KR101808954B1 - Method and apparatus for calculating weighted centrality of accounts based on transaction ledger - Google Patents

Abstract

An apparatus for drawing a social relationship based on a transaction ledger comprises: a data storage unit for storing account information, software for calculating a social relationship between accounts and calculating a scale of value of an account, social relationship information between accounts, and scale-of-value information of a calculated account; and a processor for calculating weighted centrality of each account for calculating a scale of value of an account in a social relationship between accounts drawn based on a transaction ledger generated by a transaction between users having the account.

Description

[0001] METHOD AND APPARATUS FOR CALCULATING WEIGHTED CENTRALITY OF ACCOUNTS [0002] BASED ON TRANSACTION LEDGER [0003]

The present invention relates to a method and apparatus for calculating a weighted centrality measure of an account based on a transaction ledger, and more particularly, to a method and apparatus for calculating a weighted centrality measure of an account based on a transaction ledger, A method and apparatus for calculating a weighted centroid scale of an account based on a transaction ledger that calculates a weighted centroid measure.

Accounts are identification information that distinguishes users from trading partners in common banking and block-chain transactions. When an arbitrary transaction occurs between accounts, the transaction details are recorded in the transaction ledger.

Addresses are given for each account in the block chain transaction. In the block chain transaction, the address can store, transmit, and settle various digital virtual currencies that can be paid for in-kind and on-line transactions.

In addition to bit coin, there are bit coin, light coin, dark coin, name coin, porcelain coin, and etherium in digital virtual currency using block chain.

The common feature is that they are operated with a block chain in which all transaction details that are traded online are collected and stored using digital virtual currency including a trader bit coin. The medium in which the transaction details are recorded is called the transaction director.

The bit coin consists of a structure in which no central device exists for issuing and managing a call. Instead, the transaction of the bit coin is performed by a distributed database based on peer-to-peer network (P2P), and transactions are performed based on the public key cryptography.

Such a bit coin having a payment method has an advantage not only in that it can be used without providing information such as a card number, an expiration date, a CVC number, and personal information necessary for payment of a credit card, but also a fee for use is cheap.

Also, the bit coin is recorded in the block chain, and the electronic wallet manages a public key and a private key for the address of the block chain. And a bit coin transaction based on the public address derived from the public key.

The problem to be solved by the present invention is to calculate the weighted centrality measure of the account based on the transaction ledger which calculates the weighted centroid measure of each account in the social relation between the accounts derived based on the transaction ledger generated by the transaction between the users having the account And to provide a method and apparatus therefor.

According to an aspect of the present invention, there is provided an information processing system including a data storage unit for storing account information, software for calculating a social relation between accounts, software for calculating a value scale of accounts, social relationship information between accounts, A processor that calculates the weighted centrality of each account for calculating the value measure of the account in the social relations between accounts derived based on the transaction ledger generated by the transactions between the users having the transactions A derivation device is provided.

The account may include a block chain address.

The processor may derive a social relationship between the accounts using transactions between the accounts.

The processor may calculate a weighted centroid measure such that the sum of the weighted centroid measures of each account converges to the sum of the local weights of the respective accounts.

The processor can calculate a weighted centroid measure of the account using the local weight component determined for an arbitrary account and the weighted centroid metric component of a neighboring account having a social relationship with the account.

The processor can calculate the weighted centrality of each account by the following equation.

WC (A) = LW (A) * sr + (1-sr) * WC (N1) / NH (N1) + ... + WC (Nn) / NH (Nn)

Here, WC denotes Weighted Centrality, WC (A) is Weighted Center of Node A, LW is Local Weight, and LW (A) is Local Weight of Node A.

SR is the self ratio, WC (N1) is the weighted centroid of the first neighbor node N1 of node A, and WC (Nn) is the weighted centroid of the nth neighbor node Nn of node A.

NH is the number of neighboring nodes, NH (N1) is the number of neighboring nodes of N1, which is the first neighboring node of node A, NH (Nn) is the number of neighboring nodes of Nn, to be.

The local weight component for the arbitrary account may be determined to be a value independent of the neighbor account having a social relationship with the account.

The processor may calculate the local weight of the corresponding account by applying a predetermined weight to the size of the balance, the owner confirmation, and the change ratio.

The processor can calculate the local weight of each account by the following equation:

LW = SA * NH * (100% -CR) * LV

SA: Size of Amt (Size of balance)

LW: Local Weight

NH: # of Neighborhood addresses (number of neighbors)

CR: Change Ratio

LV: Level of Identity Verification

According to another aspect of the present invention, there is provided an information processing method comprising the steps of: obtaining transaction information for an arbitrary account based on a transaction ledger generated by a transaction between users having an account, thereby deriving a social relationship between the accounts; Calculating a weighted centroid of each account for calculating a value measure of the account in a relationship based on a transaction ledger.

The step of calculating the weighted centroid of each account may yield a weighted centroid measure such that the sum of the weighted centroid measures of each account converges to the sum of the local weights of the respective accounts.

The step of calculating the weighted centroid of each of the accounts may yield a weighted centroid measure of the account using the local weight component determined for any account and the weighted centroid measure component of the neighboring account having a social relationship with the account .

According to the present invention, various transactions such as financial transaction, mail transmission / reception, telephone transmission / reception, trade transaction, commodity transaction, media transmission / reception, and content transmission / reception are enabled between users having an account, The relationship between the accounts can be derived and the value of each account can be calculated in the derived relationship

According to the present invention, by supporting the community activities using the social relations between accounts derived for each account, it is possible to provide the psychological stability according to the social community activities and the performance of the transactions based on the reliability of the owners of the accounts have.

In addition, according to the present invention, an auditor can increase the efficiency of auditing to identify and monitor important accounts.

According to the present invention, the value measure of each account can be calculated from the derived social relations between accounts.

According to the present invention, by supporting the community activity using the calculated value scale for each account, it is possible to provide the psychological stability according to the social community activity and the execution of the transaction based on the trust of the owner of each account.

According to the present invention, it is possible to activate financial transactions using an account since the owners of an already secured account can implement a social media service based on an account.

In addition, according to the present invention, it is possible for users participating in transactions using accounts to form and interact with various transactions and various communities through social media services.

According to the present invention, it is possible to implement various types of social media services using a block chain.

FIG. 1 is a diagram for explaining a relationship between accounts based on a transaction ledger and a social media service system according to an embodiment of the present invention. Referring to FIG.
FIG. 2 is a diagram illustrating an apparatus for deriving an inter-account social relationship based on a transaction ledger according to an embodiment of the present invention.
3 is a diagram for explaining a transaction ledger in an apparatus for deriving an inter-account social relationship based on a transaction ledger according to an embodiment of the present invention.
FIG. 4 is a diagram for explaining social relations among accounts based on a transaction ledger according to an embodiment of the present invention.
5 is a diagram illustrating parameters of respective nodes in an inter-account social relationship according to an embodiment of the present invention.
FIG. 6 is a table in which parameters of respective nodes including local weights according to an embodiment of the present invention are summarized.
7 is a table in which parameters of respective nodes including static centrality according to an embodiment of the present invention are summarized.
8 is a table in which parameters of respective nodes including weighted centroids according to an embodiment of the present invention are summarized.
9 is a flowchart illustrating a method of deriving an inter-account social relationship based on a transaction ledger according to an embodiment of the present invention.
10 is a flowchart illustrating a method of deriving an inter-account social relationship based on a transaction ledger according to an embodiment of the present invention.
11 is a flowchart illustrating a method of deriving an inter-account social relationship based on a transaction ledger according to an embodiment of the present invention.
12 is a flowchart illustrating a method for deriving an inter-account social relationship based on a transaction ledger according to an embodiment of the present invention.
13 is a flowchart illustrating a method for deriving an inter-account social relationship based on a transaction ledger according to an embodiment of the present invention.
FIG. 14 is a flowchart illustrating a method of deriving an inter-account social relationship based on a transaction ledger according to an embodiment of the present invention.
15 is a flowchart illustrating a method for deriving an inter-account social relationship based on a transaction ledger according to an embodiment of the present invention.
FIG. 16 is a diagram for explaining a social media service apparatus using an account-to-account social relationship based on a transaction ledger according to an embodiment of the present invention.
17 is a flowchart for explaining a social media service method using an account-to-account social relationship based on a transaction ledger according to an embodiment of the present invention.

While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail. It should be understood, however, that the invention is not intended to be limited to the particular embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

Also, in the present invention, the terms account, address, and node are appropriately selected and used in order to facilitate the understanding of the invention in accordance with various characteristics of the transaction ledger. However, the present invention is not limited thereto, it means.

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

FIG. 1 is a diagram for explaining a relationship between accounts based on a transaction ledger and a social media service system according to an embodiment of the present invention. Referring to FIG.

Referring to FIG. 1, the derivation of a social relationship between accounts and the social media service system based on a transaction ledger according to an embodiment of the present invention includes an inter-account social relationship derivation apparatus 100, a social media service apparatus 200, And a transaction terminal 300 according to an embodiment of the present invention.

The inter-account social relationship derivation apparatus 100 can communicate with a plurality of transaction terminal apparatuses 300 to derive the social relations between accounts based on transaction ledgers generated by transactions between users having accounts.

The inter-account social relationship deriving apparatus 100 can calculate a value measure of an arbitrary account from the derived social relations among accounts.

Here, a transaction between users having an account may include various transactions such as financial transaction, mail transmission / reception, telephone transmission / reception, trade transaction, commodity transaction, media transmission / reception, and content transmission / reception. Financial transactions may include transactions in digital virtual currency and general bank transactions.

The social media service apparatus 200 interoperates with the apparatus 100 for deriving the relationship between accounts based on the transaction ledger, enables transactions between users having accounts, and supports community activities using the social relations among the derived accounts And can perform data processing and transmission / reception for data transmission.

The social media service apparatus 200 is interlocked with the inter-account social relationship deriving apparatus 100 based on the transaction ledger and enables transactions between users having accounts and data for supporting community activities using the calculated value scale Processing and transmission / reception can be performed.

The social media service apparatus 200 is interlocked with the inter-account social relationship deriving apparatus 100 based on the transaction ledger, and enables transactions between users having accounts, using the social relations among derived accounts and the calculated value scales Data processing and transmission and reception can be performed to support community activities.

The plurality of transaction terminal devices 300 are, for example, terminal devices used for trading digital virtual currency using a block chain. A representative digital virtual currency using a block chain may be a bit coin.

Digital virtual currency using block chains includes light coin, dark coin, name coin, pottery coin, and etherium in addition to bit coin.

A common feature of these is operating with a block chain in which all transaction details traded online using digital virtual currency including a trader bit coin are collected and stored in a plurality of transaction terminal devices.

The transactions between the accounts can be displayed as lines, and the social relations between the accounts can be derived. From each derived social relation, each account value scale can be calculated.

At this time, social relations between accounts may have a higher value measure depending on the number of transactions with other accounts. The social relations between accounts can have a higher value measure as the trading value of a trading account is higher.

A centrality calculation method can be used to measure social relations between accounts.

Various centric calculation methods such as Eigen Vector Centrality, Power Centrality, Degree Centrality, Closeness Centrality, Betweeness Centrality, and Priest Centrality This can be.

The above-described centrality calculations all have limitations that require fixing the 'n' value corresponding to the population.

Also, the formula can be difficult to use if the population is variable or too large to calculate.

For example, in the case of a bit coin block chain, theoretically, it has a population size of 160 of 2 (1,461,501,637,330,902,918,203,684,832,716,283,019,655,932,542,976), which is difficult to handle with a general computing device.

In addition, the Page Rank Algorithm, which takes into account the relationship among the centrality calculation methods, can be expressed by the following equation.

PR (A) = (1-d) + d * (PR (T1) / C (T1) + ... + PR (Tn) / C

PR: PageRank Value

d: damper value (0.85)

C: number of outlinks of Page

The PageRank uses only one variable to determine the rank value, the number of outlinks in the page (number of outlinks).

The page rank should converge to 1. Thus, when the population is very large, there is a limit to calculating or expressing the difference between nodes.

Also, since the page rank is determined only by others, the page rank has a limitation that it is difficult to reflect its own controllable elements.

The social relations between accounts can be calculated effectively by weighted centrality.

FIG. 2 is a diagram illustrating an apparatus for deriving an inter-account social relationship based on a transaction ledger according to an embodiment of the present invention.

Referring to FIG. 2, the inter-account social relationship derivation apparatus 100 based on a transaction ledger according to an embodiment of the present invention may include a data storage unit 110 and a processor 120.

The data storage unit 110 may store account information, derivation of social relations between accounts, software for calculating account value metrics, social relation information between derived accounts, and calculated value measures of accounts.

Here, the account may include, for example, a block chain address. Therefore, the value measure of the block chain address can be calculated as the value measure of the account. Here, the block chain address may be a bit coin address, which is a representative digital virtual currency using a block chain.

Digital virtual currency using block chains includes light coin, dark coin, name coin, porcelain coin, and etherium in addition to bit coin.

The common feature is that they are operated with a block chain in which all transaction details that are traded online are collected and stored using digital virtual currency including a trader bit coin.

The present invention is not limited to bit coins, but can be applied to accounts using various digital virtual currencies using a block chain. Further, the present invention is applicable not only to a block chain but also to a general bank account. In addition, the present invention can be applied to various service accounts in addition to financial accounts. For example, the present invention can be applied to a telephone number account, a mail account, a social media account, an Internet address account, device identification information, TCP / IP, a MAC address, asteroid identification information, and IoT identification information. That is, the present invention can be applied to various accounts that can derive social relations between accounts based on transaction ledgers between accounts.

In the case of a block chain, 400 to 500 transactions can be contained in a single block. In recent years, there are more than 1,700 cases. As the block size increases, it can contain far more transactions. Transactions are made mutually between block-chain addresses. One block chain address can perform transactions with a plurality of block chain addresses.

You can see the transaction by looking at the bit coin. Therefore, the correlation between block chain addresses can be grasped by using a transaction. By defining the relationship between block chain addresses using transactions, it is possible to grasp the social network between owners possessing each block chain address.

The processor 120 can derive the social relations of each account by using various additional data generated by the financial transactions among the users having the accounts, and can calculate the value measure of each account from the derived social relations.

The processor 120 may calculate a value measure of the account by a predetermined rule.

The value measure may include, for example, a valuation measure by evaluation.

The valuation measure may include a scoring scale. The valuation measure may include a rating scale. The rating scale can be defined by dividing the score by section.

The value measure may include, for example, a predictive value prediction measure.

The value measure can be calculated using the transaction information of the account.

Transaction information can include transaction information with other accounts.

The transaction information may include the frequency of transactions with other accounts. The higher the frequency of transactions, the higher the reliability scale.

The transaction information can include the value of the account and the value of the other account that performed the transaction.

For example, if an account has an account with a high value measure and a transaction, a higher value measure can be assigned than when an account and transaction with a low value scale occur.

The value measure can be represented by a plurality of badges according to the high and low values.

For example, the badge may be differentially classified, including the first badge, the second badge, the third badge, and the fourth badge. For example, the first badge may be a diamond badge. The second badge may be a gold badge. The third badge may be a silver badge. The fourth badge may be a bronze badge. However, the present invention is not limited to this, and it is possible to express a badge including characters of various tangible, intangible, and copyrighted works.

The value scale can be represented by a plurality of characters according to the high and low values. Here, the plurality of characters can be distinguished according to the importance of the account. Here, a plurality of characters can be classified according to the utilization pattern of the account. Here, the plurality of characters can be distinguished according to the characteristics of the account. For example, the characteristics of an account can include the size of the transaction, the number of transactions, the amount of the balance, and the transaction item.

The transaction information may include the account balance information.

The transaction information may include change rate information of the account.

The value measure can be calculated using owner verification of the account. For example, an account whose owner is verified according to the presence or absence of owner verification information may be given a different value measure from those that are not.

The value measure may include a reliability measure.

The relationship between each account and the calculated value of the account can be linked to a social media service account.

Processor 120 may utilize block-chain transactions as an associative line between block-chain addresses to derive a social relationship between each block-chain address.

To this end, the processor 120 uses a weighted centrality, a size of amount, and a level of accountability to calculate a value measure of each block chain address based on the derived social relations. identity verification, and change ratio can be selectively used.

The processor 120 may calculate a value measure by weighting the weighted centroid measure, the size of the balance, the account ownership confirmation, and the rate of change of the balance.

For example, the processor 120 may assign a weight 30 to the weighted centroid scale, the size of the balance, the account ownership confirmation, and a weight of 10 to the rate of change of the balance.

Processor 120 may yield a weighted centroid measure for any block-chain address. The weighted centroid measure may reflect the correlation of any block chain address with other block chain addresses.

The weighted centroid measure can be implemented by applying the page rank algorithm, but the present invention is not limited thereto.

PageRank is a method of weighting a document having a hyperlink structure such as the World Wide Web according to the relative importance. PageRank is based on the observation that more important pages receive links from more sites. For example, if page A puts a total of three links in pages B, C, and D, B gets 1/3 of A's page rank value.

The page rank also assumes a random visiting and searching model called Random Sufer. In this model, the surfer who visited the page A in the above example is satisfied with the page A and stops the search, or the user A visits the other page because the page A is not satisfied. If we say this probability (Damping Factor), B page gets rank as many pages.

The page rank of a page A is the sum of values that normalize the page rank of other pages citing the page. In other words, the page rank of page A becomes higher as the page rank value of another page that points to page A is higher. It is not a simple sum of page rank. For example, even if a page rank is high, if the page has thousands of links, the contribution of the page is low.

Processor 120 may place a segment on the weighted centroid measure calculated for each block chain address to determine the importance of the person who owns the block chain address depending on whether it belongs to the segment.

Therefore, the significance of the person can be known by looking at the arrangement according to the interval in which the value for any bit coin address belongs.

Processor 120 may use the weighted centroid metric to calculate the social relevance score for any block-chain address.

To this end, the processor 120 obtains block-chain transaction information for any block-chain address.

Processor 120 derives a social relationship between each block chain address based on the obtained block chain transaction information and calculates a weighted centroid measure between the corresponding block chain address and another block chain address based on the derived social relationship.

Processor 120 may calculate the size of the balance for any block chain address. The larger the size of the balance, the higher the reliability of the corresponding block chain address.

Processor 120 may calculate the rate of change for any block chain address. The less the change ratio, the higher the reliability of the block chain address.

Processor 120 may calculate a weighted centrality measure by defining the following equation to yield a value measure of each block chain address.

WC (A) = LW (A) * sr + (1-sr) * WC (N1) / NH (N1) + ... + WC (Nn) / NH (Nn)

WC represents Weighted Centrality, WC (A) is Weighted Center of Node A, LW is Local Weight, and LW (A) is Local Weight of Node A.

SR is the self ratio, WC (N1) is the weighted centroid of the first neighbor node N1 of node A, and WC (Nn) is the weighted centroid of the nth neighbor node Nn of node A.

NH is the number of neighboring nodes, NH (N1) is the number of neighboring nodes of N1, which is the first neighboring node of node A, NH (Nn) is the number of neighboring nodes of Nn, to be.

The sum of the weighted centrality of each node converges to the sum of the local weights. That is, the convergence value can be variously adjusted according to the result of calculation of the local weight, and the size of the convergence value can be set considering a very large single case.

The weighted centrality reflects the ratio of the external factor excluding the self ratio to the total of the values reflecting the self ratio to the local weight of the node and the weighted centroid of each node adjacent to the node divided by the number of adjacent nodes of the node And the value is the sum of the values.

The Self Ratio is a parameter for reflecting the self-factor of a node in calculating the weighted centroid of a node. Self proportion can be expressed as a ratio under self control.

Here, the number of neighbor nodes means the number of nodes that have performed transactions with the corresponding node.

Also, the convergence value of weighted centrality is adjusted flexibly according to the increment / decrement of the node, so it is more flexible to reflect the total value of the whole network.

Self Ratio (sr) means the rate of reflection of self. You can determine the rate of reflection of the value being changed by your own efforts.

For example, the larger the size of the asset held by the node, the higher the value can be calculated. The increase in these assets can be determined by the effort of the node owner.

Also, according to the Level of Identity Verification, the reliability of other factors can be determined according to the level of anonymity or blindness, so it is a factor that can reflect their own efforts.

The Number of Neighborhood is the number of nodes neighboring the node.

The local weight can be calculated by considering various factors that can be extracted from the local node.

Size of Amount

Number of Neighborhood node

Change Ratio

Number of Outbound or Inbound Transaction (number of inbound or outbound transactions)

Size of Outbound or Inbound Transaction (size of inbound or outbound transaction)

Level of Identity Verification

The LW calculation is not limited to the above parameters, but may consider various additional elements that can reflect the value of the local node.

3 is a diagram for explaining a transaction ledger in an apparatus for deriving an inter-account social relationship based on a transaction ledger according to an embodiment of the present invention.

Referring to FIG. 3, there are 13 transactions.

The first transaction involves transactions from the B address to the C address and the transaction volume is 30.386.

The second transaction involves trading from the C address to the D address and the transaction volume is 1.5.

The third transaction involves transaction from C address to E address, and the transaction amount is 27.36.

The fourth transaction involves transaction from E address to F address, and the transaction amount is 26.386.

The fifth transaction involves transactions from F address to J address, and the transaction amount is 23.286.

The sixth transaction involves transaction from J address to K address, and the transaction amount is 23.281.

The seventh transaction involves transaction from K address to E address, and the transaction amount is 16.281.

The eighth transaction involves transactions from E address to G address, and the transaction volume is 15.281.

The ninth transaction involves transactions from the G address to the H address, and the transaction amount is 14.231.

The tenth transaction involves transaction from H address to E address, and the transaction amount is 12.23.

The eleventh transaction involves transaction from E address to H address, and the transaction amount is 12.23.

The twelfth transaction involves transactions from the H address to the I address, and the transaction amount is 12.23.

The thirteenth transaction involves a transaction from the I-address to the D-address and the transaction volume is one.

FIG. 4 is a diagram for explaining social relations among accounts based on a transaction ledger according to an embodiment of the present invention.

Referring to FIG. 4, a transaction of each address can be used as an element forming a social relation between addresses, and the ledger of the corresponding transaction can be expressed by visualization.

Accordingly, the inter-account social relationship based on the transaction ledger according to an embodiment of the present invention can be derived from the transactions generated between the respective accounts B-K. For example, from account B to K, account B deals with one other account. D, F, G, I, J, and K accounts each have two different accounts. C and H accounts are dealing with three different accounts, and E accounts are dealing with five different accounts.

5 is a diagram illustrating parameters of respective nodes in an inter-account social relationship according to an embodiment of the present invention.

Referring to FIG. 5, each parameter of the K address can be seen from the B address.

The B address has a balance of 1, the number of neighboring nodes is 1, the change ratio is 1.00%, and the level of identity verification is 95.00%.

The C address has a balance of 1.5, the number of neighboring nodes is 3, the change ratio is 1.89%, and the level of Identity Verification is 90.00%.

The D address has a balance of 2.5, the number of neighboring nodes is 2, the change ratio is 1.23%, and the level of Identity Verification is 95.23%.

The E address has a balance of 1, the number of neighboring nodes is 5, the change ratio is 2.15%, and the level of identity verification is 10.25%.

The F address has a balance of 3.1, the number of neighboring nodes is 2, the change ratio is 0.50%, and the level of identity verification is 99.98%.

The G address has a balance of 1.05, the number of neighboring nodes is 2, the change ratio is 1.03%, and the level of identity verification is 7.65%.

The H address has a balance of 2.001, the number of neighboring nodes is 3, the change ratio is 1.99%, and the level of identity verification is 100.00%.

The I address has a balance of 11.23, the number of neighboring nodes is 2, the change ratio is 80.23%, and the level of identity verification is 56.65%.

The J address has a balance of 0.005, the number of neighboring nodes is 2, the change ratio is 90.01%, and the level of identity verification is 70.00%.

The K address has a balance of size 8, the number of neighboring nodes is 2, the change ratio is 0.35%, and the level of identity verification is 80.00%.

FIG. 6 is a table in which parameters of respective nodes including local weights according to an embodiment of the present invention are summarized.

6, when the local weight of each node is calculated, the local weight of the B address is 0.94050, the local weight of the C address is 3.97346, the local weight of the D address is 4.70293, the local weight of the E address is 0.50148, The local weight of the F address is 6.16777.

The local weight of the G address is 0.15900, the local weight of the H address is 5.88354, the local weight of the I address is 2.51545, the local weight of the J address is 0.00070, and the local weight of the K address is 12.75520.

In this case, the sum of the local weights is calculated to be 37.60002.

SUM (LW) = 37.60002

The above local weights can be calculated by the following equations.

LW = SA * NH * (100% -CR) * LV

SA: Size of Amt (Size of balance)

NH: # of neighborhood addresses (number of neighboring nodes)

CR: Change Ratio

LV: Level of Identity Verification

Thus, the local weight can be calculated in consideration of various factors such as the size of the balance, the number of neighboring nodes, the rate of change, and the level of the owner confirmation level.

However, the present invention is not limited to this, and there may be a method of determining local weights in various ways according to characteristics of each ledger.

7 is a table in which parameters of respective nodes including static centrality according to an embodiment of the present invention are summarized.

7, the static centrality of the B address is 0.02501, the static centrality of the C address is 0.10568, the static centrality of the D address is 0.12508, and the static centrality of the E address is 0.01334 , And the static centrality of the F address is 0.16404.

The static centrality of the G address is 0.00423, the static centrality of the H address is 0.15648, the static centrality of the I address is 0.06690, the static centrality of the J address is 0.00002 and the static centrality of the K address is 0.33923.

And the convergence value of the total static centroid is 1.

SUM (Static Centrality) = 1

Static Centrality can be calculated as LW / SUM (LW).

In order to calculate the weighted center, the self ratio should be defined.

We set the magnetic ratio to 15% in this simulation.

SR = 0.15

However, the present invention is not limited to this, and the numerical value of the magnetic ratio can be variously defined according to the characteristics of each ledger.

For example, the transaction rate may vary depending on whether the transaction ledger is a game account, a carrier account, a block-chain account, or a bank account.

For example, in the case of a game account, it is desirable to lower the self ratio, and in the case of a bank account, it may be desirable to increase the self ratio.

Also, you can change your ratio depending on whether you trade during the day or at night.

Also, depending on whether you trade during the day, how old you are, the density of transactions, and whether you are a bank credit account, your own percentage setting can be changed accordingly.

8 is a table in which parameters of respective nodes including weighted centroids according to an embodiment of the present invention are summarized.

8, the weighted centroid of the B address calculated according to the weighted centroid calculation formula is 1.36662, the weighted centroid of the C address is 4.32544, the weighted centroid of the D address is 3.20118, and the weighted centroid of the E address is 7.10174 , And the weighted centroid of the F address is 3.61798.

The weighted center of gravity of the G address is 2.48203, the center of gravity of the H address is 4.41489, the center of gravity of the I address is 2.98871, the center of gravity of the J address is 3.49534 and the center of gravity of the K address is 4.60609.

The sum of the weighted centroids is 37.60002.

SUM (WC) = 37.60002

Thus, it can be seen that the sum of the weighted centroids is equal to the sum of the local weights.

SUM (WC) = SUM (LW)

9 is a flowchart illustrating a method of deriving an inter-account social relationship based on a transaction ledger according to an embodiment of the present invention.

9, the data storage unit 110 stores account information, derivation of social relations between accounts, software for calculating account value scale, social relation information between derived accounts, and value measure information of various accounts (S1) .

Processor 120 obtains the block chain transaction information of the corresponding block chain address for any block chain address for which the value measure of the account is to be calculated (S2).

The processor 120 calculates a weighted centroid measure between the corresponding block chain address and another block chain address based on the social relation derived from the obtained block chain transaction information (S3).

The processor 120 calculates the size of the balance with respect to the block chain address based on the social relation derived from the obtained block chain transaction information (S4).

The processor 120 calculates an owner's degree of identity of the corresponding block chain address based on the social relation derived from the obtained block chain transaction information (S5).

The processor 120 calculates a change rate for the corresponding block chain address based on the social relation derived from the obtained block chain transaction information (S6).

The processor 120 may calculate a value measure of the corresponding block chain address by applying a predetermined weighting factor to the calculated weighted centroid scale, the size of the balance, the owner confirmation, and the change ratio (S7).

Here, the steps S3 to S6 may be selectively performed, and the order may be modified as desired. Also, step S7 may be performed using values selectively executed in steps S3 to S6.

10 is a flowchart illustrating a method of deriving an inter-account social relationship based on a transaction ledger according to an embodiment of the present invention.

10, the data storage unit 110 stores account information, derivation of social relations between accounts, software for calculating account value scale, social relation information between derived accounts, and value scale information of various accounts (S11) .

The processor 120 obtains the block chain transaction information of the corresponding block chain address with respect to any block chain address for which the value measure of the account is to be calculated (S12).

The processor 120 calculates a weighted centroid measure between the corresponding block chain address and another block chain address based on the social relation derived from the obtained block chain transaction information (S13).

The processor 120 calculates the size of the balance with respect to the corresponding block chain address based on the social relation derived from the acquired block chain transaction information (S14).

The processor 120 calculates the owner identity of the corresponding block chain address based on the social relation derived from the obtained block chain transaction information (S15).

The processor 120 calculates a change ratio for the block chain address based on the social relation derived from the obtained block chain transaction information (S16).

The processor 120 may calculate a value measure of the corresponding block chain address by applying a predetermined weighting factor to the calculated weighted centroid measure, the size of the balance, the owner confirmation number, and the change ratio (S17).

The processor 120 converts the calculated value measure into a score scale (S18).

Here, steps S13 to S16 may be selectively performed, and the order may be modified as desired. Also, steps S17 and S18 may be performed using the values selectively executed in steps S13 to S16.

11 is a flowchart illustrating a method of deriving an inter-account social relationship based on a transaction ledger according to an embodiment of the present invention.

11, the data storage unit 110 stores account information, derivation of social relations between accounts, calculation software for calculating account value, social relation information between accounts, and value scale information of various accounts (S21) .

The processor 120 obtains the block chain transaction information of the corresponding block chain address for any block chain address for which the value measure of the account is to be calculated (S22).

The processor 120 calculates a weighted centroid measure between the corresponding block chain address and another block chain address based on the social relation derived from the obtained block chain transaction information (S23).

The processor 120 calculates the size of the balance with respect to the block chain address based on the social relation derived from the obtained block chain transaction information (S24).

The processor 120 calculates an owner degree of identity of the corresponding block chain address based on the social relation derived from the obtained block chain transaction information (S25).

The processor 120 calculates a change rate for the corresponding block chain address based on the social relation derived from the obtained block chain transaction information (S26).

The processor 120 may calculate the value scale of the corresponding block chain address by applying a predetermined weighting factor to the calculated weighted centroid scale, the size of the balance, the owner confirmation degree, and the change ratio (S27).

The processor 120 converts the calculated value scale into a score scale, determines which interval the score scale belongs to, and calculates and provides a rating scale (S28). Here, the grade scale is defined by dividing the score by section.

Here, steps S23 to S26 may be selectively performed, and the order may be modified as desired. Also, steps S27 and S28 may be performed using values selectively executed in steps S23 through S26.

12 is a flowchart illustrating a method for deriving an inter-account social relationship based on a transaction ledger according to an embodiment of the present invention.

12, the data storage unit 110 stores account information, derivation of social relations between accounts, software for calculating account value metrics, social relation information between derived accounts, and value scale information of various accounts (S31) .

Processor 120 obtains the block chain transaction information of the corresponding block chain address for any block chain address for which the value measure of the account is to be calculated (S32).

The processor 120 calculates a weighted centroid measure between the corresponding block chain address and another block chain address based on the social relation derived from the obtained block chain transaction information (S33).

The processor 120 calculates the size of the balance with respect to the block chain address based on the social relation derived from the obtained block chain transaction information (S34).

The processor 120 calculates an owner's degree of identity of the corresponding block chain address based on the social relation derived from the obtained block chain transaction information (S35).

The processor 120 calculates a change ratio for the corresponding block chain address based on the social relation derived from the obtained block chain transaction information (S36).

The processor 120 may calculate the value scale of the corresponding block chain address by applying a predetermined weighting factor to the calculated weighted centroid scale, the size of the balance, the owner confirmation, and the change ratio (S37).

The processor 120 converts the calculated value scale into a score scale, determines which of the badges the score scale belongs to, and provides a corresponding badge image (S38). For example, a badge can be represented by a plurality of badges according to the high and low values of the value. For example, a diamond badge, a gold badge, a silver badge, or a bronze badge can be selected.

Here, steps S33 to S36 may be selectively performed, and the order may be modified as desired. Also, steps S37 and S38 may be performed using the values selectively executed in steps S33 through S36.

13 is a flowchart illustrating a method for deriving an inter-account social relationship based on a transaction ledger according to an embodiment of the present invention.

Referring to FIG. 13, the data storage unit 110 stores account information, derivation of social relations between accounts, calculation software for calculating account value, social relationship information between accounts, and value scale information of various accounts (S41) .

Processor 120 obtains the block chain transaction information of the corresponding block chain address for any block chain address for which the value measure of the account is to be calculated (S42).

The processor 120 calculates a weighted centroid measure between the corresponding block chain address and another block chain address based on the social relation derived from the obtained block chain transaction information (S43).

The processor 120 calculates the size of the balance with respect to the corresponding block chain address based on the social relation derived from the obtained block chain transaction information (S44).

The processor 120 calculates the owner identity of the corresponding block chain address based on the social relation derived from the obtained block chain transaction information (S45).

The processor 120 calculates a change ratio for the corresponding block chain address based on the social relation derived from the obtained block chain transaction information (S46).

The processor 120 may calculate the value scale of the corresponding block chain address by applying a predetermined weighting factor to the calculated weighted centroid scale, the size of the balance, the owner confirmation degree, and the change ratio (S47).

The processor 120 converts the calculated value scale into a score scale, determines which character the score scale belongs to, and provides the character image (S48). For example, a character can be represented by a plurality of characters according to the high and low value scales.

Here, steps S43 to S46 may be selectively performed, and the order may be modified as desired. Also, steps S47 and S48 may be performed using the values selectively executed in steps S43 to S46.

FIG. 14 is a flowchart illustrating a method of deriving an inter-account social relationship based on a transaction ledger according to an embodiment of the present invention.

Referring to FIG. 14, the data storage unit 110 stores account information, derivation of social relations between accounts, calculation software for calculating account value, social relationship information between accounts, and value scale information of various accounts (S51) .

Processor 120 obtains the block chain transaction information of the corresponding block chain address for any block chain address for which the value measure of the account is to be calculated (S52).

The processor 120 calculates a weighted centroid measure between the corresponding block chain address and another block chain address based on the social relation derived from the obtained block chain transaction information (S53).

The processor 120 calculates the size of the balance with respect to the corresponding block chain address based on the social relation derived from the acquired block chain transaction information (S54).

The processor 120 calculates an owner's degree of identity of the corresponding block chain address based on the social relation derived from the obtained block chain transaction information (S55).

The processor 120 calculates a change rate for the corresponding block chain address based on the social relation derived from the obtained block chain transaction information (S56).

The processor 120 may calculate the value scale of the corresponding block chain address by applying a predetermined weighting factor to the calculated weighted centroid scale, the size of the balance, the owner confirmation, and the change ratio (S57).

The processor 120 converts the calculated value measure into a score scale (S58).

The processor 120 determines an application pattern of the account, determines which character the utilization pattern belongs to, and provides the corresponding character image among the plurality of characters (S59). For example, a character can be represented by a plurality of characters according to the utilization pattern of the account.

Here, steps S53 to S56 may be selectively performed, and the order may be modified as desired. Steps S57, S58, and S59 may be performed using values selectively executed in steps S53 through S56.

15 is a flowchart illustrating a method for deriving an inter-account social relationship based on a transaction ledger according to an embodiment of the present invention.

Referring to FIG. 15, the data storage unit 110 stores account information, derivation of social relations between accounts, software for calculating account value scale, social relation information between accounts, and value scale information of various accounts (S61) .

The processor 120 obtains the block chain transaction information of the corresponding block chain address with respect to any block chain address for which the value measure of the account is to be calculated (S62).

The processor 120 calculates a weighted centroid measure between the corresponding block chain address and another block chain address based on the social relation derived from the obtained block chain transaction information (S63).

The processor 120 calculates the size of the balance with respect to the corresponding block chain address based on the social relation derived from the obtained block chain transaction information (S64).

The processor 120 calculates the owner identity of the corresponding block chain address based on the social relation derived from the obtained block chain transaction information (S65).

The processor 120 calculates a change rate for the corresponding block chain address based on the social relation derived from the obtained block chain transaction information (S66).

The processor 120 may calculate the value scale of the corresponding block chain address by applying a predetermined weight to the calculated weighted centroid scale, the size of the balance, the owner confirmation degree, and the change ratio (S67).

The processor 120 converts the calculated value scale into a score scale (S68).

The processor 120 determines the characteristics of the account, determines which character the characteristic of the account belongs to, and provides the corresponding character image among the plurality of characters (S69). For example, multiple characters can be distinguished by the nature of the account. For example, the characteristics of an account can include the size of the transaction, the number of transactions, the amount of the balance, and the transaction item.

Here, steps S63 to S66 may be selectively performed, and the order of the steps may be changed. Also, steps S67, S68, and S69 may be performed using the values selectively performed in steps S63 through S66.

FIG. 16 is a diagram for explaining a social media service apparatus using an account-to-account social relationship based on a transaction ledger according to an embodiment of the present invention.

Referring to FIG. 16, the social media service apparatus 200 using the inter-account social relationship based on the transaction ledger according to an embodiment of the present invention interworks with the inter-account social relationship deriving apparatus 100 based on the transaction ledger, Unit 210 and a processor 220. [0029]

The data storage unit 210 may store account information, social relationship information between accounts, value measure information of an account, and social media service information.

The account information, the social relationship information between accounts, and the value measure information of the account can be provided from the inter-account social relationship deriving apparatus 100 based on the transaction ledger.

Processor 220 enables transactions between users having accounts and performs data processing and transmission / reception to support community activities using derived value measures derived from social relationships between derived accounts and derived accounts can do.

To this end, the processor 220 periodically or, if there is a request from the user, provides the user with a certain account with the social relationship between accounts and the value scale information for that account with the transaction ledger-based social relationship derivation apparatus 100 As shown in Fig.

The processor 220 may perform various data processing and transmission for community activities between accounts based on the social media service information stored in the data storage unit 210, the social relations between the inquired accounts, and the value scale information.

For example, the processor 220 may implement any user transmitting a message to another user.

Processor 220 may implement any user sending a bit coin to another user. Processor 220 may implement any user receiving a bit coin from another user.

The processor 220 may post various content that any user desires.

Processor 220 may implement posting arbitrary content to other social media services in conjunction with other social media services platforms.

The processor 220 may perform various financial transactions of an account such as charging, withdrawing, and exchanging money.

Processor 220 may follow other users by paying a bit coin. If you follow other users, you can view or browse the contents posted by the users.

Processor 220 may display a preference for the content while paying a bit coin. For example, the processor 220 may express a positive response to the content. For example, the processor 200 may display a likelihood (LIKE).

Processor 220 may add comments to the main content. Processor 220 may add simple content that includes text, images, video, or projects.

The processor 220 may implement any user's tip to another user. For example, the processor 220 may receive a request from a certain user and give a tip to a user who provides the content with respect to good content.

For example, the processor 220 may vary the tip amount transmitted to another user depending on the strength with which the user presses the terminal.

For example, the processor 220 may vary the amount of tip to be delivered according to the intensity of the depression of the terminal and the duration of depression.

The processor 220 can make payment using an escrow.

In addition, the processor 220 can make a payment settlement using a bit coin.

The processor 220 may apply the fees applied at the time of financial transactions differently according to the value measure of the account. However, the present invention is not limited to this, and besides the financial transaction, it is possible to differentially apply the fee applied to various transactions.

The processor 220 may apply the transaction limits differently depending on the value measure of the account.

The processor 220 uses the social relationship between accounts or the value measure calculated for each account to provide community activity based on trustworthiness of the account holder to provide psychological stability in the performance of social community activities and financial transactions. And can perform data processing and transmission for support.

The processor 220 can perform the data processing and transmission for performing the financial transaction using the account as the owner of the already secured account can implement the social media service based on the account.

The processor 220 can perform data processing and transmission for users participating in financial transactions using an account to form various financial transactions and various communities through the social media service and communicate with each other.

17 is a flowchart illustrating a social media service method using an account value measure according to an embodiment of the present invention.

Referring to FIG. 17, the data storage unit 210 stores account information, social relationship information between accounts, account value measure information, and social media service information (S71).

The processor 220 may periodically or periodically or at the request of the user may provide the user with a certain account information about the social relationship between accounts and the value scale information for the account from the inter-account social relationship derivation apparatus 100 based on the transaction ledger (S72).

The processor 220 may display the searched account social relations, account value scale information in the social media service account of the owner who owns the account (S73)

The processor 220 can apply the fees and the transaction limits applied at the time of financial transactions differently according to the social relations among accounts or the value measure of the account (S74).

Processor 220 may enable the owners of pre-existing accounts to provide psychological stability as a result of their social community activities and financial transactions based on their accounts, And performs data processing and transmission to support community activities using the value measure (S75).

For example, the processor 220 transmits a message to another user based on the social media service information when there is a request from any user.

For example, the processor 220 sends a bit coin to the other user when requested by the user.

For example, processor 220 posts various content when requested by the user.

For example, the processor 220 may perform various transactions of accounts such as charging, withdrawing, and exchanging money.

For example, the processor 220 may follow other users by paying a bit coin.

For example, the processor 220 displays a positive response to the content while paying a bit coin, or displays a preference for the content by displaying a likelihood (LIKE).

The embodiments of the present invention described above are not implemented only by the apparatus and method, but may be implemented through a program for realizing the function corresponding to the configuration of the embodiment of the present invention or a recording medium on which the program is recorded. Such a recording medium can be executed not only on a server but also on a user terminal.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, It belongs to the scope of right.

Claims (12)

A data storage unit for storing account information, software for calculating a social relationship between accounts, calculating a value measure of an account, social relation information between accounts, and value scale information of a calculated account; And
A processor for calculating the weighted centrality of each account for calculating a value measure of the account in an inter-account social relationship derived based on a transaction ledger generated by a transaction between users having the account,
The processor calculates a weighted centroid measure of the account using the local weight component determined for an arbitrary account and the weighted centroid measure component of a neighboring account having a social relationship with the account,
The weighted centroid is a value obtained by reflecting a self ratio to a local weight of a node corresponding to an arbitrary account and a value obtained by dividing a weighted centroid of each node adjacent to the node by the number of adjacent nodes of the corresponding node, And the value of the external factor,
The Self Ratio is a parameter for reflecting the self-factor of the corresponding node in calculating the weighted center of gravity of the node,
Wherein the processor is based on a transaction ledger that calculates the weighted centrality of each account by the following equation:
WC (A) = LW (A) * sr + (1-sr) * WC (N1) / NH (N1) + ... + WC (Nn) / NH (Nn)
LW (A) is the local weight of the node A, sr is the weight of the node A, WC is the weighted centroid of the node A, WC is the weighted centroid of the node A, LW is the local weight, WC (N1) is the weighted centroid of the first neighboring node N1 of node A, WC (Nn) is the weighted centroid of the nth neighbor node Nn of node A, and NH is the number of neighboring nodes (Number NH (N1) is the number of neighbor nodes of N1, which is the first neighbor node of node A, and NH (Nn) is the number of neighbor nodes of Nn,
2. The apparatus of claim 1, wherein the account is a transaction ledger comprising a block chain address.
The apparatus of claim 1, wherein the processor derives a social relationship between the accounts using transactions between the accounts.
The method according to claim 1,
Wherein the processor calculates a weighted centroid measure such that the sum of the weighted centroid measures of each account converges to the sum of the local weights of the respective accounts.
delete delete 2. The apparatus of claim 1, wherein the local weight component for the arbitrary account is determined as a value independent from a neighbor account having a social relationship with the account.
8. The apparatus of claim 7, wherein the processor calculates the local weight of the account by applying a predetermined weight to the size of the balance, the owner confirmation, and the change ratio.
8. The apparatus of claim 7, wherein the processor is based on a transaction ledger that calculates local weights for each account by:
LW = SA * NH * (100% -CR) * LV
LW: Local Weight
SA: Size of Amt (Size of balance)
NH: # of neighborhood addresses (number of neighboring nodes)
CR: Change Ratio
LV: Level of Identity Verification
Obtaining transaction information for an arbitrary account based on a transaction ledger generated by a transaction between users having accounts, and deriving a social relationship between the accounts; And
Calculating the weighted centrality of each account for calculating the value measure of the account in the derived social relations between accounts,
Wherein the step of calculating the weighted centroid of each account calculates a weighted centroid measure of the account using the local weight component determined for any account and the weighted centroid measure component of the neighboring account having a social relationship with the account,
The weighted centroid is a value obtained by reflecting a self ratio to a local weight of a node corresponding to an arbitrary account and a value obtained by dividing a weighted centroid of each node adjacent to the node by the number of adjacent nodes of the corresponding node, And the value of the external factor,
The Self Ratio is a parameter for reflecting the self-factor of the corresponding node in calculating the weighted center of gravity of the node,
Calculating a weighted centroid of each account based on a transaction ledger that calculates the weighted centroid of each account by the following formula:
WC (A) = LW (A) * sr + (1-sr) * WC (N1) / NH (N1) + ... + WC (Nn) / NH (Nn)
LW (A) is the local weight of the node A, sr is the weight of the node A, WC is the weighted centroid of the node A, WC is the weighted centroid of the node A, LW is the local weight, WC (N1) is the weighted centroid of the first neighboring node N1 of node A, WC (Nn) is the weighted centroid of the nth neighbor node Nn of node A, and NH is the number of neighboring nodes (Number NH (N1) is the number of neighbor nodes of N1, which is the first neighbor node of node A, and NH (Nn) is the number of neighbor nodes of Nn,
11. The method of claim 10,
Wherein the step of calculating the weighted centroid of each account calculates a weighted centroid measure such that the sum of the weighted centroid measures of each account converges to the sum of the local weights of the respective accounts.
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