System, information processing method, and program

Abstract

We will provide a new system that can calculate the appropriate valuation of properties being traded. [Solution] One or more computer control circuits function as input means and display control means. Property overview information is information that shows the overview of the property being traded, and is information that does not change even if the conditions of the property transaction change. Transaction conditions information is information that shows the conditions of the property transaction shown by the property overview information, and is information set by the user. The input means inputs the property overview information and transaction conditions information into the calculation means, causing the calculation means to generate first appraisal amount information that shows the first appraisal amount of the property. The display control means displays the first appraisal amount information generated by the calculation means on a display.

Description

Technical Field

[0001] The present invention relates to a system, an information processing method, and a program.

Background Art

[0002] As an invention related to a conventional system, for example, a tenant rent setting system described in Patent Document 1 is known. This tenant rent setting system is configured to set the tenant rent for each tenant living in a tenant occupancy facility where one or more tenants live. When setting the tenant rent, advertising information regarding the tenants living in the tenant occupancy facility is distributed to vehicles, and the tenant rent for the tenants living in the tenant occupancy facility is set according to the distribution of the advertising information to the vehicles. According to the tenant rent setting system described in Patent Document 1, even for a tenant in a location with poor accessibility, it is possible to achieve high customer attraction without much effort by distributing advertising information, and it is possible to make the customers visiting the tenant occupancy facility aware of the presence of the tenants. On the other hand, on the side of the tenant occupancy facility, it is possible to set an appropriate tenant rent including the consideration for the advertising distribution.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] As described above, calculating the tenant rent is required in the field of tenant rent setting systems.

[0005] Therefore, an object of the present invention is to provide a new system, an information processing method, and a program capable of calculating the appraisal value of a property that is a transaction target.

Means for Solving the Problems

[0006] The first form is, A system comprising one or more computers, The control circuits of the one or more computers described above function as input means and display control means. Property overview information is information that shows the outline of the property being traded, and is information that does not change even if the terms and conditions of the transaction of the said property change. Transaction conditions information is information that indicates the conditions for the transaction of the property shown in the property overview information, and is information set by the user. The input means inputs the property overview information and the transaction conditions information into the calculation means, thereby causing the calculation means to generate first appraisal amount information indicating the first appraisal amount of the property. The display control means causes the first valuation amount information generated by the calculation means to be displayed on the display. It is a system.

[0007] The second form is, The application period is the period from when the application for the transaction of the aforementioned property is made available until the application is made available. The input recruitment period information indicates the recruitment period that the user has requested. The input means inputs the property overview information, the transaction conditions information, and the input application period information to the calculation means, thereby causing the calculation means to generate the first appraisal amount information indicating the first appraisal amount. This is the system described in the first form.

[0008] The third form is, The second valuation is the valuation of the property based on the aforementioned property overview information and not on the aforementioned transaction conditions information. The input means inputs the property overview information into the calculation means, thereby causing the calculation means to generate second valuation information indicating the second valuation amount of the property. The display control means causes the second valuation amount information generated by the calculation means to be displayed on the display. The system is as described in the first or second form.

[0009] The fourth form is, The second valuation is the valuation of the property based on the aforementioned property overview information and not on the aforementioned transaction conditions information. The application period is the period from when the application for the transaction of the aforementioned property is made available until the application is made available. The input means inputs the property overview information into the calculation means, causing the calculation means to generate second valuation information indicating the second valuation amount, and also causes the calculation means to generate base offering period information indicating the base offering period expected when a transaction is offered based on the second valuation amount. The display control means causes the second valuation information and the base offering period information to be displayed on the display. This is the system described in the first form.

[0010] The fifth form is, The calculation means is a machine learning model read out by the control circuits of one or more computers. The system is one of the first to fourth forms.

[0011] The sixth form is, The historical valuation information shows the historical valuation, which is the transaction price of properties that have been traded in the past. The aforementioned machine learning model is a trained model that has been trained using a combination of property overview information, transaction conditions information, and actual valuation information of one or more properties that have been traded in the past as training data. This is the system described in the fifth form.

[0012] The seventh form is, Advertising fees are the fees paid to the intermediary who facilitates the transaction of the property between the user and the customer, if the intermediary successfully completes the transaction. The aforementioned transaction terms information includes advertising cost information showing advertising costs. The system is one of the systems described in the first to sixth forms.

[0013] The eighth aspect is the property is a rental property, Free rent is a system that allows a customer to rent the property for a specified period without paying rent when a transaction for the property is concluded. The transaction condition information includes free rent information regarding the free rent set for the property. It is the system according to any one of the first to seventh aspects.

[0014] The ninth aspect is the system includes a terminal and a server, the control circuit of the terminal functions as the input means and the display control means, the control circuit of the server functions as the arithmetic means. It is the system according to any one of the first to eighth aspects.

[0015] The tenth aspect is an information processing method, in the information processing method, the control circuit of one or more computers functions as an input means and a display control means, The property summary information is information indicating the summary of the property that is the transaction target, and is information that does not change even if the conditions in the transaction of the property change. The transaction condition information is information indicating the conditions in the transaction of the property indicated by the property summary information, and is information set by the user. The input means generates first evaluation amount information indicating the first evaluation amount of the property in the arithmetic means by inputting the property summary information and the transaction condition information into the arithmetic means. The display control means causes the display to display the first evaluation amount information generated by the arithmetic means. It is an information processing method.

[0016] The eleventh aspect is a program, The program causes one or more computer control circuits to function as input means and display control means. Property overview information is information that shows the outline of the property being traded, and is information that does not change even if the terms and conditions of the transaction of the said property change. Transaction conditions information is information that indicates the conditions for the transaction of the property shown in the property overview information, and is information set by the user. The input means inputs the property overview information and the transaction conditions information into the calculation means, thereby causing the calculation means to generate first appraisal amount information indicating the first appraisal amount of the property. The display control means causes the first valuation amount information generated by the calculation means to be displayed on the display. It is a program.

[0017] The 12th form is, A system comprising one or more computers, The control circuits of the one or more computers described above function as acquisition means, calculation means, and output means. Property overview information is information that shows the outline of the property being traded, and is information that does not change even if the terms and conditions of the transaction of the said property change. Transaction conditions information is information that indicates the conditions for the transaction of the property shown in the property overview information, and is information set by the user. The acquisition means acquires the property overview information and the transaction conditions information, The calculation means generates first appraisal value information indicating the first appraisal value of the property based on the property overview information and the transaction conditions information. The output means outputs the first valuation amount information generated by the calculation means. It is a system.

[0018] The 13th form is, It is a program, The program causes the control circuits of one or more computers to function as acquisition means, calculation means, and output means. Property overview information is information that shows the outline of the property being traded, and is information that does not change even if the terms and conditions of the transaction of the said property change. Transaction conditions information is information that indicates the conditions for the transaction of the property shown in the property overview information, and is information set by the user. The acquisition means acquires the property overview information and the transaction conditions information, The calculation means generates first appraisal value information indicating the first appraisal value of the property based on the property overview information and the transaction conditions information. The output means outputs the first valuation amount information generated by the calculation means. It is a program. [Effects of the Invention]

[0019] According to the present invention, a new system, information processing method, and program can be provided that can calculate the appraised value of a property that is the subject of a transaction. [Brief explanation of the drawing]

[0020] [Figure 1] Figure 1 is a block diagram of system 1,1a. [Figure 2] Figure 2 is a block diagram of terminal 10. [Figure 3] Figure 3 is a block diagram of server 110. [Figure 4] Figure 4 shows the input and output information of the machine learning model 114a. [Figure 5] Figure 5 shows an image displayed by the display 20. [Figure 6] Figure 6 shows an image displayed by the display 20. [Figure 7] Figure 7 shows the image displayed by the display 20. [Figure 8] Figure 8 is a flowchart showing the actions performed by the control circuit 12 of terminal 10 and the control circuit 112 of server 110. [Figure 9] Figure 9 shows the image displayed by the display 20. [Figure 10] Figure 10 shows an image displayed by the display 20. [Figure 11] Figure 11 is a flowchart showing the actions performed by the control circuit 12 of terminal 10 and the control circuit 112 of server 110. [Modes for carrying out the invention]

[0021] (Embodiment) System 1 according to an embodiment of this disclosure will be described with reference to the drawings.

[0022] [Structure of System 1] First, the overall configuration of System 1 will be explained with reference to the diagrams. Figure 1 is a block diagram of System 1,1a. Figure 2 is a block diagram of Terminal 10. Figure 3 is a block diagram of Server 110.

[0023] System 1, shown in Figure 1, comprises a terminal 10 and a server 110. Terminal 10 and server 110 are connected to each other via a communication network, such as the internet or an intranet.

[0024] Terminal 10 is a computer. Terminal 10 is an information processing device used by a user. Terminal 10 is, for example, a smartphone, a tablet, or a personal computer. As shown in Figure 2, terminal 10 includes a control circuit 12, a memory circuit 14, a network interface 16, a graphics processing unit 18, a display 20, and an operation unit 26.

[0025] The memory circuit 14 stores the program PG1 and data. The memory circuit 14 is, for example, a combination of ROM (Read Only Memory), RAM (Random Access Memory), and storage (for example, flash memory or hard disk).

[0026] Program PG1 includes, for example, the following program: • OS (Operating System) programs • Programs for applications that perform information processing (e.g., web browsers, or target applications described later)

[0027] The data includes, for example, the following: • Databases referenced in information processing • Data obtained by performing information processing (i.e., the results of performing information processing)

[0028] The control circuit 12 implements the functions of the terminal 10 by executing the program PG1 stored in the memory circuit 14. The control circuit 12 is a circuit that includes, for example, at least one of the following: ·CPU(Central Processing Unit) ·GPU(Graphic Processing Unit) ·ASIC(Application Specific Integrated Circuit) ·FPGA(Field Programmable Array)

[0029] The control circuit 12 functions as an input means 42 and a display control means 44.

[0030] The network interface 16 controls communication between the terminal 10 and an external device. The external device is a server 110.

[0031] The graphics processing unit 18 displays an image on the display 20 based on the image data generated by the control circuit 12. The display 20 is either a liquid crystal display or an organic EL (Electro-Luminescence) display.

[0032] The operation unit 26 generates operation signals based on user input and outputs these signals to the control circuit 12. The operation unit 26 can be a touch panel, keyboard, mouse, or the like.

[0033] System 1 may include multiple terminals 10.

[0034] Server 110 is a computer. Server 110 is an information processing device that stores data for web pages. As shown in Figure 3, Server 110 includes a control circuit 112, a storage circuit 114, and a network interface 116.

[0035] The memory circuit 114 stores the program PG2 and data. The memory circuit 114 is, for example, a combination of ROM (Read Only Memory), RAM (Random Access Memory), and storage (for example, flash memory or hard disk).

[0036] The control circuit 112 implements the functions of the server 110 by executing the program PG2 stored in the memory circuit 114. The control circuit 112 is a circuit that includes, for example, at least one of the following: ·CPU(Central Processing Unit) ·GPU(Graphic Processing Unit) ·ASIC(Application Specific Integrated Circuit) ·FPGA(Field Programmable Array)

[0037] The control circuit 112 functions as an acquisition means 60, a calculation means 62, and an output means 64.

[0038] The memory circuit 114 stores the machine learning model 114a. The machine learning program is a program that executes a machine learning algorithm to find certain rules from the training data and generate a trained machine learning model 114a that represents the found rules. When the control circuit 112 of the server 110 executes the machine learning program, multiple training data are trained and the parameters of the inference program are adjusted. As a result, the trained machine learning model 114a is generated.

[0039] The machine learning algorithm is not particularly limited as long as it is supervised learning, and may include, for example, decision trees, nearest neighbors, Naive Bayesian classifiers, support vector machines, or neural networks. Therefore, the trained machine learning model 114a includes decision trees, nearest neighbors, Naive Bayesian classifiers, support vector machines, or neural networks. Backpropagation may be used in the machine learning process that generates the trained machine learning model 114a.

[0040] For example, a neural network includes an input layer, one or more hidden layers, and an output layer. Specifically, neural networks include deep neural networks, recurrent neural networks, or convolutional neural networks, and perform deep learning. A deep neural network, for example, includes an input layer, multiple hidden layers, and an output layer.

[0041] The network interface 116 controls communication between the server 110 and an external device. The external device is the terminal 10.

[0042] [System 1 Operation] Next, the operation of System 1 will be described. Figure 4 shows the input and output information of the machine learning model 114a. Figures 5 through 7 show the images displayed by the display 20.

[0043] The control circuit 12 of terminal 10 reads the program PG1 stored in the memory circuit 14, causing the program PG1 to execute the operations described below in the control circuit 12 of terminal 10. The program PG1 then causes the control circuit 12 of terminal 10 to function as an input means 42 and a display control means 44. In the information processing method, the control circuit 12 of terminal 10 functions as an input means 42 and a display control means 44.

[0044] The control circuit 112 of the server 110 reads the program PG2 stored in the memory circuit 114, causing the program PG2 to execute the operations described below in the control circuit 112 of the server 110. The program PG2 then causes the control circuit 112 of the server 110 to function as an acquisition means 60, an calculation means 62, and an output means 64. In the information processing method, the control circuit 112 of the server 110 functions as an acquisition means 60, an calculation means 62, and an output means 64.

[0045] First, let's explain the operation overview of System 1. System 1 uses a machine learning model 114a to estimate the appraised value of the property being traded. In this embodiment, the property is a rental property. The rental property is a dwelling unit in an apartment building. The appraised value is the rent. To realize the estimation of the appraised value of such a property being traded, as shown in Figure 4, the machine learning model 114a is a trained model that has been trained using training data I0, which is a combination of property overview information I1, transaction conditions information I2, actual appraised value information I13, and actual listing period information I4 of multiple properties that have been traded in the past.

[0046] Property Overview Information I1 is information that shows the outline of the property being traded. Property Overview Information I1 is information that does not change even if the conditions of the property transaction change. Property Overview Information I1 is information for identifying the property being traded, and information that the property being traded has unique to it. Therefore, Property Overview Information I1 is information about the property being traded that the user cannot change. Property Overview Information I1 includes Building Information I11 and Room Information I12. Building Information I11 is information about the building to which the rental property unit belongs. Building Information I11 includes the nearest station, city / ward / county, walking distance, property name, building type, year built, structure, and number of floors. The nearest station indicates the nearest station to the building. The city / ward / county indicates the city / ward / county to which the building belongs. The walking distance indicates the time required to walk from the building to the nearest station. The property name is the name of the building. The building type indicates the use and nature of the building. The building type refers to, for example, a private residence or an apartment building where multiple households live. The building age indicates the number of years since the building was constructed. The structure indicates the materials and construction methods used to build the building. Examples of structures include lightweight steel frame construction using steel frames less than 6 mm thick, and reinforced concrete construction using reinforcing bars and concrete. The number of floors indicates the number of stories above ground level.

[0047] Room Information I12 contains information about a rental property. Room Information I12 includes size, layout, amenities, and floor location. Size indicates the area of ​​the rental property. Layout indicates the number and arrangement of rooms in the rental property. Amenities indicate the equipment and functions pre-installed in the rental property. Amenities include, for example, separate bathroom and toilet, indicating that the bathroom and toilet are separate. Floor location is the floor on which the rental property is located.

[0048] Transaction conditions information I2 is information that indicates the conditions for the transaction of the property shown in the property overview information I1. Transaction conditions information I2 is information set by the user. Property overview information I1 is information attached to the property being traded. Therefore, property overview information I1 is information about the property being traded that the user can change. Note that in the case of transaction conditions information I2 as training data I0, the user is the user who entered the transaction conditions information I2 for a rental property that was traded in the past, so it does not have to match the user of terminal 10. Transaction conditions information I2 includes advertising fee information I21 and free rent information I22.

[0049] Advertising expense information I21 shows the advertising expenses for rental properties. Advertising expenses are the fees paid to real estate agents who act as intermediaries between users and customers in property transactions, when they successfully complete a property transaction. Advertising expenses may be, for example, X months' worth of rent, Y% (percentage) of the rent, or a predetermined amount (Z yen).

[0050] Free rent information I22 is information regarding the free rent period set for a property. Free rent is a system that allows a customer to rent a property for a specified period without paying rent if the transaction for the property is completed. Free rent information I22 indicates the specified period.

[0051] The historical valuation information I13 shows the historical valuation, which is the transaction amount of rental properties that have been traded in the past. In this embodiment, the historical valuation is the monthly rent of rental properties that have been traded in the past.

[0052] Actual Offering Period Information I4 indicates the actual offering period when the property shown in Property Overview Information I1 was offered for lease based on the conditions indicated in Transaction Conditions Information I2 and the actual valuation indicated in Actual Valuation Information I13. The offering period is the period from when the offering for the rental property transaction is made until it is made to end.

[0053] As described above, the machine learning model 114a learns the relationship between property overview information I1, transaction conditions information I2, actual valuation information I13, and actual listing period information I4 of multiple rental properties that have been traded in the past, using the above training data I0.

[0054] Furthermore, as shown in Figure 4, the machine learning model 114a receives property overview information I1, transaction conditions information I2, and listing period information I14 of the rental property for which the user wants to know the first valuation. Property overview information I1 shows an overview of the rental property for which the user wants to know the first valuation. As shown in Figure 5, the user uses terminal 10 to input building information I11 and room information I12, which are part of property overview information I11. Note that the details of property overview information I1 have already been explained, so further explanation will be omitted.

[0055] Transaction conditions information I2 is information that shows the conditions in the transaction of the rental property for which the user wants to know the first valuation price. As shown in Figure 6, the user inputs transaction conditions information I2 using terminal 10. Since the details of transaction conditions information I2 have already been explained, further explanation will be omitted.

[0056] The input recruitment period information I14 indicates the application period desired by the user. As shown in Figure 6, the user inputs the application period using terminal 10.

[0057] The machine learning model 114a generates first valuation information I3 based on the property overview information I1, transaction conditions information I2, and input listing period information I14 of the rental property for which the user wants to know the first valuation. The first valuation information I3 shows the first valuation, which is the valuation of the property. More specifically, the first valuation information I3 shows the first valuation, which is the valuation of the rental property shown in property overview information I1, when the rental property shown in property overview information I1 is advertised under the conditions shown in transaction conditions information I2 and input listing period information I14. As a result, as shown in Figure 7, the user can find out the rent (first valuation / appraisal amount) of the rental property when the rental property is advertised under the advertising fee, free rent period, and listing period desired by the user.

[0058] Next, the operation of System 1 will be explained in detail with reference to the diagrams. Figure 8 is a flowchart showing the actions performed by the control circuit 12 of terminal 10 and the control circuit 112 of server 110. Figure 9 shows the image displayed by display 20.

[0059] The control circuit 12 of terminal 10 displays the image shown in Figure 5 on the display 20. The user inputs property overview information I1, including building information I11 and room information I12, by operating the operation unit 26. In this embodiment, the user inputs "Hankyu Umeda" in the nearest station field, "Osaka City Kita Ward" in the city / ward / county field, "15 minutes" in the walking time field, "A Mansion" in the property name field, "Apartment Building" in the building type field, "15 years" in the year built field, "Reinforced concrete construction" in the structure field, and "15 floors" in the number of floors field. Furthermore, the user inputs "20m" in the area field. 2 Enter " in the floor plan field, enter "1K" in the amenities field, enter "separate bath and toilet" in the floor field, and enter "8th floor" in the floor location field. As a result, the control circuit 12 of terminal 10 obtains the property overview information I1 of the rental property for which the user wants to know the first valuation amount (step S1).

[0060] Next, the control circuit 12 of terminal 10 transmits the property summary information I1 acquired in step S1 to server 110 via the network interface 16 (step S2). Accordingly, the network interface 116 of server 110 receives the property summary information I1 and outputs it to the control circuit 112. As a result, the control circuit 112 (acquisition means 60) of server 110 acquires the property summary information I1 (step S101).

[0061] Next, the control circuit 112 (calculation means 62) of the server 110 generates second valuation information I7, which indicates the second valuation of the property, based on the property overview information I1. That is, the control circuit 112 of the server 110 inputs the property overview information I1 into the machine learning model 114a, causing the machine learning model 114a to generate second valuation information I7, which indicates the second valuation of the rental property (step S102). In step S102, the calculation means 62 is the machine learning model 114a read from the memory circuit 114 by the control circuit 112 of the server 110. The second valuation is the valuation of the property based on the property overview information I1 and not based on the transaction conditions information I2. At this time, the control circuit 112 of the server 110 calculates the amount of change in the second valuation when the items included in the property overview information I1 change by a predetermined amount. Specifically, the control circuit 112 of the server 110 calculates the amount of change in the second valuation when the walking distance from the station changes by 1 minute, the amount of change in the second valuation when the building age changes by 1 year, and the amount of change in the second valuation when the number of floors changes by 1 floor. Therefore, the second valuation information I7 shows the second valuation and the amount of change in the second valuation. In this embodiment, the second valuation is 81,500 yen. The amount of change in the second valuation when the walking distance from the station changes by 1 minute is 400 yen. The amount of change in the second valuation when the building age changes by 1 year is 1,800 yen. The amount of change in the second valuation when the number of floors changes by 1 floor is 1,400 yen. As described above, in step S2, the control circuit 12 (input means 42) of the terminal 10 inputs the property overview information I1 to the machine learning model 114a (calculation means 62) by transmitting the property overview information I1 to the server 110 via the network interface 16. As a result of this operation, the control circuit 12 (input means 42) of terminal 10 causes the machine learning model 114a (calculation means 62) to generate second valuation information I7 indicating the second valuation of the rental property in step S102.

[0062] Next, the control circuit 112 of the server 110 transmits the second valuation information I7 to the terminal 10 via the network interface 116 (step S103). That is, the control circuit 112 (output means 64) of the server 110 sends the machine learning model 114a (calculation means 62 The second valuation information I7 generated by the terminal 10 is output. Accordingly, the network interface 16 of the terminal 10 receives the second valuation information I7 and outputs the second valuation information I7 to the control circuit 12. As a result, the control circuit 12 of the terminal 10 acquires the second valuation information I7 (step S3).

[0063] Next, as shown in Figure 9, the control circuit 12 (display control means 44) of terminal 10 displays the second valuation amount information I7 generated by the control circuit 112 (calculation means 62) of server 110 on the display 20 (step S4). This allows the user of terminal 10 to know the second valuation amount (assessment amount) and the amount of change in the second valuation amount.

[0064] Next, the control circuit 12 of terminal 10 displays the image shown in Figure 6 on the display 20. The user inputs transaction conditions information I2, which includes advertising cost information I21 and free rent information I22, as well as input recruitment period information I14, by operating the operation unit 26. In this embodiment, the user enters "50" in the advertising cost percentage field and "6" in the free rent months field. Furthermore, the user enters "85" in the input recruitment period field. As a result, the control circuit 12 of terminal 10 obtains the transaction conditions information I2 and input recruitment period information I14 of the rental property for which the user wants to know the first valuation amount (step S5).

[0065] Next, the control circuit 12 of terminal 10 transmits the transaction conditions information I2 and input recruitment period information I14 acquired in step S5 to server 110 via the network interface 16 (step S6). Accordingly, the network interface 116 of server 110 receives the transaction conditions information I2 and input recruitment period information I14 and outputs the transaction conditions information I2 and input recruitment period information I14 to the control circuit 112. As a result, the control circuit 112 (acquisition means 60) of server 110 acquires the transaction conditions information I2 and input recruitment period information I14 (step S104).

[0066] Next, the control circuit 112 (calculation means 62) of the server 110 generates first valuation information I3, which indicates the first valuation amount of the property, based on the property overview information I1, transaction conditions information I2, and input offering period information I14, using the machine learning model 114a. That is, the control circuit 112 of the server 110 inputs the property overview information I1, transaction conditions information I2, and input offering period information I14 into the machine learning model 114a, causing the machine learning model 114a to generate first valuation information I3, which indicates the first valuation amount (step S105). In step S105, the calculation means 62 is the machine learning model 114a read from the memory circuit 114 by the control circuit 112 of the server 110. The first valuation amount is the valuation amount of the property based on the property overview information I1, transaction conditions information I2, and input offering period information I14. In this embodiment, the first valuation amount is 86,000 yen. As described above, in steps S2 and S6, the control circuit 12 (input means 42) of terminal 10 transmits property overview information I1, transaction conditions information I2, and input recruitment period information I14 to the server 110 via the network interface 16, thereby inputting the property overview information I1, transaction conditions information I2, and input recruitment period information I14 to the machine learning model 114a (calculation means 62). Through this operation, in step S105, the control circuit 12 (input means 42) of terminal 10 causes the machine learning model 114a (calculation means 62) to generate first valuation information I3 indicating the first valuation amount.

[0067] Next, the control circuit 112 of the server 110 transmits the first valuation information I3 to the terminal 10 via the network interface 16 (step S106). That is, the control circuit 112 (output means 64) of the server 110 sends the machine learning model 114a (calculation means 62 The first valuation information I3 generated by the terminal 10 is output. Accordingly, the network interface 16 of the terminal 10 receives the first valuation information I3 and outputs the first valuation information I3 to the control circuit 12. As a result, the control circuit 12 of the terminal 10 acquires the first valuation information I3 (step S7).

[0068] Finally, as shown in Figure 7, the control circuit 12 (display control means 44) of the terminal 10 displays the first valuation information I3 generated by the machine learning model 114a (calculation means 62) on the display 20 (step S8). This allows the user to know that in order to set the listing period for the rental property to 85 days, the rent for the rental property (assessed amount - first valuation) should be set to 86,000 yen.

[0069] [effect] According to System 1, a new system can be obtained that can calculate the appraised value of a property being traded. More specifically, property overview information I1 is information that shows the overview of the property being traded. Property overview information I1 is information that does not change even if the conditions of the property transaction change. Transaction condition information I2 is information that shows the conditions of the property transaction indicated by property overview information I1. Transaction condition information I2 is information set by the user. The control circuit 12 (input means 42) of terminal 10 inputs property overview information I1, transaction condition information I2, and input recruitment period information I14 into the machine learning model 114a (calculation means 62), causing the machine learning model 114a (calculation means 62) to generate first appraisal value information I3, which shows the first appraisal value. In this way, System 1 generates first appraisal value information I3, which shows the first appraisal value, using a new method that uses two types of information: property overview information I1 and transaction condition information I2. Therefore, according to System 1, a new system can be obtained that can calculate the appraised value of a property being traded.

[0070] Furthermore, System 1 can generate first valuation information I3, which shows the first valuation amount considering transaction condition information I2. More specifically, a system that calculates the valuation amount based on property overview information is used as a comparative example. In such a system, the valuation amount is not calculated based on transaction condition information. Transaction condition information includes, for example, information on advertising costs and free rent. Therefore, the user had to recalculate the valuation amount considering the transaction condition information using the valuation amount calculated based on property overview information.

[0071] On the other hand, in System 1, the control circuit 12 (input means 42) of terminal 10 inputs property overview information I1, transaction conditions information I2, and input application period information I14 to the machine learning model 114a (calculation means 62), causing the machine learning model 114a (calculation means 62) to generate first valuation information I3, which indicates the first valuation amount. Thus, according to System 1, first valuation information I3, which indicates the first valuation amount considering the transaction conditions information I2, can be generated without the user having to recalculate the valuation amount.

[0072] In System 1, the control circuit 12 (input means 42) of terminal 10 inputs property overview information I1, transaction conditions information I2, and input recruitment period information I14 to a machine learning model 114a (calculation means 62), causing the machine learning model 114a (calculation means 62) to generate first valuation information I3, which represents the first valuation amount. The input recruitment period information I14 indicates the input recruitment period, which is the recruitment period desired by the user. This allows the user to know the rent (first valuation amount) for a rental property in order to keep the rental period within the input recruitment period.

[0073] In System 1, the control circuit 12 (input means 42) of terminal 10 inputs property overview information I1 to the machine learning model 114a (calculation means 62) in step S2 by transmitting property overview information I1 to the server 110 via the network interface 16. Then, in step S102, the control circuit 12 (input means 42) of terminal 10 causes the machine learning model 114a (calculation means 62) to generate second valuation information I7, which indicates the second valuation amount of the rental property. The second valuation amount is the valuation amount of the property based on the property overview information I1 and not based on the transaction conditions information I2. This allows the user to know the rent (second valuation amount) of a rental property that takes into account the property overview information I1 but does not take into account the transaction conditions information I2.

[0074] (modified version) The following description of system 1a will be made with reference to the drawings. Figure 10 shows an image displayed by the display 20.

[0075] In system 1a, the machine learning model 114a receives property overview information I1, transaction conditions information I2, and bid valuation information I31 of the rental property for which the user wants to know the listing period, as shown in Figure 4. Property overview information I1 shows an overview of the rental property for which the user wants to know the first valuation. As shown in Figure 5, the user uses terminal 10 to input building information I11 and room information I12, which are part of property overview information I11. Since the details of property overview information I1 have already been explained, further explanation will be omitted.

[0076] Transaction conditions information I2 is information that shows the conditions in the transaction of the rental property for which the user wants to know the first valuation price. As shown in Figure 6, the user inputs transaction conditions information I2 using terminal 10. Since the details of transaction conditions information I2 have already been explained, further explanation will be omitted.

[0077] The listing valuation information I31 shows the desired asking rent (valuation) for the rental property for which the user wants to know the listing period. As shown in Figure 6, the user enters the asking rent (valuation) using terminal 10.

[0078] The machine learning model 114a generates predicted rental period information I41 based on the property overview information I1, transaction terms information I2, and rental valuation information I31 of the rental property for which the user wants to know the rental period. The predicted rental period information I41 shows the predicted rental period required for the rental property indicated by the property overview information I1 if it is advertised under the conditions indicated by the transaction terms information I2 and rental valuation information I31. As a result, as shown in Figure 10, the user can find out the rental period of the rental property if it is advertised for rent at the advertising cost, free rent period, and asking rent that the user desires.

[0079] Next, the operation of system 1a will be described in detail with reference to the diagram. Figure 11 is a flowchart showing the actions performed by the control circuit 12 of terminal 10 and the control circuit 112 of server 110.

[0080] Steps S1-S4 and S101-S103 in Figure 11 are the same as steps S1-S4 and S101-S103 in Figure 8, so their explanation is omitted.

[0081] Next, the control circuit 12 of terminal 10 displays the image shown in Figure 6 on the display 20. The user inputs transaction conditions information I2, which includes advertising cost information I21 and free rent information I22, as well as the asking price information I31, by operating the operation unit 26. In this embodiment, the user enters "50" in the advertising cost percentage field and "6" in the free rent months field. Furthermore, the user enters "81,500" in the asking rent field. As a result, the control circuit 12 of terminal 10 obtains the transaction conditions information I2 and the asking price information I31 of the rental property for which the user wants to know the first valuation (step S15).

[0082] Next, the control circuit 12 of terminal 10 transmits the transaction conditions information I2 and the offering valuation information I31 acquired in step S5 to server 110 via the network interface 16 (step S16). Accordingly, the network interface 116 of server 110 receives the transaction conditions information I2 and the offering valuation information I31 and outputs the transaction conditions information I2 and the offering valuation information I31 to the control circuit 112. As a result, the control circuit 112 of server 110 acquires the transaction conditions information I2 and the offering valuation information I31 (step S114).

[0083] Next, the control circuit 112 of the server 110 inputs the property overview information I1, transaction conditions information I2, and offering valuation information I31 to the machine learning model 114a, causing the machine learning model 114a to generate predicted offering period information I41, which indicates the predicted offering period (step S105). The predicted offering period is the expected offering period required for the rental property indicated by the property overview information I1 if the rental property indicated by the property overview information I1 is offered under the conditions indicated by the transaction conditions information I2 and offering valuation information I31. In this embodiment, the predicted offering period is 38.1 days. As described above, in steps S2 and S6, the control circuit 12 (input means 42) of the terminal 10 inputs the property overview information I1, transaction conditions information I2, and offering valuation information I31 to the machine learning model 114a (calculation means 62) by transmitting the property overview information I1, transaction conditions information I2, and offering valuation information I31 to the server 110 via the network interface 16. As a result of this operation, the control circuit 12 (input means 42) of terminal 10 causes the machine learning model 114a (calculation means 62) to generate predicted recruitment period information I41 indicating the predicted recruitment period in step S105.

[0084] Next, the control circuit 112 of the server 110 transmits the predicted subscription period information I41 to the terminal 10 via the network interface 16 (step S116). Accordingly, the network interface 16 of the terminal 10 receives the predicted subscription period information I41 and outputs the predicted subscription period information I41 to the control circuit 12. As a result, the control circuit 12 of the terminal 10 acquires the predicted subscription period information I41 (step S17).

[0085] Finally, as shown in Figure 7, the control circuit 12 (display control means 44) of the terminal 10 displays the predicted listing period information I41 generated by the machine learning model 114a (calculation means 62) on the display 20 (step S18). This allows the user to know that if the rent for the rental property is set to 86,000 yen, the listing period for the rental property will be 38.1 days.

[0086] (Other embodiments) The system according to the present invention is not limited to system 1,1a, but can be modified within the scope of its gist. Furthermore, the configuration and operation of systems 1,1a may be combined in any way.

[0087] In System 1, the control circuit 12 (input means 42) of terminal 10 may input property overview information I1 and transaction conditions information I2 to the machine learning model 114a (calculation means 62) to generate first appraisal amount information I3 indicating the first appraisal amount of the property. In other words, input offering period information I14 does not have to be used.

[0088] In System 1, the control circuit 12 (input means 42) of terminal 10 may input property overview information I1 to the machine learning model 114a (calculation means 62) to cause the machine learning model 114a (calculation means 62) to generate second valuation information I7 indicating the second valuation amount, and also cause the machine learning model 114a (calculation means 62) to generate base offering period information I8 indicating the base offering period expected if the transaction is offered based on the second valuation amount. The control circuit 12 (display control means 44) of terminal 10 may then display the second valuation information I7 and the base offering period information I8 on the display 20.

[0089] The control circuit 112 of the server 110 may also function as an input means 42 and a display control means 44. In this case, the control circuit 112 (display control means 44) of the server 110 transmits the first valuation information I3 to the terminal 10 via the network interface 16, thereby causing the terminal 10 to display the first valuation information I3.

[0090] Furthermore, the properties involved in the transaction are not limited to rental properties; they may also be properties for sale. Additionally, the properties are not limited to apartment buildings; they may also be single-family homes. Moreover, the properties are not limited to residential properties; they may also be commercial properties.

[0091] In addition, the machine learning model 114a is not required to be used in system 1,1a. That is, in system 1,1a, the control circuit 112 of server 110 may execute algorithmic processing instead of using the machine learning model 114a. [Explanation of symbols]

[0092] 1,1a: System 10: Terminal 12: Control circuits 14:Memory circuit 16: Network Interface 18: Graphics Processing Unit 20: Display 26:Operation section 42: Input method 44: Display control means 60: Acquisition means 62: Arithmetic means 64: Output means 110: Server 112: Control circuits 114:Memory circuit 114a: Machine learning models 116: Network Interface I0: Training data I1: Property Overview Information I11: Building Information I12: Room Information I13: Performance-based valuation I14: Input Application Period Information I2: Transaction Terms and Conditions I21: Advertising Cost Information I22: Free Rent Information I3: First Valuation Information I31: Information on the valuation of the offering I4: Information on the period for submitting achievements I41: Predicted Subscription Period Information I7: Second Valuation Information I8: Information on the recruitment period for bass players PG1, PG2: Program

Claims

1. A system comprising one or more computers, The control circuits of the one or more computers described above function as input means and display control means. Property overview information is information that shows the outline of the property being traded, and is information that does not change even if the terms and conditions of the transaction of the said property change. Transaction conditions information is information that indicates the conditions for the transaction of the property shown in the property overview information, and is information set by the user. The second valuation is the valuation of the property based on the aforementioned property overview information and not on the aforementioned transaction conditions information. The input means inputs the property overview information and the transaction conditions information into the calculation means, thereby causing the calculation means to generate first appraisal information indicating the first appraisal amount of the property. The input means inputs the property overview information to the calculation means, thereby causing the calculation means to generate second valuation information indicating the second valuation amount of the property. The display control means causes the first valuation information and the second valuation information generated by the calculation means to be displayed on the display. system.

2. The application period is the period from when the application for the transaction of the aforementioned property is made available until the application is made available. The input recruitment period information indicates the recruitment period that the user has requested. The input means inputs the property overview information, the transaction conditions information, and the input application period information to the calculation means, thereby causing the calculation means to generate the first appraisal amount information indicating the first appraisal amount. The system according to claim 1.

3. The solicitation period is the period from when the solicitation for the transaction of the property is started until the solicitation is ended. The input means inputs the property overview information into the calculation means, thereby causing the calculation means to generate base offering period information, which indicates the base offering period expected when a transaction is offered based on the second valuation amount. The display control means causes the base recruitment period information to be displayed on the display. The system according to claim 1.

4. The calculation means is a machine learning model read out by the control circuits of one or more computers. The system according to claim 1 or claim 2.

5. The historical valuation information shows the historical valuation, which is the transaction price of properties that have been traded in the past. The aforementioned machine learning model is a trained model that has been trained using a combination of property overview information, transaction conditions information, and actual valuation information of one or more properties that have been traded in the past as training data. The system according to claim 4.

6. Advertising fees are the fees paid to the intermediary who facilitates the transaction of the property between the user and the customer, if the intermediary successfully completes the transaction. The aforementioned transaction terms information includes advertising cost information showing advertising costs. The system according to claim 1 or claim 2.

7. The aforementioned property is a rental property. Free rent is a system in which, if a transaction for the aforementioned property is concluded, the customer can rent the property for a specified period without paying rent. The aforementioned transaction terms information includes free rent information regarding the free rent period set for the aforementioned property. The system according to claim 1 or claim 2.

8. The aforementioned system comprises a terminal and a server. The control circuit of the terminal functions as the input means and the display control means, The control circuit of the server functions as the calculation means, The system according to claim 1 or claim 2.

9. Information processing method, In the aforementioned information processing method, the control circuits of one or more computers function as input means and display control means. Property overview information is information that shows the outline of the property being traded, and is information that does not change even if the terms and conditions of the transaction of the said property change. Transaction conditions information is information that indicates the conditions for the transaction of the property shown in the property overview information, and is information set by the user. The second valuation is the valuation of the property based on the aforementioned property overview information and not on the aforementioned transaction conditions information. The input means inputs the property overview information and the transaction conditions information into the calculation means, thereby causing the calculation means to generate first appraisal information indicating the first appraisal amount of the property. The input means inputs the property overview information to the calculation means, thereby causing the calculation means to generate second valuation information indicating the second valuation amount of the property. The display control means causes the first valuation information and the second valuation information generated by the calculation means to be displayed on the display. Information processing methods.

10. It is a program, The program causes one or more computer control circuits to function as input means and display control means. Property overview information is information that shows the outline of the property being traded, and is information that does not change even if the terms and conditions of the transaction of the said property change. Transaction conditions information is information that indicates the conditions for the transaction of the property shown in the property overview information, and is information set by the user. The second valuation is the valuation of the property based on the aforementioned property overview information and not on the aforementioned transaction conditions information. The input means inputs the property overview information and the transaction conditions information into the calculation means, thereby causing the calculation means to generate first appraisal information indicating the first appraisal amount of the property. The input means inputs the property overview information to the calculation means, thereby causing the calculation means to generate second valuation information indicating the second valuation amount of the property. The display control means causes the first valuation information and the second valuation information generated by the calculation means to be displayed on the display. program.

11. A system comprising one or more computers, The control circuits of the one or more computers described above function as acquisition means, calculation means, and output means. Property overview information is information that shows the outline of the property being traded, and is information that does not change even if the terms and conditions of the transaction of the said property change. Transaction conditions information is information that indicates the conditions for the transaction of the property shown in the property overview information, and is information set by the user. The second valuation is the valuation of the property based on the aforementioned property overview information and not on the aforementioned transaction conditions information. The acquisition means acquires the property overview information and the transaction conditions information, The calculation means generates first valuation information indicating the first valuation amount of the property based on the property overview information and the transaction conditions information, and generates second valuation information indicating the second valuation amount of the property based on the property overview information. The output means outputs the first valuation information and the second valuation information generated by the calculation means. system.

12. It is a program, The program causes one or more computer control circuits to function as acquisition means, calculation means, and output means. Property overview information is information that shows the outline of the property being traded, and is information that does not change even if the terms and conditions of the transaction of the said property change. Transaction conditions information is information that indicates the conditions for the transaction of the property shown in the property overview information, and is information set by the user. The second valuation is the valuation of the property based on the aforementioned property overview information and not on the aforementioned transaction conditions information. The acquisition means acquires the property overview information and the transaction conditions information, The calculation means generates first valuation information indicating the first valuation amount of the property based on the property overview information and the transaction conditions information, and generates second valuation information indicating the second valuation amount of the property based on the property overview information. The output means outputs the first valuation information and the second valuation information generated by the calculation means. program.

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