CN111882362A - Artificial intelligence advertisement delivery system based on 5G communication network - Google Patents
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Abstract
The invention relates to an artificial intelligence advertisement putting system based on a 5G communication network, which comprises: the acquisition unit is used for acquiring user portrait data and modeling the user portrait data according to a preset mode; the advertisement recommendation unit is internally provided with heterogeneous advertisement materials, acquires historical browsing information of a user through the acquisition unit, collects advertisement materials of user traffic, extracts text keywords through analysis and establishes an advertisement tag database; the method comprises the steps that an advertisement tag database is cleaned according to the similarity between advertisement materials browsed by a user and a user interest set to obtain user preference information, the user preference information is weighted, and advertisement materials interesting to the user are obtained and sorted; the delivery unit optimizes the data of the advertisement materials which are sequenced at the front by using an algorithm and carries out intelligent directional delivery; and the training unit is used for receiving the user behavior information, integrating the multi-dimensional behavior data under multiple scenes, acquiring the backflow data, inputting the backflow data into the neural network model, performing model training and generating more accurate advertisement label data.
Description
Technical Field
The invention relates to an advertisement delivery system, in particular to an artificial intelligent advertisement delivery system based on a 5G communication network.
Background
In the application practice of mobile internet advertisement under the application of user-oriented thinking, the key point is that the needs and psychology of users are thoroughly known, and a large amount of manpower and time cost is consumed for accurately subdividing and judging target users, which undoubtedly also brings a practical bottleneck to large-scale advertisement delivery.
However, when a new artificial intelligence technology appears and is applied to advertisement propagation, not only can users be quickly identified to obtain information and high-standard user segmentation be realized, but also an advertisement content analyst can predict user behaviors and advertisement effects based on an algorithm model of the analyst, so that the quality and efficiency of advertisement analysis work are improved to a great extent, and the delivery cost is reduced.
The current 5G era comes, and the 5G communication technology mainly has three characteristics: the transmission speed is fast, the quality is high and the intelligence is integrated. First, in a network environment with enhanced transmission speed and quality, users will have a greater degree of dependence on the mobile internet, so their concentration on mobile terminals and usage time will increase, which undoubtedly brings a jet of east wind to mobile advertising marketing. Moreover, the existing mobile advertisement is limited by the transmission speed, the occupied ratio of the video advertisement is not high, and the concept of the product and the brand cannot be completely shown, but in the 5G era, the occupied ratio of the video advertisement may be increased, and the playing time length of the video advertisement is correspondingly adjusted. Secondly, the real intelligent integration of everything interconnection can be realized in a 5G network platform, for example, the application of unmanned technology and telemedicine needs to be based on the high-speed network environment, and an entrance is opened for realizing multi-field penetration of mobile interconnection advertisement propagation. Meanwhile, in the aspect of the expression form, the mobile internet advertisement has more space for selection and imagination, and can interact with the user in a richer form.
The traditional capturing, storing and data analyzing technology cannot be matched with the traditional capturing, storing and data analyzing technology, on one hand, a large amount of new data cannot be effectively collected, on the other hand, in the data analyzing process, due to the fact that the relevance between the captured data is not available, the data analyzing model is inaccurate, and finally the behavior characteristics of the user cannot be accurately grasped.
Disclosure of Invention
The invention overcomes the defects of the prior art and provides an artificial intelligent advertisement delivery system based on a 5G communication network.
In order to achieve the purpose, the invention adopts the technical scheme that: an artificial intelligence advertisement putting system based on 5G communication network, comprising:
the acquisition unit is used for acquiring user portrait data and modeling the user portrait data according to a preset mode;
the advertisement recommendation unit is internally provided with heterogeneous advertisement materials, acquires user behavior information through the acquisition unit, collects advertisement materials of user traffic, extracts text keywords through analysis and establishes an advertisement tag database;
the method comprises the steps that an advertisement tag database is cleaned according to the similarity between advertisement materials browsed by a user and a user interest set to obtain user preference information, the user preference information is weighted, and advertisement materials interesting to the user are obtained and sorted;
the delivery unit optimizes the data of the advertisement materials which are sequenced at the front by using an algorithm and carries out intelligent directional delivery;
the training unit is used for receiving user behavior information, integrating multi-dimensional behavior data under multiple scenes to obtain backflow data, inputting the backflow data into a neural network model, performing model training and generating more accurate advertisement label data;
and the control unit is used for controlling the information call of the releasing unit, the acquisition unit and the database.
In a preferred embodiment of the present invention, the neural network model can be a convolutional neural network, the reflow data is input into the convolutional neural network, a plurality of feature maps are generated by performing a local convolution calculation through a convolution kernel, nonlinear data is output through an activation function, and features of a user and an advertisement are extracted.
In a preferred embodiment of the present invention, the recommendation system further includes a scoring unit, wherein the scoring unit scores the advertisement preference by the user to obtain a scoring matrix, and obtains the user with high similarity through analysis of the scoring matrix to obtain the recommendation list.
In a preferred embodiment of the invention, the scoring unit scores the user into 5 gradients, and the user marks 1 score when clicking the advertisement; the user clicks the advertisement and stays on the advertisement page for more than 10-20s and records the time for 2 minutes; the user stays on the advertisement page for more than 1 minute and is marked as 3 minutes; the user downloads and registers for 4 points; the user generated consumption behavior as 5 points.
In a preferred embodiment of the present invention, the advertisement recommendation unit is capable of generating a behavior log by analyzing the user behavior information.
In a preferred embodiment of the present invention, the user behavior information includes one or more combinations of historical browsing information, historical purchased goods information, historical searched goods information, historical collected data information, and historical searched video resources.
In a preferred embodiment of the invention, the training device further comprises a communication unit, wherein the communication unit is used for communication connection among the acquisition unit, the advertisement recommendation unit, the delivery unit and the training unit, and the communication mode in the communication unit can be selected from Bluetooth or wireless communication.
In a preferred embodiment of the invention, the self-editing unit comprises a touch screen, and a user can edit the portrait data by himself through the touch screen and transmit the portrait data to the advertisement recommending unit to match with advertisement materials with high user similarity.
In a preferred embodiment of the invention, the image data includes basic characteristics for the user, purchasing power, hobbies, behavioral characteristics, and social networking.
In a preferred embodiment of the present invention, the training unit obtains the user behavior information through the learning feedback module, and performs reverse correction on the weighted value of the advertisement material in the delivery unit.
The invention solves the defects in the background technology, and has the following beneficial effects:
(1) this application is on the basis of a large amount of analysis user's actions, through a large amount of user's action analysis, can be accurate match user and suitable advertisement, under the holding of artificial intelligence algorithm, can also carry out continuous self-learning iteration through learning feedback module, very big improvement the precision that the advertisement was put in to can carry out specific input along with situations such as time, region, the audience matching degree obtains very big improvement.
(2) The advertisement front end is displayed under the high-speed holding of a 5G communication network, richer advertisement display materials can be used, such as video advertisements, HTML5 dynamic advertisements and the like, the interactive advertisement form can help advertisement publishers to obtain more user demands, the frequency of watching advertisements by users is greatly improved, and the media can be quickly docked by an advertisement system through an open SDK/API (software development kit/application programming interface) mode.
(3) The method has the advantages that the user is accurately positioned, the advanced technology of artificial intelligence is applied to the advertising industry, and accurate marketing based on big data becomes possible. And the precise positioning is realized by integrating data sets of various layers, types and structures. Breaking barriers of various media resources, realizing data flow, perfecting a data ecological chain and constructing a user behavior characteristic database. The user groups are subdivided, and the user groups with the most requirements are found for advertisement content pushing, so that the advertisement propagation efficiency is improved to a great extent, and the waste of resources is reduced.
(4) The method introduces the scoring unit, measures the interest degree of the user to the advertisement according to the scoring level of the user, and accurately matches and puts the advertisement according to the scoring level.
Drawings
The invention is further illustrated with reference to the following figures and examples.
FIG. 1 is a flow diagram of an artificial intelligence advertising system in accordance with a preferred embodiment of the present invention;
Detailed Description
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
In the description of the present application, it is to be understood that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like are used in the orientation or positional relationship indicated in the drawings for convenience in describing the present application and for simplicity in description, and are not intended to indicate or imply that the referenced devices or elements must have a particular orientation, be constructed in a particular orientation, and be operated in a particular manner, and are not to be considered limiting of the scope of the present application. Furthermore, the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first," "second," etc. may explicitly or implicitly include one or more of that feature. In the description of the invention, the meaning of "a plurality" is two or more unless otherwise specified.
In the description of the present application, it is to be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art through specific situations.
To facilitate an understanding of the invention, the invention will now be described more fully with reference to the accompanying drawings. Preferred embodiments of the present invention are shown in the drawings. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
The invention will now be described in further detail with reference to the accompanying drawings and examples, which are simplified schematic drawings and illustrate only the basic structure of the invention in a schematic manner, and thus show only the constituents relevant to the invention.
As shown in FIG. 1, the present invention discloses a flow chart of an artificial intelligence advertisement delivery system;
specifically, an artificial intelligence advertisement putting system based on 5G communication network includes:
s102, an acquisition unit, a storage unit and a display unit, wherein the acquisition unit is used for acquiring user portrait data and modeling the user portrait data according to a preset mode;
s104, an advertisement recommending unit is provided, different types of advertisement materials are arranged in the advertisement recommending unit, user behavior information is acquired through an acquisition unit, advertisement materials of user traffic are collected, text keywords are extracted through analysis, and an advertisement tag database is established;
s106, an advertisement tag database is cleaned according to the similarity between the advertisement materials browsed by the user and the user interest set to obtain user preference information, the user preference information is weighted, and the advertisement materials interested by the user are obtained and sorted;
s108, a delivery unit performs data optimization on the advertisement materials which are sequenced in the front by using an algorithm, and performs intelligent directional delivery;
s110, a training unit, wherein the training unit is used for receiving user behavior information, integrating multi-dimensional behavior data under multiple scenes to obtain backflow data, inputting the backflow data into a neural network model, and performing model training to generate more accurate advertisement label data;
and S112, a control unit, wherein the control unit is used for controlling the information call of the releasing unit, the collecting unit and the database.
It should be noted that semantic analysis is performed by collecting advertisement material, behavior paths, and the like of user traffic. The user preference for the advertisement content can be promoted by aiming at the similarity between the advertisement material browsed by the user and the user interest set. The whole process is roughly divided into three steps: step one, acquiring an advertisement material text, and expressing a text keyword in a vector mode according to the importance degree of the text keyword through analysis and extraction; and step two, converting the interest set of the user into a vector mode. If the initialization interest set is empty, filling the initialization interest set with a default value; and step three, calculating the degree of association between the two.
According to the embodiment of the invention, the neural network model can be a convolutional neural network, the backflow data is input into the convolutional neural network, local convolution calculation is carried out through a convolution kernel to generate a plurality of feature maps, nonlinear data is output through an activation function, and features of a user and an advertisement are extracted.
According to the embodiment of the invention, the recommendation system further comprises a scoring unit, wherein the scoring unit scores the advertisement preference through the user to obtain a scoring matrix, and obtains the user with high similarity through the analysis of the scoring matrix to obtain the recommendation list.
According to the embodiment of the invention, the scoring unit is used for grading the user into 5 gradients, and the user marks 1 score when clicking the advertisement; the user clicks the advertisement and stays on the advertisement page for more than 10-20s and records the time for 2 minutes; the user stays on the advertisement page for more than 1 minute and is marked as 3 minutes; the user downloads and registers for 4 points; the user generated consumption behavior as 5 points.
It should be noted that, according to the embodiment of the present invention, the advertisement recommendation unit can generate the behavior log by analyzing the user behavior information.
According to the embodiment of the invention, the user behavior information comprises one or more combinations of historical browsing information, historical purchased commodity information, historical searched commodity information, historical collected data information and historical searched video resources.
According to the embodiment of the invention, the intelligent training system further comprises a communication unit, wherein the communication unit is used for communication connection among the acquisition unit, the advertisement recommendation unit, the putting unit and the training unit, and the communication mode in the communication unit can be selected to be a Bluetooth mode or a wireless mode for communication.
According to the embodiment of the invention, the self-editing unit comprises a touch screen, a user can edit the portrait data by himself through the touch screen and transmit the portrait data to the advertisement recommending unit, and the portrait data is matched with advertisement materials with high user similarity.
It should be noted that, a large amount of image data edited by a user is preprocessed and then data cleaning is performed, the cleaning process includes data inspection, account numbers which are invalid are clear, residual user data are extracted, and a unique identification user signature is formulated.
According to an embodiment of the invention, the image data includes basic characteristics for, purchasing power, hobbies, behavioral characteristics, and social networks.
According to the embodiment of the invention, the training unit acquires the user behavior information through the learning feedback module and reversely corrects the weight value of the advertisement material in the launching unit.
This application is on the basis of a large amount of analysis user's actions, through a large amount of user's action analysis, can be accurate match user and suitable advertisement, under the holding of artificial intelligence algorithm, can also carry out continuous self-learning iteration through learning feedback module, very big improvement the precision that the advertisement was put in to can carry out specific input along with situations such as time, region, the audience matching degree obtains very big improvement.
The advertisement front end is displayed under the high-speed holding of a 5G communication network, richer advertisement display materials can be used, such as video advertisements, HTML5 dynamic advertisements and the like, the interactive advertisement form can help advertisement publishers to obtain more user demands, the frequency of watching advertisements by users is greatly improved, and the media can be quickly docked by an advertisement system through an open SDK/API (software development kit/application programming interface) mode.
The method has the advantages that the user is accurately positioned, the advanced technology of artificial intelligence is applied to the advertising industry, and accurate marketing based on big data becomes possible. And the precise positioning is realized by integrating data sets of various layers, types and structures. Breaking barriers of various media resources, realizing data flow, perfecting a data ecological chain and constructing a user behavior characteristic database. The user groups are subdivided, and the user groups with the most requirements are found for advertisement content pushing, so that the advertisement propagation efficiency is improved to a great extent, and the waste of resources is reduced.
The method introduces the scoring unit, measures the interest degree of the user to the advertisement according to the scoring level of the user, and accurately matches and puts the advertisement according to the scoring level.
In light of the foregoing description of the preferred embodiment of the present invention, it is to be understood that various changes and modifications may be made by one skilled in the art without departing from the spirit and scope of the invention. The technical scope of the present invention is not limited to the content of the specification, and must be determined according to the scope of the claims.
Claims (10)
1. An artificial intelligence advertisement putting system based on 5G communication network, its characterized in that includes:
the acquisition unit is used for acquiring and acquiring user portrait data and modeling the user portrait data according to a preset mode;
the advertisement recommendation unit is internally provided with heterogeneous advertisement materials, acquires user behavior information through the acquisition unit, collects advertisement materials of user traffic, extracts text keywords through analysis and establishes an advertisement tag database;
the method comprises the steps that an advertisement tag database is cleaned according to the similarity between advertisement materials browsed by a user and a user interest set to obtain user preference information, the user preference information is weighted, and advertisement materials interesting to the user are obtained and sorted;
the delivery unit optimizes the data of the advertisement materials which are sequenced at the front by using an algorithm and carries out intelligent directional delivery;
the training unit is used for receiving user behavior information, integrating multi-dimensional behavior data under multiple scenes to obtain backflow data, inputting the backflow data into a neural network model, performing model training and generating more accurate advertisement label data;
and the control unit is used for controlling the information call of the releasing unit, the acquisition unit and the database.
2. The artificial intelligence advertising system based on the 5G communication network of claim 1, wherein: the neural network model can be a convolutional neural network, backflow data are input into the convolutional neural network, local convolutional calculation is carried out through a convolutional kernel to generate a plurality of feature maps, nonlinear data are output through an activation function, and features of a user and the advertisement are extracted.
3. The artificial intelligence advertising system based on the 5G communication network of claim 1, wherein: the system also comprises a scoring unit, wherein the scoring unit scores the favor of the advertisement by the user to obtain a scoring matrix, and obtains the user with high similarity by analyzing the scoring matrix to obtain a recommendation list.
4. The artificial intelligence advertising system based on the 5G communication network of claim 4, wherein: the scoring unit is used for grading the user into 5 gradients, and the user marks 1 score when clicking the advertisement; the user clicks the advertisement and stays on the advertisement page for more than 10-20s and records the time for 2 minutes; the user stays on the advertisement page for more than 1 minute and is marked as 3 minutes; the user downloads and registers for 4 points; the user generated consumption behavior as 5 points.
5. The artificial intelligence advertising system based on the 5G communication network of claim 3, wherein: the advertisement recommendation unit can generate a behavior log by analyzing the user behavior information.
6. The artificial intelligence advertising system based on the 5G communication network of claim 1, wherein: the user behavior information comprises one or more of historical browsing information, historical purchased commodity information, historical searched commodity information, historical collected data information and historical searched video resources.
7. The artificial intelligence advertising system based on the 5G communication network of claim 1, wherein: the intelligent advertising training system is characterized by further comprising a communication unit, wherein the communication unit is used for communication connection among the acquisition unit, the advertising recommendation unit, the putting unit and the training unit, and the communication mode in the communication unit can be selected to be communicated in a Bluetooth or wireless mode.
8. The artificial intelligence advertising system based on the 5G communication network of claim 1, wherein: the self-editing unit comprises a touch screen, a user can edit the portrait data through the touch screen, the portrait data are transmitted to the advertisement recommending unit, and the portrait data are matched with advertisement materials with high user similarity.
9. The artificial intelligence advertising system based on the 5G communication network of claim 8, wherein: the image data includes basic characteristics for, purchasing power, hobbies, behavioral characteristics, and social networks.
10. The artificial intelligence advertising system based on the 5G communication network of claim 1, wherein: the training unit acquires user behavior information through the learning feedback module and reversely corrects the weight value of the advertisement material in the launching unit.
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