KR100541625B1 - Method and system for predicting future prices of real estate in wired and wireless internet environment - Google Patents

Abstract

The present invention relates to a method and system for providing a real estate future price prediction service in a wired and wireless Internet environment.

Receives the future price prediction service request signal from the subscriber terminal which can use the wired / wireless internet service, authenticates the subscriber, and uses the corresponding real estate price prediction model corresponding to the region where the real estate is located among one or more built real estate price prediction models. A real estate information providing server which calculates a future price for the selected real estate and provides it to the subscriber terminal; And stores data selected by the subscriber, real estate inventory data by region, detailed data on registered real estate, and one or more evaluation items for calculating the future quote or real estate investment index, and is embedded in the real estate information providing server or externally via a communication network. It provides a method and system for providing a real estate future price prediction service in a wired or wireless Internet environment, characterized in that it comprises a database unit connected to interworking.

According to the present invention, the user can know not only past and present prices but also future prices for desired real estate, thereby making it possible to make a reasonable investment in real estate.

Future price forecast service, SPSS, regression, real estate price prediction model, investment index

Description

Method and System for Providing Future Price Estimation Service of Real Estate by Using the Internet}

1 is a block diagram schematically illustrating a system for providing a real estate future price prediction service according to a preferred embodiment of the present invention;

2 is a block diagram showing a detailed configuration for each function of the real estate information providing server and database unit according to an embodiment of the present invention;

3 is an initial screen of a real estate future price prediction service according to an embodiment of the present invention;

4A and 4B are exemplary screens showing various result screens provided by a future price prediction service according to an embodiment of the present invention;

5a to 5c are exemplary screens showing various result screens provided by future quotes and comparative analysis service according to an embodiment of the present invention,

6 is a flowchart illustrating a process of providing a real estate future price prediction service according to an embodiment of the present invention.

<Explanation of symbols for the main parts of the drawings>

100: real estate future price prediction service system 110: subscriber terminal

112: Cellular Phone 114: PD

116: personal computer 120: wired and wireless Internet network

122: mobile communication network 124: Internet

130: real estate information providing server 140: database unit

211: past / present price analysis module 212: future price calculation module

213: moving average line generation module 214: investment index calculation module

215: membership authentication module 216: payment module

221: Subscriber DB 222: Real Estate Listing DB

223: Individual Real Estate Information DB 224: Investment Index DB

The present invention relates to a method and system for providing a real estate future price prediction service in a wired and wireless Internet environment. More specifically, each region's unique property price prediction model applies environmental factors such as housing environment, traffic environment, education environment, complex, and equilibrium to economic fluctuation index, corporate bond interest rate, and real estate sales index. The present invention relates to a method and system for predicting future quotes, price fluctuations, and price fluctuation rates.

Real estate is one of the essential rituals of man's social life, and has changed in various ways with human life. This change in housing culture is being recognized as a high value-added investment target to make money by breaking away from the basic concept of real estate. Therefore, in the sale of real estate, the task of quickly and accurately collecting optimal information must first be performed.

Conventionally, in order to obtain various kinds of information about real estate, consumers have to go directly to a real estate agent to obtain information or through print media such as magazines and newspapers about real estate for sale, radio or TV. However, there is a problem that the method of visiting a real estate agent directly requires a lot of time and effort to obtain desired information, and the method of using print media has limited the amount of real estate information that a consumer can obtain.

In order to solve these problems, with the rapid spread of the Internet environment, a number of real estate-related websites that provide real estate information using the Internet have begun to appear. Real estate websites receive information from off-line real estate agencies or individuals with information on buying, selling, renting, leasing, consulting, etc., and real estate related information such as rights analysis, registration, finance, directors, and interiors. All-in-one service is provided in one-stop.

However, the information provided by real estate websites are currently biased to price information such as public land prices and actual trading prices of apartments, general houses, shopping malls, etc., and sale information such as auction information or alarm information. As a result, customers do not satisfy their needs for various real estate-related information, and as a result, they are unable to make profits due to a low amount of payment to pay the information fee by registering as a paid member.

Therefore, customers who want real estate-related information are in dire need of more specialized and differentiated real-estate contents, and website operators also continue to seek ways to improve customer service satisfaction and generate revenue through differentiated services. Doing.

The present invention devised to meet the above-described needs, the unique real estate prices for each region applying environmental factors such as residential environment, transportation environment, educational environment, complex and equilibrium of real estate to economic fluctuation index, corporate bond interest rate and real estate trading index The purpose of the present invention is to present a method and system for predicting future prices, price fluctuations, price fluctuation rates, etc. of each property according to the prediction model.

To this end, the present invention is a system for providing a real estate future price prediction service through a wired and wireless Internet network, receives a future price prediction service request signal from a subscriber terminal that can use the wired and wireless Internet service to authenticate the subscriber and process payment A real estate information providing server configured to calculate a future price for the selected real estate by using a corresponding real estate price prediction model corresponding to a region where a selected real estate is located among one or more built real estate price prediction models, and provide the same to the subscriber terminal; And store data of the subscriber, real estate inventory data by region, detailed data on registered real estate, and one or more evaluation items for calculating the future price or real estate investment index, and are embedded in the real estate information providing server or through a wired communication network. It provides a real estate future price prediction service providing system in a wired or wireless Internet environment, characterized in that it comprises a database unit connected to and linked from the outside.

In addition, the real estate price prediction model according to the present invention uses a multiple regression analysis and is executed on the SPSS statistical package, the year of occupancy, staircase structure, total households, region, equilibrium, construction companies, economic fluctuation index, corporate bond interest rate and real estate It provides a real estate future price prediction service providing system in a wired or wireless Internet environment, characterized in that performed using one or more prediction factors of the basic prediction factor group consisting of a trading index.

In addition, among the basic predictor groups belonging to the real estate price forecasting model, one or more predictors among various factors influencing the formation of real estate prices such as economic fluctuation index and corporate bond interest rate and real estate trading index fluctuate over time. Therefore, the system provides a real-time future price prediction service providing system through wired / wireless internet environment by reflecting experts, individuals who know the current situation, automation system or statistics using wired / wireless terminals.

According to another object of the present invention is a method for providing a real estate future price prediction service between a real estate information providing server and at least one subscriber terminal connected through a wired or wireless Internet network, comprising: (a) predicting a future price from the connected subscriber terminal; Receiving a service request signal; (b) generating and transmitting a payment screen for the service to perform a payment process of the use price; (c) calculating a future price using a real estate price prediction model corresponding to the number of the selected real estate; And (d) generating a comprehensive price result screen including the calculated real estate future price and transmitting it to the subscriber station.

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

First of all, in adding reference numerals to the components of each drawing, it should be noted that the same reference numerals are used as much as possible even if displayed on different drawings. In addition, in describing the present invention, when it is determined that the detailed description of the related well-known configuration or function may obscure the gist of the present invention, the detailed description thereof will be omitted.

1 is a block diagram schematically showing an entire system for providing a real estate future price prediction service according to a preferred embodiment of the present invention.

Real estate future price prediction service system 100 in a wired or wireless Internet environment according to an embodiment of the present invention provides a large number of subscriber terminal unit 110 is installed web browser program, real estate future price prediction service according to the present invention The real estate information providing server 130, the database unit 140 and the subscriber terminal 110 and the wired and wireless Internet network 120 as a communication network connecting the real estate information providing server 130 is made.

First, in the real estate future price prediction service according to an embodiment of the present invention, the real estate is a building having a roof, walls, and pillars settled on land, and includes a single house, multi-family house, multi-family house, townhouse, apartment building, and the like. It is a comprehensive concept that means all floating assets in contrast to real estate such as land.

The subscriber station 110 is generally a personal computer 116, but may be any communication means as long as data can be transmitted and received and wired / wireless Internet service is available. For example, it may be a cellular phone 112, a personal digital assistant (PDA) 114, a personal communication system (PCS) phone, a hand-held PC, a laptop, etc., which can use a wireless Internet service. have. The subscriber station 110 includes a general modem and a Public Switched Telephone Network (PSTN) network, a cable modem and a cable broadcasting network, a LAN card and a LAN network, an intranet of a LAN card and an enterprise, a mobile communication network interworking with a communication module and a wireless Internet gateway. It can be connected to an external internet network through the Internet.

In addition, the subscriber terminal 110 should be provided with a browser program for transmitting and receiving data with the real estate information providing server 130 using a predetermined protocol. When the subscriber terminal 110 is a personal computer 116, the browser program may be Microsoft's Internet Explorer or Netscape Communicator's Netscape Communicator. In addition, when the subscriber station 110 is a wireless communication device such as a cellular phone 112, PDA 114, etc. may be a WAP (Wireless Application Protocol) browser, ME (Mobile Explorer) browser, etc. It is not limited.

The wired / wireless internet network 120 connecting the real estate information providing server 130 and the subscriber terminal 110 is a computer network capable of transmitting and receiving data, and a wired internet network 124 such as an open Internet and a closed intranet. Alternatively, a wireless Internet network interworking with the mobile communication network 122 may be used. However, any communication network may be used as long as data transmission and reception are possible.

The wired / wireless Internet network 120 of the present invention is a TCP / IP protocol and various services or systems existing in the upper layer, that is, HyperText Transfer Protocol (HTTP), Telnet, File Transfer Protocol (FTP), Domain Name System (DNS), The global open computer network architecture that provides Simple Mail Transfer Protocol (SMTP), Simple Network Management Protocol (SNMP), Network File Service (NFS), and Network Information Service (NIS).

The mobile communication network 122 constituting the wireless Internet network is a conventional network for voice communication between terminals, that is, a base station (BS), a mobile telephone switching office (MTSO), and a home location register (HLR). Location Register) and Network Management System (NMS). It also includes components such as WAP gateways and Packet Data Serving Nodes (PDSNs) that enable the transmission and reception of wireless packet data, so that information related to real estate in the form of HTML, SMTP, XML, HDML, or general files can be provided. It is possible to transmit and receive between the subscriber terminal 110 and the real estate information providing server 130.

Since the subscriber station 110 and the wired / wireless internet network 120 may be implemented using a conventional method as it is or without change, a detailed description thereof will be omitted.

The real estate information providing server 130 according to an exemplary embodiment of the present invention receives a real estate future price prediction request signal for a specific region registered on a webpage from a specific subscriber terminal 110 and calculates a future price of the selected real estate accordingly. By transmitting to the subscriber terminal 110. Here, the real estate is a concept including an apartment, a general house, a residential house, etc., but an apartment that can be easily classified according to the name and the number of sheets will be preferable.

In addition, the real estate information providing server 130 is a web for operating a wired website and / or a wired website for providing real estate information to the subscriber terminal 110 connected to it through the wired and wireless Internet network 120 It would be desirable to be a server. The wired website processes the service subscription, setting, change, and provision through the wired internet network using the personal computer 116, and the wireless website uses the wireless communication terminals 112 and 114. It handles service subscription, setting, change, and provision through the network. To this end, a wired website may include a number of web pages created based on HyperText Markup Language (HTML), and a wireless website may include a plurality of web pages created based on Wireless Markup Language (WML). can do.

On the other hand, the real estate information providing server 130 according to an embodiment of the present invention provides not only the future price of the real estate, but also information such as past prices and current prices and respective graphs. Here, the future price of the real estate is meant to include price information, price fluctuation range, price fluctuation rate information, and the like including the upper limit price, the lower limit price, and the average price of the property after a certain period of time, for example, one year later. In addition, price fluctuation is a figure in which the fluctuation of future real estate prices according to the current real estate prices is expressed in units of dollars, and the price change rate is a percentage (%) of fluctuation of future real estate prices according to current real estate prices. to be.

Meanwhile, the real estate information providing server 130 may calculate and provide a real estate investment index indicating a degree of investment for individual real estate. Here, the real estate investment index indicates the area, number of rooms, number of bathrooms, building structure, heating method, incense, number of parkings per household, complex size, year of construction, facilities, environment, surrounding schools, It is calculated by setting a certain score for each evaluation item such as walking time with subway stations, surrounding area conditions, and price trends. Each valuation item is assigned a higher score for better facilities, so the higher the real estate investment index, the higher the value of investment in the property.

On the other hand, the internal configuration of the real estate information providing server 130 according to a preferred embodiment of the present invention will be described in more detail with reference to FIG.

The database unit 140 is connected to the real estate information providing server 130, the basic information including the personal information of the subscribers to join the real estate information providing server 130, real estate list information by region of each city / ward / district, Stores real estate details, investment index element information, and more. An internal configuration of the database unit 140 according to an embodiment of the present invention will be described in more detail with reference to FIG. 2.

Meanwhile, although FIG. 1 illustrates that the database unit 140 is built outside the real estate information providing server 130 and connected through a predetermined communication network such as a dedicated line or a LAN, the database unit 140 is a real estate information providing server. It may be included in the 130 construction.

2 is a block diagram schematically showing the detailed configuration for each function of the real estate information providing server 130 and the database unit 140 according to an embodiment of the present invention.

The real estate information providing server 130 according to the preferred embodiment of the present invention includes a past / current price analysis module 211 for analyzing past and present real estate prices, a future price analysis module 212 for analyzing future real estate prices, A moving average line generation module 213 for generating a moving average line, an investment index calculation module 214 for calculating a real estate investment index, a member authentication module 215 for authenticating a member, and a payment screen are provided to perform payment for service use. Payment module 216 or the like.

Meanwhile, the database unit 140 may include a subscriber database 221 for storing basic information of the subscriber, a real estate list database 222 for storing real estate lists such as apartments, general houses, and residential houses, and the real estate list database. An individual real estate information database 223 for storing detailed information about the information, an investment index element database 224 for storing a plurality of element item information for determining a real estate investment index, and the like.

Meanwhile, although not shown in FIG. 2, each module 211 ˜ 215 included in the real estate information providing server 130 may use a database management system (DBMS) embedded in the real estate information providing server 130. Data is recorded in each of the databases 221 to 224 of the database unit 140, or the recorded data is read or changed.

The following describes the detailed configuration and function of each module.

The historical / current price analysis module 211 reads the past price history and the current price history for each individual property stored in the individual property information database 223 which will be described later. Create analysis tables, historical / current price graphs, and more.

The historical price analysis table includes information on the highest price for sale, minimum price for sale, maximum price for charter, minimum price for charter, and the record date for each maximum price from the date of occupancy of the property to the current date. The current price analysis table, similar to the previous price table, contains information on the current highest price, lowest price, highest price, and lowest price at the present time, and includes information on the monthly deposit and the monthly rent amount if the monthly rent is set. have.

The historical price change table includes information on the upper and lower monthly sales, lower and upper bounds, and the upper and lower monthly rents, the upper and lower rents and leases from the date of occupancy to the current date. The historical / current price analysis graph shows the change in the average price of real estate sold from the year of residence to the present in the form of a bar graph on a yearly, quarterly and monthly basis.

The future price calculation module 212 receives the selection information input by the user using the subscriber terminal 110 through the wired / wireless internet network 120, and the real estate listing database 222 and the individual real estate information database 223. Read the corresponding data to generate future price forecast table and future price forecast graph.

The future price forecast table includes information on the future price of the property selected by the user, for example, price information including an upper limit price, a lower limit price, and an average price after one year, price fluctuations, and price change rate information. In addition, information on future average prices, future average fluctuations, and future average price fluctuation rates for the real estates of the East, the City, and the City for the region where the user-selected real estate is located are included. The future price forecast graph includes a bar graph that shows the future average price, future future average price, old future average price, and future future average price for the property you selected.

On the other hand, the future price calculation module 212 predicts future prices using a "real estate price prediction model" corresponding to the "City" in which the user-selected real estate is located.

The real estate price prediction model is a unique model according to Seoul, some cities of Gyeonggi-do, and Incheon Metropolitan City, which provide a real estate future price prediction service according to an exemplary embodiment of the present invention. Of course, if more cities provide real estate future price prediction services in the future, a unique model for forecasting real estate prices will be provided.

On the other hand, the real estate price prediction model uses a statistical package called Statistical Package for Social Science (SPSS), which is characterized by easily deriving desired results from simple descriptive statistics to complex multivariate statistical analysis. In addition, we use the given data to identify the functional relationships between variables such as social phenomena or natural phenomena, and regression, an analysis technique that predicts or explains the dependent variable values corresponding to independent variable values using this function relationship. I use it. Here, an independent variable is a variable that affects another variable, and a dependent variable is a variable that is affected by another variable.

Such regression analysis is classified into simple regression analysis which analyzes linear relationship between independent variable and dependent variable when there is one independent variable and multiple regression analysis when there are multiple independent variables. The embodiment of the present invention uses multiple regression analysis that is more widely used than simple regression analysis because it predicts future market prices using various variables. In general, multiple regression analysis is performed using multiple regression equations expressed as Y = a + bX ₁ + cX ₂ + ... Where a, b and c are estimates and X ₁ and X ₂ are independent variables.

On the other hand, each real estate price prediction model used by the future price calculation module 212 is an independent variable in the multiple regression analysis, including the year of occupancy, stair structure, total households, region, equilibrium, construction company, economic fluctuation index, corporate bond interest rate, Real estate sales index and the like. Here, the year of occupancy is divided into units of years, the staircase structure is divided into corridors and terraces, the total number of households is divided into units of 500 households, the area is divided by the average selling price per unit, and the equilibrium is divided into units of 10 pyeong. However, builders can be divided into three stages. In addition, the economic fluctuation index uses the economic fluctuation index announced monthly by the National Statistical Office, and corporate bond interest rate and trading index may be input periodically by the operator or manager of the real estate information providing server 130, but it is information that changes every moment. In consideration of this, it may be desirable to allow the user to input the information at the time of using the real estate future prediction service.

On the other hand, among the independent variables used in the real estate price prediction model, the year of occupancy, stairway structure, total households, region, equilibrium, and construction company have a value of "1" if the real estate meets a predetermined threshold condition. If not, it has a value of "0". For example, in the case of occupancy year, if the condition is set to move in after 1990, it has a value of 0 when moving in before 1990, and has a value of 1 when moving in after 1990. In addition, the staircase structure in the staircase structure = 1, corridor type = 0, 500 generations or more in the total number of households, less than 500 generations = 0, 30 or more equilibrium in equilibrium = less than 30 equilibrium = 0 and the like. Of course, the threshold condition set for each independent variable may be set differently depending on the situation.

The moving average line generation module 213 is a module for generating a moving average line for a moving average line price analysis technique mainly used in securities investment. The moving average line is a line connecting the points that are recognized on the average for the real estate for a period of time as one point per month and connecting the points in a straight line. The moving average line can be used as a basis for determining the point of sale for the property.

According to an embodiment of the present invention, the moving average line generation module 213 reads past sale price information on a specific property stored in the individual property information database 223 for the past 3 months, the past 6 months and the past 12 months from the present time. A moving average line of 3 months, a 6 month moving average line, and a 12 month moving average line are generated. In addition, a quoted average line that connects past sale prices for the property on a monthly basis is generated and displayed along with each moving average line on the moving average line graph.

On the other hand, in the stock price analysis, the case where the short-term moving average line exceeds the long-term moving average line upward from the bottom is called golden cross, and the short-term moving average line crosses the long-term moving average line downward from the top and down the dead cross. Cold Cross is used as a buy signal and Dead Cross is used as a sell signal. Similarly, in the embodiment of the present invention, the point of time when the price average line breaks through each moving average line is a purchase point, and the point of time when the price average line breaks downward is a selling point.

The method of determining when to buy and sell using the moving average line is widely used in the stock investment technique, and thus a detailed description thereof will be omitted.

The investment index calculation module 214 calculates a real estate investment index that numerically expresses the value of the real estate by differentially setting values for some items of the information of the individual real estate stored in the individual real estate information database 223. Perform. That is, the determination index calculation module 214 is the area of the individual real estate information, the number of rooms, the number of bathrooms, stairs structure, heating method, direction, the number of parking per household, the total number of households, building year, amenities, surroundings, surroundings Each property investment index is calculated by assigning scores to items such as schools, distances from nearby subway stations, and surrounding real estate conditions.

For example, the regional area items are set to differentiate scores by group. Gangnam-gu, Seocho-gu, Yongsan-gu, and Songpa-gu are 10 points in 1 group, Gwangjin-gu, Yangcheon-gu, Gwacheon-si are 9 points in 2 groups, and some cities in Gyeonggi-do, Incheon, etc. Is how 5 points are set to 6 groups. The number of rooms is 3 points for 3 rooms, 2 points for 2 rooms, 1 point for 1 room, 3 points for stairs, 2 points for corridor, 3 points for district heating, 2 points for individual heating, center One point of heating, the total number of household items can be set to 6 points for more than 1,000 households, 5 points for 800-999 households, 4 points for 500-799 households, 3 points for 300-499 households, 2 points for less than 300 households, etc. There will be. Of course, the scores assigned to each item described above are just one example, and any number of other scores may be assigned.

Since the real estate investment index is a quantification of items that have a significant influence on the price formation of the real estate, the user can use the real estate investment index and the contents and scores of each evaluation item to use them as data for purchasing the best real estate suitable for them. There will be.

The member authentication module 215 authenticates a user who has registered as a member of the real estate information providing server 130 by using an ID and a password. The payment module 216 provides a payment screen to a member who wants to use a real estate quote service including a real estate future quote according to an embodiment of the present invention, and uses an external financial settlement information (not shown). The payment is processed by sending it to.

The database unit 140 includes a subscriber database 221, a real estate listing database 222, an individual real estate information database 223, an investment index item database 224, and the like.

The subscriber database 221 stores information such as a member ID, a password, a name, a date of birth, a contact phone number, and an address input by a user registered as a member in the real estate information providing server 130.

The real estate listing database 222 stores a list of real estate located in regions such as city, ward, dong and the like, and the past and current prices are classified and stored by equilibrium or real estate name. Here, the historical price held by the real estate listing database 222 is past monthly sale price information for each real estate, and the current price is the current monthly sale upper and lower limits, the charter upper and lower limits, and optional monthly rent information for each real estate. (The monthly rent deposit and the monthly rent amount).

Meanwhile, according to an exemplary embodiment of the present invention, the user may view the historical price information, the current price information, and the real estate detailed information for a certain period on a web screen for free. Here, the predetermined period is set to six months before the current month. On the other hand, when the user wants to view the historical price information or the future price information before a predetermined period of time for a particular property on the web screen, it is provided only when the payment by the payment module 216 is normally processed.

The individual real estate information database 223 stores detailed information about apartments, residential houses, mall houses, and the like, nationwide. Here, the detailed information includes price information including the upper and lower selling prices, the charter upper and lower prices, and optionally included monthly rent information, and the equilibrium detailed information including the number of households by equilibrium, the total floors, the number of rooms / bathrooms, and the total number of living rooms.

In addition, real estate including location, transportation environment, structure, dedicated area, contractor, number of parkings per household, total number of houses, occupancy year, heating method, heating fuel, nearby parks, nearby banks, nearby educational facilities, personal living facilities, etc. It includes detailed information and market price information, including price per sale and market value for the property, including the real estate, the town, town, and city where the property is located. In addition, information on contact information, information on loans for housing funds, information on sales of the equilibrium, chartered goods, and rent items on the equilibrium are stored.

The investment index item database 224 stores a plurality of investment index items described in the above-described investment index calculation module 214 and scores that are differentially set for each item.

The database described above is a relational database management system (RDBMS) such as Oracle, Infomix, Sybase, DB2, or object-oriented database management such as Gemston, Orion, O2, etc. The system (OODBMS) and the XML Native Database such as Excelon, Tamino, Sekaiju, etc. can be implemented for the purposes of the present invention and achieve their functions. It has appropriate fields or elements for it.

In addition, the subscriber database 221, the real estate listing database 222, the individual real estate information database 223, and the investment index item database 224 may be integrated into one database as necessary.

Since the construction and management of the database required for the present invention can be sufficiently performed by those skilled in the art, detailed description thereof will be omitted.

3 is an initial screen of a real estate future price prediction service according to an embodiment of the present invention.

In the initial screen of the web page provided by the real estate information providing server 130, the user selects a real estate future price prediction service menu, and selects a specific regional area (unit of province or province), a specific district, a specific town, and a specific apartment name and equilibrium. 3, the initial screen of the real estate future price prediction service shown in FIG. 3 is displayed on the subscriber terminal 110. Here, if the user has not performed a login (Log-in), a login screen is provided first to perform a login process.

The initial screen of the real estate future price prediction service is composed of a detailed description area of the real estate future price prediction service and a selection area for selecting a future price prediction service item and a future price and comparative analysis service item. Here, the future price prediction service is a service that provides a future price for a selected real estate, while the future price and comparative analysis service is a service that provides a comparison data between two real estate by selecting two real estate.

On the other hand, in each of the selection area of the future price prediction service item and the selection area of the future price and comparative analysis service item, a description of the service contents provided by each service is briefly described. For example, future price forecasting services include current and future price analysis, historical trends in past prices for the past one to six years, past-present-future trend graphs, future price fluctuation rates, future price forecast results, and three-month, six-month and 12-month moving average line graph service. On the other hand, the future quote and comparative analysis service provides all the services provided by the future quote prediction service for the selected two real estate, and additionally provides a comparison of the two real estate for each service item.

4A and 4B are exemplary screens illustrating various result screens provided by a future price prediction service according to an exemplary embodiment of the present invention.

Referring to FIG. 4A, the name and location information of the real estate selected by the user is displayed at the top, and the current price table, the past price table, the past price change trend table, and the past-present-future price trend graph are displayed. Here, the past price change trend of the desired year can be checked by selecting a particular year item from the year items at the bottom of the past price change trend table. In addition, the past-present-future price trend graph shows the bargaining average price from the year of moving in one year to the future point in time. If you select a specific year, the graph shows the quarterly or monthly price trend of the selected year. Can be displayed.

Referring to FIG. 4B, a current and future price graph, a future price prediction result synthesis table, and a moving average line graph are displayed. The current and future price graphs are classified into a current price graph and a future price graph, and bar graphs show the current and future real estate prices and the average selling prices of the east, the west, and the city in which the selected real estate is located. In particular, at the top of each bar graph of the future quote graph, the price change rate of the future quote against the current quote is recorded as a percentage.

The future price forecast result composite table contains the current and future upper, lower and average prices, fluctuations and fluctuation rates for the selected real estate, the current and future average prices, fluctuations and fluctuation rates for the east, the wards and states where the selected real estate is located. Included. The moving average line graph displays moving average lines and quoted average lines for the selected real estate in the past three, six and twelve months from the present time.

5A through 5C are exemplary screens illustrating various result screens provided by future price and comparative analysis services according to an exemplary embodiment of the present invention.

Referring to FIG. 5A, names and location information of two real estates selected by a user are displayed at the top, and a current price table, a past price analysis and comparison table, a past price change trend, and a comparison table are displayed. The items constituting each table are the same as those described with reference to FIG. 4A. However, unlike FIG. 4A, the items constituting each table are different in that the details of two real estates are provided together.

5B shows a present and future price graph and a future price prediction result synthesis table. Since the information recorded in each graph and table displayed in FIG. 5B differs from the screen of FIG. 4B only in that it targets two real estates, detailed descriptions thereof will be omitted.

FIG. 5C is a moving average line graph of two selected real estates. Since the same content is the same as the moving average line graph of FIG. 4B, detailed descriptions thereof will be omitted as in FIG. 5B.

6 is a flowchart illustrating a process of providing a real estate future price prediction service according to an embodiment of the present invention.

The subscriber terminal 110 accesses the real estate information providing server 130 through the wired or wireless Internet network 120 (S600). The subscriber terminal 110 connected to the real estate information providing server 130 receives a login screen and transmits an ID and password input by the user to perform a login operation (S602). Of course, the real estate information providing server 130 may perform a member registration process by providing a member registration screen for the subscriber terminal 110 that is not subscribed. In addition, in the case of a WAP service, such as automatic authentication using the subscriber's telephone number, the login process by inputting such ID and password may be omitted.

The subscriber terminal 110 logging in to the real estate information providing server 130 requests a future price prediction service web page for using the future price prediction service, and requests the future price prediction service web page through the wired / wireless Internet network 120. It is provided (S604). The user of the subscriber terminal 110 selects the name and the equilibrium of a specific real estate to check the future price on the received future price prediction service web page, and transmits a future price prediction service request signal to the real estate information providing server 130. (S606).

The real estate information providing server 130 receiving the future price prediction service request signal transmitted from the subscriber terminal 110 selects a service selection screen for selecting one of a future price prediction service and a future price and comparative analysis service. The mobile station transmits the data to the subscriber station 110 through the wired / wireless internet network 120 (S608). When the user selects a specific service item on the service selection screen, the subscriber terminal 110 generates a service selection signal and transmits the service selection signal to the real estate information providing server 130 and receives the service selection signal. The terminal determines whether the future price prediction service or the future price and comparative analysis service is selected (S610).

If it is determined in step S610 that the quote and comparison analysis service are selected in advance, the real estate information providing server 130 provides the subscriber terminal unit 110 with a comparison target real estate setting screen for setting the conditions of the comparison target real estate. A target real estate selection signal is received (S612). Here, the comparison target real estate setting screen is a second comparison target real estate selection area to be compared with the first comparison target real estate information area consisting of the area information, apartment name and equilibrium information for the real estate selected by the user and the first comparison target real estate information area It is constructed.

In addition, the second comparison target real estate selection area includes a large area (city, metropolitan city and province) selection, a middle region (city, district, and county) selection, a subregion (eup, myeon, and dong) selection, and an apartment name selection. And an equilibrium selection item. In addition, each selection item is activated in the order of Large Area-> Middle Area-> Small Area-> Apartment Name-> Equilibrium. In other words, if a specific large region (Seoul city) is selected, the middle region selection item is activated, if a specific middle region (Gangnam-gu) is selected, the small region selection item is activated, and if a specific small region (Yeoksam-dong) is selected, the apartment selection item is activated. It is.

The real estate information providing server 130 that has received the comparison target real estate selection signal transmits a payment screen for the service to the subscriber terminal (S614). On the other hand, if the real estate information providing server 130 determines that the future price prediction service is selected as a result of the determination in step S610, the process proceeds to step S614 and transmits the payment screen for the service to the subscriber terminal 110.

The payment module 216 of the real estate information providing server 130 receives data related to the payment from the subscriber terminal 110 to process the payment, but determines whether the payment is successful (S616). If the payment is not successful in step S616, the process of the requested service is terminated.

On the other hand, if the real estate information providing server 130 determines that the payment is successful as a result of the determination in step S616, by driving the future price calculation module 212 to calculate the future price for the selected one or two real estate (S618) . Of course, the real estate information providing server 130 may also drive the past / current price analysis module 211 in operation S618 to additionally analyze the past and present prices as well as future prices for the selected real estate.

When the real estate information providing server 130 finishes the calculation of the future quote in step S618, the real estate information providing server 130 generates a comprehensive quote result screen and transmits the result to the subscriber terminal 110 (S620). Here, as described in FIGS. 4A to 5C, the comprehensive price result screen may include various information about current and past prices as well as various information about future prices.

Meanwhile, according to an exemplary embodiment of the present invention, among the various predictors of the real estate price prediction model used by the future price calculation module 212 to predict the future price, the user may directly change the corporate bond interest rate and the trading index. Therefore, it may be possible to add a predictive factor changing screen for changing the corporate bond interest rate and / or trading index between the step S612 and the step S614 of FIG. 6 or before the future price calculation module is driven after the successful payment.

On the other hand, in the embodiment of the present invention is described as an example of the economic change index, corporate bond interest rate and trading index that can be adjusted among the predictive factors used in the real estate price prediction model, any economic indicators affecting the formation of real estate prices It may be included. For example, one or more economic indicators such as CP (Commercial Paper) return, CD (Certificate of Deposit) return, call rate, Treasury bond interest rate, stock price, exchange rate, international rate may be optionally included.

The above description is merely illustrative of the present invention, and those skilled in the art to which the present invention pertains may various modifications without departing from the essential characteristics of the present invention. Accordingly, the embodiments disclosed herein are not intended to limit the present invention but to describe the present invention, and the spirit and scope of the present invention are not limited by these embodiments. It is intended that the scope of the invention be interpreted by the following claims, and that all descriptions within the scope equivalent thereto shall be construed as being included in the scope of the present invention.

 As described above, the conventional real estate information providing websites provided only past and present price information and for sale information. However, according to the present invention, the past and present detailed price information and future price information, such as one year later, for the real estate in a nationwide range according to the present invention. It is possible to provide differentiated services to customers by providing even in detail.

In addition, by providing differentiated, high-quality real estate information services for a fee, the company provides investment guidance to customers in the same region, equilibrium and price range by calculating and providing a reasonable real estate investment index. It also has the advantage.

In addition, by using real estate information accumulated for more than 10 years and high accuracy multiple regression analysis as a technique for predicting future prices, it provides not only reliable future price prediction service but also adjusts corporate bond interest rate and real estate trading index in real time. As it predicts future quotes, it provides a more accurate future quote prediction service.

Claims (22)

As a system for providing real estate future price prediction service through wired and wireless internet network, Receives the future price forecast service request signal from the subscriber terminal that can use the wired / wireless Internet service, authenticates the subscriber, processes the payment, and corresponds to the region where the selected real estate is located among one or more built-in real estate price prediction models. A real estate information providing server which calculates a future price for the selected real estate using a price prediction model and provides it to the subscriber terminal; And Data of the subscriber, real estate inventory data by region, detailed data on registered real estate, and one or more evaluation items for calculating the future quote or real estate investment index, and are stored in the real estate information providing server or externally through a wired communication network. Database unit connected to and linked from Real estate future price prediction service providing system in a wired or wireless Internet environment comprising a. The method of claim 1, The real estate price prediction model uses a multiple regression technique and is executed on a statistical package for social science (SPSS) statistical package. . The method of claim 2, The real estate price prediction model is characterized by using one or more predictors of the basic predictor group consisting of occupancy year, staircase structure, total households, region, equilibrium, construction company, economic fluctuation index, corporate bond interest rate and real estate trading index of the real estate. System for forecasting future prices of real estate in wired and wireless Internet environments. The method of claim 3, wherein The real estate price prediction model is included in the basic predictor group and each additional predictor group consisting of CP (commercial paper) return, CD (Certificate of Deposit) return, call rate, treasury bond interest rate, stock price, exchange rate and international interest rate. A system for predicting real estate future price service in a wired or wireless Internet environment, characterized in that it comprises one or more of the predictors. The method of claim 3, wherein And at least one predictor of the economic fluctuation index, the corporate bond interest rate, and the real estate transaction index according to time. The method of claim 4, wherein The real estate price prediction model is a real-time future price prediction service providing system in a wired / wireless internet environment, characterized in that the specific model for each region including the real estate number. The method of claim 1, The future price is a real-time future price prediction service providing system in a wired or wireless Internet environment, characterized in that the price after a period specified by the user based on the request date requesting the real estate future price prediction service. The method of claim 1, And the real estate information providing server provides a current price and / or a past price to the subscriber station together with the future price for the selected real estate. The method of claim 1, The real estate targeted by the real estate future price prediction service is a building having a roof, walls, and pillars settled on land, and includes one or more buildings of a single house, a multi-family house, a multi-family house, a townhouse, and an apartment. System for forecasting future prices of real estate in wired and wireless Internet environments. According to claim 1, wherein the real estate information providing server A historical / current price analysis module for analyzing and providing past and / or current price information on the selected real estate; A future price calculation module for calculating and providing a future price for the selected real estate; A member authentication module for processing member authentication of the user who requested the future price analysis service; And Payment module for processing the payment of the usage fee for the future price analysis service System for predicting real estate future price service in a wired or wireless Internet environment, characterized in that it comprises one or more of. The method of claim 10, The real estate information providing server is a data used to determine the selling time of the selected real estate, and displays the average recognized selling price for a predetermined period as one point per month and connects the points in a straight line. A real estate future price prediction service providing system of a wired and wireless internet environment, further comprising a moving average line generation module for generating a moving average line. The method according to claim 1 or 10, The real estate information providing server is the area of the real estate, the number of rooms, the number of bathrooms, building structure, heating method, incense, the number of parking spaces per household, complex size, year of construction, amenities, environment, surrounding school, walking time with subway stations, The wired / wireless Internet, characterized in that further comprising an investment index calculation module for calculating the real estate investment index, the sum of the scores corresponding to the one or more evaluation items of the selected real estate of each evaluation item consisting of surrounding conditions and price trends System for forecasting future prices of real estate in the environment. The method of claim 1, The subscriber terminal includes at least one device of a personal computer, a cellular phone, a personal digital assistant, a personal communication system (PCS) phone, a hand-held PC, and a notebook computer. System for predicting real estate future price in a wired or wireless Internet environment, characterized in that. A method for providing a real estate future price prediction service between a real estate information providing server and at least one subscriber terminal connected through a wired or wireless internet network, (a) receiving a future price prediction service request signal from the connected subscriber station; (b) generating and transmitting a payment screen for the service to perform a payment process of the use price; (c) calculating a future price using a real estate price prediction model corresponding to the number of the selected real estate; And (d) generating a comprehensive price result screen including the calculated real estate future price and transmitting it to the subscriber station; Method for providing a real estate future price prediction service in a wired or wireless Internet environment comprising a. The method of claim 14, The real estate information providing server analyzes past, present and future price information for a single real estate with the subscriber terminal accessing it, and selects a future price prediction service and provides past, present and future price information for two real estates. Method for providing a real estate future price prediction service in a wired or wireless Internet environment, characterized by providing a future price web page that includes a future price and a comparison analysis service selection items to provide an analysis and comparison. 15. The method of claim 14, wherein in step (a) When the real estate information providing server receives a future price and comparison analysis service request signal from the subscriber station, the real estate information providing server further provides a step of selecting or inputting information of one comparison target real estate to be compared with the already selected real estate. A method of providing real estate future price prediction service in internet environment. The method of claim 14, wherein in step (b) The real estate information providing server includes an interest rate including a corporate bond interest rate among the items used in the real estate price prediction model before the generation of the payment screen or the operation of calculating the real estate future price after the payment is successfully made. Or a screen for changing a real estate sales index to the subscriber terminal, wherein the real estate future price prediction service is provided in a wired or wireless Internet environment. The method according to claim 14 or 17, And the real estate information providing server calculates the real estate future price by applying a changed interest rate and / or a changed real estate sale index to the real estate price prediction model. The method of claim 14, wherein in step (d) The comprehensive quote result screen includes a current quote table, a past quote table, a trend chart of past quotes, a past-present-future quote trend graph, a present and future quote graph, a future quote forecast result table, and a moving average line graph. Method for providing a real estate future price prediction service in a wired or wireless Internet environment, characterized in that it comprises one or more of. The method of claim 19, The future price forecast result synthesis table includes current and future upper and lower limits, average and average prices of the selected real estate, fluctuation information and fluctuation rate information of prices, and the present and future states of the province, city, and state corresponding to the number of the selected real estate. A method of providing real estate future price prediction service in a wired / wireless Internet environment, characterized in that one or more of the average price, price fluctuation information, and fluctuation rate information are included. The method of claim 19, In the moving average line graph, the moving average line and the price average line of the selected real estate for the past 3 months, 6 months and 12 months from the present time point are shown together. How to Provide. 15. The method of claim 14, wherein in step (a) When the future price and comparative analysis service request signal is received, the comprehensive price result screen includes a current price table, past price analysis and comparison table, past price change trend and comparison table, current and future price graph, and future price forecast result synthesis table. And a moving average line graph for the selected two real estates.

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