KR101783476B1 - A system and method for distributing profit by providing source data in data transaction service - Google Patents

Abstract

There is provided a method of providing a data transaction service, comprising the steps of uploading source data from a data providing terminal, and performing a source value judgment based on a value judgment algorithm including the size, speed, diversity and quality of the data A step of weighting at least one parameter of the source data as a commodity to process the commodity; determining a commodity value based on a value judging algorithm based on a value judging algorithm for the commodated commodity; And intermediating the transaction when at least one data purchasing terminal has been purchased.

Description

TECHNICAL FIELD [0001] The present invention relates to a data distribution service and a data distribution service,

The present invention relates to a data transaction service providing method and a data transaction service for distributing a certain amount of revenue to a original data provider for data sales when a data transaction in which data is used in a data transaction service is an actual transaction, To a system and method for distributing revenue based on the provision of source data.

Recently, as big data storage and processing become a hot topic, there is a need for data transactions that are stored and accumulated all over the world.

Historically, data consumers have been collecting, processing, analyzing and consuming data directly. This type of data industry is a self-sufficient data processing industry in terms of industrial evolution. If data consumers have to intervene in all forms of processing until they process and finalize the data, the work of the data scientist is a difficult and difficult task.

In this difficult self-contained data processing industry, the structure of the industry is changing as a marketplace for data that producers produce and circulate large amounts of data and link them to end users. Data marketplace enables not only producers and consumers but also collectors, dealers and processors to participate in the process, which creates added value and makes it easier for the final consumer to process and sell the necessary forms. Through the marketplace, the data distribution and processing industries are growing and the market ecosystem is being formed through them.

The data processing process includes various processes such as collecting, integrating, transforming, cleaning, filtering, aggregating, and mash-up after data production. Which can be interpreted, evaluated, analyzed, consumed, or reproduced to enter the reprocessing process cycle. In other words, the process from production to consumption is complex and multistage.

On the other hand, the original data can become a data product itself and can have a value, and the value can be changed through the process of data commodification, that is, the processing. In this connection, Korean Patent Laid-Open Publication No. 2009-0005503 (published on Jan. 14, 2009) discloses a configuration for judging the value of data.

However, the above-described configuration merely discloses a configuration for determining a price before a transaction is performed, and it is urgently required to develop a system capable of distributing an appropriate profit to an original data provider according to the extent of data processing when data transactions are made, have.

One embodiment of the present invention is a revenue distribution system that can be used in a data trading platform, and a method of distributing revenue to a party who has provided source data to data providers, And a virtuous circle structure of data transactions that can be provided. It should be understood, however, that the technical scope of the present invention is not limited to the above-described technical problems, and other technical problems may exist.

As a technical means for achieving the above technical object, an embodiment of the present invention is a method for receiving data from a data providing terminal, comprising the steps of: uploading source data from a data providing terminal; uploading the uploaded source data with data size, speed, diversity and quality Determining a source value based on a value judgment algorithm based on a value judgment algorithm based on a value judgment algorithm with respect to the processed goods; A step of intermediating the transaction when the purchase of at least one data purchasing terminal occurs by uploading the commodity whose value of the commodity value has been completed, and the step of distributing the commodity as the contribution to the profit by a certain calculation method when the profit is generated .

According to any one of the above-mentioned objects of the present invention, a profit distribution system that can be used for a data trading platform and a method of distributing revenue to a party who has provided source data through data distribution, It can include a virtuous cycle structure of data transactions that can be beneficial to the information provider. By enabling the distribution of revenue to the data providers, it is possible to activate data provisioning and allow the data buyer to select a variety of data on the data transaction platform. It is possible to enlarge the width of In addition, if the data trading platform presents a convenient pricing standard and a profit distribution method to the original data provider, and distributes the revenue by agreement, shortening the period in which data commodification can be started can shorten the expense of exposing the data commodity to the platform.

1 is a block diagram illustrating a data transaction service providing system according to an embodiment of the present invention.
FIG. 2 is a block diagram illustrating a data transaction service providing server shown in FIG. 1. Referring to FIG.
3 is a block diagram illustrating a data transaction service according to an embodiment of the present invention.
4 is a block diagram illustrating an embodiment of a data transaction service according to an embodiment of the present invention.
5 is a flowchart illustrating a method of providing a data transaction service according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings, which will be readily apparent to those skilled in the art. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. In order to clearly illustrate the present invention, parts not related to the description are omitted, and similar parts are denoted by like reference characters throughout the specification.

Throughout the specification, when a part is referred to as being "connected" to another part, it includes not only "directly connected" but also "electrically connected" with another part in between . Also, when an element is referred to as "including" an element, it is to be understood that the element may include other elements as well as other elements, And does not preclude the presence or addition of one or more other features, integers, steps, operations, components, parts, or combinations thereof.

The terms "about "," substantially ", etc. used to the extent that they are used throughout the specification are used in their numerical value or in close proximity to their numerical values when the manufacturing and material tolerances inherent in the stated meanings are presented, Accurate or absolute numbers are used to help prevent unauthorized exploitation by unauthorized intruders of the referenced disclosure. The word " step (or step) "or" step "does not mean" step for. &Quot;

In this specification, the term " part " includes a unit realized by hardware, a unit realized by software, and a unit realized by using both. Further, one unit may be implemented using two or more hardware, or two or more units may be implemented by one hardware.

In this specification, some of the operations or functions described as being performed by a terminal, a device, or a device may be performed instead in a server connected to the terminal, device, or device. Likewise, some of the operations or functions described as being performed by the server may also be performed in a terminal, device or device connected to the server.

In this specification, some of the operations or functions described in the mapping or matching with the terminal are mapping or matching the unique number of the terminal, which is the identification data of the terminal, or the identification information of the individual . ≪ / RTI >

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, the present invention will be described in detail with reference to the accompanying drawings.

1 is a block diagram illustrating a data transaction service providing system according to an embodiment of the present invention. Referring to FIG. 1, a data transaction service providing system 1 may include a data providing terminal 100, a data transaction service providing server 300, and at least one data purchasing terminal 400. However, the data transaction service providing system 1 of FIG. 1 is only an embodiment of the present invention, and thus the present invention is not limited to FIG.

At this time, the respective components of FIG. 1 are generally connected through a network 200. For example, as shown in FIG. 1, the data providing terminal 100 may be connected to the data transaction service providing server 300 through the network 200. The data providing terminal 100 may be connected to at least one data purchasing terminal 400 through the network 200. [ Also, the data transaction service providing server 300 may be connected to at least one data purchasing terminal 400 via the network 200. Also, at least one data purchasing terminal 400 may be connected to the data transaction service providing server 300 and the data providing terminal 100 through the network 200.

Here, the network 200 refers to a connection structure capable of exchanging information between nodes such as a plurality of terminals and servers. One example of such a network 200 is a 3rd Generation Partnership Project (3GPP) network, A 5th Generation Partnership Project (5GPP) network, a World Interoperability for Microwave Access (WIMAX) network, an Internet, a LAN (Local Area Network), a Wireless LAN (Local Area Network) Wide area network (PAN), a personal area network (PAN), a satellite broadcast network, an analog broadcast network, a DMB (Digital Multimedia Broadcasting) network, and the like. The network 200 also includes, but is not limited to, a short range, medium and long range network including a Bluetooth network, an NFC network, an RFID network, and the like.

The data providing terminal 100, the data transaction service providing server 300, and the at least one data purchasing terminal 400 shown in FIG. 1 are not limited to those shown in FIG.

The data providing terminal 100 may be a terminal that provides data. At this time, the data may be source data, i.e., unprocessed, non-commercialized data. The data providing terminal 100 may be a terminal that receives a fee for data sales from the data transaction service providing server 300.

Here, the data providing terminal 100 may be implemented as a computer capable of connecting to a remote server or terminal through the network 200. [ Here, the computer may include, for example, a notebook, a desktop, a laptop, and the like on which a WEB browser is installed. At this time, the data providing terminal 100 may be implemented as a terminal capable of connecting to a remote server or terminal through the network 200. [ The data providing terminal 100 is a wireless communication device that is guaranteed to be portable and mobility, for example, as a navigation device, a personal communication system (PCS), a global system for mobile communications (GSM), a personal digital cellular (PDC) Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication) -2000, CDMA (Code Division Multiple Access) -2000, W-CDMA (W- A handheld based wireless communication device such as a smart phone, a smartphone, a smartpad, a tablet PC, and the like.

The data transaction service providing server 300 may be a server that transmits a data transaction service web page, a program, an application, an application page, and a user interface to the data providing terminal 100 and the at least one data purchasing terminal 400. Here, the data transaction service providing server 300 may be a server for receiving source data, processing the data, and commodifying the data. The data transaction service providing server 300 may be a server that provides a certain percentage of the sold proceeds to the data providing terminal 100 as a fee.

At this time, the data transaction service providing server 300 may be implemented as a computer capable of connecting to a remote server or terminal through the network 200. [ Here, the computer may include, for example, a notebook, a desktop, a laptop, and the like on which a WEB browser is installed.

At least one data purchasing terminal 400 may be a terminal that purchases processed and merchandized data. Here, at least one data purchasing terminal 400 may be implemented as a computer capable of connecting to a remote server or terminal through the network 200. Here, the computer may include, for example, a notebook, a desktop, a laptop, and the like on which a WEB browser is installed. At this time, at least one data purchasing terminal 400 may be implemented as a terminal capable of connecting to a remote server or terminal through the network 200. At least one data purchasing terminal 400 may be a wireless communication device with guaranteed portability and mobility, such as navigation, PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular) , A PHS (Personal Handyphone System), a PDA (Personal Digital Assistant), an IMT (International Mobile Telecommunication) -2000, a CDMA (Code Division Multiple Access) -2000, a W-CDMA Based wireless communication device such as a wireless Internet terminal, a smartphone, a smartpad, a tablet PC, and the like.

FIG. 2 is a block diagram illustrating a data transaction service providing server shown in FIG. 1, FIG. 3 is a diagram illustrating a data transaction service according to an embodiment of the present invention, FIG. FIG. 6 is a configuration diagram for explaining an embodiment in which a data transaction service according to an embodiment is implemented. FIG.

2, a data transaction service providing server 300 according to an exemplary embodiment of the present invention includes an upload unit 310, a source determination unit 320, a processing unit 330, a product determination unit 340, A mediating unit 350, a settlement unit 360, and a big data unit 370.

(Not shown) operating in conjunction with the data transaction service providing server 300 or the data transaction service providing server 300 according to an embodiment of the present invention may be connected to the data providing terminal 100 and the at least one data purchasing terminal 300. [ The data providing terminal 100 and the at least one data purchasing terminal 400 may be configured to transmit data transaction service applications, programs, app pages, web pages, Web pages, etc. can be installed or opened. In addition, a service program may be operated in the data providing terminal 100 and at least one data purchasing terminal 400 using a script executed in a web browser. Here, a web browser is a program that enables a WWW (World Wide Web) service, and is a program for receiving and displaying hypertext described in hypertext mark-up language (HTML), for example, Netscape (Netscape) An Explorer, chrome, and the like. Further, the application refers to an application on the terminal, for example, an app (app) running on a mobile terminal (smart phone).

At this time, the connection of the network 200 can be established by connecting the data providing terminal 100, the data transaction service providing server 300, and at least one data purchasing terminal 400 to the network 200, Means creating a communication object at the point of contact. The data transaction service providing server 300 can exchange data with each other through a communication object.

The upload unit 310 can upload the source data from the data providing terminal 100.

The source determination unit 320 can determine the source value of the uploaded source data based on a value determination algorithm including data size, speed, diversity and quality.

At this time, the value judgment algorithm is based on the capacity, speed, diversity and quality of the source data, and the capacity of the source data can determine the price per unit size and the cell of the data. In addition, the value determination algorithm may be based on the number of columns and the number of criteria with different units of source data diversity. At this time, the quality of the source data is considered based on the management regulations of the public data, and the latestness, accuracy, and interconnectivity are taken into consideration. The more the null, the unit of measurement, If there is a condition, it can be increased as the constraint condition is satisfied, the metadata is displayed, and there is no data duplication or inconsistency.

The processing section 330 can process the source data as a product by weighting at least one parameter. The at least one parameter includes at least one of a variance analysis, a time series analysis, a current analysis, a comparative analysis, a diagnostic analysis, an optimization analysis and a predictive analysis. In processing a product, The nulls can be removed from the data, and the sum, average, minimum, and maximum values of the data can be calculated.

The product determination unit 340 can determine the product value based on the value determination algorithm based on the value determination algorithm for the processed product. At this time, when processing the source data into a commodity, the commodity determination unit 340 assigns weights to at least one parameter among at least one parameter, adds the weights of the at least one parameter used, Can be performed.

The product judging unit 340 can calculate the demand level of the contents included in the goods through the search word and the keyword when the goods are judged on the basis of the value judging algorithm based on the value judging algorithm for the processed goods. In addition, the product judging unit 340 judges whether the contents contained in the content, the number of the frames whose similarity degree of the search words and the keywords are equal to or higher than the preset value, , The value of the product can be increased.

The mediating unit 350 can mediate the transaction when the purchasing of the at least one data purchasing terminal 400 occurs by uploading the commodity value-judged commodity.

The settlement unit 360 uploads the commodity value-judged goods in the intermediary unit 350 and intermediates the transaction when the purchase of the at least one data purchasing terminal 400 occurs, and then the value difference between the source data and the commodity The fee may be calculated as a predetermined ratio. Then, the settlement unit 360 can settle the calculated fee to the data providing terminal 100. [

When the purchase of the at least one data purchasing terminal 400 occurs, the big data unit 370 uploads the commodity value-judged goods in the intermediary unit 350, and intermediates the transaction, The buyer's purchase pattern, and the buyer's personal information as big data.

Then, the big data unit 370 can perform data mining based on the collected large data based on the customer behavior prediction model, and can extract the product based on the customer behavior prediction data predicted by the data mining. Further, the big data unit 370 can transmit the extracted goods to at least one purchasing terminal having the customer behavior prediction data, respectively.

At this time, the data transaction service providing server 300 includes a mashup platform for collecting, storing and managing multi-channel, multi-format heterogeneous data based on distributed processing based on the Hadob Big Data Platform for processing big data, Based analysis engine through a combination of learning algorithms.

Also, the product can be reprocessed and reproduced through a query analysis of at least one data purchasing terminal 400.

The value determination algorithm and the merchandising process described above are as shown in Table 1, and the original value data determination algorithm is defined as Algorithm 1, the product value determination algorithm is defined as Algorithm 2, and the profit distribution algorithm is defined as Algorithm 3.

function Classification Classification criteria Algorithm 1 (y1)





















Capacity (x1)


A. aMB per 1MB ex) 100 won B. per cell b) ex) 1 won  Allows you to choose between two methods ex) 57KB Example file: 570 won per MB, 940 won per cell Speed (x2)






 second  minute  city  Work  week  month  year  No updates Diversity (x3)


 Number of columns in different units (for example, two lengths (m) and two lengths (cm))  Number of criteria (Hit by two local temperature and yearly temperature) Quality (x4) (considering currentness, accuracy, and interconnectivity based on public data management guidelines)





 No Nulls  Include unit of measure  Marked to standard code classification  Meets constraints when constraints exist  Show metadata  No data duplication  No data discrepancy Product processing










Method (x5)










1. Null Removal 2. Total 3. Average 4. Minimum value, maximum value 5. Analysis of variance 6. Time Series Analysis 7. Other methods · Status analysis · comparison analysis · Diagnostic Analysis · Optimization analysis · Predictive analysis Algorithm 2 (y2)
Reflecting the process of product processing  Analytical data Weights are given to the machining methods used in the commercialization process to sum the weights of all the machining methods used. Reflection of source data value judgment (Algorithm 1)  Same as algorithm 1 Algorithm 3 (y3)
Revenue distribution
 From the difference between the analytical data value and the source data value Distributes revenue to source data providers at a certain rate (ex. 1%) in a fee-based manner

At this time, in the commercialization process, the original data uploaded by the data provider may be stored in the data transaction service providing server 300 and may be subjected to a data commercialization process. At this time, there are a process of checking whether the data is usable data in the commercialization process, and a fusion process of judging the data value and increasing the value.

Here, the available data should include the data collection period and the survey method, and the first column should contain a brief description indicating the data type as the main language. Also, if there is a unit of the data type in the second column, the unit should be displayed and there should be no empty cell. If the available data is checked, it can be determined whether the data is different from the existing data in order to determine the data value. If you have different units, collection period, or survey method, you will have higher value.

In this case, the results that can be extracted by the above three algorithms are designated as y1, y2, and y3, and the items included in each algorithm are defined as x1 to x5. In addition, the same ratio as the weight not yet determined can be expressed as a lower case letter such as a to g, as shown in Table 2 below.

Algorithm 1 value judgment 1 0 < y1 < = 100
a, b, c, d <- proportaion
y1
= a * max (A: x1 * 100 circle | B: x1 * 1 circle)
+ if (x2 < 60 sec then b < - b8
else x2 <60 min then b <- b7
else x2 <24 hour then b <- b6
else x2 <7 day then b <- b5
else x2 <30 day then b <- b4
else x2 <12 month then b <- b3
else x2 <1 year then b <- b2
else b <- b1)
+ c * count (x3)
+ d * count (x4) Algorithm 2 value judgment 2 0 < y2 < = 100
e, f <- proportaion
y2
= if (x5 = 'Situation Analysis', a1
else x5 = 'Comparative analysis', a2
else x5 = 'Diagnostic analysis', a3
else x5 = 'Optimization analysis', a4
else x5 = 'predictive analysis', a5) * count (x5)
+ b * y1 Algorithm 3 Distribution Revenue g <- revenue distribution proportion (ex. 1%)
y3
= a * (y2-y1)

The data transaction service according to an embodiment of the present invention is a service for distributing a certain rate of profit to an information provider when a data commodity in which original data for sales is used is an actual transaction and sales are recognized by the company, . At this time, a company operating a platform can upload and sell data items to the data trading platform, or can receive data from other institutions, companies and individuals.

At this time, the original data can be a data product itself and can have a value, and it can have value through the process of data commercialization. Accordingly, it is expected that the platform operator will be able to negotiate the pricing and profit distribution after receiving the original data because it is necessary to inspect and commercialize the provided original data as sales value data. However, If you distribute revenue after data commodity sales, data commodity platforms can result in faster data commodity sales.

The data transaction service of the present invention will be summarized with reference to FIG.

First, the process of uploading the source data (S3100) is performed.

At this time, the data provider can directly upload csv, xlsx and xml data on the WEB. Here, the data provider can input the price when the original data is uploaded, and this price is not reflected in the price, but is referred to in the pricing. Pricing is based on data size, variety, and usability, and can be automated in the form of algorithms.

The original data uploaded by the data provider is stored in the server of the data transaction platform operating company and goes through the data commercialization process. The merchandising process is a process of checking whether the data is usable data, a process of determining the data value and increasing the value, and may include the process of determining the value of the source data, the processing of the merchandise, and the process of judging the merchandise value.

The available data should include the data collection period and the method of investigation, and a brief description of the type of the reactor should be provided. Also, if there is a unit of data type, the unit should be displayed and there should be no empty cell. Also, if the available data is checked, it is judged whether or not the data is different from the existing data in order to judge the data value. If the existing data, unit, collection period, and survey method are different, the value will increase and if it is the same kind as existing, it will not affect the value.

The next step is to determine the source data value (S3200). The value of source data can be judged according to classification criteria, for example, capacity, speed, diversity, quality, etc. (Algorithm 1 applied).

Then, it is a step of goods processing (S3300). At this time, source data can be processed and commercialized through null elimination, sum, average, minimum value, maximum value, variance analysis, time series analysis, current analysis, comparative analysis, diagnosis analysis, optimization analysis, have.

The following is the product extraction (S3400) and the value determination step (S3500). Weights can be applied to each processing method used in the process of commercialization of analytical data, and the weights of all the processing methods used can be summed up and applied. In addition, it is possible to judge the value of source data according to classification criteria, that is, capacity, speed diversity, and quality, similar to the value judgment of source data (Algorithm 2 applied).

Then, it is the purchase step (S3600) of the analysis data. Data buyers can select and purchase a variety of data through a data trading platform.

Finally, step S3700 is to distribute revenue to the source data provider. When the original data uploaded by the data provider is traded and revenue is generated, the revenue is distributed to the original data provider. Here, the distribution amount can be calculated in consideration of the labor cost, system operation cost, management cost, data processing degree, etc. input into the merchandising process.

Referring to FIG. 4, the data transaction service providing server 300 can process big data based on the Hadoob Big data platform, using a mashup platform and an analysis platform.

The data transaction service providing method of FIGS. 2 to 4 is not described in the description of FIG. 1, because it can be easily deduced from the same or explained contents of the data transaction service providing method. Omit it.

5 is a flowchart illustrating a method of providing a data transaction service according to an embodiment of the present invention.

Referring to FIG. 5, the data transaction service providing server receives original data from the data providing terminal (S5100).

Then, the data transaction service providing server can perform the source value judgment based on the value judgment algorithm including the size, speed, diversity and quality of the uploaded source data (S5200).

In addition, the data transaction service providing server may process the source data as a commodity by weighting at least one parameter (S5300).

Then, the data transaction service providing server makes a product value determination based on a value judgment algorithm based on a value judgment algorithm for the processed goods (S5400).

Then, the data transaction service providing server, when the purchase of at least one data purchasing terminal occurs by uploading the goods for which the commodity value determination is completed, intermediates the transaction (S5500).

Finally, when the purchase is made and the profit is generated, the profit is distributed / paid to the data provider (S5600).

The data transaction service providing method of FIG. 5, which is not described above, can be easily deduced from the same or described contents of the data transaction service providing method described above with reference to FIGS. 1 to 4, Omit it.

The method of providing a data transaction service according to the embodiment described with reference to FIG. 5 may also be implemented in the form of a recording medium including instructions executable by a computer, such as an application executed by a computer or a program module. Computer readable media can be any available media that can be accessed by a computer and includes both volatile and nonvolatile media, removable and non-removable media. In addition, the computer-readable medium may include both computer storage media and communication media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Communication media typically includes any information delivery media, including computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave, or other transport mechanism.

The method of providing a data transaction service according to an embodiment of the present invention may be executed by an application installed in a terminal (which may include a program included in a platform or an operating system basically installed in the terminal) (I.e., a program) directly installed on a master terminal by a user via an application providing server such as an application store server, an application, or a web server associated with the service. In this regard, the method of providing a data transaction service according to an embodiment of the present invention described above is implemented as an application installed in a terminal or directly installed by a user (i.e., a program) and a computer- Can be recorded on the medium.

It will be understood by those skilled in the art that the foregoing description of the present invention is for illustrative purposes only and that those of ordinary skill in the art can readily understand that various changes and modifications may be made without departing from the spirit or essential characteristics of the present invention. will be. It is therefore to be understood that the above-described embodiments are illustrative in all aspects and not restrictive. For example, each component described as a single entity may be distributed and implemented, and components described as being distributed may also be implemented in a combined form.

The scope of the present invention is defined by the appended claims rather than the detailed description and all changes or modifications derived from the meaning and scope of the claims and their equivalents are to be construed as being included within the scope of the present invention do.

Claims (9)

A method for providing revenue distribution and data transaction service according to the provision of source data executed in a data transaction service providing server,
Receiving original data from a data providing terminal;
Performing a source value judgment on the uploaded source data based on a value determination algorithm including data size, speed, diversity and quality;
Processing the source data by weighting at least one parameter as a commodity;
Determining a product value based on a value determination algorithm based on the value determination algorithm for the processed product;
A step of intermediating the transaction when the purchase of the at least one data purchasing terminal occurs by uploading the commodity having the commodity value determination;
Calculating a predetermined ratio of a difference in value between the source data and the commodity to a commission;
Paying the calculated fee to the data providing terminal;
Lt; / RTI &gt;
Wherein the value determination algorithm is based on size, speed, diversity and quality of the source data,
The size of the source data determines the unit size of the data and the price per cell,
The diversity of the source data is based on the number of columns and the number of the reference columns,
The quality of the source data is based on the management rules of the public data, considering the latestness, accuracy, and interconnectivity, and the more the null, the unit of measurement, the standard code classification, The more metadata is displayed, the higher the degree of duplication or inconsistency of data,
Wherein the step of determining the product value based on the value determination algorithm based on the value determination algorithm for the processed product comprises:
Calculating a demand level of contents included in the product through a keyword and a keyword;
When the content, the number of frames having a similarity degree of the search word and the keyword equal to or larger than a preset value, the size of the source data, and the degree of inclusion of data mapped to the search word and the keyword are high in descending order of the calculated demand level, Steps to increase the value of the product
The method comprising the steps of: providing a source data to a customer;
delete delete The method according to claim 1,
Wherein the at least one parameter comprises:
Wherein the analysis includes at least one of an analysis of variance, a time series analysis, a current analysis, a comparative analysis, a diagnostic analysis,
Wherein when the product is processed, nulls are removed from the source data when a null is present, and the sum, average, minimum value, and maximum value of the data are calculated. Service delivery method.
The method according to claim 1,
In the step of determining the product value based on the value judgment algorithm based on the value judgment algorithm for the processed goods,
Assigning weights to at least one parameter of said at least one parameter when processing said source data into a commodity and summing weights of said at least one parameter to effect reflection on said processing
The method comprising the steps of: providing a source data to a customer;
delete The method according to claim 1,
After the step of intermediating the transaction when the purchase of the at least one data purchasing terminal occurs by uploading the commodity whose judgment of the commodity value has been completed,
Collecting, as big data, a history including a search word of the at least one data purchasing terminal, a buying pattern of the purchaser, and personal information of the purchaser;
Performing data mining on the collected big data based on a customer behavior prediction model;
Extracting a product based on predicted customer behavior prediction data by the data mining;
Transmitting the extracted goods to at least one purchasing terminal having the customer behavior prediction data;
Wherein the method further comprises the step of providing the source data and distributing the data.
8. The method of claim 7,
The data transaction service providing server is based on the Hadob Big Data Platform for processing the big data,
Based distribution analysis and data transaction service using source-based data analysis, which uses a mashup platform for collection, storage and management of multi-channel, multi-format heterogeneous data based on distributed processing, Delivery method.
The method according to claim 1,
Wherein the product is reprocessed and reproduced through a query analysis of the at least one data purchasing terminal.

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