profile | |
| US8433595B2 (en) | Information providing system | |
| CN107092629A (en) | Recommend method and device | |
| US9208444B1 (en) | Determining happiness indices | |
| Moital et al. | A cross national study of golf tourists' satisfaction | |
| CN109241454A (en) | A kind of point of interest recommended method merging social networks and picture material | |
| CN107133277A (en) | Recommend method in a kind of tourist attractions based on Dynamic Theme model and matrix decomposition | |
| CN109408712A (en) | A kind of construction method of travel agency user multidimensional information portrait | |
| CN102385727A (en) | ID-value assessment device, ID-value assessment system, and ID-value assessment method | |
| CN108446944A (en) | A kind of the determination method, apparatus and electronic equipment in resident city | |
| US10909553B1 (en) | Systems and methods for generating an affinity graph | |
| Hung et al. | Understanding luxury shopping destination preference using conjoint analysis and traditional item-based measurement | |
| CN109272390A (en) | The personalized recommendation method of fusion scoring and label information | |
| Botha et al. | Expenditure-based segmentation of visitors to Aardklop National Arts Festival | |
| Maddison | Increasing returns to information and the survival of Broadway theatre productions | |
| Thrane | Modelling tourists’ length of stay: A call for a ‘back-to-basic’approach | |
| CN106503045A (en) | A kind of method and device for updating ATL | |
| US20150066743A1 (en) | System and method for socially connecting payment card holders | |
| Jung et al. | Does the star power matter? | |
| Birkin et al. | The classification of space-time behaviour patterns in a British city from crowd-sourced data | |
| Scheinbaum et al. | The role of faraway fans in sporting event sponsorship: Why sponsor patronage is stronger among fans who travel far to events | |
| Živković et al. | Comparative analysis of Facebook and communication activities of the mountain hotels in Stara Planina, Kopaonik and Zlatibor | |
| Barešová et al. | An aging population: A competitive advantage for 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 | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20201225 Termination date: 20220105 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |