JP2013161293A - System, method, and program for providing real estate evaluation information - Google Patents

Abstract

A real estate evaluation information providing system, a real estate evaluation information providing method, and a real estate evaluation information providing program for providing accurate real estate price evaluation information are provided.
A property management server 20 is connected to a plurality of real estate company terminals 10, and acquires property data of real estate from these to perform centralized management. The property management server 20 is connected to the price index calculation server 30. The price index calculation server 30 acquires the property data of the real estate managed by the property management server 20, and, among the property data of the real estate, the first price index and the second price index for each price category for each region category. calculate. The price index calculation server 30 transmits the first price index and the second price index to the investor terminal 50 connected via the house price index providing server 40.
[Selection] Figure 1

Description

  The present invention relates to a real estate evaluation information providing system, a real estate evaluation information providing method, and a real estate evaluation information providing program for providing real estate evaluation information for evaluating trends in real estate prices.

  Conventionally, a method has been studied in which an average change rate for each region is calculated using a public land price, and a reevaluation of real estate is performed using this average change rate (see, for example, Patent Document 1). In the technology described in this document, the computer calculates the individual fluctuation rate by dividing the price difference calculated using the previous land price data by the previous published land price or the standard land price, and the published land within the specific area. Or, calculate the average of the individual fluctuation rates of the reference location The computer calculates the current price of the target property by multiplying the price of the target property by the average rate of change of the specific area to which the target property belongs.

Japanese Patent Laying-Open No. 2003-331031 (first page, FIG. 4)

  However, when the rate of change calculated using the official land price is used as in the above document, the standard public land price is not frequently published (for example, once a year), so a timely evaluation of real estate price trends It was difficult to do.

  The present invention has been made to solve the above problems, and provides a real estate evaluation information providing system, a real estate evaluation information providing method, and a real estate evaluation information providing program for providing accurate real estate price evaluation information. There is.

  In order to solve the above-mentioned problems, the invention according to claim 1 is a property data storage unit that stores property information about a property subject to real estate transaction, a real estate company system that registers the property information, A real estate evaluation information providing system comprising a control unit connected to an investor terminal that provides real estate evaluation information, wherein the control unit obtains property information about a real estate transaction target from the real estate company system And means for recording in the property data storage unit, means for extracting property information in the evaluation target area from the property data storage unit, and the offer price in the evaluation target region using the offer price included in the property information. The gist is provided with a price index calculating means for calculating a real estate evaluation index and a means for providing the real estate evaluation index to an investor terminal.

  According to a second aspect of the present invention, in the real estate evaluation information providing system according to the first aspect, the property information includes an address of a property subject to real estate transaction, and the control unit includes the property information. If the address is determined to be the same property, the information processing apparatus further includes a unit for performing a name identification process to be combined into one property, and the price index calculation unit uses the property information for which the name identification process has been performed, to evaluate the real estate The gist is to calculate the index.

  The invention according to claim 3 is the real estate evaluation information providing system according to claim 1 or 2, wherein the control unit uses a regression equation having an item value included in the property information as an explanatory variable, and the regression equation. The model value to be substituted into the evaluation function calculated by using is stored, and the price index calculation means calculates the evaluation function by performing a multiple regression analysis of the offer price on the explanatory variables included in the property information. Then, the gist is to calculate the real estate evaluation index by introducing the model value of the model case to the evaluation function.

  According to a fourth aspect of the present invention, in the real estate evaluation information providing system according to any one of the first to third aspects, the price index calculating means identifies a special property based on property information of an evaluation target area. The gist is to calculate the real estate evaluation index by weighting the special property.

  The invention according to claim 5 is a property data storage unit storing property information about a property subject to real estate transaction, a real estate company system in which the property information is registered, and an investor terminal that provides property evaluation information A real estate evaluation information providing system including a control unit connected to the real estate evaluation information, the real estate evaluation information being provided by the control unit from the real estate company system. The property information of the property, and recording the property information in the property data storage unit; extracting the property information of the evaluation target area from the property data storage unit; and using the offer price included in the property information A summary is provided with a price index calculation stage for calculating a real estate evaluation index of a local offer price and a stage of providing the real estate evaluation index to an investor terminal.

  The invention according to claim 6 is a property data storage unit that stores property information about a property subject to real estate transaction, a real estate company system that registers the property information, and an investor terminal that provides property evaluation information A program for providing the real estate evaluation information using a real estate evaluation information providing system having a control unit connected to the control unit, wherein the control unit is connected to the real estate company system from the real estate company system. Using the offer price included in the property information, the means for acquiring property information of the property and recording the property information in the property data storage unit, extracting the property information of the evaluation target region from the property data storage unit, Summary of the invention is to function as a price index calculating means for calculating a real estate evaluation index of a solicited price and a means for providing the real estate evaluation index to an investor terminal To.

(Function)
According to the first, fifth, or sixth aspect, the control unit acquires the property information about the real estate transaction target from the real estate company system, and records it in the property data storage unit. The control unit extracts the property information of the evaluation target area from the property data storage unit. The control unit calculates a real estate evaluation index of the offer price in the evaluation target area using the offer price included in the property information, and provides the real estate evaluation index to the investor terminal. Thereby, since the property information about the transaction object of the real estate is updated every day, for example, it is possible to provide accurate real estate evaluation information that evaluates the trend of the real estate price with a higher update frequency.

  According to claim 2, when the control unit determines that the property is the same by using the address of the property information, the control unit performs a name identification process for collecting the properties into one property. The control unit calculates a real estate evaluation index using the property information subjected to the name identification process. As a result, in order to acquire a lot of property information, even if properties are acquired from multiple real estate company systems, overlapping properties can be combined into one, providing more accurate property evaluation information can do.

  According to claim 3, the control unit calculates the evaluation function by performing multiple regression analysis of the offer price on the explanatory variable included in the property information. The control unit calculates the real estate evaluation index by introducing the model value of the model case into the evaluation function. Thereby, more accurate real estate evaluation information can be provided for the entire property information in the area.

  According to claim 4, the control unit specifies the special property based on the property information of the evaluation target area, weights the special property, and calculates the real estate evaluation index. Thereby, since the property evaluation index is calculated in consideration of the special circumstances of the property, more accurate property evaluation information can be provided.

  According to the present invention, accurate property price evaluation information can be provided.

The schematic block diagram explaining the structure of the real estate evaluation information provision system of embodiment. It is explanatory drawing for demonstrating the data structure of embodiment, Comprising: (a) is the property data for rent, (b) is the property data for sale, (c) is handling source data, (d) is the house price. Explanatory drawing of index data. It is a flowchart for demonstrating the process sequence of each process of embodiment, Comprising: (a) Real estate evaluation information calculation process, (b) is a house price index calculation process. Explanatory drawing for demonstrating the kind of expensive property, and its determination logic. The flowchart for demonstrating the process sequence of the expensive property evaluation process in the example of a change. Explanatory drawing for demonstrating the kind of expensive property and determination logic in the example of a change.

  Hereinafter, an embodiment embodying the present invention will be described with reference to FIGS. In the present embodiment, a real estate evaluation information providing system that provides information on a house price index calculated for each region using the offer price (a desired rental price or a desired sales price) of a real estate property will be described. Here, as shown in FIG. 1, a price index calculation server 30 as a real estate evaluation information providing system is used. This price index calculation server 30 is connected to the property management server 20 via a network. Further, the property management server 20 is connected to a plurality of real estate company terminals 10 via the Internet. In the present embodiment, the property management server 20 and the real estate company terminal 10 constitute a real estate company system.

  Further, the price index calculation server 30 is connected to the house price index providing server 40. The house price index providing server 40 is connected to the investor terminal 50 via the Internet.

  Each real estate company terminal 10 is a computer terminal used for managing (registering or deleting) information on real estate properties handled by the real estate company. The investor terminal 50 is a computer terminal used by an investor to acquire a house price index. The real estate company terminal 10 and the investor terminal 50 include an input unit and a display unit. The input unit includes a keyboard, a pointing device, and the like, and the display unit includes a display.

  The property management server 20 is a server computer that collectively manages real estate properties handled by each real estate company. For this reason, real estate property information is acquired from the real estate company terminal 10, and the real estate property information is managed. The property management server 20 includes a property data storage unit 22, a property image data storage unit 23, and a handling source data storage unit 24.

  The property data storage unit 22 stores property data regarding real estate handled by the real estate company. In the present embodiment, as shown in FIG. 2, property data 221 for a real estate property to be rented and property data 222 for a real estate property to be bought and sold are stored. These property data 221 and 222 are updated based on information on real estate properties acquired regularly (for example, every day) from the real estate company terminal 10. Specifically, when information on real estate properties managed by each real estate company is acquired, after deleting the property data 221 and 222 recorded so far, the property data 221 corresponding to the acquired real estate property information , 222 are recorded.

  As shown in FIG. 2 (a), the property data 221 for rental property includes property code, property type, land area, floor area, building date, management cost, floor, balcony area, building structure, This includes data on the Tori type, alongside codes, station codes, and walking time. Further, the property data 221 includes data relating to the prefecture name, location name, building name, room number, latitude / longitude, rent, outline, multi-layer occupation, top floor number of building, and handling source identifier.

In the property code data area, data relating to an identifier (property code) for identifying each property for rent is recorded.
In the property type data area, data relating to an identifier (type code) for specifying the type of usage of the property is recorded. In the rental property data 222, the types of residential apartments, residential apartments, business stores, and the like are specified.

  The land area, floor area, date of construction, management cost, location floor, balcony area data area, respectively, the land area, floor area, construction date, management cost, number of floors with this property (Location), data on the area of the balcony is recorded.

  Each data area of the building structure and floor plan type relates to an identifier for specifying the structure of the property (wooden, steel reinforcement, etc.) and an identifier for specifying the floor plan of the property (one room, dining / kitchen, etc.). Data is recorded.

  In the area code data area, station code data area, and walking time data area, an identifier (line code) for identifying the railway line of the nearest station of this property, and for identifying the nearest station of this property, respectively. An identifier (station code) and data relating to the time required for walking from the nearest station to this property are recorded.

In each data area of the prefecture name and the location name, data relating to the name of the prefecture where the property is located and the name of the location are recorded.
In each data area of the building name and room number, data on the name of the building in which the property is stored and the room number of the property are recorded.

In the latitude / longitude data area, data relating to the latitude and longitude of the property is recorded.
In the rent data area, data relating to the desired rent amount of this property is recorded.
In the summary data area, flag data for specifying the summary of the property is recorded. In this embodiment, a flag indicating whether it is a penthouse, a flag indicating whether it is a maisonette type, a flag indicating whether it has a roof balcony, a flag indicating whether it is a corner dwelling unit, a flag indicating whether it has a private garden, wide Data relating to a flag indicating whether or not a span (a layout with a wide frontage) is recorded.

Data related to a flag indicating that the property occupies a plurality of layers (a property occupied by a plurality of layers) is recorded in the multi-layer occupation data area.
In the building top floor data area, when the property is an apartment house, data relating to the floor number of the top floor of the apartment house where the property is located is recorded.
In the handling source identifier data area, data relating to an identifier (handling source identifier) for specifying a real estate company handling the property is recorded.

  In addition, as shown in FIG. 2B, the property data 222 for real estate for sale includes property code, property type, land area, floor area, building date, management cost, floor, balcony area, building structure. , Floor plan type, railway line code, station code, data on walking time are included. Further, the property data 222 includes data relating to the prefecture name, location name, building name, room number, latitude / longitude, sales amount, summary, multi-layer occupation, top floor number of the building, and handling source identifier.

In the property code data area, data relating to an identifier (property code) for specifying each property for sale is recorded.
In the property type data area, data relating to an identifier (type code) for specifying the type of usage of the property is recorded. In the property data 221 for sale, the type of condominium, detached house, part of a building other than a house, all buildings other than a house, land, and the like are specified.

Data similar to the property data 221 of the rental property is recorded in each data area of land area to latitude / longitude.
In the sales amount data area, data relating to the desired sales amount of this property is recorded.
Data similar to the property data 221 of the rental property is recorded in each data area of the summary to the handling source identifier.

  On the other hand, the property image data storage unit 23 stores data relating to images of real estate properties. Each image data is stored in association with a property code and an image identifier. Specifically, image data such as floor plans and overview maps of real estate is stored. This image data is recorded when acquired from the real estate company terminal 10.

  Further, as shown in FIG. 2C, the handling source data storage unit 24 stores handling source data 240 relating to a real estate company handling the property. The handling source data 240 is recorded when a real estate company providing property information is registered. The handling source data 240 includes data concerning a handling source identifier, a company name, an inquiry mail address, a license number, and a location.

  In the handling source identifier data area, data relating to an identifier (handling source identifier) for specifying each real estate company is recorded. The property data (221, 222) and the handling source data 240 are associated with each other through the handling source identifier.

Data relating to the name of the real estate company is recorded in the company name data area.
In the inquiry mail address data area, data relating to a contact address (here, an email address) for making an inquiry to the real estate company is recorded.

In the license number data area, data relating to the license number of the real estate company's residential building business is recorded.
In the location data area, data relating to the location (address) of the real estate company is recorded.

  On the other hand, the price index calculation server 30 is a server computer that calculates a price index as real estate evaluation information. For this reason, the price index calculation server 30 includes a control unit 31, a property data storage unit 32, and a house price index data storage unit 33.

  The control unit 31 includes control means including a CPU, a RAM, a ROM (not shown), and the like, and will be described later (each process at the name identification stage, the evaluation target specifying stage, and the house price index calculation stage). To do. And the control part 31 functions as the name collation means 311, the evaluation object specification means 312, and the house price index calculation means 313 by execution of the real estate evaluation information provision program.

The name collation unit 311 executes a name collation process for collecting the same property into a single property when the same property is registered as a plurality of property data.
The evaluation target specifying unit 312 executes processing for specifying a target for calculating a house price index. For this reason, in the present embodiment, the evaluation target specifying unit 312 holds data related to a special property determination reference value such as an expensive property. For example, a roof balcony determination area for determining a roof balcony property as a relatively expensive property is stored.

  The house price index calculating means 313 executes a process for calculating a house price index for each region and for each price category. For this reason, the house price index calculation means 313 stores data relating to the region classification and the price classification. For example, when calculating the home price index in Tokyo, the entire Tokyo area, Tokyo 23 wards, Tokyo metropolitan area, Hachioji city, Tokyo, Tokyo district, etc. are used as the regional division. As for price classification, in the case of rental, the entire price range is 100,000 yen or less, more than 100,000 to less than 300,000 yen, 300,000 or more, etc. In the case of buying and selling, the entire price range is 30 million. Yen or less, more than 30 million to less than 70 million yen, 70 million yen or more are used.

  The house price index calculating means 313 of the present embodiment calculates a first price index using a median value and a second price index based on hedonic analysis. For this reason, the house price index calculating means 313 stores the first price reference value and the second price reference value for calculating the first price index and the second price index, respectively. As the first and second price reference values, the median of the unit price of square meters calculated on a predetermined reference date and the model price are used, respectively. Further, the house price index calculating means 313 stores a hedonic analysis regression equation for calculating the second price index and a model value for calculating the model price from the regression equation. As the model value, the specification of a house that is a reference for index calculation is used. In the present embodiment, the regression equation for hedonic analysis is a value using item values included in the property data and values calculated from these as explanatory variables. For example, the following equation is used.

ln (P) = a + b.ln (N) + c.Q + d.R + e.S + f.T + g.U +... (1)
Here, P is an explained variable and indicates a solicited price. N is the floor area, Q is the number of months of construction, R is the starting station time, S is the time required for walking, T is the tsubos management fee, U is the floor, and a to g are coefficients. Here, the starting station time is the time from the starting station to the nearest station of the property. The model value is a value of an explanatory variable for an average property. Further, the house price index calculating means 313 includes a starting station time table for specifying the starting station time corresponding to the station code.

  Similarly to the property data storage unit 22, the property data storage unit 32 stores property data 321 about a real estate property to be rented and property data 322 about a real estate property to be bought and sold. The property data 321 and 322 are the same data as the property data 221 and 222, respectively, and are periodically updated based on the property data storage unit 22.

  The house price index data storage unit 33 stores house price index data 330 for real estate evaluation information for each region category and for each price category for each rental and sale. This house price index data 330 is recorded when a real estate information calculation process to be described later is executed. The house price index data 330 includes data related to rental transaction type, region classification, price classification, first price index, and second price index.

In the rental transaction type data area, data for specifying the type of real estate (rental or transaction) is recorded.
In the region division data area and the price division data area, data related to the region division and the price division are recorded, respectively.

  In the first price index data area, data related to the first price index in the rental transaction type, the area classification, and the price classification is recorded. In the present embodiment, this first price index is calculated based on the median square meter unit price of the property price (rental fee or sales amount).

  In the second price index data area, data relating to the second price index in the rental transaction type, area classification, and price classification is recorded. In the present embodiment, the second price index is calculated based on a regression equation and a model value into which a coefficient calculated by a hedonic analysis of a property price (rental or sales amount) is substituted.

  The house price index providing server 40 is a server computer that transmits a house price index in response to a request from the investor terminal 50. The home price index providing server 40 includes a home price index data storage unit 42. The house price index providing server 40 transmits the data recorded in the house price index data storage unit 42 to the investor terminal 50 in response to a request from the investor terminal 50.

  The house price index data storage unit 42 stores house price index data 420 in the same manner as the house price index data storage unit 33. The house price index data 420 is the same data as the house price index data 330 and is periodically updated based on the house price index data storage unit 33.

Next, a processing procedure for real estate information calculation processing performed using the system configured as described above will be described with reference to FIGS.
(Real estate information calculation process)
First, real estate evaluation information calculation processing will be described with reference to FIG. This real estate evaluation information calculation processing is executed periodically (for example, every day). This embodiment demonstrates the case where real estate evaluation information is calculated using the property information about "condominium" of sale object. Since the property evaluation information based on the property to be rented is the same processing as in the case of buying and selling, detailed description is omitted.

  First, the control unit 31 of the price index calculation server 30 executes a property data acquisition process (step S1-1). Specifically, the evaluation target specifying unit 312 of the control unit 31 extracts property data 322 in which a flag indicating “apartment” is recorded in the property type data area in the property data storage unit 32. Further, the evaluation target specifying unit 312 extracts the property data 322 whose location code, exclusive area, management cost, railway line code, station code, walking time, and sales price are not blank from the extracted property data 322. Further, the evaluation target specifying unit 312 calculates the number of building months using the building age and the current date of the extracted property data 322, and extracts the property data 322 of the sale with the building months of “1 to 500” months. . Next, the evaluation target specifying unit 312 calculates the basis management cost by dividing the management cost by the floor area using the extracted property data 322. Then, the evaluation target specifying unit 312 extracts property data 322 having a calculated basis management cost of 1200 yen or less.

  Next, the control unit 31 of the price index calculation server 30 executes a name identification process (step S1-2). Specifically, the name identification unit 311 of the control unit 31 includes the property data 322 having the same address (prefecture name, location name and room number), location floor, floor area, and price among the extracted property data 322 to be sold and sold. Judge whether there is. When the property data 322 having the same information is detected, only one property data 322 is extracted.

  Next, the control unit 31 of the price index calculation server 30 executes an expensive property exclusion process (step S1-3). Specifically, the evaluation target specifying unit 312 of the control unit 31 specifies a relatively expensive property and extracts items other than the property data 322 of this property. In this embodiment, a penthouse property, a maisonette property, a roof balcony property, a corner dwelling property, a property with a private garden, and a wide span property are excluded from the evaluation target as expensive properties. This expensive property determination process will be described later with reference to FIG.

  Next, the control unit 31 of the price index calculation server 30 repeatedly executes the processes of steps S1-4 to S1-6 for each region division range. Here, the control unit 31 sequentially specifies the region classification as the calculation target region.

  Next, the control unit 31 of the price index calculation server 30 executes the property specifying process according to the region classification (step S1-4). Specifically, the evaluation target specifying unit 312 of the control unit 31 specifies the property data 322 including the property address (prefecture name and location name) in the calculation target area.

And the control part 31 of the price index calculation server 30 performs the following processes for every price division range. Here, the control part 31 specifies a price classification sequentially as a calculation object price range.
Here, the control unit 31 of the price index calculation server 30 executes a property specifying process corresponding to the price category (step S1-5). Specifically, the evaluation target specifying unit 312 of the control unit 31 specifies the property data 322 in which the sales amount of the property data 322 in the calculation target region is included in the calculation target price range.

  Next, the control part 31 of the price index calculation server 30 performs a house price index calculation process (step S1-6). Specifically, the house price index calculation means 313 of the control unit 31 executes house price index calculation processing using the property data 322 in the specified calculation target price range. Details of the home price index calculation processing will be described later with reference to FIG.

  Next, the control part 31 of the price index calculation server 30 executes the output process of the house price index (step S1-7). Specifically, the house price index calculating means 313 of the control unit 31 transmits the house price index data 330 recorded in the house price index data storage unit 33 to the house price index providing server 40. In this case, the house price index providing server 40 records the acquired house price index data in the house price index data storage unit 42.

  Thereafter, the investor uses the investor terminal 50 to transmit a request for home price index data to the home price index providing server 40. In response to this request, the house price index providing server 40 acquires the house price index data stored in the house price index data storage unit 42, generates information providing screen data including this, and transmits it to the investor terminal 50. To do. This information provision screen includes information on the house price index for each price category for each district category. And the investor terminal 50 displays the acquired information provision screen on a display.

(Price index calculation process)
Next, the house price index calculation process (step S1-6) described above will be described with reference to FIG.

  First, the control unit 31 of the price index calculation server 30 executes a process for calculating a square meter unit price (step S2-1). Specifically, the house price index calculating means 313 of the control unit 31 calculates the unit price of the floor area of the processing target property by dividing the sales amount of each specified property data 322 by the floor area.

  Next, the control unit 31 of the price index calculation server 30 executes a first price index calculation process (step S2-2). Here, the median of the square meter unit price is calculated first. Specifically, the house price index calculating means 313 of the control unit 31 rearranges the property data 322 of the property to be processed in ascending order of the square meter unit price. When the property data 322 is an odd number, the house price index calculation means 313 specifies the square meter price of the central property data 322 as the median in the arrangement order. On the other hand, when the property data 322 is an even number, the house price index calculation means 313 specifies the average value of the unit prices of the two center property data 322 in the arrangement order as the median. Next, the house price index calculating means 313 calculates the first price index by dividing the specified median value by the first price reference value and multiplying by “100”. Then, the house price index calculating means 313 generates the house price index data 330 and records it in the house price index data storage unit 33. In this case, the house price index calculation means 313 records the rental transaction type, the region classification, the price classification, and the first price index in the house price index data 330.

  Next, the control unit 31 of the price index calculation server 30 executes a hedonic analysis process (step S2-3). Specifically, the house price index calculating means 313 of the control unit 31 specifies the starting station time from the station code of each specified property data 322 using the starting station time table. The house price index calculation means 313 performs a known regression analysis using the floor area of each property, the number of months of construction, the time required for walking, the starting station time, the tsubo management fee, and the floor, and the coefficients a to g of the regression equation are calculated. calculate.

Next, the control unit 31 of the price index calculation server 30 executes the calculation process of the second price index (step S2-4). Specifically, the house price index calculation means 313 of the control unit 31 calculates the model price by substituting the model value into the regression equation in which the calculated coefficients a to g are set. Next, the house price index calculation means 313 calculates the second price index by dividing the calculated model price by the second price reference value and multiplying by “100”. Then, the house price index calculation means 313 additionally records the calculated second price index in the house price index data 330.
Thus, the price index calculation process ends.

(Specific processing of expensive properties)
Next, the expensive property specifying process in the above-described expensive property exclusion process (step S1-3) will be described in detail with reference to FIG.

<Identification of penthouse properties>
Here, the evaluation target specifying unit 312 of the control unit 31 executes a determination process based on the outline penthouse information (step S11). Specifically, the evaluation target specifying unit 312 determines that the property is a penthouse property when a flag indicating a penthouse is recorded in the summary data area of the specified property data 322.

  In addition, the evaluation target specifying unit 312 of the control unit 31 executes a determination process based on the coincidence between the top floor number of the building and the located floor (step S12). Specifically, the evaluation target specifying unit 312 compares the value of the top floor data area of the specified property data 322 with the value of the location floor data area, and if both values match, the penthouse Is determined.

<Maisonette Property>
Here, the evaluation target specifying unit 312 of the control unit 31 executes a determination process based on the outline maisonette information (step S21). Specifically, the evaluation target specifying unit 312 determines that the object is a maisonette property when a flag indicating a maisonette is recorded in the summary data area of the identified property data 322.

  Further, the evaluation target specifying unit 312 of the control unit 31 executes a determination process based on the occupation information of a plurality of layers (Step S22). Specifically, the evaluation target specifying unit 312 determines that the property is a maisonette property when a flag indicating that the property is a multi-tier occupation property is recorded in the multi-tier occupation data area of the identified property data 322.

<Roof balcony property>
The evaluation target specifying unit 312 of the control unit 31 executes determination processing based on the summary roof balcony information (step S31). Specifically, when the flag indicating the roof balcony is recorded in the summary data area of the specified property data 322, the evaluation target specifying unit 312 determines that the property is a roof balcony property.

  Further, the evaluation target specifying unit 312 of the control unit 31 executes a determination process based on the balcony area (step S32). Specifically, when the value recorded in the balcony area data area of the property data 322 is equal to or larger than the roof balcony determination area, the evaluation target specifying unit 312 determines that the property is a roof balcony property.

<Square unit properties>
Here, the evaluation target specifying unit 312 of the control unit 31 executes a determination process based on the outline corner dwelling unit information (step S41). Specifically, the evaluation target specifying unit 312 determines that the property is a corner dwelling property when a flag indicating that it is a corner dwelling unit is recorded in the summary data area of the identified property data 322.

  Further, the evaluation target specifying unit 312 of the control unit 31 executes a determination process based on the room number information whose lower two digits are “01” (step S42). Specifically, when the last two digits of the room number of the specified property data 322 is “01”, the evaluation target specifying unit 312 determines that the property is a corner dwelling unit.

  Furthermore, the evaluation target specifying unit 312 of the control unit 31 executes a determination process based on the building maximum room number information (step S43). Specifically, the evaluation target specifying unit 312 specifies all the properties in the same building as the specified property data 322. Then, the evaluation target specifying unit 312 extracts the last two digits of the room numbers of all the specified properties, and specifies the maximum value of the last two digits as the building maximum room number. The evaluation target specifying unit 312 determines that the building is a corner dwelling unit when the maximum building room number matches the last two digits of the room number.

  Further, the evaluation target specifying unit 312 of the control unit 31 executes a determination process based on the room number information of the other “corner dwelling unit” (step S44). Specifically, the evaluation target specifying unit 312 searches for the property data 322 having the same address as the identified property data 322 address. When the property data 322 of another building with the same address is extracted, the evaluation target specifying unit 312 searches for the property data 322 described as a corner dwelling unit in the summary data area of the extracted property data 322. When the corresponding property data 322 is extracted, the evaluation target specifying unit 312 determines that the property data 322 having the lower two-digit room number that matches the last two digits of the room number of the property data 322 is a corner dwelling property. To do.

<Property with private garden>
The evaluation target specifying unit 312 of the control unit 31 executes a determination process based on the summary dedicated garden information (step S51). Specifically, the evaluation target specifying unit 312 determines that the property is a property with a dedicated garden when a flag indicating that the property is with a dedicated garden is recorded in the summary data area of the specified property data 322.

<Wide span property>
The evaluation target specifying unit 312 of the control unit 31 executes determination processing based on the summary wide span information (step S51). Specifically, the evaluation target specifying unit 312 determines a wide span property when a flag indicating that the property is a wide span property is recorded in the summary data area of the specified property data 322.

According to this embodiment, the following effects can be obtained.
(1) In this embodiment, the control unit 31 of the price index calculation server 30 uses the property data 322 about information on real estate properties handled by the real estate company, and the price index for each price category range for each region category range. The calculation process is executed, and the output process of the house price index is executed (steps S1-6, S1-7). Thereby, since the property information about the object of real estate is updated every day, for example, accurate property evaluation information can be provided with high update frequency.

  (2) In this embodiment, the control unit 31 of the price index calculation server 30 calculates a regression equation coefficient by hedonic analysis in the price index calculation process (step S1-6), and the regression equation in which this coefficient is set. The model value is substituted into to calculate the model price, and the second price index is calculated using this model price. Thereby, more accurate real estate evaluation can be performed on the entire property data belonging to the area division range and the price division range.

  (3) In the present embodiment, the control unit 31 of the price index calculation server 30 extracts only the latest property data 322 when there is property data 322 having the same property address, floor, floor area, and price. As a result, a name identification process to be combined into one property is executed (step S1-2). Thereby, in order to acquire a lot of property information, even if properties are acquired from a plurality of real estate company terminals 10, duplicate properties can be combined into one, so that more accurate property evaluation is performed. be able to.

  (4) In the present embodiment, the control unit 31 of the price index calculation server 30 extracts items other than the property data 322 of the property identified as the overvalued property in the overvalued property exclusion process (step S1-3). As a result, since the house price index is calculated excluding the property that has an expensive element such as the structure, a more accurate real estate evaluation can be performed.

Moreover, you may change the said embodiment as follows.
In the real estate evaluation information calculation process of the above embodiment, the control unit 31 of the price index calculation server 30 executes the expensive property exclusion process (step S1-3). Instead of excluding the overpriced property from the target property data, the house price index may be calculated using a value calculated by weighting the overpriced property according to the type of the property. Here, in the area division range to be calculated, a property that deviates from the overall trend may be specified as a relatively expensive property. Specifically, the control unit 31 stores a determination logic, a determination reference value, and a premium adjustment coefficient in association with the type of the expensive property. Here, the type of expensive property is, for example, a penthouse property to a wide span property. The determination logic is a program for specifying each type. The determination reference value is a reference value for determining that this type of property is an expensive property. The premium adjustment factor is a discount rate (a value equal to or lower than “1”) for the same handling as other properties that are not expensive properties. This premium adjustment coefficient is a value for offsetting a general premium rate specified according to the type, and is used by multiplying the offer price of the expensive property.

Then, in the property evaluation information calculation process, after the property is specified in the property specifying process (step S1-4) according to the region classification, the expensive property evaluation process shown in FIG. 5 is executed.
In this overpriced property evaluation process, first, the control unit 31 of the price index calculation server 30 executes a process for specifying the type of overpriced property (step S3-1). Specifically, the control unit 31 sequentially reads out the stored types of expensive properties. Then, the control unit 31 repeatedly executes the following processing for each read type.

  Next, the control unit 31 of the price index calculation server 30 executes a process for specifying an expensive property (step S3-2). Specifically, the control unit 31 uses the determination logic program corresponding to this type to specify the type of property to be determined.

  Next, the control unit 31 of the price index calculation server 30 executes a calculation process of the ratio of the overvalued property in the evaluation target property (step S3-3). Specifically, the control unit 31 counts the total number of properties that are determined to belong to the calculation target area division range. The control unit 31 counts the number of expensive properties of the type specified in step S3-2. And the control part 31 divides the number of this kind of expensive property by the total number, and calculates the ratio (expensive property ratio) of the ratio property in an evaluation object property.

  Next, the control unit 31 of the price index calculation server 30 executes a determination process as to whether or not the overpriced property ratio is greater than or equal to the determination reference value (step S3-4). Specifically, the control unit 31 compares the calculated premium property ratio with this type of determination reference value.

  When the ratio of the overpriced property is equal to or greater than the determination reference value (in the case of “NO” in step S3-4), the control unit 31 of the price index calculation server 30 determines that the price is high. In this case, the control unit 31 performs the adjustment solicitation price calculation process by multiplying the solicited price of each premium property identified in step S3-2 by this kind of premium adjustment coefficient (step S3-5). . Then, the adjusted offer price is temporarily stored.

  On the other hand, when the ratio of the overpriced property is less than the criterion value (in the case of “YES” in step S3-4), step S3-5 is skipped. The above processing is repeated for all types of expensive properties.

  Thereby, in an area where there are many specific types of overpriced properties, the house price index is calculated using the offer price of the overpriced property as it is, so that it is possible to perform real estate evaluation in consideration of housing conditions in the region. Also, in areas where there are few specific types of overpriced properties, an index is calculated for the offer price of the overpriced property taking into account the overpriced rate according to the type, so real estate evaluation information including the price of overpriced properties Can be provided.

  In the above-described embodiment, the control unit 31 of the price index calculation server 30 executes the expensive property exclusion process (step S1-3). Excluded objects are not limited to expensive properties, but can be applied to special properties with special circumstances (for example, cheap properties). In this case, such a special property can be excluded, or weighting according to the type of the special property can be performed as shown in FIG. It is also possible to use exclusion and weighting together. Thereby, real estate evaluation information can be provided in consideration of special circumstances.

  In the above embodiment, in the expensive property exclusion process (step S1-3), the control unit 31 of the price index calculation server 30 identifies the expensive property based on the flag indicating each property recorded in the summary data area. did. The method for identifying the expensive property is not limited to this. For example, each property may be specified by confirming whether or not a specific keyword is included in the explanatory text in the overview.

  -In the expensive property exclusion process (step S1-3) of the above-described embodiment, the control unit 31 of the price index calculation server 30 identifies a penthouse property to a wide span property as an expensive property. Expensive properties are not limited to these. For example, as shown in FIG. 6, famous properties, tower-type properties, two-unit one-elevator properties, properties with specific management methods, properties with specific rights, properties within a specific range from a station, properties along a popular line, A property etc. may be specified as a relatively expensive property. For this property, the control unit 31 of the price index calculation server 30 makes a determination as follows, for example.

<Famous property>
The control unit 31 of the price index calculation server 30 holds a table storing names (famous building names) of famous buildings. And the control part 31 performs the determination process based on a building name (step S71). Specifically, when the building name of the specified property data 322 matches the famous building name, the control unit 31 specifies a relatively expensive property.

<Tower type property>
The control unit 31 of the price index calculation server 30 executes a determination process based on “the 20th floor or more” of the building top floor (step S72). Specifically, when the value of the building top floor data area of the specified property data 322 is “20” or more, the control unit 31 specifies a tower type property.

<2 units, 1 elevator property>
The outline data area of the property data 322 (222) includes a flag indicating a two-house one elevator property. The control unit 31 of the price index calculation server 30 executes a determination process based on the general two-house one-elevator information (step S73). Specifically, the control unit 31 determines that the house is an elevator house with two houses when a flag indicating a two house and one elevator house is recorded in the summary data area of the article data 322.

<Specific management method properties>
The outline data area of the property data 322 (222) includes a flag indicating 24-hour manned management. Then, the control unit 31 of the price index calculation server 30 executes a determination process based on the summary 24-hour manned management information (step S74). Specifically, when a flag indicating 24-hour manned management is recorded in the summary data area of the property data 322, the control unit 31 determines that the property is a specific management method property.

<Specific rights-related properties>
The property data 322 (222) includes data related to the type of rights to be sold. In the right type data area, when the real estate is a condominium, a flag indicating ownership, ground right, lease right or the like is recorded. And the control part 31 of the price index calculation server 30 performs the determination process based on the rights relation outline (step S75). Specifically, when a flag indicating ownership is recorded in the right type data area of the specified property data 322, the control unit 31 identifies the property as an overpriced property.

<Property within a predetermined range from the station>
The control part 31 has memorize | stored the walk required time determination value (for example, 5 minutes) used as an expensive property. The control unit 31 of the price index calculation server 30 executes determination processing based on the required walking time (step S76). Specifically, when the required walking time of the specified property data 322 is equal to or less than the required walking time determination value, the control unit 31 determines that the property is within a predetermined range from the station.

<Property along the popular line>
The control unit 31 of the price index calculation server 30 holds a table that stores the line codes along popular lines that are expensive. And the control part 31 of the price index calculation server 30 performs a determination process based on a railway line code (step S77). Specifically, when the line code of the specified property data 322 matches the route code of the popular route, the control unit 31 determines that the property is along the specific route.

<Property in popular area>
The control unit 31 of the price index calculation server 30 holds a table storing station codes of popular areas that are expensive. And the control part 31 of the price index calculation server 30 performs a determination process based on a station code (step S78). Specifically, when the station code of the specified property data 322 matches the station code of the popular area, the control unit 31 determines that the property is along a specific rail line.

  In the house price index calculation process (step S1-6) of the above embodiment, the control unit 31 of the price index calculation server 30 uses the first price index using the median and the second price index using the regression equation. Was calculated as property evaluation information. The property evaluation information provided by the price index calculation server 30 is not limited to these, and may be calculated using other statistical values such as standard deviation.

  DESCRIPTION OF SYMBOLS 10 ... Real estate company terminal, 20 ... Property management server, 22, 32 ... Property data storage part, 23 ... Property image data storage part, 24 ... Handling source data storage part, 30 ... Price index calculation server, 31 ... Control part, 33 , 42 ... Housing price index data storage unit, 40 ... Housing price index providing server, 50 ... Investor terminal, 311 ... Name identification means, 312 ... Evaluation object specifying means, 313 ... Housing price index calculating means.

Claims (6)

A property data storage unit that stores property information about properties subject to real estate transactions;
A real estate evaluation information providing system comprising a real estate company system that registers the property information and a control unit connected to an investor terminal that provides real estate evaluation information,
The control unit is
From the real estate company system, acquiring property information about a transaction object of real estate, and recording the property information in the property data storage unit;
Means for extracting property information of the evaluation target area from the property data storage unit;
A price index calculating means for calculating a real estate evaluation index of the offer price in the evaluation target area using the offer price included in the property information;
Means for providing the property evaluation index to an investor terminal;
Real estate evaluation information providing system characterized by comprising The property information includes the address of the property subject to real estate transaction,
When the control unit determines that the property is the same property using the address of the property information, the control unit further includes means for performing a name identification process to be combined into one property,
The real estate evaluation information providing system according to claim 1, wherein the price index calculating means calculates the real estate evaluation index using the property information subjected to the name identification process. The control unit stores a regression equation having the value of an item included in the property information as an explanatory variable, and a model value to be substituted into an evaluation function calculated using the regression equation,
The price index calculating means includes:
Calculate the evaluation function by performing multiple regression analysis of the offer price on the explanatory variables included in the property information,
The real estate evaluation information providing system according to claim 1 or 2, wherein a real estate evaluation index is calculated by introducing a model value of a model case into the evaluation function. The price index calculating means includes:
Based on the property information of the area to be evaluated, identify special properties,
The real estate evaluation information provision system according to any one of claims 1 to 3, wherein the special property is weighted to calculate a real estate evaluation index. A property data storage unit that stores property information about properties subject to real estate transactions;
To provide the real estate evaluation information using a real estate evaluation information providing system including a real estate company system in which the property information is registered and a control unit connected to an investor terminal that provides the real estate evaluation information. The method of
The control unit is
Acquiring property information about the object of real estate transaction from the real estate company system and recording it in the property data storage unit;
Extracting property information of the evaluation target area from the property data storage unit;
A price index calculation stage for calculating a real estate valuation index of the offer price in the evaluation target area using the offer price included in the property information;
Providing the real estate valuation index to an investor terminal;
A method for providing property evaluation information characterized by comprising: A property data storage unit that stores property information about properties subject to real estate transactions;
To provide the real estate evaluation information using a real estate evaluation information providing system including a real estate company system in which the property information is registered and a control unit connected to an investor terminal that provides the real estate evaluation information. The program of
The control unit
Means for acquiring property information about a real estate transaction target from the real estate company system and recording the property information in the property data storage unit;
Means for extracting property information of an evaluation target area from the property data storage unit;
Using the offer price included in the property information to function as a price index calculation means for calculating a real estate evaluation index of the offer price in the evaluation target region, and a means for providing the real estate evaluation index to an investor terminal A featured real estate evaluation information provision program.

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