KR20220073295A - Apparatus for estimating market price of real estate and method thereof - Google Patents

Abstract

The present invention relates to a real estate market price estimation apparatus, and the real estate price estimation apparatus according to an embodiment of the present invention includes: a data collection unit for collecting real estate-related data including real transaction price data of real estate, ledger data, and land characteristic data; A data refiner that compares the characteristic information of the real transaction data with the characteristic information of the ledger data and land characteristic data to match the location of the matching real estate to the location of the real transaction price and generates a list of transaction data for the real estate ; and extracting a plurality of HLPAs for the real estate to be evaluated using the characteristic information of the real estate whose location is matched, and generating a market price estimation model for the real estate to be evaluated using the extracted characteristic information of the real estate in the HLPAs. and a market price estimation unit for estimating the market price of the real estate to be assessed by inputting the characteristic information of the real estate to be assessed in the generated market price estimation model.

Description

Apparatus and method for estimating real estate prices

The present invention relates to an apparatus and method for estimating a real estate market price, and more particularly, to an apparatus and method for estimating a real estate market price by refining and using real transaction price information.

Real estate information has traditionally been provided in the form of a human network through a real estate agent, but it was difficult to collect and utilize a wide range of real estate information due to spatial limitations.

With the enforcement of the Act on Promotion of Provision and Use of Public Data in 2013, an environment has been created to process and utilize various public data on real estate provided by the state, such as real transaction price information and registered information on real estate. are being provided.

For example, Korean Patent Laid-Open No. 10-2017-0143258 discloses a technology for estimating housing prices using public data on real estate.

KR 10-2017-0143258 A

The present invention is to solve the problems of the prior art described above, by using real transaction price data, ledger data, and official price data to match location information where the actual transaction price is an undisclosed part of real estate, and estimate the market price of the real estate to be evaluated using this By doing so, it is possible to estimate a more accurate real estate market price.

The problems of the present invention are not limited to the problems mentioned above, and other problems not mentioned will be clearly understood by those skilled in the art from the following description.

The real estate market price estimation apparatus according to an embodiment of the present invention includes a data collection unit for collecting real estate-related data including real transaction price data of real estate, ledger data, and land characteristic data, characteristic information of the actual transaction price data, and the ledger data and land A data refiner that compares the characteristic information of the characteristic data to match the location of the matching real estate to the location of the real estate for the actual transaction and generates a list of transaction data for the real estate using the characteristic information of the real estate with the matching location Extracting a plurality of HLPAs for the real estate to be evaluated, generating a market price estimation model for the real estate to be assessed using the extracted characteristic information of the real estate in the HLPAs, and adding the price estimation model to the value of the real estate to be assessed It may include a market price estimation unit for estimating the market price of the real estate to be evaluated by inputting characteristic information.

In an embodiment, the data refiner includes a location connecting unit that matches location information, which is undisclosed information among the characteristic information of the actual transaction data, using the characteristic information of the ledger data and land characteristic data, the actual transaction of real estate with the location matched If the price is a lump sum transaction amount of land and building, the transaction price distribution unit that distributes the estimated building price and the estimated land price, and the actual transaction price and the estimated land price of the real estate matching the location are compared with the individual announced market price for the real estate Thus, when it is determined that the actual transaction is an abnormal transaction, an abnormal transaction removal unit for excluding the transaction data list corresponding to the actual transaction may be included.

In one embodiment, when the real estate corresponding to the real transaction data is land, the location connection unit selects the first place of the city, gun-gu, usage area, area, and street among the characteristic information of the actual transaction price data and the characteristic information of the ledger data The location information of the ledger data that is matched by comparison may be matched with the location information of the real estate for which the actual transaction is made.

In an embodiment, when the real estate corresponding to the actual transaction price data is an apartment house, the location connection unit includes city, county, street, building year, number of floors, and exclusive area among the characteristic information of the actual transaction price data and the characteristic information of the ledger data. by comparing the location information of the matching ledger data can be matched with the location information of the real estate transaction.

In one embodiment, when the real estate corresponding to the real transaction price data is any one of a single-family house, a multi-family house, a commercial or a business building, the location connection unit is selected from among the characteristic information of the actual transaction price data and the characteristic information of the ledger data. The location information of the matching ledger data can be matched with the location information of the real estate by comparing the city, county, street, use area, land area, road conditions, main use, building area, and total floor area.

In one embodiment, the abnormal transaction removal unit compares the actual transaction price of the real estate with the location matched and the estimated land price with the individual official land price for the real estate. may be determined as an abnormal transaction and the list of transaction data corresponding to the actual transaction may be excluded.

In an embodiment, the price estimating unit includes a HLPA setting unit configured to set transaction data satisfying a location, a transaction time, and a price level from a preset evaluation target real estate among the transaction data list as the HLPA real estate; A comparison target real estate extraction unit that extracts a predetermined comparison target real estate according to a preset classification standard among the set HLPAs real estate and multiple regression analysis using characteristic information of the predetermined comparison target real estate as an independent variable. A market price estimation model generation unit may be included to generate a market price estimation model for the market, and input characteristic information of the target real estate to be evaluated in the generated market price estimation model to estimate the market price of the real estate to be evaluated.

In an embodiment, the price estimation model generator is a multidimensional equation generated through multiple regression analysis using, as independent variables, a use area, a use situation, a road surface, and a shape among the characteristic information of the real estate to be evaluated when the real estate to be evaluated is land. can be generated as a price estimation model.

In an embodiment, the market price estimation model generation unit determines the case classification, use, number of floors, area, elapsed years, elevator, number of parking spaces and price point among the characteristic information of the real estate when the real estate to be evaluated is a row house or a multi-family house A multidimensional equation generated through multiple regression analysis with independent variables can be generated as a price estimation model.

In an embodiment, the market price estimation model generation unit is a medium regression using the case classification, the number of floors, the area, the elapsed years, the number of parking spaces, and the price point among the characteristic information of the real estate as independent variables when the real estate to be evaluated is a small and medium-sized apartment complex. A multidimensional equation generated through analysis can be generated as a price estimation model.

In an embodiment, the price estimation model generation unit estimates the market price using a multidimensional equation generated through multiple regression analysis using the number of floors, area, and transaction date as independent variables among the characteristic information of the real estate when the real estate to be evaluated is a large apartment complex. model can be created.

In an embodiment, the market price estimation unit may further include an estimated market price verification unit for verifying the estimated market price by comparing the estimated market price of the real estate to be evaluated with the published price of the corresponding real estate.

In an embodiment, the real estate price estimation apparatus may further include a user interface for inputting evaluation target real estate information and providing the estimated market price information.

The real estate market price estimation method according to an embodiment of the present invention comprises the steps of acquiring real transaction price data, ledger data and official price data for real estate, real estate characteristic information of the real transaction price data, and real estate characteristic information of the ledger data and official price data. Comparing and matching the location of the matching real estate to the location of the real estate for the actual transaction, setting the HLPA real estate for the real estate to be evaluated using the characteristic information of the real estate with the matching location, and the extracted HLPAs generating a market price estimation model for the real estate to be evaluated using the characteristic information of the real estate in the area, and estimating the market price of the real estate to be assessed by inputting the characteristic information of the real estate to be assessed in the generated market price estimation model have.

Prior to this, the terms or words used in the present specification and claims should not be construed in the ordinary and dictionary meaning, and the inventor may properly define the concept of the term to describe his invention in the best way. Based on the principle that there is, it should be interpreted as meaning and concept consistent with the technical idea of the present invention.

According to the present invention, location information of real estate for real transaction can be matched. Accordingly, the accuracy of the estimated market price of the real estate to be evaluated provided by the real estate price estimation apparatus may be improved.

According to the present invention, when the actual transaction price is a lump sum transaction amount of land and a building, the actual transaction price can be divided into the estimated building price and the estimated land price. Accordingly, distortion of the land price can be prevented and the accuracy of the estimated market price of the real estate to be evaluated can be further improved.

According to the present invention, it is possible to remove the transaction data list for the actual transaction price data determined to be an abnormal transaction among the actual transaction price data matched with the location. Accordingly, the accuracy of the estimated market price of the real estate to be evaluated provided by the real estate market estimation apparatus may be further improved.

Effects of the present invention are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description of the claims.

1 is a view showing a real estate price estimation system including a real estate price estimation apparatus according to an embodiment of the present invention.
2 is a view showing a real estate price estimation apparatus according to an embodiment of the present invention.
3 is a view showing characteristic information of actual transaction price data.
4A is a diagram illustrating an example of a method for the location connection unit to link location information about land among actual transaction price data.
4B is a diagram illustrating an example of how the location connection unit connects location information regarding an apartment house among actual transaction price data.
4C is a diagram illustrating an example of a method for the location connection unit to connect location information about a single-family house, a multi-family house, a commercial building, or a business building among actual transaction price data.
FIG. 5 is a diagram showing, by way of example, the classification criteria for the HLPAs setting unit to set the HLPAs real estate among the transaction data lists.
6 is a diagram illustrating a selection condition for the comparative example extraction unit to select a comparative example real estate from among HLPAs real estate.
7A is a diagram illustrating characteristic information and an application code for generating a market price estimation model when the market price estimation model generating unit is the real estate to be assessed is land.
7B is a diagram illustrating characteristic information and an application code for generating a market price estimation model when the real estate to be evaluated by the market price estimation model generation unit is a row house or a multi-family house.
7C is a diagram illustrating characteristic information and an application code for generating a market price estimation model when the market price estimation model generating unit is a small and medium-sized apartment complex as the real estate to be evaluated.
FIG. 7D is a diagram showing, by way of example, characteristic information and an application code for the market price estimation model generating unit for generating the market price estimation model when the real estate to be evaluated is a large-scale apartment.
8 is a diagram illustrating a method for estimating a real estate market price according to an embodiment of the present invention.
9 is a diagram illustrating an exemplary computing device capable of implementing the apparatus for estimating real estate prices according to an embodiment of the present invention.

Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. Advantages and features of the present disclosure, and methods of achieving them will become apparent with reference to the embodiments described below in detail in conjunction with the accompanying drawings. However, the technical spirit of the present disclosure is not limited to the following embodiments, but may be implemented in various different forms, and only the following embodiments complete the technical spirit of the present disclosure, and in the technical field to which the present disclosure belongs It is provided to fully inform those of ordinary skill in the art of the scope of the present disclosure, and the technical spirit of the present disclosure is only defined by the scope of the claims.

In adding reference numerals to the components of each drawing, it should be noted that the same components are given the same reference numerals as much as possible even though they are indicated on different drawings. In addition, in describing the present disclosure, if it is determined that a detailed description of a related known configuration or function may obscure the gist of the present disclosure, the detailed description thereof will be omitted.

Unless otherwise defined, all terms (including technical and scientific terms) used herein may be used with the meaning commonly understood by those of ordinary skill in the art to which this disclosure belongs. In addition, terms defined in a commonly used dictionary are not to be interpreted ideally or excessively unless clearly defined in particular. The terminology used herein is for the purpose of describing the embodiments and is not intended to limit the present disclosure. In this specification, the singular also includes the plural unless specifically stated otherwise in the phrase.

In addition, in describing the components of the present disclosure, terms such as first, second, A, B, (a), (b), etc. may be used. These terms are only for distinguishing the elements from other elements, and the essence, order, or order of the elements are not limited by the terms. When a component is described as being “connected”, “coupled” or “connected” to another component, the component may be directly connected to or connected to the other component, but another component is between each component. It should be understood that elements may also be “connected,” “coupled,” or “connected.”

As used herein, “comprises” and/or “comprising” refers to a referenced component, step, operation, and/or component of one or more other components, steps, operations and/or components. The presence or addition is not excluded.

Prior to a description of various embodiments of the present disclosure, some terms used in the embodiments will be clarified.

Real estate refers to property that cannot be moved, such as land, buildings, or trees. The present invention relates to a system and method for calculating a real estate price, wherein the real estate in the present invention is a concept including at least one of land and buildings for which price can be calculated. It is a concept that includes apartments, multi-family houses, and officetels.

The official standard land price refers to ^the appropriate price per unit area (m2) announced by selecting and surveying representative standard lots (500,000 lots) among the national land (about 30 million lots). The price per unit area of individual land determined and announced by the head of a Si/Gun/Gu after being verified by an appraiser based on the announced standard official land price, collecting opinions from landowners, and deliberation by the Si/Gun/Gu Real Estate Evaluation Committee (circle/m ² ) means.

In the present invention, the official land price is a concept that includes not only the standard official land price and individual official land price of land, but also the official prices of the aforementioned single/multi-family houses, apartments, row houses/multi-family houses, and officetels.

1 is a view showing a real estate price estimation system including a price estimation apparatus according to an embodiment of the present invention.

The real estate price estimation system 10 may include a public data server 11 , a client 12 , and a real estate price estimation apparatus 100 .

The public data server 11 , the client 12 , and the real estate price estimation apparatus 100 may be connected through a network. The network may be implemented as various communication networks, such as wired or wireless.

The real estate data server 11 may provide real estate-related data to the real estate price estimation apparatus 100 through a network. Real estate-related data provided by the real estate data server 11 may include public real estate data and private real estate data. The public real estate data may include, but is not limited to, actual transaction price data, land characteristic data, and various ledger data. In addition, the private real estate data may include appraisal data for real estate, but is not limited thereto.

The user terminal 12 may include, but is not limited to, a PC, a smart phone, a notebook computer, and the like. The user may be connected to the real estate market price estimation apparatus 100 through the user terminal 12 to receive an estimated market price for the real estate to be evaluated for which the user wants to check the market price. Also, the user terminal 12 may input information on the real estate to be evaluated into the real estate market price estimation apparatus 100 .

The real estate price estimation apparatus 100 is a data collection unit 110 that collects various data on real estate from the real estate data server 11, and analyzes the collected data to match location information on real estate corresponding to the corresponding real transaction data. It may include a data refining unit 120, a market price estimation unit 130 for estimating the market price of the real estate to be evaluated by using the transaction data list to which the location information is matched.

In addition, the real estate price estimation apparatus 100 may further include a database 150 capable of storing real estate-related data collected by the data collection unit 110 . The database 150 may store a list of transaction data for real estate in which the actual transaction price information and the location information are matched in the data refiner 120 .

In addition, the real estate price estimation apparatus 100 may further include a user interface unit 140 for receiving information about the real estate to be evaluated from the client or providing the estimated market price to the client. The user interface unit 140 may include a keyboard, a microphone, and the like for receiving evaluation target real estate information. In addition, the user interface unit 140 may include a display device, a speaker, etc. for providing the estimated market price for the real estate to be evaluated to the client.

2 is a view showing an apparatus for estimating real estate prices according to an embodiment of the present invention, FIG. 3 is a view showing characteristic information of actual transaction price data, and FIGS. 4A to 4C are the location of the real estate corresponding to the real transaction price data in which the location connection unit is located It is a diagram exemplarily showing a method of linking information, and FIG. 5 is a diagram illustrating the classification criteria for the HLPA setting unit to set the HLPAs real estate among the transaction data lists, and FIG. 6 is a comparative example extraction It is a view exemplarily showing selection conditions for selecting a comparative example real estate among additional HLPAs real estate, and FIGS. 7A to 7C illustrate characteristic information for generating a market price estimation model by the market price estimation model generator and an application code therefor It is a drawing that shows

Hereinafter, the real estate price estimation apparatus 100 according to an embodiment of the present invention will be described in more detail with reference to FIGS. 2 to 7 .

The data collection unit 110 may crawl real transaction price data, various ledger data, land characteristic data, appraisal data, etc. in accordance with a period set in the real estate data server 11 and store it in the database 150 .

For example, the data collection unit 110 may crawl the actual transaction price data 30 days prior to the current time every 7 days and store it in the database 150 . Alternatively, the data collection unit 110 may crawl the appraisal data every 7 days and store it in the database 150 .

The data refining unit 120 is a location connection unit 121 that connects the location of the real estate where the actual transaction is performed, and the transaction price for distributing the lump-sum sale amount to the estimated building price and the estimated land price when the actual transaction for real estate is a lump-sum sale of land and building Includes a distribution unit 122 and an abnormal transaction removal unit 123 that determines whether an actual transaction case for real estate is an abnormal transaction, and removes the actual transaction case so as not to use the actual transaction case for tense estimation if it is determined to be an abnormal transaction do.

The location connection unit 121 uses real estate data obtained from the real estate data server 11 to check and match location information, which is undisclosed information of the actual transaction price data. 3 shows various characteristic information of actual transaction price data.

Referring to FIG. 3 , the actual transaction price data has an undisclosed characteristic, and this undisclosed characteristic is location-related information that can specify real estate. For example, if the real estate is land or general real estate, the undisclosed characteristics are street address information of the real estate, and if the real estate is a collective real estate, the undisclosed characteristics are street address information, dong and house information.

Since the actual transaction price data reflects the actual price at which the real estate is traded in the market, you can check the overall real estate market price in the area where the real estate is located, but due to the undisclosed nature, you cannot confirm the actual transaction for the real estate in a specific location. Therefore, when estimating the real estate market price to be evaluated using the actual transaction price information for which the location is not specified, the accuracy of the estimated market price may be somewhat reduced.

Accordingly, the real estate price estimation apparatus 100 according to the present invention finds and matches the undisclosed characteristics of the actual transaction price data using the property information of the real estate ledger data and the land characteristic data through the location connection unit 121 .

4A exemplarily shows a method for the location connection unit 121 to match location information when the real estate corresponding to the actual transaction data is land.

The location connection unit 121 receives the actual transaction price data, the ledger data, and the land characteristic data from the database 150 (S110).

The location connection unit 121 determines whether the corresponding transaction is an equity transaction by using the public characteristic information of the received real transaction data (S120). When the location connection unit 121 determines that the transaction is an equity transaction, the actual transaction data is classified as unrefined data (S150). Unrefined data means data that is not used for price estimation.

When the location connection unit 121 determines that the transaction is not an equity transaction, the location connection unit 121 determines whether the characteristic information of the actual transaction data, the ledger data, and the land characteristic data matches (S130) If the movable property is land, the location connection unit ( 121) is the first digit information of city, county and gu information, use area information, area information, and street address information that confirms whether or not it matches. If there is a real estate having the same characteristic information, the location connection unit 121 matches the location information of the real estate with the location information of the real estate to be traded (S140). Through this process, the street information, which is an undisclosed characteristic of actual transaction price data for land, can be specified.

4B exemplarily shows a method for the location connection unit 121 to match location information when the real estate corresponding to the actual transaction data is an apartment house.

The location connection unit 121 receives actual transaction price data and ledger data from the database 150 (S210).

The location connection unit 121 compares the received real transaction price data and the characteristic information of the ledger data with each other to confirm whether there is a real estate that matches the city/gun-gu information, the street address information, the building year information, and the number of floors (S220). If there is no matching real estate, the location connection unit 121 classifies the corresponding actual transaction price data as unrefined data (S250).

If there is a matching real estate, the location connection unit 121 additionally checks whether the exclusive area information matches (S230). When the exclusive area information does not match, the location connection unit 121 classifies the actual transaction price data as unrefined data (S250).

When there is a real estate with the same exclusive area information, the location connection unit 121 matches the location information of the real estate with the location information of the real estate to be traded (S240). Through this process, dong and lake information, which are undisclosed characteristics of actual transaction price data for apartment houses, can be specified.

FIG. 4C exemplarily shows how the location connection unit 121 matches location information when the real estate corresponding to the actual transaction data is a detached house, a multi-family house, a commercial building, or a business building.

The location connection unit 121 receives the actual transaction price data, the ledger data, and the land characteristic data from the database 150 (S310).

The location connection unit 121 compares the input real transaction price data, the ledger data, and the property information of the land characteristic data, and compares the characteristics information of the city, gun and gu information, use area information, land area information, road condition information, main use information, construction year information, total floor area information, It is checked whether there is a real estate whose address information matches (S320).

If there is no matching real estate, the location connection unit 121 checks whether the attached lot number (general title part) information exists (S340). If there is no attached lot number (general title part) information, the location connection unit 121 classifies the actual transaction price data as unrefined data (S360). If the attached lot number (general title part) information exists, the location connection unit 121 inputs the total floor area information by adding the land area of the annexed lot number information to step S310 (S350).

If there is a matching real estate, the location connection unit 121 matches the location information of the corresponding real estate with the location information of the actual transaction (S330). Through this process, information on the street address or dong and number, which is an undisclosed characteristic of the actual transaction price data for single-family houses, multi-family houses, commercial buildings, or office buildings, can be specified.

The transaction price distribution unit 122 allocates the actual transaction price to the estimated building price and the estimated land price when the actual transaction price of the real estate with the matching location is the lump-sum transaction amount of the land and the building.

The transaction price distribution unit 122 deducts the estimated building price from the collective transaction amount by using the land residual method of the appraisal theory, and then derives the estimated transaction price of the land only. That is, the transaction price distribution unit 122 may calculate the estimated land price from the lump sum transaction amount through Equation 1 below. Here, the estimated building price can be calculated through Equation 2 below by depreciating and correcting the cost of repurchasing of the target object by using the cost method of the appraisal theory.

<Equation 1>

Estimated land price = Actual transaction price (batch transaction amount) - Estimated building price,

<Equation 2>

Estimated building price = cost of resourcing - adjusted depreciation

Depreciation adjusted amount = Repurchase cost X (useful life - elapsed life) / useful life

Here, the cost of re-procurement can be applied based on the structure information, usage information, and date of approval of use of the ledger data for buildings, and the depreciation correction is applied to the useful life of each building structure by applying the straight-line method (useful life method). It can be calculated using the elapsed years (the elapsed period from the date of approval for use to the time of transaction).

As described above, when the actual transaction price is a lump sum transaction amount between land and buildings, the land price may be distorted depending on the structure of the building, the usage status, and the elapsed years. By calculating, there is an advantage in that it is possible to estimate the market price of real estate more accurately.

The abnormal transaction removal unit 123 determines whether the actual transaction price is an abnormal transaction by comparing the actual transaction price and the estimated land price of the real estate with the matching location with the individual official land price for the corresponding real estate, and if it is determined as an abnormal transaction, the actual transaction may not create a list of transaction data corresponding to the actual transaction by determining that the data is inappropriate data.

For example, if the actual transaction price of the actual transaction price data is lower than the individual official price of the real estate, the abnormal transaction removal unit 123 determines the actual transaction case as an abnormal transaction case, and does not generate a list of transaction data corresponding to the actual transaction. can

For example, when the estimated land price estimated by the transaction price distribution unit 122 is lower than the individual official price of the real estate, the abnormal transaction removal unit 123 determines that the actual transaction case is an abnormal transaction case, and a transaction corresponding to the actual transaction. You may not create a data list.

Through this abnormal transaction removal unit 123, the accuracy of the market price estimated by the real estate price estimation apparatus 100 is further improved by not using the actual transaction price data, which is different from the appropriate market price according to the circumstances of the transaction party, for price estimation can be

The price estimation unit 130 includes a HLPA setting unit 131 that sets the transaction data satisfying the location, transaction time, and price level from the real estate to be evaluated among the transaction data list as the HLPAs real estate, and the set HLPAs. Evaluation through multiple regression analysis using the comparison target real estate extraction unit 132 for extracting predetermined comparison target real estate according to preset classification criteria among real estate and the characteristic information of the predetermined comparison target real estate as an independent variable and a market price estimation model generator 133 for generating a market price estimation model for the target real estate and estimating the market price of the target real estate by inputting characteristic information of the target real estate to the generated market price estimation model. In addition, the market price estimation unit 130 may further include an estimated market price verification unit 134 for verifying the estimated market price by comparing the estimated market price of the real estate to be evaluated with the published price of the corresponding real estate.

5 exemplarily shows the classification criteria applied by the HLPA setting unit 131 to set the HLPAs real estate. Referring to FIG. 5 , in the HLPA setting unit 131, the location of the real estate among the transaction data is within 500 m from the real estate to be evaluated, the transaction time is within 2 years from the date of price calculation (the date of estimation of the market price), and the price level Transaction data satisfying the conditions set in FIG. 5 may be set as real estate in the HLPAs. The above-described classification criteria are exemplary, and may be changed to other criteria as necessary.

That is, the real estate in the HLPA set by the HLPA setting unit 131 is real estate having a transaction price determined to be comparable to the real estate subject to evaluation.

The comparison target real estate extractor 132 may select a predetermined number of real estate in the HLPAs set by the HLPAs setting unit 131 according to the set classification criteria. 6 exemplarily shows the classification criteria applied by the comparison target real estate extraction unit 132 .

For example, the comparison target real estate extraction unit 132 may apply the setting criteria of FIG. 6 to select 10 cases from among a plurality of HLPAs and sort them in descending order.

The comparison target real estate extraction unit 132 selects the HLPAs real estate based on a predetermined classification criterion once again and generates a market price estimation model using the selected comparison target real estate, thereby enabling more accurate market price estimation.

The market price estimation model generation unit 133 generates a market price estimation model for estimating the market price of the real estate to be evaluated through multiple regression analysis using characteristic information on the real estate to be compared.

For example, the market price estimation model generator 133 generates the multidimensional equation of Equation 3 below by performing multiple regression analysis on characteristic information of a plurality of selected comparison target real estate when the real estate to be evaluated is land. and it can be created as a price estimation model for the real estate to be evaluated.

<Equation 3>

Here, the use area, usage situation, road contact surface, and shape are independent variables, ε _i is a constant, and β ₁ , β ₂ , β ₃ , and β ₄ are regression coefficients.

The market price estimation model generation unit 133 applies the application code shown in FIG. 7A to specific information corresponding to an independent variable among specific information of the real estate to be assessed in the generated market price estimation model, and estimates for the real estate to be assessed You can create a quote.

For example, the market price estimation model generation unit 133 performs multiple regression analysis on the characteristic information of a plurality of selected comparison target real estate when the real estate to be evaluated is a row house or a multi-family house to obtain a result of Equation 4 below. A multidimensional equation can be generated and it can be generated as a price estimation model for the real estate to be evaluated.

<Equation 4>

Here, case classification, use, floor, area, elapsed years, elevator, number of parking spaces, and price point are independent variables, ε _i is a constant, β ₁ , β ₂ , β ₃ , β ₄ , β ₅ , β ₆ , β ₇ , and β ₈ are the regression coefficients.

The market price estimation model generation unit 133 applies the application code shown in FIG. 7B to specific information corresponding to an independent variable among specific information of the real estate to be assessed in the generated market price estimation model, and estimates for the real estate to be assessed You can create a quote.

For example, the market price estimation model generation unit 133 performs multiple regression analysis on the characteristic information of a plurality of selected comparison target real estate when the real estate to be evaluated is a small and medium-sized apartment complex to obtain the multidimensional equation of Equation 5 below. can be created and it can be created as a market price estimation model for the real estate to be evaluated.

<Equation 5>

Here, case classification, floor, area, age, number of parking spaces, and price point are independent variables, ε _i is a constant, β ₁ , β ₂ , β ₃ , β ₄ , β ₅ , β ₆ are regression coefficients. to be.

The market price estimation model generation unit 133 applies the application code shown in FIG. 7C to specific information corresponding to an independent variable among specific information of the real estate to be assessed in the generated market price estimation model, and estimates for the real estate to be assessed You can create a quote.

For example, the market price estimation model generation unit 133 performs multiple regression analysis on the characteristic information of a plurality of selected comparison target real estate when the real estate to be evaluated is a large apartment complex to obtain the multidimensional equation of Equation 6 below. It can be created and created as a price estimation model for the real estate to be evaluated.

<Equation 6>

Here, floor, area, and transaction date are independent variables, ε _i is a constant, and β ₁ , β ₂ , and β ₃ are regression coefficients.

The market price estimation model generation unit 133 applies the application code shown in FIG. 7D to specific information corresponding to the independent variable among specific information of the real estate to be assessed in the generated market price estimation model, and estimates for the real estate to be assessed You can create a quote.

As described above, the real estate price estimation apparatus 100 according to an embodiment of the present invention matches location information, which is an undisclosed characteristic of real transaction price data, using ledger data, land characteristic data, etc., and provides real transaction data with matching location. By estimating the market price of the real estate to be evaluated using the

In addition, the real estate market price estimation apparatus 100 according to an embodiment of the present invention calculates the estimated land price when the actual transaction is a collective transaction of land and buildings, thereby reducing distortion of the land price, enabling more accurate estimation of the real estate market price do.

In addition, the real estate market price estimation apparatus 100 according to an embodiment of the present invention compares the actual transaction price and the individual official land price, and when the actual transaction price is lower than the individual official land price, the actual transaction case is judged as an abnormal transaction and is not used for market price estimation. , it is possible to increase the accuracy of the estimated market price.

Hereinafter, a method for estimating a real estate market price according to an embodiment of the present invention will be described.

Each step of the real estate price estimation method may be performed by the real estate price estimation apparatus. Here, the real estate price estimation apparatus may be a computing device, and each step of the method may be implemented with one or more instructions executed by a processor of the computing device.

8 is an exemplary flowchart illustrating a method for estimating a real estate market price according to the present invention. However, this is only a preferred embodiment for achieving the object of the present invention, and it goes without saying that some steps may be added or deleted as needed.

As shown in FIG. 8 , the real estate market price estimation method first acquires real transaction price data, ledger data, and land characteristic data for real estate in step S410. For this step, refer to the description of the data collection unit 110 further.

In step S420, property information of the acquired real estate data is compared to match the location information of the real estate transaction. For this step, reference will be made to the description of the data refiner 120 further.

In step S430, the HLPAs real estate for the real estate to be evaluated is set by using the characteristic information of the real estate with the matching location. For this step, refer to the description of the price estimation unit 130 further.

In step S440, a market price estimation model is generated based on the characteristic information of the real estate in the HLPAs to estimate the market price of the real estate to be evaluated. For this step, refer to the description of the price estimation unit 130 further.

According to the real estate market price estimation method according to an embodiment of the present invention described above, location information, which is an undisclosed characteristic of the actual transaction price, is matched with the real transaction price real estate to specify the real estate in which the corresponding actual transaction has been made, and evaluated using information on the specified real estate By estimating the market price for the target real estate, the market price estimation can be made more accurately.

Hereinafter, an exemplary computing device 1000 capable of implementing the real estate price estimation apparatus of the present invention will be described with reference to FIG. 9 .

As shown in FIG. 9 , the computing device 1000 includes one or more processors 1100 , a bus 1300 , a communication interface 1400 , and a memory for loading a computer program executed by the processor 1100 (load). 1200 ) and a storage 1500 for storing the computer program 1600 . However, only the components related to the embodiment of the present invention are illustrated in FIG. 9 . Accordingly, a person skilled in the art to which the present invention pertains can see that other general-purpose components other than the components shown in FIG. 12 may be further included. That is, the computing device 1000 may further include various components in addition to the components illustrated in FIG. 9 .

The processor 1100 controls the overall operation of each component of the computing device 1000 . The processor 1100 includes at least one of a central processing unit (CPU), a micro processor unit (MPU), a micro controller unit (MCU), a graphic processing unit (GPU), or any type of processor well known in the art. can be configured. In addition, the processor 1100 may perform an operation on at least one application or program for executing the method/operation according to the embodiments of the present invention. The computing device 1000 may include one or more processors.

The memory 1200 stores various data, commands, and/or information. The memory 1200 may load one or more programs 1600 from the storage 1500 to execute methods/operations according to embodiments of the present disclosure. For example, when the computer program 1600 is loaded into the memory 1200 , the data refiner 120 , the price estimation unit 130 , and the like as shown in FIG. 1 may be implemented on the memory 1200 . The memory 1200 may be implemented as a volatile memory such as RAM, but is not limited thereto.

The bus 1300 provides a communication function between components of the computing device 1000 . The bus 1300 may be implemented as various types of buses, such as an address bus, a data bus, and a control bus.

The communication interface 1400 supports wired/wireless Internet communication of the computing device 1000 . Also, the communication interface 1400 may support various communication methods other than Internet communication. To this end, the communication interface 1400 may be configured to include a communication module well-known in the technical field of the present disclosure. In some embodiments, communication interface 1400 may be omitted.

The storage 1500 may non-temporarily store one or more programs 1600 . The storage 1500 is a non-volatile memory, such as a read only memory (ROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a flash memory, a hard disk, a removable disk, or well-known in the art to which the present disclosure pertains. It may be configured to include any type of computer-readable recording medium.

The computer program 1600 may include one or more instructions that, when loaded into the memory 1200 , cause the processor 1100 to perform methods/operations according to various embodiments of the present invention. That is, the processor 1100 may perform the method/operation according to the embodiments of the present invention by executing one or more instructions.

The technical idea of the present invention described with reference to FIGS. 1 to 9 may be implemented as computer-readable codes on a computer-readable medium. The computer-readable recording medium may be, for example, a removable recording medium (CD, DVD, Blu-ray disk, USB storage device, removable hard disk) or a fixed recording medium (ROM, RAM, computer-equipped hard disk). have. The computer program recorded on the computer-readable recording medium may be transmitted to another computing device through a network such as the Internet and installed in the other computing device, thereby being used in the other computing device.

Although the present invention has been described in detail through specific examples, it is intended to describe the present invention in detail, and the present invention is not limited thereto. It is clear that the modification or improvement is possible.

All simple modifications or changes of the present invention are within the scope of the present invention, and the specific scope of protection of the present invention will be made clear by the appended claims.

10: Real Estate Price Estimation System
11: Real Estate Data Server
12: user terminal
100: real estate price estimation device
110: data collection unit
120: data refiner
130: price estimation unit
140: user interface unit
150: database

Claims (16)

a data collection unit that collects real estate-related public data including real-estate transaction price data, ledger data, and land characteristic data;
a data refiner that compares the characteristic information of the real transaction price data with the characteristic information of the ledger data and the land characteristic data to match a matching real estate location as the location of the real transaction price and generates a transaction data list for the real estate; and
Extracting a plurality of HLPAs for the real estate to be evaluated using the characteristic information of the real estate with the location matched, and generating a market price estimation model for the real estate to be evaluated using the extracted characteristic information of the real estate in the HLPAs; , Real estate market price estimation apparatus comprising a market price estimation unit for estimating the market price of the real estate to be assessed by inputting the characteristic information of the real estate to be assessed in the generated market price estimation model. The method of claim 1,
The data purification unit,
a location connection unit for matching location information, which is undisclosed information among the characteristic information of the actual transaction price data, using characteristic information of the ledger data and the published price data;
a transaction price distribution unit for distributing the estimated building price and the estimated land price when the actual transaction price of the real estate with the matching location is a lump sum transaction amount of land and building; and
An abnormal transaction removal unit for excluding the list of transaction data corresponding to the actual transaction when the actual transaction price is judged to be an abnormal transaction by comparing the actual transaction price of the real estate with the matching location and the estimated land price with the individual announced market price for the corresponding real estate Real estate price estimation device, characterized in that. 3. The method of claim 2,
The location connection part,
When the real estate corresponding to the actual transaction data is land, the location of the real estate that matches the first digit of the city, gun-gu, use area, area, and street number among the characteristic information of the actual transaction price data, the ledger data, and the land characteristic data Real estate market price estimation apparatus, characterized in that the information is matched with the location information of the real estate in which the actual transaction is made. 3. The method of claim 2,
The location connection part,
When the real estate corresponding to the real transaction data is an apartment house, among the property information of the real transaction price data and the ledger data, city, county, street, building year, number of floors, and exclusive area are compared with each other to obtain the location information of the matching real estate for the real transaction Real estate price estimation device, characterized in that matching with the location information of the real estate. 3. The method of claim 2,
The location connection part,
When the real estate corresponding to the real transaction price data is any one of a single-family house, a multi-family house, a commercial or business building, a city, gun-gu, street number, use area, land among the characteristic information of the actual transaction price data, the land characteristic data, and the ledger data Real estate market price estimation apparatus, characterized in that by comparing the area, road conditions, main use, building area, and total floor area, the location information of the matching real estate is matched with the location information of the real estate for the actual transaction. 3. The method of claim 2,
The transaction price distribution unit is expressed by the following equation,
<Equation>
Estimated land price = Actual transaction price - Estimated building price,
where, the estimated building price = re-procurement cost - depreciation-adjusted amount, and depreciation-adjusted amount = re-procurement cost X (useful life - elapsed years) / useful life
A real estate market price estimation apparatus, characterized in that the estimated land price and the estimated building price are distributed from the actual transaction price using 3. The method of claim 2,
The abnormal transaction removal unit,
Comparing the actual transaction price of the real estate with the matching location and the estimated land price with the individual official land price for the real estate, if the actual transaction price or the estimated land price is lower than the individual official land price, the actual transaction is judged as an abnormal transaction and corresponding to the actual transaction Real estate price estimation device, characterized in that excluding the transaction data list. The method of claim 1,
The price estimation unit,
a HLPA setting unit for setting transaction data satisfying a location, a transaction time, and a price level from a preset evaluation target real estate among the transaction data list as HLPAs real estate;
a comparison target real estate extraction unit for extracting a predetermined comparison target real estate from among the set HLPAs real estate according to a preset classification criterion; and
A market price estimation model for the real estate to be assessed is generated through multiple regression analysis using the characteristic information of the predetermined comparison target real estate as an independent variable, and characteristic information of the real estate to be assessed is input to the generated market price estimation model to determine the value of the real estate to be assessed. Real estate price estimation apparatus comprising a price estimation model generator for estimating the market price. 9. The method of claim 8,
The regular price estimation model generation unit,
Real estate, characterized in that when the real estate to be evaluated is land, a multidimensional equation generated through multiple regression analysis using the use area, usage situation, road interface, and shape among the characteristic information of the real estate as independent variables is generated as a market price estimation model price estimation device. 9. The method of claim 8,
The regular price estimation model generation unit,
If the real estate to be evaluated is a row house or a multi-family house, the multi-dimensionality generated through multiple regression analysis using case classification, use, number of floors, area, elapsed years, elevator, number of parking spaces, and price point as independent variables among the characteristic information of the real estate Real estate price estimation apparatus, characterized in that generating the equation as a price estimation model. 9. The method of claim 8,
The regular price estimation model generation unit,
If the real estate to be evaluated is a small and medium-sized apartment complex, the multidimensional equation generated through multiple regression analysis using case classification, number of floors, area, elapsed years, number of parking spaces, and price point as independent variables among the characteristic information of the real estate is used as the market price estimation model. Real estate price estimation device, characterized in that for generating. 9. The method of claim 8,
The regular price estimation model generation unit,
When the real estate to be evaluated is a large apartment complex, a real estate market price estimation device, characterized in that it generates a multidimensional equation generated through multiple regression analysis using the number of floors, area, and transaction date as independent variables among the characteristic information of the real estate as a market price estimation model . 9. The method of claim 8,
The regular price estimation unit,
The real estate market price estimation apparatus, characterized in that it further comprises an estimated market price verification unit for verifying the estimated market price by comparing the estimated market price of the real estate to be evaluated with the published price of the real estate. The method of claim 1,
The real estate price estimation device,
Real estate price estimation apparatus for inputting evaluation target real estate information, and further comprising a user interface unit for providing estimated market price information. In the real estate price estimation method performed by the real estate price estimation apparatus,
acquiring real transaction price data, ledger data, and land characteristic data for real estate;
comparing the property information of the real transaction price data, the ledger data, and the land characteristic data to match the location of the matching real estate as the location of the real estate for the actual transaction;
setting a real estate in the HLPA for the real estate to be evaluated by using the characteristic information of the real estate to which the location is matched; and
Creating a market price estimation model for the real estate to be assessed using the extracted characteristic information of the real estate in the HLPAs, and inputting the characteristic information of the real estate to be assessed in the generated market price estimation model to estimate the market price of the real estate to be assessed A method for estimating real estate prices, comprising the steps of. Combined with the real estate price estimation device,
acquiring real transaction price data, ledger data, and land characteristic data for real estate;
comparing the property information of the real transaction price data, the ledger data, and the land characteristic data to match the location of the matching real estate as the location of the real estate for the actual transaction;
setting a real estate in the HLPA for the real estate to be evaluated by using the characteristic information of the real estate to which the location is matched; and
Creating a market price estimation model for the real estate to be assessed using the extracted characteristic information of the real estate in the HLPAs, and inputting the characteristic information of the real estate to be assessed in the generated market price estimation model to estimate the market price of the real estate to be assessed A real estate price estimation program stored in a computer-readable recording medium to execute the steps.

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