KR20120124524A - Apparatus and Method for Customer Propensity Based Information Service, Cloud Computing Service Apparatus - Google Patents

Abstract

PURPOSE: A customer tendency-based information service device, a method thereof, and a cloud computing service device thereof are provided to supply customized regional information matched with customer tendencies by matching the customer tendencies and regional tendencies with each grid cell and storing the matched tendencies. CONSTITUTION: A grid cell dividing unit(311) divides map information into grid cells having a predetermined size. A regional tendency analyzing unit(313) analyzes information related to a POI(point of interest) in each cell. The regional tendency analyzing unit selects a regional tendency of each cell according to the analysis result. A customer tendency classifying unit(315) classifies a customer tendency of a customer to match the customer tendency with the regional tendency. [Reference numerals] (300) Traffic processing unit; (311) Grid cell dividing unit; (313) Regional tendency analyzing unit; (315) Customer tendency classifying unit; (317) Algorithm performing unit; (318) Information providing unit; (AA) Communication network; (BB) DB

Description

Apparatus and Method for Customer Propensity Based Information Service, Cloud Computing Service Apparatus}

An embodiment of the present invention relates to an information service device and method based on customer preference, and a cloud computing service device. More specifically, each area on the map is divided into grid cells of the appropriate size and shape according to the service characteristics, and the customer's propensity and regional propensity for the service users are matched and stored for each grid cell, so that they can be customized according to the customer's propensity. The present invention relates to an apparatus and method for providing information service based on customer preference and a cloud computing service apparatus.

The contents described in the following sections provide background information related to the embodiments of the present invention, but it does not constitute a prior art.

With the development of communication technologies and services using the Internet and mobile communication, and the evolution of mobile communication terminals such as mobile phones, personal digital assistants (PDAs), notebooks, etc., location-based services (LBS) are one of the areas with high growth potential. It is established as one. Location-based service is a service system that provides various services to users based on location information obtained through a mobile communication network or a global positioning system (GPS), which is connected to a base station or a satellite navigation device to a mobile communication terminal. It is a service that provides various services related to location such as location tracking service, public safety service, location based information service by mounting chip. That is, location-based service is a service that provides various services based on location information obtained through wired and wireless communication networks.

Location-based service essentially links information about the region of the customer's current location. Current location-based service collects information on each region on the map based on a point of interest (POI) and links it with location-based services. It provides a variety of information. Here, the POI may be classified into data displaying major facilities, stations, airports, terminals, hotels, etc. on a digital numerical map with coordinates, search data commonly used for searching for a destination, and background data displayed only on a desktop. If the user knows the information about the destination, that is, the address, telephone number or the exact name of the destination, the destination can be directly searched by directly inputting the data. On the contrary, if the user does not have accurate information about the destination, the final destination may be searched step by step according to genre steps.

However, the conventional POI-based location-based service simply provides information on each point but does not provide information for identifying the characteristics of the region itself. In addition, conventionally, since POI information about a specific point in each region is uniformly provided to all service users, information irrelevant to the propensity of the service user itself is not very useful.

An embodiment of the present invention provides a service that reflects the characteristics of a region based on geographic information as well as simple location of the service user, ie, coordinate information and region information, by utilizing information on a context or tendency of a customer in a location-based service. An object of the present invention is to provide a customer orientation-based information service device and method, and a cloud computing service device.

In addition, to provide customer orientation-based information service devices and methods and cloud computing service devices that can provide services such as predicted or recommended information by selecting based on the propensity of the appropriate region when providing customized location services based on the customer's inclination. There is another purpose.

Customer orientation-based information service device according to an embodiment of the present invention comprises a grid cell separator for dividing the map information into grid cells of a predetermined size; A regional propensity analyzer for analyzing POI related information existing in each grid cell and selecting local propensities of the grid cells according to an analysis result; A customer propensity classification unit for classifying a customer propensity of a customer requesting information on the local propensity using a terminal and matching the local propensity existing for each grid cell; An algorithm performing unit for selecting a grid cell of the information on the local tendency matching the customer tendency when requesting the information related to the local tendency; And an information providing unit providing local terminal-related information to the terminal based on the local tendency defined in the grid cell selected by the algorithm performing unit.

According to an aspect of the present invention, there is provided a cloud computing service apparatus, including: a cloud information processor configured to process an application related information by driving an application to provide a customer orientation based related service to a terminal; An algorithm performing unit for selecting a grid cell of the information on the local tendency matching the customer tendency when requesting the information related to the local tendency from the terminal; And an information providing unit providing local terminal-related information to the terminal based on the local tendency defined in the grid cell selected by the algorithm performing unit.

Customer disposition based information service method according to an embodiment of the present invention comprises the steps of: dividing the map information into grid cells of a predetermined size; Analyzing the POI related information existing in each grid cell and selecting a local tendency of the grid cell according to an analysis result; Classifying customer propensities of customers requesting information on the local propensities using a terminal and matching the local propensities existing for each grid cell; Selecting a grid cell of information about the regional orientation that matches the customer preference when requesting information related to the regional preference; And providing, to the terminal, information on a local tendency based on the local tendency defined in the selected grid cell.

According to an embodiment of the present invention, when providing a location-based service, it is possible to provide a service reflecting the characteristics of an area based on geographic information as well as simple coordinate information and area information. In addition, since the service is provided as a predicted or recommended information based on the propensity of the appropriate region when providing a customized location service based on the customer's situation or propensity information, the regional propensity analysis technology is used for business to consumer (B2C) customers. In addition to personalized location services, it can be used in the B2B (Business to Business) market such as real estate analysis.

1 is a view showing a customer orientation-based customized information providing system according to an embodiment of the present invention,
FIG. 2 is a diagram illustrating a DB structure of the customer tendency based information service device of FIG. 1; FIG.
3 is a diagram illustrating a structure of an information service apparatus based on customer tendency of FIG. 1;
4 is an exemplary diagram of a grid cell divided by the grid cell separator of FIG. 3;
5 is a view showing a customer orientation based information service method according to an embodiment of the present invention;
FIG. 6 is a diagram illustrating a system for providing customized information based on customer tendency under a cloud computing environment according to another embodiment of the present invention; FIG.
FIG. 7 is a diagram illustrating a structure of a cloud computing service device of FIG. 6.

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

1 is a view showing a customer preference based customized information providing system according to an embodiment of the present invention, Figure 2 is a view showing a DB structure of the customer orientation based information service device of FIG. 3 is a diagram illustrating the structure of the customer propensity based service device of FIG. 1, and FIG. 4 is an exemplary diagram of grid cells divided by the grid cell separator of FIG. 3.

As shown in Figures 1 to 4, the customer propensity-based customized information providing system according to an embodiment of the present invention includes a communication network 110 and a customer propensity-based information service device 120, further comprising a terminal 100 It may include.

In an embodiment of the present invention, the terminal 100 can be applied to various wired and wireless environments, and is classified into a personal digital assistant (PDA), a cellular phone, a smartphone, and the like by a communication type, and a personal communication service (PCS) phone that is classified by a communication method. It may include a Global System for Mobile (GSM) phone, a Wideband CDMA (W-CDMA) phone, a CDMA-2000 phone, a Mobile Broadband System (MBS) phone, and the like. Here, the MBS phone is a terminal to be used in the next generation system which is currently discussed. In addition, the terminal 100 may further include a desktop computer, a laptop computer, a netbook and a tablet PC, and even a cloud terminal used under a cloud computing environment.

The terminal 100 may include a wireless communication module and a wireless LAN module, and further include a GPS module. As the wireless communication module is provided, the terminal 100 connects to the communication network 110 to perform a normal voice call or data communication with the other party. In addition, since the terminal 100 includes a wireless LAN module, the terminal 100 may receive various web page data by accessing the communication network 110 through an AP (access point) recognized in the vicinity. Furthermore, the terminal 100 is classified into a GPS terminal and a non-GPS terminal according to whether a GPS module is provided. When the terminal 100 includes a GPS module, the terminal 100 receives data provided through a GPS satellite.

The terminal 100 includes a wireless application protocol (WAP), which is an internet access protocol, a Microsoft Internet Explorer (MIE) based on HTML using an HTTP protocol, a handheld device transport protocol (HDPT), and an NTT. The DoKoMo i-Mode or a specific telecommunication company's wireless Internet connection browser is used to access the Internet via the communication network 110. Among the Internet access protocols used in the terminal 100, MIE uses m-HTML, which is shortened by slightly modifying HTML, and in the case of i-Mode, a language called compact HTML (c-HTML), which is a subset of HTML, is used. do.

Recently, a terminal 100 such as a smartphone uses a browser for wireless Internet access of a specific telecommunication company such as Opera Mini for iPhone to provide a faster wireless Internet, or in close proximity to the terminal 100 in connection with it. Wi-Fi and WiBro networks are also used to provide wireless high-speed Internet.

The communication network 110 includes both wired and wireless communication networks. For example, the communication network 110 may include a base station controller, a base station transmitter and / or a repeater as a wireless communication network. Here, the base station controller serves to relay signals between the base station transmitter and the switching center. The communication network 110 supports both synchronous and asynchronous. Therefore, in case of synchronous (CDMA), the transmitting and receiving base station transmitter will be a base station transmission system (BTS), and in case of asynchronous (WCDMA), the transmitting and receiving base station transmitter will be a base station transmission system (BTS). (Radio Tranceiver Subsystem), the transmitting and receiving base station controller will be a Radio Network Controller (RNC). Of course, the communication network 110 according to an embodiment of the present invention is not limited thereto, and may be used as a connection network of a GSM network and a next generation mobile communication system to be implemented in the future, for example, a cloud computing network under a cloud computing environment. It can be said.

The customer disposition-based information service apparatus 120 divides the map of the nation into grid cell units, and analyzes the disposition of each region for each grid cell as shown in FIG. 2, and stores it in the DB 120a. The customer tendency of the users who use the service is matched with the local tendency and stored in the DB 120a. The customer propensity-based information service device 120 classifies and stores the information consistently to determine the preference region of the customer so that, upon request of the service user, the customer propensity-based information service device 120 can quickly provide customized local information suitable for the customer's preference. do. For example, the customer propensity-based information service device 120 analyzes customer propensity, and if the user is interested in a restaurant or a clothing store, the user of the terminal 100 is located in a restaurant or clothing where a local tendency is shown. Alternatively, clothing-related information may be provided as POI information. Here, the POI represents user's interest information about buildings and shops displayed on the electronic map such as the terminal 100 or navigation. When the service request is made, the terminal 100 may provide a MAC address and information on the surrounding AP or base station, and thus the customer propensity-based information service apparatus 120 may use the information provided by the terminal 100 to provide a local area. It is possible to select a grid cell in which the propensity or customer propensity is defined, and finally, it is possible to provide information suitable for the propensity of the service requester based on the regional propensity information of the selected grid cell.

In order to perform the above function, the customer propensity-based information service apparatus 120 may include a traffic processor 300 and a propensity information processor 310 as shown in FIG. 3. Here, the traffic processing unit 300 may include a control unit and an interface unit, the control unit serves to control the overall information processed in the customer propensity-based information service device 120, the interface unit is a device having different characteristics of each other Functions such as information conversion can be performed so as to interwork. Here, the device having different characteristics may correspond to a POI database for providing POI information to the customer propensity-based information service device 120 as a list or a customer propensity database for providing information on customer propensity. .

The propensity information processor 310 may include a grid cell separator 311, a local propensity analyzer 313, a customer propensity classifier 315, an algorithm performer 317, and an information provider 318.

The grid cell separator 311 divides the map data stored in the DB 120a into arbitrary grid cells as shown in FIG. 4, and may assign IDs to the grid cells. The grid cell may have a square shape such as 100 × 100, 50 × 50, 30 × 30, 25 × 25, 20 × 20, 10 × 10, 5 × 5, and 1 × 1, but embodiments of the present invention According to the service characteristics of the region, grid cells can be configured in various shapes such as triangles, rectangles, pentagons, and circles, and grid sizes can be variously selected. Here, the service characteristics of the region will be described later, but it means that it is an area of convenience such as a restaurant or a shopping area where department stores are concentrated.

The regional tendency analysis unit 313 checks the POI distribution in each grid cell based on the POI database for the grid cells classified by the grid cell separator 311, classifies the POI distribution by category, and classifies each. The propensity for regions in the divided grid cells may be selected using POI-related information such as the number of POIs or polygons, ie, the polygon area occupied by the POI information. For this purpose, although not shown separately in the drawing, the regional propensity analyzer 313 may be linked to the POI database through the traffic processor 300, and the detailed configuration includes a POI distribution checker, a category classifier, and a propensity selector. can do. In conjunction with the POI database, the regional propensity analysis unit 313 may check the ID or coordinates of the grid cells and receive a distribution list of POIs to check the POI distribution. For example, within the selected grid cells, Banpo Woosung Apartment and Banpo Shopping Town You can check the distribution of POIs such as Express Bus Terminal, Gangnam Shopping Center, etc. In addition, through the category classification section, for example, convenience (large category)> restaurant (medium category)> fast food (small category)> burger king or shopping (large category)> large retail store (medium category)> department store (small category)> Lotte Department Store Stepwise information can be classified into categories, for example. Further, in order to select the propensity or representative propensity of the region, the propensity selector determines the number of POI information existing in each grid cell, and corresponds to the POI information having the maximum number of each POI information. The information can be selected as representative propensity information. Alternatively, the characteristic information ratio according to the number of POI information is calculated, and when the characteristic information ratio is greater than or equal to the threshold, the characteristic information having the corresponding characteristic information ratio may be set as representative propensity information. In this case, the characteristic information ratio a` may be expressed as in Equation 1.

[Equation 1]

a` = a / k × 100

Here, a is the number of pieces of POI information, and k is the number of pieces of total POI information.

In relation to Equation 1, the regional propensity analyzer 313 may set, as another example, characteristic information having the corresponding characteristic information ratio as representative propensity information when the characteristic information ratio is greater than or equal to a preset reference ratio. When the deviation value of the highest characteristic information ratio and the lane characteristic information ratio among each characteristic information ratio is greater than or equal to the preset reference ratio, the characteristic information having the highest characteristic information ratio may be set as representative propensity information. When the deviation between the information ratio and the lane characteristic information ratio is smaller than the preset reference ratio, the characteristic information having the highest characteristic information ratio and the characteristic information having the lane characteristic information ratio may be jointly set as representative propensity information. In this case, the regional propensity analyzer 313 may calculate representative propensity information based on information having the same category among characteristic information existing in the grid cell.

In addition, the regional tendency analysis unit 313 according to an embodiment of the present invention may classify POI areas in order to select a representative tendency for each grid cell, and select a representative tendency by calculating an area ratio. For this purpose, the regional propensity analyzer 313 may further include a POI area classifier and an area ratio calculator. In other words, the area propensity analyzer 313 classifies the area of the POI in the grid cell by category through the POI area classifier. That is, the area of the POI included in the same category among the identified POI distributions in the selected grid cell is classified. The ratio of the area of the POI for each category to the total area of the divided grid cells is calculated. In this case, if the area of the selected grid is k and the area of the POI included in the specific category is a, the area ratio (a`) of the POI included in the specific category may be expressed as in Equation (1).

As described above, the region propensity analyzer 313 may select the propensity for the region in the selected grid cell based on the calculated ratio of the area. For example, a category included in the predetermined upper X% among the ratios of the POI area for each category in the selected grid cell is selected as the propensity for the area in the grid cell, and the ratio of the category with the highest ratio in the selected grid cell is selected. When the difference between the ratios of the other categories is greater than or equal to the set POI superiority reference ratio, the category having the highest ratio may be selected as the representative propensity for the region in the selected grid cell.

The customer tendency classification unit 315 may store the related information in the DB 120a by matching the tendency of the user with respect to the user of the terminal 100, that is, the communication service users, and the local tendency. In other words, the customer propensity classification unit 315 performs a task of matching the propensity information of the customer provided in a separate customer propensity database with the local propensity. To this end, the customer propensity classification unit 315 may additionally perform a process of analyzing and classifying the information on the propensity of the customer. If the customer tendency classification unit 315 or the customer propensity database analyzes the usage information or behavior record related to the usage pattern or consumption pattern for the user of the specific terminal 100 or the information provided by the customer when the new subscription of the terminal 100 is performed. Based on the analysis results, if a particular service user had a great interest in real estate, the customer propensity classification unit 315 allows the customer to be matched to a grid cell having a regional propensity. When matching, it is desirable to match each other with respect to a preferred area that the customer is more interested in so that it can be stored in the DB 120a. Here, since a particular customer shows interest in various fields, and the propensity may change depending on the situation or timing of his / her own situation, the customer propensity classification unit 315 may update related information or update the updated information on the customer propensity. It may be provided periodically from the database to match the customer preferences with the local tendencies.

The algorithm execution unit 317 may perform an algorithm that matches, ie, maps, the local tendencies stored for each grid cell and the customer tendencies for the users who use the service to the terminal 100, but the service user requests the service. An algorithm may be performed to identify location information of a service user and to provide customized location information suitable for a customer's inclination based on location information. For example, the algorithm performing unit 317 may implement algorithms that match each other when a service user having a propensity of A prefers a local grid of a and c propensities. When a service user requests a service in a specific area, the algorithm performing unit 317 may implement an algorithm and first select a grid of areas having a and c tendencies as candidate groups. Afterwards, the algorithm performing unit 317 additionally checks AP information or base station information provided when the service is requested among the grid cells of the candidate group, and finally extracts the local tendency of the local grid cells.

The information provider 318 may provide, for example, POI information as service information to the service requester in consideration of the local tendency of the selected grid cell according to the algorithm execution result of the algorithm execution unit 317. For example, if the service user of the terminal 100 showed considerable interest in real estate or food for a particular area of Gangnam, the real estate-related information may be provided as POI information in the area or when passing through the area. In case of passing by, POI information about food is provided to provide information indicating the region or geographical tendency of the region.

Meanwhile, the information provider 318 may provide the service requester with not only POI information as service information but also coordinate information of the grid cell calculated through the customer preference. For example, when a friend A requests a B friend's location in a service such as a friend finder, the customer propensity-based information service device 120 may be based on a friend B's inclination independently or in conjunction with a location device. It may be possible to measure position and give A accurate positioning results.

5 is a view showing a customer disposition-based information service method according to an embodiment of the present invention.

Referring to FIG. 5 together with FIG. 1, the customer propensity-based information service apparatus 120 classifies map information stored in the DB 120a into grid cells of various sizes and shapes according to service characteristics of a region (S501). Here, the service characteristics of the region can be said to distinguish whether the region divided by the grid cell is a living area with many restaurants, fast food stores, etc., or a shopping area with many large retail stores or department stores.

In addition, the customer propensity-based information service apparatus 120 analyzes POI related information on each of the divided grid cells and selects local service characteristics, that is, regional propensities, according to the analysis result (S503). For example, by identifying the number of POI information of a region having a specific grid cell, the large number of POI information is divided into small, medium, and large categories so that regional propensity according to the number of POIs can be selected, Regional trends can be selected based on polygons, or polygonal areas, such as calculating the ratio of the area of POI for each category, such as convenience and shopping, to the total area. In this regard, since it has been described above sufficiently, further description thereof will be omitted.

As described above, when the local propensity is determined for each grid cell, the customer propensity-based information service apparatus 120 classifies the propensities of the customers, matches the local propensities, and stores related information (S505). For example, if it is determined that the area having a particular grid cell has a property-related tendency as a dense area of houses, it is determined to map the propensity of customers interested in the property of the area. Alternatively, if a customer who frequently uses a specific department store in Gangnam determines that shopping is frequent, matching the customer to a local grid cell of Gangnam that has a corresponding regional tendency or by reflecting the customer's propensity in the grid cell The inclination is classified.

Subsequently, when there is a service request from the service user, the customer propensity-based information service apparatus 120 performs a process of selecting an optimal grid cell suitable for the customer propensity based on the location of the corresponding customer (S507). In other words, when a customer as a service user requests a service in a dense area of a house or a shopping mall, the customer propensity-based information service device 120 may provide POI information suitable for the customer's propensity based on the location of the customer. To this end, the customer propensity-based information service apparatus 120 may first select a plurality of grid cells in which a local tendency matched with the propensity of the customer is defined based on the location information provided when the service is requested, as a candidate group. Subsequently, the location information may be additionally considered to implement an algorithm for selecting an optimal lattice cell. If it is not necessary to select a grid cell of a separate candidate group, information on the local tendency of the selected grid cell may be immediately provided.

In addition, the customer propensity-based information service apparatus 120 may provide the local propensity related information to the service requester based on the regional propensity defined in the finally selected grid cell (S509). For example, if the grid cell of the candidate group is selected based on the MAC address, the AP or base station information is additionally used in the candidate cell to select the optimal grid cell according to the customer's preference, and the regional trend defined in the optimal grid cell. It is possible to provide the service requester with information about the PO or POI information related to the local tendency to the service requester.

FIG. 6 is a diagram illustrating a system for providing customized information based on customer tendency under a cloud computing environment according to another exemplary embodiment of the present invention.

As shown in FIG. 6, the customer orientation-based customized information providing system in a cloud computing environment includes a communication network 610 and a cloud computing service device 620, and part or all of the terminal 600 and the cloud provider 630. It may further include.

In this case, the terminal 600 refers to a cloud terminal that performs only basic internet access and basic computing functions by having minimum hardware and software resources applied under a cloud computing environment.

According to another exemplary embodiment of the present invention, the terminal 600 receives a computing resource such as software, such as software, which exists in an intangible form, such as a cloud, for example, from a cloud computing service device 620, and receives related information from a cloud computing service device 620. Process and provide the information back to the cloud computing service device 620 to store and manage the data, or to run the customer orientation based application on the cloud computing service device 620 and the terminal 600 receives only the result. The cloud computing service device 620 stores and manages data.

For example, when the terminal 600 accesses the cloud computing service device 620 using a web browser and receives a list of specific customer propensity-based applications as a kind of service catalog, the terminal 600 selects a specific customer propensity-based application selected from the list. Operation between the terminal 600 and the cloud computing service device 620 may be performed. In this process, the terminal 600 receives and processes the information requested by the cloud computing service device 620, and the cloud computing service device 620 provides the information requested by the terminal 600 and is processed by the terminal 600. Performs a read / write function to receive and store a piece of information again.

The cloud computing service device 620 is a device for storing and managing computing resources such as software existing in an intangible form. For example, the cloud computing service device 620 provides a terminal 600 with a specific customer orientation based application requested by the terminal 600. By receiving and storing the application-related information is processed by processing, or running a specific customer orientation based application in the internal request of the terminal 600, processing the application-related information requested by the terminal 600, and stores the processing result And management. In this process, the cloud computing service device 620 may perform authentication requested by the consumer of the terminal 600, and provide customer propensity information according to the authentication result.

In addition, the cloud computing service device 620 may connect to the cloud provider 630 via the communication network 610 and register a resource provided by the cloud provider 630 using a virtual organization technology. have. This enables developers to quickly develop applications through an application programming interface (API) provided by a service provider, that is, the cloud computing service device 620, without developing a specific customer orientation-based application from the beginning. At 620, the cloud provider 630 is managed. The API here refers to the language or message format used to communicate between the operating system and the application.

The terminal 600, the communication network 610, and the cloud computing service device 620 according to another exemplary embodiment of the present invention except for the above description are the terminal according to the exemplary embodiment of the present invention described with reference to FIGS. 1 and 3. 100, the communication network 110 and the customer propensity-based information service apparatus 120 do not differ from the contents thereof, and the description thereof will be omitted.

FIG. 7 is a diagram illustrating a structure of a cloud computing service device of FIG. 6.

Referring to FIG. 7 along with FIG. 6, the cloud computing service device 620 may include a traffic processor 700 and a cloud computing unit 710. Here, the traffic processing unit 700 may include a controller (not shown) and an interface unit (not shown), which controls the overall signal or data processed by the cloud computing service device 620 and the interface. The unit serves as an interface to interwork with the communication network 610 and the DB 620a. In the process, for example, the interface unit may additionally perform a function such as information conversion.

The cloud computing unit 710 includes an algorithm performing unit 717, an information providing unit 718, and a cloud information processing unit 719, and includes a grid cell separator 711, a regional propensity analyzer 713, and a customer propensity classification. It may further include some or all of the portion 715. The grid cell separator 711, the regional propensity analyzer 713, the customer propensity classifier 715, the algorithm performer 717, the information provider 718, and the cloud information processor 719 may be a traffic processor. 700, more precisely, to process the information under the control of the controller.

The cloud information processor 719 performs a process of registering various applications that the cloud provider 630 rapidly develops through an API provided by the cloud computing service device 620. In this process, the cloud information processing unit 719 may set a rating or determine a price for the application, for example, and generate a list including the rating and the price. Then, when the terminal 600 accesses the cloud computing service device 620 online through a web browser and requests an application for using a specific service, for example, the terminal 600 may provide the list under the control of the traffic processing unit 700. When the terminal 600 requests a specific customer propensity-based application therein, the application-related information requested by the terminal 600 may be processed, and the processing result may be stored and managed.

Other than the above, the grid cell separator 711, the regional propensity analyzer 713, the customer propensity classifier 715, and the algorithm performer of the cloud computing service device 620 according to another exemplary embodiment of the present invention. 717 and the information providing unit 718 include the grid cell separator 311, the local tendency analyzer 313, the customer propensity classifier 315, and the algorithm performer of the propensity information processor 310 described with reference to FIG. 3. 317 and the information providing unit 318 are not significantly different from the description, so the descriptions will be omitted and no further description will be omitted.

In the above description, all elements constituting the embodiments of the present invention are described as being combined or operating in combination, but the present invention is not necessarily limited to the embodiments. That is, all of the components may be selectively combined to operate in one or more within the scope of the present invention, and those skilled in the art to which the present invention pertains may vary without departing from the essential characteristics of the present invention. Modifications and variations will be possible. Therefore, the embodiments disclosed in the present invention are not intended to limit the technical spirit of the present invention but to describe the scope of the technical spirit of the present invention by these embodiments. The scope of protection of the present invention should be construed according to the following claims, and all technical ideas within the scope of the same shall be included in the scope of the present invention.

An embodiment of the present invention relates to an apparatus and method for customer orientation based information service. According to an embodiment of the present invention, when providing a location-based service, it is possible to provide a service reflecting the characteristics of an area based on geographic information as well as simple coordinate information and area information. In addition, since the service is provided as a predicted or recommended information based on the propensity of the appropriate area when providing a customized location service based on the customer's situation or propensity information, the regional propensity analysis technology is not only used for the B2C customer's personalized location service. It can be used in various ways in the B2B market such as real estate analysis.

100, 600: terminal 110, 610: communication network
120, 620: customer disposition based information service device 300, 700: traffic processing unit
310: propensity information processing unit 311, 711: grid cell division unit
313, 713: Regional trend analysis unit 315, 715: Customer propensity classification unit
317, 717: algorithm execution unit 318, 718: information providing unit
710: cloud computing unit 719: cloud information processing unit

Claims (15)

A grid cell separator for dividing map information into grid cells of a predetermined size;
A regional propensity analyzer for analyzing POI information related to each grid cell and selecting local propensity of the grid cells according to an analysis result;
A customer propensity classification unit for classifying a customer propensity of a customer requesting information on the local propensity using a terminal and matching the local propensity existing for each grid cell;
An algorithm performing unit for selecting a grid cell of the information on the local tendency matching the customer tendency when requesting the information related to the local tendency; And
An information providing unit providing local terminal-related information to the terminal based on the local tendency defined in the grid cell selected by the algorithm performing unit;
Customer orientation-based information service device comprising a. The method of claim 1,
The regional propensity analyzer determines the number of POIs present in each of the grid cells as the POI related information, and selects characteristic information corresponding to POI information having the maximum number of the POIs as regional propensity of the grid cells. Customer propensity based information service device. The method of claim 1,
The region propensity analyzer calculates a ratio of each characteristic information according to the number of POI information present in each of the grid cells. Customer orientation-based information service device, characterized in that selected by the propensity. The method of claim 3,
The characteristic information ratio (a`) is a relational expression
a` = a / k × 100
wherein a is the number of pieces of POI information and k is the number of pieces of total POI information. The method of claim 1,
The regional tendency analysis unit,
A POI distribution checking unit for checking a POI distribution existing in the grid cell;
A category classification unit classifying the identified POI distribution by category; And
A propensity selector for selecting a category having a POI distribution ratio equal to or greater than a set reference ratio among the categories classified by the category classification unit as a propensity for a region in the grid cell.
Customer orientation-based information service device comprising a. The method of claim 5,
The customer disposition based information service device,
A POI area classification unit for classifying POI areas in the grid cells by categories; And
Further comprising an area ratio calculation unit for calculating the ratio of the area of the POI for each category to the total area of the grid cell,
And the propensity selecting unit selects the propensity for the area based on the ratio of the area calculated by the area ratio calculating unit. The method of claim 1,
The customer preference classification unit is linked to the customer preference database,
The customer propensity database is a customer propensity-based information service device, characterized in that for analyzing the customer propensity for the customer of the terminal provides the analysis information to the customer propensity classification unit. The method of claim 1,
The algorithm performing unit selects a plurality of lattice cells of information on the local tendency matching the customer tendency as a candidate group, and selects an optimal lattice cell among the grid cells of the candidate group. . The method of claim 1,
And the information providing unit provides POI information related to real estate as the regional propensity related information when it is determined that the regional propensity defined in the grid cell is a real estate region. A cloud information processor configured to process application-related information by driving an application to provide a customer disposition-based related service to a terminal;
An algorithm performing unit for selecting a grid cell of the information on the local tendency matching the customer tendency when requesting the information related to the local tendency from the terminal; And
An information providing unit providing local terminal-related information to the terminal based on the local tendency defined in the grid cell selected by the algorithm performing unit;
Cloud computing service device comprising a. Dividing the map information into grid cells of a predetermined size;
Analyzing point-of-interest (POI) related information existing for each grid cell, and selecting a local tendency of the grid cell according to an analysis result;
Classifying customer propensities of customers requesting information on the local propensities using a terminal and matching the local propensities existing for each grid cell;
Selecting a grid cell of information about the regional orientation that matches the customer preference when requesting information related to the regional preference; And
Providing information regarding a local tendency to the terminal based on the local tendency defined in the selected grid cell;
Customer propensity based information service method comprising a. The method of claim 11,
Selecting the local tendency of the grid cell,
Analyzing the number of POI information existing in each grid cell as the POI-related information, and as a result of analysis, the characteristic information of the POI information having a large number of POI information is selected as the regional propensity of the grid cell. Information service method. The method of claim 11,
Selecting the local tendency of the grid cell,
Analyzing the area of the POI for each category by classifying the POI information present in each grid cell as the POI-related information, wherein the ratio of the area of the POI to the total area of the grid cell is equal to or greater than a reference ratio. Customer orientation-based information service method characterized in that selected by the propensity for the region within the cell. The method of claim 11,
Selecting a grid cell of the information on the local tendency,
Selecting a plurality of grid cells matching the customer tendency as a candidate group; And
Selecting an optimal lattice cell among the lattice cells of the candidate group
Customer propensity based information service method comprising a. 15. The method of claim 14,
The selecting of the optimal grid cell may include at least one of a MAC address of the terminal provided when a request for information related to the local tendency, an access point (AP) for communicating with the terminal, and base station information. A customer propensity-based information service method comprising selecting an optimal grid cell using information.

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