CN112927025A - Advertisement pushing method, device, equipment and medium based on big data analysis - Google Patents

Advertisement pushing method, device, equipment and medium based on big data analysis Download PDF

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Publication number
CN112927025A
CN112927025A CN202110342088.5A CN202110342088A CN112927025A CN 112927025 A CN112927025 A CN 112927025A CN 202110342088 A CN202110342088 A CN 202110342088A CN 112927025 A CN112927025 A CN 112927025A
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client
advertisement
walking route
label attribute
face
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石恺宁
余锦鸿
梅海峰
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Xiamen Ruiwei Information Technology Co ltd
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Xiamen Ruiwei Information Technology Co ltd
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Priority to CN202110342088.5A priority Critical patent/CN112927025A/en
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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
    • G06Q30/0242—Determining effectiveness of advertisements
    • G06Q30/0244—Optimization
    • 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

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  • Strategic Management (AREA)
  • Engineering & Computer Science (AREA)
  • Accounting & Taxation (AREA)
  • Development Economics (AREA)
  • Finance (AREA)
  • Economics (AREA)
  • Game Theory and Decision Science (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Marketing (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Information Transfer Between Computers (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention provides an advertisement pushing method, device, equipment and medium based on big data analysis, wherein the method comprises the following steps: carrying out face detection on the obtained face to obtain face features; acquiring a walking route of the customer according to the face characteristics, and if the walking route exists, setting the label attribute of the customer according to the walking route; playing the corresponding advertisement according to the label attribute; if the walking route does not exist and the client has a label attribute, playing the corresponding advertisement according to the label attribute; if the walking route does not exist and the label attribute does not exist in the client, the label attribute of the client is not set, and the corresponding advertisement is played according to the age and the gender of the client; the walking route is used for predicting the next target location of the customer; and analyzing the pedestrian track according to the face recognition result and the background big data to carry out accurate advertisement pushing, and optimizing a pushing algorithm according to the feedback watched by the client.

Description

Advertisement pushing method, device, equipment and medium based on big data analysis
Technical Field
The invention relates to the technical field of computers, in particular to an advertisement pushing method, device, equipment and medium based on big data analysis.
Background
The advertisement propelling movement system of many advertisement machines on the market all is the advertisement of prestoring in the random play advertisement machine at present, and even some advertisement machines used face identification technique, also only come the propelling movement advertisement through people's age sex, and prior art has following problem:
1. the pushed advertisement is poor in pertinence even from the analysis of age and gender, and the requirement of accurate pushing is difficult to meet;
2. under different light environment, the age difference identified by different picture quality is large, and accurate advertisement putting can not be achieved.
Disclosure of Invention
The technical problem to be solved by the invention is to provide an advertisement pushing method, device, equipment and medium based on big data analysis, wherein the pedestrian track is analyzed according to a face recognition result and background big data to carry out accurate advertisement pushing, and a pushing algorithm is optimized according to feedback watched by a client.
In a first aspect, the present invention provides an advertisement push method based on big data analysis, including:
step 1, carrying out face detection on the obtained face to obtain face characteristics;
step 2, acquiring a walking route of the customer according to the face characteristics, and if the walking route exists, setting the label attribute of the customer according to the walking route; playing the corresponding advertisement according to the label attribute;
if the walking route does not exist and the client has a label attribute, playing the corresponding advertisement according to the label attribute; if the walking route does not exist and the label attribute does not exist in the client, the label attribute of the client is not set, and the corresponding advertisement is played according to the age and the gender of the client;
the walking route is used for predicting the next target location of the customer.
Further, still include:
and 3, when the advertisement is played, storing the advertisement ID, the human face characteristics, the age and the sex of the client and the watching time length for optimizing an advertisement pushing algorithm.
Further, the walking route is as follows: and acquiring the position data uploaded by the camera in the set area range of the client through the human face characteristics to obtain the walking route of the client.
In a second aspect, the present invention provides an advertisement delivery device based on big data analysis, including:
the module for acquiring the face features performs face detection on the acquired face to obtain the face features;
the advertisement pushing module is used for acquiring a walking route of the client according to the face characteristics, and if the walking route exists, setting the label attribute of the client according to the walking route; playing the corresponding advertisement according to the label attribute;
if the walking route does not exist and the client has a label attribute, playing the corresponding advertisement according to the label attribute; if the walking route does not exist and the label attribute does not exist in the client, the label attribute of the client is not set, and the corresponding advertisement is played according to the age and the gender of the client;
the walking route is used for predicting the next target location of the customer.
Further, still include:
and the data storage module is used for storing the advertisement ID, the human face characteristics, the age and the sex of the client and the watching time length when the advertisement is played, and is used for optimizing an advertisement pushing algorithm.
Further, the walking route is as follows: and acquiring the position data uploaded by the camera in the set area range of the client through the human face characteristics to obtain the walking route of the client.
In a third aspect, the present invention provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of the first aspect when executing the program.
In a fourth aspect, the invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the method of the first aspect.
One or more technical solutions provided in the embodiments of the present invention have at least the following technical effects or advantages:
1. the activity track of a client is fully considered, the user attribute label is given, the advertisement is pushed according to the label, and the advertisement pushing precision is higher than that of the advertisement pushing directly according to the age and sex of the client, so that the advertisement pushing method is easier to attract the attention of the client;
2. and continuously optimizing an advertisement push algorithm according to the feedback of the user, wherein the aim is to prolong the watching-off time of the target client.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
Drawings
The invention will be further described with reference to the following examples with reference to the accompanying drawings.
FIG. 1 is a flow chart of a method according to one embodiment of the present invention;
FIG. 2 is a schematic structural diagram of an apparatus according to a second embodiment of the present invention;
FIG. 3 is a block flow diagram of the present invention.
Detailed Description
The embodiment of the application provides an advertisement pushing method, an advertisement pushing device, equipment and a medium based on big data analysis, solves the technical problem that an advertisement pushed by an advertisement machine is inaccurate, and achieves the beneficial effects of improving the accuracy of personalized advertisement pushing of the advertisement machine and guiding more users to pay attention to advertisement contents pushed by the advertisement machine.
The technical scheme in the embodiment of the application has the following general idea:
obtaining the activity track of the user according to the background big data analysis; according to the activity track of the user, typing attribute labels for the outgoing of the user, wherein the attribute labels comprise shopping, dinner gathering, sports, movies, work and the like, and pushing related advertisements according to the attribute labels; and continuously optimizing an advertisement pushing algorithm according to the characteristic information of the client and the feedback of the advertisement watching duration.
As shown in fig. 3, the method specifically includes the following steps:
1. the face detection function of the front-end advertising machine uses the existing face recognition SDK, the SDK provides face detection (face position, size and angle), tracking, feature extraction and age and gender analysis functions, the advertising machine program uses the SDK to acquire the largest front face in the camera in real time for analysis, the face features are extracted (the front-end extraction features are beneficial to relieving the pressure of a rear-end server), and the face features are uploaded to the rear end for processing. Meanwhile, the face tracking function can count the time length of the front face of the client facing the advertising machine and the time length of watching the advertisement, so that the advertising machine can continuously play the advertisement labeled by the client as long as the client is still in the picture and watches the advertisement (the front face faces the camera).
2. After the back end obtains the face features reported by the front end, the back end compares the features uploaded by all cameras in the nearby area to obtain the route of the customer nearby, obtains the label attributes (including shopping, dinner gathering, sports, movies, work and the like) of the customer according to the route, and pushes the label attributes to the front-end advertising machine. If the characteristics reported by the upper nearby area are not compared, which indicates that the client is captured by the camera for the first time, the client is assigned with the label attribute according to the age and gender.
Comparing the features uploaded by all cameras in the nearby area to obtain a route of a customer nearby, counting data of all routes the same as the customer, analyzing the next most likely place of the customer, giving the label attributes (including shopping, dinner gathering, sports, movies, work and the like) of the customer, and pushing the label attributes to a front-end advertising machine.
3. The front-end advertising machine stores the attributes of the client labels pushed by the back end into a list, the list updates the client information currently in the camera picture of the advertising machine in real time, after the current advertisement of the advertising machine is played, the latest client information is taken out from the list, and the related advertisement is pushed according to the attributes of the labels. If the advertising machine is not networked, the advertisement is directly pushed according to the age and sex of the client.
4. When one advertisement is played, the front-end advertisement machine uploads the advertisement ID and the information of the age, sex, watching duration and the like of the target client to the rear end for analysis, and an advertisement pushing algorithm is optimized. The back-end optimization algorithm carries out forward matching according to the watching duration of the target client and other characteristic information (age and sex, attribute labels and the like) of the client, and the longer the watching duration is, the higher the matching degree is, and the shorter the watching duration is, the lower the matching degree is.
5. The advertisement push algorithm refers to the existing common recommendation algorithm, and information such as age, sex, interest (watching duration) and the like of a user is one of the most important input information of an advertisement recommendation algorithm model. The age, sex and watching duration of the user are obtained, the preference degree of the user can be better judged according to the information, so that training of the recommendation algorithm model is supervised, the robustness of the recommendation model is finally increased, and the recommendation algorithm is optimized.
Example one
As shown in fig. 1, the present embodiment provides an advertisement push method based on big data analysis, including:
step 1, carrying out face detection on the obtained face to obtain face characteristics;
step 2, acquiring a walking route of the customer according to the face characteristics, and if the walking route exists, setting the label attribute of the customer according to the walking route; playing the corresponding advertisement according to the label attribute;
if the walking route does not exist and the client has a label attribute, playing the corresponding advertisement according to the label attribute; if the walking route does not exist and the label attribute does not exist in the client, the label attribute of the client is not set, and the corresponding advertisement is played according to the age and the gender of the client;
the walking route is used for predicting the next target location of the customer, and the walking route is as follows: acquiring position data uploaded by a camera in a set area range of the client through the face characteristics to obtain a walking route of the client;
and 3, when the advertisement is played, storing the advertisement ID, the human face characteristics, the age and the sex of the client and the watching time length for optimizing an advertisement pushing algorithm.
Based on the same inventive concept, the application also provides a device corresponding to the method in the first embodiment, which is detailed in the second embodiment.
Example two
As shown in fig. 2, in the present embodiment, a second aspect is provided, and the present invention provides an advertisement push apparatus based on big data analysis, including:
the module for acquiring the face features performs face detection on the acquired face to obtain the face features;
the advertisement pushing module is used for acquiring a walking route of the client according to the face characteristics, and if the walking route exists, setting the label attribute of the client according to the walking route; playing the corresponding advertisement according to the label attribute;
if the walking route does not exist and the client has a label attribute, playing the corresponding advertisement according to the label attribute; if the walking route does not exist and the label attribute does not exist in the client, the label attribute of the client is not set, and the corresponding advertisement is played according to the age and the gender of the client;
the walking route is used for predicting the next target location of the customer, and the walking route is as follows: acquiring position data uploaded by a camera in a set area range of the client through the face characteristics to obtain a walking route of the client;
and the data storage module is used for storing the advertisement ID, the human face characteristics, the age and the sex of the client and the watching time length when the advertisement is played, and is used for optimizing an advertisement pushing algorithm.
Since the apparatus described in the second embodiment of the present invention is an apparatus used for implementing the method of the first embodiment of the present invention, based on the method described in the first embodiment of the present invention, a person skilled in the art can understand the specific structure and the deformation of the apparatus, and thus the details are not described herein. All the devices adopted in the method of the first embodiment of the present invention belong to the protection scope of the present invention.
Based on the same inventive concept, the application provides an electronic device embodiment corresponding to the first embodiment, which is detailed in the third embodiment.
EXAMPLE III
The embodiment provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, any one of the embodiments may be implemented.
Since the electronic device described in this embodiment is a device used for implementing the method in the first embodiment of the present application, based on the method described in the first embodiment of the present application, a specific implementation of the electronic device in this embodiment and various variations thereof can be understood by those skilled in the art, and therefore, how to implement the method in the first embodiment of the present application by the electronic device is not described in detail herein. The equipment used by those skilled in the art to implement the methods in the embodiments of the present application is within the scope of the present application.
Based on the same inventive concept, the application provides a storage medium corresponding to the fourth embodiment, which is described in detail in the fourth embodiment.
Example four
The present embodiment provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, any one of the first embodiment can be implemented.
The technical scheme provided in the embodiment of the application at least has the following technical effects or advantages: according to the method, the device, the equipment and the medium provided by the embodiment of the application, the activity track of the client is fully considered, the user attribute label is given, the advertisement is pushed according to the label, and the advertisement pushing precision is higher than that of the advertisement pushing directly according to the age and sex of the client, so that the attention of the client is attracted more easily; and continuously optimizing the advertisement pushing algorithm according to the feedback of the user, wherein the aim is to prolong the watching time of the target client.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Although specific embodiments of the invention have been described above, it will be understood by those skilled in the art that the specific embodiments described are illustrative only and are not limiting upon the scope of the invention, and that equivalent modifications and variations can be made by those skilled in the art without departing from the spirit of the invention, which is to be limited only by the appended claims.

Claims (8)

1. An advertisement pushing method based on big data analysis is characterized in that: the method comprises the following steps:
step 1, carrying out face detection on the obtained face to obtain face characteristics;
step 2, acquiring a walking route of the customer according to the face characteristics, and if the walking route exists, setting the label attribute of the customer according to the walking route; playing the corresponding advertisement according to the label attribute;
if the walking route does not exist and the client has a label attribute, playing the corresponding advertisement according to the label attribute; if the walking route does not exist and the label attribute does not exist in the client, the label attribute of the client is not set, and the corresponding advertisement is played according to the age and the gender of the client;
the walking route is used for predicting the next target location of the customer.
2. The advertisement pushing method based on big data analysis according to claim 1, wherein: further comprising:
and 3, when the advertisement is played, storing the advertisement ID, the human face characteristics, the age and the sex of the client and the watching time length for optimizing an advertisement pushing algorithm.
3. The advertisement pushing method based on big data analysis according to claim 1, wherein: the walking route is as follows: and acquiring the position data uploaded by the camera in the set area range of the client through the human face characteristics to obtain the walking route of the client.
4. The utility model provides an advertisement pusher based on big data analysis which characterized in that: the method comprises the following steps:
the module for acquiring the face features performs face detection on the acquired face to obtain the face features;
the advertisement pushing module is used for acquiring a walking route of the client according to the face characteristics, and if the walking route exists, setting the label attribute of the client according to the walking route; playing the corresponding advertisement according to the label attribute;
if the walking route does not exist and the client has a label attribute, playing the corresponding advertisement according to the label attribute; if the walking route does not exist and the label attribute does not exist in the client, the label attribute of the client is not set, and the corresponding advertisement is played according to the age and the gender of the client;
the walking route is used for predicting the next target location of the customer.
5. The advertisement pushing device based on big data analysis according to claim 4, wherein: further comprising:
and the data storage module is used for storing the advertisement ID, the human face characteristics, the age and the sex of the client and the watching time length when the advertisement is played, and is used for optimizing an advertisement pushing algorithm.
6. The advertisement pushing device based on big data analysis according to claim 4, wherein: the walking route is as follows: and acquiring the position data uploaded by the camera in the set area range of the client through the human face characteristics to obtain the walking route of the client.
7. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 3 when executing the program.
8. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 3.
CN202110342088.5A 2021-03-30 2021-03-30 Advertisement pushing method, device, equipment and medium based on big data analysis Pending CN112927025A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110342088.5A CN112927025A (en) 2021-03-30 2021-03-30 Advertisement pushing method, device, equipment and medium based on big data analysis

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110342088.5A CN112927025A (en) 2021-03-30 2021-03-30 Advertisement pushing method, device, equipment and medium based on big data analysis

Publications (1)

Publication Number Publication Date
CN112927025A true CN112927025A (en) 2021-06-08

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