KR20220104665A - Method and system for providing advertiser service - Google Patents

Abstract

An advertiser service providing method is a service providing method for advertisers, which includes the steps of: receiving information on a product to be sold from an advertiser terminal; from the advertisement server, receiving social network data on the product to be sold from the SNS server, and extracting keywords and favorable impressions from the social network data; estimating, by the advertisement server, the expected sales volume of the product to be sold based on the preference through an estimation model; calculating, by the advertisement server, an advertisement cost based on the estimated sales volume; and providing, by the advertisement server, each data of the estimated sales volume and actual sales volume to the advertiser terminal.

Description

Method and system for providing advertiser service

The present invention relates to a method and system for providing advertiser services. In detail, it relates to a method and system for operating product advertisements for advertisers.

In general, the seller who sells products online or offline is most interested in how to maximize profits by selecting good products and selling many products at an appropriate profit.

A seller who purchases goods from a manufacturer or imports and sells goods from a foreign country spends a lot of money and time to find good products do or do In addition, the manufacturer invests a lot of time and money to develop a new product and mass-produce it, and spends a lot of advertising money to advertise the new product in order to maximize the sales of the developed and manufactured new product.

It is very important to predict in advance how much the product the seller wants to sell can be sold to customers in order to avoid risk and manage the business stably. It is also important for management to invest in marketing expenses based on the predicted sales volume.

The problem to be solved by the present invention is to provide a method for determining the needs of general consumers for advertisement target products, automatically predicting sales volume accordingly, and calculating an advertisement cost budget according to the predicted sales volume. will be.

An advertiser service providing method according to an embodiment of the present invention for solving the above problem is a service providing method for an advertiser, comprising the steps of: an advertisement server receiving information about a product to be sold from an advertiser terminal; receiving social network data on the item for sale from a server, extracting keywords and favorable feelings from the social network data; retrieving competitive product information so that the advertisement server calculates the operating profit of the competing product, the advertisement server calculating the advertisement cost based on the operating profit of the competing product, the expected sales volume, and the favorable feeling and providing, by the advertisement server, each data of the expected sales volume and the actual sales volume to the advertiser terminal.

In the step of extracting the keyword and favorable impression, the shopping mall advertisement server searches for a user post by the name of the item to be sold in the SNS server, and performs natural language processing in the searched user post for the name and sale of the item to be sold. After a similar word of the target article is set as the keyword, the keyword may be extracted.

In the step of extracting the keyword and the goodwill, the shopping mall advertisement server scores the user post based on the number of times the keyword is extracted using the goodwill, the frequency with which the keyword is extracted, and the sentiment information of the keyword. Thereafter, a user posting greater than or equal to a preset reference value may be selected as a candidate user posting.

The advertisement server may repeat the scoring operation a plurality of times when there is no user posting equal to or greater than the preset reference value in the scoring result.

In the step of estimating the expected sales volume, the shopping mall advertisement server includes the previous month's sales volume, the total number of user posts searched for by the name of the item to be sold, the candidate user post, the sale price of the item to be sold, and the item to be sold. The expected sales volume may be estimated based on an average price of the same type of article and a weight value according to the favorable feeling.

The weight value may be determined through a weight prediction model provided from an artificial neural network.

In the step of retrieving the competitive product information, the shopping mall advertisement server acquires the previous sales sales volume of the competitive product, the previous advertisement cost and the favorable impression information from the information stored in the shopping mall advertisement server, and in the step of calculating the advertisement cost, The advertisement cost may be calculated based on at least one of the operating profit of the competing product calculated based on the information obtained in the step of searching the competitive product information and the factors used to estimate the expected sales volume.

The shopping mall advertisement server, in the step of calculating the advertisement cost, calculates the advertisement cost based on the estimated monthly sales volume estimated in the step of estimating the expected sales volume and the actual sales volume in the previous month, wherein the advertisement cost may be different from month to month can

In a non-transitory recording medium according to an embodiment of the present invention for solving the above problems, a program for executing the method for providing the advertiser service is recorded and read by a computer.

A computer program according to an embodiment of the present invention for solving the above problems is recorded in a non-transitory recording medium in order to execute the method for providing the advertiser service in the advertisement server that provides the service to the advertiser.

An advertisement server according to an embodiment of the present invention for solving the above problem includes at least one processor, and instructions for instructing the at least one processor to perform at least one operation. An advertisement server for providing a service to an advertiser, the advertisement server comprising a memory for storing receiving social network data on the item for sale from an SNS server, extracting keywords and favorable feelings from the social network data; estimating, the advertisement server searching for competitive product information to calculate the operating profit of the competitor product, the advertisement server calculating the advertisement cost based on the operating profit of the competitor product, the expected sales volume, and the favorable feeling and providing, by the advertisement server, each data of the expected sales volume and the actual sales volume to the advertiser terminal.

An advertisement service providing system according to an embodiment of the present invention for solving the above problems is a system for providing a service to an advertiser, wherein at least one processor and the at least one processor perform at least one operation ( operation), an advertisement server including a memory for storing instructions instructing to perform the operation, an artificial neural network connected to the advertisement server, and a communication network connected to the advertisement server through a communication network to provide social network data An SNS server, and an advertiser terminal connected to the advertisement server through the communication network and installed with a program for providing the service, wherein the at least one operation is performed by the advertisement server from the advertiser terminal information on the item to be sold receiving, by the advertisement server, receiving social network data for the item to be sold from an SNS server, and extracting keywords and favorable feelings from the social network data; estimating the expected sales volume of the item to be sold, the advertisement server retrieving competitive product information to calculate the operating profit of the competing product, the advertisement server performing the operating profit of the competing product, the expected sales volume and calculating an advertisement cost based on the favorable feeling, and providing, by the advertisement server, each data of the expected sales volume and the actual sales volume to the advertiser terminal.

According to an embodiment of the present invention, it is possible to automatically provide a predicted sales volume for an item to be sold, thereby minimizing a loss in marketing cost investment.

1 is a configuration diagram schematically showing the overall configuration of an advertisement providing system according to an embodiment of the present invention.
2 is a flowchart related to a method for providing an advertiser service according to an embodiment of the present invention.
3 is a diagram illustrating a process in which an advertisement providing system according to an embodiment of the present invention calculates an expected sales volume and an advertisement cost.
4 is a diagram illustrating a configuration of an estimation model included in an advertisement server according to an embodiment of the present invention.
5 is a diagram for explaining an artificial neural network according to an embodiment of the present invention.
6 is a diagram illustrating a configuration of an estimation model provided in an advertisement server according to an embodiment of the present invention.
7 is a graph illustrating an expected sales volume of an item to be sold according to the presence or absence of advertising cost of a competing product.
8 is a graph displaying information on expected sales volume and actual sales volume according to an embodiment of the present invention.
9 is a diagram illustrating a wireless communication system that can be applied in a communication process according to an embodiment of the present invention.
FIG. 10 is a diagram illustrating a base station in the wireless communication system according to FIG. 9 .
11 is a diagram illustrating a terminal in the wireless communication system of FIG. 9 .
12 is a diagram illustrating a communication interface in the wireless communication system according to FIG. 9 .
13 is a diagram exemplarily illustrating a hardware configuration of an advertisement server according to an embodiment of the present invention.

Advantages and features of the present invention and methods of achieving them will become apparent with reference to the embodiments described below in detail in conjunction with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but will be implemented in a variety of different forms, only these embodiments allow the disclosure of the present invention to be complete, and common knowledge in the technical field to which the present invention belongs It is provided to fully inform the possessor of the scope of the invention, and the present invention is only defined by the scope of the claims.

The singular expression includes the plural expression unless the context clearly dictates otherwise. Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a configuration diagram schematically showing the overall configuration of an advertisement providing system according to an embodiment of the present invention.

The advertisement providing system may provide the advertiser with information on the expected sales volume of the item (product) for sale. The advertisement providing system may set a differentiated advertisement cost according to the expected sales volume for each item to be sold, and may provide information on change in sales volume according to the advertisement cost.

Referring to FIG. 1 , the advertisement providing system may include an advertisement server 10 , an SNS server 20 , and an advertiser terminal 30 .

The advertisement server 10 provides a service for estimating the expected sales volume of an advertiser's sale item through an estimation model (eg, 190 in FIG. 4 ), a service for setting a differential advertisement cost according to the expected sales volume, and a change in sales volume according to the advertisement cost It may include a function of providing a service for displaying information.

The advertisement server 10 may store information on a plurality of products. For example, the advertisement server 10 may store information such as past sales volume of a plurality of products and previously calculated advertisement costs. As an embodiment, the advertisement server 10 may include a function for searching and extracting necessary information from information on a plurality of products stored in the advertisement server 10 .

The advertisement server 10 provides the above services (hereinafter, advertiser service) through an artificial intelligence model learned based on machine learning (machine learning) provided from the artificial neural network 11 connected to the advertisement server 10. can

In an embodiment, the advertisement server 10 may obtain data related to the sale item and the consumer's preference data related to the sale item from the SNS server 20 , and may estimate the expected sales volume based on the data.

The advertisement server 10 may provide advertiser services through programs (or applications) installed in each of the advertiser terminals 30 . Here, the program refers to software developed so that a user can perform a specific task using a device. In addition, a program may consist of instructions necessary to perform a specific task. Here, the commands constituting the program may be different from each other according to the type of the operating system.

The advertiser terminal 30 may be configured to receive an advertiser service provided by the advertisement server 10 through a program installed in the advertiser terminal 30 . For example, when the advertiser uploads information on items to be sold to the advertisement server 10 through the advertiser terminal 30 , the advertiser terminal 30 controls the advertisement server 10 to control the expected sales volume of the item for sale and advertisement cost. And it may be configured to display sales volume change information according to the advertising cost.

The advertiser terminal 30 may include a processor, a controller, an integrated circuit, a programmable logic circuit, or other database and signal processing device in any combination, in addition to one or more memories, a transmitter and a receiver, a display, and It may include a communication module capable of communicating with various devices. In addition, it may include a computer program that performs data operation through a specified algorithm and displays the result so that it can be recognized from the outside through a display, and a buyer interface (UI; User Interface) implemented so that the buyer can operate it. can The advertiser terminal 30 may include any device or equipment including a memory associated with a processor. A processor may implement an operating system and may execute computer programs known as instructions, software codes, executables, applications, apps, and the like.

For example, the advertiser terminal 30 may include a smart phone, a personal computer, a laptop computer, a mobile communication device (including a wireless device), a workstation, a tablet computer, or a portable digital assistant (PDA), respectively.

In the advertiser terminal 30 , a program for receiving the advertiser service from the advertisement server 10 may be installed. The advertiser terminal 30 may include a non-transitory storage medium in which the advertiser service program is stored. According to an embodiment, a plurality of advertiser terminals 30 may be provided in the advertisement providing system.

The SNS server 20 may store various services and data related to a plurality of contents provided from each of the various services. In various embodiments, the SNS server 20 may include a server that provides a social network service (SNS). The SNS server 20 may store social data that users who use the SNS service upload through their accounts. In various embodiments, the SNS server 20 may include a management server for a website related to product content (eg, product review), and the SNS server 20 includes data on the number of members of the website, data on the increase/decrease in the number of members. and post increase/decrease data. In various embodiments, the social data may include social data in the form of text, social data in the form of an image, and social data in the form of a video.

In various embodiments, the SNS server 20 may receive a transmission request of data related to a specific item from the advertisement server 10 through the communication network 40 , and according to the transmission request, a specific item among a large amount of pre-stored data It is possible to extract only the related data and provide it to the advertisement server 10 .

According to an embodiment, a plurality of advertisement servers 10 may be provided in the advertisement providing system.

Communication between the advertisement server 10 , the SNS server 20 , and the advertiser terminal 30 may be performed through the communication network 40 . The communication network 40 may use standard communication technologies and/or protocols related to wired/wireless networks.

2 is a flowchart related to a method for providing an advertiser service according to an embodiment of the present invention. 3 is a diagram illustrating a process in which an advertisement providing system according to an embodiment of the present invention calculates an expected sales volume and an advertisement cost. 4 is a diagram illustrating a configuration of an estimation model included in an advertisement server according to an embodiment of the present invention. 5 is a diagram for explaining an artificial neural network according to an embodiment of the present invention. 6 is a diagram illustrating a configuration of an estimation model provided in an advertisement server according to an embodiment of the present invention. 7 is a graph illustrating an expected sales volume of an item to be sold according to the presence or absence of advertising cost of a competing product. 8 is a graph displaying information on expected sales volume and actual sales volume according to an embodiment of the present invention.

Referring to FIG. 2 , the advertiser service providing method includes a target product information reception step (S110), a target product related data collection step (S120), an estimated sales volume estimation step (S130), a competitive product information search step (S140), and advertisement cost calculation It includes a step (S150) and a step (S160) of providing sales volume change data of the target article.

In the present specification, it is described that each step is performed in turn according to the flowchart, but unless the spirit of the invention is changed, some steps shown to be performed in succession are performed simultaneously, the order of some steps is changed, or some steps are performed It is obvious that , may be omitted, or other steps may be further included between each step.

Referring to FIG. 2 , the step of receiving target product information ( S110 ) corresponds to a step in which the advertisement server 10 receives information on the target product from the advertiser terminal 30 .

For example, the advertiser may input information such as the type of item to be sold, detailed specifications, and price into the advertiser terminal 30 . In this step, the advertiser terminal 30 may provide information input by the advertiser to the advertisement server 10 .

Referring to FIGS. 2 and 3 , in the step S120 of collecting the relevant data of the target article, the advertisement server 10 receives the social network data 210 for the target article from the SNS server 20, and the social network data ( 210) corresponds to the step of extracting keywords and favorable feelings.

First, the advertisement server 10 may search for a user post in the SNS server 20 with the name of the item to be sold. Here, the search result may be social network data 210 . The social network data 210 may include a plurality of user posts 220 .

Thereafter, the advertisement server 10 may extract keywords from each of the searched user posts 220 and extract goodwill information. The advertisement server 10 extracts keywords from the searched user posts 220 and performs natural language processing (NLP) on the extracted keywords to determine at least one topic for each post and an article covered by the posts. can For example, natural language processing is a framework or algorithm that can implement natural language processing, Python's NTLK (Python NLTK), Sanford's CoreNLP (Sanford CoreNLP), Apache's OpenNLP (Apache OpenNLP), Microsoft It can be implemented using Turing, BERT, GPT-2, or the like.

The advertisement server 10 may determine the association between the corresponding user post 220 and the item to be sold based on the extracted keyword. For example, the advertisement server 10 may extract the name of the item to be sold and a similar word of the item to be sold from each user post 220 using a pre-built data dictionary. The advertisement server 10 may set both the name of the product to be sold and a similar word of the target product as keywords, and extract the keyword from the user post 220 . The advertisement server 10 may determine the number and frequency of keywords for each user post 220 .

The advertisement server 10 may obtain favorable impression information of each user post 220 based on a function of displaying a good feeling (eg, an icon such as 'like') provided for each user post 220 in the SNS server 20 . have.

The advertisement server 10 may score each user post 220 by using a keyword for each user post 220 . For example, the advertisement server 10 determines the number of times keywords are extracted from within the plurality of user posts 220 , the frequency with which keywords are extracted, and emotional information of the keywords (eg, whether the extracted keyword is a keyword indicating a positive meaning, or A score may be calculated for each of the plurality of user posts 220 based on (information indicating whether the keyword indicates a negative meaning).

Also, the advertisement server 10 may select a candidate post from among the plurality of user posts 220 according to the scoring result. For example, the advertisement server 10 may configure the user posts 220 (eg, user posts 220) in which a result value calculated as a scoring result among a plurality of user posts 220 is equal to or greater than a preset reference value (eg, 60 points). #1, #2, and #N) may be selected as candidate user posts 220 .

The advertisement server 10 performs the operation of scoring the plurality of user posts 220 multiple times when there is no user post 220 whose result value calculated as a scoring result is equal to or greater than a preset reference value among the plurality of user posts 220 . It can be repeated over and over again.

In one embodiment, various means for scoring a plurality of user posts 220 may be utilized. For example, information on the number of mentions of the user post 220 itself, users' liking for the user post 220 , users' expectations for the item in the user post 220 , and the type of item users want, etc. are collected. and can be created.

For example, even if the user's post 220 itself is often mentioned and the likeability is high, users may not necessarily want the item. Therefore, there is a need to analyze the user's expectations for the item of the user post 220, which may require an additional step different from the method of analyzing the popularity, liking, or recognition of the user post 220 itself. .

For example, when a reference is made to the user post 220 , other keywords mentioned together with the corresponding user post 220 may be collected in association. Positive and negative words associated with the user post 220 may be classified from the collected keywords, and keywords related to articles corresponding to a pre-stored article database may be classified. For example, the article database may refer to a database storing information on the types of articles that can be manufactured or are currently sold. For example, as the number of times that users mention a keyword corresponding to a specific user post 220 and a keyword such as a cup or cell phone case together increases, the number of times that users mention a keyword such as a cup or a cell phone case together increases the number of times that users use a cup or a cell phone case made from the corresponding user post 220 . It can be judged that the product is expected to be manufactured. The advertisement server 10 may not only check the user's expectations for product sales from the collected information, but may also check information that the users want a specific type of product in some cases. 2 and 4 , the estimated sales volume estimation step S130 corresponds to a step in which the advertisement server 10 estimates the sales target sales volume of the item to be sold based on the data collected through the SNS server 20 .

The advertisement server 10 may include an estimation model 190 for estimating the expected sales volume and calculating the advertisement cost. In an embodiment, the estimation model 190 may estimate the expected sales volume using the collected goodwill information. For example, the estimation model 190 may estimate the next month's expected sales volume (S ₁ ) of the item to be sold by applying Equation 1 below.

In Equation 1, R ₀ is the sales volume (actual sales volume) in the previous month of the item to be sold, #P is the total number of user posts 220 searched for by the name of the item to be sold, and #P _C is the user post that is greater than or equal to the scoring result criterion value. (candidate user posts), R is the sale price of the item to be sold, R _D is the average price of the same type of item as the item to be sold, and δ corresponds to a weighted value according to the favorable feeling.

In a similar manner to the above, the estimation model 190 may determine the sales volume S ₂ after 2 months and the sales volume S ₃ after 3 months by applying Equation 2 .

1, 2, and 5 , the advertisement server 10 may determine a weight δ according to the good feeling through the artificial neural network 11 .

In an embodiment, the weight may be determined through the weight prediction model 320 provided from the artificial neural network 11 . The artificial neural network 11 is a predictive model implemented in software or hardware that mimics the computational power of a biological system using a large number of artificial neurons (or nodes).

The weight prediction model 320 may be supervised by the weight prediction model learning unit 310 using characteristic values and coefficient weights of training data. In this case, supervised learning refers to learning to find an output value according to a given input value using data having an input value and an output value corresponding thereto as learning data, and means learning performed in a state where the correct answer is known. The set of input and output values given to supervised learning is called training data. That is, the above-described characteristic value of the training data is an input value, and the favorable sensitivity weight of the training data is an output value, which may be used as training data for supervised learning of the weight prediction model 320 .

For example, the weight prediction model learning unit 310 converts a characteristic value of the training data into a unique first one-hot vector to generate an input value, and sets the camera parameter of the training data to a unique value. After generating an output value by converting it into a second one-hot vector, the weight prediction model 320 may be supervised by using the generated input and output values. Here, the first one-hot vector and the second one-hot vector may be vectors in which one of component values constituting the vector is '1' and the other component values are configured as '0'.

In one example, the weight prediction model 320 receives an input value, and has a connection strength (or weight) for each of the output values of the input layer and the input layer having nodes corresponding to the number of components of the first one-hot vector. one or more hidden layers outputting by multiplying by and adding a bias; and an output layer for multiplying each output value of the hidden layer by a connection strength (or weight) and outputting the result using an activation function. Here, the activation function may be a LeRU function or a Softmax function, but is not limited thereto. Connection strength and bias can be continuously updated by supervised learning.

Specifically, the weight prediction model 320 is to be supervised so that the output value of the loss function according to the given input value (first one-hot vector) and output value (second one-hot vector) is minimized. can For example, the loss function H(Y, Y`) may be defined as in Equation 3 below.

In Equation 3, Ym may be the m-th component of the second one-hot vector, and Yom may be the m-th component of the output vector output by receiving the first one-hot vector from the weight prediction model 320 .

As the amount of training data increases, more supervised learning is performed on the weight prediction model 320 to increase the accuracy of the weight prediction model 320 .

An artificial neural network may be used for the weight prediction model 320 . For example, the weight prediction model 320 may be implemented as a Bidirectional LSTM (Bi-LSTM) or a Convolutional Neural Network (CNN).

The weight prediction model 320 may predict a weight according to the favorable feeling of the user post 220 by using the test data input from the user.

2, 4, 8 and 9, in the competitive product information search step (S140), the advertisement server 10 calculates the operating profit of the product to be sold and the same product (competitive product), the competitor product This corresponds to the step of searching for information on the advertisement server 10 in the advertisement server 10 . The advertisement cost calculation step ( S150 ) corresponds to a step in which the advertisement server 10 calculates the advertisement cost based on the estimated sales volume estimated in the estimated sales volume estimation step ( S130 ).

In an embodiment, the advertisement server 10 may include information on a plurality of advertisers. For example, the advertisement server 10 may store information such as sales volume, market share, and advertisement cost for various products. Accordingly, information on products for various advertisers as well as the corresponding advertiser may be stored in the advertisement server 10 .

In one embodiment, the advertisement server 10 may predict the operating profit for each product of a plurality of advertisers. For example, the advertisement server 10 applies Equation 4 below to predict the previous month's operating profit ( _OC ) for each product of a plurality of advertisers based on the sales volume, market share, advertisement cost, and favorability. .

In Equation 4, S _C is the previous sales volume of the competitive product, W _C is the previous advertisement cost of the competitive product, β is a weighted value according to the market share of the competitive product ( _MC ), and γ is the favorable sensitivity of the competitive product. It is a weight value according to the numerical value (δ _C ). Similar to that described above, the good feeling value of the competitive product may be obtained based on a display function of a good feeling (eg, an icon such as 'like') provided for each user post 220 in the SNS server 20 .

In one embodiment, the advertisement server 10 may calculate the advertisement cost based on factors used to estimate the expected sales volume, the expected sales volume, and the operating profit of the competing product (in Equation 4). In one embodiment, the advertisement server 10 may calculate different advertisement costs for each month for the item to be sold.

Also, in calculating the advertisement cost, the advertisement server 10 may consider information on the same type of product as the product to be sold. In general, when advertising costs increase, it is possible to increase market share for the same product. However, if a competing seller who sells a competing product invests heavily in advertising cost, the increase rate may be lowered even though the market share increases as the advertising cost of the item to be sold is increased (see FIG. 7 ). However, if the advertising cost is lowered, the operating profit per one item to be sold may increase.

For example, the advertisement server 10 may calculate the monthly advertisement cost to have a reasonable value in view of the operating profit and expected sales per one item to be sold. For example, the advertisement server 10 may calculate the monthly advertisement cost by applying Equation 5 below.

9 together, in Equation 5, Q _n is the advertising cost of the nth month, S _n is the expected sales volume of the nth month, R ₀ is the actual sales volume of the previous month, U is the basic advertising unit price set for each item to be sold, and δ corresponds to the weight value according to the favorable feeling. Also, W _C is the previous month's advertising cost of the competitive product, and T ₀ ' corresponds to the percentage change in sales volume of the competitive product in the previous month. In other words, the advertising cost is calculated by dividing the advertising cost by the estimated sales according to the advertising cost, taking into account competing products, determining the advertising cost for which the actual sales in the previous month is the minimum, and then the estimated sales without considering the competing products and the actual sales in the previous month can be determined by multiplying the difference in the basic advertising unit price for each item to be sold compared to the weighted value according to the affinity, multiplying the previous month's advertising cost of the competitive product compared to the previous month's sales change rate of the competitive product, and dividing by the competitor's operating profit in the previous month have. In Equation 5, ε corresponds to a constant value.

As an embodiment, the advertisement server 10 may calculate different advertisement costs for each month as in Equation 5 above. Here, the previous month means the month immediately preceding the month for which advertising costs are calculated. In calculating the advertising cost, by excluding the advertising cost according to the actual sales volume of the previous month from the advertising cost according to the expected sales volume, the cost difference with the advertisement cost based on the actual sales volume can be minimized.

2 and 8, in the step of providing the sales volume change data of the target product (S160), the advertisement server 10 provides each data of the expected sales volume and the actual sales volume of the target product to the advertiser terminal 30. corresponds to The advertiser may check the predicted sales graph and the actual sales graph of the item to be sold displayed through the advertiser terminal 30 .

As an embodiment, the advertisement server 10 may display a graph showing the expected sales volume and the actual sales volume from the advertisement start time to the current point through the advertiser terminal 30 .

9 is a diagram illustrating a wireless communication system that can be applied in a communication process according to an embodiment of the present invention. FIG. 10 is a diagram illustrating a base station in the wireless communication system according to FIG. 9 . 11 is a diagram illustrating a terminal in the wireless communication system of FIG. 9 . 12 is a diagram illustrating a communication interface in the wireless communication system according to FIG. 9 .

Hereinafter, a wireless communication network system (communication network 40) that supports communication between various servers (eg, advertisement server 10 and SNS server 20) and terminals (eg, advertiser terminal 30) of An example is given and demonstrated concretely as an example. In the following description, a first node (device) may be an anchor/donor node or a centralized unit (CU) of an anchor/donor node, and a second node (device) may be an anchor/donor node or a distributed unit (DU) of a relay node. can be

9 to 12 , as a part of a node using a wireless channel in a wireless communication system, a base station (BS), a terminal, a server, and the like may be included.

A base station is a network infrastructure that provides terminals and wireless access to terminals. A base station has coverage defined as a certain geographic area according to the distance over which signals can be transmitted.

A base station is an "access point (AP)", "enodeb (eNB)", "5th generation (5G) node", "wireless point", " It may be referred to as a "transmission/reception point (TRP)".

The base station, the terminal, and the terminal may transmit and receive radio signals in millimeter wave (mmWave) bands (eg, 28 GHz, 30 GHz, 38 GHz, 60 GHz). In this case, the base station, the terminal, and the terminal may perform beamforming to improve the channel gain. Beamforming may include transmit beamforming and receive beamforming. That is, the base station, the terminal, and the terminal may impart directivity to the transmitted signal and the received signal. To this end, the base station, the terminal, and the terminal may select a serving beam through a beam search procedure or a beam management procedure. Thereafter, communication may be performed using a resource that is in a quasi co-located relationship with a resource carrying the serving beam.

The first antenna port and the second antenna port are considered quasi-co-located if the large-scale properties of the channel through which the symbol of the first antenna port is carried can be inferred from the channel through which the symbol of the second antenna port is carried. The large-scale attribute may include one or more of delay spread, Doppler spread, Doppler shift, average gain, average delay, and spatial Rx parameters.

Hereinafter, a base station is exemplified in the above-described wireless communication system. The terms "-module", "-unit" or "-er" used hereinafter may mean a unit that processes at least one function or operation, and includes hardware, software, or hardware and software. can be implemented as a combination of

The base station may include a wireless communication interface, a backhaul communication interface, a storage unit and a controller.

The wireless communication interface performs a function of transmitting and receiving signals through a wireless channel. For example, the wireless communication interface may perform a conversion function between a baseband signal and a bit stream according to a physical layer standard of the system. For example, in data transmission, a wireless communication interface compresses and modulates a transmitted bit stream to produce a complex symbol. In addition, upon data reception, the wireless communication interface demodulates and decodes the baseband signal to reconstruct the received bit stream.

The wireless communication interface performs a function of transmitting and receiving signals through a wireless channel. For example, the wireless communication interface may perform a conversion function between a baseband signal and a bit stream according to a physical layer standard of the system. For example, in data transmission, a wireless communication interface compresses and modulates a transmitted bit stream to produce a complex symbol. In addition, upon data reception, the wireless communication interface demodulates and decodes the baseband signal to reconstruct the received bit stream.

In addition, the wireless communication interface up-converts the base band signal into a radio frequency (RF) band signal, transmits the converted signal through the antenna, and then down-converts the RF band signal received through the antenna into a base band signal. To this end, the wireless communication interface includes a transmission filter, a reception filter, an amplifier, a mixer, an oscillator, a digital-to-analog converter (DAC), It may include an analog-to-digital converter (ADC) and the like. Also, the wireless communication interface may include a plurality of transmission/reception paths. Further, the wireless communication interface may include at least one antenna array including a plurality of antenna elements.

In terms of hardware, the wireless communication interface may include a digital unit and an analog unit, and the analog unit may include a plurality of sub-units according to operating power, operating frequency, and the like. The digital unit may be implemented with at least one processor (eg, a digital signal processor (DSP)).

The wireless communication interface transmits and receives signals as described above. Accordingly, a wireless communication interface may be referred to as a "transmitter", "receiver" or "transceiver". In addition, in the following description, transmission/reception performed through a wireless channel may be used to include processing performed in a wireless communication interface as described above.

The backhaul communication interface provides an interface for performing communication with other nodes in the network. That is, the backhaul communication interface converts the bit stream transmitted to another node, for example, another access node, another base station, a higher node or a core network from a base station converts the physical signal received from the other node into a physical signal. convert to stream

The storage unit stores data such as basic programs, applications, and setting information for operation of the base station. The storage unit may include a volatile memory, a non-volatile memory, or a combination of a volatile memory and a non-volatile memory.

The controller controls the overall operation of the base station. For example, the controller transmits and receives signals through a wireless communication interface or a backhaul communication interface. The controller also writes data to the storage and reads the recorded data. The controller can perform the function of the protocol stack required by the communication standard. According to another implementation, the protocol stack may be included in a wireless communication interface. To this end, the controller may include at least one processor.

According to an embodiment, the controller may control the base station to perform an operation according to an embodiment of the present invention.

According to various embodiments, a donor node of a wireless communication system includes at least one processor, a transceiver operatively coupled to the at least one processor, and a plurality of radio bearers for a terminal accessing the relay node. and send to the relay node a first message including first information related to the donor node regarding receive, from the relay node, a second message including second information related to the relay node regarding a plurality of radio bearers for the terminal; Data for the terminal may be transmitted to the relay node. Data may be transmitted to the terminal through a plurality of radio bearers based on the first information and the second information.

According to various embodiments, a radio bearer among a plurality of radio bearers may aggregate a plurality of radio bearers. the at least one processor is further configured to determine a radio bearer for the terminal accessing the relay node and a multiple radio bearer aggregated by the radio bearer; Alternatively, a radio bearer for a terminal accessing the relay node may be determined.

According to various embodiments, the first message may include one or more of the following: identification of a terminal accessing the relay node; display information indicating the type of terminal accessing the relay node; information on a radio bearer of a terminal accessing a relay node; information on the radio bearer delivered by the terminal accessing the relay node; information on the tunnel established for the radio bearer between the donor node and the relay node; information on the aggregated multiple radio bearers; radio bearer mapping information; information about the address on the side of the donor node; information on the address of the relay node side; indication information corresponding to a radio bearer of a terminal accessing a relay node; indication information indicating the relay node to allocate a new address to a radio bearer for a terminal accessing the relay node; a list of address information that cannot be used by a relay node that transmits data of a radio bearer of a terminal accessing the relay node; and information related to security configuration.

According to various embodiments, the second message may include one or more of the following: identification of a terminal accessing the relay node; information on radio bearers accepted by the relay node; information on radio bearers not acknowledged by the relay node; information on radio bearers partially granted by the relay node; radio bearer mapping information; configuration information of a terminal accessing the relay node generated by the relay node; information on the address of the relay node side; and information related to security configuration.

According to various embodiments, the second message may further include information on the integrated multi-radio bearer.

According to various embodiments, the donor node may include a central unit of the donor node, and the relay node may include a distributed unit of the donor node.

According to various embodiments, a relay node of a wireless communication system includes at least one processor, a transceiver operatively coupled to the at least one processor, and a plurality of terminals accessing the relay node from a donor node. configured to receive a first message including first information related to a donor node regarding a radio bearer of ; transmit a second message including second information related to the relay node regarding the plurality of radio bearers to the terminal to the donor node; It is possible to receive data for the terminal from the donor node. Data may be transmitted to the terminal through a plurality of radio bearers based on the first information and the second information.

According to various embodiments, a radio bearer among a plurality of radio bearers may aggregate a plurality of radio bearers. the at least one processor is further configured to determine a radio bearer for the terminal accessing the relay node and a multiple radio bearer aggregated by the radio bearer; Alternatively, multiple radio bearers aggregated by the radio bearer may be determined.

According to various embodiments, the first message may include one or more of the following: identification of a terminal accessing the relay node; display information indicating the type of terminal accessing the relay node; information on a radio bearer of a terminal accessing a relay node; information on the radio bearer delivered by the terminal accessing the relay node; information on the tunnel established for the radio bearer between the donor node and the relay node; information on the aggregated multiple radio bearers; radio bearer mapping information; information about the address on the side of the donor node; information on the address of the relay node side; indication information corresponding to a radio bearer of a terminal accessing a relay node; indication information indicating the relay node to allocate a new address to a radio bearer for a terminal accessing the relay node; a list of address information that cannot be used by a relay node that transmits data of a radio bearer of a terminal accessing the relay node; and information related to security configuration.

According to various embodiments, the second message may include one or more of the following: identification of a terminal accessing the relay node; information on radio bearers accepted by the relay node; information on radio bearers not acknowledged by the relay node; information on radio bearers partially granted by the relay node; radio bearer mapping information; configuration information of a terminal accessing the relay node generated by the relay node; information on the address of the relay node side; and information related to security configuration.

According to various embodiments, the second message may further include information on the integrated multi-radio bearer.

According to various embodiments, the donor node may include a central unit of the donor node, and the relay node may include a distributed unit of the donor node.

Hereinafter, components of a terminal in the above-described wireless communication system are illustrated. The components of the terminal described below may be merged or integrated with the components of the terminal according to the above-described contents as components of a general-purpose terminal supported by the wireless communication system. Contents described with reference may be interpreted as having priority. The terms “-module”, “-unit” or “-er” used below may refer to a unit that processes at least one function.

The terminal includes a communication interface, a storage unit and a controller.

The communication interface performs a function of transmitting and receiving signals through a wireless channel. For example, the communication interface performs a conversion function between a baseband signal and a bit stream according to the physical layer standard of the system. For example, in data transmission, a communication interface compresses and modulates a transport bit stream to produce a complex symbol. In addition, upon data reception, the communication interface demodulates and decodes the baseband signal to reconstruct the received bit stream. In addition, the communication interface up-converts the base band signal into an RF band signal, transmits the converted signal through the antenna, and then down-converts the RF band signal received through the antenna into a base band signal. For example, the communication interface may include a transmission filter, a reception filter, an amplifier, a mixer, an oscillator, and a digital-to-analog converter (DAC). , an analog-to-digital converter (ADC), and the like.

Also, the communication interface may include a plurality of transmission/reception paths. Further, the communication interface may include at least one antenna array including a plurality of antenna elements. On the hardware side, the wireless communication interface may include a digital circuit and an analog circuit (eg, a radio frequency integrated circuit, RFIC). The digital circuit may be implemented with at least one processor (eg, DSP). The communication interface may include a plurality of RF chains. The communication interface may perform beamforming.

The communication interface transmits and receives signals as described above. Accordingly, a communication interface may be referred to as a "transmitter", "receiver" or "transceiver". In addition, in the following description, transmission/reception performed through a wireless channel may be used to include processing performed in a communication interface as described above.

The storage unit stores data such as basic programs, applications, and setting information for the operation of the terminal. The storage unit may include a volatile memory, a non-volatile memory, or a combination of a volatile memory and a non-volatile memory. In addition, the storage unit provides the stored data according to the request of the controller.

The controller controls the overall operation of the terminal. For example, the controller sends and receives signals through a communication interface. The controller also writes data to the storage and reads the recorded data. The controller can perform the function of the protocol stack required by the communication standard. According to another implementation, the protocol stack may be included in the communication interface. To this end, the controller may include at least one processor or microprocessor or may reproduce a part of the processor. Also, a part of the communication interface or controller may be referred to as a communication processor (CP).

According to an embodiment of the present invention, the controller may control the terminal to perform the operation according to the embodiment of the present invention.

Hereinafter, a communication interface in a wireless communication system is exemplified.

The communication interface includes compression and modulation circuitry, digital beamforming circuitry, a plurality of transmission paths, and analog beamforming circuitry.

The compression and modulation circuitry performs channel compression. At least one of a low-density parity check (LDPC) code, a convolutional code, and a polar code may be used for channel compression. The compression and modulation circuitry generates modulation symbols by performing constellation mapping.

The digital beamforming circuit performs beamforming on a digital signal (eg, a modulation symbol). To this end, the digital beamforming circuit multiplexes the modulation symbols by the beamforming weight value. The beamforming weight may be used to change the size and phrase of a signal, and may be referred to as a “precoding matrix” or a “precoder”. The digital beamforming circuit outputs digital beamformed modulation symbols to a plurality of transmission paths. In this case, modulation symbols may be multiplexed or the same modulation symbol may be provided to a plurality of transmission paths according to a multiple-antenna technology (multiple input multiple output, MIMO) transmission method.

The plurality of transmission paths converts the digital beamformed digital signal into an analog signal. To this end, each of the plurality of transmission paths may include an inverse fast Fourier transform (IFFT) calculation unit, a cyclic prefix (CP) insertion unit, a DAC, and an up-conversion unit. The CP insertion unit is for an orthogonal frequency division multiplexing (OFDM) method and may be omitted when other physical layer methods (eg, a filter bank multi-carrier: FBMC) are applied. That is, the plurality of transmission paths provide independent signal processing processes for a plurality of streams generated through digital beamforming. However, depending on the implementation, some elements of a plurality of transmission paths may be used in common.

The analog beamforming circuit performs beamforming on an analog signal. To this end, the digital beamforming circuit multiplexes the analog signal by the beamforming weight value. Beamformed weights are used to change the size and text of the signal. More specifically, the analog beamforming circuit may be configured in various ways according to a connection structure between the plurality of transmission paths and the antenna. For example, each of the plurality of transmission paths may be connected to one antenna array. In another example, a plurality of transmission paths may be coupled to one antenna array. In another example, the plurality of transmission paths may be adaptively coupled to one antenna array or may be coupled to two or more antenna arrays.

The steps of the method or algorithm described in relation to the embodiment of the present invention may be implemented directly in hardware, implemented as a software module executed by hardware, or implemented by a combination thereof. A software module may include random access memory (RAM), read only memory (ROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, hard disk, removable disk, CD-ROM, or It may reside in any type of computer-readable recording medium well known in the art to which the present invention pertains.

13 is a diagram exemplarily illustrating a hardware configuration of an advertisement server according to an embodiment of the present invention.

Referring to FIG. 13 , the advertisement server 10 stores at least one processor 110 and instructions for instructing the at least one processor 110 to perform at least one operation. It may include a memory 120 .

Here, the at least one processor 110 may mean a central processing unit (CPU), a graphics processing unit (GPU), or a dedicated processor on which methods according to embodiments of the present invention are performed. can The memory 120 may be configured as at least one of a volatile storage medium and a non-volatile storage medium. For example, the memory 120 may be configured as at least one of a read only memory (ROM) and a random access memory (RAM). The storage device 160 may be a hard disk drive (HDD), a solid state drive (SSD), or the like.

Also, the advertisement server 10 may include a transceiver 130 that performs communication through the communication network 40 . Also, the advertisement server 10 may further include an input interface device 140 , an output interface device 150 , a storage device 160 , and the like. Each of the components included in the advertisement server 10 may be connected by a bus 170 to communicate with each other. The advertisement server 10 may include functions such as a push server, a gateway server, and a name server.

As described above, embodiments according to the technical idea of the present invention have been described with reference to the accompanying drawings, but those of ordinary skill in the art to which the present invention pertains will have other specific forms without changing the technical spirit or essential features of the present invention. It will be understood that it can be implemented as It should be understood that the embodiments described above are illustrative in all respects and not restrictive.

10: ad server 11: artificial neural network
110: processor 120: memory
140: input interface device 150: output interface device
160: storage device 190: estimated model
20: SNS server 210: social network data
220: user post 30: advertiser terminal
310: weighted prediction model learning unit 320: weighted prediction model
40: communication network

Claims (10)

A method of providing a service to an advertiser, comprising:
receiving, by the advertisement server, information on the item to be sold from the advertiser terminal;
receiving, by the advertisement server, social network data for the item to be sold from the SNS server, and extracting keywords and favorable feelings from the social network data;
estimating, by the advertisement server, an expected sales volume of the item to be sold based on the favorable feeling through an estimation model;
retrieving, by the advertisement server, competitive product information to calculate the operating profit of the competing product;
calculating, by the advertisement server, an advertisement cost based on the operating profit of the competing product, the expected sales volume, and the favorable feeling; and
Comprising the step of providing, by the advertisement server, each data of the expected sales volume and the actual sales volume to the advertiser terminal, the advertiser service providing method. The method of claim 1,
The commercial advertisement server, in the step of extracting the keyword and favorable impression,
A user post is searched for by the name of the item to be sold in the SNS server, and the keyword is extracted after setting the name of the item to be sold and a similar word of the item to be sold as the keyword through natural language processing in the searched user post How to provide advertiser services. 3. The method of claim 2,
The commercial advertisement server, in the step of extracting the keyword and favorable impression,
After scoring the user post based on the number of times the keyword is extracted using the favorable feeling, the frequency at which the keyword is extracted, and the sentiment information of the keyword, a user post having a value greater than or equal to a preset reference value is selected as a candidate user post How to provide advertiser services. 4. The method of claim 3,
The commercial advertisement server, in the step of estimating the expected sales volume,
Sales in the previous month, the total number of user posts searched for by the name of the item to be sold, the candidate user post, the sale price of the item to be sold, the average price of the item same as the item to be sold, and the weighted value according to the favorable preference Based on the estimated sales volume, an advertiser service providing method. 5. The method of claim 4,
The method for providing an advertiser service, wherein the weight value is determined through an artificial neural network-based weight prediction model. 6. The method of claim 5,
The commercial advertising server,
In the step of retrieving the competitive product information, the previous sales sales volume of the competitive product, the previous advertisement cost and the favorable impression information of the competitive product are obtained from the information stored in the shopping mall advertisement server,
In the step of calculating the advertisement cost, the advertisement cost based on at least one of the factors used to estimate the expected sales volume and the operating profit of the competitive product calculated based on the information obtained in the step of searching the competitive product information A method of providing advertiser services to calculate . A non-transitory recording medium in which a program for executing the method according to claim 1 is recorded and readable by a computer. A computer program recorded in a non-transitory recording medium to execute the method according to claim 1 in an advertisement server providing a service to an advertiser. at least one processor; and
An advertisement server providing a service to an advertiser, comprising a memory storing instructions instructing the at least one processor to perform at least one operation,
The at least one operation is
receiving, by the advertisement server, information on the item to be sold from the advertiser terminal;
receiving, by the advertisement server, social network data for the item to be sold from the SNS server, and extracting keywords and favorable feelings from the social network data;
estimating, by the advertisement server, an expected sales volume of the item to be sold based on the favorable feeling through an estimation model;
retrieving, by the advertisement server, competitive product information to calculate the operating profit of the competing product;
calculating, by the advertisement server, an advertisement cost based on the operating profit of the competing product, the expected sales volume, and the favorable feeling; and
and providing, by the advertisement server, each data of the expected sales volume and the actual sales volume to the advertiser terminal. As a system for providing services to advertisers,
an advertisement server including at least one processor and a memory storing instructions instructing the at least one processor to perform at least one operation;
an artificial neural network connected to the advertisement server;
an SNS server connected to the advertisement server through a communication network to provide social network data; and
and an advertiser terminal connected to the advertisement server through the communication network and installed with a program for providing the service,
The at least one operation is
receiving, by the advertisement server, information on the item to be sold from the advertiser terminal;
receiving, by the advertisement server, social network data for the item to be sold from the SNS server, and extracting keywords and favorable feelings from the social network data;
estimating, by the advertisement server, an expected sales volume of the item to be sold based on the favorable feeling through an estimation model;
retrieving, by the advertisement server, competitive product information to calculate the operating profit of the competing product;
calculating, by the advertisement server, an advertisement cost based on the operating profit of the competing product, the expected sales volume, and the favorable feeling; and
The advertisement service providing system comprising the step of providing, by the advertisement server, each data of the expected sales volume and the actual sales volume to the advertiser terminal.

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