CN111192094A - Intelligent advertising method and device - Google Patents

Intelligent advertising method and device Download PDF

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Publication number
CN111192094A
CN111192094A CN202010010021.7A CN202010010021A CN111192094A CN 111192094 A CN111192094 A CN 111192094A CN 202010010021 A CN202010010021 A CN 202010010021A CN 111192094 A CN111192094 A CN 111192094A
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advertisement
user
bidding
consumption
current
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CN111192094B (en
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李强
吴帆
薛超
伍霖
胡先才
陈焱军
杨武
肖博娜
黄甜
周希
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Wuhan Cirrost Technology Co ltd
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Wuhan Cirrost Technology Co ltd
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    • 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
    • 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
    • G06Q30/0273—Determination of fees for advertising
    • G06Q30/0275—Auctions
    • 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
    • G06Q30/0277—Online advertisement
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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Abstract

The invention relates to the technical field of intelligent advertisements, and provides an intelligent advertisement method and device. The method comprises the steps of obtaining one or more pieces of user information in a current scene; generating one or more advertisement bidding tickets according to the user information; and generating a current advertisement bidding result according to the advertisement bidding list, and playing advertisement contents according to the bidding result. According to the invention, the camera is introduced to collect the face images of the users, so that a plurality of users in the current scene (such as an elevator advertisement putting scene) can be identified, and the advertisement bidding documents are analyzed by big data to carry user distribution on each consumption type, consumption attributes of each user and/or advertisement attributes of the users in the current scene, so that a targeted reference dimension is provided for advertisement bidding, and finally presented advertisement contents have higher pertinence and effectiveness.

Description

Intelligent advertising method and device
[ technical field ] A method for producing a semiconductor device
The invention relates to the technical field of intelligent advertisements, in particular to an intelligent advertisement method and device.
[ background of the invention ]
With the popularization of 5G networks, the concept of the intelligent Internet of things is concerned more and more. The application field of the intelligent Internet of things relates to aspects of daily life, and the most direct advantages brought by the intelligent Internet of things are represented by effective identification and recognition of each terminal device and substantial broadening of transmission channel bandwidth among the terminal devices.
However, the concept of the intelligent internet of things in the prior art is more a channel category, and is really implemented in each application field, and the functional characteristics of the corresponding intelligent internet of things are not fully exerted. The method is characterized in that an elevator inner advertisement screen is taken as an example, along with the widening of internet bandwidth, the mode of the method is really changed, the method is only limited to a mode of storing advertisements by using a memory card originally and is replaced by a mode of utilizing the internet to update online every day, however, even if the method is improved, the existing elevator inner advertisement screen advertisement putting mode is still scheduled, the advertisements are played in a set playing sequence, the mode cannot meet more and more advertisement putting requirements, and the effective advertisement putting effect cannot be achieved.
In view of the above, overcoming the drawbacks of the prior art is an urgent problem in the art.
[ summary of the invention ]
The technical problem to be solved by the invention is that the existing advertisement putting method similar to the advertisement screen in the elevator still plays the advertisements according to the scheduled work and the set playing sequence, and the method cannot meet more and more advertisement putting requirements and cannot achieve effective advertisement putting effect.
The invention adopts the following technical scheme:
in a first aspect, the present invention provides a smart advertisement method, including:
acquiring one or more pieces of user information in a current scene, wherein the user information is obtained by converting a face image of a user acquired by a camera;
generating one or more advertisement bidding tickets according to the user information; the advertisement bidding document carries one or more of user distribution on each consumption type, consumption attributes of each user and advertisement attributes of the user in the current scene;
and generating a current advertisement bidding result according to the advertisement bidding list, and playing advertisement contents according to the bidding result.
Preferably, the consumption attribute of the user comprises one or more items of consumption capacity of the user, consumption intention of the user and historical consumption records of the user;
the user distribution on the consumption type is specifically a type range for analyzing the user distribution on the consumption type is set according to the currently owned participating bidding advertisement type;
the advertisement attribute of the user in the current scene comprises one or more items of total times of occurrence, frequency, effective advertisement browsing times and average scene staying time of the user.
Preferably, the generating of the current advertisement bidding result according to the advertisement bidding list and the playing of the advertisement content according to the bidding result specifically include:
calculating the total consumption potential on the corresponding consumption type according to the user distribution on the consumption type and the consumption capacity of each user;
screening one or more target consumption types according to the total consumption potential on the corresponding consumption type;
and bidding the advertisement content to be played according to the target consumption type, wherein one or more advertisement sources matched with the target consumption type participate in bidding, and the advertisement source with the highest bidding price obtains the playing permission of the advertisement content to be played.
Preferably, the one or more advertisement sources matching the target consumption type participate in bidding, which specifically includes:
analyzing the probability of effectively browsing the advertisements by the user by each advertisement source according to the time length of the advertisement and the average time length of the scene where the user stays;
determining the probability that the corresponding user is the target consumption object of the advertisement source by combining the single consumption capacity of each user as the target consumption type;
analyzing the probability that the user is a fatigue consumption object by combining the total times and frequency of the advertisement sources and the effective advertisement browsing times of the user;
and combining the probability of effectively browsing the advertisement by the user, the probability of the target consumption object and/or the probability of the fatigue consumption object as bidding reference factors to complete respective bidding.
Preferably, the average duration of the user staying in the scene specifically includes:
calculating according to the floor clicked when the user enters the elevator, the floor where the current elevator is located and the running state of the elevator; the running state of the elevator comprises one or more of an ascending state, a descending state and a clicked demand state of each floor.
Preferably, the effective browsing advertisement includes:
the user face image collected by the camera faces the advertisement screen, the camera collects that the user does not wear an earphone and/or the camera collects that the user is not in a third-party equipment use state currently, and then the user is determined to finish effective browsing of a round of advertisements.
Preferably, when the current scene is an elevator screen advertisement, the method further includes:
confirming that the user in the elevator leaves before the current advertisement is played and a new user enters the elevator, ending the playing of the current advertisement in advance, and returning the advertisement bidding amount according to the content proportion of the advertisement content which is not played in the corresponding current advertisement relative to the total content proportion of the current advertisement;
and starting a new round of user information acquisition, bidding list generation and advertisement playing according to a bidding result aiming at a user who newly enters the elevator.
Preferably, the advertisement comprises a bid advertisement and a default advertisement, wherein the default advertisement is used for triggering playing when the camera detects that the elevator door is opened, and the playing time of the default advertisement is set to be less than a first preset threshold value.
Preferably, the current scene comprises public activity places, washrooms, halls and waiting rooms of a shopping mall.
In a second aspect, the present invention further provides a smart advertisement method, for implementing the smart advertisement method in the first aspect, where the apparatus includes:
at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor for performing the smart advertisement method of the first aspect.
In a third aspect, the present invention also provides a non-transitory computer storage medium storing computer-executable instructions for execution by one or more processors for performing the smart advertisement method of the first aspect.
According to the invention, the camera is introduced to collect the face images of the users, so that a plurality of users in the current scene (such as an elevator advertisement putting scene) can be identified, and the advertisement bidding documents are analyzed by big data to carry user distribution on each consumption type, consumption attributes of each user and/or advertisement attributes of the users in the current scene, so that a targeted reference dimension is provided for advertisement bidding, and finally presented advertisement contents have higher pertinence and effectiveness. Compared with the prior art, the conventional sequential advertisement delivery method can well solve the problem of overflow of advertisement delivery parties and the problem of low efficiency of the conventional advertisement delivery method.
[ description of the drawings ]
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the embodiments of the present invention will be briefly described below. It is obvious that the drawings described below are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
FIG. 1 is a flow chart of a smart advertising method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a smart advertisement system architecture according to an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating a bidding process in a smart advertising method according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of different types of consuming capabilities in a smart advertisement provided by an embodiment of the present invention;
FIG. 5 is a schematic diagram illustrating a bidding process in a smart advertising method according to an embodiment of the present invention;
fig. 6 is a schematic diagram illustrating a bidding process of an elevator scenario in the intelligent advertising method according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of an intelligent advertisement device according to an embodiment of the present invention.
[ detailed description ] embodiments
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In the description of the present invention, the terms "inner", "outer", "longitudinal", "lateral", "upper", "lower", "top", "bottom", and the like indicate orientations or positional relationships based on those shown in the drawings, and are for convenience only to describe the present invention without requiring the present invention to be necessarily constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.
In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
Example 1:
an embodiment 1 of the present invention provides an intelligent advertisement method, as shown in fig. 1, including:
in step 201, one or more pieces of user information in the current scene are acquired, wherein the user information is obtained by converting a face image of a user acquired by a camera.
As shown in fig. 2, in the implementation process of the embodiment of the present invention, a preferred implementation manner is further provided for the user information, and the face image of the user acquired by the camera is converted, and the face features are identified by the face, and sending the portrait characteristics and the current event ID to a proxy server, sending a request message carrying the portrait characteristics to a third-party data platform (for example, a payment treasure which is successfully popularized by using face payment) which establishes a cooperative relationship with the proxy server, finishing the search of the user portrait locally by the third-party data platform by using the portrait characteristics and returning the message carrying the event ID and the user portrait to the proxy server (after the step, the portrait characteristic information is hidden and the event ID is used as a representative of the portrait characteristics), wherein the user portrait comprises the consumption attributes of each user. The advertisement bidding server then uses the user representation results to bid on advertisements. Namely, the advertisement auction system realizes accurate advertisement delivery on the premise of not acquiring user data.
In step 202, generating one or more advertisement bidding documents according to the user information; the advertisement bidding document carries one or more of user distribution on each consumption type, consumption attributes of each user and advertisement attributes of the user in the current scene.
Wherein the consumption attribute of the user comprises one or more items of consumption capacity of the user, consumption intention of the user and historical consumption records of the user;
the user distribution on the consumption type is specifically a type range for analyzing the user distribution on the consumption type is set according to the currently owned participating bidding advertisement type;
the advertisement attribute of the user in the current scene comprises one or more items of total times of occurrence, frequency, effective advertisement browsing times and average scene staying time of the user.
According to the example scenario shown in step 201, the advertisement bidding document is generated by the proxy server in fig. 2, wherein the proxy server sends the advertisement type currently subscribed for bidding by the advertisement slot to the advertisement bidding server after receiving the consumption attribute of the user, and generates the currently owned advertisement type participating in bidding by combining the consumption attribute to set a type range for analyzing the user distribution on the consumption type; the advertisement attribute in the current scene is preferably managed by the proxy server, so that the portrait characteristics of the user can be more effectively ensured to be transmitted only between the proxy server and third-party big data, and the security of the privacy of the user is ensured.
If the privacy of the user does not need to be considered, that is, the face recognition, the proxy server, the third-party big data and the advertisement bidding server shown in fig. 2 all can carry portrait features in the transmission message, the advertisement attributes of the user in the current scene can be stored in the advertisement bidding server, so that the efficiency of completing the whole advertisement bidding is further improved. The process of sending the advertisement attributes of the user in the current scenario to the ad bidding server via the proxy server in the above scheme can be avoided.
In step 203, a current advertisement bidding result is generated according to the advertisement bidding list, and advertisement content is played according to the bidding result.
According to the embodiment of the invention, the camera is introduced to collect the face images of the users, so that a plurality of users in the current scene (such as an elevator advertisement putting scene) can be identified, and the advertisement bidding documents carrying the user distribution on each consumption type, the consumption attributes of each user and/or the advertisement attributes of the users in the current scene are analyzed through big data, so that a targeted reference dimension is provided for advertisement bidding, and finally presented advertisement contents have higher pertinence and effectiveness. Compared with the prior art, the conventional sequential advertisement delivery method can well solve the problem of overflow of advertisement delivery parties and the problem of low efficiency of the conventional advertisement delivery method.
With reference to the embodiment of the present invention, according to the above-described expanded user distribution on each consumption type, consumption attributes of each user, and advertisement attribute description of the user in the current scene, corresponding to what is involved in step 203 in embodiment 1, a current round of advertisement bidding result is generated according to the advertisement bidding sheet, and advertisement content is played according to the bidding result, and there is a specific implementation manner, as shown in fig. 3, which specifically includes:
in step 301, the total consumption potential of the corresponding consumption type is calculated according to the user distribution of the consumption type and the consumption capacity of each user.
As shown in fig. 4, the total consumption potential in the consumption type proposed in step 301 according to the embodiment of the present invention is a schematic diagram, where specific units of 300, 100, 200, and 400 may be hundreds, thousands, etc., and are specifically determined according to different consumption types, and the total consumption potential in the consumption type is further statistically obtained according to the user face information acquired in the current scene and the consumption attributes of the user acquired by the third-party big data platform, that is, the consumption potential value of type 1 is 300, which represents the sum of the total consumption potentials of all users acquired in the current scene under the corresponding type 1, and the consumption capacity for each user can be statistically obtained according to the savings of the user and/or the consumption record of the history under the corresponding type 1.
In step 302, one or more target consumption types are selected from the corresponding consumption types according to the total consumption potential of the corresponding consumption types.
The significance of this step is that, aiming at the user characteristics in the current scene, the target consumption type is firstly screened out through the steps 301 and 302, so that the effectiveness of the next bidding advertisement can be improved, namely the mainstream consumption direction (i.e. consumption type) of the users in the current scene and the current batch is screened out.
In step 303, bidding on the advertisement content to be played according to the target consumption type, where one or more advertisement sources matched with the target consumption type participate in bidding, and the advertisement source with the highest bidding price obtains the playing permission of the advertisement content to be played.
In connection with the embodiment of the present invention, for the one or more advertisement sources matching the target consumption type involved in the step 303 mentioned above to participate in the bidding, there is also an alternative implementation scheme, as shown in fig. 5, which specifically includes:
in step 401, each advertisement source analyzes the probability that the user effectively browses the advertisement according to the time length of the advertisement itself and the average duration of the scene where the user stays.
The average duration of the user staying in the scene specifically includes: calculating according to the floor clicked when the user enters the elevator, the floor where the current elevator is located and the running state of the elevator; the running state of the elevator comprises one or more of an ascending state, a descending state and a clicked demand state of each floor.
The reason why the operation state of the elevator is considered is that if the current user is an elevator going from 22 floors and selects 1 floor as the purpose, and if the elevator state is going to 28 floors and then goes to 1 floor, the corresponding real stay time of the user will increase. The average time of the user staying in the scene described in step 401 is only used in the case that the bid time of the advertisement is required to be very short, for example, the user just enters the scene and the default advertisement just finishes, and the execution time of the above steps given to the system is very limited, and the average time counted according to the history is most effective.
Wherein the default advertisement is: the advertisements comprise bidding advertisements and default advertisements, wherein the default advertisements are used for triggering playing when the camera detects that the elevator door is opened, and the playing time of the default advertisements is set to be smaller than a first preset threshold value.
The longer the average time length of the user staying in the scene is compared with the time length of the advertisement source combined with the advertisement, the higher the probability that the corresponding user effectively browses the advertisement is, and if the average time length of the user staying in the scene exceeds 20%, the probability that the user effectively browses the advertisement is determined to be 100%. On the other hand, if the score is scored from 1-10 points, the corresponding score may be 10 points.
In step 402, each advertisement source determines the probability that the corresponding user is the target consumption object of itself in combination with the individual consumption capability of each user as the target consumption type.
This is strongly related according to the target consumption groups of different advertisement sources, and the individual consumption capacity of the target consumption type is expected by the advertisement sources, and the corresponding top-going users are the target consumption objects of the users, and are also statistically obtained according to the savings and/or history of each user in the consumption records of the corresponding type 1 (i.e. expanded in step 301). For example, if the user's consumption capacity exceeds 50% of the individual consumption capacity of the advertisement source target consumption type, the corresponding probability may be designated as 100%. On the other hand, if the score is scored from 1-10 points, the corresponding score may be 10 points.
In step 403, the probability that the user is a fatigue consumption object is analyzed by each advertisement source according to the total times and frequency of the user appearing and the times of effectively browsing advertisements.
The step 403 is opposite to the positive terms of the step 401 and the step 402; the probability and score calculated in step 403 will be used as a negative sub-item to participate in the final calculation, where it is considered that if the total number of times, frequency and number of times of effective advertisement browsing of the user are large, it is determined that the same advertisement will produce a fatigue promotion effect for the user, and at this time, it is not very desirable for the advertisement source to invest a high bid amount for similar users, but it is not excluded that such users still push the advertisement if they have high consumption capacity, so there is an operation of performing a comprehensive evaluation of the above steps 401, 402 and 403 in step 404.
In step 404, the probability of effective advertisement browsing, the probability of target consumption object and/or the probability of fatigue consumption object of the user are used as bidding reference factors to complete respective bidding.
It should be emphasized that the probability of effective advertisement browsing by the user, the probability of the target consumption object and/or the probability of the fatigue consumption object are used as the reference factors of bidding, which are only used as the reference factors of the advertisement sources, and the real bidding price is determined according to the set value of each advertisement source, usually according to the set maximum value, and is calculated as the weight according to the calculated probability or score.
In a specific implementation scheme, a stricter evaluation criterion is provided for the effective advertisement browsing, and the step includes the relationship between the time length of each advertisement source, which is provided in step 401, in combination with the average duration of the user's stay scene, which is further defined by the following contents, which specifically includes:
the user face image collected by the camera faces the advertisement screen, the camera collects that the user does not wear an earphone and/or the camera collects that the user is not in a third-party equipment use state currently, and then the user is determined to finish effective browsing of a round of advertisements.
In a specific implementation scheme, the facial image of the user collected by the camera faces the advertisement screen, the camera collects that the user does not wear the earphone and/or the camera collects that the user is not currently in the third-party device use state, and the probability or the scored weight calculated in step 401 is used as the weight, that is, the further constraint condition is not satisfied, for example, if the facial image of the user collected by the camera does not face the advertisement screen, the camera collects that the user wears the earphone and/or the camera collects that the user is currently in the third-party device use state, the weighting processing of the discount type is performed on the basis of the probability or the scoring in step 401, that is, if the original probability in step 401 is 100%, the probability after the weight discount of any one item occurs is 80%, and if the two items occur, the probability after the weight discount is 70%, the probability after weight discount is 50% when the three items happen.
In combination with the embodiment of the present invention, in consideration of more rigorous and efficient advertisement bidding requirements, when the current scene is an elevator screen advertisement, as shown in fig. 6, the method further includes:
in step 501, it is confirmed that the user leaves the elevator and a new user enters the elevator before the current advertisement is played, the current advertisement is played in advance, and the bid amount of the advertisement is returned according to the ratio of the content of the advertisement which is not played in the corresponding current advertisement to the total content of the current advertisement.
In step 502, a new round of user information acquisition, bidding list generation, and advertisement playing according to the bidding result is started for the user who newly enters the elevator.
Wherein step 502 is meant to encompass the relevant steps of fig. 1, fig. 3, and/or fig. 5, described above.
Example 2:
fig. 7 is a schematic structural diagram of an intelligent advertisement device according to an embodiment of the present invention. The smart advertisement device of the present embodiment includes one or more processors 21 and a memory 22. In fig. 7, one processor 21 is taken as an example.
The processor 21 and the memory 22 may be connected by a bus or other means, and fig. 7 illustrates the connection by a bus as an example.
The memory 22, which is a non-volatile computer-readable storage medium, may be used to store non-volatile software programs and non-volatile computer-executable programs, such as the smart advertisement method in embodiment 1. The processor 21 executes the smart advertising method by executing non-volatile software programs and instructions stored in the memory 22.
The memory 22 may include high speed random access memory and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, the memory 22 may optionally include memory located remotely from the processor 21, and these remote memories may be connected to the processor 21 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The program instructions/modules are stored in the memory 22 and, when executed by the one or more processors 21, perform the smart advertisement method of embodiment 1 described above, for example, perform the steps illustrated in fig. 1, 3, 5, and 6 described above.
It should be noted that, for the information interaction, execution process and other contents between the modules and units in the apparatus and system, the specific contents may refer to the description in the embodiment of the method of the present invention because the same concept is used as the embodiment of the processing method of the present invention, and are not described herein again.
Those of ordinary skill in the art will appreciate that all or part of the steps of the various methods of the embodiments may be implemented by associated hardware as instructed by a program, which may be stored on a computer-readable storage medium, which may include: a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic or optical disk, or the like.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.

Claims (10)

1. A smart advertising method, comprising:
acquiring one or more pieces of user information in a current scene, wherein the user information is obtained by converting a face image of a user acquired by a camera;
generating one or more advertisement bidding tickets according to the user information; the advertisement bidding document carries one or more of user distribution on each consumption type, consumption attributes of each user and advertisement attributes of the user in the current scene;
and generating a current advertisement bidding result according to the advertisement bidding list, and playing advertisement contents according to the bidding result.
2. The smart advertising method according to claim 1, wherein:
the consumption attribute of the user comprises one or more items of consumption capacity of the user, consumption intention of the user and historical consumption records of the user;
the user distribution on the consumption type is specifically a type range for analyzing the user distribution on the consumption type is set according to the currently owned participating bidding advertisement type;
the advertisement attribute of the user in the current scene comprises one or more items of total times of occurrence, frequency, effective advertisement browsing times and average scene staying time of the user.
3. The intelligent advertising method according to claim 2, wherein generating a current round of advertisement bidding result according to the advertisement bidding ticket, and playing advertisement content according to the bidding result specifically comprises:
calculating the total consumption potential on the corresponding consumption type according to the user distribution on the consumption type and the consumption capacity of each user;
screening one or more target consumption types according to the total consumption potential on the corresponding consumption type;
and bidding the advertisement content to be played according to the target consumption type, wherein one or more advertisement sources matched with the target consumption type participate in bidding, and the advertisement source with the highest bidding price obtains the playing permission of the advertisement content to be played.
4. The intelligent advertising method according to claim 3, wherein the one or more advertisement sources matching the target consumption type participate in bidding, specifically comprising:
analyzing the probability of effectively browsing the advertisements by the user by each advertisement source according to the time length of the advertisement and the average time length of the scene where the user stays;
determining the probability that the corresponding user is the target consumption object of the advertisement source by combining the single consumption capacity of each user as the target consumption type;
analyzing the probability that the user is a fatigue consumption object by combining the total times and frequency of the advertisement sources and the effective advertisement browsing times of the user;
and combining the probability of effectively browsing the advertisement by the user, the probability of the target consumption object and/or the probability of the fatigue consumption object as bidding reference factors to complete respective bidding.
5. The intelligent advertising method according to claim 4, wherein the average duration of the user staying in the scene specifically comprises:
calculating according to the floor clicked when the user enters the elevator, the floor where the current elevator is located and the running state of the elevator; the running state of the elevator comprises one or more of an ascending state, a descending state and a clicked demand state of each floor.
6. The smart advertising method of claim 2, wherein the effective browsing of advertisements comprises:
the user face image collected by the camera faces the advertisement screen, the camera collects that the user does not wear an earphone and/or the camera collects that the user is not in a third-party equipment use state currently, and then the user is determined to finish effective browsing of a round of advertisements.
7. The intelligent advertising method according to claim 1, wherein when the current scene is an elevator screen advertisement, the method further comprises:
confirming that the user in the elevator leaves before the current advertisement is played and a new user enters the elevator, ending the playing of the current advertisement in advance, and returning the advertisement bidding amount according to the content proportion of the advertisement content which is not played in the corresponding current advertisement relative to the total content proportion of the current advertisement;
and starting a new round of user information acquisition, bidding list generation and advertisement playing according to a bidding result aiming at a user who newly enters the elevator.
8. The smart advertisement method according to claim 7, wherein the advertisement comprises a bid advertisement and a default advertisement, wherein the default advertisement is used for triggering playing when the camera detects that the elevator door is opened, and the playing time of the default advertisement is set to be less than a first preset threshold value.
9. The intelligent advertising method according to any one of claims 1 to 8, wherein the current scene includes public places of activity, restrooms, halls and waiting rooms of a mall.
10. A smart advertising method, characterized in that the apparatus comprises:
at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor for performing the smart advertisement method of any of claims 1-9.
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Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140344073A1 (en) * 2013-05-14 2014-11-20 Microsoft Corporation Real-time advertisement bidding
CN105046532A (en) * 2015-08-07 2015-11-11 北京品友互动信息技术有限公司 Bidding method and device
CN107886371A (en) * 2017-11-30 2018-04-06 浙江小屏信息技术有限公司 Advertisement sending method and device based on elevator scene
CN108320178A (en) * 2018-01-08 2018-07-24 深圳豪威显示科技有限公司 A kind of advertisement sending method and device based on recognition of face
CN108985845A (en) * 2018-07-18 2018-12-11 北京旷视科技有限公司 Broadcast monitoring method, apparatus and system
CN109242555A (en) * 2018-08-24 2019-01-18 深圳艺达文化传媒有限公司 Voice-based advertisement broadcast method and Related product
CN109978618A (en) * 2019-03-22 2019-07-05 成都大象分形智能科技有限公司 Advertisement interacts jettison system under line based on cloud artificial intelligence
CN110111128A (en) * 2019-03-28 2019-08-09 厦门理工学院 A kind of apartment elevator advertisement broadcast method, device and equipment
CN110135883A (en) * 2019-03-27 2019-08-16 浙江新再灵科技股份有限公司 A kind of method and system of elevator crowd portrayal and commercial audience analysis
CN110490643A (en) * 2019-07-30 2019-11-22 恒大智慧科技有限公司 A kind of advertisement sending method, system and server
CN110570243A (en) * 2019-08-29 2019-12-13 上海光是信息科技有限公司 Advertisement adapting method suitable for hardware advertisement screen

Patent Citations (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140344073A1 (en) * 2013-05-14 2014-11-20 Microsoft Corporation Real-time advertisement bidding
CN105046532A (en) * 2015-08-07 2015-11-11 北京品友互动信息技术有限公司 Bidding method and device
CN107886371A (en) * 2017-11-30 2018-04-06 浙江小屏信息技术有限公司 Advertisement sending method and device based on elevator scene
CN108320178A (en) * 2018-01-08 2018-07-24 深圳豪威显示科技有限公司 A kind of advertisement sending method and device based on recognition of face
CN108985845A (en) * 2018-07-18 2018-12-11 北京旷视科技有限公司 Broadcast monitoring method, apparatus and system
CN109242555A (en) * 2018-08-24 2019-01-18 深圳艺达文化传媒有限公司 Voice-based advertisement broadcast method and Related product
CN109978618A (en) * 2019-03-22 2019-07-05 成都大象分形智能科技有限公司 Advertisement interacts jettison system under line based on cloud artificial intelligence
CN110135883A (en) * 2019-03-27 2019-08-16 浙江新再灵科技股份有限公司 A kind of method and system of elevator crowd portrayal and commercial audience analysis
CN110111128A (en) * 2019-03-28 2019-08-09 厦门理工学院 A kind of apartment elevator advertisement broadcast method, device and equipment
CN110490643A (en) * 2019-07-30 2019-11-22 恒大智慧科技有限公司 A kind of advertisement sending method, system and server
CN110570243A (en) * 2019-08-29 2019-12-13 上海光是信息科技有限公司 Advertisement adapting method suitable for hardware advertisement screen

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