KR101868583B1

KR101868583B1 - Method for providing affiliate store recommendation service using bigdata analysis with objective information

Info

Publication number: KR101868583B1
Application number: KR1020170102965A
Authority: KR
Inventors: 박종엽
Original assignee: 박종엽
Priority date: 2017-08-14
Filing date: 2017-08-14
Publication date: 2018-06-19

Abstract

There is provided a merchant recommendation service providing method using objective big data analysis, comprising the steps of: collecting settlement information from at least one user terminal by a user of at least one user terminal using at least one payment means; Collecting information including at least one merchant location and industry type from the terminal and converting the information into a database, extracting merchant information, authorized amount, and user information of at least one user terminal from the collected payment information, A step of mapping and storing user information, authorization amount, and approval number of user terminals for each terminal, extracting user information of a search word and a search terminal when receiving a search word from a search terminal searching at least one merchant terminal, Similar to the user information of the search terminal Aligning the at least one merchant, based on the amount and the number of payments on the at least one user terminal with the user information in the range of includes the step of transmitting a search terminal.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for providing a recommendation service to a merchant using an objective big data analysis,

The present invention relates to a method for providing a merchant recommendation service using an objective big data analysis, and provides a method for providing reliable information when recommending an affiliate shop by analyzing objective data corresponding to sales of the merchant.

With the development of digital technology, various advanced scenarios have been developed for each application service with big data analysis. It has started to be applied in real life, and it has become possible to collect a lot of data physically. As a result, analysis contents and service quality have been improved. Also, in the field of commercial analysis and marketing analysis service, many financial institutions and credit card companies have begun to utilize Big Data technology to enhance commercial analysis and merchant analysis. It is a trend to develop a composite service.

At this time, a method of recommending a merchant using card data is performed by a method using a social network. In this regard, Korean Patent Laid-Open Publication No. 2008-0087273 (published on August 07, 2012) discloses a method in which a customer terminal obtains purchase information from a credit card company server by receiving an approval message from a customer using a credit card A process of providing a customized service by extracting a purchase propensity and a characteristic therefrom, and a process of providing a customized service by extracting a purchase propensity and a characteristic from the customer terminal, The customer's past purchasing information is acquired and the customer's purchase propensity and characteristics are analyzed using the same to search for a merchant similar to the purchasing tendency based on the current position of the customer terminal, And discloses a service for recommending information.

However, when analyzing the taste of the customer terminal is only a prediction, and when an error occurs in refining and classifying the big data, the result is junk data which is distorted and can not provide accurate information, Even if you use unstructured data such as SNS at the time of recommendation, it is not clear that the SNS is being used as an advertisement as well as the fact that it does not accurately reflect the user's taste, and even if a personalized service is provided, If you want to see or receive a service item, it is not suitable at all.

An embodiment of the present invention classifies and databases databases of merchants based on the number and the amount of sales of cards at a merchant's merchandise store. When a merchant searches for merchandise or service merchandise, It is possible to extract franchisees based on objective data that does not include the subject of the user, thereby providing reliability and human self-filtering, It is possible to provide a merchant recommendation service providing method using objective big data analysis. 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.

According to an aspect of the present invention, there is provided a method for managing payment information, the method comprising: collecting payment information from at least one user terminal using at least one payment means by a user of at least one user terminal; Collecting information including at least one merchant's location and industry type from at least one merchant terminal and converting the information into a database, extracting merchant information, an approved amount, and user information of at least one user terminal from the collected payment information A step of mapping and storing the user information of the user terminal, the approval amount and the approval number for each of the at least one merchant terminal, storing the user information of the search terminal and the user information of the search terminal when receiving the search word from the search terminal searching at least one merchant terminal, Extracting the user information of the search terminal, And sorting at least one merchant based on the amount and frequency of payment made by the at least one user terminal having the user information within the similarity range and transmitting the sorted merchant to the search terminal.

According to any one of the above-mentioned objects of the present invention, the merchant is classified and databaseized on the basis of the number of card sales and the amount of money at the merchant's merchant, and when the merchant searches for merchandise or service goods, It is possible to extract the franchisee based on objective data that does not include the subject of the user by feeding back to the searcher by extracting and sorting the franchisees that the similar or the same user generates the most sales and frequently goes, It does not require filtering and it can be a stepping stone that can lead to sales increase of small business owners. It can promote the store effectively through convenient digital promotion and find consumers to inform the right place at the right time. I can play a role as a teacher.

FIG. 1 is a block diagram for explaining a merchant recommendation service providing system using an objective big data analysis according to an embodiment of the present invention.
FIG. 2 is a block diagram illustrating a merchant recommendation service providing server shown in FIG. 1. Referring to FIG.
FIG. 3 is a view for explaining various embodiments in which a merchant recommendation service is implemented according to an embodiment of the present invention.
4 is a diagram illustrating a process in which data is transmitted and received between the respective components included in the merchant recommendation service providing system using the objective big data analysis of FIG. 1 according to an embodiment of the present invention.
5 is a flowchart illustrating a method of providing a merchant recommendation service using objective big data analysis 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 used for mapping or matching the unique number of the terminal or the identification information of the individual, which is the identification data of the terminal . &Lt; / RTI >

In this specification, at least one meaning may be interpreted as singular or plural, and when using at least one term, it may be deleted in duplicate below, Can be interpreted.

In this specification, a card includes both a virtual card and a physical card, and a text message can be interpreted as including all the messages transmitted to the mobile terminal.

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

FIG. 1 is a block diagram for explaining a merchant recommendation service providing system using an objective big data analysis according to an embodiment of the present invention. Referring to FIG. 1, the merchant recommendation service providing system 1 may include a user terminal 100, a merchant recommendation service providing server 300, an affiliate shop terminal 400, and a card issuer server 500. However, since the system 1 for providing the merchant recommendation service using the objective big data analysis of FIG. 1 is only an embodiment of the present invention, 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 user terminal 100 may be connected to the merchant recommendation service providing server 300 through the network 200. The user terminal 100 may be connected to the merchant terminal 400 and the card issuer server 500 through the network 200. [ The merchant recommendation service providing server 300 may be connected to the user terminal 100, the merchant terminal 400, the card issuer server 500, and the search terminal 600 through the network 200. The merchant terminal 400 may be connected to the user terminal 100, the merchant recommendation service providing server 300, and the card issuer server 500 through the network 200. [ The card issuer server 500 may be connected to the user terminal 100, the merchant recommendation service providing server 300, the merchant terminal 400, and the search terminal 600 through the network 200. The search terminal 600 may be connected to the merchant recommendation service providing server 300, the merchant terminal 400 and the card issuer server 500 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. An example of such a network 200 is RF, 3rd Generation Partnership Project (3GPP) Network, an LTE (Long Term Evolution) network, a 5rd Generation Partnership Project (5 GPP) network, a World Interoperability for Microwave Access (WIMAX) network, the Internet, a LAN (Local Area Network) But are not limited to, a Wide Area Network (WAN), a Personal Area Network (PAN), a Bluetooth network, an NFC network, a satellite broadcast network, an analog broadcast network, and a DMB (Digital Multimedia Broadcasting) network.

The user terminal 100 may be a terminal of a user who uses a merchant recommendation service. When receiving a text message for card approval from the card issuer server 500, the user terminal 100 transmits the location where the text message was received, the user's information, and a text message to the merchant recommendation service providing server 300 Or the like. In addition, the user terminal 100 may be a terminal that makes a payment from the merchant terminal 400 using a point or a reserve provided from the merchant recommendation service providing server 300. The user terminal 100 may be a terminal that stores payment means such as an NFC card, an app card, a credit card, or the like. At this time, the user terminal 100 is defined as the user terminal 100 as a role of providing information, but may be defined as the search terminal 600 when defined as a role of searching for information, and vice versa. The operation of the search terminal 600 will be described below.

Here, the user 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 set-top box, a notebook equipped with a web browser (WEB Browser), a desktop, a laptop, and the like. At this time, the user terminal 100 may be implemented as a terminal capable of connecting to a remote server or a terminal through the network 200. The user terminal 100 may be, for example, a wireless communication device with guaranteed portability and mobility, such as a navigation system, a Personal Communication System (PCS), a Global System for Mobile communications (GSM), a Personal Digital Cellular (PDC) Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication) -2000, Code Division Multiple Access (CDMA) -2000, W-Code Division Multiple Access (W-CDMA), Wibro (Wireless Broadband Internet) A handheld based wireless communication device such as a smartphone, a smartpad, a tablet PC, and the like.

The merchant recommendation service providing server 300 may be a server that provides a merchant recommendation service web page, an app page, a program, or an application. The merchant recommendation service providing server 300 may be a server that collects payment approval text messages received from the user terminal 100 and collects and collects user information and text message receiving locations when collecting messages . The merchant recommendation service providing server 300 may be a server that checks the integrity of the data by integrating the information and position of the merchant where the sales occurred, the user's information, the payment amount, etc., and then updates the log with the log of the big data . The merchant recommendation service providing server 300 may be a server that converts big data into quantitative data and classifies and arranges the sales and the number of merchants by merchants. Accordingly, when the search is performed in the search terminal 600, the merchant recommendation service providing server 300 extracts the information of the user who generated the sales with the same conditions as the searcher, To the search terminal 600. In this case, The merchant recommendation service providing server 300 may be a server that periodically updates the merchant terminal 400 to allow the searchers to check the latest information and determine whether to delete the merchant terminal 400.

At this time, the merchant recommendation 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.

The merchant terminal 400 may be a terminal that uploads advertisements or events to the merchant recommendation service providing server 300 at a preset frequency and frequency. When the user terminal 100 desires to use the reserve, the merchant terminal 400 may be a terminal that pays the reserve within a predetermined amount or percentage. In addition, the merchant terminal 400 may be a terminal that provides sales and menu information recorded at the POS to the merchant recommendation service providing server 300. [

Here, the merchant terminal 400 may be implemented as a computer that can access a remote server or terminal through the network 200. Here, the computer may include, for example, a POS, a notebook equipped with a web browser (WEB Browser), a desktop, a laptop, and the like. At this time, the merchant terminal 400 may be implemented as a terminal capable of connecting to a remote server or terminal through the network 200. [ The merchant terminal 400 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) Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication) -2000, Code Division Multiple Access (CDMA) -2000, W-Code Division Multiple Access (W-CDMA), Wibro (Wireless Broadband Internet) A handheld based wireless communication device such as a smartphone, a smartpad, a tablet PC, and the like.

The card issuer server 500 may be a server that transmits a card usage history message to the user terminal 100 when the user terminal 100 has paid the card. At this time, if the card company server 500 is committed to share the card usage history with the merchant recommendation service providing server 300, the merchant server 500 provides the merchant recommendation service providing server 300 with sales history, card usage details, Server.

Here, the card issuer server 500 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 POS, a notebook equipped with a web browser (WEB Browser), a desktop, a laptop, and the like.

The search terminal 600 may be a terminal of a searcher who wants to search for a merchant or receive a recommendation. At this time, the type of the merchant includes a business type that provides goods or service goods, and does not limit the types of merchants. In addition, when the searcher is input, the search terminal 600 may be a terminal that provides the location and information of the searcher in the background mode to the merchant recommendation service providing server 300 together with the searcher. When a user having a condition similar to or identical to the searcher provided by the search terminal 600 is extracted and the franchisee that generates the frequent or frequent sales is extracted from the search terminal 600, . Needless to say, the search terminal 600 may function as the user terminal 100 as described above in the user terminal 100.

Here, the search terminal 600 may be implemented as a computer that can access a remote server or terminal through the network 200. [ Here, the computer may include, for example, a set-top box, a notebook equipped with a web browser (WEB Browser), a desktop, a laptop, and the like. At this time, the search terminal 600 may be implemented as a terminal capable of connecting to a remote server or terminal through the network 200. The search terminal 600 is a wireless communication device that ensures portability 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) Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication) -2000, Code Division Multiple Access (CDMA) -2000, W-Code Division Multiple Access (W-CDMA), Wibro (Wireless Broadband Internet) A handheld based wireless communication device such as a smartphone, a smartpad, a tablet PC, and the like.

FIG. 2 is a block diagram illustrating a merchant recommendation service providing server shown in FIG. 1, and FIG. 3 is a diagram illustrating various embodiments in which a merchant recommendation service is implemented according to an embodiment of the present invention.

2, the merchant recommendation service providing server 300 according to an exemplary embodiment of the present invention includes a collecting unit 310, a database generating unit 320, an extracting unit 330, a storing unit 340, The advertisement management unit 380, and the update unit 390. The advertisement management unit 380 may include an advertisement management unit 350, a pre-study unit 360, a rank management unit 370,

The merchant recommendation service providing server 300 or the other server (not shown) operating in cooperation with the merchant recommendation service providing server 300 according to the embodiment of the present invention may be installed in the user terminal 100, the merchant terminal 400, The user terminal 100, the merchant terminal 400, and the search terminal 600, when transmitting the merchant recommendation service application, the program, the application page, the web page, etc. using the objective big data analysis to the search terminal 600, You can install or open a merchant recommendation service application, program, app page, web page, etc. using objective big data analysis. Also, the service program may be executed in the user terminal 100, the merchant terminal 400, and the search terminal 600 using a script executed in the 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 is performed by connecting the user terminal 100, the merchant recommendation service providing server 300, the merchant terminal 400, the card issuer server 500 and the search terminal 600 to the network 200 Means creating a communication object at the communication contact for communication with the terminal. The merchant recommendation service providing server 300 can exchange data with each other through a communication object.

The collecting unit 310 may collect the payment information from at least one user terminal 100 by using at least one payment means by the user of the at least one user terminal 100. Here, the at least one settlement means may be composed of at least one or at least one combination of tag settlement, app settlement, card settlement or account transfer. In other words, even if the card is not a card, the merchant can use the virtual account, the account transfer, and the like using the QR code settlement or the like, and therefore the settlement means is not limited to the above.

Here, when the user of at least one user terminal 100 collects payment information from at least one user terminal 100 using at least one payment means, the collecting unit 310 may collect at least one user The terminal 100 can collect the collection target message corresponding to the payment information.

Here, the collection object message is generated when an application installed in at least one user terminal 100 registers a message reception receiver in an OS (Operating System) of at least one user terminal 100, and whenever a message reception event occurs, Can be collected by receiving this message.

At this time, the text message received at the user terminal 100 can be collected at the merchant recommendation service providing server 300 based on the card acceptance message. The collecting unit 310 collects the mobile phone number, the merchant name, , A receiving area, a credit card company, a credit card number, or the like, to determine whether the message is a card acceptance message. At this time, it may be a message received from the card company as the reply number of the received text message. Here, invalid text messages may be filtered out, even if they are excluded from the collection target data or collected by the collection unit 310. [

Here, the type of the invalid text message may be as follows, but it is not limited thereto, and it will be obvious that it can be changed according to the embodiment or the embodiment. First, when the reply number is not a card number, that is, a message between individuals may be excluded from the collection object. If the reply number is not the card acceptance message even though it is the card issuer number, for example, the overdue guidance or payment guidance message may be excluded. It may also be the case that the reply number is in the form of a card issuer number or a card acceptance message, for example, when the reply number is modified on the web page and sent as a card issuer approval message. Further, it may be a case where the position of the merchant and the position at the time of receiving a character are regarded as a mismatch and manipulated message.

In addition, sensitive card acceptance messages such as personal information can be collected in a state in which personal information is excluded. For example, a card acceptance message of a franchisee whose personal information is sensitive, such as a hospital, may be stored unmodified with the mobile phone number.

In summary, when collecting unit 310 collects payment information from at least one user terminal 100 using at least one payment means, at least one user terminal 100 collects payment information from the user terminal 100 ) Can request a text message which is an approval message corresponding to the settlement from the settlement entity. At this time, when the place where the text message is received by the user terminal 100 matches the address of the merchant payment by the user, and the text message is an approval message corresponding to the payment, Information can be collected.

In addition, the messages collected can be limited to objective data. In other words, comments and ratings are highly likely to be stolen as ads that impersonate a user's review, and SNS and others are not as reliable as they are using features like advertising as a function of information delivery. Accordingly, in one embodiment of the present invention, the merchant is recommended only by the payment approval message, and the subjective opinion of the consumer is outputted only to the comment, without affecting the ranking selection. However, it does not exclude the addition of subjective opinions.

The database generating unit 320 may collect information from at least one merchant terminal 400 including at least one merchant's location and type of industry to form a database. For example, a merchant may use a business number, a password, a mobile phone number, a wire number, an address, a business type, an item, a permitted mobile phone number (plural), a hash tag, Can be provided.

Here, when collecting information including at least one merchant's location and industry type from at least one merchant terminal 400 and converting the collected information into a database, the database generating unit 320 acquires information from at least one merchant terminal 400, The location and the type of business can be collected and converted into a database. At this time, when at least one merchant is registered in at least one user terminal 100, approval of at least three users may be databaseized and uploaded as a necessary condition. In other words, when a member who is not a business owner wants to register an affiliate, it is possible to register it by obtaining more than 3 approval. It is obvious that the number of members can be increased or decreased without being limited to three members.

The extracting unit 330 can extract the merchant information, the authorized amount, and the user information of at least one user terminal 100 from the collected payment information.

The storage unit 340 may map and store the user information, the authorized amount, and the authorized number of the user terminal 100 for each of the at least one merchant terminal 400. The storage unit 340 stores at least one information of at least one user terminal 100 when at least one user terminal 100 stores user information, authorization amount, and approval frequency for each of the at least one franchise terminal 400 The information collected from the matching employee terminal or the merchant's main terminal can be excluded. For example, sales are manipulated to exclude an abnormal user to be searched from the search terminal 600. At this time, in addition to the above-described embodiments, methods for excluding an abnormal user may vary, and it will be obvious that the present invention is not limited thereto.

The search unit 350 may extract the search word and the user information of the search terminal 600 when receiving the search word from the search terminal 600 searching at least one merchant terminal 400. [

The transmitting unit 360 sorts at least one merchant based on the amount and frequency of payment made by the at least one user terminal 100 having the user information within the degree of similarity with the user information of the search terminal 600, 600). At this time, the transmitting unit 360 sorts and searches at least one merchant based on the amount and frequency of payment made by the at least one user terminal 100 having the user information within the degree of similarity with the user information of the search terminal 600 In the case where the search terminal 600 sets a time period when transmitting to the terminal 600, the at least one franchise point can be sorted and added to the search terminal 600 by adding a condition within the set time period. That is, if the user wants to find a hot restaurant for the last three months, he may limit the user to three months, or manually set the period to limit the data to the data within that period.

The rank management unit 370 maps and stores the user information of the user terminal 100, the approval amount and the approval number for each of at least one merchant terminal 400 in the storage unit 340, And the number of visits for each user terminal 100 in descending order. The rank management unit 370 may select the user terminal 100 ranked in the predetermined ranking for each of the at least one merchant terminal 400. The rank management unit 370 may provide the selected user terminal 100 with a predetermined ratio or a reserve amount of the predetermined amount available in at least one merchant terminal 400. [

The advertisement management unit 380 collects information including at least one merchant's location and industry type from at least one merchant terminal 400 in the database processing unit 320 and converts the database into at least one merchant terminal 400, The selection time and the event information for the selected item. If the event information is a range that satisfies a preset period and a preset number based on the event information log uploaded from at least one merchant terminal 400, the advertisement managing unit 380 may transmit the event to at least one user And allow the terminal 100 to display it.

That is, at least one merchant terminal 400 can guide a member's visit to a store using the service of the present invention by inputting event information for a specific time or specific item. For example, it may be event information such as 20% discount on all items or 20% discount on all items when visiting 7-10 pm on 8/11. In order to reduce the fatigue of members' advertisement event display, For example, an event can be made only once a week, and a fee may be charged at the time of event registration. However, the present invention is not limited thereto and various embodiments may be possible.

The updating unit 390 updates the at least one merchant shop 600 based on the amount and the number of payments made by the at least one user terminal 100 having the user information in the degree of similarity with the user information of the search terminal 600 in the transmitting unit 360. [ And may determine whether to delete information of at least one merchant terminal 400 based on a payment pattern of at least one user terminal 100 after sorting the at least one user terminal 100 to the search terminal 600, 100) at a predetermined period. That is, when the merchant is not currently operating, the operating time is changed, or the business type is changed, if the merchant does not update in real time or in a short cycle, it may happen that the application of the service of the present invention is trusted and visited, This is because the disbelief in the invention of the invention can be a reason for not using it again. Accordingly, in the event that the sales are reduced, the business type is changed, or the business is no longer operated, the update is performed in real time or periodically so as not to inconvenience the user.

In addition, although the merchant recommendation service providing server 300 according to the embodiment of the present invention can provide various information on restaurants (recommend merchants) using the sales information of the card company, If not analyzed, quantitative data alone can lead to errors.

For example, it is not possible to obtain information on a commercial franchise only by an administrative address of a franchisee, and a large franchise that is generated by quantifying the ranking based only on internal information such as the number of sales and amount, or a small- In order to eliminate distortion, the accuracy can be increased by building trade information and comparing it with external information.

First, the merchant recommendation service providing server 300 can use the approval details data to perform statistical analysis of six characteristic factors, such as sex, age, frequency of use, type of purchase commodity, consumption amount, and main purchase time period. Next, based on the address information, the merchant recommendation service providing server 300 can estimate the approximate merchandise centered on the map coordinates of the merchant having the largest number of nearby merchant stores .

Here, the location characteristics can include the population factor of the number of households and the number of the households in the commercial area, which means the concept of the spatial point, and whether there are competitors due to the competition factors. Here, the population factor can be defined as the definition and independent variables in the first commercial area, and the economic factors can be set as independent variables such as the ownership rate of the home ownership, the local tax payment, the local tax payment per person, and the car ownership rate per household. Accessibility factors include consideration of the presence of roads, the presence of subways, and the number of bus routes, and the competition factors include the concept of convenience such as business area, parking lot number, and the number of competitors. At this time, the number of competitors can be considered by considering the mutual influences among each of the competing stores by classifying the competitive stores located in the first data base based on the big data defined by the population factor.

Also, the process of adding the address information of the added merchant in comparison with the external merchandise information to the estimation result, the final merchandise map is derived, and the merchant store list can be retained. In this way, it is possible to save not only the cost but also the fairly accurate information. In the taste ranking information of the list of the merchant merchants constructed in this manner, the score, combined with the external information, A direction for constructing a separate restaurant score by weighting external information such as internal information, customer rating, number of reviews, number of photos uploaded, and number of blog reviews may be added.

Hereinafter, the merchant recommendation service using the objective big data analysis having the above-described configuration will be described with reference to FIG.

3, (a) the user terminal 100 has paid the coffee value through the merchant terminal 400, the credit card company server 500 has transmitted the approval message to the user terminal 100, and the merchant recommendation service It is assumed that the providing server 300 confirms the settlement and confirms the location and the user.

At this time, (b) the merchant recommendation service providing server 300 classifies and stores a user, a sex, a sales amount, and a number for each merchant store, and builds a database, (c) ), The merchant recommendation service providing server 300 generates the sales of the user with the condition of the user = (20) + (female) at the merchant = (Sadang-dong) And transmits the sorted information to the search terminal 600. Accordingly, the searcher can grasp the place where other people who have similar or same conditions as the person himself / herself often live, and can provide services that can be visited with confidence even if they do not inconvenience of reading all the reviews of the restaurant Can be provided.

(d) On the other hand, if it is assumed that the search terminal 600 searches for the price of Korean food of Yangjae-dong (the person who bought the most Korean food in Yangjae Dong most frequently), the merchant recommendation service providing server 300 transmits the Korean- It is possible to sort the users having a large number of sales and the number of users in order and provide them to the search terminal 600. At this time, when one person is selected at the search terminal 600, the merchant recommendation service providing server 300 can grasp and show where the selected person is most frequently and most frequently visited in Yangjae-dong.

(E) Assuming that the user terminal 100 holds the reserve according to the providing of the information or the sales at the merchant, the merchant recommendation service providing server 300 receives the merchandise from the merchant terminal 400 The settlement can be made according to the established contract (predetermined amount, predetermined number of times, predetermined percentage, etc.).

(F) The user terminal 100 updates the payment information to the merchant recommendation service providing server 300 continuously so that searchers can obtain the latest information, and the reliability of the information is increased.

The method of providing the merchant recommendation service using the objective big data analysis of FIGS. 2 and 3 is the same as the description of the method of providing the merchant recommend service using the objective big data analysis, The description will be omitted because it can be easily deduced from the description.

4 is a diagram illustrating a process in which data is transmitted and received between the respective components included in the merchant recommendation service providing system using the objective big data analysis of FIG. 1 according to an embodiment of the present invention. Hereinafter, an example of a process of transmitting and receiving data between the respective components will be described with reference to FIG. 4. However, the present invention is not limited to such an embodiment, It is apparent to those skilled in the art that the process of transmitting and receiving data can be changed.

Referring to FIG. 4, the merchant recommendation service providing server 300 registers an affiliate shop in the merchant terminal 400 (S4100), registers the user information in the user terminal 100, and stores it in a database (S4200 ).

On the other hand, in the case where the payment time of the user terminal 100 occurs, the merchant terminal 400 makes an approval request to the card issuer server 500 (S4400), confirms the information of the user in the card issuer server 500, (S4500), the user terminal 100 receives the approval message (S4600).

At this time, the user terminal 100 transmits the approval message to the merchant recommendation service providing server 300 in the background mode (S4610). The merchant recommendation service providing server 300 transmits the approval message to the merchant recommendation service providing server 300, The sales amount information, and the like are stored for each merchant (S4700), processed into the format data of the big data (S4710), and the processed data is classified into the sales number, the amount, and the payer by the merchant.

The merchant recommendation service providing server 300 searches for an affiliate shop in the search terminal 600 and transmits a search word (S4800). The merchant recommendation service providing server 300 searches for sales of another user having the same or similar conditions as the search word, (S4810).

Then, the merchant recommendation service providing server 300 extracts and arranges merchant points or users (S4830), and transmits them to the search terminal 600 (S4850, S4870).

Here, the user terminal 100 continuously transmits an approval message to the merchant recommendation service providing server 300, and accordingly, the merchant recommendation service providing server 300 updates the status of the merchant (S4910, S4930) For example, if the sales are lost, it may be a way to delete it from the list by declaring a closure.

The order between the above-described steps S4100 to S4930 is only an example, but is not limited thereto. That is, the order among the above-described steps S4100 to S4930 may be mutually varied, and some of the steps may be executed or deleted at the same time.

The method of providing the merchant recommendation service using the objective big data analysis of FIG. 4 is the same as the description of the method of providing the merchant recommendation service using the objective big data analysis described above with reference to FIGS. 1 to 3 The description will be omitted because it can be easily deduced from the description.

5 is a flowchart illustrating a method of providing a merchant recommendation service using objective big data analysis according to an embodiment of the present invention. Referring to FIG. 5, the merchant recommendation service providing server collects payment information from at least one user terminal using at least one payment means by a user of at least one user terminal (S5100).

Then, the merchant recommendation service providing server collects information including at least one merchant location and industry type from at least one merchant terminal (S5200), and acquires merchandise information, an approved amount, and at least one The user information of the user terminal is extracted (S5300).

In addition, the merchant recommendation service providing server maps user information, authorization amount, and approval number of the user terminal to at least one merchant terminal (S5400), and receives the search word from the search terminal searching at least one merchant terminal , The user information of the search term and the search terminal is extracted (S5500).

The merchant recommendation service providing server arranges at least one merchant based on the amount and frequency of payment made by at least one user terminal having user information within the degree of similarity with the user information of the search terminal, and transmits the sorted merchant to the search terminal (S5600 ).

The method of providing the merchant recommendation service using the objective big data analysis of FIG. 5 is the same as the description of the method of providing the merchant recommend service using the objective big data analysis described above with reference to FIGS. 1 to 4 The description will be omitted because it can be easily deduced from the description.

The method of providing the merchant recommendation service using the objective big data analysis according to the embodiment described with reference to FIG. 5 may be performed in the form of a recording medium including an application executed by a computer or a command executable by a computer such as a program module Can be implemented. 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. 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.

The method of providing the merchant recommendation service using the objective big data analysis according to an embodiment of the present invention may include an application installed basically in the terminal (which may include a program included in a platform or an operating system basically installed in the terminal) And may be executed by an application (that is, 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 sense, the method of providing the merchant recommendation service using the objective big data analysis according to the embodiment of the present invention is basically installed in the terminal or implemented as an application (i.e., program) directly installed by the user, And can be recorded on a computer-readable recording 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

A merchant recommendation service providing method executed by a merchant recommendation service providing server,
Collecting payment information from at least one user terminal using at least one payment means by a user of the at least one user terminal;
Collecting information including at least one merchant location and industry type from at least one merchant terminal and converting the information into a database;
Extracting the merchant information, the authorized amount, and the user information of the at least one user terminal from the collected payment information;
Mapping and storing the user information, the authorized amount, and the authorized number of the user terminal for each of the at least one merchant terminal;
Extracting user information of the search term and the search term when receiving the search term from the search terminal searching the at least one merchant terminal; And
Arranging at least one franchisee on the basis of the amount and frequency of payment made by at least one user terminal having user information in a similarity degree range to user information of the search terminal and transmitting the sorted franchisee to the search terminal;
Determining whether to delete information of the at least one merchant terminal based on the payment pattern of the at least one user terminal; And
Updating the payment information of the at least one user terminal to a predetermined period;
Wherein the merchant recommendation service is provided by using an objective big data analysis.

The method according to claim 1,
Wherein the collecting of the payment information, which the user of the at least one user terminal has made using at least one payment means, from the at least one user terminal,
Collecting a collection subject message corresponding to the payment information from the at least one user terminal,
Wherein the collection target message includes at least one of an application installed in the at least one user terminal,
Wherein the message reception receiver is registered in an OS (Operating System) of the at least one user terminal, and the application is collected by receiving the message each time a message reception event occurs, and providing the merchant recommendation service using the objective big data analysis Way.

The method according to claim 1,
Wherein the at least one payment means comprises at least one of at least one of tag payment, app payment, card payment, or account transfer, or a combination of at least one thereof.

The method according to claim 1,
And a step of mapping and storing the user information, the approved amount, and the permitted number of times of the user terminal for each of the at least one merchant terminal,
Arranging the at least one user terminal in descending order based on the sales amount and the number of visits for each of the at least one merchant terminal;
Selecting a user terminal ranked in a predetermined order for each of the at least one merchant terminal;
Providing the selected user terminal with a reserve ratio of a predetermined ratio or a preset amount usable in the at least one merchant terminal;
Wherein the merchant recommendation service further includes objective big data analysis.

The method according to claim 1,
The step of mapping the user information, the authorized amount, and the authorized number of the user terminal for each of the at least one merchant terminal,
If the information of the at least one user terminal coincides with the employee terminal or the merchant terminal of the at least one merchant, excluding the information collected from the matching employee terminal or the merchant terminal;
Wherein the merchant recommendation service is provided by using an objective big data analysis.

The method according to claim 1,
Collecting information including the location and industry type of the at least one merchant point from the at least one merchant terminal,
Collecting information including at least one merchant location and an industry type from the at least one user terminal and converting the information into a database;
Lt; / RTI >
Wherein the at least one merchant is registered in the at least one user terminal and the approval of at least three users is databaseed and uploaded when the at least one merchant is registered in the at least one user terminal.

The method according to claim 1,
Collecting information including at least one merchant's location and industry type from the at least one merchant terminal,
Receiving event information on the selected time and the selected item from the at least one merchant terminal;
Allowing an event to be displayed on the at least one user terminal if the event information is in a range that satisfies a preset period and a predetermined number based on an event information log uploaded from the at least one merchant terminal;
Wherein the merchant recommendation service further includes objective big data analysis.

The method according to claim 1,
Wherein the collecting of the payment information, which the user of the at least one user terminal has made using at least one payment means, from the at least one user terminal,
Requesting a text message, which is an approval message corresponding to the payment, from the payment entity from the user terminal;
Lt; / RTI >
The merchant recommendation service providing server,
Wherein the location where the character message is received at the user terminal matches the address of the merchant that the user has paid,
And collecting, when the text message is the approval message corresponding to the payment, the payment information, using the objective big data analysis.

The method according to claim 1,
Wherein the step of sorting at least one merchant based on the amount and frequency of payment made by the at least one user terminal having user information within the similarity degree range to the user information of the search terminal,
Arranging the at least one franchisee by adding a condition within the set time period to the search terminal when the search terminal sets the period;
Wherein the merchant recommendation service is provided by using an objective big data analysis.

delete