JP2003196369A - Real estate evaluation system and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a reasonable price of a property which a purchaser/a seller desire to purchase/sell. <P>SOLUTION: A real estate retrieval/evaluation system 10 is provided at least with: an area evaluation DB (data base) 28 prepared by every area and for storing data about items regarding accessibility indicating accessibility to a prescribed function in the area; and a real estate evaluation part 18 for specifying the attributes of a specified property to be evaluated and an area to which the property belongs and for estimating the reasonable price of the property according to data regarding a transaction case example including an actual transaction price and the data about the items in the area evaluation data base. <P>COPYRIGHT: (C)2003,JPO

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a system for giving an objective evaluation to a real estate that a buyer wants to buy or a real estate that a seller wants to sell in order to promote matching of supply and demand of real estate. .

[0002]

2. Description of the Related Art In order to find real estate that meets the needs of customers, real estate property search systems have been put into practical use. In this property search system, a user (buyer) inputs a desired railway line, property details, etc., and introduces properties that meet these conditions. This mechanism entrusts the user himself with consideration of area selection and property size.

[0003]

In the conventional property search system, by specifying the area in which the user desires to live, the property in the area is presented together with its attribute (site area) and price. However, since the area in which the user desires to live is an abstract one, it is difficult to find the desired property of the user.

Further, a fixed price is given to the searched property. Originally, the price of a real estate property should be flexibly determined according to the demand / supply balance, the property of the property, and other conditions. However, there is a problem that it is practically impossible for the buyer to judge whether or not the price is eligible.

Similarly, the seller cannot know whether the price he / she wants to sell is appropriate or not. It is hoped that these sellers and buyers will be able to promote matching of real estate supply and demand by knowing more objective prices of properties.

[0006] It is an object of the present invention to provide a system in which a buyer / seller can present a proper price of a property desired to purchase / sell. Further, according to the present invention, a desired property can be provided to the buyer in a timely manner by finding an area where the buyer's own life image can be easily realized based on the lifestyle and intention of the buyer and linking it with the property database. The purpose is to provide a system.

[0007]

SUMMARY OF THE INVENTION An object of the present invention is to evaluate an area evaluation database which stores data of at least items related to accessibility which are generated for each area and which indicate accessibility to a predetermined function of the area. Property / area identification means for identifying the property to be identified and the attribute of the property and the area to which the property belongs, data on a transaction example including the actual transaction price, and data for the item in the area evaluation database And a real estate evaluation means for estimating a proper price of a property based on the above. In a preferred embodiment, it is further provided with area evaluation data generation means for generating the area evaluation data based on various statistical data regarding the area.

[0008] In a more preferred embodiment, the real estate evaluation means uses the data relating to the transaction case as an objective variable,
And, as the factor that forms the land price, the data of the items stored in the area evaluation database, and the data of the attribute of the property are used as explanatory variables by multivariate analysis to determine the significance of the explanatory variables, The land price function is determined based on the significance, and the land price function is used to estimate the proper price. For example, the real estate evaluation means, y is the land price that is an objective variable, a is a constant term, b to d
Is a partial regression coefficient and x is an explanatory variable, 1) y = a + bx ₁ + cx ₂ + dx ₃ + ... 2) Ln (y) = a + bLn (x ₁ ) + cLn
_{(X 2) + dLn (x} 3) + ··· (y = exp (a) × x 1 b × x 2 c × x 3 d × ···) 3) y = a + bLn (x 1) + cLn (x 2 ) + DL
It is desirable to estimate the suitable land price based on any of n (x ₃ ) +.

More preferably, the real estate evaluation means is
It is configured to select the most appropriate formula from the formulas 1) to 3). In a preferred embodiment, the real estate evaluation means has items stored in the area evaluation database based on the result of the multivariate analysis, and
Select a predetermined item and / or attribute from the attributes of the property.

[0010] In another preferred embodiment, there is further provided a property search means for searching a property that is considered to be desired from a property database that stores data related to real estate properties based on the user's wishes, and the searched property Is configured to estimate a fair price for. More preferably, the property search means refers to the area evaluation database based on the lifestyle of the user, searches for an area that matches the user's wish, and the system searches for a property existing in the area. Is configured.

Further, an object of the present invention is a program for estimating a proper price of a real estate property, which specifies the property to be evaluated, and the attribute of the property and the area to which the property belongs. , Data on transaction cases including actual transaction prices, and data on the above items in the area evaluation database that stores at least data on items related to accessibility generated for each area and indicating accessibility to a predetermined function of the area. And a real estate evaluation step of estimating a proper price of a property based on the above. Also achieved by a real estate evaluation program characterized by causing a computer to execute.

The data in the area evaluation database may be generated based on power consumption data or questionnaire data based on a user questionnaire in addition to the above statistical data. For example, the area evaluation data generation means may use the power consumption data to generate data relating to activities such as the activity status of people, the payment status of electricity, the operating status of buildings, and the income status.

More preferably, the area evaluation database includes an accessibility layer including index data indicating convenience of the area, an activity layer including index data indicating activity status of a company in the area, and an index indicating comfort of the area. And an amenity layer containing data. For example, the accessibility layer includes shopping convenience (commercial accessibility), employment convenience (business accessibility), and convenience of receiving public services, and these conveniences range from a certain area to a facility or area having a service function. Accessibility formula: generalization cost =
It may be measured based on travel cost + travel time x time value, and may be quantified together with this and the amount of service function including floor area, number of employees, or sales amount.

[0014] Preferably, the activity layer includes the number of households, business establishments and companies living in the area,
Belonging to the area, data indicating the status of people and companies in the area, indicating whether they are active, what are the attributes of those households, establishments, and companies, and what are the infrastructure conditions in that area? What is the activity status of households, business establishments, companies, etc. Shows the activity status of people and businesses in the area, which indicates what kind of households, business establishments, and businesses have moved in / out in a year. Contains data. Preferably, the amenity layer includes numerical data regarding landscape / view, noise, abundance of nature, community situation, and crime occurrence situation.

The program according to the present invention is recorded in a recording medium, for example. Examples of media include EPROM devices, flash memory devices, flexible disks, hard disks, magnetic tapes, magneto-optical disks,
CD (including CD-ROM and Video-CD), DV
D (DVD-Video, DVD-ROM, DVD-R
(Including AM), ROM cartridge, RAM memory cartridge with battery backup, flash memory cartridge, non-volatile RAM cartridge, etc.

Further, it includes a communication medium such as a wire communication medium such as a telephone line and a wireless communication medium such as a microwave line. The Internet is also included in the communication medium here. What is a medium?
Information (mainly digital data,
A program) is recorded, and a processing device such as a computer or a dedicated processor can be caused to perform a predetermined function. In short, download the program to your computer by some means,
It may be any one that executes a predetermined function.

[0017]

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described below with reference to the accompanying drawings. FIG. 1 is a block diagram showing the configuration of the real estate search / evaluation system according to the present embodiment. As shown in FIG. 1, a real estate search / evaluation system (hereinafter, referred to as “this system” in some cases) 10 generates a variety of data with a processing unit 14 that executes processing of property search and real estate evaluation. ,
The data generation / holding unit 16 holds data. The processing unit 14 is a property search unit (hereinafter, also referred to as “property search application” in some cases) 18 that searches for a desired property, and a real estate evaluation unit (hereinafter, in some cases, “real estate evaluation application”) that evaluates real estate. Also referred to as a) 20.

The data generating / holding unit 16 is the system 1
An area evaluation generation unit 24 that creates an evaluation value for each area, and an original data DB that stores original data for creating evaluation data that consists of evaluation values for each area
26 and area evaluation D for storing the created evaluation data
B28 and various data related to real estate actually traded (for example, transaction price per unit area, site area,
Transaction example D that remembers site shape, surrounding road conditions, etc.)
B30 and.

The original data DB 26 stores various data which will be described later as factors for forming land prices, data based on user questionnaires, and the like. The area evaluation DB 28 includes, for each area described later, an accessibility layer including index data indicating the convenience of the area, an activity layer including index data indicating the activity status of companies in the area, and an index indicating the comfort of the area. Various data regarding each layer of the amenity layer including data is stored. The system 10 also includes an interface (I / I) for controlling data exchange via a network such as the Internet.
F) 22 is provided. For example, I / F22 is We
b interface is provided.

Further, the present system 10 is a property DB 3 which stores properties provided by real estate dealers and intermediaries.
Equipped with 2. The data about the property can be accumulated in the property DB 32 by transmitting the data from the computer of the above-mentioned vendor via the network. The property DB 32 does not need to be installed in the system 10, and may be provided in the system of a real estate dealer or a broker via a network. In this case, the property search unit 20 of the present system 10 may search the DB in the system of the above-mentioned vendor via the network.

Further, the present system is provided with a user needs database (DB) 34 in which the property search by the user and the result thereof, the evaluation result of the searched property, and the like are stored in association with the information for specifying the user. .
The outline of the processing in the real estate search / evaluation system 10 having the above configuration will be described below. A user (customer) who searches for a property and wants to obtain an evaluation of the property is also referred to as a “buyer” in some cases.

When the buyer operates the computer to access the system 10 via the network,
The interface 22 displays the required image on the browser of the computer. When the buyer inputs a desired lifestyle, etc. in the input field on the image, the property search unit 20 searches the area matching the needs of the buyer based on the input lifestyle data, and within the area. Search for properties that match the conditions. Further, the real estate evaluation unit 18 refers to the selling price of the property and verifies its validity.

The present system can output the area desired by the buyer only by inputting the desired lifestyle according to a predetermined format. The conventional system is
First, the user only decided the desired area and supported the search for the property within the area. On the other hand, this system does not require area input. This is because the system includes the area evaluation database 28 that stores data for each area. Less than,
The operation of each unit will be described in more detail. The property search unit 20 reads index data such as local convenience (accessibility to city functions), local activity status (local activity), and local environment (local amenity) from the area evaluation DB 28, and then reads them. And the needs of the buyer.

[0024] The property search unit 20 finds an area where the buyer's own lifestyle image can be easily realized from the buyer's lifestyle and intention (area consulting).
At the same time, it is possible to search the property 32 and provide the buyer with timely and optimal property information. Figure 2
6 is a flowchart showing an outline of processing by the property search unit 20. The buyer (user) refers to the image displayed on the browser of the computer, inputs a predetermined character in the required input field, or selects from the menu to express the desired lifestyle. Various data are input (step 201).

The property search unit 20 digitizes various data representing the input lifestyle (step 20).
2). In reality, the needs of the buyer are quantified based on various sample analyzes and multivariate analysis. Next, the property search unit 20 searches the area evaluation DB 28 and identifies an area that matches the needs of the buyer (step 30).
3).

Further, the property search section 20 is provided with a property DB 32.
Is searched for a property that matches the needs of the buyer within the specified area (step 204). This makes it possible to find a suitable property in an area that meets the needs of the buyer. Searching for properties is realized by matching property attributes such as restricted zone, floor area ratio, roadway conditions, direction, site scale, site shape and the like.
In this way, it is possible to search for suitable properties that match the lifestyle of the buyer. The property searched by the buyer is stored in the user needs DB 34 in association with information (for example, a user ID) identifying the buyer.

The real estate evaluation section 18 uses various data in the transaction case DB 30 to apply a predetermined multiple regression equation to estimate the sale price. For example, the person who wants to sell the real estate (seller) can grasp the “estimated price” from the latest transaction example by inputting necessary information (for example, attributes) regarding the property desired to be sold.
On the other hand, the buyer can judge the appropriateness of the price of the desired property, for example, the property found by the property search unit 20.

FIG. 3 is a flow chart showing an outline of the processing executed by the real estate evaluation section 18. The processing of the real estate evaluation unit 18 includes processing for obtaining a land price function (steps 301 to 304) and processing for calculating an actual evaluation value of the property (step 305). First, the processing for obtaining the land price function will be described. First, the real estate evaluation unit 18 collects a large number of transaction case price data, which are objective variables, from the transaction case DB 30 (step 3).
01). Here it is desirable to collect as many transaction case prices as possible. Therefore, not only the data in the transaction case DB 30 of the system 10 but also the transaction case price data held in the DB of another system may be acquired via the network. The transaction case price is a unit price, that is, a price per unit area (for example, 1 m ² or 1 tsubo), and is preferably a so-called vacant lot price.

Next, the real estate evaluation section 18 searches the area evaluation DB 28 as the explanatory variable data, and acquires the items which are the factors that form the land price. For example, in the present embodiment, as the explanatory variable, data regarding the following items can be used. (1) Site area (2) Site shape (width: depth ratio) (3) Structure of the building being built (4) Width of front road (5) Water, gas, sewer maintenance status (6) Nearest Distance from station (7) Designation of designated area (8) Designated floor area ratio (9) Designation of fire-prevention area (10) Effective floor area ratio (created in consideration of restricted area and front road width) (11) Nearest commercial facility Distance (12) Accessibility to commercial functions (Commercial ACS) (13) Accessibility to business functions (Business ACS)

For example, of the above items, (1)-
(5) and (10) are stored in the transaction case DB 30 in association with the actual transaction case. Further, (6), (7) to (9), and (11) can be collected based on the address of the transaction case. Of course, the transaction example DB 30 may store the data of these items, but it goes without saying that the data may be obtained by searching the DB of another system based on the address. Further, (11) and (12) of the above items are generated by the area evaluation generation unit 24, which will be described later, and stored in the area evaluation DB 28.

Next, the real estate evaluation section 18 judges the significance of the explanatory variable by the multivariate analysis (step 303),
Then, a predetermined land price function is obtained (step 304).
As the analysis method, a correlation analysis between the objective variable and the explanatory variable, multiple regression analysis, or the like is used. Further, as the function form, not only the linear form but also the multiplication form, the double logarithmic form, the semilogarithmic form and the like can be used. FIG. 4 is a flowchart showing the processing in steps 303 and 304 in more detail. Prior to the multiple regression analysis, the correlation between the extracted items is calculated (step 401). FIG. 5A shows step 301,
An example of the data value of each item extracted in 302, FIG.
(B) is a figure which shows an example of these correlations. Figure 5
As shown in (a), in the extracted data table 500, the width of the front road, the effective floor area ratio, the distance from the nearest station, the distance to the nearest commercial facility, and the commercial ACS are initially set.
Are listed as candidates for explanatory variables. In the correlation table 510 based on these, the candidate of the explanatory variable having a high correlation with the transaction case price (land price) which is a non-explanatory function can be grasped. For example, it can be seen that the commercial ACS has the highest correlation coefficient, and the transaction case price (land price) increases as the commercial ACS increases.

Next, a certain function form is selected (step 402), the function form is used, and multiple regression analysis is executed using all the explanatory variable candidates as the explanatory variables (step 403). For example, it is considered that the result of the first multiple regression analysis using a linear land price function as described later is as shown in FIG. 6 (a). For example, by referring to the regression statistical table 601, the analysis accuracy of the multiple regression analysis can be grasped. In particular, the closer the degree of freedom adjusted R-square is to 1, the higher the analysis system. Also, multiple regression equation 602
In the above, the partial regression coefficient is a coefficient for returning each explanatory variable to the transaction case price (land price), and the t value represents the explanatory power of the explanatory variable. The greater the absolute value of the t value, the greater the explanatory power.

In the above example, the explanatory variables and partial regression
Using numbers, the land price y is expressed as: y = a + bx₁+ Cx_Two+ Dx_Three+ Ex_Four+ Fx₅ The real estate evaluation section 18 performs a sufficient analysis based on the above result.
It is judged whether or not the accuracy is obtained (step 40).
4). For example, in the example shown in FIG.
Sufficient analysis accuracy because there are unsatisfactory values
Is determined not to have been obtained (NO in step 404).
(No). This is because the partial regression coefficient of the front road width is negative.
(Ie, the wider the width of the front road,
(Meaning that the basement will be low)
It In addition, the correlation function also relates to the distance to commercial facilities.
The partial regression coefficient is
It is the sign of Lath (multicollinearity). Alternatively, t value
, There are some whose absolute value is less than 1.
May not be suitable for use as an explanatory variable
(Judgment of significance of explanatory variables).

Therefore, the real estate evaluation section 18 narrows down the candidates by referring to the mutual correlation values of the explanatory variables and the t value of the explanatory variables (step 405), and further executes the multiple regression analysis (step 403). . For example, in the above example, the front road width is excluded from the candidates in consideration of the high correlation value between the front road width and the effective volume ratio and the higher t value of the effective volume ratio. Considering that the distance to the commercial facility and the distance from the nearest station and the correlation value of the commercial ACS are respectively high and the t value of the commercial ACS is the highest, the distance to the commercial facility and the closest distance to the commercial facility are considered. The distance from the station is excluded from the candidates.

FIG. 6B is a table showing the result of the second multiple regression analysis in the above example. Regression statistics table 61
Referring to 1, it can be understood that the coefficient of determination with corrected degrees of freedom becomes higher and the analysis accuracy is improved, as compared with the regression statistical table 601 by the first multiple regression analysis. Also,
By referring to the multiple regression equation 612, it can be understood that there is no inconvenience in the sign condition of the partial regression coefficient and the t value is sufficiently high. In this way, when there is sufficient analysis accuracy over a predetermined level, this is determined as the land price function related to the functional form.

The processing of steps 403 to 405 is executed for other functional forms (step 40).
6, 402), the land price function can be obtained. Furthermore, of the obtained underground functions, the most suitable function form is selected and used for the estimation of the actual land price.
For this purpose, in the land price function of each function form, the coefficient of determination with the adjusted degree of freedom is compared, and the one having the largest value may be adopted.

In the present embodiment, as the land price function, the following function form can be used, for example. In the following functions, y is land price (explained variable), a
Is a constant term, b to d are partial regression coefficients, and x _{1 to} x ₃ are land price forming factors (explanatory variables). Land price function (linear, addition _{type) y = a + bx 1 +} cx 2 + dx 3 + ··· land price function (logarithmic _{type) Ln (y) = a +} bLn (x 1) + cLn (x 2) + d
_{Ln (x 3) + ··· (} y = exp (a) × x 1 b × x 2 c × x 3 d × ···) land value function (semi-log _{type) y = a + bLn (x} 1) + cLn (x ₂ ) + dLn (x
₃ ) + ...

In this way, when the optimum land price function is obtained, the real estate evaluation section calculates an estimated value of the suitable sale price of the property that the buyer wants and the property that the seller intends to sell (step 305). In this way, it is possible to derive an appropriate price from the property of the property (for example, address, site area, front road width) and area evaluation data. Such real estate evaluation is also stored in the user needs DB 34 in association with the information (user ID) that identifies the buyer or the seller.

Next, the area evaluation generator 24 according to this embodiment will be described. First, various data (area evaluation data) generated by the area evaluation generator 24
Therefore, the explanation will be added again. In the area evaluation DB 28,
It has layers of an accessibility layer, an activity layer, and an amenity layer, and stores data belonging to each layer. FIG. 7 is a diagram showing an example of a data structure in the area evaluation DB 28.

As shown in FIG. 7, the accessibility layer 701 includes convenience for shopping (commercial ACS), employment opportunity (business ACS), convenience for public facilities such as public offices, post offices, hospitals, parks and schools. Is included. The activity layer 702 includes, for example, data indicating the activity status of residents and workers, the payment status of electricity charges, the operation status of buildings, etc., using the power consumption data. The amenity layer 703 includes data on green coverage, sky ratio, openness / closedness of communities, ease of living by life stage, and the like. These accessibility layers 70
The data belonging to 1 to the amenity layer 703 are generated by the area evaluation generation unit 24 by acquiring the data from the original data DB 26 and performing necessary processing.

The data of the accessibility layer and its generation will be described in more detail. here,
The amount of service functions (floor area, number of employees, sales amount) is calculated by calculating an index that indicates the accessibility from a certain point (or area) to facilities with service functions (for example, commercial facilities such as supermarkets). In addition, the convenience of the point (or area) is quantified. Note that, as shown in FIG. 7, in the present embodiment, the chome of a certain town is used as an area unit, and an index relating to the area is calculated. Also, the index is calculated by converting the accessibility into a cost (generalization cost = moving cost + moving time + time value). For example,
The calculation of the commercial ACS will be described with reference to the flowchart of FIG.

First, a commercial accumulation site located within a predetermined range (for example, a range with a radius of 10 km) from a certain area is selected (step 801). The area evaluation generator 24
Accessibility when using the railway to the commercial accumulation value (steps 802 to 804) and accessibility when using a car (steps 805 to 807)
Are calculated respectively.

More specifically, the area evaluation generator 24
Calculates the time required to reach the commercial accumulation area when using the railroad (step 802), and then calculates the time cost and generalization cost when using the railroad (step 80).
3). These can be acquired by the following method. Measure the distance from the area to the nearest station, and measure the distance from the commercial cluster to the nearest station. The required walking time is calculated by dividing the sum of the distances obtained in the above and above by the average walking speed. Measure the boarding time from the above nearest station to the nearest station. The required time can be obtained by adding the above and. Further, the time cost is obtained by multiplying the required time by the time evaluation value. This time evaluation value is a statistical value obtained from national income, population, and working hours per person. Generalized cost is calculated by adding the boarding fare to the time cost.

Next, the area evaluation generation unit 24 generalizes
For some commercial clusters "i", based on cost, railway
Calculate accessibility ACS-Ti by use
(Step 804). In the present embodiment, ACS-
Ti can be calculated as follows. ACS-Ti = (number of employees in commercial accumulation area) / (generalization
cost)^α Here, α is a distance decreasing coefficient, and for example, α = 1.2.
Can be set to.

Further, the generalized cost for using the automobile is also obtained in substantially the same manner (steps 805 and 806). Measure the distance from the area to the commercial cluster. The required time is calculated by dividing the road obtained above by the average vehicle speed. By multiplying the required time by the time evaluation value, the time cost can be obtained. Further, the generalized cost can be obtained by multiplying the time cost by the cost coefficient and, if necessary, adding the toll road charge. The cost coefficient is a coefficient used to take into account the cost of gasoline and the like.

Next, the area evaluation generating unit 24, based on the generalized cost, with respect to the commercial accumulation place “i”,
The accessibility ACS-Ri by car use is calculated (step 807). It is calculated in the same manner as ACS-Ti.

Such processing is executed for all commercial accumulation areas within a predetermined range from the area (step 9).
01). When ACS-Ti and ACS-Ri are generated for each commercial accumulation area, the area evaluation generation unit 24
Acquires the accessibility ACS-T by railway use by taking the sum of each ACS-Ti (step 9
02) together with the sum of each ACS-Ri, the accessibility ACS-R by using the automobile is obtained (step 903). Furthermore, the area evaluation generation unit 24
Refers to, for example, a person trip survey to obtain the transportation share ratios α and β between the railroad and the automobile, and calculates commercial ACS = α (ACS-T) + β (ACS-R) (step 904). ). This will be the commercial ACS in the area.

The calculation of the business ACS will be briefly described below. In this embodiment, the business ACS
With respect to the above, the following formula is used by using an industrial employee in a predetermined range from the target area and a road distance from each area located in the predetermined range to the target area. Work ACS = Σ [(number of industrial employees in a certain area) / (road distance between the area and the target area) ^β ] Note that β is a distance reduction coefficient. Accessibility regarding government offices, schools, etc. can also be acquired by a method similar to the calculation of commercial ACS.

In this way, the accessibility layer data for each area can be stored in the area evaluation DB 28. By using GIS for distance measurement, it is possible to further facilitate processing and improve accuracy.

Next, a description will be added regarding the activity layer. The activity layer is composed of two categories: data representing the status of people and companies in the area and data representing the activity status of people and companies in the area. In the former, how many households, establishments, companies, etc. live and work in the area, and what are the attributes of those households, establishments, companies, etc.
It is data that shows what the infrastructure status of the area is. On the other hand, the latter shows the activity status of households, establishments, companies, etc. belonging to the area, and the households, establishments, and companies that have moved in / out in a year. The data. To generate activity layer data, for example,
Electric power contract data (contract type, number of contracts), power consumption data (electricity usage amount by contract type), national census (small area totals, totals by towns and letters, etc.), business establishment / company statistical survey (small areas) Etc.) is used. The area evaluation generator 24
With reference to the above data, various data belonging to the activity layer are generated.

The data of the amenity layer are evaluation data for judging the comfort of people in various activities such as comfort and working comfort. By making the consumer himself an evaluator and collecting a large number of evaluation results, the data can be made objective. Amenity data such as comfort and working comfort also include the consumer's evaluation of views and landscapes in the area.

To obtain amenity data, 1 a year
It is desirable to conduct a questionnaire survey to consumers (electric contractors) once or several times and make it based on the content. The content of the questionnaire should be items that can be scored in terms of living comfort. For example, there are things related to landscape / views, things related to noise, abundance of nature (green, parks, etc.), the situation of communities (neighborhood associations and residents' associations), the occurrence of crimes, etc.

As described above, according to the present embodiment, the property search unit 20 searches for an area that matches the lifestyle of the buyer and matches the conditions in the area. Search for properties. Further, the real estate evaluation unit 18 estimates the appropriate transaction price of the property based on the data in the area evaluation DB 28 and the like. Therefore, the buyer can not only find the desired property but also know the reasonable price of the property. further,
It is possible for the seller to know the reasonable selling price.

This system or a part of this system can be applied to the following business, for example. For example, it can be applied to a business (content business) that provides area evaluation data as content data. For example, data (area evaluation data) in the area evaluation DB for real estate companies (including intermediaries), commercial companies (retail, food and drink), information service companies, local governments (metropolitan area), countries, etc. Can be provided. Further, it is also possible to develop an application utilizing the area evaluation data and operate a business (ASP) to be provided.

In addition, many existing property search systems are
Enter the line and property details that the customer (consumer) desires,
It is a mechanism to introduce properties that meet these conditions. This mechanism entrusts the customer himself with consideration of area selection and property size. On the other hand, this system analyzes needs based on the behavior pattern and orientation of the customer (consumer) in order to promote matching of real estate supply and demand.
It is a real estate marketing system that has the function of promptly selecting (assessing) an area that meets the needs obtained through analysis and providing the customer (consumer) with the property information supplied in that area. This system will allow customers (consumers) to make faster decision-making on property purchases than ever before. Furthermore, in the assessment, area evaluation data can be used to comprehensively analyze and match the needs of buyers.

The present invention is not limited to the above embodiments, and various modifications can be made within the scope of the invention described in the claims, and these are also included in the scope of the present invention. It goes without saying that this is what is done. For example, in the above-described embodiment, data that belongs to the accessibility layer (for example, commercial ACS) out of the data stored in the area evaluation DB 28 is used in the real estate evaluation, but the data is not limited to this. Instead, it goes without saying that data belonging to the activity layer or the amenity layer may be used.

In the above embodiment, the commercial A
For the calculation of CS, the number of employees in the commercial accumulation area is used, but the present invention is not limited to this. Other indicators showing the size of the commercial accumulation area, for example, sales floor area may be used. . In addition, for the calculation of commercial ACS
Needless to say, it is possible to consider not only the car but also the accessibility on foot if necessary. This also applies to accessibility at government offices and schools.

In the above embodiment, the user needs DB 34 stores the search results by the buyer and the real estate evaluation results. From the information stored in the user needs DB 34, it is possible to know what area the user likes. Furthermore, the information in the user needs DB 34 is set to 1 in the area evaluation DB 28.
It may be configured so that it is stored as a layer and can be used for area evaluation.

[0059]

According to the present invention, the buyer / seller can present the proper price of the property desired to be purchased / sold. In addition, it is possible to provide the desired property in a timely manner by finding an area that makes it easy for the buyer to realize their own lifestyle image based on their lifestyle and orientation and linking it with the property database. Become.

[Brief description of drawings]

FIG. 1 is a real estate search / execution according to the present embodiment.
It is a block diagram which shows the structure of an evaluation system.

FIG. 2 is a flowchart showing an outline of processing by a property search unit according to the present embodiment.

FIG. 3 is a flowchart showing an outline of processing executed by a real estate evaluation section according to the present embodiment.

FIG. 4 is a block diagram of steps 303 and 304 of FIG.
3 is a flowchart showing the process in step 1 in more detail.

5 (a) is a diagram showing an example of data values of respective items extracted in steps 301 and 302, and FIG. 5 (b) is a diagram showing an example of these correlations.

FIG. 6 is a diagram showing an example of multiple regression analysis in the present embodiment.

FIG. 7 is an area evaluation D according to the present embodiment.
It is a figure which shows the example of the data structure in B.

FIG. 8 is a flowchart showing processing relating to calculation of commercial ACS according to the present embodiment.

FIG. 9 is a flowchart showing processing relating to calculation of commercial ACS according to the present embodiment.

[Explanation of symbols]

10 Real Estate Search / Evaluation System 14 Processing unit 16 Data generation / holding unit 18 Real Estate Evaluation Department 20 Property Search Department 22 Interface 24 Area evaluation generator 26 Original data DB 28 area evaluation DB 30 transaction case DB 32 property DB 34 User Needs DB

   ─────────────────────────────────────────────────── ─── Continued front page    (72) Inventor Takayuki Yoshida             2-26-11 Shiba Orchid Building 2 Shiba, Minato-ku, Tokyo             Floor Alpha Forum Co., Ltd. (72) Inventor Tetsuya Saigo             3-2-1 Nishi-Shimbashi, Minato-ku, Tokyo             8th floor Alpha Prime Ja Co., Ltd.             In the bread

Claims (16)

[Claims] 1. At least one generated for each area,
Property / Area specification that specifies the property of the area and the area to which the property belongs and the area evaluation database that stores the data of the items related to accessibility that indicates the accessibility to the specified functions of the area. A real estate evaluation comprising means and a real estate evaluation means for estimating an appropriate price of the property based on the transaction case data including the actual transaction price and the data of the item in the area evaluation database. system. 2. The real estate evaluation system according to claim 1, further comprising area evaluation data generation means for generating the area evaluation data based on various statistical data regarding the area. 3. The real estate evaluation means uses data related to a transaction case as an objective variable and factors of forming land prices, including data of items stored in the area evaluation database and data of attributes of the property. , As an explanatory variable, the significance of the explanatory variable is determined by multivariate analysis, the land price function is determined based on the significance, and the land price function is used to estimate the appropriate price. The real estate evaluation system according to claim 1 or 2, which is characterized. 4. The real estate evaluation means, when y is a land price which is an objective variable, a is a constant term, b to d are partial regression coefficients, and x is an explanatory variable, 1) y = a + bx ₁ + cx ₂ + dx ₃ + ... 2) Ln (y) = a + bLn (x ₁ ) + cLn
_{(X 2) + dLn (x} 3) + ··· (y = exp (a) × x 1 b × x 2 c × x 3 d × ···) 3) y = a + bLn (x 1) + cLn (x 2 ) + DL
The real estate evaluation system according to claim 3, wherein the real estate evaluation system is configured to estimate an appropriate land price based on any one of n (x ₃ ) +. 5. The real estate evaluation system according to claim 4, wherein the real estate evaluation means is configured to select the most appropriate expression from the expressions 1) to 3). 6. The real estate evaluation means is configured to select a predetermined item and / or attribute from the items stored in the area evaluation database and the property attribute based on the result of the multivariate analysis. The real estate evaluation system according to any one of claims 3 to 5, wherein 7. A property search means for searching a property database, which stores data related to real estate properties, based on a user's request, for a property that is considered to be desired, and an appropriate price for the searched property is estimated. The real estate evaluation system according to claim 1, wherein the real estate evaluation system is configured as described above. 8. The property search means refers to the area evaluation database based on the lifestyle of the user, searches for an area that matches the user's wishes, and searches for properties existing in the area. The real estate evaluation system according to claim 7, which is configured as follows. 9. A program for estimating a proper price of a real estate property, which comprises identifying a property to be evaluated, identifying attributes of the property and an area to which the property belongs, and an actual transaction price. Based on the data on the transaction cases including and the data of the items in the area evaluation database that stores at least the data of the items related to accessibility, which is generated for each area and indicates the accessibility to the predetermined function of the area, A real estate evaluation program characterized by causing a computer to execute a real estate evaluation step of estimating an appropriate price. 10. The real estate evaluation program according to claim 9, further comprising causing the computer to execute the step of generating the area evaluation data based on various statistical data regarding the area. 11. In the real estate evaluation step, the data of items stored in the area evaluation database and the data of the property of the property are used as a factor for forming a land price, with the data relating to a transaction case as an objective variable,
As an explanatory variable, by multivariate analysis, a step of determining the significance of the explanatory variable, a step of determining a land price function based on the significance, and a step of estimating an appropriate price by using the land price function, The real estate evaluation program according to claim 9, which is executed by the computer. 12. In the real estate evaluation step, y
Is a land variable which is an objective variable, a is a constant term, b to d are partial regression coefficients, and x is an explanatory variable, 1) y = a + bx ₁ + cx ₂ + dx ₃ + ... 2) Ln (y) = a + bLn (x ₁ ) + cLn
_{(X 2) + dLn (x} 3) + ··· (y = exp (a) × x 1 b × x 2 c × x 3 d × ···) 3) y = a + bLn (x 1) + cLn (x 2 ) + DL
The step of estimating the suitable land price based on any of n (x ₃ ) + ...
The real estate evaluation program according to claim 11, which is executed by the computer. 13. The real estate evaluation program according to claim 12, further comprising causing the computer to execute the step of selecting the most appropriate expression from the expressions 1) to 3) in the real estate evaluation step. . 14. The step of selecting a predetermined item and / or attribute from the items stored in the area evaluation database and the property attribute based on the result of the multivariate analysis in the real estate evaluation step, The real estate evaluation program according to any one of claims 11 to 13, which is executed by a computer. 15. A property search step of searching a property database that stores desired property data based on a user's request, and a step of estimating a proper price for the searched property. 15. The real estate evaluation program according to claim 14, wherein the computer is caused to execute. 16. In the property searching step, based on the lifestyle of the user, referring to the area evaluation database, searching for an area that matches the user's wish, and searching for a property existing in the area. 16. The real estate evaluation program according to claim 15, characterized by causing the computer to execute.