CN114331522A - Personalized advertisement broadcasting method and system based on user portrait and storage medium - Google Patents
Personalized advertisement broadcasting method and system based on user portrait and storage medium Download PDFInfo
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Abstract
The invention relates to the technical field of advertisement pushing, in particular to a personalized advertisement broadcasting method and system based on user portrait and a storage medium. The system includes server and advertisement show end, advertisement show end and server communication connection, the server includes: a user portrait module: the system comprises a user portrait for obtaining advertisement audience users; big data analysis module: the system is used for acquiring the hot spot advertisements and analyzing operation scene classification data and time-space thermodynamic diagram data of the hot spot advertisements; the advertisement acquisition module: the system comprises a server and a server, wherein the server is used for acquiring client information and advertisement information to be pushed by a client; a release analysis module: the system comprises a database, a database server and a database server, wherein the database is used for storing the time-space thermodynamic diagram data; the advertisement distribution module: and the advertisement information is distributed to the advertisement display end corresponding to the putting place and is played in the best putting time. The invention can accurately push the advertisement, improve the advertising effect and reduce the cost of advertisement pushing.
Description
Technical Field
The invention relates to the technical field of advertisement pushing, in particular to a personalized advertisement broadcasting method and system based on user portrait and a storage medium.
Background
With the deep application of big data in the internet industry, the advertisement push service is also developing at a high speed with the increasing speed of the internet data volume. The internet advertisement information pushing system is developed by utilizing an IP network technology and can push advertisement pictures with different formats to a browsing device of a network on-line user at regular time and fixed point. However, as the distribution of industries becomes more and more detailed, previous coverage promotion cannot be relied upon. Because the blind advertisement coverage can not attract effective people, but can cause the discomfort and discomfort of consumers, the expected propaganda effect can not be achieved, and the cost is high.
Disclosure of Invention
An object of the present invention is to provide a personalized advertisement broadcasting system based on a user figure, which can accurately push an advertisement, improve the advertising effect of the advertisement, and reduce the cost of advertisement push.
In order to achieve the above object, there is provided a personalized advertisement broadcasting system based on user portrait, including a server and an advertisement displaying end, the advertisement displaying end being in communication connection with the server, the server including:
a user portrait module: the system comprises a user portrait for obtaining advertisement audience users;
the server further comprises the following modules:
big data analysis module: the system is used for analyzing hot advertisements in the advertisements played by the advertisement display ends in different setting positions through a big data technology and a user portrait, and analyzing operation scene classification data and time-space thermodynamic diagram data of the hot advertisements;
the advertisement acquisition module: the system comprises a server and a server, wherein the server is used for acquiring client information and advertisement information to be pushed by a client;
a scene classification module: the system is used for classifying operation scenes according to the client information and the advertisement content of the advertisement information; matching the operation scene classification data with the time-space thermodynamic diagram data of the corresponding operation scene;
a release analysis module: the system comprises a database, a database server and a database server, wherein the database is used for storing the time-space thermodynamic diagram data;
the advertisement distribution module: and the advertisement information is distributed to the advertisement display end corresponding to the putting place and is played in the best putting time.
The principle and the advantages are as follows:
1. the user portrait module can acquire the user portrait of the advertisement audience user, and is convenient for knowing which users like and which users do not like in each place; therefore, data support is made for accurate pushing of the advertisement. Moreover, the service objects of the advertisements can be focused and concentrated more through the user portrait; thereby improving the advertising effect.
2. The big data analysis module can analyze and know hot advertisements in the advertisements played by the advertisement display ends in different setting positions through a big data analysis technology. Meanwhile, the operation scene classification data and the time-space thermodynamic diagram data of the hot spot advertisement can be analyzed; the classification of the hot spot advertisement field is completed by operating scene classification data, and the temporal spatial thermodynamic diagram data is the classification of hot spot advertisement time and space. By operating the scene classification data and the time-space thermodynamic diagram data, on one hand, the data reference can be provided for subsequent advertisement delivery by a client conveniently, and on the other hand, the required advertisement can be provided for audience users on the other hand. Therefore, the advertisement pushing is conveniently and accurately carried out, and the cost of the advertisement pushing is reduced.
3. The scene classification module, the delivery analysis module and the advertisement distribution module are arranged, so that the optimal delivery time and the delivery place of the advertisement information can be calculated according to the advertisement content of the client information and the advertisement information, and the advertisement can be automatically played in the corresponding place and time, so that the advertisement can be conveniently and accurately delivered, and the waste of fund caused by meaningless advertisement delivery is avoided. And the advertising effect can be improved by pushing the advertisement in the high-quality point position and the prime time. Meanwhile, compared with the existing manual background advertisement putting, the advertisement putting method has the advantages that the labor input is greatly reduced for the advertisement putting party, the system can be used for controlling and implementing the advertisement putting method completely, artificial subjective errors are avoided, the advertisement putting error rate is lower, and the labor cost is greatly saved.
Further, the server further comprises the following modules:
a flow acquisition module: the method comprises the steps of obtaining flow data of an advertisement display end corresponding to the hotspot advertisement;
an interval grading module: and generating time interval pricing data for advertisement putting of each advertisement display end according to the operation scene classification data, the time space thermodynamic diagram data and the flow data of the hot spot advertisements.
Resource pricing is carried out on the high-quality point positions and the prime time of the advertisements through time interval pricing data, data reference is conveniently provided for the investment gravity centers of resource equipment such as advertisement propaganda and the like, and meanwhile investment cost of recovery equipment is facilitated.
Further, the server further comprises the following modules:
a budget analysis module: the cost budget is used for analyzing the cost budget of the customer for putting the advertisement according to the customer information;
a release time analysis module: the system is used for analyzing the preset time length for the advertisement delivery of the client according to the client information;
a release recommendation module: and the system is used for searching the matched advertisement display end, the position information of the advertisement display end, the corresponding flow data and the putting time according to the cost budget, the preset duration and the time interval pricing data, and recommending the advertisement display end, the position information, the corresponding flow data and the putting time to the client.
The advertisement pushing device has the advantages that the advertisement pushing can be accurately achieved according to the conditions of the clients, and therefore the cost of the advertisement pushing is reduced.
Further, the advertisement content analysis method of the advertisement information includes, but is not limited to, natural language analysis NLP, keyword analysis TF-IDF, image recognition ResNet, and image recognition YOLO.
The method and the device are convenient for accurately acquiring the content of the advertisement so as to complete the classification of the advertisement, thereby being convenient for providing data support for accurate advertisement pushing and further reducing the cost of advertisement pushing.
The invention also aims to provide a personalized advertisement broadcasting method based on user portrait, which is applied to the system and comprises the following steps:
user portrait drawing step: obtaining a user representation of an advertisement audience user;
and (3) big data analysis: analyzing hot advertisements in the advertisements played by the advertisement display ends in different setting positions through a big data technology and a user portrait, and analyzing operation scene classification data and time-space thermodynamic diagram data of the hot advertisements;
and (3) advertisement acquisition: acquiring client information and advertisement information to be pushed by a client;
a scene classification step: classifying operation scenes according to the client information and the advertisement content of the advertisement information; matching the operation scene classification data with the time-space thermodynamic diagram data of the corresponding operation scene;
and (3) putting analysis: calculating the optimal delivery time and delivery place of the advertisement information according to the time-space thermodynamic diagram data;
and an advertisement distribution step: and distributing the advertisement information to an advertisement display end corresponding to the putting place, and playing the advertisement information at the optimal putting time.
The principle and the advantages are as follows:
1. the user portrait step is set, so that the user portrait of the advertisement audience user can be obtained, and the users in various places can conveniently know what the users like and what the users do not like; therefore, data support is made for accurate pushing of the advertisement. Moreover, the service objects of the advertisements can be focused and concentrated more through the user portrait; thereby improving the advertising effect.
2. The big data analysis step is set, so that hot advertisements in advertisements played by advertisement display ends in different setting positions can be analyzed, and operation scene classification data and time-space thermodynamic diagram data of the hot advertisements are analyzed; by operating the scene classification data and the time-space thermodynamic diagram data, on one hand, a client can provide data reference for subsequent advertisement delivery conveniently, and on the other hand, required advertisements can be provided for audience users on the other hand. Thereby convenient accurate advertisement propelling movement of carrying on.
3. The setting of the scene classification step, the putting analysis step and the advertisement distribution step can calculate the optimal putting time and the putting place of the advertisement information according to the client information and the advertisement content of the advertisement information, thereby facilitating the accurate advertisement push. But also can improve the advertising effect of the advertisement and reduce the cost of advertisement pushing.
Further, the method also comprises the following steps:
a flow obtaining step: acquiring flow data of an advertisement display end corresponding to the hotspot advertisement;
and (3) interval classification step: and generating time interval pricing data for advertisement putting of each advertisement display end according to the operation scene classification data, the time space thermodynamic diagram data and the flow data of the hot spot advertisements.
The pricing of the resources is realized through the pricing data of the time intervals, the advertisement pushing can be accurately realized conveniently according to the conditions of the clients, and meanwhile, the investment center of the resources and the investment cost of the recovery equipment are facilitated.
Further, the method also comprises the following steps:
budget analyzing step: analyzing the cost budget of the customer for delivering the advertisement according to the customer information;
and (3) analyzing the putting time: analyzing the preset time length for putting the advertisement by the client according to the client information;
and a release recommendation step: and searching the matched advertisement display end, the position information of the advertisement display end, the corresponding flow data and the putting time according to the cost budget, the preset duration and the time interval pricing data, and recommending to the client.
The advertisement pushing device has the advantages that the advertisement pushing can be accurately achieved according to the conditions of the clients, and therefore the cost of the advertisement pushing is reduced.
Further, the advertisement content analysis method of the advertisement information includes, but is not limited to, natural language analysis NLP, keyword analysis TF-IDF, image recognition ResNet, and image recognition YOLO. The method and the device are convenient for accurately acquiring the content of the advertisement so as to complete the classification of the advertisement, thereby being convenient for providing data support for accurate advertisement pushing and further reducing the cost of advertisement pushing.
It is another object of the present invention to provide a computer-readable storage medium, wherein the computer-readable storage medium includes a personalized advertisement broadcasting program based on a user portrait, and when the personalized advertisement broadcasting program based on the user portrait is executed by a processor, the steps of the personalized advertisement broadcasting method based on the user portrait are implemented.
Drawings
FIG. 1 is a logic block diagram of a personalized advertising delivery system based on a user representation according to an embodiment of the present invention.
Detailed Description
The following is further detailed by way of specific embodiments:
examples
A personalized advertising delivery system based on a user representation, substantially as described with reference to figure 1: the system comprises a server, a client and an advertisement display end, wherein the client and the advertisement display end are in communication connection with the server, the client is used for customers to use, and the customer group comprises enterprises, shop merchants or individuals. The advertisement show end is the display screen and places in each position, for example the corridor of market passes through, the corridor passageway of elevator, the corridor passageway of subway etc. gather people's flow easily place. But also can be arranged on buildings of shops and shopping streets. The advertisement showing end is used for playing advertisements to users of clients (audience groups of the advertisements), and the server comprises:
a user portrait module: the system is used for collecting and filtering user behavior logs and storing important contents so as to obtain a user portrait of an advertisement audience user; wherein the user portrayal can make the service object of the advertisement focus and concentrate more. The user portrait belongs to a mature data analysis in the field of big data analysis, so details of the user portrait are not repeated in this embodiment.
Big data analysis module: the system is used for analyzing hot spot advertisements, local advertisement trends, hot spot advertisement contents and the like in the advertisements played by the advertisement display ends with different setting positions through a big data technology and user portrait, and analyzing operation scene classification data and time-space thermodynamic diagram data of the hot spot advertisements according to map data and position distribution data of the advertisement display ends; the time-space thermodynamic diagram data specifically comprises a time thermodynamic diagram and a space thermodynamic diagram. The time thermodynamic diagram can conveniently know which time period has the highest flow rate, and the space thermodynamic diagram can conveniently know which place has the highest flow rate.
The advertisement acquisition module: the system comprises a client, a server and a server, wherein the client is used for acquiring client information and advertisement information to be pushed by a client through the client; the customer information comprises the shop name, the operation range, the cost budget for putting the advertisement, the preset time for putting the advertisement and the like of the customer. And the advertisement information to be pushed is the finished product advertisement which needs to be delivered and played by the client.
A scene classification module: the system is used for classifying operation scenes according to the client information and the advertisement content of the advertisement information; matching the operation scene classification data with the time-space thermodynamic diagram data of the corresponding operation scene; the advertisement content analysis method of the advertisement information comprises methods of natural language analysis (NLP), keyword analysis (TF-IDF), image recognition (ResNet), image recognition (YOLO) and the like, so that the advertisement content can be clearly known, and the subsequent operation scene classification can be facilitated. The operation scene classification is used for analyzing the advertisement classification suitable for the corresponding operation scene through (including but not limited to) a collaborative filtering algorithm and the like, recommendation and a recent algorithm, a support vector machine and other traditional data analysis algorithms and a deep learning algorithm.
A release analysis module: the system comprises a database, a database server and a database server, wherein the database is used for storing the time-space thermodynamic diagram data;
the advertisement distribution module: and the advertisement information is distributed to the advertisement display end corresponding to the putting place and is played in the best putting time. For example, mr. chen needs to advertise for his bookstore to increase efficiency. The system of the embodiment can automatically match the advertising spots around the school and the office building and carry out centralized delivery in the dining time. For example, many mr's need to advertise to massage shops. The system of the present embodiment automatically matches the advertisement spots in the periphery of the office building, where the advertisement is delivered at office hours, and the advertisement spots in the periphery of the apartment building, where the advertisement is delivered at rest hours. For example, a property company puts in new open floor advertisements. The system scheme of the implementation automatically matches places with large pedestrian volume, and performs recurrent delivery in the time with high pedestrian volume of the store.
A flow acquisition module: the method comprises the steps of obtaining flow data of an advertisement display end corresponding to the hotspot advertisement;
an interval grading module: and generating time interval pricing data for advertisement putting of each advertisement display end according to the operation scene classification data, the time space thermodynamic diagram data and the flow data of the hot spot advertisements.
A budget analysis module: the cost budget is used for analyzing the cost budget of the customer for putting the advertisement according to the customer information;
a release time analysis module: the system is used for analyzing the preset time length for the advertisement delivery of the client according to the client information;
a release recommendation module: and the system is used for searching the matched advertisement display end, the position information of the advertisement display end, the corresponding flow data and the putting time according to the cost budget, the preset duration and the time interval pricing data, and recommending the advertisement display end, the position information of the advertisement display end, the corresponding flow data and the putting time to the client. For example, mr. chen needs to place advertisements for their bookstores, which is a low cost. The system of the embodiment can automatically match the advertising spots around the school and the office building and carry out centralized delivery in the dining time. For example, many mr need to place advertisements for massage shops, and the placement cost is low. The system of the present embodiment automatically matches the advertisement spots in the periphery of the office building, where the advertisement is delivered at office hours, and the advertisement spots in the periphery of the apartment building, where the advertisement is delivered at rest hours. For example, a certain property company puts new open floor advertisements, and the putting cost is high. The system scheme of the implementation automatically matches places with large pedestrian volume, and performs recurrent delivery in the time with high pedestrian volume of the store.
A personalized advertisement broadcasting method based on user portrait is applied to the system and specifically comprises the following steps:
user portrait drawing step: obtaining a user representation of an advertisement audience user;
and (3) big data analysis: analyzing hot advertisements in the advertisements played by the advertisement display ends in different setting positions through a big data technology and a user portrait, and analyzing operation scene classification data and time-space thermodynamic diagram data of the hot advertisements;
and (3) advertisement acquisition: acquiring client information and advertisement information to be pushed by a client;
a scene classification step: classifying operation scenes according to the client information and the advertisement content of the advertisement information; matching the operation scene classification data with the time-space thermodynamic diagram data of the corresponding operation scene; the advertisement content analysis method of the advertisement information includes, but is not limited to, natural language analysis NLP, keyword analysis TF-IDF, image recognition ResNet and image recognition YOLO. And the operation scene classification is used for analyzing the advertisement classification suitable for the corresponding operation scene through (including but not limited to) a collaborative filtering algorithm and the like together with the recommendation and a traditional data analysis algorithm such as a recent algorithm, a support vector machine and the like.
And (3) putting analysis: calculating the optimal delivery time and delivery place of the advertisement information according to the time-space thermodynamic diagram data;
and an advertisement distribution step: and distributing the advertisement information to an advertisement display end corresponding to the putting place, and playing the advertisement information at the optimal putting time.
A flow obtaining step: acquiring flow data of an advertisement display end corresponding to the hotspot advertisement;
and (3) interval classification step: and generating time interval pricing data for advertisement putting of each advertisement display end according to the operation scene classification data, the time space thermodynamic diagram data and the flow data of the hot spot advertisements.
Budget analyzing step: analyzing the cost budget of the customer for delivering the advertisement according to the customer information;
and (3) analyzing the putting time: analyzing the preset time length for putting the advertisement by the client according to the client information;
and a release recommendation step: and searching the matched advertisement display end, the position information of the advertisement display end, the corresponding flow data and the putting time according to the cost budget, the preset duration and the time interval pricing data, and recommending to the client.
A computer readable storage medium having a user representation-based personalized advertising transmission program embodied therein, the user representation-based personalized advertising transmission program when executed by a processor implementing the steps of the user representation-based personalized advertising transmission method.
It will be understood by those skilled in the art that all or part of the processes of the above-described personalized advertisement broadcasting method based on user portrait may be implemented by a computer program instructing associated hardware, where the program may be stored in a non-volatile computer readable storage medium, and when executed, the program may include the processes of the above-described embodiments of the personalized advertisement broadcasting method based on user portrait. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The foregoing is merely an example of the present invention, and common general knowledge in the field of known specific structures and characteristics is described herein in more detail, so that a person of ordinary skill in the art can understand all the prior art in the field and have the ability to apply routine experimentation before the present date, after knowing that all the common general knowledge in the field of the invention before the application date or the priority date of the invention, and the person of ordinary skill in the art can, in light of the teaching provided herein, combine his or her own abilities to complete and implement the present invention, and some typical known structures or known methods should not become an obstacle to the implementation of the present invention. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (9)
1. Personalized advertisement broadcasting system based on user portrait, including server and advertisement show end, advertisement show end and server communication connection, the server includes:
a user portrait module: the system comprises a user portrait for obtaining advertisement audience users;
the method is characterized in that: the server further comprises the following modules:
big data analysis module: the system is used for analyzing hot advertisements in the advertisements played by the advertisement display ends in different setting positions through a big data technology and a user portrait, and analyzing operation scene classification data and time-space thermodynamic diagram data of the hot advertisements;
the advertisement acquisition module: the system comprises a server and a server, wherein the server is used for acquiring client information and advertisement information to be pushed by a client;
a scene classification module: the system is used for classifying operation scenes according to the client information and the advertisement content of the advertisement information; matching the operation scene classification data with the time-space thermodynamic diagram data of the corresponding operation scene;
a release analysis module: the system comprises a database, a database server and a database server, wherein the database is used for storing the time-space thermodynamic diagram data;
the advertisement distribution module: and the advertisement information is distributed to the advertisement display end corresponding to the putting place and is played in the best putting time.
2. The user representation based personalized advertising delivery system of claim 1, wherein: the server further comprises the following modules:
a flow acquisition module: the method comprises the steps of obtaining flow data of an advertisement display end corresponding to the hotspot advertisement;
an interval grading module: and generating time interval pricing data for advertisement putting of each advertisement display end according to the operation scene classification data, the time space thermodynamic diagram data and the flow data of the hot spot advertisements.
3. The user representation based personalized advertising delivery system of claim 2, wherein: the server further comprises the following modules:
a budget analysis module: the cost budget is used for analyzing the cost budget of the customer for putting the advertisement according to the customer information;
a release time analysis module: the system is used for analyzing the preset time length for the advertisement delivery of the client according to the client information;
a release recommendation module: and the system is used for searching the matched advertisement display end, the position information of the advertisement display end, the corresponding flow data and the putting time according to the cost budget, the preset duration and the time interval pricing data, and recommending the advertisement display end, the position information, the corresponding flow data and the putting time to the client.
4. The user representation based personalized advertising delivery system of claim 1, wherein: the advertisement content analysis method of the advertisement information includes, but is not limited to, natural language analysis NLP, keyword analysis TF-IDF, image recognition ResNet and image recognition YOLO.
5. The personalized advertisement broadcasting method based on the user portrait is characterized by comprising the following steps:
user portrait drawing step: obtaining a user representation of an advertisement audience user;
and (3) big data analysis: analyzing hot advertisements in the advertisements played by the advertisement display ends in different setting positions through a big data technology and a user portrait, and analyzing operation scene classification data and time-space thermodynamic diagram data of the hot advertisements;
and (3) advertisement acquisition: acquiring client information and advertisement information to be pushed by a client;
a scene classification step: classifying operation scenes according to the client information and the advertisement content of the advertisement information; matching the operation scene classification data with the time-space thermodynamic diagram data of the corresponding operation scene;
and (3) putting analysis: calculating the optimal delivery time and delivery place of the advertisement information according to the time-space thermodynamic diagram data;
and an advertisement distribution step: and distributing the advertisement information to an advertisement display end corresponding to the putting place, and playing the advertisement information at the optimal putting time.
6. The method of claim 5, wherein the personalized advertising presentation based on the user representation comprises: further comprising the steps of:
a flow obtaining step: acquiring flow data of an advertisement display end corresponding to the hotspot advertisement;
and (3) interval classification step: and generating time interval pricing data for advertisement putting of each advertisement display end according to the operation scene classification data, the time space thermodynamic diagram data and the flow data of the hot spot advertisements.
7. The method of claim 6, wherein the personalized advertising presentation based on the user representation comprises: further comprising the steps of:
budget analyzing step: analyzing the cost budget of the customer for delivering the advertisement according to the customer information;
and (3) analyzing the putting time: analyzing the preset time length for putting the advertisement by the client according to the client information;
and a release recommendation step: and searching the matched advertisement display end, the position information of the advertisement display end, the corresponding flow data and the putting time according to the cost budget, the preset duration and the time interval pricing data, and recommending to the client.
8. The method of claim 5, wherein the personalized advertising presentation based on the user representation comprises: the advertisement content analysis method of the advertisement information includes, but is not limited to, natural language analysis NLP, keyword analysis TF-IDF, image recognition ResNet and image recognition YOLO.
9. A computer-readable storage medium characterized by: the computer readable storage medium includes a user representation-based personalized advertising transmission program, which when executed by a processor implements the steps of the user representation-based personalized advertising transmission method of any one of claims 4 to 6.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114841749A (en) * | 2022-05-17 | 2022-08-02 | 广东鑫洋互联网科技有限公司 | Accurate business information pushing method based on LBS and machine learning |
| CN116805255A (en) * | 2023-06-05 | 2023-09-26 | 深圳市瀚力科技有限公司 | Advertisement automatic optimizing throwing system based on user image analysis |
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2021
- 2021-12-24 CN CN202111600888.9A patent/CN114331522A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114841749A (en) * | 2022-05-17 | 2022-08-02 | 广东鑫洋互联网科技有限公司 | Accurate business information pushing method based on LBS and machine learning |
| CN114841749B (en) * | 2022-05-17 | 2024-05-28 | 鑫洋互联网科技(广州)有限公司 | Accurate business information pushing method based on LBS and machine learning |
| CN116805255A (en) * | 2023-06-05 | 2023-09-26 | 深圳市瀚力科技有限公司 | Advertisement automatic optimizing throwing system based on user image analysis |
| CN116805255B (en) * | 2023-06-05 | 2024-04-23 | 深圳市瀚力科技有限公司 | Advertisement automatic optimizing throwing system based on user image analysis |
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