KR102540367B1 - Apparatus, method and program for providing economic information sharing service - Google Patents

Abstract

According to an embodiment of the present invention, an apparatus for providing an economic information sharing service is provided. The device may include at least one processor; and a memory for storing instructions instructing the at least one processor to perform at least one operation. In addition, the at least one operation may include receiving consumer information from a consumer terminal; determining recommended content using the consumer information; and providing the recommended content to the consumer terminal, and determining the recommended content using the consumer information includes a first investment field corresponding to the consumer terminal using the consumer information, a first investment propensity, and determining a first investment country and generating a first vector using the first investment field, the first investment propensity, and the first investment country; Using the text of each of the plurality of contents stored in the database, the second investment field, the second investment propensity, and the second investment country corresponding to each of the contents are determined, and the second investment field, the second investment propensity and generating a second vector corresponding to each of the contents by using the second investment country; and determining a degree of relevance of each of the contents by using the first vector and the second vector, and determining the recommended content by using the degree of relevance.

Description

Apparatus, method and program for providing economic information sharing service {APPARATUS, METHOD AND PROGRAM FOR PROVIDING ECONOMIC INFORMATION SHARING SERVICE}

The present invention relates to an economic information sharing service providing apparatus, method and program.

Unless otherwise indicated herein, material described in this section is not prior art to the claims in this application, and inclusion in this section is not an admission that it is prior art.

As platforms for providing information diversify, a lot of information is being provided through TV broadcasting, Internet broadcasting platforms, video platforms, social network services (SNSs), and the like.

In particular, as the level of education and interest in technology and investment increase, a vast amount of economic information is being provided on platforms.

However, in most cases, information is provided in one direction, and there is a problem in that individual investors are suffering unilateral damage because they do not obtain practically necessary information.

An object of the present invention is to provide an economic information sharing service providing apparatus, method, and program in which users using the economic information sharing service can supply and consume content.

Another object of the present invention is to provide an apparatus, method, and program for providing an economic information sharing service, in which a user's content that provides relatively new and high-quality content can increase exposure.

One aspect of the present invention for achieving the above object provides an apparatus for providing an economic information sharing service.

In addition, the device, at least one processor (processor); and a memory for storing instructions instructing the at least one processor to perform at least one operation.

In addition, the at least one operation may include receiving consumer information from a consumer terminal; determining recommended content using the consumer information; and providing the recommended content to the consumer terminal.

In addition, the operation of determining recommended content using the consumer information determines a first investment field, a first investment propensity, and a first investment country corresponding to the consumer terminal using the consumer information, the first investment field, generating a first vector by using the first investment propensity and the first investment country; Using the text of each of the plurality of contents stored in the database, the second investment field, the second investment propensity, and the second investment country corresponding to each of the contents are determined, and the second investment field, the second investment propensity and generating a second vector corresponding to each of the contents by using the second investment country; and determining a degree of relevance of each of the contents by using the first vector and the second vector, and determining the recommended content by using the degree of relevance.

The determining of the recommended content using the degree of relevance may include determining, as preliminary recommended content, the contents having a degree of relevance greater than a preset reference degree of relevance; and determining a recommendation degree of each of the preliminary recommended contents by multiplying the degree of association of each of the preliminary recommended contents by a recommendation coefficient of each of the preliminary contents.

In addition, the at least one operation may include receiving new content from a provider terminal; determining a category of the new content; determining a document similarity of each of the contents included in the category by using the new contents; determining the new content as higher content when there is no content whose document similarity is greater than a preset first criterion similarity among the content; Creating a block on a blockchain network, generating a Non-Fungible Token (NFT) containing upper provider information including identification information of the upper content, and including the generated NFT in the generated block movement; Among the contents, if there is content whose document similarity is greater than the first criterion similarity, the new content is determined as lower content, and the content whose document similarity is greater than the first criterion similarity among the contents is the existing upper content. operation to determine; and searching for a block including an NFT including identification information of the existing upper content in the blockchain network, and updating the NFT of the searched block to include lower provider information including identification information of the lower content and distribution coefficient. Actions may be included.

In addition, the operation of determining the content having the document similarity greater than the first criterion similarity among the contents as the existing higher content, wherein the document similarity among the contents is greater than the first criterion similarity and equal to or less than a preset second criterion similarity. determining the content as the first existing higher content; and determining, among the contents, the contents having the document similarity greater than the second criterion similarity as the second existing upper contents.

In addition, a block containing an NFT containing the identification information of the existing upper content is searched in the blockchain network, and the NFT of the searched block is updated to include the identification information of the lower content and the lower supplier information including the distribution coefficient. The operation is to search for a block including an NFT including the identification information of the first existing upper content in the blockchain network, and the NFT of the searched block includes the identification information of the lower content and the first distribution coefficient. Updating to include sub-provider information; and searching for a block including an NFT including the identification information of the second existing upper content in the blockchain network, and the NFT of the searched block includes the lower level provider information including the identification information of the lower content and the second distribution coefficient. It may include an operation of updating to include.

In addition, the at least one operation evaluates the content that matches the identification information of the upper content included in the upper level provider information of the NFT when the evaluation period reaches the evaluation point after a preset evaluation period has elapsed from the time of generation of the NFT. action to determine the score; and determining a recommendation score of a provider that matches the identification information of the upper content and a provider that matches the identification information of the lower content, using the upper provider information, the lower provider information, and the evaluation score included in the NFT. Including, the recommendation coefficient may be determined by the recommendation score.

According to an embodiment of the present invention, since content exposure increases as relatively new and high-quality content is produced, more profits can be distributed to users who create new and high-quality content. Accordingly, it is possible to induce users using the service to create new and high-quality content rather than simply copying content.

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1 is a schematic diagram of a system for providing an economic information sharing service according to an embodiment.
FIG. 2 is a block diagram showing functional modules of the service providing apparatus according to FIG. 1 by way of example.
3 is a flowchart illustrating a process of providing a shared service by the service providing apparatus according to FIG. 1 .
FIG. 4 is a flowchart illustrating a process of determining recommended content by the service providing apparatus according to FIG. 1 .
5 is a flowchart illustrating a process of registering content by the service providing device according to FIG. 1 .
6 is a flowchart illustrating a process of distributing compensation for content by the service providing apparatus according to FIG. 1 .
7 is a diagram showing the hardware configuration of the service providing apparatus according to FIG. 1 by way of example.

Since the present invention can make various changes and have various embodiments, 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 specific embodiments, and should be understood to include all modifications, equivalents, and substitutes included in the spirit and scope of the present invention. Like reference numerals have been used for like elements throughout the description of each figure.

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

It is understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, but other elements may exist in the middle. It should be. On the other hand, when an element is referred to as “directly connected” or “directly connected” to another element, it should be understood that no other element exists in the middle.

Terms used in this 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 dictates otherwise. In this application, the terms "include" or "have" are intended to designate that there is a feature, number, step, operation, component, part, or combination thereof described in the specification, but one or more other features It should be understood that the presence or addition of numbers, steps, operations, components, parts, or combinations thereof is not precluded.

Unless defined otherwise, 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 such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related art, and unless explicitly defined in the present application, they should not be interpreted in an ideal or excessively formal meaning. don't

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

1 is a schematic diagram of a system for providing an economic information sharing service according to an embodiment.

Referring to FIG. 1 , a system for providing an economic information sharing service includes a service providing device 100 , a supplier terminal 200 , a consumer terminal 300 and an evaluator terminal 400 .

The supplier terminal 200 is a terminal of a supplier who wants to share economic content and receive a reward for sharing economic content through an economic information sharing service, and provides supplier information to the service providing device 100 . The service providing apparatus 100 receives provider information and generates provider identification information matched with the provider. In one embodiment, the provider terminal 200 may receive economic content created by another provider from the service providing device 100 .

The consumer terminal 300 is a terminal of a consumer who wants to receive economic content through an economic information sharing service, and provides consumer information to the service providing device 100 . The service providing apparatus 100 receives consumer information and generates consumer identification information matched with the consumer.

In one embodiment, the service providing apparatus 100 provides a survey including a plurality of preset questions to the consumer terminal 300, and receives a survey result including answers to the questions from the consumer terminal 300. can do. In one embodiment, consumer information may include survey results.

In one embodiment, the consumer terminal 300 may provide economic content generated by the consumer to the service providing apparatus 100 .

The evaluator terminal 400 is an evaluator terminal that evaluates contents provided to the economic information sharing service, and provides evaluation scores for the contents to the service providing apparatus 100 .

Examples of the supplier terminal 200, the consumer terminal 300, and the evaluator terminal 400 include a communicable desktop computer, a laptop computer, a notebook, a smart phone, Tablet PC, mobile phone, smart watch, smart glass, e-book reader, PMP (portable multimedia player), portable game console, navigation device, digital Digital camera, digital multimedia broadcasting (DMB) player, digital audio recorder, digital audio player, digital video recorder, digital video player, It may be a PDA (Personal Digital Assistant) or the like.

The service providing apparatus 100 is a server for providing an economic information sharing service to the supplier terminal 200 and the consumer terminal 300, and communicates with the plurality of supplier terminals 200 and the plurality of consumer terminals 300. can possibly be connected.

FIG. 2 is a block diagram showing functional modules of the service providing apparatus 100 according to FIG. 1 by way of example.

Referring to FIG. 2 , the service providing device 100 includes a recommended content determination unit 101 , a compensation management unit 102 , a subscription management unit 103 , a content registration unit 104 and a content settlement unit 105 .

FIG. 3 is a flowchart illustrating a process in which the service providing apparatus 100 according to FIG. 1 provides a shared service.

The recommended content determination unit 101 receives consumer information from the consumer terminal 300 (S110). The recommended content determination unit 101 may provide a user interface through which consumer information may be input to the consumer terminal 300 .

The recommended content determination unit 101 determines recommended content using the received consumer information (S120).

FIG. 4 is a flowchart illustrating a process in which the service providing apparatus 100 according to FIG. 1 determines recommended content.

The recommended content determination unit 101 determines the degree of association of each of the contents stored in the database using the received consumer information (S121).

In one embodiment, the recommended content determination unit 101 provides a survey including a plurality of preset questions to the consumer terminal 300, and returns a survey result including answers to the questions from the consumer terminal 300. can receive In one embodiment, consumer information may include survey results.

In one embodiment, each of the first questions about the investment field may be a choice type question including a plurality of options. In the database of the service providing device 100, answers to the first questions and investment fields are pre-matched and stored, and the recommended content determination unit 101 determines the investment matched with the answers to the first questions in the database. You can select a field and decide the selected investment field as the investment field of the consumer.

In one embodiment, each of the second items on investment propensity may be a choice type item including a plurality of options. In the database of the service providing device 100, answers to the second questions and investment propensity are pre-matched and stored, and the recommended content determination unit 101 determines the investment matched with the answers to the second questions in the database. The propensity can be selected, and the selected investment propensity can be determined as the investment propensity of the consumer.

In one embodiment, each of the third questions about the investment country may be a choice type question including a plurality of options. In the database of the service providing device 100, answers to the third questions and investment countries are stored in advance and matched, and the recommended content determination unit 101 determines the investment matched with the answers to the third questions in the database. You can select a country and determine the selected investment country as the consumer's investment country.

The recommended content determination unit 101 may generate a first vector using an investment field of interest, an investment propensity, and an investment country. In one embodiment, the first vector may be a multi-dimensional vector having each of an investment field, an investment propensity, and an investment country as dimension values.

The recommended content determination unit 101 divides the text included in the content into morpheme units using a pre-learned natural language processing model, inputs the morphemes as input values to the first artificial neural network that has been learned in advance, and from the first artificial neural network. investment can be obtained. In one embodiment, the first artificial neural network may be generated through machine learning using a learning data set including learning data generated by labeling investment fields on learning morphemes. In one embodiment, a Recurrent Neural Network (RNN), Bidirectional Encoder Representations from Transformers (BERT), and the like may be used to learn the first artificial neural network.

The recommended content determination unit 101 divides the text included in the content into morpheme units using a pre-learned natural language processing model, inputs the morphemes as input values to the pre-learned second artificial neural network, investment propensity can be obtained. In one embodiment, the second artificial neural network may be generated through machine learning using a learning data set including learning data generated by labeling morphemes for learning with propensity to invest. In one embodiment, a Recurrent Neural Network (RNN), Bidirectional Encoder Representations from Transformers (BERT), and the like may be used to learn the second artificial neural network.

The recommended content determination unit 101 classifies the text included in the content into morpheme units using a pre-learned natural language processing model, inputs the morphemes as input values to the pre-learned third artificial neural network, and obtains the result from the third artificial neural network. You can get an investment country. In an embodiment, the third artificial neural network may be generated through machine learning using a learning data set including learning data generated by labeling investment countries on morphemes for learning. In one embodiment, a Recurrent Neural Network (RNN), Bidirectional Encoder Representations from Transformers (BERT), and the like may be used to learn the third artificial neural network.

The recommended content determination unit 101 may generate a second vector corresponding to the content by using an investment field corresponding to the content, an investment propensity, and an investment country. In one embodiment, the second vector may be a multi-dimensional vector having each of the investment field, investment propensity, and investment country as dimension values. The recommended content determination unit 101 may generate a second vector of each of the contents.

The recommended content determination unit 101 may determine the cosine similarity between the first vector and the second vector as the degree of content relevance.

Cosine similarity can be determined by Equation 1 below.

In Equation 1 above, S denotes similarity, A denotes the first vector, and B denotes the second vector.

The recommended content determination unit 101 determines, as preliminary recommended content, contents having a degree of relevance greater than a preset reference degree of relevance (S122).

The recommended content determination unit 101 determines the degree of recommendation of each of the preliminary recommended contents by multiplying the degree of association of each of the preliminary recommended contents by the recommendation coefficient of each of the preliminary recommended contents (S123).

Content and recommendation coefficients are matched and stored in the database. The recommended content determination unit 101 searches the database for a recommendation coefficient matching the preliminary recommended content, and multiplies the retrieved recommendation coefficient by the relevance of the preliminary recommended content to correct the relevance.

Content and recommendation scores are matched and stored in the database, and a recommendation coefficient may be determined based on the recommendation scores. In one embodiment, the higher the recommendation score, the higher the recommendation coefficient is determined, and the lower the recommendation score, the lower the recommendation coefficient. In one embodiment, a plurality of recommendation score ranges and a plurality of recommendation coefficients are previously matched and stored in the database, and a recommendation coefficient matching the recommendation score range including the recommendation score of the content may be determined as the recommendation coefficient of the content.

The recommended content determination unit 101 determines, as recommended content, preliminary recommended content whose corrected recommendation degree is greater than a preset standard recommendation degree (S124).

Referring back to FIG. 3 , the recommended content determination unit 101 provides the recommended content to the consumer terminal 300 .

The recommended content determination unit 101 provides a user interface capable of displaying the provided recommended content to the consumer terminal 300 .

The reward management unit 102 receives a reward providing signal from the consumer terminal 300 (S140).

The compensation management unit 102 may provide the user terminal 300 with a user interface through which the scale of the compensation and the identification information of the provider of the content to be paid are input.

The reward management unit 102 receives a reward providing signal including the scale of the reward and identification information of the supplier from the consumer terminal 300 (S140).

The compensation management unit 102 matches the scale of the compensation and identification information of the supplier and stores them in the database (S150).

The compensation management unit 102 provides a compensation payment signal including the amount of compensation and the identification information of the consumer who paid the compensation to the supplier terminal 200 that matches the identification information of the supplier (S160).

The compensation management unit 102 may provide the supplier terminal 200 with a user interface capable of displaying the amount of compensation and the identification information of the consumer who has paid the compensation.

The subscription management unit 103 receives a subscription signal including supplier identification information from the consumer terminal 300 (S170).

The subscription management unit 103 may provide the consumer terminal 300 with a user interface through which identification information of a provider to be subscribed to may be input.

The subscription management unit 103 matches the identification information of the supplier included in the subscription signal with the identification information of the consumer who provided the subscription signal, and stores the matching information in the database (S180).

The subscription management unit 103 provides a subscription notification signal including the identification information of the consumer who provided the subscription signal to the provider terminal 200 that matches the identification information of the provider included in the subscription signal (S190).

The subscription management unit 103 may provide the provider terminal 200 with a user interface capable of displaying identification information of providers matched with identification information of the provider.

The recommended content determination unit 101 may determine, as recommended content to be provided to the consumer terminal 200 , contents of a provider that matches the consumer of the consumer terminal 200 through subscription.

5 is a flowchart illustrating a process of registering content by the service providing apparatus 100 according to FIG. 1 .

The content registration unit 104 receives content from the provider terminal 200 (S210).

The content registration unit 104 may provide the provider terminal 200 with a user interface capable of creating content.

The content registration unit 104 determines the category of the content (S220).

The content registration unit 104 matches the identification information of the provider that created the content, the content, and the category of the content, and stores the matching information in the database.

In one embodiment, the content registration unit 104 divides the text included in the content into morpheme units using a pre-learned natural language processing model, inputs the morphemes as input values to the pre-learned fourth artificial neural network, and A category can be obtained from an artificial neural network. In one embodiment, the fourth artificial neural network may be generated through machine learning using a learning data set including learning data generated by labeling morphemes for learning with categories. In one embodiment, a Recurrent Neural Network (RNN), Bidirectional Encoder Representations from Transformers (BERT), and the like may be used to learn the fourth artificial neural network.

The content registration unit 104 determines the document similarity of each existing content included in the same category by using the content (S230).

Existing content refers to content already registered through steps S210 to S290.

The content registration unit 104 selects a plurality of existing contents included in the same category as the content category from the database, compares the selected existing contents with the content, and determines a document similarity of each of the existing contents.

In an embodiment, the content registration unit 104 may generate a first document vector corresponding to the content by multiplying a word vector of words included in the content by a weight. For example, a first document vector may be generated by dividing a set of word vectors obtained by multiplying word vectors by TF-IDFs (weights) of words by the sum of TF-IDFs of words. Also, the content registration unit 104 may generate a second document vector corresponding to the existing content in the same manner as the content.

In an embodiment, the content registration unit 104 may determine document similarity of existing content using the first document vector and the second document vector.

In one embodiment, document similarity may be determined using Equation 2 below.

In Equation 2 above, D denotes document similarity, E denotes the first document vector, and F denotes the second document vector.

The content registration unit 104 determines whether there is existing content whose document similarity is greater than a preset first criterion similarity (S240).

If there is no existing content whose document similarity is greater than the preset first criterion similarity among the selected existing contents, the content registration unit 104 determines the content as the higher content (S245).

In addition, the content registration unit 104 creates a block on the blockchain, generates a Non-Fungible Token (NFT) including identification information of the upper content, and includes the NFT in the generated block (S250).

In one embodiment, the identification information of the higher content may include identification information of the provider who created the higher content, and the number of the supplier of the higher content.

The content registration unit 104 creates a block in a ledger of a peer of a blockchain network communicatively connected to the service providing device 100 . In addition, the content registration unit 104 generates an NFT including identification information of upper content, and includes the NFT in the generated block.

Among the selected existing contents, when there exists an existing content having a document similarity greater than a preset first criterion similarity, the content registration unit 104 determines the content as lower content (S255).

In addition, the content registration unit 104 determines existing content having a document similarity greater than the first criterion similarity and equal to or less than a preset second criterion similarity as the first existing higher order content (S260).

The second criterion similarity is set higher than the first criterion similarity.

In addition, the content registration unit 104 searches for a block including an NFT including identification information of the first existing upper content, and lower provider information including the NFT of the searched block includes the identification information of the lower content and the first distribution coefficient. It is updated to include (S270). In one embodiment, the first distribution coefficient may be a value less than 1. In one embodiment, the identification information of the first existing higher content may include identification information of a provider who created the first existing higher content and what number the first existing higher content is from the provider. In one embodiment, the identification information of the lower content may include identification information of the provider who created the lower content and what number the lower content belongs to the provider.

The content registration unit 104 searches for a block including an NFT including identification information of the first existing upper content in a blockchain network communicatively connected to the service providing device 100 . In addition, the content registration unit 104 updates the NFT included in the block to include identification information of lower content.

In addition, the content registration unit 104 determines existing content having a document similarity greater than the second standard similarity as the second existing upper content (S280).

In addition, the content registration unit 104 searches for a block including an NFT including the identification information of the second existing upper content, and the NFT of the searched block contains the identification information of the lower content and the lower provider information including the second distribution coefficient. It is updated to include (S290). In one embodiment, the second partition coefficient may be smaller than 1 and larger than the first partition coefficient. In one embodiment, the identification information of the second existing higher content may include identification information of a provider who created the second existing higher content and what number the second existing higher content is from the provider. In one embodiment, the identification information of the lower content may include identification information of the provider who created the lower content and what number the lower content belongs to the provider.

The content registration unit 104 searches for a block including an NFT including identification information of the second existing upper content in a blockchain network communicatively connected to the service providing device 100 . In addition, the content registration unit 104 updates the NFT included in the block to include identification information of lower content.

Through this, original content that does not copy other content may be determined as higher content. Also, derived content similar to other content may be determined as lower content. In addition, an NFT including identification information of the upper content is generated, and identification information of lower contents derived from the upper content may be continuously included in the generated NFT.

FIG. 6 is a flowchart illustrating a process in which the service providing apparatus 100 according to FIG. 1 distributes rewards for content.

The content settlement unit 105 determines whether a preset evaluation period has elapsed from the time the NFT is generated (S310).

When the evaluation period is warned, the content settlement unit 105 determines whether the NFT evaluation time has arrived (S320).

In one embodiment, the content settlement unit 105 provides the plurality of evaluator terminals 400 with upper content corresponding to the identification information of the upper content included in the upper supplier information included in the NFT, and the evaluator terminal 400 ) may receive a first signal corresponding to the arrival of the evaluation time point or a second signal corresponding to the non-arrival of the evaluation time point from each of the evaluation time points. The content settlement unit 105 may determine whether an evaluation point has been reached by using the number of received first signals and the number of second signals. For example, when the ratio of the number of first signals to the number of second signals is greater than a preset criterion, the content settlement unit 105 may determine that the evaluation point has arrived. For example, when the number of first signals is greater than the number of second signals, the content settlement unit 105 may determine that the evaluation point has arrived.

If the evaluation time point has not been reached, the content settlement unit 105 extends the evaluation time point for the NFT (S360).

When the evaluation point is reached, the content settlement unit 105 determines the evaluation score for the upper content corresponding to the NFT (S330).

In one embodiment, the content settlement unit 105 provides the plurality of evaluator terminals 400 with upper content corresponding to the identification information of the upper content included in the upper supplier information included in the NFT, and the evaluator terminal 400 ) may receive evaluation scores from each of them. The content settlement unit 105 may determine an evaluation score using the received evaluation scores. For example, the content calculator 105 may determine an average value of the received evaluation scores as an evaluation score for higher content.

The content settlement unit 105 distributes recommendation scores using upper and lower supplier information and evaluation scores included in the NFT (S340).

The content settlement unit 105 recommends distribution to providers matching the identification information of the provider included in the identification information of the upper content included in the upper provider information included in the NFT (or referred to as 'first identification information'). determine the score. In one embodiment, the content settlement unit 105 may determine the evaluation score as a recommendation score of a provider that matches the first identification information.

The content settlement unit 105 recommends points to be distributed to suppliers that match the identification information (or referred to as 'second identification information') of the supplier included in the identification information of the lower content included in the lower supplier information included in the NFT. decide In one embodiment, the content settlement unit 105 may determine a value obtained by multiplying the evaluation score by the first distribution coefficient or the second distribution coefficient included in the lower-order provider information as the recommendation score of the provider matching the second identification information. . In one embodiment, the content settlement unit 105 calculates a value obtained by multiplying the evaluation score by the first distribution coefficient or the second distribution coefficient included in the lower supplier information by the ranking coefficient, and then calculates the number of providers matching the second identification information. It can be determined by the recommendation score. In one embodiment, the rank coefficient is a coefficient less than 1, and may be determined based on the rank of the lower provider information included in the NFT. The rank coefficient when the rank included in the NFT is 3rd may be set smaller than the rank coefficient when the rank included in the NFT is 2nd.

Through this, recommendation scores can be distributed to providers who have created new content and providers who have created derived content. The more new and high-quality content is produced, the more recommendation points are given to the supplier, so the content of the provider who creates the new and high-quality content is exposed to more consumers, and accordingly, the new and high-quality content is provided. More profits can be distributed to producers.

That is, providers using the service can be induced to create new and high-quality content rather than simply copying content.

FIG. 7 is a diagram showing the hardware configuration of the service providing apparatus 100 according to FIG. 1 by way of example.

Referring to FIG. 7 , the service providing apparatus 100 stores at least one processor 110 and instructions instructing the at least one processor 110 to perform at least one operation. It may include a memory (memory) to.

The at least one operation may include the components 101 to 105 of the above-described service providing apparatus 100 or other functions or operation methods.

Here, the at least one processor 110 may mean a central processing unit (CPU), a graphics processing unit (GPU), or a dedicated processor for performing methods according to embodiments of the present invention. can Each of the memory 120 and the storage device 160 may include at least one of a volatile storage medium and a non-volatile storage medium.

For example, the memory 120 may be one of a read only memory (ROM) and a random access memory (RAM), and the storage device 160 may be a flash-memory. , a hard disk drive (HDD), a solid state drive (SSD), or various memory cards (eg, a micro SD card).

In addition, the device 100 may include a transceiver 130 that performs communication through a wireless network. In addition, the device 100 may further include an input interface device 140 , an output interface device 150 , a storage device 160 , and the like. Each component included in the device 100 may be connected by a bus 170 to communicate with each other.

For example, the device 100 may include a communicable desktop computer, a laptop computer, a notebook, a smart phone, a tablet PC, and a mobile phone. , smart watch, smart glass, e-book reader, PMP (portable multimedia player), portable game device, navigation device, digital camera, DMB (digital multimedia broadcasting) player , a digital audio recorder, a digital audio player, a digital video recorder, a digital video player, a personal digital assistant (PDA), and the like.

The methods according to the present invention may be implemented in the form of program instructions that can be executed by various computer means and recorded on a computer readable medium. Computer readable media may include program instructions, data files, data structures, etc. alone or in combination. Program instructions recorded on a computer readable medium may be specially designed and configured for the present invention or may be known and usable to those skilled in computer software.

Examples of computer readable media may include hardware devices specially configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like. Examples of program instructions may include not only machine language codes generated by a compiler but also high-level language codes that can be executed by a computer using an interpreter and the like. The hardware device described above may be configured to operate with at least one software module to perform the operations of the present invention, and vice versa.

In addition, the above-described method or device may be implemented by combining all or some of its components or functions, or may be implemented separately.

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 claims below. You will understand that it can be done.

Claims (5)

As a device for providing economic information sharing services,
The device,
processor; and
A memory for storing instructions instructing the processor to perform at least one operation;
At least one operation,
receiving consumer information from a consumer terminal;
The first investment field, the first investment tendency, and the first investment country corresponding to the consumer terminal are determined using the consumer information, and the first investment field, the first investment tendency, and the first investment country are determined. 1 operation to create a vector;
The second investment field corresponding to each of the plurality of first contents, the second investment propensity, and the second investment by using the text included in each of the plurality of first contents matched with each of the plurality of first contents and stored in advance in the database. determining a country and generating a second vector corresponding to each of the plurality of first contents by using the second investment field, the second investment propensity, and the second investment country;
determining a degree of relevance of the first content using the first vector and the second vector;
determining, as preliminary recommended content, the first content having a degree of relevance greater than a preset reference degree of relevance;
determining a recommendation degree of the preliminary recommended content by multiplying the degree of association of the preliminary recommended content with a recommendation coefficient previously matched with the preliminary recommended content and stored in the database;
determining, as recommended content, the preliminary recommended content having a higher recommendation degree than a preset reference recommendation degree;
providing the recommended content to the consumer terminal;
receiving second content from a provider terminal;
determining a category of the second content;
A first document vector is generated using text included in the second content, and a second document of each of the plurality of first contents is generated using text included in each of the plurality of first contents previously included in the category. generating a vector and determining a cosine similarity between a first document vector and a second document vector as a document similarity of each of the plurality of first contents;
determining the second content as an upper content when the first content having a document similarity greater than a preset first criterion similarity among the plurality of first content does not exist;
An operation of generating a block on a blockchain network, generating a Non-Fungible Token (NFT) including upper provider information including identification information of the upper content, and including the generated NFT in the generated block;
Among the plurality of first contents, if the first content having a document similarity greater than the first criterion similarity and less than or equal to a preset second criterion similarity exists, the second content is determined as a lower level content, and in the blockchain network A block including an NFT including identification information of the first content having the document similarity greater than the first criterion similarity and equal to or less than a preset second criterion similarity is searched, and the NFT of the searched block is the identification information of the lower content and the pre-set second criterion similarity. updating to include sub-supplier information including the set first distribution coefficient;
When the first content having a document similarity greater than the second criterion similarity exists among the plurality of first contents, the second content is determined as the lower content, and the document similarity in the blockchain network is higher than the second criterion similarity. 2 Search for a block including an NFT including the identification information of the first content greater than the criterion similarity, and the NFT of the searched block determines the sub provider information including the identification information of the sub content and a preset second distribution coefficient. update to include;
Searching for a block including an NFT including identification information of the upper content, and determining an evaluation score of the upper content that matches the identification information of the upper content included in the NFT of the searched block as a recommendation score of the upper content movement; and
A value obtained by multiplying the evaluation score by the first distribution coefficient or the second distribution coefficient included in the lower provider information included in the NFT of the searched block after searching for a block including an NFT including identification information of the upper content. Including the operation of determining as the recommendation score of the lower content,
The higher the recommendation score is, the higher the recommendation coefficient is set, and the lower the recommendation score is, the lower the recommendation coefficient is set.
The first partition coefficient is a preset value smaller than 1, and the second partition coefficient is a preset value smaller than 1 and larger than the first partition coefficient,
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