WO2022092776A1 - Serveur pour fournir une plateforme publicitaire et système associé - Google Patents

Serveur pour fournir une plateforme publicitaire et système associé Download PDF

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Publication number
WO2022092776A1
WO2022092776A1 PCT/KR2021/015133 KR2021015133W WO2022092776A1 WO 2022092776 A1 WO2022092776 A1 WO 2022092776A1 KR 2021015133 W KR2021015133 W KR 2021015133W WO 2022092776 A1 WO2022092776 A1 WO 2022092776A1
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information
advertisement
user
user terminal
information indicating
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PCT/KR2021/015133
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English (en)
Korean (ko)
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채중규
조승현
권태인
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주식회사 알파브라더스
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Publication of WO2022092776A1 publication Critical patent/WO2022092776A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising

Definitions

  • the present invention relates to a server and system for providing an advertisement platform.
  • US Patent Registration No. 8438170, US Patent Registration No. 9105048, US Publication No. 2006-0282312 and Korean Patent Publication No. 10-2020-0019397 disclose a method of providing an advertisement service.
  • a consumer relevance value related to an item is determined based on a cooperative filtering algorithm, and information related to an item is transmitted to a consumer based on the consumer relevance value
  • the cooperative filtering algorithm is a consumer create a ranked list of items based on the transaction history associated with the consumer, the consumer's demographics, the consumer profile, the transaction account type, the transaction account associated with the consumer, Re-rank the ranked list of items based on
  • an advertisement server providing an advertisement service, comprising: an advertisement selecting unit for selecting one instant product advertisement from among a plurality of pre-stored instant product advertisements based on media content being reproduced in a user terminal; At least one interaction among a plurality of interactions preset in relation to the advertisement object unit and the advertisement object for transmitting the advertisement object of the selected instantaneous product advertisement to the user terminal at the viewing time for viewing the media content in the user terminal; An advertisement providing unit for providing an instant product advertisement corresponding to the advertisement object to the user terminal based on whether or not occurred, wherein the plurality of interactions include at least one of a speech interaction and a touch interaction occurring through the user terminal start to do
  • the present invention intends to propose a server and a system for providing an enhanced advertisement platform.
  • An embodiment of the present invention aims to provide a server and a system for providing an advertisement platform.
  • an embodiment of the present invention has an object to provide an artificial intelligence-based marketing automation solution.
  • a management server operating an advertisement platform includes: a communication module for receiving first information input by a user through the advertisement platform from a user terminal executing the advertisement platform; and controlling information indicating a plurality of advertisement categories to be output through the user terminal, obtaining first selection information of a user corresponding to the plurality of advertisement categories from the user terminal, the first selection information and the first information a control module for controlling to generate information indicating a plurality of recommended advertisement companies based on and output the information through the user terminal; includes
  • the first information includes the user's personal information, information indicating the user's industry type, information indicating the user's marketing purpose, and information indicating the available budget of the user.
  • control module is characterized in that, based on the user's first information, generating information indicating a recommendation score corresponding to each of the plurality of advertisement categories and controlling to output the generated information through the user terminal.
  • the control module includes a block chain module, and the block chain module generates recommendation score block data corresponding to the information indicating the recommendation score and transmits it to the user terminal.
  • An advertisement platform operating method of a management server includes: receiving first information input by a user through the advertisement platform from a user terminal executing the advertisement platform; controlling information indicating a plurality of advertisement categories to be output through a user terminal; obtaining first selection information of a user corresponding to a plurality of advertisement categories from the user terminal; and generating information indicating a plurality of recommended advertisement companies based on the first selection information and the first information and controlling the generation to be output through the user terminal.
  • the present invention discloses a computer-readable recording medium in which a program for executing an advertisement platform operating method is recorded.
  • the present invention discloses a computer program stored in a medium to execute an advertisement platform operating method using a computer.
  • an embodiment of the present invention may provide an artificial intelligence-based marketing automation solution to the user.
  • the effects obtainable in the present invention are not limited to the above-mentioned effects, and other effects not mentioned may be clearly understood by those of ordinary skill in the art to which the present invention belongs from the following description. will be.
  • FIG. 1 is a diagram illustrating a system for providing an advertisement platform according to an embodiment of the present invention.
  • FIG. 2 is a block diagram illustrating a management server operating an advertisement platform according to an embodiment of the present invention.
  • FIG. 3 is a flowchart illustrating a method of operating an advertisement platform according to an embodiment of the present invention.
  • FIG. 4 is a diagram for explaining an advertisement platform according to an embodiment of the present invention.
  • FIG. 5 is a diagram for explaining an advertisement platform according to an embodiment of the present invention.
  • FIG. 6 is a diagram for explaining an advertisement platform according to an embodiment of the present invention.
  • FIG. 7 and 8 are flowcharts illustrating a method of operating an advertisement platform according to an embodiment of the present invention.
  • FIG. 9 is a block diagram illustrating a control module of a management server according to an embodiment of the present invention.
  • FIG. 7 is a flowchart illustrating a method of operating an advertisement platform according to an embodiment of the present invention.
  • the management server 110 may include obtaining first information (S710).
  • the first information may include information indicating the user's industry type, information indicating the user's marketing purpose, information indicating a budget available to the user, and may further include personal information of the user.
  • the management server 110 may include calculating a category recommendation score for each of a plurality of advertisement categories based on the first information (S720).
  • the plurality of advertisement categories may include place advertisements, blog advertisements, SNS advertisements, image advertisements, video advertisements, pop-up advertisements, voice advertisements, and the like.
  • the place advertisement may include a map for a specific place.
  • the category recommendation score may be information indicating the obtained first information about the user and the relevance, suitability, and marketing success potential of each of the plurality of advertisement categories.
  • control module 210 is the user's personal information, information representing the user's industry (first industry information, second industry information), information representing the user's marketing purpose, information representing the budget available to the user
  • a category recommendation score (and/or information indicating a category recommendation score) may be determined or generated based on at least one of
  • information indicating the category recommendation score may be generated by the artificial intelligence module 910 and/or the block chain module 920 of the control module 210, which will be described later.
  • an advertisement category that is effective marketing with respect to the first industry information and/or the second industry information among the plurality of advertisement categories may have a higher category recommendation score. (and/or the first recommendation bonus point may be reflected).
  • An may be the first recommendation bonus point corresponding to the nth advertisement category among the N advertisement categories.
  • N is the number of a plurality of advertisement categories
  • n is a category corresponding to the nth when N categories are sequentially arranged (1 ⁇ n ⁇ N).
  • R may be an arbitrary value set to express the first recommended additional point value as 0 to 100, and for example, R may be set to '50'.
  • Xmn is an effect value of 0 to 50 on the marketing effect of the n-th advertisement category on the m-th industry information, and this effect value may be a preset value.
  • M is the number of second type of industry information corresponding to the first type of industry information, and m may mean industry information corresponding to the mth when M pieces of industry information are listed in order. (1 ⁇ m ⁇ M)
  • an advertisement category with a high probability of performing advertisement within a budget available to the user may be set with a higher category recommendation score (and/or category recommendation).
  • the second recommended additional point may be reflected in the score).
  • Bn may be a second recommendation bonus point corresponding to the nth advertisement category among the N advertisement categories.
  • N is the number of a plurality of advertisement categories
  • n is a category corresponding to the nth when N categories are sequentially arranged (1 ⁇ n ⁇ N).
  • R may be an arbitrary value set to express the first recommended additional point value as 0 to 100, and for example, R may be set to '50'.
  • P may be the user's available budget.
  • Yn may mean a category execution budget for the n-th.
  • an advertisement category that is effective marketing may have a higher category recommendation score. (and/or a third recommended bonus point may be reflected).
  • Cn may be a third recommendation plus point corresponding to the nth advertisement category among the N advertisement categories.
  • N is the number of a plurality of advertisement categories
  • n is a category corresponding to the nth when N categories are sequentially arranged (1 ⁇ n ⁇ N).
  • Zln is an effect value of 0 to 50 on the marketing effect of the n-th advertisement category for the l-th marketing purpose, and this effect value may be a preset value.
  • L is the number of marketing purpose items, and l may mean a marketing purpose corresponding to the lth when L marketing purposes are sequentially arranged. (1 ⁇ l ⁇ L)
  • control module 210 may assign different weights to the first to third recommendation points. That is, the control module 210 may give weights to the recommended additional points corresponding to the items for which the user's marketing objectives are preset to be weighted.
  • the product promotion item may be preset to give twice the weight. This is because the marketing effect according to the type of advertisement for sales improvement, corporate promotion, and product promotion is relatively superior to that of advertisement type according to industry information or budget range.
  • control module 210 may assign a double weight to the recommended additional points corresponding to the corresponding purpose.
  • the brand recognition item among information indicating the user's marketing purpose may be preset to give three times the weight. This is because the marketing effect according to the advertisement type of the brand recognition item is significantly superior to that of the advertisement type according to the industry information or the budget range.
  • control module 210 may assign a three-fold weight to the recommended additional points corresponding to the corresponding purpose.
  • control module 210 considers the marketing purpose as a factor more important than the industry information or the available budget range when the user's marketing purpose is to improve sales, corporate promotion, product promotion, and/or brand awareness. to give weight, and based on this, it is possible to calculate a recommendation score for an advertisement category.
  • the formula for calculating the recommended score is as follows.
  • Dn may be a recommendation score corresponding to the nth advertisement category among the N advertisement categories.
  • N is the number of a plurality of advertisement categories
  • n is a category corresponding to the nth when N categories are sequentially arranged (1 ⁇ n ⁇ N).
  • Wl may be a weight for marketing purposes corresponding to the l-th. Wl may be preset among values between 1 and 5 according to marketing purposes.
  • L is the number of marketing purpose items, and l may mean a marketing purpose corresponding to the lth when L marketing purposes are sequentially arranged. (1 ⁇ l ⁇ L)
  • the management server 110 may include outputting the category recommendation score through the user terminal (S730).
  • the management server 110 may control information indicating the category recommendation score to be output through a website and/or a mobile app output from the user terminal 120 .
  • the management server 110 may include outputting the category recommendation score and category information corresponding thereto through the user terminal (S740).
  • the management server 110 may control to generate information on a category having a high category recommendation score among a plurality of advertisement categories and output it through the user terminal 120 .
  • each category recommendation score may be displayed together, and the website and/or mobile app of the present invention displays information representing the plurality of advertisement categories in the order of the highest recommendation score. or you can print it out.
  • the method may include the step of the management server 110 acquiring the first selection information corresponding to the plurality of advertisement categories through the user terminal (S750).
  • the user may select at least one of a plurality of advertisement categories on the website and/or mobile app. For example, the user may touch or click at least one of a plurality of advertisement categories displayed through the website and/or mobile app, i) a signal corresponding to the touch is transmitted to the management server 110, The management server 110 may generate the first selection information, or ii) the user terminal 120 may generate and transmit the first selection information corresponding to the touch to the management server 110 .
  • the S710 to S750 may be implemented sequentially, but the order may be changed and implemented, and only some of the S710 to S750 may be implemented in combination with other substrates (methods) of the present invention.
  • FIG. 8 is a flowchart illustrating a method of operating an advertisement platform according to an embodiment of the present invention.
  • the method according to an embodiment of the present invention may include generating, by the management server 110 , information indicating a matching score based on the user's first information ( S810 ).
  • the matching score may be information indicating the degree of relevance, suitability, and recommendation between the user and each of the plurality of recommended advertisement companies.
  • control module 210 includes the user's personal information, information representing the user's industry (first industry information, second industry information), information representing the user's marketing purpose, information representing the budget available to the user, the user Matching score ( and/or information indicative of a match score). Also, the information indicating the matching score may be generated by the artificial intelligence module 910 and/or the block chain module 920 of the control module 210, which will be described later.
  • the matching score may be set higher. Also, for example, if the user has a history of using an advertisement service at the corresponding company and/or has a history of payment using the advertisement service, the matching score of the corresponding advertisement company may be set higher (and/or Alternatively, the first matching additional point may be reflected in the matching score).
  • the matching score may be set higher (and/or the second matching bonus may be reflected in the matching score) there is).
  • the matching score may be set higher.
  • an advertising service that can be provided only with the user's reward (points) For an advertising company supporting
  • the management server 110 may set a higher matching score for the corresponding company (and/or the fourth matching added point may be reflected in the matching score).
  • the method may include the step of the management server 110 outputting information indicating the matching score (S820).
  • the management server 110 may control the information indicating the matching score to be output through a website and/or a mobile app output from the user terminal 120 .
  • the method may include the step of the management server 110 generating information indicating a plurality of recommended advertisement companies and outputting the information through the user terminal (S830).
  • the management server 110 may control to generate information indicating a plurality of recommended advertisement companies supporting at least one advertisement category corresponding to the first selection information and output the information through the user terminal 120 .
  • Each of the information indicating the plurality of recommended advertising companies may be displayed together with a matching score, and the website and/or mobile app of the present invention displays information indicating the plurality of recommended advertising companies in the order of the highest matching score. or you can print it out.
  • the method may include the step of the management server 110 acquiring the second selection information corresponding to the plurality of recommended advertising companies through the user terminal (S840).
  • the user may select at least one of a plurality of advertising companies on the website and/or mobile app. For example, the user may touch or click at least one of a plurality of advertising companies displayed through the website and/or mobile app, i) a signal corresponding to the touch is transmitted to the management server 110
  • the management server 110 may generate the second selection information, or ii) the user terminal 120 may generate and transmit the second selection information corresponding to the touch to the management server 110 .
  • S810 to S840 may be sequentially implemented, but the order may be changed and implemented, and only some of S810 to S840 may be implemented in combination with other descriptions (methods) of the present invention.
  • FIG. 9 is a block diagram illustrating a control module of a management server according to an embodiment of the present invention.
  • control module 210 of the management server 110 may include an artificial intelligence module 910 and a block chain module 920 .
  • the AI module 910 may i) generate a recommendation score for a plurality of advertisement categories, and/or ii) generate a matching score for an advertisement company based on the AI network.
  • the artificial intelligence module 910 uses machine learning on big data stored in the storage module 250 to i) generate a recommendation score for a plurality of advertisement categories, and/or ii) You can create a matching score for the advertiser.
  • the artificial intelligence module 910 may learn the artificial intelligence network by using the big data stored in the storage module 250 of the management server 110 as an input variable.
  • the artificial intelligence module 910 may perform learning so that an accurate correlation can be derived using a deep learning technique, which is a field of machine learning.
  • the artificial intelligence module 910 may include a plurality of second users (ie, previous customers) who used the website and/or mobile app prior to the first user using the website and/or mobile app of the present invention.
  • the artificial intelligence network can be trained by using the information input by the user as learning data.
  • the artificial intelligence module 910 may learn the artificial intelligence network according to a first learning mode, and the artificial intelligence module 910 may i) the second user input in the first learning mode.
  • personal information of the second user information indicating the type of business of the second user (the first type of information of the second user, information about the second type of business of the second user), information indicating the marketing purpose of the second user, available to the second user
  • the artificial intelligence network may be trained by using the information indicating the difference between the received time points as learning data.
  • the artificial intelligence module 910 may obtain an output from the learned artificial intelligence network based on an input input to the learned artificial intelligence network as described above.
  • the input may be the user's first information, the user's first selection information, etc.
  • the output may be the i) the recommendation score and/or ii) the matching score (and/or information indicating the matching score).
  • the artificial intelligence module 910 may i) generate a recommendation score for a plurality of advertisement categories, and/or ii) generate a matching score (and/or information indicating the matching score).
  • the artificial intelligence module 910 may calculate a weight of a plurality of inputs in the function through deep learning through learning.
  • various models such as RNN (Recurrent Neural Network), DNN (Deep Neural Network), and DRNN (Dynamic Recurrent Neural Network) may be used as an AI network model used for such learning.
  • RNN is a deep learning technique that considers current data and past data at the same time.
  • Recurrent neural network refers to a neural network in which connections between units constituting an artificial neural network constitute a directed cycle.
  • various methods may be used for a structure capable of constructing a recurrent neural network (RNN), for example, a fully recurrent network, a hopfield network, an Elman network, an ESN (Echo). state network), long short term memory network (LSTM), bi-directional RNN, continuous-time RNN (CTRNN), hierarchical RNN, and secondary RNN are representative examples.
  • methods for learning a recurrent neural network (RNN) methods such as gradient descent, Hessian Free Optimization, and Global Optimization Method may be used.
  • the block chain module 920 is configured to include the recommendation score and/or the information representing the matching score so that the information representing the matching score can be transmitted to another network node (eg, the user terminal 120) based on the block chain technology. Based on the recommendation score and/or the matching score block data may be generated. Recommendation score and/or matching score block data generated by the block chain module 920 may be transmitted to the user terminal 120 through the communication module 220 . Also, the management server 110 may store at least one element included in the recommendation score and/or the matching score block data in the block chain 252 (not shown).
  • a block chain is a decentralized storage that cannot be forged and/or tampered with, created and managed by a peer-to-peer (P2P) network.
  • a block chain refers to a collection of data blocks created by transactions (indivisible unit work between two parties) one after another in the form of a chain. Since the previous block is encrypted one after another and data agreed by more than half of the users is recognized as real data, it is impossible to forge and/or falsify data once recorded.
  • a typical application of block chain is Bitcoin, a decentralized electronic currency that records the transaction process of cryptocurrency. Confirmed transaction details that occur between users for a certain period of time can be stored in the block chain. And, many users each have their own copy of the blockchain, and transaction details can be made public to everyone. In this way, only the transaction details agreed by more than half of the users are recognized as real data, and can be stored in blocks to be stored permanently.
  • each of the management server 110, the user terminal 120, and the first network node 130 to the fourth network node 160 of the present invention is a block chain node that includes a block chain or can control block data.
  • the management server 110 groups the first information received from the user terminal 120, the first selection information, the second selection information, information indicating a recommended advertisement company, information indicating a matching score, and/or the like. After hashing and storing in the block chain, forgery and/or falsification of the first information, the first selection information, the second selection information, information indicating a recommended advertising company, information indicating a recommendation score and/or a matching score, etc. can be verified or judged.
  • the blockchain module 920 generates a recommendation score and/or matching score block data including a Merkle hash based on information indicating a recommendation score and/or a matching score, and , information indicating a plurality of recommendation scores and/or matching scores may be grouped to include the generated Merkle hash.
  • the management server 110 converts the contents to be stored in the storage module 250 (eg, recommendation score and/or matching score block data including a Merkle hash based on information indicating the recommendation score and/or matching score) as a blockchain transaction. It can be created and transmitted to other blockchain nodes (120, 130, 140, 150, 160) participating in the blockchain network 100 .
  • the information indicating the recommendation score and/or the matching score to be stored in the blockchain transaction may include a Merkle hash identifier, a group identifier, and/or an identifier of a previous group.
  • Management server 110 based on at least one of a predetermined time and the number of information indicating the stored recommendation score and/or matching score, the at least one element stored in the block chain 252 and the grouped recommendation score and / Alternatively, the integrity of the stored recommendation score and/or the information indicating the matching score may be verified by comparing at least one element included in the information indicating the matching score. When the information indicating the stored recommendation score and/or matching score is not integrity, the management server 110 may output the integrity status through the output module 240 .
  • the management server 110 is an administrator (eg, a second user) who manages the management server 110 . ) may output the integrity or not through the output module 240 so that the information can be known.
  • the control module 210 may generate a certificate for determining the integrity of the stored block chain and transmit it to the other block chain nodes 120, 130, 140, 150, 160.
  • the certificate may include information of information indicating the stored at least one recommendation score and/or matching score, information of information indicating the grouped recommendation score and/or matching score, and information of the stored block chain.
  • the certificate may be used by the management server 110 to determine whether information indicating the recommendation score and/or the matching score is integrity.
  • the control module 210 is configured to allow the request of at least one element to the stored block chain i) through a website and/or mobile app that provides or supports an information providing service indicating the recommendation score and/or matching score of the present invention. , and/or ii) when received from another blockchain node (120, 130, 140, 150, 160), i) output the requested at least one element through the website and/or mobile app, and/or ii) It can be transmitted to other blockchain nodes (120, 130, 140, 150, 160).
  • the method of controlling the system 100, the management server 110, the user terminal 120, and/or the network entity 130, 140, 150, 160, etc. according to the present invention may be performed through various computer means. It may be implemented in the form of a program instruction that can be recorded on a computer-readable medium.
  • various embodiments of the present invention described above may be performed through an embedded server provided in the electronic device or an external server of the electronic device.
  • the various embodiments described above are a recording medium (readable by a computer or similar device) using software, hardware, or a combination thereof. It may be implemented as software including instructions stored in a computer readable recording medium). In some cases, the embodiments described herein may be implemented by the processor itself. According to the software implementation, embodiments such as the procedures and functions described in this specification may be implemented as separate software modules. Each of the software modules may perform one or more functions and operations described herein.
  • a computer or a similar device is a device capable of calling a stored command from a storage medium and operating according to the called command, and may include the device according to the disclosed embodiments.
  • the processor may directly or use other components under the control of the processor to perform a function corresponding to the instruction. Instructions may include code generated or executed by a compiler or interpreter.
  • the device-readable recording medium may be provided in the form of a non-transitory computer readable recording medium.
  • 'non-transitory' means that the storage medium does not include a signal and is tangible, and does not distinguish that data is semi-permanently or temporarily stored in the storage medium.
  • the non-transitory computer-readable medium refers to a medium that stores data semi-permanently, rather than a medium that stores data for a short moment, such as a register, cache, memory, etc., and can be read by a device.
  • Specific examples of the non-transitory computer-readable medium may include a CD, DVD, hard disk, Blu-ray disk, USB, memory card, ROM, and the like.

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Abstract

La présente invention se rapporte à un serveur pour fournir une plateforme publicitaire et à un système associé. Un mode de réalisation de la présente invention présente un serveur de gestion pour faire fonctionner une plateforme publicitaire, comprenant : un module de communication pour recevoir, en provenance d'un terminal utilisateur pour exécuter la plateforme publicitaire, des premières informations entrées par un utilisateur par l'intermédiaire de la plateforme publicitaire ; et un module de commande pour commander de telle sorte que des informations indiquant une pluralité de catégories publicitaires soient délivrées par l'intermédiaire du terminal utilisateur, des premières informations de sélection de l'utilisateur correspondant à la pluralité de catégories publicitaires soient obtenues à partir du terminal utilisateur et des informations indiquant une pluralité d'agences publicitaires recommandées soient générées sur la base des premières informations de sélection et des premières informations de façon à être délivrées par l'intermédiaire du terminal utilisateur.
PCT/KR2021/015133 2020-04-29 2021-10-26 Serveur pour fournir une plateforme publicitaire et système associé WO2022092776A1 (fr)

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KR20140122310A (ko) * 2013-04-09 2014-10-20 박동명 스마트 기기를 이용한 모바일 광고 방법 및 그 시스템
KR102066371B1 (ko) * 2019-03-26 2020-01-14 김보언 블록체인 기반 에이전시 매칭방법, 장치 및 프로그램
KR102133539B1 (ko) * 2020-04-07 2020-07-13 채중규 광고 플랫폼을 제공하는 서버 및 그 시스템
KR102162827B1 (ko) * 2020-05-21 2020-10-07 허브넷굿컴퍼니닷컴 주식회사 마케팅 정보 제공 플랫폼을 지원하는 시스템

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