KR102176519B1 - Method and apparatus for operating platform for matching professional - Google Patents

Abstract

The present invention relates to an expert matching platform control method performed by a server. The method includes the steps of: receiving an expert profile information request signal from a terminal; transmitting expert profile information to the terminal; receiving an expert service request signal from the terminal; transmitting the expert service request signal to a payment server; receiving a payment completion confirmation signal from the payment server; transmitting an expert service to the terminal; and determining the degree of exposure to the expert who provides the expert service based on payment information related to the expert service.

Description

Expert Matching Platform Operation Method and Device {METHOD AND APPARATUS FOR OPERATING PLATFORM FOR MATCHING PROFESSIONAL}

The present invention relates to a platform operating method and apparatus for matching a user and an expert, and more particularly, to a method and apparatus for a user to use a service provided by an expert in a non-face-to-face manner.

In the era of the 4th industrial revolution, it is expected that the depth, speed, and range will be greatly expanded based on hyperconnectivity and superintelligence. As a result, not only various industrial fields arise, but also numerous new fields, such as the fusion of existing and new industrial fields, are expected to occur. There is no or very few experts in the field. Therefore, it is necessary to discover and recruit experts in each field, and to cooperate with experts in each field.

In addition, the period of production activities will be extended due to the extended life expectancy in the future, and there is a need for each expert to make the field a “business” for a lifetime, not just a job.

In addition, it is desirable to ensure that 　experts can be treated based on their ability in each field, but in the case of an organization such as an existing company, it is difficult to make use of the individuality of each 　expert because it seeks equity among employees and stability of the entire organization. However, there were problems such as being unable to be given treatment according to ability, and becoming a manager rather than using it as careers accumulate.

On the other hand, Blockchain, also known as a public transaction ledger, is a technology that prevents hacking that can occur when trading with virtual currency. In the case of existing financial companies, transaction records are stored on a centralized server, whereas blockchain sends transaction details to all users participating in transactions, and it is matched with each transaction to prevent data forgery. Have.

For example, blockchain is applied to Bitcoin, a representative online virtual currency. Bitcoin transparently records transaction details in a ledger that anyone can read, and several computers using Bitcoin verify this record every 10 minutes to prevent hacking. Recently, various coins have been developed and provided to solve the shortcomings of bitcoin, and various tokens are functioning as virtual currency with the advent of coins with platform-like functions.

In addition, as various distributed applications (DAPPs) using a virtual currency platform are developed and used, the utilization of the blockchain is increasing.

Furthermore, 　Experts 　Managed on the platform, various information such as detailed information of experts, work experience, specialty field, and project execution experience can be transmitted and received through signals in WLAN (wireless local area network) system environment, 4G environment, 5G environment, etc. have.

An object of the present invention for solving the above problems is to provide a platform operating method for matching users and experts.

Another object of the present invention for solving the above problems is to provide a method for a user to use a service provided by an expert in a non-face-to-face manner.

In an embodiment of the present invention for achieving the above object, the expert matching platform control method performed by the server includes receiving an expert profile information request signal from a terminal, transmitting the expert profile information to the terminal, the terminal Receiving an expert service request signal from, transmitting the expert service request signal to a payment server, receiving a payment completion confirmation signal from the payment server, transmitting the expert service to the terminal, and the expert It may include the step of determining an exposure level to the expert who provides the expert service based on payment information related to the service.

Here, the payment completion confirmation signal may be transmitted based on the blockchain currency transmitted by the terminal to the payment server.

Here, the payment completion confirmation signal is transmitted in a self-decodable first to fifth redundancy version, and the server includes at least three redundancy of the first to fifth redundancy versions. When decoding is successful for a version, and the at least three redundancy versions include payment completion information of the terminal, the expert service may be transmitted to the terminal.

Here, the payment information related to the expert service includes information on a conversion rate for payment of a coaching right and total sales amount information, and determining an exposure level to an expert who provides the expert service based on the payment information related to the expert service, It may be performed based on a sum of a value obtained by multiplying a first weight by the coaching right payment conversion rate and a value obtained by multiplying the total sales amount by a second weight.

Here, the server may request retransmission to the payment server when decoding fails for at least three redundant versions of the first to fifth redundancy versions of the payment completion confirmation signal.

Here, the first to fifth redundancy versions are sequentially transmitted from the first redundancy version to the fifth redundancy version, and the first to fifth redundancy versions all include information related to payment completion of the terminal, , Different encodings may be applied to the first to fifth redundancy versions.

Here, the first weight may be a value larger than the second weight.

A server performing expert matching platform control according to an embodiment of the present invention for achieving the above object includes at least one memory and a processor, and the processor receives an expert profile information request signal from a terminal, and the Transmitting the expert profile information to a terminal, receiving an expert service request signal from the terminal, sending the expert service request signal to a payment server, receiving a payment completion confirmation signal from the payment server, and receiving the expert service request signal from the terminal, It may be set to transmit a service, and to determine an exposure level to an expert who provides the expert service based on payment information related to the expert service.

According to the present invention, a user can use a service for an expert he or she desires in a non-face-to-face manner.

According to the present invention, the user can use the service for the expert during the period of purchase, or purchase the expert's book or other products through the platform. Here, the platform may judge a popular expert based on the coaching right and sales amount paid by users, and expose the popular expert to the top.

1 is a view showing payment servers, management servers, and user terminals for an expert matching platform according to an embodiment of the present invention.
FIG. 2 is a flowchart illustrating a method of receiving expert service from a management server by a terminal using a platform according to an embodiment of the present invention.
3 is a flowchart illustrating a method of receiving an expert service from a management server by a terminal using a platform according to an embodiment of the present invention.
4 is a conceptual diagram illustrating an expert matching platform according to an embodiment of the present invention.
5 is another conceptual diagram illustrating an expert matching platform according to an embodiment of the present invention.
6 is a flowchart showing an operation performed in a server according to an embodiment of the present invention.

In the present invention, various modifications may be made and various embodiments may be provided, and specific embodiments will be illustrated in the drawings and described in detail in the detailed description. However, this is not intended to limit the present invention to a specific embodiment, it is to be understood to include all changes, equivalents, and substitutes included in the spirit and scope of the present invention. In describing each drawing, similar reference numerals have been used for similar elements.

Terms such as first, second, A, and B may be used to describe various elements, but the elements should not be limited by the terms. These terms are used only for the purpose of distinguishing one component from another component. For example, without departing from the scope of the present invention, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element. The term "and/or" includes a combination of a plurality of related stated items or any of a plurality of related stated items.

When a component is referred to as being "connected" or "connected" to another component, it is understood that it may be directly connected or connected to the other component, but other components may exist in the middle. Should be. On the other hand, when a component is referred to as being "directly connected" or "directly connected" to another component, it should be understood that there is no other component in the middle.

The terms used in the present application are only used to describe specific embodiments, and are not intended to limit the present invention. Singular expressions include plural expressions unless the context clearly indicates otherwise. In the present application, terms such as "comprise" or "have" are intended to designate the presence of features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, but one or more other features. It is to be understood that the presence or addition of elements or numbers, steps, actions, components, parts, or combinations thereof, does not preclude in advance.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs. Terms as defined in a commonly used dictionary should be interpreted as having a meaning consistent with the meaning in the context of the related technology, and should not be interpreted as an ideal or excessively formal meaning unless explicitly defined in this application. Does not.

Hereinafter, preferred embodiments of the present invention will be described in more detail with reference to the accompanying drawings. In describing the present invention, in order to facilitate an overall understanding, the same reference numerals are used for the same elements in the drawings, and duplicate descriptions for the same elements are omitted.

In the present specification, 　expert may be understood to mean all kinds of people with a predetermined expertise in a specific field, and the criteria are not limited. All kinds of experienced, educated, or talented persons capable of performing work in a specific field can be referred to as experts, but preferably, it is understood to mean a person with a certain experience in a specific field. Can be.

Accordingly, 　experts according to the present disclosure may mean 　experts who satisfy the requirements required by a specific group, as well as 　experts of the existing conceptual, common, and general criteria.

Meanwhile, in the present disclosure, the term “expert” refers to an individual single expert, but is not limited thereto. In other words, a specific group itself can be viewed as an expert.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

Each of the steps described in this specification is described as being performed by a computer or a server, but the subject of each step is not limited thereto, and at least some of the steps may be performed by different devices according to embodiments.

1 is a view showing payment servers, management servers, and user terminals for an expert matching platform according to an embodiment of the present invention.

Referring to FIG. 1, payment servers 10, management servers 20, and user terminals 30 are illustrated. For example, the payment server 10 and the management server 20 may be the same entity. For example, the payment server 10 and the management server 20 may be logically divided units.

In the disclosed embodiment, each of the user terminals 30 records transaction details based on a preset rule, and the recorded transaction details are recorded in each block and propagated to the payment servers 10, respectively. Stored and managed.

In the disclosed embodiment, the payment servers 10 may mean servers equipped with a block chain for authenticating and recording transaction information. In one embodiment, the transaction information may refer to transaction information based on virtual currency, but may refer to information on various events performed based on the blockchain, and such transaction information is Is saved.

Virtual currency according to the disclosed embodiment is understood as a concept that collectively refers to all kinds of non-real money whose transaction details are managed through a block chain such as electronic money and cryptocurrency.

The cryptocurrency according to the disclosed embodiment may be a cryptocurrency in the form of a coin that is managed by a separate mainnet, or may be a cryptocurrency in the form of a token that utilizes the infrastructure of other coins such as the Ethereum network. Not limited.

However, in an embodiment, the payment servers 10 may support a blockchain-based virtual currency as described above, but are not limited thereto, and may also support a general payment system. That is, in the payment method, a general payment method can be used in addition to the blockchain-based payment method.

In one embodiment, the virtual currency provided to each of the user terminals 30 is managed by the management server 20 as already generated or issued, and may be provided according to the transaction details of each of the user terminals 30. have.

For example, the management server 20 may perform an operation to generate a block for storing transaction details occurring between the user terminals 30, and may generate a block through Proof Of Work. According to an embodiment, the management server 20 may receive a predetermined virtual currency generated in return and distribute it to the user terminals 30 according to the transaction details of the user terminals 30.

In one embodiment, as transaction details are recorded by each of the user terminals 30, a virtual currency may be generated according to a preset rule and provided to the user terminals 30, and this may be used for mining (mining) virtual currency. ).

In general, cryptocurrency mining is performed by one of Proof Of Work (POW), Proof Of Stake (POS), and Proof Of Importance (POI). The above-described methods are one of the distributed summation algorithms used to guarantee the reliability of a distributed system.

In the disclosed embodiment, a transaction between user terminals 30 and a method of providing virtual currency accordingly are performed by a smart contract.

In one embodiment, the user terminal 30 provides information to the management server 20, and the management server 20 provides the information to the payment servers 10 when the information is information to be stored in the blockchain. Can provide. The payment servers 10 may store the corresponding information in a block chain, and in this process, verification of the information based on the block chain may be performed. In this case, only information that has been successfully verified can be recorded on the blockchain.

In addition, when there is information that needs to be verified, the user terminal 30 may provide the information to the management server 20. In this case, the management server 20 can verify this based on the information stored in the block chain. In this process, the management server 20 obtains information for verifying the corresponding information from the payment servers 10, Accordingly, verification can be performed. The management server 20 may provide the verification result to the user terminal 30 or may provide a service to the user terminal 30 based on the verification result.

Unlike the existing centralized server-based system, this blockchain system has the advantage of providing higher security by providing a decentralized distributed processing system and providing reliability that cannot be manipulated by a specific subject.

In addition, since it functions as a platform that can provide various blockchain-based applications in recent years, its utilization is expected to increase further.

Each of the steps described in this specification is described as being performed by a server, but the subject of each step is not limited thereto, and at least some of the steps may be performed by different devices according to embodiments. For example, it goes without saying that each of the steps described in this specification may be performed by a computer, a cloud, or the like.

In one embodiment, the server 20 may mean a computer used to perform tasks according to one or more services provided by the offline 　 expert 　 platform, and if the server 100 is an online 　 expert 　 platform, online 　 expert 　 manages the platform It may mean a server to perform, but is not limited thereto.

In one embodiment, the server 20 may register a 　 expert according to the registration request of the experts, and collect 　 expert information about the registered 　 expert. In addition, the server 20 may acquire project information that experts can perform, distribute it to experts, and perform all administrative and management tasks for this.

On the other hand, 　 experts may be freelance 　 experts, but according to the embodiment may be 　 experts employed by a specific company. Similarly, experts may be individuals, but may also be groups (such as companies) including a plurality of experts.

FIG. 2 is a flowchart illustrating a method of receiving expert service from a management server by a terminal using a platform according to an embodiment of the present invention.

Referring to FIG. 2, the terminal 30 may be a device that supports an expert matching platform, and the management server 20 may be a device that provides an expert matching platform service. The user may receive an expert matching platform service from the management server 20 using the terminal 30.

The terminal 30 may transmit an expert information request signal to the management server 20 (S201). For example, the user may transmit an expert information request signal to the management server 20 using the terminal 30. For example, the terminal 30 may request profile information of an expert. The management server 20 may receive an expert information request signal from the terminal 30 (S201).

When receiving the expert information request signal from the terminal 30, the management server 20 may provide expert information to the terminal 30 (S202). For example, the management server 20 may transmit the requested expert profile information to the terminal 30. For example, expert profile information may be provided for free.

The user may obtain expert profile information through the terminal 30, and may determine whether to request a service for a corresponding expert based on the expert profile information. For example, a user may review profile information of a plurality of experts and purchase a lecture for a favorite expert.

The terminal 30 may transmit an expert service request signal to the management server 20 (S211). For example, expert services may be lectures, books, counseling, projects, coaching rights, etc. provided by experts. For example, services such as lectures, books, counseling, projects, and coaching rights provided by experts may be charged.

The management server 20 may receive an expert service request signal from the terminal 30 (S211). The management server 20 may provide expert services (eg, lectures, books, consultations, projects, coaching rights, etc. provided by experts) to the terminal 30 (S212).

3 is a flowchart illustrating a method of receiving an expert service from a management server by a terminal using a platform according to an embodiment of the present invention.

For example, the payment server 10 and the management server 20 may be the same entity. For example, the payment server 10 and the management server 20 may be logically divided units.

3, the terminal 30 may be a device that supports an expert matching platform, the management server 20 may be a device that provides an expert matching platform service, and the payment server 10 is the terminal 30 It may be a device that checks payment information from and allows the management server 20 to request an expert service.

For example, a user may receive an expert matching platform service from the management server 20 using the terminal 30.

The terminal 30 may transmit an expert information request signal to the management server 20 (S301). For example, the user may transmit an expert information request signal to the management server 20 using the terminal 30. For example, the terminal 30 may request profile information of an expert. The management server 20 may receive an expert information request signal from the terminal 30 (S301).

When receiving the expert information request signal from the terminal 30, the management server 20 may provide expert information to the terminal 30 (S302). For example, the management server 20 may transmit the requested expert profile information to the terminal 30. For example, expert profile information may be provided for free.

The user may obtain expert profile information through the terminal 30, and may determine whether to request a service for a corresponding expert based on the expert profile information. For example, a user may review profile information of a plurality of experts and purchase a lecture for a favorite expert.

The terminal 30 may transmit an expert service request signal to the management server 20 (S311). For example, expert services may be lectures, books, counseling, projects, coaching rights, etc. provided by experts. For example, services such as lectures, books, counseling, projects, and coaching rights provided by experts may be charged.

The management server 20 may receive an expert service request signal from the terminal 30 (S311). The management server 20 may transmit the expert service request signal received from the terminal 30 to the payment server 10 (S312).

When the payment server 10 receives an expert service request from the management server 20, the payment server 10 may transmit a payment request signal to the corresponding terminal 30 (S321).

When the terminal 30 receives a payment request signal from the payment server 10, the terminal 30 may perform payment for the requested expert service (S322). For example, payment can be performed through blockchain currency. For example, payment may be performed by a general method (eg, card payment, account transfer, etc.).

When payment is completed from the terminal 30, the payment server 10 may transmit a payment confirmation signal to the management server 20 (S331). The management server 20 may receive a payment completion confirmation signal from the payment server 10 (S331).

The payment completion confirmation signal may consist of a plurality of redundancy versions based on a hybrid automatic repeat request (HARQ) operation.

The HARQ technique is a technique that combines a forward error correction (FEC) scheme and an automatic repeat request (ARQ) scheme. According to the HARQ scheme, it is checked whether the data received by the physical layer contains an error that cannot be decoded, and if an error occurs, performance is improved by requesting retransmission.

The HARQ-based receiver basically attempts error correction for received data and determines whether to retransmit using an error detection code. The error detection code may be various codes. For example, in the case of using a cyclic redundancy check (CRC), when an error of received data is detected through a CRC detection process, the receiver transmits a non-acknowledgement (NACK) signal to the transmitter. Upon receiving the NACK signal, the transmitter transmits appropriate retransmission data according to the HARQ mode. A receiver receiving retransmission data improves reception performance by combining and decoding previous data and retransmission data.

The HARQ mode can be classified into Chase combining and IR (incremental redundancy). Chase combining is a method of obtaining a signal-to-noise ratio (SNR) gain by combining data with retransmitted data without discarding the error-detected data. IR is a method of obtaining a coding gain by incrementally transmitting additional redundant information to retransmitted data.

Chase combining is a method in which the same coded bit as the initial transmission is retransmitted. In the IR (incremental redundancy) scheme, the coded bit to be retransmitted after the initial transmission may be different as follows. Accordingly, when the IR scheme is used, the STA performing retransmission generally transmits the IR version (or packet version/retransmission version) to the receiving STA. The receiving STA may combine and decode the received packet/signal.

HARQ can have an effect of increasing coverage in a low SNR environment (eg, an environment in which the distance between the transmitting terminal and the receiving terminal is far). HARQ can have an effect of increasing throughput in a high SNR environment.

For example, the payment completion confirmation signal may be transmitted in a self-decodable first to fifth redundancy version. The self-decodeable first to fifth redundancy versions may mean that even if only any one of the first to fifth redundancy versions is successfully received, the receiving end can obtain information related to the payment completion confirmation signal. That is, the first to fifth redundancy versions of the payment completion confirmation signal may each include information related to payment completion confirmation by the terminal 30. The management server 20 may acquire information related to the successful payment of the terminal 30 even if only one of the first to fifth redundancy versions has been successfully received. Even if the management server 20 does not completely successfully receive each of the first to fifth redundancy versions, it is possible to increase the gain by combining the first to fifth redundancy versions, so that it can decode the payment completion confirmation signal. I can.

The management server 20 may provide an expert service to the terminal 30 (S322). The payment completion confirmation signal, or any other important signal, may require high reliability of the information. Thus, for example, the management server 20 succeeds in decoding at least three redundancy versions of the first to fifth redundancy versions, and the at least three redundancy versions transmit payment completion information of the terminal 30. When included, the expert service may be transmitted to the terminal (S322).

The management server 20 may request retransmission of a payment completion confirmation signal from the payment server when decoding fails for at least three redundancy versions of the first to fifth redundancy versions of the payment completion confirmation signal.

For example, the first redundancy version to the fifth redundancy version may be sequentially transmitted.

4 is a conceptual diagram illustrating an expert matching platform according to an embodiment of the present invention.

Referring to FIG. 4, a server (eg, a database) may collect user data from a terminal (eg, a user). The user of the expert matching platform may be a customer who uses the service of an expert or an expert who provides expert service.

User data may include information related to expert profiles, expert lectures, expert counseling, etc. provided by the service provider. User data may include a list of lectures paid by a service user, information on purchasing a coaching right for a corresponding expert after a lecture payment (i.e., coaching right payment conversion rate), information on an amount paid for each expert (i.e., sales amount), etc. .

A server (eg, a database) may generate and analyze big data based on user data and user experience (UX). For example, the server may generate and analyze information related to what kind of service the service user wants, what type of expert they want, what service they use, which service has a high repurchase rate. For example, the server can automatically recommend lectures to service users based on the analysis results. For example, the server may recommend lectures and/or coaches suitable to service users based on the results of big data analysis.

5 is another conceptual diagram illustrating an expert matching platform according to an embodiment of the present invention.

Referring to FIG. 5, a terminal (eg, a user) may input search information into an expert matching platform (eg, an application or a homepage). For example, the terminal may input a search word “language” in the expert matching platform. That is, the server may receive input data for a search word'language' from the terminal.

For example, the language category may include compulsory education, social English, and language-specific categories. For example, the compulsory education category may include elementary education, secondary education, and high school education categories. For example, the social English category may include TOEIC, OPIC, and IELTS categories. For example, the TOEIC category may include a list of experts such as AAA, BBB, and CCC. For example, the language-specific categories may include English, Vietnamese, and Chinese categories.

For example, the terminal may select language/social English/TOEIC/AAA information.

For example, even if the terminal only inputs input data of'language', the server may provide information corresponding to language/social English/TOEIC/AAA to the terminal based on the analysis result based on big data. That is, the server may select and provide customized lecture (output data) to the terminal.

For example, the list of experts AAA, BBB, and CCC provided by the server may be determined based on payment information related to a service provided by the corresponding expert. For example, the list of experts exposed above the search results provided by the server may be determined in the order of the highest conversion rate for coaching rights payments and/or the total amount of lecture sales, based on the coaching rights payment conversion rate and the total lecture sales.

The conversion rate for payment of coaching rights may mean a rate at which a user who listens to a lecture by a specific expert pays a coaching right for a corresponding expert. The total lecture sales may be the sum of the sales of lectures by a specific expert.

For example, based on a value obtained by multiplying a conversion rate for a coaching right payment by a first weight and a value obtained by multiplying a total lecture sales amount by a second weight, an expert who is exposed to the top of the search result may be determined.

6 is a flowchart showing an operation performed in a server according to an embodiment of the present invention.

Referring to FIG. 6, the server of FIG. 6 may include the management server 20 described in FIGS. 1 to 3, the payment server 10, the database described in FIG. 4, and the server described in FIG. 5. . For example, the payment server 10 and the management server 20 may be the same entity. For example, the payment server 10 and the management server 20 may be logically divided units.

The server may receive a request for providing a profile from the terminal (S600). For example, the user may transmit an expert information request signal to the management server using the terminal. For example, the terminal may request profile information of an expert. The server may receive an expert information request signal from the terminal (S600).

When the server receives the expert information request signal from the terminal, the server may provide expert information to the terminal (S601). For example, the server may transmit the requested expert profile information to the terminal. For example, expert profile information may be provided for free.

The user may obtain expert profile information through the terminal, and may determine whether to request a service for a corresponding expert based on the expert profile information. For example, a user may review profile information of a plurality of experts and purchase a lecture for a favorite expert.

The server may receive an expert service request signal from the terminal (S602). For example, expert services may be lectures, books, counseling, projects, coaching rights, etc. provided by experts. For example, services such as lectures, books, counseling, projects, and coaching rights provided by experts may be charged.

The server may receive an expert lecture request signal from the terminal (S602). The server may transmit the expert lecture request signal received from the terminal to the payment server (eg, payment server 10) (S603).

When the payment server receives an expert lecture request from the server, it may transmit a payment request signal to the corresponding terminal. When the terminal receives the payment request signal from the payment server, the terminal may perform payment for the requested expert lecture. For example, payment can be performed through blockchain currency. For example, payment may be performed by a general method (eg, card payment, account transfer, etc.).

When payment is completed from the terminal, the payment server may transmit a payment confirmation signal to the server. The server may receive a payment confirmation signal from the payment server (S604).

The payment completion confirmation signal may consist of a plurality of redundancy versions based on a hybrid automatic repeat request (HARQ) operation.

The HARQ technique is a technique that combines a forward error correction (FEC) scheme and an automatic repeat request (ARQ) scheme. According to the HARQ scheme, it is checked whether the data received by the physical layer contains an error that cannot be decoded, and if an error occurs, performance is improved by requesting retransmission.

The HARQ-based receiver basically attempts error correction for received data and determines whether to retransmit using an error detection code. The error detection code may be various codes. For example, in the case of using a cyclic redundancy check (CRC), when an error of received data is detected through a CRC detection process, the receiver transmits a non-acknowledgement (NACK) signal to the transmitter. Upon receiving the NACK signal, the transmitter transmits appropriate retransmission data according to the HARQ mode. A receiver receiving retransmission data improves reception performance by combining and decoding previous data and retransmission data.

The HARQ mode can be classified into Chase combining and IR (incremental redundancy). Chase combining is a method of obtaining a signal-to-noise ratio (SNR) gain by combining data with retransmitted data without discarding the error-detected data. IR is a method of obtaining a coding gain by incrementally transmitting additional redundant information to retransmitted data.

Chase combining is a method in which the same coded bit as the initial transmission is retransmitted. In the IR (incremental redundancy) scheme, the coded bit to be retransmitted after the initial transmission may be different as follows. Accordingly, when the IR scheme is used, the STA performing retransmission generally transmits the IR version (or packet version/retransmission version) to the receiving STA. The receiving STA may combine and decode the received packet/signal.

HARQ can have an effect of increasing coverage in a low SNR environment (eg, an environment in which the distance between the transmitting terminal and the receiving terminal is far). HARQ can have an effect of increasing throughput in a high SNR environment.

For example, the payment completion confirmation signal may be transmitted in a self-decodable first to fifth redundancy version. The self-decodeable first to fifth redundancy versions may mean that even if only any one of the first to fifth redundancy versions is successfully received, the receiving end can obtain information related to the payment completion confirmation signal. That is, each of the first to fifth redundancy versions of the payment completion confirmation signal may include information related to payment completion confirmation by the terminal. Even if only any one of the first to fifth redundancy versions has been successfully received, the server may obtain information related to the successful payment of the terminal. Even if the server does not completely successfully receive each of the first to fifth redundancy versions, it is possible to increase a gain by combining the first to fifth redundancy versions, and thus, decode the payment completion confirmation signal.

The payment completion confirmation signal, or any other important signal, may require high reliability of the information. Thus, for example, when the server succeeds in decoding at least three redundancy versions of the first to fifth redundancy versions, and the at least three redundancy versions include payment completion information of the terminal, the server tells the terminal the Expert lectures can be provided (S605). Therefore, the reliability of signal transmission can be greatly improved.

When decoding fails for at least three redundant versions of the first to fifth redundancy versions of the payment completion confirmation signal, the server may request the payment server to retransmit a payment completion confirmation signal. For example, the first redundancy version to the fifth redundancy version may be sequentially transmitted.

The server may receive an expert coaching right request signal from the terminal (S606). The server may transmit the expert lecture request signal received from the terminal to the payment server (eg, payment server 10) (S607).

When the payment server receives an expert lecture request from the server, it may transmit a payment request signal to the corresponding terminal. When the terminal receives the payment request signal from the payment server, the terminal may perform payment for the requested expert lecture. For example, payment can be performed through blockchain currency. For example, payment may be performed by a general method (eg, card payment, account transfer, etc.).

When payment is completed from the terminal, the payment server may transmit a payment confirmation signal to the server. The server may receive a payment completion confirmation signal from the payment server (S608).

The payment completion confirmation signal, or any other important signal, may require high reliability of the information. Thus, for example, when the server succeeds in decoding at least three redundancy versions of the first to fifth redundancy versions, and the at least three redundancy versions include payment completion information of the terminal, the server tells the terminal the Expert lectures can be provided (S609). Therefore, the reliability of signal transmission can be greatly improved.

The server may calculate a score based on payment information related to a service provided by an expert (S610). For example, the list of experts AAA, BBB, and CCC provided by the server may be determined based on payment information related to a service provided by the corresponding expert.

The server may determine an expert exposed at the top of the search result based on a score calculated based on payment information related to a service provided by the expert (S611).

For example, the list of experts exposed above the search results provided by the server may be determined in the order of the highest conversion rate for coaching rights payments and/or the total amount of lecture sales, based on the coaching rights payment conversion rate and the total lecture sales.

The conversion rate for payment of coaching rights may mean a rate at which a user who listens to a lecture by a specific expert pays a coaching right for a corresponding expert. The total lecture sales may be the sum of the sales of lectures by a specific expert.

For example, based on a value obtained by multiplying a conversion rate for a coaching right payment by a first weight and a value obtained by multiplying a total lecture sales amount by a second weight, an expert who is exposed to the top of the search result may be determined.

Some of the detailed steps shown in the example of FIG. 6 may not be required and may be omitted. For example, steps related to the expert lecture service (S602, S603, S605) of FIG. 6 may be replaced with other expert services (eg, books, counseling, coaching rights, etc.), and steps related to expert coaching rights service (S606, S607, S609) can also be replaced by other expert services. Alternatively, steps S606 to S609 may be omitted. Alternatively, steps S602 to S605 may be omitted. In addition, other steps may be added in addition to the steps shown in FIG. 6. The order of the steps may be different. For example, steps S610 and S611 may be performed before S600. Some of the above steps may have their own technical meaning.

The operation according to an embodiment of the present invention can be implemented as a computer-readable program or code on a computer-readable recording medium. The computer-readable recording medium includes all types of recording devices that store data that can be read by a computer system. In addition, the computer-readable recording medium may be distributed over a computer system connected through a network to store and execute a computer-readable program or code in a distributed manner.

In addition, the computer-readable recording medium may include a hardware device specially configured to store and execute program commands, such as ROM, RAM, and flash memory. The program instructions may include not only machine language codes such as those produced by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like.

While some aspects of the invention have been described in the context of an apparatus, it may also represent a description according to a corresponding method, where a block or apparatus corresponds to a method step or characteristic of a method step. Similarly, aspects described in the context of a method can also be represented by a corresponding block or item or a feature of a corresponding device. Some or all of the method steps may be performed by (or using) a hardware device such as, for example, a microprocessor, a programmable computer or electronic circuit. In some embodiments, one or more of the most important method steps may be performed by such an apparatus.

In embodiments, a programmable logic device (eg, a field programmable gate array) may be used to perform some or all of the functionality of the methods described herein. In embodiments, the field programmable gate array may work with a microprocessor to perform one of the methods described herein. In general, the methods are preferably performed by some hardware device.

Although the above has been described with reference to preferred embodiments of the present invention, those skilled in the art will variously modify and change the present invention within the scope not departing from the spirit and scope of the present invention described in the following claims. You will understand that you can do it.

Claims (5)

In the expert matching platform control method performed by the server,
Receiving an expert profile information request signal from a terminal;
Transmitting the expert profile information to the terminal;
Receiving an expert service request signal from the terminal;
Transmitting the expert service request signal to a payment server;
Receiving a payment completion confirmation signal from the payment server;
Transmitting the expert service to the terminal; And
Including the step of determining an exposure degree to the expert providing the expert service based on payment information related to the expert service,
Payment information related to the expert service,
Information on the conversion rate of the coaching right payment indicating the ratio of the terminals that paid for the coaching right service of the specific expert among the terminals that were taking a lecture by paying for a specific expert's lecture, and about the total lecture sales totaling the sales of the lecture of the specific expert. Contain information,
Determining the degree of exposure to the expert who provides the expert service based on payment information related to the expert service,
Calculating a score of the specific expert based on a sum of a value obtained by multiplying the coaching right payment conversion rate by a first weight and a value obtained by multiplying the total sales amount of the lecture by a second weight; And
Including the step of determining an exposure level related to the higher exposure of the specific expert from the search result provided by the server based on the score of the specific expert,
The first weight is a value greater than the second weight,
Way. The method according to claim 1,
The payment completion confirmation signal,
Transmitted based on the blockchain currency transmitted by the terminal to the payment server,
Way. delete delete The method according to claim 1,
The payment completion confirmation signal,
It is transmitted in a self-decodable first to fifth redundancy version,
The server,
It succeeds in decoding at least three redundant versions of the first to fifth redundancy versions,
Transmitting the expert service to the terminal when the at least three redundancy versions include payment completion information of the terminal,
Way.

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